Oddelek za geografijo, Filozofska fakulteta Univerze v Ljubljani Dela Department of Geography, Faculty of Arts, University of Ljubljana 56 LJUBLJANA 2021 ISSN 0354-0596 DELA 56 2021 Elektronska izdaja — Electronic edition ISSN 1854-1089 Založnik — Published by Znanstvena založba Filozofske fakultete Univerze v Ljubljani Izdajatelj — Issued by Oddelek za geografijo, Filozofska fakulteta Univerze v Ljubljani Za založbo — For the Publisher Mojca Schlamberger Brezar, dekanja Filozofske fakultete Mednarodni uredniški odbor — International Editorial Board Nejc Bobovnik, Marko Krevs, Simon Kušar, Karel Natek, Darko Ogrin, Irma Potocnik Slavic, Dejan Rebernik, Serge Schmitz (Ličge, Belgija), Laura Šakaja (Zagreb, Hrvaška), Katja Vintar Mally, Miroslav Vysoudil (Olomouc, Ceška) Urednika — Editors Dejan Cigale (glavni urednik), Mojca Ilc Klun Upravnik — Editorial Secretary Nejc Bobovnik Namizno založništvo — Desktop Publishing Žiga Valetic Tisk — Printed by Birografika Bori, d. o. o. Naklada — Edition 400 izvodov Naslov uredništva — Publisher’s address Oddelek za geografijo, Filozofska fakulteta Univerze v Ljubljani, Aškerceva 2, SI-1000 Ljubljana Elektronski dostop — On-line access http://revije.ff.uni-lj.si/Dela DELA so vkljucena v – DELA is included in Scopus, CGP – Current Geographical Publications, DOAJ, ERIH PLUS, GEOBASE, Central and Eastern European Academic Source, GeoRef, Russian Academy of Sciences Biblio­graphies, TOC Premier, International Bibliography of the Social Sciences Izdano s financno pomocjo Javne agencije za raziskovalno dejavnost Republike Slovenije in Oddelka za geografijo FF Univerze v Ljubljani. To delo je ponujeno pod licenco Creative Commons Priznanje avtorstva­-Deljenje pod enakimi pogoji 4.0 Mednarodna licenca. / This work is licen­sed under a Creative Commons Attribution-ShareAlike 4.0 International License. VSEBINA CONTENTS RAZPRAVE PAPERS Barbara Lampic, Alenka Kastelic Prepoznavanje in evidentiranje mejic: preverjanje razlicnih metod na pilotnem obmocju Ljubljanskega barja ......................................................................................................... 5 Identification and recording of hedgerows: testing different methods in a pilot area of the Ljubljana Marshes ................................................................................................................ 29 Katja Vintar Mally Socialno-ekonomske in okoljske znacilnosti regionalnega razvoja Slovenije po letu 2010 .................................................................................................................................... 53 Socioeconomic and environmental characteristics of regional development in Slovenia after 2010 ..................................................................................................................... 71 Živa Novljan Morfometrija in gostota vrtac na izbranih pobocjih slovenskega krasa ............................... 89 Morphometry and density of dolines on slopes of Slovenian karst (Summary) ...................... 106 Jasna Sitar Organizacijski ucinki socialnega kapitala pri delovanju organizacij v Upravni enoti Litija .................................................................................................................................... 109 Organizational effects of social capital in the operation of organizations in the Litija Administrative Unit (Summary) ................................................................................................ 129 Boštjan Rogelj Ali je nova ureditev volilnih okrajev za državnozborske volitve ustavna? ......................... 131 Is the new regulation of constituencies for parliamentary elections in Slovenia constitutional? (Summary) ......................................................................................................... 152 Katja Vintar Mally, Nejc Bobovnik, Barbara Lampic, Simon Kušar Attitudes of farmers towards nature conservation in selected areas of dry grasslands in Eastern Slovenia ...................................................................................................................... 157 Odnos kmetov do varstva narave na izbranih obmocjih suhih travišc v vzhodni Sloveniji (Povzetek) ...................................................................................................................... 173 Jostina Dhimitri, Lekë Pepkolaj, Blerta Avdia Geography and math teachers in distance learning education amid COVID-19 pandemic in Albania .................................................................................................................. 175 Ucitelji geografije in matematike v izobraževanju na daljavo v casu pandemije covida-19 v Albaniji (Povzetek) .................................................................................................. 190 Mirela Altic The influence of Blaž Kocen (Blasius Kozenn) and his geographical atlas on the development of Croatian school cartography ......................................................................... 193 Vpliv Blaža Kocena (Blasiusa Kozenna) in njegovega geografskega atlasa na razvoj hrvaške šolske kartografije (Povzetek) ........................................................................................ 217 POROCILA REPORTS .............................................................................................................. 219 1 UVOD Zmanjševanje pokrajinske pestrosti in neustrezno upravljanje s posameznimi sestavi­nami pokrajine sta med pomembnimi dejavniki izgube biotske raznovrstnosti v vecini držav Evropske unije in Sloveniji. Krajinske znacilnosti (izraz krajinske znacilnosti ali prvine uporabljamo na mestih, kjer povzemamo besedilo uradnih dokumentov, sicer uporabljamo izraz pokrajinske znacilnosti) namrec povecujejo možnost ohranjanja biotske raznovrstnosti predvsem kmetijskih ekosistemov (Resolucija o Nacionalnem programu …, 2020). Številne, za kmetijsko pridelavo vitalne ekosistemske storitve (kot npr. opraševanje, naravno zatiranje škodljivcev v kmetijstvu, zmanjševanje ne­gativnih vplivov vetra, suše ipd.), so neposredno in mocno odvisne od ustrezne za­stopanosti pokrajinskih znacilnosti v (kmetijski) kulturni pokrajini (Stališce sticišca SVARUN, 2020). Pri obravnavanju (po)krajinskih znacilnosti v prispevku sledimo opredelitvi krajin­skih znacilnosti v ciljnem raziskovalnem projektu (Golobic in sod., 2015), kjer so razvr­šcene v štiri skupine in vkljucujejo geomorfološke in rastlinske krajinske prvine (grbi­naste travnike, kraške kotanje, balvane, terase ipd.), rastlinske krajinske prvine (gozdne zaplate, mejice, obvodna vegetacija, vlažni travniki ipd.), vodne krajinske prvine (lokal­na zamocvirjenja, nizka in visoka barja, jarki) in grajene objekte (suhozidi). Manjša pokrajinska pestrost je najveckrat posledica sprememb v uporabi (sodob­nih) kmetijskih tehnologij, velike racionalizacije proizvodnih stroškov, modernizacije in intenzifikacije kmetijske proizvodnje. Socasno na obmocjih z manj ugodnimi na­ravnimi razmerami za kmetijsko pridelavo prihaja do opušcanja rabe in zarašcanja kmetijske pokrajine. K spremembam prispevajo tudi povsem administrativni razlogi, ki so vezani na pogoje upravicenosti podpor kmetijskim gospodarstvom, ter posledic­no prizadevanja kmetov za povecanje upravicenih kmetijskih površin, saj pokrajin­ske znacilnosti vecinoma niso priznane kot upravicena raba za prejemanje podpor iz naslova ukrepov kmetijske politike (Golobic in sod., 2015; Stališce sticišca SVARUN, 2020). Zmanjševanje, ponekod pa celo izginjanje pokrajinskih znacilnosti je poveza­no tudi z urbanizacijo in fragmentacijo prostora, turizmom in rekreacijo, razrastom invazivnih (tujerodnih) rastlinskih vrst in podnebnimi spremembami. Okoljska vizija zadnje Resolucije o nacionalnem programu varstva okolja za ob­dobje 2020–2030 je ohranjena narava in zdravo okolje v Sloveniji in zunaj nje, kar omogoca in bo omogocalo kakovostno življenje zdajšnjim in prihodnjim generaci­jam. Tudi tu v okviru varovanja, ohranjanja in izboljševanja naravnega kapitala Slove­nije med cilji naslavljajo ohranjanje tistih pokrajinskih znacilnosti, ki so pomembne za biotsko raznovrstnost. V resoluciji ugotavljajo, da so krajinska pestrost in krajin­ske znacilnosti pretežno odvisne od naravnih procesov in socialno-ekonomskih raz­mer (Resolucija o Nacionalnem programu …, 2020). V Sloveniji zaradi raznolikih geografskih razmer in dolge tradicije kultiviranja zemljišc (še) prevladuje mozaicna pokrajina, katere sestavni deli so drobne strukture (vodotoki in drugi vodni pojavi, posamezno drevje ali skupine dreves, žive meje, mejice, suhozidi, drevoredi), eksten­zivne kmetijske površine (npr. malo gnojeni ali negnojeni travniki in pašniki), moza­icni preplet njiv z razlicnimi kulturami in gozdovi, s katerimi trajnostno gospodarijo. T. i. »poenostavljanje krajine«, ki smo mu prica marsikje v Sloveniji, vodi v izginjanje naravnih struktur in kulturnih elementov, zmanjšuje mozaicnost ter s tem tudi krajin­sko pestrost in biotsko raznovrstnost (Resolucija o Nacionalnem programu …, 2020). Za varstvo omenjenih pokrajinskih znacilnosti je treba torej ohranjati lastnosti, zaradi katerih so deli pokrajine ali njeni elementi opredeljeni kot pokrajinska znacil­nost. Tu je odlocilnega pomena spremljanje in usmerjanje posegov v prostor (Lampic, Kušar, Zavodnik Lamovšek, 2017). Mejice so opredeljene kot »rastlinska krajinska prvina« (Golobic in sod., 2015). Sestavlja jih linijsko lesnato rastlinstvo (drevesa in grmovje), ki pa je lahko podvrženo številnim in hitrim spremembam. Ce se za mejice ustrezno ne skrbi, stalno spreminja­jo svojo dolžino in obliko. Ker gre za linijske strukture pretežno grmovne zarasti, se jih razmeroma enostavno tudi poseka. Mejice se po drugi strani tudi hitro zarašcajo, najpogosteje na tistih delih kmetijskega zemljišca, ki ga kmet zaradi slabše kakovosti, težje dostopnosti in drugih vzrokov preneha obdelovati. Posebno pozornost smo v prispevku namenili prepoznavanju in evidentiranju me­jic s pomocjo digitalnih ortofoto in lidarskih posnetkov. Njihova najvecja pomanjklji­vost je ažurnost, saj so bili lidarsko zajeti podatki za celotno Slovenijo zajeti le enkrat, medtem ko se digitalne ortofoto posnetke posodablja na dve do štiri leta. Za ucinkovitejše ohranjanje posameznih pokrajinskih prvin (npr. grbinastih trav­nikov, mejic idr.), ki v kombinaciji z ostalimi sestavinami ustvarjajo pokrajinske zna­cilnosti, je potrebno zagotavljanje podatkovnih zbirk, ki temeljijo na ustreznih naci­nih evidentiranja posameznih pokrajinskih prvin. Odsotnost monitoringov tako ovi­ra sam sistem spremljanja pojava, nadzor in ustrezno ukrepanje ob negativnih pro­cesih. Ta pomanjkljivost je bila prepoznana tudi na ravni izvajanja kmetijske politike, kjer sta v Skupnem strateškem nacrtu 2023–2027 posebej izpostavljena izboljševanje ter razširitev razlicnih prostorskih slojev za izvedbo naravovarstvenih podintervencij, ki se bodo nanašale na mejice, mokrišca in obcutljivo trajno travinje na obmocjih Natura 2020 idr. (MKGP, 2021). 2 TEORETICNA IZHODIŠCA Mejice so kot pomemben element v prostoru prepoznane širom po svetu. Strokovno utemeljena in z raziskavami dobro podprta je njihova obravnava v državah Zahodne Evrope in Severne Amerike (npr. Allende Álvarez, Gómez Mediavilla, López Estéba­nez, 2021; Allende Álvarez in sod., 2021; Graham in sod., 2018; Litza in sod., 2022). V Združenem kraljestvu jih npr. ciljno varujejo s posebnim Predpisom o varovanju mejic (The hedgerow regulations, 1997). Zaradi obsežnih in hitrih sprememb v pro­storu (intenziviranje kmetijstva, uporaba sodobne tehnologije, širjenje urbaniziranih površin, spremembe politike upravljanja kmetijskih zemljišc) pa se na svetovni ravni soocamo z njihovim postopnim izginjanjem (Baudry, Bunce, Burel, 2000; Burel, Bau­dry, 1990; Molnarova, 2008) in tako ohranjanje mejic postaja vse vecji izziv. Obravnava mejic tudi terminološko še ni poenotena. V tuji literaturi se najpogo­steje pojavljata dva pojma: živa meja (ang. hedge) in mejica (ang. hedgerow), vendar je njuna uporaba nekonsistentna. Živa meja predstavlja lesno komponento mejne za­rasti, medtem ko mejice (hedgerow) vkljucujejo tudi zelišcno komponento in kanal ob mejici (Forman, Baudry, 1984). Ker v Sloveniji nimamo enega uveljavljenega ter­mina, se uporabljajo poimenovanja, kot so živice, omejki ali živa meja. Terminološke zagate so se nekoliko razrešile z uvedbo operacije Ohranjanje mejic, ki se izvaja v okviru Kmetijsko okoljskih in podnebnih ukrepov (KOPOP) Skupne kmetijske poli­tike (SKP). S to operacijo se je v kmetijskem in naravovarstvenem sektorju uveljavila oznaka mejica (MKGP, 2019). Do razhajanj prihaja tudi pri opredelitvi minimalne dolžine mejic. V raziskavi smo izhajali iz definicije Ministrstva za kmetijstvo, gozdarstvo in prehrano (MKGP), ki mejice oznacuje kot vsaj 10 metrov dolge in pri krošnji najvec 20 metrov široke strnjene in samostojne linije lesne vegetacije, ki morajo biti široke vec kot dva metra (MKGP, 2019). Obravnava mejic ter njihovo ustrezno upravljanje sta pomembna zaradi številnih in med seboj dopolnjujocih funkcij, ki jih mejice opravljajo. Predstavljajo prehranjevalni habitat za številne živali, kar je še posebnega pomena v intenzivno obdelani kmetijski pokrajini. So pomembni migracijski in preletni koridorji, ki med seboj povezujejo razlicne ekosisteme. Pomembno je, da so mejice sestavljene iz raznovrstnih avtohto­nih vrst s tako razvito grmovno plastjo, ki omogoca dostop svetlobe do najnižjih plasti (Dondina in sod., 2016; Garratt in sod., 2017; Heath in sod., 2017). Mejice zmanjšuje­jo vplive vetra, suše, neurij in toce, kontrolirajo vodni tok ter zadržijo izpiranje hranil iz kmetijskih zemljišc v vodotoke. Na eni strani omejujejo širjenje za kmetijstvo ško­dljivih organizmov (MKGP, 2021), po drugi služijo kot zatocišce živalim, tako divjim kot pašnim. Velik pomen mejic v kmetijski pokrajini je v njihovem preprecevanju vetrne erozije (Earnshaw, 2004; MKGP, 2021). Kakovost zašcite je odvisna od veli­kosti drevja; tako je ucinek vetrne zašcite 56 metrov za dvometrskim grmom in 560 metrov za 20-metrsko mejico (Forman, Baudry, 1984). Med pomembnimi ekosistem­skimi storitvami je tudi uravnavanje lokalnega podnebja, saj se na obmocju mejic in v njihovi okolici vzpostavi posebna mikroklima (MKGP, 2021). Na obmocju mejic so višje vsebnosti vode in organskega ogljika v prsti, kar prispeva k višji produktivnosti zemljišc (Sanchez in sod., 2010). Mejice predstavljajo tudi vir surovin, med katerimi je najpomembnejši les, ki je imel pomembno vlogo predvsem v preteklosti in v deželah, kjer primanjkuje gozdnih površin (Burel, Baudry, 1990). Ima pa prisotnost mejic tudi nekatere negativne ucinke, saj lahko mejice privabljajo nekatere škodljive žuželke ter ptice, ki škodujejo posevkom na bližnjih njivah (Farmers and hedgerow management, 2019), s povzrocanjem sence pa vplivajo na kolicino pridelka (Oreszczyn, Lane, 2000). Mejice prispevajo k pokrajinski pestrosti kulturne pokrajine in razbijajo njeno mo­notonost (Golobic in sod., 2015), pogosto pa razmejujejo posestva razlicnih lastnikov (Baudry, Bunce, Burel, 2000). Imajo torej velik estetski pomen, o katerem se redko piše in je o njem narejenih malo študij, a je pomemben dejavnik ohranjanja mejic (Burel, Baudry, 1990). V Sloveniji so mejice ena izmed pokrajinskih prvin, pomembnih za ohranjanje biot­ske raznovrstnosti, ki so bile opredeljene v projektu Opredelitev krajinske pestrosti in znacilnosti, pomembnih za ohranjanje biotske raznovrstnosti (Golobic in sod., 2015). Med krajinske prvine štejemo še npr. vodne jarke, suhozide, obvodno vegetacijo, grbi­naste travnike idr. Na kmetijskih zemljišcih so te prvine kljucnega pomena za ohranja­nje številnih rastlinskih ter živalskih vrst, imajo pa tudi veliko drugih koristnih funkcij za cloveka in samo pokrajino (Golobic in sod., 2015). Eden od ciljev Skupne kmetijske politike po letu 2020 je okrepiti prispevek kmetijstva k varstvu biotske raznovrstnosti s pomocjo varovanja pestrosti pokrajinskih prvin (Biodiversty and farmland landscapes, 2020). Skupna usmeritev za vse navedene prvine je njihovo ohranjanje predvsem v in­tenzivno obdelani kmetijski pokrajini in ekstenzivna raba njihove neposredne okolice. Za te prvine v Sloveniji nimamo ustreznih podatkovnih podlag za spremljanje stanja ali pa poenotenega sistema njihovega varovanja (Golobic in sod., 2015). Kakovost opravljanja razlicnih funkcij mejic pa je odvisna predvsem od njihove strukture. Zato so se številni avtorji (Boutin in sod., 2002; Burel, Baudry, 1990; Garratt in sod., 2017) v svojih raziskavah mejic lotili njihove tipologije (npr. Allende Álvarez, Gómez Mediavilla, López Estébanez, 2021; Allende Álvarez in sod., 2021). Strinjajo se, da so najbolj kakovostne tiste mejice, ki so vecvrstne, goste, sestavljene iz dreves in grmovja ter se prepletajo z drugimi mejicami, tako da sestavljajo sistem oziroma mre­žo mejic (Boutin in sod., 2002; Baudry, Bunce, Burel, 2000; Forman, Baudry, 1984; Hedgerow survey handbook ..., 2007). Za potrebe naše raziskave smo izdelali lastno, slovenskim razmeram prilagojeno tipologijo mejic (Kastelic, 2019). Koncna tipologija vkljucuje pet tipov mejic: 1. Strukturirane mejice so tiste, ki vkljucujejo vse tri plasti rastlinstva: drevesno, grmovno in zelišcno. So vertikalno povezane in nudijo razlicne habitate za šte­vilne živalske vrste, zato so z naravovarstvenega vidika najbolj kakovostne. 2. Grmovne mejice so sestavljene iz grmovne in zelišcne zarasti. Grmovna zarast je gosta, ustvarja vertikalno povezanost in je težko prehodna. 3. Polstrukturirane mejice so sestavljene iz drevesne, grmovne in zelišcne zarasti. Razlika med strukturiranim in polstrukturiranim tipom je, da je pri slednjem grmovna zarast redkejša, nižja in je zato mejica bolj prehodna. 4. Drevesne mejice sestavljajo drevesa in zelišcna zarast. 5. Kombinirane mejice so daljše mejice, v katerih se izmenjata najmanj dva tipa mejice. Njihove lastnosti so odvisne od tipov, ki jo sestavljajo. Slika 2: Kombinirane mejice (kombinacija grmovne in drevesne plasti) so na Ljubljanskem barju prisotne v vecjem številu (foto: A. Kastelic). Z vidika opravljanja funkcij (za cloveka, živalstvo in pokrajino) so najustreznejše strukturirane mejice, ki so sestavljene iz vseh treh slojev, sledijo grmovne in polstruk­turirane mejice, medtem ko so drevesne mejice za opravljanje npr. naravovarstvenih funkcij manj primerne. Slika 3: Strukturirane mejice na Ljubljanskem barju opravljajo še posebej pomembne nara­vo­varstvene funkcije, saj se nahajajo med intenzivnimi kmetijskimi površinami (foto: A. Kastelic). Slika 4: Drevesne mejice tvorijo drevesa in zelišcna zarast. Na sliki je primer drevesne mejice na Ljubljanskem barju, ki zaradi intenzivnega izsekavanja in cišcenja ter drugih rab izgublja svoje funkcije (foto: B. Lampic). 3 PRISOTNOST IN PREPOZNAVNOST MEJIC V SLOVENIJI Mejice v Sloveniji so prisotne na obmocju celotne države, prihaja pa do precejšnjih pokrajinskih razlik. Na Krasu so npr. nastajale ob suhozidovju (Šmid Hribar, 2008), medtem ko so na Gorickem z mejicami omejevali pašnike (Domanjko, Malacic, 2009). O njihovi biološki funkciji je bilo napisanih nekaj diplomskih del, Janez Božic pa je že leta 1969 napisal delo Protivetrni nasadi (vetrobrani) v nižinskih predelih Slovenije (Premrl, Turk, 2013). Posledicno o stanju mejic v Sloveniji vemo razmeroma malo, nekoliko bolj sistematicno pa se spremlja tiste mejice, ki so vkljucene v kmetijsko operacijo Ohranjanje mejic. Operacija Ohranjanje mejic je ena izmed operacij ukrepa KOPOP (kmetijsko­-okoljska-podnebna placila) v PRP (2014–2020, kot podinetervencija se bo izvajala tudi v programskem obdobju 2023–2027). Podpira vzdrževanje in ohranjanje me­jic na razlicnih vrstah rabe kmetijskih zemljišc in pomeni ohranjanje enega izmed pomembnih elementov kmetijske kulturne pokrajine. Operacija se izvaja vse od leta 2017, kmet pa se ob vstopu v operacijo zaveže za izvajanje vsaj za pet let. Višina pla­cila za izvajanje operacije znaša 1,60 EUR za tekoci meter letno (MKGP, 2019). Pri vzdrževanju mejic je treba poskrbeti za njihovo redcenje, odstranjevati suhe veje in jih obrezovati. Placila so namenjena izpadu dohodka kmeta (ponekod zmanjšan pridelek v senci, težja obdelava) in za dodatno delo, vezano na vzdrževanje mejic (Cus, 2019; Žvikart, 2019). Najpomembnejše je njihovo obrezovanje (na dve leti), vendar ne v casu gnezdenju ptic (med 1. marcem in 30. septembrom) (MKGP, 2019). Preglednica 1: Število in dolžina mejic, vkljucenih v operacijo Ohranjanje mejic na sedmih obmocjih Natura 2000. Obmocje Natura 2000 Število mejic Skupna dolžina (m) Najdaljša mejica (m) Najkrajša mejica (m) Povprecna dolžina (m) Krakovski gozd –Šentjernejsko polje 404 44.875 792 11 111 dolina Reke 383 27.833 421 10 73 dolina Vipave 123 8.783 328 15 71 Planinsko polje 298 27.368 586 13 92 Ljubljansko barje 2.720 290.876 1.254 11 107 Drava 286 32.793 691 14 115 Mura 308 26.030 545 15 85 Skupaj 4.522 458.558 1.254 10 101 Vir podatkov: MKPG, 2018b. Operacija Ohranjanje mejic se je v letu 2019 izvajala na sedmih obmocjih Nature 2000 (Krakovski gozd - Šentjernejsko polje, dolina Reke, dolina Vipave, Planinsko po­lje, Ljubljansko polje, Drava, Mura) (MKGP, 2019). V operacijo so vkljucena obmocja, kjer mejicam najbolj grozi izginotje (Žvikart, 2019). Vseh mejic v operaciji je 4522, njihova skupna dolžina pa znaša 458.558 metrov. Povprecna dolžina mejice je 101 meter, najdaljša meri kar 1254 metrov, najkrajša pa 10 m (MKGP, 2018b). Slika 5: Prikaz obmocij izvajanja operacije Ohranjanje mejic v Sloveniji. V letu 2018 so se v operacijo Ohranjanje mejic vkljucila 104 kmetijska gospodarstva (KMG), ki so skupaj vzdrževala 134 kilometrov mejic. V okviru operacije jim je bilo izplacanih okoli 214.400 EUR. Od tega je bila vecina (kar 90 %) prijavljenih kmetov z Ljubljanskega barja, medtem ko je število v operacijo vkljucenih KMG na drugih ob­mocjih skromno (Cus, 2019). Razlogi za velike razlike v številu prijavljenih kmetov med obmocji so v številu in dolžini mejic. Na Ljubljanskem barju jih je najvec, so najdaljše in so širše prisoten element v kulturni pokrajini. Na odlocitev za vstop v operacijo po­membno vpliva odnos kmeta do mejice, razumevanje same operacije ter (predvsem) aktivnost in prizadevanje kmetijskih svetovalcev (Žvikart, 2019; Cuš, 2019). Operacija Ohranjanje mejic šciti in ohranja 4.522 mejic na sedmih obmocjih Na­ture 2000 (MKGP, 2018b). Te mejice so (bolj) varne pred posekom, pri preostalih pa še vedno redno prihaja do izsekavanja ali krcenja, saj je njihovo varovanje, tudi na obmocju Krajinskega parka Ljubljansko barje, s trenutnimi zakonskimi podlagami težko izvedljivo. Še bolj pa je zaskrbljujoce dejstvo, da nimamo podatkov in informa­cij, kaj se dogaja z mejicami na preostalem obmocju Slovenije. Nimamo nobenega po­datka o njihovem številu, dolžini, strukturi in aktualnih procesih. Ce neustrezna rav­nanja zasledimo na bolj varovanih obmocjih izvajanja operacije lahko predvidevamo, da so drugod razmere še slabše. Tako npr. na obmocju Krajinskega parka Ljubljansko barje ugotavljajo, da so bili z izsekavanjem (torej unicenjem) mejic kršeni predpisi s podrocja varstva narave. Socasno pa je kmet, po odstranitvi mejic, lahko brez ovir zemljišce (travinje) vpisal v zbirno vlogo kot njivo ter prejel kmetijska placila. Sistem pravil in kmetijskih predpisov v Sloveniji ocitno deluje na nacin, da omogoca izpla­cevanje evropskih kmetijskih placil tudi za ravnanja, ki pomenijo krnitev narave in kršitev naravovarstvenih predpisov (Jancar, 2018). 4 LJUBLJANSKO BARJE KOT PILOTNO OBMOCJE Za nadaljnje delo smo izbrali pilotno obmocje Ljubljansko barje, kamor smo usmerili vse nadaljnje korake raziskave, skupaj s terenskim popisom mejic. Ljubljansko barje leži v osrednji Sloveniji na južnem delu Ljubljanske kotline in obsega 120 kvadratnih kilometrov (Pavšic, 2008). Zanj je znacilna mozaicna pokrajina, preplet njiv, barjan­skih travnikov, pašnikov, kanalov, vodotokov in mejic, ki so eden izmed pomembnej­ših gradnikov pokrajine (Strokovne podlage za ustanovitev …, 2007). Glavna ovira za razvoj kmetijstva sta zamocvirjenost in talna voda; kljub temu so leta 2017 obdelovali 82 % površin. Na skoraj polovici njiv je kot kulturna rastlina zastopana (silažna) koru­za, kar predstavlja nevarnost, da Ljubljansko barje postane monotona monokulturna pokrajina. Velikost kmetij na Ljubljanskem barju je glede na slovenske razmere nad­povprecna (12,72 ha) (Kmetijstvo na Ljubljanskem barju, 2019). Mejice so na Ljubljanskem barju tradicionalni pokrajinski element. Njihova razšir­jenost v preteklosti je bila še vecja, predvsem ob kanalih. Bile so pomemben vir suro­vin (les), oznacevale so meje parcel razlicnih lastnikov, danes pa te funkcije izgubljajo. Gostota in sestava mejic se znotraj Ljubljanskega barja precej razlikujeta. Tako je v zarasti mejic na obrobju vec vrb, pri mejicah v notranjosti pa prevladujejo jelše. Veliko drevesne in grmovne zarasti so posekali ob cišcenju pri vzpostavitvi graficnih enot rabe kmetijskega gospodarstva (GERK-ov). Z intenziviranjem kmetijstva so tako za marsikaterega kmeta postale moteci element. Na Ljubljanskem barju je v operacijo Ohranjanje mejic vec kmetov vkljucenih na zahodnem delu, na vzhodnem delu pa je njihovo število manjše. Vecina kmetov v Operaciji ima preko 2000 metrov mejic, dva kmeta pa celo po 10 kilometrov mejic (Pecjak, 2019). Slika 7: Znacilna polstrukturirana mejica med travniki na Ljubljanskem barju (foto: A. Kastelic). 5 METODE Zavod RS za varstvo narave (ZRSVN) je po pooblastilu MKGP leta 2016 pripravil prvi evidencni sloj mejic v Sloveniji (Bucik in sod., 2017). Sloj je bil izdelan na podlagi digital­nih ortofoto posnetkov iz leta 2014, kjer so aerofotografije transformirane iz centralne v ortogonalno projekcijo in so mersko primerljive s kartami (Zbirke prostorskih podatkov, 2019). Zaradi implementacije operacije Ohranjanje mejic v okviru KOPOP je bil sloj prip­ravljen v kratkem casu. Prepoznavanje mejic je temeljilo na uporabi starejših ortofoto po­snetkov, zato je bila kakovost prvega evidencnega sloja ponekod slabša, saj so bile mejice evidentirane površno ali pa je prišlo do napak zaradi sprememb v dejanski rabi oziroma odstranitvi mejic. Sloj mejic 2018 je bil dopolnjen in izboljšan na podlagi novejših orto­foto posnetkov (iz leta 2017) ter terenskih porocil (Cuš, 2019; Žvikart, 2019). Oba uradna sloja mejic (2016 in 2018) smo preverili na terenu tudi za potrebe raziskave in ugotovili številne nepravilnosti. S preliminarnim terenskim delom smo leta 2017 na severovzho­dnem delu Ljubljanskega barja ugotovili razlike med dejanskim stanjem v prostoru in evidencnim slojem mejic 2016 na kar 62 % mejic (izbranega obmocja). Ob ponovnem terenskem preverjanju v letu 2019 (preverjali smo sloj mejic 2018) je bilo zaznanih manj razlik (Kastelic, 2019). Pokazala se je kljucna vloga terenskega preverjanja stanja mejic pa tudi njegova zahtevnost in zamudnost (Bucik in sod., 2017; Kastelic, 2019). Ker se prepoznavanje in evidentiranje mejic neposredno s pomocjo ortofoto posnetkov ter terenskim delom nista izkazala za optimalni rešitvi pri evidentiranju mejic, smo meji­ce identificirali še na podlagi lidarsko zajetih podatkov. Uporabili smo posnetke s portala E-vode, za katerega skrbi ARSO. Metodo smo preverili na manjšem pilotnem obmocju (ki je bilo predstavljeno predhodno), kjer so mejice zastopane v vecjem številu, hkrati pa je dovolj blizu Ljubljane. Lasersko skeniranje za Ljubljansko barje je bilo izvedeno v letih 2014 in 2015 z locljivostjo 10 tock na m2 (Izvedba laserskega skeniranja …, 2015). Pilotno obmocje dveh kvadratnih kilometrov, ki leži na severu Ljubljanskega bar­ja, vkljucuje razlicne tipe mejic, heterogena pa je tudi raba tal. Osnovni sloj lidarsko zajetih podatkov je bil filtriran na sloj LAS DATASET. Filtrirali smo ga na srednjo in visoko vegetacijo, saj to ustreza kriterijem mejice. Zaradi iskanja najboljšega nacina evidentiranja mejic z uporabo lidarsko zajetih podatkov sta bila preizkušena dva pri­stopa: pristop 1 oz. gostota krošenj ter pristop 2 oz. intenzivnost odboja. Slika 8: Shematicni prikaz uporabljenih metodoloških pristopov z lidarsko zajetimi podatki. Na sliki 8 sta prikazana dva razlicna nacina obdelave lidarskih podatkov, rezultat pa sta dva razlicna prostorska prikaza mejic. Gostota krošenj ali pokrovnost je ocena razmerja med tlemi in vrhovi krošenj, kot je vidno iz zraka. Izracunali smo jo s po­mocjo podatkov o gostoti talnih in vegetacijskih tock. Metoda je uporabna za meritve v naravi, kot je npr. izracun biomase in vegetacijskega pokrova (Estimating forest ca­nopy density ..., 2019). Intenzivnost odboja ali intenziteta pomeni jakost odbitega signala oziroma raz­merje med jakostjo sprejete svetlobe na laserskem skenerju. Uporablja se kot pripo­mocek pri identificiranju elementov in kot nadomestek za letalske posnetke. Sama karta je rastrski prikaz vrednosti izmerjene intenzivnosti odboja. Zajema eno valovno dolžino, in sicer cloveku nevidni bližnji infrardeci del spektra, ki je le malo vecja od valovnih dolžin vidnega spektra, zato je prikaz precej podoben dojemanju vidne svet­lobe. Lahko locimo gosto posnete tocke, kot so drevesa, hiše ali ceste, še posebej na površju, brez višinskih razlik. Težko je predvidevati koncni razpon vrednosti, saj so koncne vrednosti odvisne od vec spremenljivk, razlicnih senzorjev in so brez merske enote (Švab Lenarcic, Oštir, 2015). V zakljucni fazi smo še rocno zarisali linijske strukture mejic in tako dobili dva vektorska sloja. Vse analize so bile opravljene s programskim orodjem ArcMap 10.7. 6 REZULTATI Prepoznavanje mejic v prostoru s pomocjo razlicnih postopkov (1. terensko zajema­nje (2017), 2. dva pristopa, temeljeca na lidarsko zajetih podatkih, 3. dva evidencna sloja mejic (MKGP 2016 in 2018)) je za pilotno obmocje na Ljubljanskem barju dalo razlicne rezultate (preglednica 2). To se odraža v številu in skupni dolžini mejic, ki se med vsemi postopki opazno razlikujejo. Preglednica 2: Pilotno obmocje Ljubljanskega barja – evidentirano število in dolžina mejic z razlicnimi pristopi. Postopki Število mejic Skupna dolžina mejic (m) Evidencni sloj mejic 2016 88 9.468 Terensko evidentiranje mejic 2017 122 11.427 Evidencni sloj mejic 2018 101 10.536 Lidarsko zajeti podatki – gostota krošenj 127 13.978 Lidarsko zajeti podatki – intenzivnost odboja 130 12.788 Vir podatkov: Bucik in sod., 2017; MKGP, 2016; 2018b. Analiza mejic iz obeh uradnih evidencnih slojev mejic iz let 2016 in 2018 kaže, da je na obravnavanem pilotnem obmocju leta 2018 zabeleženo vecje število in vecja skupna dolžina mejic. Takšno stanje nas je presenetilo, saj se je v tem obdobju skupno število mejic na celotnem obmocju Ljubljanskega barja precej zmanjšalo, in sicer z 2952 na 2720. Manjša je bila tudi njihova skupna dolžina (za 50.000 m) (MKGP, 2016; 2018b). Ti podatki opozarjajo na vprašljivo primernost DOF posnetkov iz leta 2014, ki so bili uporabljeni za pripravo evidencnega sloja mejic 2016. Podrobneje smo se problema lotili na manjšem pilotnem obmocju, kjer je bilo leta 2016 v evidencni sloj zajetih 88 mejic, dve leti kasneje pa 101 mejica. Vzrokov za takšne razlike je lahko vec. Spremembe so vezane na obmocje s pretežno njivsko rabo. Analiza rabe tal v obeh letih kaže na opušcanje njiv in s tem na vecje zarašcanje povr­šin, kar lahko pripelje do nastanka novih mejic. K slabši natancnosti lahko prispeva že omenjeno prvo zajemanje mejic s starejših DOF posnetkov. Zacetek izvajanja opera­cije Ohranjanje mejic (leta 2017) je vnesel spremembe v nacin upravljanja z mejicami, kar bi lahko vplivalo na njihov manjši posek. Glavne razlike med evidencnim slojem in terenskim popisnim slojem so vecinoma v grmovnih mejicah na njivskih površi­nah na vzhodnem delu obmocja. Grmovne mejice so namrec tip mejic, ki se najhitreje zaraste in verjetno zaradi tega še niso bile opazne na DOF posnetkih. Glede na predstavljeno se rezultati evidencnih slojev niso izkazali za optimalne, zato smo se odlocili za razvoj dveh lastnih metodoloških pristopov, ki sta izvedena s pomocjo lidarsko zajetih podatkov in sta podrobneje opisana v metodološkem po­glavju 5. Karta gostota krošenj (D) nam prikazuje gostoto drevesnih in grmovnih krošenj. Mejice so bile vidne kot linijski prikazi krošenj. Pri evidentiranju mejic smo morali biti pozorni, da smo zajemali jasno vidne linijske zarasti, ki pa niso smele biti širše od dvajsetih metrov. Dve razlicni metodi (gostota krošenj in intenzivnost odboja), ki sta temeljili na lidarsko zajetih podatkih, sta dali razlicne rezultate. Razlog je v razlicnih stopnjah vidnosti in tudi v sami podobi mejic. Pri karti intenzivnosti odboja mejice predstavljajo pasovi, v katerih se ne prepozna oblik lesnate vegetacije, medtem ko lahko pri karti gostote krošenj prepoznamo krošnje, kar zagotavlja jasno vidnost tudi ožjih pasov vegetacije. Slika 9: Prikaz in primerjava razlicnega obsega evidentiranih mejic, prepoznanih po razlicnih metodah (na izseku pilotnega obmocja Ljubljanskega barja). Preglednica 3: Število evidentiranih mejic z razlicnimi metodološkimi pristopi na pilotnem obmocju Ljubljanskega barja. Sloj mejic Evidencni sloj 2016 Evidencni sloj 2018 Terensko evidentiranje 2017 Lidarsko zajeti podatki – gostota krošenj Lidarsko zajeti podatki – intenzivnost odboja Evidencni sloj 2016 +13 +34 +39 +42 Evidencni sloj 2018 –13 +21 +26 +29 Terensko evidentiranje 2017 –33 –21 +5 +8 Lidarsko zajeti podat­ki – gostota krošenj –39 –26 –5 +3 Lidarsko za­jeti podatki – intenzivnost odboja –42 –29 –8 –3 Vir podatkov: Bucik in sod., 2017; MKGP, 2016; 2018b. Pri evidentiranju mejic na pilotnem obmocju Ljubljanskega barja je bilo prepoz­nanih najmanj mejic v obeh uradnih evidencah mejic (Evidencni sloj 2016 in 2018). S terenskim popisovanjem mejic ter slojema mejic, ki smo jih izdelali na osnovi li­darsko zajetih podatkov, smo evidentirali vec mejic. Tudi razlike med temi tremi sloji mejic so razmeroma majhne in zato sklepamo, da so ti ustreznejši. Preglednica 4: Dolžine evidentiranih mejic (v metrih) z razlicnimi metodološkimi pristopi na Ljubljanskem barju. Sloj mejic Evidencni sloj 2016 Evidencni sloj 2018 Terensko evidentiranje 2017 Lidarsko zajeti podatki – gostota krošenj Lidarsko zajeti podatki – intenzivnost odboja Evidencni sloj 2016 +1.068 +1.959 +4.510 +3.320 Evidencni sloj 2018 –1.068 +891 +3.442 +2.252 Terensko evidentiranje –1.959 –891 +2.551 +1.361 Lidarsko zajeti podatki – gostota krošenj –4.510 –3.442 –2.551 –1.190 Lidarsko zajeti podatki – intenzivnost odboja –3.320 –2.252 –1.361 +1.190 Vir podatkov: Bucik in sod., 2017; MKGP, 2016; 2018b. Zanimivo je, da se evidencni sloj mejic 2018 tako po številu kot po skupni dolžini mejic manj razlikuje od sloja mejic, evidentiranih s pomocjo lidarsko zajetih podat­kov, kot evidencni sloj 2016. Tak rezultat deloma preseneca zaradi manjše casovne razlike med DOF posnetki (ki so osnova za evidencni sloj 2016) in lidarskimi posnet­ki, ki so bili zajeti med letoma 2014 in 2015. Naši rezultati kažejo na slabšo natancnost uradnega evidencnega sloja mejic 2016. Razlike med terenskim popisom in rezultati obeh lidarskih pristopov so manjše predvsem pri skupnem številu mejic, do razlik pa prihaja pri dolžini grmovnih mejic med njivami. Ugotavljamo, da se na razlicnih posnetkih mejice vizualno razlicno dobro zaznajo. To vpliva na razlike v njihovih dolžinah pri vseh slojih, ki smo jih zajeli digitalno. Med analiziranjem podatkov smo zaznali vec razlik med lidarskimi in DOF posnetki. Te razlike tudi nakazujejo prednosti oziroma slabosti uporabe enih oziroma drugih podatkovnih slojev. Pomembna tehnicna razlika je že v velikosti datotek. Velikost li­darskega posnetka, ki meri en kvadratni kilometer, je 101 MB, medtem ko je DOF slika, ki prikazuje obmocje petih kvadratnih kilometrov, velika približno 315 MB. Tudi prepoznavanje mejic je na lidarskih slojih težje kot na slojih DOF, saj slednji omogocajo lažje in hitrejše prepoznavanje linijskih struktur mejic. Po drugi strani pa je prednost lidarskih podatkov v tem, da jih je mogoce filtrirati, na ta nacin pa se na sliki lahko vidi samo srednja in visoka vegetacija, zato so linijske strukture bolj jasne in lažje prepoznavne kot na DOF posnetkih. Na lidarskih posnetkih tudi ni senc, ki se lahko pojavijo na posnetkih DOF in ovirajo vizualno prepoznavanje, hkrati pa je na lidarskih posnetkih laže zaznati vrzeli med mejicami. Omeniti še velja, da se pri evidentiranju mejic pri uporabi obeh posnetkov pojavlja problem prepoznavanja dre­voredov in ostalih (linijskih) nasadov, ki ne sodijo med mejice. 7 ZAKLJUCEK Operacija Ohranjanje mejic, ki se izvaja v okviru ukrepa KOPOP, predstavlja prvi sis­temski poskus ohranjanja in vzdrževanja mejic v Sloveniji. Na sedmih obmocjih v Slove­niji (Krakovski gozd - Šentjernejsko polje, dolina Reke, dolina Vipave, Planinsko polje, Ljubljansko polje, Drava, Mura), kjer so mejice že opredeljene v evidencnem sloju mejic, se je posledicno med lastniki zemljišc, kmeti in kmetijskimi svetovalci zacelo pogosteje naslavljati problematiko njihovega vzdrževanja in ohranjanja (Cuš, 2019; Žvikart, 2019). V novem programskem obdobju si lahko obetamo izboljševanje ter razširitev razlicnih prostorskih slojev za izvedbo naravovarstvenih podintervencij, kar bo v praksi pome­nilo razširitev evidencnega sloja mejic še na druga obmocja Slovenije (MKGP, 2021). Zaradi prepoznanih težav naravovarstvenega in kmetijskega resorja, vezanih na kakovost in vzdrževanje uradne evidence mejic, iskanja ucinkovitejših nacinov po­pisovanja novih obmocij z mejicami in spremljanja njihovega vzdrževanja, smo se v raziskavi osredotocili na razvoj metod prepoznavanja in vzpostavljanja sloja mejic. Obstojeci sistem spremljanja in posodabljanja podatkov je pomanjkljiv in ne sledi dejanskim razmeram na terenu. Naše podrobnejše raziskave na pilotnem obmocja Ljubljanskega barja med letoma 2017 in 2019 kažejo, da nobeden od treh preverjenih nacinov prepoznavanja in evi­dentiranja mejic (z uporabo digitalnih ortofoto posnetkov, lidarsko zajetih podatkov, s terenskim delom) ni povsem ustrezen, vendar ima vsak pristop dolocene prednosti in slabosti. Ugotavljamo, da ažuren prostorski sloj mejic zahteva uporabo najnovejših dostopnih podatkov in razlicnih tehnik, kljub zamudnosti pa je treba metode kombi­nirati s terenskimi ogledi in popisom. Evidentiranje mejic z uporabo lidarsko zajetih podatkov poleg pristopov, predstavljenih v prispevku, ponuja še druge možne rešitve, vendar bi že s predstavljenimi (in preizkušenimi) metodami prepoznavanja in eviden­tiranja zagotovo lahko razširili evidencni sloj mejic tudi na druga obmocja v Sloveniji. Zakljucimo lahko, da se prikazi mejic, izdelani po razlicnih metodoloških pristo­pih, ki smo jih izvedli na pilotnem obmocju Ljubljanskega barja, razlikujejo. Razlike bi se verjetno pokazale tudi na drugih obmocjih mejic v Sloveniji. Med postopki sicer ne prihaja do velikih razhajanj v številu in dolžinah mejic, so pa razlike pomembne zaradi dejstva, da se kmetijska placila za operacijo Ohranjanje mejic nanašajo na dolžinski meter mejice. Placilo je v programskem obdobju 2014–2020 znašalo 1,6 EUR za tekoci meter mejice, namenjeno pa je izravnavi stroškov kmeta, ki nastanejo zaradi njihovega urejanja in vzdrževanja (MKGP, 2019). Ker o obsegu in kakovosti mejic izven evidencnega sloja trenutno v Sloveniji nima­mo podatkov, ukrepi za ohranjanje pa se v okviru Operacije mejic drugod ne morejo izvajati, upraviceno pricakujemo, da bodo zaradi teženj v kmetijstvu in drugih prostor­skih pritiskov te prvine v prostoru še bolj ogrožene. Obstojeco evidenco mejic je treba nadgraditi tudi v vsebinskem smislu. Trenutno se spremljata le dolžina in sklenjenost mejic, ne pa tudi njihova kakovost. Poskusno smo atribute za spremljanje razširili že v okviru naše raziskave, in sicer z dodatnim podatkom o tipu mejic. Na podlagi terenske opredelitve tipa mejice lahko bolje ocenimo oziroma sklepamo na obseg in kakovost funkcij, ki jih dolocena mejica lahko opravlja. Zaradi prepoznane kakovosti funkcij me­jic bi laže opredelili obmocja, kjer je njihovo varovanje še posebej pomembno, oziroma obmocja z manj kakovostnimi mejicami, ki bi jih bilo treba izboljšati. Prispevek nakazuje nekatere rešitve v smeri nadgradnje obstojecega nacionalnega evidencnega sloja mejic. Za ohranjanje in ucinkovito varovanje mejic bodo, poleg me­todološko ustrezno podprtega evidentiranja, odlocilnega pomena ukrepi in usmeritve s podrocij kmetijstva, varstva narave in urejanja prostora. Predvsem pa je potrebno kontinuirano ozavešcanje kmetov, lastnikov zemljišc in širše javnosti o številnih funk­cijah mejic v kulturni kmetijski pokrajini. Literatura in viri Allende Álvarez, F., Gómez Mediavilla, G., López Estébanez, N., 2021. Environmen­tal, demographic and policy drivers of change in Mediterranean hedgerow lan­dscape (Central Spain). Land Use Policy, 103, 105342. DOI: 10.1016/j.landuse­pol.2021.105342. Allende Álvarez, F., Gomez-Mediavilla, G., López-Estébanez, N., Molina Holgado, P., 2021. Classification of Mediterranean hedgerows: A methodological approximati­on. MethodsX, 8, 101355. DOI: 10.1016/j.mex.2021.101355. Baudry, J., Bunce, R. G. H., Burel, F., 2000. 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URL: http://www.e-prostor.gov.si/zbirke­-prostorskih-podatkov/topografski-in-kartografski-podatki/ortofoto/ (citirano 1. 2. 2019). Žvikart, M., 2019. Pomen mejic za Zavod za Varstvo Narave RS (osebni vir, 22. 3. 2019). Ljubljana. 1 INTRODUCTION The loss of landscape diversity and inadequate management of individual landscape components are among the major factors contributing to biodiversity loss in most EU countries and in Slovenia. Landscape features (the term landscape features or ele­ments is used in places where the text of official documents is summarised) increase the potential for biodiversity conservation, particularly in agricultural ecosystems (Resolucija o Nacionalnem programu ..., 2020). Many ecosystem services vital for ag­ricultural production (such as pollination, natural pest control in agriculture, mitiga­tion of the negative impacts of wind, drought, etc.) are directly and strongly depend­ent on an adequate representation of landscape features in the (agricultural) cultural landscape (Stališce sticišca SVARUN, 2020). In the treatment of landscape features, the paper follows the definition of landscape features in the target research project (Golobic et al., 2015), where they are divided into four groups: geomorphological and vegetation landscape elements (hilly meadows, karst hollows, boulders, terraces, etc.), vegetation landscape elements (forest patches, hedgerows, riparian vegetation, wet meadows, etc.), water landscape elements (local swamps, low-moor and high-moor, ditches) and built structures (dry stone walls). Reduced landscape diversity is most often the result of changes in the use of (mod­ern) agricultural technologies, major rationalisation of production costs, and mod­ernisation and intensification of agricultural production. At the same time, in areas with less favourable natural conditions for agricultural production, there has been abandonment and overgrowth of agricultural landscapes. Purely administrative rea­sons linked to the eligibility conditions for farm support and, consequently, farmers’ efforts to increase the eligible agricultural area are also contributing to the changes, as landscape features are largely not recognised as an eligible use for support under agricultural policy measures (Golobic et al., 2015; Stališce sticišca SVARUN, 2020). The decline and sometimes even disappearance of landscape features is also linked to urbanisation and fragmentation, tourism and recreation, the spread of invasive (non-native) plant species and climate change. The environmental vision of the latest Resolution on the National Programme for Environmental Protection for 2020–2030 is preserved nature and a healthy environ­ment in Slovenia and beyond, which enables and will enable a quality life for pre­sent and future generations. Here again, the objectives of protecting, preserving and enhancing Slovenia’s natural capital include the conservation of landscape features that are important for biodiversity. The Resolution notes that landscape diversity and landscape features are largely dependent on natural processes and socio-economic conditions (Resolucija o Nacionalnem programu ..., 2020). In Slovenia, due to the diverse geographical conditions and the long tradition of land cultivation, a mosaic landscape is (still) predominant, with fine structures (watercourses and other water phenomena, individual trees or groups of trees, hedges, hedgerows, dry walls, tree avenues), extensive agricultural areas (e.g. low-fertilised or unfertilised meadows and pastures), a mosaic of arable fields with different crops and sustainably managed for­ests. The “simplification of the landscape”, which is being witnessed in many parts of Slovenia, is leading to the disappearance of natural structures and cultural elements, reducing the mosaic nature and thus landscape diversity and biodiversity (Resolucija o Nacionalnem programu ...,2020). The protection of these landscape features therefore requires the preservation of the characteristics that make parts of the landscape, or elements of it. Here, monitoring and guiding spatial interventions is crucial (Lampic, Kušar, Zavodnik Lamovšek, 2017). Hedgerows are defined as a “landscape vegetation feature” (Golobic et al., 2015). They are composed of linear woody vegetation (trees and shrubs), which can be sub­ject to numerous and rapid changes. If they are not properly managed, their length and shape change constantly. As they are linear structures of predominantly shrubby vegetation, they are also relatively easy to cut down. On the other hand, they also be­come overgrown quickly, most often on parts of farmland that the farmer has stopped cultivating due to poorer quality, less accessibility and other reasons. In this paper, we have paid special attention to the identification and recording of hedgerows using digital orthophoto and lidar imagery. Their biggest drawback is their timeliness, as lidar data for the whole of Slovenia have been captured only once, while digital orthophotos are updated every two to four years. In order to more effectively conserve the individual landscape features (e.g. hilly meadows, hedgerows, etc.), it is necessary to provide databases based on appropriate ways of recording these features. The absence of monitoring thus hampers the very sys­tem of monitoring the phenomenon, surveillance and appropriate action in the event of negative processes. This shortcoming has also been identified at the level of agricultural policy implementation, where the Joint Strategic Plan 2023–2027 specifically highlights the improvement and extension of the different spatial layers for the implementation of nature conservation sub-interventions, which will relate to hedgerows, wetlands, sensi­tive permanent grasslands in Natura 2020 sites, etc. (MAFF, 2021). 2 THEORETICAL STARTING POINTS The hedgerow is recognised worldwide as an important landscape element. Their treatment in Western European and North American countries is well established and supported by research (e.g. Allende Álvarez, Gómez Mediavilla, López Estéban­ez, 2021; Allende Álvarez et al., 2021; Graham et al., 2018; Litza et al., 2022). In the UK, for example, they are protected in a targeted way through the Hedgerow Regula­tions (1997). However, due to large-scale and rapid spatial changes (intensification of agriculture, use of modern technology, expansion of urbanised areas, changes in farmland management policies), hedgerows are facing their gradual loss at a global scale (Baudry, Bunce, Burel, 2000; Burel, Baudry, 1990; Molnarova, 2008), and thus conservation of hedgerows is becoming increasingly challenging. The treatment of hedgerows is also not yet uniform in terms of terminology. The two most commonly used terms in the foreign literature are hedge and hedgerow, but their use is inconsistent. Hedges represent the woody component of the boundary vegeta­tion, whereas hedgerows include a herbaceous component and a canal adjacent to the hedgerow (Forman, Baudry, 1984). As there is no single established term in Slovenia, terms such as “živice”, “omejki” and “živa meja” are used. Terminological conundrums have been somewhat resolved with the introduction of the Conservation of Hedgerows operation, which is part of the Agri-environmental-climate scheme (AECS) under the Common Agricultural Policy (CAP). This operation has established the term “hedge­row” (Slov. “mejica”) in the agricultural and nature conservation sector (MAFF, 2019). There are also discrepancies in the definition of the minimum length of hedgerows. In the survey, we used the definition of the Ministry of Agriculture, Forestry and Food (MAFF), which defines hedgerows as compact and independent lines of woody veg­etation at least 10 metres long and no more than 20 metres wide at the canopy, which must be more than two metres wide (MAFF, 2019). The importance of the management and proper treatment of hedgerows lies in the multiple and complementary functions that they provide. They provide forag­ing habitat for many animals, which is particularly important in intensively farmed landscapes. They are important migration and flyway corridors linking different eco­systems. An important fact is that hedgerows are composed of a diversity of native species with a shrub layer developed to allow light to reach the lowest layers (Dondina et al., 2016; Garratt et al., 2017; Heath et al., 2017). Hedgerows reduce the impacts of wind, drought, storms and hail, control water flow and delay nutrient leaching from farmland into watercourses. On the one hand, they limit the spread of organisms harmful to agriculture (MAFF, 2021), and on the other hand, they serve as a refuge for animals, both wild and grazing. The great importance of hedgerows in the agricultural landscape lies in their prevention of wind erosion (Earnshaw, 2004; MAFF, 2021). The quality of the protection depends on the size of the trees, so that the effect of windbreak is 56 metres for a two-metre shrub and 560 metres for a 20-metre thicket (Forman, Baudry, 1984). Another important ecosystem service is the regulation of the local climate, as a specific microclimate is established in and around hedgerows (MAFF, 2021). In the area of the hedgerows, soil water and organic carbon contents are higher, which contributes to higher land productivity (Sanchez et al., 2010). They are also a source of raw materials, the most important of which is timber, which has played an important role especially in the past and in countries where forest cover is scarce (Burel, Baudry, 1990). However, the presence of hedgerows also has some negative effects, as hedgerows can attract some harmful insects and birds that damage crops in nearby fields (Farmers and hedgerow management, 2019), and they affect crop yields by causing shade (Oreszczyn, Lane, 2000). Hedgerows contribute to the landscape diversity of the cultural landscape and break up its monotony (Golobic et al., 2015), and they often demarcate properties of different owners (Baudry, Bunce, Burel, 2000). They therefore have a great aesthetic importance, which is rarely written about and few studies have been conducted on it, but is an important factor in the conservation of hedgerows (Burel, Baudry, 1990). In Slovenia, hedgerows are one of the landscape features important for biodiversity conservation identified in the project Identification of landscape diversity and features important for biodiversity conservation (Golobic et al., 2015). Landscape features in­clude, e.g., water ditches, dry walls, riparian vegetation, hilly meadows, etc. On agri­cultural land, these features are crucial for the conservation of many species of flora and fauna, but also have many other beneficial functions for people and the landscape itself (Golobic et al., 2015). One of the objectives of the post-2020 Common Agricul­tural Policy is to strengthen the contribution of agriculture to biodiversity conserva­tion through the protection of the diversity of landscape features (Biodiversity and farmland landscapes, 2020). The common thread running through all these features is their conservation, particularly in intensively farmed landscapes, and extensive use of their immediate surroundings. Slovenia does not have adequate data to monitor the status of these elements or a unified system for their protection (Golobic et al., 2015). The quality of the different functions of hedgerows depends mainly on their struc­ture. For this reason, a number of authors (Boutin et al., 2002; Burel, Baudry, 1990; Garratt et al., 2017) have addressed the typology of hedgerows in their research (e.g. Allende Álvarez et al., 2021; Allende Álvarez, Gómez Mediavilla, López Estébanez, 2021). They agree that the best quality hedgerows are those that are multi-species, dense, composed of trees and shrubs, and intermingled with other hedgerows to form a system or network of hedgerows (Baudry, Bunce, Burel, 2000; Boutin et al., 2002; Forman, Baudry, 1984; Hedgerow Survey Handbook ..., 2007). For the purposes of our research, we have developed our own typology of hedge­rows, adapted to Slovenian conditions (Kastelic, 2019). The final typology includes five types of hedgerows: 1) Structured hedgerows are those that include all three layers of vegetation: trees, shrubs and herbs. They are vertically connected and provide a variety of habitats for many species, and are therefore of the highest quality from a nature conser­vation point of view. 2) Shrub hedgerows are made up of shrubs and herbs. Shrub vegetation is dense, creates vertical connectivity and is difficult to pass through. 3) Semi-structured hedgerows are made up of trees, shrubs and herbaceous vegeta­tion. The difference between the structured and the semi-structured type is that in the latter the shrub cover is thinner, lower and therefore the hedgerow is more passable. 4) Tree hedgerows are made up of trees and herbaceous vegetation. 5) Combined hedgerows are longer hedgerows in which at least two types of hedge­row alternate. Their characteristics depend on the types that make it up. Figure 2: Combined hedgerows (a combination of shrub and tree layers) are more abundant in the Ljubljana Marshes (photo: A. Kastelic). In terms of function (for people, fauna and landscape), structured hedgerows, which are composed of all three layers, are the most suitable, followed by shrub hedgerows and semi-structured hedgerows, while tree hedgerows are less suitable for e.g. nature conservation functions. Figure 3: Structured hedgerows in the Ljubljana Marshes have particularly important nature conservation functions, as they are located among intensive agricultural areas (photo: A. Kastelic). Figure 4: Tree hedgerows are formed by trees and herbaceous vegetation. An example of a tree hedgerow in the Ljubljana Marshes, which is losing its function due to intensive clearing and cutting and other uses (photo: B. Lampic). 3 PRESENCE AND VISIBILITY OF HEDGEROWS IN SLOVENIA Hedgerows are present throughout the country, but there are significant landscape differences. In the Karst, for example, they were created along drystacks (Šmid Hribar, 2008), while in Goricko they were used to border pastures (Domanjko, Malacic, 2009). Several theses have been written on their biological function, and Janez Božic wrote a publication on windbreaks in lowland areas of Slovenia as early as 1969 (Premrl, Turk, 2013). As a result, relatively little is known about the state of hedgerows in Slovenia, and those hedgerows that are included in the agricultural operation Conservation of Hedgerows are monitored in a slightly more systematic way. The Conservation of Hedgerows operation is one of the operations of the AECS measure in the CAP (2014–2020, to be implemented as a sub-measure also in the pro­gramme period 2023–2027). It supports the maintenance and conservation of hedge­rows in different types of agricultural land use and constitutes the preservation of one of the important elements of the agricultural landscape. The operation has been run­ning since 2017 and the farmer commits to at least five years of operation when enter­ing it. The amount of the payment for the implementation of the operation is EUR 1.60 per running metre per year (MAFF, 2019). The maintenance of the hedgerows must include thinning, removal of dead branches and pruning. Payments are made for the farmer’s loss of income (in some cases reduced yields due to shade, more dif­ficult cultivation) and for the extra work involved in maintaining the hedgerows (Cus, 2019; Žvikart, 2019). The most important is their pruning (every two years), but not during the bird nesting season (between 1 March and 30 September) (MAFF, 2019). Table 1: Number and length of hedgerows included in the Conservation of Hedgerows operation in seven Natura 2000 sites. Natura 2000 site Number of hedgerows Total length (m) Longest hedgerow (m) Shortest hedgerow (m) Average length (m) Krakovski gozd –Šentjernejsko polje 404 44.875 792 11 111 Reka valley 383 27.833 421 10 73 Vipava valley 123 8.783 328 15 71 Planinsko polje 298 27.368 586 13 92 The Ljubljana Marshes 2.720 290.876 1.254 11 107 Drava 286 32.793 691 14 115 Mura 308 26.030 545 15 85 Total 4.522 458.558 1.254 10 101 Source of data: MAFF, 2018b. In 2019, the Conservation of Hedgerows operation was implemented in seven Nat­ura 2000 sites (Krakovski gozd – Šentjernejsko polje, Reka valley, Vipava valley, Pla­ninsko polje, Ljubljansko polje, Drava, Mura) (MAFF, 2019). The operation includes areas where the hedgerows are most at risk of disappearing (Žvikart, 2019). The total number of hedgerows in the operation is 4,522 and their total length is 458,558 me­tres. The average length of a hedgerow is 101 metres, the longest is 1,254 metres and the shortest is 10 metres (MAFF, 2018b). Figure 5: Map of the implementation areas of the Conservation of Hedgerows operation in Slovenia. In 2018, 104 agricultural holdings took part in the Conservation of Hedgerows operation, maintaining a total of 134 kilometres of hedgerows. Around EUR 214,400 was paid to them as part of the operation. The majority of these, 90%, were farmers from the Ljubljana Marshes (Slov. Ljubljansko barje), while the number of farmers in­volved in the operation in other areas is modest (Cuš, 2019). The reasons for the large differences in the number of farmers registered between the areas are the number and length of the hedgerows. In the Ljubljana Marshes, they are the most numerous, the longest and a widely present element in the cultural landscape. The decision to join the operation is significantly influenced by the farmer’s attitude towards the hedge­row, the understanding of the operation itself and (above all) the activity and efforts of the agricultural advisors (Cus, 2019; Žvikart, 2019). The Conservation of Hedgerows operation is protecting and conserving 4,522 hedgerows in seven Natura 2000 sites (MAFF, 2018b). These hedgerows are (more) safe from clearing, while the remaining ones are still regularly cleared or deforested, as their protection, even in the area of the Ljubljana Marshes Landscape Park, is dif­ficult to achieve with the current legal framework. Even more worrying is the fact that we have no data and no information on what is happening to hedgerows in the rest of Slovenia. We have no information on their number, length, structure and current pro­cesses. If inappropriate practices are observed in the more protected areas of the op­eration, we can assume that the situation is even worse elsewhere. For example, in the Ljubljana Marshes Landscape Park, the clearing (i.e. destruction) of hedgerows has been found to be in breach of nature protection regulations. At the same time, after the removal of the hedgerows, the farmer was able to register the land (grassland) as arable land and receive agricultural payments without hindrance. The system of rules and agricultural regulations in Slovenia seems to work in a way that allows European agricultural payments to also be paid for practices that constitute a violation of nature and nature conservation regulations (Jancar, 2018). 4 LJUBLJANA MARSHES AS A PILOT AREA For further work, we selected the pilot area of the Ljubljana Marshes, where we fo­cused all further steps of the survey, including the field inventory of hedgerows. The Ljubljana Marshes are located in central Slovenia in the southern part of the Ljubljana Basin and cover 120 square kilometres (Pavšic, 2008). It is characterised by a mosaic landscape, an interlacement of arable fields, marsh meadows, pastures, canals, water­courses and hedgerows, which are one of the most important building blocks of the landscape (Strokovne podlage za ustanovitev ..., 2007). The main constraints to agri­cultural development are waterlogging and soil water, yet 82% of the area was culti­vated in 2017. Almost half of the arable land is cultivated with (silage) maize as a crop, which poses the risk of the Ljubljana Marshes becoming a monotonous monoculture landscape. The size of farms in the Ljubljana Marshes is above average (12.72ha) in relation to Slovenian conditions (Kmetijstvo na Ljubljanskem barju, 2019). Hedgerows are a traditional landscape feature in the Ljubljana Marshes. In the past, they were even more widespread, especially along canals. They were an important source of raw materials (timber) and marked the boundaries of plots owned by differ­ent owners, but today they are losing these functions. The density and composition of hedgerows vary considerably within the Ljubljana Marshes. For example, the vegeta­tion of the hedgerows on the periphery is dominated by willows, while the hedgerows in the interior are dominated by alders. Much of the tree and shrub cover was cleared during the establishment of graphic units of agricultural holdings use (GERKs). The intensification of agriculture has made them a nuisance for many farmers. In the Ljubljana Marshes, more farmers are involved in the Conservation of Hedgerows op­eration in the western part of the area, while the number of farmers involved in the operation is smaller in the eastern part. Most of the farmers in the operation have over 2000 metres of hedgerows, and two farmers have as much as 10 kilometres of hedgerows (Pecjak, 2019). Figure 6: Survey area in the northern part of the Ljubljana Marshes. The selected pilot area within the Ljubljana Marshes is two square kilometres in size and lies in a Natura 2000 site within the Ljubljana Marshes Landscape Park. The Land­scape Park’s protection regimes protect the hedgerows from cutting and maintenance works between 15 March and 30 September (Uredba o Krajinskem parku ..., 2008), but in practice there are problems with monitoring compliance with the regulations set out in the Regulation (Japelj, 2019). The pilot area is dominated by arable fields (54%) and marshy hedgerows (20%) (MAFF, 2018a), while structured and shrubby types are pre­dominant among the hedgerows, which are identified as the highest quality types (Kas­telic, 2019). Figure 7: A typical semi-structured hedgerow between meadows in the Ljubljana Marshes. 5 METHODS In 2016, the Slovenian Nature Conservation Agency (ZRSVN), under the mandate of the Ministry of Agriculture and Rural Development, prepared the first inventory layer of hedgerows in Slovenia (Bucik et al., 2017). The layer was based on digital orthophotos from 2014, where aerial photographs are transformed from central to orthogonal projec­tion and are dimensionally comparable to maps (Zbirke prostorskih ..., 2019). Due to the implementation of the Conservation of Hedgerows operation under the AECS, the layer was prepared in a short time and the identification of the hedgerows was based on the use of older orthophotos. Therefore, the quality of the first inventory layer was poorer in some places, as the hedgerows were recorded in a superficial way or there were errors due to changes in the actual use or removal of the hedgerows. The 2018 hedgerow layer has been updated and improved based on more recent orthophotos (from 2017) and field re­ports (Cuš, 2019; Žvikart, 2019). Both official boundary layers (2016 and 2018) were also field-checked for the purposes of the survey and a number of anomalies were found. Pre­liminary field work in 2017 in the north-eastern part of the Ljubljana Marshes recorded differences between the actual spatial situation and the 2016 hedgerow layer of record in 62% of the hedgerows (selected area). When the field verification was carried out again in 2019 (the 2018 hedgerow layer was verified), fewer differences were detected (Kastelic, 2019), demonstrating the key role of field verification of the status of hedgerows, as well as its complexity and time-consuming nature (Bucik et al., 2017; Kastelic, 2019). As the identification and recording of hedgerows directly using orthophoto im­ages and fieldwork did not prove to be optimal solutions for recording hedgerows, we identified hedgerows using lidar-captured data. We used imagery from the E-waters (Slov. E-vode) portal, which is maintained by Slovenian Environment Agency. We tested the method in a small pilot area (presented previously), where the hedgerows are more abundant and the location is close enough to Ljubljana. Laser scanning for the Ljubljana Marshes was carried out in 2014 and 2015, with a resolution of 10 pixels per m2 (Izvedba laserskega ..., 2015). The two-square-kilometre pilot area, located in the north of the Ljubljana Marshes, includes a variety of different types of grassland, and land use is heterogeneous. The base layer of lidar-captured data was filtered on the LAS DATASET layer and filtered on me­dium and high vegetation, as this corresponds to the criteria of a hedgerow. In order to find the best way to record the hedgerows using the lidar-captured data, two approaches were tested: approach 1 or canopy density, and approach 2 or reflection intensity. Figure 8: Schematic representation of the methodological approaches used with lidar-captured data. Figure 8 shows two different ways of processing the lidar data, resulting in two dif­ferent spatial representations of the hedgerows. Canopy density or canopy cover is an estimate of the ratio of ground to canopy tops as seen from the air. It was calculated using ground and vegetation point density data. The method is useful for measure­ments in nature, such as calculating biomass and vegetation cover (Estimating forest canopy density ..., 2019). Reflection intensity is the intensity of the reflected signal or the ratio of the inten­sity of the received light on the laser scanner. It is used as an aid in the identification of features and as a surrogate for aerial photographs. The map itself is a raster repre­sentation of the measured reflection intensity value. It covers one wavelength, namely the near-infrared part of the spectrum invisible to humans, which is only slightly larger than the wavelengths of the visible spectrum, so the display is quite similar to the perception of visible light. We can distinguish densely imaged points such as trees, houses, a road, especially at the surface, without height differences. It is difficult to predict the final range of values, as the final values depend on several variables, different sensors and are without a unit of measurement (Švab Lenarcic, Oštir, 2015). In the final stage, the line structures of the hedgerows were drawn manually, result­ing in two vector layers. All analyses were performed using ArcMap 10.7. 6 RESULTS Identification of hedgerows using different procedures (1. field recording (2017), 2. two approaches based on lidar-captured data, 3. two MAFF hedgerow inventory lay­ers (2016 and 2018)) yielded different results for the pilot area in the Ljubljana Marsh­es (Table 2). This is reflected in the number and total length of the hedgerows, which varies noticeably between all treatments. Table 2: The Ljubljana Marshes pilot area – recorded number and length of hedgerows with different approaches. Procedures Number of hedgerows Total length of hedgerows (m) Hedgerow inventory layer 2016 88 9.468 Field recording of hedgerows 2017 122 11.427 Hedgerow inventory layer 2018 101 10.536 Lidar-captured data – Canopy density 127 13.978 Lidar-captured data – Reflection intensity 130 12.788 Source of data: Bucik et al., 2017; MAFF, 2016; 2018b. An analysis of the hedgerows of the two official boundary inventory layers from 2016 and 2018 shows that the pilot area in 2018 recorded a higher number and total length of hedgerows. This situation surprised us, as the total number of hedgerows in the whole area of the Ljubljana Marshes decreased significantly during this period, from 2952 to 2720. The total length of the hedgerows also decreased (by 50,000 m) (MAFF, 2016; 2018b). These data point to the questionable suitability of the 2014 DOF imagery used to compile the 2016 hedgerow inventory layer. We looked at the problem in more detail in a smaller pilot area, where 88 hedgerows were included in the inventory layer in 2016 and 101 two years later. There could be several reasons for these differences. The changes are linked to an area with predomi­nantly arable land use. The analysis of land use in both years shows an abandonment of arable land and thus an increase in overgrowth, which may lead to the creation of new hedgerows. The previously mentioned first capture of hedgerows from older DOF images may contribute to the lower accuracy. The start of the implementation of the Conservation of Hedgerows operation (in 2017) has introduced changes in the way the hedgerows are managed, which could have an impact on their reduced clear­ing. The main differences between the inventory layer and the field inventory layer are mainly in the shrub hedgerows in the arable areas in the eastern part of the site. Shrub hedgerows are the type of hedgerow that grows most quickly and probably for this reason were not yet visible on the DOF imagery. In view of the above, the results of the inventory layers did not prove to be optimal, and we decided to develop two methodological approaches of our own, implemented using lidar-captured data, which are described in more detail in the methodology section of Chapter 5. The canopy density map (D) shows the density of tree and shrub canopies. The boxes were visible as line graphs of the canopy. When recording the hedgerows, care had to be taken to capture clearly visible linear vegetation, which could not be more than 20 metres wide. Two different methods (canopy density and reflection intensity) based on lidar-captured data gave different results. This is due to the different levels of visibility of the images. The difference also lies in the image of the hedgerows themselves. In the reflection intensity map, the hedgerows are represented by strips in which no woody vegetation forms can be discerned, whereas in the canopy density map, the canopy can be discerned, providing a clear view of even narrower strips of vegetation. Figure 9: Illustration and comparison of the different extent of recorded hedgerows identified by the different methods (on a section of the Ljubljana Marshes pilot area). Table 3: Number of recorded hedgerows with different methodological approaches in the Ljubljana Marshes pilot area. Hedgerow layer Inventory layer 2016 Inventory layer 2018 Field recording 2017 Lidar-captured data – canopy density Lidar-captured data – reflection intensity Inventory layer 2016 +13 +34 +39 +42 Inventory layer 2018 –13 +21 +26 +29 Field recording 2017 –33 –21 +5 +8 Lidar-captured data – canopy density –39 –26 –5 +3 Lidar-captured data – reflecti­on intensity –42 –29 –8 –3 Source of data: Bucik et al., 2017; MAFF, 2016; 2018b. The least number of hedgerows were identified in the two official records of hedge­rows (Inventory Layer 2016 and 2018) when recording the hedgerows in the Ljubljana Marshes pilot area. A larger number of more hedgerows were recorded through the field inventory of hedgerows and the two hedgerow layers that were created based on the lidar-captured data. The differences between these three hedgerow layers are also relatively small and we therefore conclude that these are more relevant. Table 4: Lengths of recorded hedgerows (in metres) using different methodological approaches in the Ljubljana Marshes. Hedgerow layer Inventory layer 2016 Inventory layer 2018 Field recording 2017 Lidar-captured data – canopy density Lidar-captured data – reflection intensity Hedgerow layer +1.068 +1.959 +4.510 +3.320 Inventory layer 2016 –1.068 +891 +3.442 +2.252 Inventory layer 2018 –1.959 –891 +2.551 +1.361 Field recording –4.510 –3.442 –2.551 –1.190 Lidar-captured data – canopy density –3.320 –2.252 –1.361 +1.190 Lidar-captured data – reflection intensity Source of data: Bucik et al., 2017; MAFF, 2016; 2018b. Interestingly, the 2018 hedgerow inventory layer, both in terms of number and total length of hedgerows, differs less from the lidar-captured hedgerows than the 2016 inventory layer. This result is partly surprising due to the smaller temporal differ­ence between the DOF imagery (which is the basis for the 2016 inventory layer) and the lidar imagery that was captured between 2014 and 2015. Our results suggest that the accuracy of the official 2016 hedgerow inventory layer is lower. The differences between the field inventory and the results of the two lidar approaches are minor, especially for the total number of hedgerows, but there are differences for the length of shrub hedgerows between fields. We find that different images show different visual perception of the hedgerows. This has an impact on the differences in their lengths in all the layers we captured digitally. During data analysis, we detected several differences between lidar and DOF images. These differences also indicate the advantages and disadvantages of using one data layer or the other. One important technical difference is the size of the files. A lidar image measuring one square kilometre is 101 MB in size, whereas a DOF image covering an area of five square kilometres is approximately 315 MB in size. Identify­ing boundaries is also more difficult on lidar layers than on DOF layers, as the latter make it easier and faster to identify the linear structures of the hedgerows. On the other hand, lidar data has the advantage that it can be filtered, so that only the middle and high vegetation can be seen in the image, making the linear structures clearer and easier to identify than in DOF images. The lidar images also lack the shadows that can appear in DOF images and hinder visual identification, while the lidar images make it easier to detect gaps between hedgerows. It is also worth mentioning that the identification of tree avenues and other (linear) plantations that do not belong to the hedgerow layer is a problem when recording hedgerows from both images. 7 CONCLUSION The Conservation of Hedgerows operation, which is implemented within the frame­work of the AECS measure, represents the first systematic attempt to conserve and maintain hedgerows in Slovenia. In seven areas in Slovenia (Krakovski gozd – Šentjernejsko polje, Reka valley, Vipava valley, Planinsko polje, Ljubljansko polje, Drava, Mura), where hedgerows are already identified in the hedgerow inventory layer, the issue of their maintenance and conservation has consequently started to be addressed more frequently among landowners, farmers and agricultural advisors (Cuš, 2019; Žvikart, 2019). In the new programming period, we can look forward to improving and expanding the different spatial layers for the implementation of nature conservation sub-interventions, which in practice will mean the extension of the re­cord layer of hedgerows to other areas of Slovenia (MAFF, 2021). In view of the problems identified by the nature conservation and agricultural sec­tors, related to the quality and maintenance of the official records of hedgerows, the search for more efficient ways to inventory new areas of hedgerows and to monitor their maintenance, the study focused on the development of methods to identify and establish the hedgerow layer. The existing system of monitoring and updating data is flawed and does not keep pace with the actual situation on the ground. Our more detailed research in the Ljubljana Marshes pilot area between 2017 and 2019 shows that none of the three tested methods of identifying and recording hedge­rows (from digital orthophotos, lidar-captured data, fieldwork) is entirely appropriate, but each approach has certain advantages and disadvantages. We note that an up-to-date spatial layer of hedgerows requires the use of the latest available data and different techniques, and although time-consuming, the methods need to be combined with field visits and inventories. The recording of hedgerows using lidar-captured data, in addition to the approaches presented in the paper, offers other possible solutions, but the identi­fication and recording methods already presented (and tested) could certainly be used to extend the recording layer of hedgerows to other areas in Slovenia. In conclusion, the illustrations of the hedgerows produced according to the differ­ent methodological approaches that we have carried out in the pilot area of the Lju­bljana Marshes differ. Differences are also likely to be found in other areas of hedgerows in Slovenia. Although there are no large differences in the number and length of the hedgerows between the procedures, the differences are important due to the fact that the agricultural payments for the Conservation of Hedgerows operation relate to the length of a hedgerow per linear metre. The payment in the 2014–2020 programming period was EUR 1.60 per linear metre of hedgerow and is intended to compensate the farmer for the costs incurred for their management and maintenance (MAFF, 2019). As we currently have no data on the extent and quality of the hedgerows outside the inventory layer in Slovenia, and conservation measures cannot be implemented else­where under the hedgerow operation, it is reasonable to expect that agricultural trends and other spatial pressures will put these features at even greater risk. The existing in­ventory of hedgerows also needs to be upgraded in terms of content. At present, only the length and connectivity of the hedgerows are monitored, but not their quality. We have already experimentally extended the monitoring attributes in the context of our survey by adding information on the type of hedgerows. The field definition of the type of hedgerow can be used to better assess or infer the extent and quality of the functions that a particular hedgerow can perform. 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Skladnejši regionalni razvoj se v Sloveniji spodbu­ja tako z nacionalno zakonodajo in ukrepi (Zakon o spodbujanju skladnega ..., 2011) kot tudi s kohezijsko politiko Evropske unije, ki krepi ekonomsko, socialno in teritorialno kohezijo, za prihajajoce programsko obdobje pa napoveduje še posebej veliko podpo­ro zelenemu in digitalnemu prehodu (Cohesion policy 2021–2027, 2021). Slovenija in njene regije niso zavezane k trajnostnemu razvoju le prek regionalne politike, temvec tudi s številnimi drugimi politikami in dokumenti, kot sta denimo krovni evropska in nacionalna strategija trajnostnega razvoja (Renewed EU sustainable development strategy, 2006; Strategija razvoja Slovenije 2030, 2017) ter Evropski zeleni dogovor (The European green deal, 2019), ki vsebinsko sledijo zlasti Agendi 2030 (Transfor­ming our world …, 2015) oziroma njeni predhodnici Agendi 21 (1992). Analiza v clanku se nanaša na dvanajst slovenskih statisticnih regij na ravni NUTS-3 (v nadaljevanju: regije), ki v Sloveniji nimajo statusa administrativnih enot, so pa vseeno odgovorne za nacrtovanje regionalne politike in izvajanje nalog regionalnega razvoja (Zakon o spodbujanju skladnega ..., 2011) kot tako imenovane razvojne regi­je. V ospredju zanimanja preucitve so bile znacilnosti regionalnega razvoja Slovenije in njihovo vrednotenje v luci približevanja ciljem trajnostnega kot tudi skladnejšega regionalnega razvoja na socialno-ekonomskem in okoljskem podrocju. V ta namen smo preucili štiri sintezne kazalnike (bruto domaci proizvod na prebivalca, ekološki odtis na prebivalca, indeks razvojne ogroženosti in kazalnik trajnostnega regionalne­ga razvoja) ter podrobneje še vseh 32 kazalnikov, vkljucenih v izracun kazalnika traj­nostnega regionalnega razvoja. Raziskava je na podlagi analize stanja in trendov po letu 2010 skušala odgovoriti na vprašanje, na katerih podrocjih se regije približujejo ciljem bolj skladnega in trajnostnega razvoja oziroma na katerih podrocjih izkazujejo najvecji zaostanek. 2 TEORETICNA IZHODIŠCA IN METODE Za regionalno politiko v Sloveniji je kljucnega pomena Zakon o spodbujanju skladne­ga regionalnega razvoja (2011), ki opredeljuje regionalno politiko kot strukturno po­litiko za doseganje skladnega regionalnega razvoja, pri cemer naj bi se vse odlocitve sprejemale v skladu z nacelom trajnostnega razvoja. Zakon doloca, da so temeljni stra­teški in programski dokumenti na ravni regij regionalni razvojni programi, ki se prip­ravljajo za vecletna programska obdobja, vlada pa doloca cilje in usmeritve zanje prek dveh strategij: strategije razvoja Slovenije in strategije prostorskega razvoja (Zakon o spodbujanju skladnega ..., 2011). Medtem ko je bila zadnja Strategija razvoja Slovenije za obdobje do leta 2030 sprejeta v letu 2017, je Strategija prostorskega razvoja do leta 2050 še vedno v postopkih priprave (Priprava Strategije …, 2021). Strategija razvoja Slovenije sicer skladnejšega regionalnega razvoja ne izpostavlja niti med strateškimi usmeritvami niti med cilji, a kljub temu na vec mestih poudari pomen enakomernej­šega razvoja države in njenih regij. Prav tako je osrednja ambicija strategije doseganje kakovostnega življenja za vse prebivalce, kar se nanaša na vse regije v državi in kar naj bi bilo možno doseci »z uravnoteženim gospodarskim, družbenim in okoljskim razvojem, ki upošteva omejitve in zmožnosti planeta ter ustvarja pogoje in priložnosti za sedanje in prihodnje rodove« (Strategija razvoja Slovenije, 2017, str. 17). Ker se v Sloveniji ne pripravlja vec samostojne državne strategije regionalnega razvoja (Pecar, 2020b), se lahko regije pri pripravi regionalnih razvojnih programov za programsko obdobje 2021–2027 opirajo le na navedeni strategiji ter usmeritve resornega ministr­stva (Operativni nacrt …, 2019) in vlade (Cilji, usmeritve in instrumenti …, 2019). Do leta 2030 morajo regionalni razvojni programi upoštevati štiri osnovne razvojne cilje (Cilji, usmeritve in instrumenti …, 2019, str. 21): • »dvig kakovosti življenja v vseh regijah z uravnoteženim gospodarskim, družbe­nim in okoljskim razvojem, ki temelji na nacelih trajnostnega razvoja, • razvojno dohitevanje evropskih regij, • zmanjšanje regionalnih razvojnih razlik, • uresnicevanje razvojnih potencialov in izkorišcanje globalnih priložnosti z mednarodnim medregionalnim povezovanjem in sodelovanjem«. V Sloveniji tako obstajajo podlage za spodbujanje skladnejšega regionalnega ra­zvoja, ki naj bi ob dvigu kakovosti življenja v vseh regijah stremel k zmanjševanju regionalnih razlik in doseganju ciljev trajnostnega razvoja na vseh temeljnih pod­rocjih (ekonomskem, socialnem in okoljskem). Pogreša pa se celovit in enoten nacin spremljanja ucinkov regionalne politike (Pecar, 2020b), saj zakon doloca le nacin raz­vršcanja regij po stopnji razvitosti s tako imenovanim indeksom razvojne ogroženosti (Zakon o spodbujanju skladnega ..., 2011), vladno gradivo za programsko obdobje 2021–2027 (Cilji, usmeritve in instrumenti …, 2019) pa za spremljanje posameznih ciljev predlaga vec kazalnikov, a zanje ne doloca ciljnih vrednosti. Kljub temu lahko v prihodnje na racun opredelitve teh kazalnikov pricakujemo dolocen napredek pri spremljanju ucinkov regionalne politike v primerjavi s predhodnimi obdobji. Za preucitev socialno-ekonomskih in okoljskih znacilnosti regionalnega razvoja slovenskih regij po letu 2010 smo uporabili štiri kljucne kazalnike, ki se lahko upora­bljajo na ravni regij in so izrazito sinteznega znacaja: bruto domaci proizvod (BDP) na prebivalca, indeks razvojne ogroženosti (IRO), ekološki odtis (EO) na prebival­ca in kazalnik trajnostnega regionalnega razvoja (KTRR). Izbrana so bila zadnja leta oziroma obdobja, za katera so na voljo razpoložljivi podatki in izracuni navedenih kazalnikov. V nadaljevanju smo bolj podrobno preucili trende v zadnjem desetletju prek KTRR, ki v svoj izracun vkljucuje kar 32 kazalnikov za ekonomske, socialne in okoljske vidike trajnostnega razvoja, med njimi tudi BDP na prebivalca in posamezne kazalnike, ki jih upošteva tudi IRO. BDP na prebivalca je že desetletja vodilni kazalnik gospodarske blaginje in gospo­darske rasti, neupraviceno pa se ga še vedno uporablja tudi za ponazarjanje socialno­-ekonomskega napredka in blaginje (Kalimeris in sod., 2020; van den Bergh, 2009; Ward in sod., 2016). Kljub mnogim metodološkim pomanjkljivostim smo ga izbrali za kljucni ekonomski kazalnik za potrebe osnovne primerjave regij, vec drugih kazal­nikov z ekonomskega podrocja namrec vkljucujeta tako KTRR kot tudi IRO. BDP na prebivalca je Strategija razvoja Slovenije (2017) dolocila za enega izmed šestih kljuc­nih kazalnikov za spremljanje uspešnosti strategije, po kateri ima država do leta 2030 cilj doseci povprecje BDP na prebivalca v Evropski uniji (v izhodišcnem letu 2015 je dosegala 83 % povprecnega BDP na prebivalca v Evropski uniji). Na drugi strani smo za vodilni okoljski kazalnik izbrali EO na prebivalca, ki izracu­nava obseg bioproduktivnih kopnih in vodnih površin, potrebnih za proizvodnjo virov, ki jih porablja povprecni prebivalec dolocenega obmocja, in za absorpcijo proizvedenih odpadkov. EO se izraža v globalnih hektarjih (gha) kot hektarjih s povprecno svetovno produktivnostjo (Global Footprint Network, 2019). Ceprav tudi ta kazalnik izkazuje mnoge metodološke omejitve (Galli in sod., 2016), je izjemno uporaben za ozavešcanje in komuniciranje problematike pretirane potrošnje (O'Neill in sod., 2018; Wiedmann, Barrett, 2010), zlasti še v luci preseganja nosilnih zmogljivosti okolja. Socasno se namrec izracunava tudi biokapaciteta obmocij oziroma zmogljivost biosfere, da zagotavlja in obnavlja naravne vire in storitve (Global Footprint Network, 2019). V Strategiji razvoja Slovenije (2017) je bil EO na prebivalca izbran za kazalnik pri vrednotenju doseganja cilja trajnostnega upravljanja naravnih virov. Strategija je za cilj zastavila, da se od izho­dišcnega leta 2013 do leta 2030 EO na prebivalca Slovenije zniža s 4,7 gha na prebivalca na 3,8 gha na prebivalca. Po zadnjih izracunih Global Footprint Networka (2021) je leta 2017 EO na prebivalca v Sloveniji znašal 4,9 gha in je tako za 2,7 gha presegal razpolo­žljivo biokapaciteto na prebivalca v državi. V analizi smo uporabili izracune ekološkega odtisa in biokapacitete slovenskih regij za leto 2016 iz študije, ki so jo Lin in sodelavci (2020) pripravili kot izhodišce za oblikovanje regionalnih razvojnih programov, za ka­tere je država dolocila, da se ekološki odtis uporablja kot vodilni kazalnik na podrocju okolja (Cilji, usmeritve in instrumenti …, 2019). Tretji izbrani kazalnik je IRO, katerega izracunavanje je predpisano v Zakonu o spodbujanju skladnega regionalnega razvoja (2011) in pripadajocem pravilniku za posamezno programsko obdobje (Pravilnik o razvrstitvi …, 2021). V skladu s tema dokumentoma IRO vkljucuje 14 kazalnikov: BDP na prebivalca, bruto dodana vred­nost na zaposlenega, bruto investicije v osnovna sredstva v % BDP, stopnja registri­rane brezposelnosti mladih (15–29 let), stopnja delovne aktivnosti (20–64 let), delež prebivalstva s terciarno izobrazbo (25–64 let), bruto domaci izdatki za raziskovalno in razvojno dejavnost v % BDP, delež precišcene odpadne vode s sekundarnim in terciarnim cišcenjem, delež varovanih obmocij, ocenjena škoda zaradi elementarnih nesrec v % BDP, stopnja registrirane brezposelnosti, indeks staranja prebivalstva, raz­položljivi dohodek na prebivalca in gostota poselitve. Zadnji izracuni IRO so na voljo za leto 2019 (Pecar, 2020a) in prav na njihovi podlagi je bilo opravljeno razvršcanje regij po stopnji razvitosti za programsko obdobje 2021–2027. Že pred uvedbo IRO v spremljanje ucinkov regionalne politike v Sloveniji je bil raz­vit KTRR, ki je bil izracunan za vec zaporednih obdobij od druge polovice 90. let 20. stoletja dalje z osnovnim namenom spremljanja oddaljevanja oziroma približevanja slo­venskih regij ciljem trajnostnega razvoja (Vintar, 2003; Vintar Mally, 2009; 2018; 2021). Tudi KTRR je doživel nekaj metodoloških sprememb zaradi (ne)razpoložljivosti podat­kov ali sprememb v zbiranju uporabljenih podatkov. Za obdobje 2015–2019 je bil KTRR izracunan na podlagi naslednjih 32 kazalnikov (Vintar Mally, 2021): • ekonomski kazalniki: BDP na prebivalca, bruto dodana vrednost na prebivalca, investicije v osnovna sredstva na prebivalca, povprecni izdatki za raziskovanje in razvoj v % BDP, razpoložljivi dohodek na prebivalca, delež zaposlenih v storitve­nih dejavnostih; • socialni kazalniki: delež brezposelnih s I. in II. stopnjo izobrazbe, delež žensk med brezposelnimi, gostota poselitve, indeks rasti prebivalstva, indeks staranja, povprecna starost umrlega, stopnja tveganja socialne izkljucenosti, stanovanjske površine na prebivalca, stopnja registrirane brezposelnosti, število študentov na 1000 prebivalcev, delež gospodinjstev z uporabo osebnih racunalnikov, delež višje- in visokošolsko izobraženih; • okoljski kazalniki: delež ekološko obdelanih kmetijskih zemljišc, gozdnate po­vršine na prebivalca, indeks rasti cestnega tovornega prometa, intenzivno ob­delana kmetijska zemljišca na prebivalca, delež gospodinjstev v onesnaženem okolju, komunalni odpadki na prebivalca, delež Natura 2000 obmocij, poraba vode na prebivalca, investicije v varstvo okolja v % BDP, delež pozidanih povr­šin, delež precišcene odpadne vode, delež stanovanj z daljinskim ogrevanjem, stopnja motorizacije, živinorejska gostota. Ugotovimo lahko, da IRO in KTRR vkljucujeta šest enakih socialno-ekonomskih kazalnikov (tj. BDP na prebivalca, delež prebivalstva s terciarno izobrazbo (25–64 let), stopnja registrirane brezposelnosti, indeks staranja prebivalstva, razpoložljivi dohodek na prebivalca in gostota poselitve), vendar se pri oblikovanju sestavljenega kazalnika uporabljata povsem razlicni metodi. Za KTRR je uporabljen izracun stan­dardnega odklona pri vsakem posameznem kazalniku, kar je osnova za razvršcanje regij v štiri razrede glede na oddaljenost vrednosti od povprecja regij in želene smeri gibanja kazalnika z vidika trajnostnega razvoja. Ocena (++, +, - ali - -), ki je regiji dodeljena pri vsakem kazalniku, je izhodišce za izracunavanje povprecne ocene regije na vsakem izmed treh razvojnih podrocij – ekonomskem, socialnem in okoljskem – in povprecne vrednosti vseh treh podrocij, ki je vrednost KTRR (Vintar Mally, 2021). Pri IRO se izracunavajo standardizirane vrednosti za vsak kazalnik na lestvici od 0 do 1, in sicer na podlagi uporabe minimalnih in maksimalnih vrednosti, ki se pojav­ljajo v regijah pri posameznih kazalnikih. Medtem ko ima pri IRO vsak izmed štiri­najstih kazalnikov enako težo oziroma vpliv na koncni rezultat (Pecar, 2018), imajo pri KTRR enako težo le kazalniki znotraj posameznega podrocja (ekonomskega, so­cialnega in okoljskega), na koncno višino KTRR regije pa ima enak vpliv vsako izmed treh podrocij. Sklenemo lahko, da imajo okoljski kazalniki pri KTRR tretjinski vpliv na koncno vrednost sestavljenega kazalnika, pri IRO pa najvec petino vpliva (tj. trije kazalniki od skupno 14, ce ob kazalnikih o deležu precišcene odpadne vode in deležu varovanih obmocij za okoljski kazalnik štejemo tudi ocenjeno škodo zaradi elemen­tarnih nesrec). 3 REZULTATI IN RAZPRAVA Z vidika bolj skladnega in trajnostnega razvoja je zaželeno zviševanje materialne bla­ginje in z njo tudi rast bruto domacega proizvoda. V letu 2019 je bil najnižji BDP na prebivalca v Zasavski (12.287 EUR na prebivalca) in najvišji v Osrednjeslovenski regiji (32.620 EUR na prebivalca), razmerje med obema regijama pa je po tem kazalniku znašalo 1 : 2,7. Navedeno kaže na še vedno velike razlike med regijami, ki so se v ob­dobju 2010–2019 povecale (leta 2010 je bilo razmerje 1 : 2,4) (SURS, 2021). V trojici gospodarsko najšibkejših regij so bile Zasavska, Pomurska in Primorsko-notranjska regija, med najmocnejšimi pa ob Osrednjeslovenski regiji še Jugovzhodna Slovenija in Obalno-kraška regija (preglednica 1). V zgornjo polovico lestvice so se tako uvrstile vse statisticne regije, ki na NUTS-2 ravni tvorijo kohezijsko regijo Zahodna Sloveni­ja (tj. Osrednjeslovenska, Obalno-kraška, Gorenjska in Goriška regija), dodatno pa tudi Jugovzhodna Slovenija in Savinjska regija iz kohezijske regije Vzhodna Slovenija (slika 1). Podobne rezultate kažejo tudi izracuni IRO, po katerih se rangi pri devetih regijah povsem ujemajo oziroma razlikujejo za najvec eno mesto s tistimi pri BDP na prebivalca, medtem ko se je Podravska regija po IRO uvrstila za dve mesti slabše kot po BDP na prebivalca, Zasavska in Gorenjska pa za tri mesta višje. Po izracunih IRO za leto 2019 se je za najbolj razvito oziroma najmanj razvojno ogroženo izkazala Osrednjeslovenska regija (indeks 49,6), za najmanj razvite pa Pomurska (172,5), Pri­morsko-notranjska (138,3) in Podravska regija (133,4). Primerjava rezultatov IRO za leti 2014 in 2019 je pokazala, da so se v vecini regij kazalniki, ki so vkljuceni v IRO, izboljšali, vendar se je zaostanek regij za Osrednjeslovensko še povecal in s tem tudi razlika med najbolje in najslabše uvršcenima regijama (Pecar, 2020a). Izracuni BDP in IRO torej kažejo napredek regij, a tudi povecanje medregionalnih razlik. Preglednica 1: Primerjava rezultatov slovenskih staticnih regij po izbranih razvojnih kazalnikih. BDP na prebivalca (€), 2019 Ekološki odtis na prebivalca (gha), 2016 Biokapa­citeta na prebivalca (gha), 2016 Indeks razvojne ogrože­nosti, 2019 Kazalnik trajnostnega regionalne­ga razvoja, 2015–2019 Osrednjeslovenska 32.620 5,28 1,11 49,6 0,73 Jugovzhodna Slovenija 23.096 5,27 5,38 93,0 0,48 Gorenjska 20.790 5,29 2,69 85,3 0,48 Goriška 20.707 5,29 5,30 117,1 0,44 Obalno-kraška 22.894 5,26 2,54 103,2 0,18 Primorsko-notranjska 16.154 5,25 8,02 138,3 0,17 Koroška 18.694 5,40 3,98 127,7 -0,09 Savinjska 20.954 5,19 2,15 109,3 -0,31 Posavska 19.456 5,19 3,03 121,8 -0,36 Zasavska 12.287 5,16 2,18 132,3 -0,45 Podravska 18.887 5,18 1,46 133,4 -0,59 Pomurska 15.705 5,15 2,46 172,5 -0,82 Slovenija 23.165 5,24 2,50 / / Viri: Lin in sod., 2020; Pecar, 2020a; SURS, 2021; Vintar Mally, 2021. Opomba: s krepko pisavo so zapisane najugodnejše vrednosti posameznih kazalnikov. V primerjavi z rezultati predhodno predstavljenih, pretežno socialno-ekonomskih kazalnikov, se regije razvršcajo povsem drugace po EO na prebivalca kot sinteznem kazalniku pritiskov na okolje. Pri tem kazalniku so za trajnostni razvoj slovenskih regij ugodnejše nižje vrednosti, zato so najvišje uvršcene regije z najnižjimi pritiski na oko­lje. Leta 2016 je imela najnižji EO na prebivalca Pomurska regija s 5,15 gha na prebi­valca, najvecjega pa Koroška regija s 5,40 gha na prebivalca, kar je v tej regiji posledica nadpovprecno visokega odtisa prometa in gospodinjstev (Lin in sod., 2020). Slovenija veckratno presega razpoložljivo globalno biokapaciteto na prebivalca, ki znaša 1,6 gha, prav tako pa tudi biokapaciteto svojega ozemlja. Razvojno neugodna je tudi ugotovi­tev, da se je ekološki odtis države od zacetka 90. let 20. stoletja vecinoma poveceval, z izjemo vecjega upada, ki je sledil svetovni financno-gospodarski krizi pred dobrim desetletjem (Global Footprint Network, 2021). Primerjava biokapacitete in EO na pre­bivalca (preglednica 1) za vecino regij pokaže ekološki deficit, saj EO prebivalcev regije bistveno presega biokapaciteto njenega ozemlja. Po višini ekološkega deficita najbolj izstopata Osrednjeslovenska (4,17 gha na prebivalca) in Podravska regija (3,72 gha na prebivalca). Le tri regije z najvecjo biokapaciteto – Primorsko-notranjska, Jugovzhodna Slovenija in Goriška regija – izkazujejo presežek biokapacitete nad ekološkim odtisom, kar je predvsem posledica najbolj obsežnih gozdnatih površin v razmerju do števila prebivalcev. Ekološki deficit kaže, da je razvojni vzorec v državi izrazito netrajnosten in da se v vecini regij socialno-ekonomski razvoj odvija na racun izcrpavanja global­nih ali lokalnih okoljskih virov in onesnaževanja okolja. Glede na nacin izracunavanja ekološkega odtisa so ti ucinki porazdeljeni na vsa obmocja, s katerih se prebivalci regij oskrbujejo z blagom in storitvami kot tudi viri surovin in energije. Razlike v višini EO na prebivalca so med regijami bistveno manjše od razlik v bruto domacem proizvodu, na podlagi cesar bi lahko sklepali, da se v gospodarsko uspešnejših regijah ustvarja viš­ja dodana vrednost s primerjalno manjšimi pritiski na okolje. Najvecje razlike v rangih po BDP na prebivalca in EO na prebivalca so v Pomurski in Zasavski regiji, ki imata najnižji vrednosti EO na prebivalca in hkrati tudi najnižji vrednosti BDP na prebivalca. V povprecju se rangi regij po obeh kazalnikih razlikujejo za pet mest, nadpovprecno še pri Osrednjeslovenski regiji (prva po BDP na prebivalca in deveti najvišji EO na pre­bivalca) in Jugovzhodni Sloveniji (druga po BDP na prebivalca in osmi najvišji EO na prebivalca). Podobno velike so tudi razlike v rangih EO na prebivalca in IRO. Slika 1: Rangi slovenskih statisticnih regij po izbranih razvojnih kazalnikih, 2015–2019. KTRR enakovredno vkljucuje v izracun tako kazalnike z ekonomskega, socialnega kot tudi okoljskega podrocja, zato so že v izhodišcu pricakovani drugacni rezultati kot pri predhodnih kazalnikih. Razvršcanje regij po KTRR je primerjalno bližje razvr­šcanju po višini IRO kot pa po izkljucno ekonomskem (BDP na prebivalca) ali okolj­skem kazalniku (EO na prebivalca). Poleg izbire vkljucenih kazalnikov na razlike med KTRR in IRO najbolj vpliva dejstvo, da imajo pri KTRR socialni in ekonomski kazal­niki manjšo težo oziroma enako kot okoljski (tj. vsako podrocje ima tretjino vpliva). Najvišje uvršcene po KTRR so regije v zahodnem delu države: Osrednje­slovenska, Gorenjska, Jugovzhodna Slovenija, Goriška, Obalno-kraška in Primorsko-notranjska regija. Rangi IRO in KTRR so se v osmih regijah razlikovali za najvec eno mesto, med­tem ko je bila Goriška regija po KTRR uvršcena za dve mesti višje (na cetrto mesto po KTRR) in Posavska regija za dve mesti nižje (na deveto mesto po KTRR). Najbolj sta odstopali Savinjska regija, ki se je po KTRR uvrstila za tri mesta nižje (na osmo mesto) kot po IRO, Primorsko-notranjska pa kar za pet mest višje (na šesto mesto) kot po IRO. Za izracun KTRR je bilo na ekonomskem podrocju upoštevanih šest kazalnikov, na socialnem podrocju dvanajst in na okoljskem podrocju štirinajst kazalnikov. Tudi primerjava rezultatov regij po podrocjih KTRR (preglednica 2) pokaže na velik razko­rak v rangih regij na socialnem in ekonomskem podrocju v primerjavi z rangi regij na okoljskem podrocju (slika 2). Medtem ko se regije na zahodu države, zlasti še tiste iz kohezijske regije Zahodna Slovenija, uvršcajo po ekonomskih in socialnih kazalnikih na vrh lestvice, rezultati pri okoljskih kazalnikih bistveno odstopajo od tega vzorca. Najbolj izrazit primer je Osrednjeslovenska regija, ki zaseda prvo mesto na ekonom­skem in drugo na socialnem podrocju, na okoljskem podrocju pa se je uvrstila na zadnje mesto. Znaten razkorak med ugodnostjo socialno-ekonomskega in okoljskega podrocja za dolgorocni trajnostni razvoj je tudi v Obalno-kraški in Gorenjski regi­ji. Na drugi strani pa sta na okoljskem podrocju zasedli prvi dve mesti Zasavska in Koroška regija, ki sta med socialno-ekonomsko šibkejšimi. Ceprav so v obeh regijah prisotna obmocja starih okoljskih bremen, pa po kazalnikih pritiskov na okolje (npr. poljedelstva, prometa, pozidanih površin, rabe vode in nastajanja odpadkov) in kazal­nikih odzivov (npr. ekološko kmetijstvo, daljinsko ogrevanje) kažeta nadpovprecno ugodno stanje in trende. Preglednica 2: Povprecne ocene slovenskih statisticnih regij na glavnih razvojnih podrocjih in kazalnik trajnostnega regionalnega razvoja, 2015–2019. Ekonomski kazalniki Socialni kazalniki Okoljski kazalniki Kazalnik trajnostnega regionalnega razvoja vrednost rang Osrednjeslovenska 1,83 1,00 -0,64 0,73 1 Jugovzhodna Slovenija 0,83 0,25 0,36 0,48 2–3 Gorenjska 0,33 1,25 -0,14 0,48 2–3 Goriška 0,33 0,92 0,07 0,44 4 Obalno-kraška 0,50 0,33 -0,29 0,18 5 Primorsko-notranjska -0,67 0,67 0,50 0,17 6 Koroška -0,67 -0,17 0,57 -0,09 7 Savinjska 0,00 -0,42 -0,50 -0,31 8 Posavska -0,67 -0,42 0,00 -0,36 9 Zasavska -1,17 -0,83 0,64 -0,45 10 Podravska -0,83 -0,50 -0,43 -0,59 11 Pomurska -1,17 -1,00 -0,29 -0,82 12 Vir: Vintar Mally, 2021. Primerjava izracunov KTRR za obdobje 2015–2019 s predhodnimi obdobji je po­kazala, da se je najbolj spreminjal prav položaj regij na okoljskem podrocju, medtem ko so razlike na socialnem in ekonomskem podrocju bolj zakoreninjene oziroma so razmerja manj spremenljiva (Vintar Mally, 2018; 2021). Prav tako se je v obdobju 2015–2019 ponovno potrdilo, da so bile razlike med regijami najmanjše na okoljskem podrocju, kjer je znašala razlika med najboljše ocenjeno Zasavsko regijo in najslabše ocenjeno Osrednjeslovensko regijo 1,28. Na ekonomskem podrocju je znašala razlika med najbolje in najslabše uvršceno regijo 3,0, na socialnem podrocju pa 2,25. Z vidika skladnejšega razvoja slovenskih regij je spodbudna predvsem ugotovitev, da so se pri ekonomskih kazalnikih KTRR nekoliko zmanjšale razlike, medtem ko so na social­nem podrocju ostale nespremenjene. Zelo malo se je v zadnjem desetletju spremenil tudi vrstni red regij po višini KTRR (preglednica 3), saj so le tri regije spremenile mesto na lestvici kot posledica dejstva, da sta Jugovzhodna Slovenija in Gorenjska v zadnjem obdobju prehiteli Goriško regijo, ki je bila predhodno na drugem mestu. Slika 2: Rangi slovenskih statisticnih regij na glavnih razvojnih podrocjih in pri kazalniku trajnostnega regionalnega razvoja, 2015–2019. Preglednica 3: Primerjava kazalnika trajnostnega regionalnega razvoja v obdobjih 2010–2014 in 2015–2019. 2010–2014 2015–2019 vrednost rang vrednost rang Osrednjeslovenska 0,85 1 0,73 1 Jugovzhodna Slovenija 0,44 3 0,48 2–3 Gorenjska 0,32 4 0,48 2–3 Goriška 0,45 2 0,44 4 Obalno-kraška 0,30 5 0,18 5 Primorsko-notranjska 0,27 6 0,17 6 Koroška -0,14 7 -0,09 7 Savinjska -0,17 8 -0,31 8 Posavska -0,54 9 -0,36 9 Zasavska -0,70 10 -0,45 10 Podravska -0,76 11 -0,59 11 Pomurska -0,77 12 -0,82 12 Vir: Vintar Mally, 2018; 2021. Podrobnejša preucitev rezultatov za vseh 32 kazalnikov, ki so bili vkljuceni v izra­cun KTRR v obdobjih 2010–2014 in 2015–2019, nudi še boljši vpogled v socialno­-ekonomske in okoljske znacilnosti regionalnega razvoja po letu 2010 in v ugodnost teh trendov za trajnostni razvoj države. Na socialno-ekonomskem podrocju je prišlo do izboljšanja pri vecini analiziranih kazalnikov, saj so regije napredovale v smeri gospodarskih ciljev trajnostnega razvoja, zmanjšala se je brezposelnost (na splošno in pri razlicnih skupinah prebivalcev) in izboljšala izobrazba prebivalcev, ki v povprecju živijo dlje in v boljših stanovanjskih razmerah. Med neugodnimi socialno-ekonom­skimi trendi velja izpostaviti povprecno zmanjšanje izdatkov za raziskovanje in razvoj, staranje prebivalstva, upadanje prebivalstvene rasti v nekaterih regijah in zgošcevanje prebivalstva v drugih. Za razliko od socialno-ekonomskih kazalnikov je primerjava trendov in stanja pri okoljskih kazalnikih pokazala vecinoma oddaljevanje od ciljev trajnostnega razvoja. Bolj trajnostne prakse smo tako v povprecju zasledili na po­drocju ogrevanja gospodinjstev s širjenjem daljinskega ogrevanja in v kmetijstvu s širjenjem ekološkega kmetijstva ter zmanjševanjem pritiskov na intenzivno obdelanih kmetijskih zemljišcih in s strani živinoreje. Neugodni so zlasti trendi povecevanja rabe vode, narašcanja kolicin komunalnih odpadkov, širjenja pozidanih površin, rasti cestnega tovornega prometa, povecevanja stopnje motorizacije in zniževanja deleža investicij v varstvo okolja, medtem ko ostaja obseg ekološko pomembnih obmocij, kot so obmocja Natura 2000 in površine gozda na prebivalca, vecinoma nespremenjen. Ob tem je treba izpostaviti, da opisano ne velja za vse regije enako in da so nekatere vseeno uspele doseci izboljšanje tudi na podrocjih, kjer tega povprecje ne kaže. Na podlagi preucitve posamicnih ekonomskih, socialnih in okoljskih kazalnikov trajnostnega razvoja smo lahko posebej identificirali tista podrocja, na katerih je re­lativni zaostanek regije za povprecjem najvecji in na katera bi bilo treba prioritetno usmeriti prizadevanja za doseganje ciljev bolj skladnega in trajnostnega razvoja v po­sameznih regijah (preglednica 4). Preglednica 4: Podrocja, na katerih posamezne slovenske statisticne regije izkazujejo z vidika trajnostnega razvoja izrazito neugodno stanje ali trende. Statisticna regija Podrocje Statisticna regija Podrocje Pomurska • višina razpoložljivega dohodka na prebivalca, • upadanje števila prebivalcev, • staranje prebivalstva*, • stopnja brezposelnosti*, • višje- in visokošolsko izobraževanje – zastopanost študentov, delež diplomantov, • obseg intenzivno obdelanih kmetijskih zemljišc*, • razširjenost ekološkega kmetijstva, • delež gospodinjstev, živecih v onesnaženem okolju*, • razširjenost daljinskega ogrevanja gospodinjstev. Podravska • višina razpoložljivega dohodka na prebivalca, • življenjsko pricakovanje – starost ob smrti, • stopnja tveganja socialne izkljucenosti*, • obseg gozdnatih površin, • delež pozidanih površin*. Zasavska • višina bruto domacega proizvoda, • ustvarjena dodana vrednost na prebivalca, • investicije v osnovna sredstva, • upadanje števila prebivalcev, • stopnja tveganja socialne izkljucenosti*, • obseg stanovanjskih površin, • raba racunalnikov v gospodinjstvih, • delež gospodinjstev, živecih v onesnaženem okolju*, • delež Natura 2000 obmocij. Posavska • življenjsko pricakovanje – starost ob smrti. Statisticna regija Podrocje Statisticna regija Podrocje Savinjska • obseg stanovanjskih površin, • delež gospodinjstev, živecih v onesnaženem okolju*, • delež Natura 2000 obmocij, • delež precišcene odpadne vode. Koroška • zaposlenost v storitvenih dejavnostih, • brezposelnost žensk*, • življenjsko pricakovanje – starost ob smrti, • stopnja tveganja socialne izkljucenosti*, • živinorejska gostota*. Primor­sko-no­tranjska • rast cestnega tovornega prometa*, • razširjenost daljinskega ogrevanja gospodinjstev, • stopnja motorizacije*. Obalno-kraška • višje- in visokošolsko izobraževanje – zastopanost študentov, • rast cestnega tovornega prometa*, • kolicine komunalnih odpadkov*, • raba vode*. Goriška • raba vode*, • delež precišcene odpadne vode, • stopnja motorizacije*. Gorenjska • živinorejska gostota*. Jugov­zhodna Slovenija • zaposlenost v storitvenih dejavnostih, • brezposelnost slabše izobraženih*, • raba racunalnikov v gospodinjstvih. Osrednje-slovenska • rast gostote poselitve*, • obseg gozdnatih površin, • delež pozidanih površin*, • delež precišcene odpadne vode. Opomba: Pri posamezni regiji so izpostavljena le tista podrocja, na katerih je bil rezultat regije za vec kot en standardni odklon slabši od povprecja regij (tj. ocena – – z vidika ugodnosti za trajnostni razvoj). *Zviševanje vrednosti na tem podrocju pomeni oddaljevanje od trajnostnega razvoja. 4 SKLEPI S preucitvijo izbranih kazalnikov smo ugotovili, da je bil razvojni napredek slovenskih statisticnih regij po letu 2010 omejen le na posamezna socialno-ekonomska in okolj­ska podrocja ali razmerja. V splošnem ne moremo potrditi, da regije napredujejo v smeri ciljev trajnostnega in skladnejšega razvoja, saj preuceni kazalniki ne kažejo, da bi bil v zadnjem desetletju razvoj na ekonomskem, socialnem in okoljskem podrocju uravnotežen in da bi se regionalne razvojne razlike zmanjševale. Ceprav se je BDP na prebivalca v državi in regijah zviševal, so se razlike med re­gijami postopoma nekoliko povecale. Podobno se ugotavlja tudi na podlagi izracu­nov IRO, katerega kazalniki sicer kažejo izboljšanje stanja, a hkrati tudi povecanje medregionalnih razlik (Pecar, 2020a). Na okoljskem podrocju ne prihaja do želenega zmanjšanja pritiskov na okolje, država in vecina regij ob tem izkazujejo tudi ekološki deficit, ki opozarja na netrajnostni razvojni vzorec, po katerem se socialno-ekonom­ski razvoj odvija na racun degradacije okolja. Višji ekološki odtis in slabše rezultate na okoljskem podrocju trajnostnega razvoja imajo regije z zahodne polovice države (zlasti iz kohezijske regije Zahodna Slovenija), ki se sicer po socialnih in ekonomskih kazalnikih uvršcajo med najuspešnejše. Izjema je Primorsko-notranjska regija, saj je po razvojnih znacilnostih bolj podobna regijam z vzhodnega dela države. Predvsem iz opazovanja trendov pri KTRR izhaja ugotovitev, da so se na ekonom­skem podrocju razlike med regijami po letu 2010 nekoliko zmanjšale, medtem ko tega ni moc potrditi za socialno in okoljsko podrocje. Posebej pogosto so se rangi regij spreminjali pri okoljskih kazalnikih. Na eni strani vecina socialnih in ekonomskih ka­zalnikov KTRR v zadnjem desetletju kaže na približevanje ciljem trajnostnega razvoja (npr. zmanjšanje brezposelnosti, izboljšanje izobrazbe, daljše življenjsko pricakovanje, boljše stanovanjske razmere, višji dohodki ipd.), na drugi strani pa vecina okoljskih kazalnikov še vedno kaže na oddaljevanje od njih, kar se ujema tudi z ugotovitvami pri ekološkem odtisu in je povezano zlasti s povecevanjem rabe naravnih virov. Pri interpretaciji rezultatov je treba upoštevati, da preuceni kazalniki pokrivajo le omejeno število znacilnosti regionalnega razvoja in še vedno izkazujejo mnoge me­todološke pomanjkljivosti. Za bolj konkretno spremljanje ucinkovitosti regionalne politike bi bilo priporocljivo dogovoriti ciljne vrednosti za posamezne kazalnike in vzpostaviti celovit, poenoten sistem vrednotenja. Posamezne regije se soocajo z raz­nolikimi razvojnimi izzivi, zato bi si morala slovenska regionalna politika v prihodnje bolj ciljno prizadevati za preusmerjanje napredka v smer trajnostnega razvoja na tis­tih podrocjih, kjer se trenutno od njih odmikamo, poleg tega pa posebno pozornost namenjati podrocjem, na katerih posamezne regije najbolj zaostajajo, saj bo v naspro­tnem primeru težko zmanjšati regionalne razvojne razlike in dosegati ustrezno raven blaginje v okviru nosilnih zmogljivosti okolja. Zahvala Raziskavo je financno podprla Javna agencija za raziskovalno dejavnost Republike Slove­nije v okviru raziskovalnega programa Trajnostni regionalni razvoj Slovenije (P6-0229). Literatura in viri Agenda 21. 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Ljubljana: Uradni list Repu­blike Slovenije. 1 INTRODUCTION Over the past two decades, the long-term efforts of Slovenia’s regional policy to reduce development disparities in the country have been increasingly backed by support for more sustainable development patterns. More balanced regional development in Slovenia is promoted by national legislation and measures (Promotion of Balanced Regional..., 2011) as well as by the cohesion policy of the European Union, which encourages economic, social and territorial cohesion. The upcoming programming period anticipates particularly strong support for the green and digital transition (Co­hesion Policy 2021–2027, 2021). Slovenia and its regions are committed to sustainable development not only through regional policy but also through many other policies and documents, such as the umbrella European and national strategy for sustainable development (Renewed EU Sustainable Development Strategy, 2006; Slovenian De­velopment Strategy 2030, 2017) and The European Green Deal (2019), the contents of which closely follow Agenda 2030 (Transforming Our World…, 2015) and its prede­cessor Agenda 21 (1992). The analysis presented in this article is based on the twelve Slovenian statistical regions at the NUTS-3 level (hereinafter: regions), which do not have the status of administrative units in Slovenia but are nevertheless responsible for regional policy planning and regional development tasks (Promotion of Balanced Regional..., 2011) as so-called development regions. The focus of the research was on the characteristics of Slovenia’s regional development and its evaluation in the light of approaching the goals of sustainable as well as more balanced regional development in the socioeco­nomic and environmental fields. For this purpose, we examined four synthetic indica­tors (gross domestic product per capita, ecological footprint per capita, development risk index and indicator of sustainable regional development) and also studied in more detail all 32 indicators included in the calculation of the indicator of sustainable regional development. Based on the analysis of the current state as well as trends after 2010, the study sought to answer the question in which areas regions are approaching the goals of more balanced and sustainable development and in which areas they are most lagging behind. 2 THEORETICAL BACKGROUND AND METHODS The Promotion of Balanced Regional Development Act (2011) is of key importance for regional policy in Slovenia. It defines regional policy as a structural policy for achieving balanced regional development, with all decisions to be taken in keeping with the principle of sustainable development. The Act stipulates that regional devel­opment programs prepared for multi-year programming periods are the basic strate­gic and program documents at the regional level, and the government sets goals and guidelines for them through two strategies: Slovenia’s development strategy and spa­tial development strategy (Promotion of Balanced Regional..., 2011). While the most recent Slovenian Development Strategy for the period until 2030 was adopted in 2017, the Strategy for Spatial Development until 2050 is still in preparation (Priprava Strategije…, 2021). Slovenia’s development strategy does not prioritize more coher­ent regional development either in terms of strategic guidelines or goals, but it nev­ertheless emphasizes the importance of more balanced development for the country and its regions in several places. The central ambition of the strategy is to achieve a high quality of life for all inhabitants, which applies to all regions in the country and which can be achieved “through balanced economic, social and environmental de­velopment which takes account of the planet’s limitations and creates conditions and opportunities for present and future generations” (Slovenian Development Strategy 2030, 2017, p. 17). As Slovenia no longer prepares an independent national strategy for regional development (Pecar, 2020b), the regions can only rely on the said strate­gies and the guidelines of the line ministry (Operativni nacrt…, 2019) and the gov­ernment (Cilji, usmeritve in instrumenti…, 2019) in preparing regional development programs for the 2021–2027 programming period. By 2030, regional development programs must take into account four basic development objectives (Cilji, usmeritve in instrumenti…, 2019, p. 21): • “raising the quality of life in all regions through balanced economic, social and environmental development based on the principles of sustainable development, • catching up with European regions in terms of development, • reducing regional development disparities, • realization of development potential and exploitation of global opportunities through international interregional integration and cooperation”. Thus Slovenia has a basis for the promotion of more balanced regional develop­ment, which, while increasing the quality of life in all regions, is expected to reduce regional disparities and achieve the goals of sustainable development in all basic ar­eas (economic, social and environmental). However, a comprehensive and unified approach to monitoring the results of regional policy is lacking (Pecar, 2020b), as the law only determines the method for classifying regions according to the level of development with the so-called development risk index (Promotion of Balanced Re­gional..., 2011); government materials for the programming period 2021–2027 (Cilji, usmeritve in instrumenti…, 2019) propose several indicators for monitoring indi­vidual objectives but do not set target values for them. Nevertheless, in the future we can expect some progress in monitoring the effects of regional policy compared to previous periods with the defining of these indicators. To study the socioeconomic and environmental characteristics of the regional de­velopment of Slovenian regions after 2010, we used four key indicators that can be used at the regional level and are highly synthetic: gross domestic product (GDP) per capita, development risk index (DRI), ecological footprint (EF) per capita and the indicator of sustainable regional development (ISRD). The last years or periods for which data and calculations of the above-mentioned indicators are available were selected. We then examined the trends of the last decade in more detail through the ISRD, which includes as many as 32 indicators for economic, social and environ­mental aspects of sustainable development, including GDP per capita and individual indicators that are also taken into account by the DRI. GDP per capita has been a leading indicator of economic prosperity and growth for decades, but its continued use to reflect socioeconomic progress and welfare is unjustified (Kalimeris et al., 2020; van den Bergh, 2009; Ward et al., 2016). Despite its many methodological shortcomings, it was chosen as a key economic indicator for the needs of a basic comparison of regions, as several other indicators in the economic field include both the ISRD and the DRI. GDP per capita was set by the Slovenian Development Strategy 2030 (2017) as one of six key indicators for monitoring the success of the strategy, according to which the country aims to achieve the average GDP per capita in the European Union by 2030 (in the base year 2015, the country had reached 83% of the average GDP per capita in the European Union). At the same time, we have chosen the EF per capita as the leading environmental indicator, which calculates the amount of bioproductive land and water areas needed to produce resources consumed by the average inhabitant of a given area and to ab­sorb the waste generated. The EF is expressed in global hectares (gha) as hectares with average global productivity (Global Footprint Network, 2019). Although this indicator also has many methodological limitations (Galli et al., 2016), it is extremely useful for raising awareness and communicating the problem of excessive consump­tion (O’Neill et al., 2018; Wiedmann, Barrett, 2010), especially in terms of exceed­ing the carrying capacity of the environment. At the same time, the biocapacity of regions as the capacity of the biosphere to provide and renew natural resources and services is calculated (Global Footprint Network, 2019). The EF per capita was chosen by the Slovenian Development Strategy 2030 (2017) as an indicator in evaluating the achievement of the goal of sustainable management of natural resources. The goal set by the strategy is to reduce the EF per capita in Slovenia from 4.7 gha per capita to 3.8 gha per capita from the base year 2013 to 2030. According to the latest calculations of the Global Footprint Network (2021), in 2017 the EF per capita in Slovenia amounted to 4.9 gha and thus exceeded the available biocapacity per capita in the country by 2.7 gha. In our analysis, we used the calculations of the ecological footprint and bio­capacity of Slovenian regions for 2016 from a study prepared by Lin et al. (2020) as a starting point for the formulation of regional development programs, for which the government stipulated that the ecological footprint be used as the leading indicator in the environmental field (Cilji, usmeritve in instrumenti…, 2019). The third selected indicator is the DRI, whose calculation is described in the Pro­motion of Balanced Regional Development Act (Promotion of Balanced Regional..., 2011) and the accompanying guidelines for each programming period (Pravilnik o razvrstitvi…, 2021). Based on these documents, the DRI includes 14 indicators: GDP per capita, gross value added per employee, gross fixed capital formation as a per­centage of GDP, registered youth unemployment rate (15–29 years), employment rate (20–64 years), share of college degree holders (25–64 years), gross domestic expendi­ture on research and development as a percentage of GDP, share of treated wastewater with secondary and tertiary treatment, share of protected areas, estimated damage due to natural disasters as a percentage of GDP, registered unemployment rate, popu­lation aging index, disposable income per capita and population density. The latest calculations of the DRI are available for 2019 (Pecar, 2020a) and based on these a classification of regions according to the level of development for the programming period 2021–2027 was performed. Even before the introduction of the DRI for the purpose of monitoring the results of regional policies in Slovenia, the ISRD had been developed and calculated for several consecutive periods from the second half of the 1990s on in order to assess Slovenian regions’ success or lack thereof in approaching the goals of sustainable development (Vintar, 2003; Vintar Mally, 2009; 2018; 2021). The ISRD has also undergone some methodological changes due to (in)availability of data or changes in the collection of data used. For the period 2015–2019, the ISRD was calculated on the basis of the fol­lowing 32 indicators (Vintar Mally, 2021): • economic indicators: GDP per capita, gross value added per capita, expenditure on fixed assets per capita, average R&D expenditure as a share of GDP, dispos­able income per capita, share of service sector employees; • social indicators: unemployed with uncompleted or completed primary school, share of unemployed women, population density, population growth index, population aging index, average age at death, at-risk-of-poverty or social exclu­sion rate, usable floor area, registered unemployment rate, number of students per thousand inhabitants, share of households with PC users, share of college degree holders; • environmental indicators: share of organically farmed land, wooded areas per capita, road freight transport growth index, intensively farmed land per capi­ta, share of households in polluted environment, municipal waste per capita, share of Natura 2000 sites, water consumption per capita, average expenditure on environmental protection as a share of GDP, share of built-up areas, share of treated wastewater, share of housing with district heating in place, motorization rate, livestock density index. Worth noting is that the DRI and ISRD include six identical socioconomic indi­cators (i.e. GDP per capita, share of college degree holders (25–64 years), registered unemployment rate, population aging index, disposable income per capita and popu­lation density); however, completely different methods are used in formulating the composite indicator. For the ISRD the calculation of the standard deviation for each individual indicator is used, which forms the basis for classifying regions into four classes according to the distance of the value from the regional average and the de­sired direction of the indicator from the point of view of sustainable development. The score (++, +, - or - -) assigned to the region for each indicator is the starting point for calculating the average score of the region in each of the three development areas – economic, social and environmental – and the average of all three areas, which is the ISRD value (Vintar Mally, 2021). In the case of the DRI, standardized values are calculated for each indicator on a scale from 0 to 1, based on the application of the minimum and maximum values that occur in the regions for particular indicators. Whereas in the DRI each of the fourteen indicators has the same weight or influence on the final result (Pecar, 2018), in the ISRD only the indicators within a particular individual area (economic, social and environmental) have the same weight, and each of the three areas has the same influence on the final value of the ISRD for the region. It can be concluded that environmental indicators in the ISRD have one-third of the influence on the final value of the composite indicator, while in the DRI they have at most a one-fifth impact (i.e. three indicators out of fourteen, if we count alongside the indicators on the share of treated wastewater and the share of protected areas also damage due to natural disasters). 3 RESULTS AND DISCUSSION From the standpoint of more balanced and sustainable development, it is desirable to increase material prosperity and growth in gross domestic product. In 2019, the lowest GDP per capita was in the Zasavska region (EUR 12,287 per capita) and the highest in the Osrednjeslovenska region (EUR 32,620 per capita), with the ratio between the two regions being 1:2.7. This indicates that there are still large differences between regions, and moreover these increased in the period 2010–2019 (in 2010 the ratio was 1:2.4) (SURS, 2021). The three economically weakest regions were the Zasavska, Pomur­ska and Primorsko-notranjska regions, while among the strongest were, in addition to the Osrednjeslovenska region, the Jugovzhodna Slovenija and Obalno-kraška re­gions (Table 1). Thus all statistical regions that make up the cohesion region Zahodna Slovenija (i.e. the Osrednjeslovenska, Obalno-kraška, Gorenjska and Goriška regions) at the NUTS-2 level, as well as the Jugovzhodna Slovenija and Savinjska regions from the cohesion region Vzhodna Slovenia, ranked in the top half of the scale (Figure 1). Similar results are shown by the DRI calculations, according to which the rankings in nine regions completely overlap with or differ by no more than one place from the rankings for GDP per capita, while the Podravska region ranked two places higher in GDP per capita, and the Zasavska and Gorenjska regions three places lower. Based on the calculations of the DRI for 2019, the Osrednjeslovenska region proved to be the most developed and least at risk (index 49.6), while the Pomurska region (172.5), Primorsko-notranjska region (138.3) and Podravska region (133.4) proved to be the least developed. A comparison of the results of the DRI for 2014 and 2019 showed that in most regions the indicators included in the DRI have improved, but the lagging of regions behind Osrednjeslovenska has increased and thus also the difference between the best and worst ranked regions (Pecar, 2020a). The GDP and DRI calculations thus show the progress of the regions, but also an increase in interregional disparities. Table 1: Comparison of the results of Slovenian statistical regions based on selected development indicators. GDP per capita (€), 2019 Ecological footprint per capita (gha), 2016 Biocapacity per capita (gha), 2016 Develo­pment risk index, 2019 Indicator of sustainable regional de­velopment, 2015–2019 Osrednjeslovenska 32,620 5.28 1.11 49.6 0.73 Jugovzhodna Slovenija 23,096 5.27 5.38 93.0 0.48 Gorenjska 20,790 5.29 2.69 85.3 0.48 Goriška 20,707 5.29 5.30 117.1 0.44 Obalno-kraška 22,894 5.26 2.54 103.2 0.18 Primorsko-notranjska 16,154 5.25 8.02 138.3 0.17 Koroška 18,694 5.40 3.98 127.7 -0.09 Savinjska 20,954 5.19 2.15 109.3 -0.31 Posavska 19,456 5.19 3.03 121.8 -0.36 Zasavska 12,287 5.16 2.18 132.3 -0.45 Podravska 18,887 5.18 1.46 133.4 -0.59 Pomurska 15,705 5.15 2.46 172.5 -0.82 Slovenija 23,165 5.24 2.50 / / Sources: Lin et al., 2020; Pecar, 2020a; SURS, 2021; Vintar Mally, 2021. Note: The most favorable values of indicators are written in bold. In contrast to the results of the primarily socioeconomic indicators presented above, the regions are ranked completely differently based on the EF per capita as compared to the synthetic indicator of environmental pressures. In this indicator, lower values are more favorable for sustainable development of Slovenian regions, so the regions with the lowest environmental pressures are ranked highest. In 2016, the Pomurska region had the lowest EF per capita at 5.15 gha per capita and the Koroška region the highest at 5.40 gha per capita, due to the higher than average footprint of transport and of households in this region (Lin et al., 2020). Slovenia exceeds the available global biocapacity per capita, which amounts to 1.6 gha, by several times as well as the biocapacity of its own territory. Unfavorable from the standpoint of devel­opment is the fact that the country’s ecological footprint has mainly increased since the early 1990s, with the exception of a major downturn following the global finan­cial and economic crisis more than a decade ago (Global Footprint Network, 2021). A comparison of biocapacity and EF per capita (Table 1) shows an ecological deficit for most regions, as the EF of the region’s population significantly exceeds the bio­capacity of its territory. The Osrednjeslovenska region (4.17 gha per capita) and the Podravska region (3.72 gha per capita) stand out the most in terms of the size of the ecological deficit. Only three regions with the highest biocapacity – the Primorsko-Notranjska, Jugovzhodna Slovenija and Goriška regions – show an excess of bioca­pacity over the ecological footprint, which is due mainly to the largest wooded areas in relation to the population. The ecological deficit shows that the development pat­tern in the country is highly unsustainable and that in most regions socioeconomic development is taking place at the expense of depletion of global or local environ­mental resources and environmental pollution. Depending on the way the ecological footprint is calculated, these effects are scattered across all areas from which the in­habitants of the regions are supplied with goods and services as well as sources of raw materials and energy. The differences in the level of EF per capita between regions are significantly smaller than the differences in gross domestic product, which leads to the conclusion that in economically more prosperous regions higher added value is created with comparatively lower pressures on the environment. The largest differ­ences in the rankings by GDP per capita and EF per capita are in the Pomurska and Zasavska regions, which have the lowest values for EF per capita and at the same time the lowest values for GDP per capita. On average, the rankings of the regions differ by five places, above average in the Osrednjeslovenska region (first in terms of GDP per capita and ninth highest EF per capita) and Jugovzhodna Slovenija (second in terms of GDP per capita and eighth highest EF per capita). The differences in the rankings of EF per capita and DRI are similarly large. Figure 1: Ranking of Slovenian statistical regions based on selected development indicators, 2015–2019. The ISRD gives equal weight to indicators from the economic, social and envi­ronmental fields in the calculation, so results different from the previous indicators are expected from the outset. The ranking of regions based on the ISRD is compara­tively closer to the ranking based on the level of the DRI than that based on a purely economic (GDP per capita) or environmental indicator (EF per capita). In addition to the choice of indicators included, the differences between the ISRD and the DRI are most influenced by the fact that social and economic indicators have less weight in the ISRD, equal to that of environmental indicators (i.e. each area has a one-third influence). The regions in the western part of the country are ranked highest accord­ing to the ISRD: the Osrednjeslovenska, Gorenjska, Jugovzhodna Slovenija, Goriška, Obalno-kraška and Primorsko-notranjska regions. The rankings of the DRI and the ISRD differed by a maximum of one place in eight regions, while the Goriška re­gion was ranked two places higher (in fourth place according to the ISRD) and the Posavska region two places lower (ninth place according to the ISRD). The Savinjska region stood out the most, ranking three places lower (eighth place) based on the ISRD compared to the DRI, and the Primorsko-notranjska region was as much as five places higher (sixth place) based on the ISRD compared to the DRI. Six indicators were taken into account for the calculation of the ISRD in the eco­nomic field, twelve in the social field and fourteen in the environmental field. A com­parison of the results of the regions by ISRD fields (Table 2) also shows a large differ­ence in the rankings of the regions in the social and economic fields as compared to their rankings in the environmental field (Figure 2). While the regions in the western part of the country, especially those from the cohesion region Zahodna Slovenija, rank at the top of the scale according to economic and social indicators, the results in environmental indicators deviate significantly from this pattern. The most strik­ing example is the Osrednjeslovenska region, which ranks first in the economic and second in the social field, yet ranked last in the environmental field. There is also a sig­nificant gap between the favorability of the socioeconomic fields and of the environ­mental field for long-term sustainable development in the Obalno-kraška and Gore­njska regions. Conversely, in the environmental field the top two places were held by the Zasavska and Koroška regions, which socioeconomically rank among the weaker. Although areas that were subjected to past environmental degradation are present in both regions, indicators of environmental pressures (e.g. agriculture, transport, built-up areas, water consumption and waste generation) and response indicators (e.g. or­ganic farming, district heating) show above-average favorable conditions and trends. Table 2: Average scores of Slovenian statistical regions in the main development areas and the indicator of sustainable regional development, 2015–2019. Economic indicators Social indicators Environ­mental indicators Indicator of sustainable regional development value ranking Osrednjeslovenska 1.83 1.00 -0.64 0.73 1 Jugovzhodna Slovenija 0.83 0.25 0.36 0.48 2–3 Gorenjska 0.33 1.25 -0.14 0.48 2–3 Goriška 0.33 0.92 0.07 0.44 4 Obalno-kraška 0.50 0.33 -0.29 0.18 5 Primorsko-notranjska -0.67 0.67 0.50 0.17 6 Koroška -0.67 -0.17 0.57 -0.09 7 Savinjska 0.00 -0.42 -0.50 -0.31 8 Posavska -0.67 -0.42 0.00 -0.36 9 Zasavska -1.17 -0.83 0.64 -0.45 10 Podravska -0.83 -0.50 -0.43 -0.59 11 Pomurska -1.17 -1.00 -0.29 -0.82 12 Source: Vintar Mally, 2021. A comparison of the ISRD calculations for the period 2015–2019 with previ­ous periods showed that the relative positions of the regions in the environmental field changed the most, while the differences in the social and economic fields are more fixed and the relationships less variable (Vintar Mally, 2018; 2021). In the pe­riod 2015–2019 it was also confirmed that the differences between the regions were the smallest in the environmental field, where the difference between the best rated Zasavska region and the worst rated Osrednjeslovenska region was 1.28. By compari­son, in the economic field the difference between the best and worst ranked regions was 3.0, and in the social field 2.25. From the standpoint of more balanced develop­ment of Slovenian regions, it is especially encouraging to note that the differences in the economic indicators of ISRD have shown a slight decrease, while in the social field they have remained unchanged. The order of the regions according to the value of the ISRD has changed very little over the last decade (Table 3), as only three regions have changed their place on the scale, with Jugovzhodna Slovenija and Gorenjska having recently overtaken the Goriška region, which used to be in second place. Figure 2: Rankings of Slovenian statistical regions in the main development areas and the indicator of sustainable regional development, 2015–2019. Table 3: Comparison of the indicator of sustainable regional development in the periods 2010–2014 and 2015–2019. 2010–2014 2015–2019 value ranking value ranking Osrednjeslovenska 0.85 1 0.73 1 Jugovzhodna Slovenija 0.44 3 0.48 2–3 Gorenjska 0.32 4 0.48 2–3 Goriška 0.45 2 0.44 4 Obalno-kraška 0.30 5 0.18 5 Primorsko-notranjska 0.27 6 0.17 6 Koroška -0.14 7 -0.09 7 Savinjska -0.17 8 -0.31 8 Posavska -0.54 9 -0.36 9 Zasavska -0.70 10 -0.45 10 Podravska -0.76 11 -0.59 11 Pomurska -0.77 12 -0.82 12 Sources: Vintar Mally, 2018; 2021. A closer examination of the results for all 32 indicators included in the calculation of the ISRD in the periods 2010–2014 and 2015–2019 provides an even better insight into the socioeconomic and environmental characteristics of regional development after 2010 and the favorability of these trends for the sustainable development of the country. In the socioeconomic fields, there was an improvement in most of the in­dicators analyzed, as the regions advanced towards the economic goals of sustain­able development, showing reduced unemployment (in general and among different groups of the population) and improved education of the population, with people liv­ing longer on average and having better housing conditions. Adverse socioeconomic trends worth noting are reductions in R&D expenditure on average, population aging, declining population growth in some regions and population densification in others. In contrast to socioeconomic indicators, a comparison of trends and current condi­tions with respect to environmental indicators has largely shown a move away from the goals of sustainable development. On average, more sustainable practices were found in the area of household heating through an expansion of district heating and in agriculture through an expansion of organic farming and reduced pressures on intensively cultivated agricultural land and from livestock farming. Trends of increas­ing water consumption and municipal waste, expansion of built-up areas, increasing road freight transport, increased rate of motorization and reduction of the share of investment in environmental protection are particularly unfavorable, while the scope of ecologically significant areas such as Natura 2000 and wooded areas per capita remains largely unchanged. It should be noted that this does not apply equally to all regions and some have nevertheless managed to achieve improvement even in areas where the average does not show this. Based on the examination of particular economic, social and environmental in­dicators of sustainable development, we were able to identify those areas where the relative lagging behind of the region is the largest and to which ones priority should be given in working towards the achievement of more coherent and sustainable devel­opment goals in particular regions (Table 4). Table 4: Areas in which particular Slovenian statistical regions show distinctly unfavorable conditions or trends from the standpoint of sustainable development. Statistical region Area Statistical region Area Pomurska • disposable income per capita, • population decline, • population aging*, • unemployment rate*, • higher education – number of students, population with tertiary education, • extent of intensively farmed land*, • expansion of organic farming, • share of households living in a polluted environment*, • housing with district heating in place. Podravska • disposable income per capita, • life expectancy – average age at death, • at-risk-of-poverty or social exclusion rate*, • extent of wooded areas, • share of built-up areas*. Zasavska • GDP per capita, • gross added value per capita, • expenditure on fixed assets, • population decline, • at-risk-of-poverty or social exclusion rate*, • usable floor area, • use of PCs in households, • share of households living in a polluted environment*, • share of Natura 2000 sites. Posavska • life expectancy – average age at death. Statistical region Area Statistical region Area Savinjska • usable floor area, • share of households living in a polluted environment*, • share of Natura 2000 sites, • share of treated wastewater. Koroška • employment in service sector, • unemployment of women*, • life expectancy – average age at death, • at-risk-of-poverty or social exclusion rate*, • livestock density*. Primor­sko-no­tranjska • road freight transport growth*, • housing with district heating in place, • motorization rate*. Obalno-kraška • higher education – number of students, • road freight transport growth*, • amounts of municipal waste*, • water consumption*. Goriška • water consumption*, • share of treated wastewater, • motorization rate*. Gorenjska • livestock density*. Jugov­zhodna Slovenija • employment in service sector, • unemployed with uncompleted or completed primary school*, • use of PCs in households. Osrednje-slovenska • growth in population density*, • extent of wooded areas, • share of built-up areas*, • share of treated wastewater. Note: For each region, only those areas are highlighted where the region’s score was more than one standard deviation worse than the regional average (i.e. the score - - in terms of favorability for sustainable development). *A higher value in this area means a shift away from sustainable development. 4 CONCLUSIONS Through an examination of selected indicators, we found that the progress of Slove­nian statistical regions after 2010 has been limited to particular socioeconomic and environmental areas or relationships. In general, we cannot confirm that the regions are moving towards the goals of sustainable and more balanced development, as the indicators examined do not show that economic, social and environmental develop­ment has been balanced over the last decade or that regional development disparities are diminishing. Although GDP per capita in the country and regions has increased, regional dis­parities have gradually increased somewhat. A similar finding emerges based on DRI calculations, whose indicators show improvement but also an increase in interregion­al disparities (Pecar, 2020a). In the environmental field, there has not been the desired reduction in environmental pressures, and the country as a whole as well as most regions show an ecological deficit, indicative of an unsustainable development pattern in which socioeconomic development takes place at the expense of environmental degradation. Regions from the western half of the country (especially from the cohe­sion region Zahodna Slovenija) have a higher ecological footprint and poorer results in the environmental field of sustainable development, though they are otherwise among the most successful in terms of social and economic indicators. An exception is the Primorsko-notranjska region, as it is more similar in development characteris­tics to regions from the eastern part of the country. The observed trends in the ISRD in particular show that economic disparities be­tween regions have narrowed slightly after 2010, but this cannot be confirmed for the social and environmental fields. The relative ranking of the regions changed particu­larly frequently with respect to environmental indicators. On the one hand, most of the social and economic indicators of the ISRD over the last decade indicate progress towards the goals of sustainable development (e.g. reduced unemployment, improved education, greater life expectancy, better housing, higher incomes, etc.), but on the other hand most of the environmental indicators still show a shift away from them, which is also in line with the findings regarding the ecological footprint and is associ­ated especially with an increase in the use of natural resources. When interpreting the results, it should be borne in mind that the indicators stud­ied cover only a limited number of characteristics of regional development and still have many methodological shortcomings. In order to monitor the efficiency of re­gional policy more concretely, it would be advisable to agree on targets for individual indicators and to create a comprehensive, uniform evaluation system. Individual re­gions face a variety of development challenges, therefore Slovenia’s regional policy in the future should make more targeted efforts to direct progress towards sustainable development in those areas where we are currently moving away from it, and pay spe­cial attention to areas in which particular regions most lag behind, otherwise it will be difficult to reduce regional development disparities and achieve an adequate level of prosperity within the carrying capacity of the environment. Acknowledgement The research for this paper was financially supported by the Slovenian Research Agency, a research program Sustainable regional development of Slovenia (P6-0229). References Agenda 21. Programme of action for sustainable development, Rio declaration on environment and development. The United Nations Conference on environment and development. 1992. Rio de Janeiro. Cilji, usmeritve in instrumenti regionalne politike ter strateška izhodišca prostorskega razvoja za pripravo regionalnih razvojnih programov 2021–2027. 2019. Ljubljana: Ministrstvo za gospodarski razvoj in tehnologijo. URL: https://www.gov.si/teme/spodbujanje-regionalnega-razvoja/ (accessed 20.11.2021). Cohesion policy 2021–2027. 2021. URL: https://ec.europa.eu/regional_policy/en/2021_2027/ (accessed 20.11.2021). Galli, A., Giampietro, M., Goldfinger, S., Lazarus, E., Lin, D., Saltelli, A., Wackernagel, M., Müller, F., 2016. Questioning the ecological footprint. Ecological Indicators, 69, pp. 224–232. 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Okoljevarstveni vidiki sonaravnega regionalnega razvoja Slovenije. Magistrsko delo. Ljubljana: Oddelek za geografijo Filozofske fakultete Univerze v Ljubljani. Vintar Mally, K., 2009. (Ne)sonaravnost razvoja slovenskih regij. V: Nared, J., Perko, D. (ur.). Razvojni izzivi Slovenije. Ljubljana: Geografski inštitut Antona Melika ZRC SAZU, pp. 263–270. Vintar Mally, K., 2018. Regional differences in Slovenia from the viewpoint of achiev­ing Europe’s sustainable development. Acta Geographica Slovenica, 58, 2, pp. 31–46. DOI: https://doi.org/10.3986/AGS.3309. Vintar Mally, K., 2021. Trends in regional development in Slovenia in the light of the goals of sustainable development. European Journal of Geography, 12, 2, pp. 36–51. DOI: https://doi.org/10.48088/ejg.k.mal.12.2.36.51. Ward, J. D., Sutton, P. C., Werner, A. D., Costanza, R., Mohr, S. H., Simmons, C. T., 2016. Is decoupling GDP growth from environmental impact possible? PLoS ONE: 11, 10. DOI: https://doi.org/10.1371/journal.pone.0164733. Wiedmann, T., Barrett, J., 2010. A review of the ecological footprint indicator – Perceptions and methods. Sustainability, 2, 6, pp. 1645–1693. DOI: https://doi.org/10.3390/su2061645. MORPHOMETRY AND DENSITY OF DOLINES ON SLOPES OF SLOVENIAN KARST Abstract Dolines are the most typical surface form of mid-latitude karst. Analyses of digital elevation model with GIS make it possible to study the doline density and their mor­phometric characteristics as a function of the slope on which they are located. Three areas with comparable relief, geological, climatic and hydrological conditions on the Hrušica, Snežnik and Slavnik hills were studied. The results show proportionality of density and most of the selected morphometric parameters with slope inclination. Keywords: geomorphology, GIS, remote sensing, digital elevation model, slope inc­lination, Slovenia 1 UVOD Vrtace so najbolj tipicna in pogosta površinska kraška reliefna oblika zmernih geo­grafskih širin (Ford, Williams, 2007; Sweeting, 1972; Waltham, Fookes, 2003). So kra­ške kotanje z bolj ali manj pravilnimi krožnimi obodi in konkavnimi profili pobocij ter razlicnih dimenzij, premer njihovih obodov pa je vecji od njihovih globin (Gams, 2004; Sauro, 2012). Vrtace najvecjo gostoto dosegajo na kompaktnih apnencih (Gams, 2000; Frelih, 2014). Nižje gostote vrtac so bile izmerjene na paleogenskih apnencih, najvišje pa na krednih apnencih (Mihevc, 2001; Radinja, 1969). Vrtace so oblikova­ne na površju z nakloni do 24° (Frelih, 2014) oziroma 30–33° (Gams, 2000; Kranjc, 1981), 90 % pa jih je na površju z nakloni do 20° (Mihevc, Mihevc, 2021). Lega vrtac na pobocju povzroca tudi asimetrijo, saj so podaljšane v smeri naklona. Višje ležeca pobocja vrtac so položnejša, saj zbirajo vec vode in je raztapljanje tako intenzivnejše kot na nižje ležecih pobocjih, ki so strmejša (Ford, Williams, 2007; Jennings, 1971). Praviloma naj bi bile starejše vrtace globlje (Habic, 1978). Kljub številnim raziskavam vrtac pa njihova gostota in morfometricne lastnosti v odvisnosti od razlicnih vrednosti naklona pobocja še niso bile sistematicno proucene. Na podlagi reliefnih, geoloških, hidroloških in podnebnih znacilnosti smo izbrali tri obmocja proucevanja na slovenskem krasu. Vrtace smo na izbranih obmocjih iden­tificirali z uporabo avtomatiziranega postopka daljinskega zaznavanja kraških kotanj na podlagi digitalnega modela višin (Digitalni model …, 2017; Grlj, 2014), vizualne interpretacije prostorskih podatkov ter terenskega pregleda. Iz pridobljenih podatkov smo nato izracunali gostoto in morfometricne lastnosti vrtac, ki smo jih v nadaljeva­nju med sabo primerjali glede na naklon površja. 2 TEORETSKA IZHODIŠCA Vrtace so majhne do srednje velike kraške kotanje in so tipicne ter najbolj pogoste re­liefne oblike krasa zmernih geografskih širin (Sweeting, 1972). Nastajajo na karbonat­nih kamninah ali na evaporitih, lahko pa tudi na silikatnih kamninah, kot je kvarcit (Waltham, Fookes, 2003). Njihov nastanek je posledica razlicnih procesov – raztaplja­nja, udorov, sufozije in pogrezanja, najpogosteje pa gre za kombinacijo teh procesov v odvisnosti od razlicnih litoloških in strukturnih dejavnikov v okolju (Ford, Williams, 2007; Mihevc, 2010; Sauro, 2012). Obodi vrtac so bolj ali manj okrogle oblike, profili pa so konkavni (Ford, Williams, 2007; Gams, 2004; Sauro, 2012). Vrtace v globino merijo od nekaj decimetrov do nekaj deset metrov, izjemoma tudi vec kot sto metrov, njihovi premeri pa so v razponu od nekaj do tisoc metrov (Ford, Williams, 2007; Swe­eting, 1972). Za vrtace je znacilno, da so premeri oboda vecji od globin (Gams, 2004). Pobocja vrtac so lahko položna, le blago nagnjena, ali pa strma, že skoraj stenasta, ter skalnata ali porašcena (Ford, Williams, 2007; Sauro, 2012). Vrtace, ki so oblikovane na pobocjih, so plitvejše pod nižje ležecim delom oboda. Višje ležeci deli njihovih po­bocij so bolj uravnani, saj naj bi zbirali vec vode in je raztapljanje tako bolj intenzivno kot na nižje ležecih pobocjih, ki so bolj strma (Ford, Williams, 2007; Jennings, 1971). Praviloma naj bi bile starejše vrtace globlje (Habic, 1978). Na oblikovanost in gostoto vrtac vplivajo razlicni dejavniki v prostoru, poleg nji­hovega nastanka ter litoloških, strukturnih, podnebnih in hidroloških znacilnosti ob­mocja tudi relief oziroma natancneje naklon površja (Bahun, 1969; Car, 1982; Car, Šebela, 1998; Ford in Williams, 2007; Gams, 2000; 2004; Verbovšek, 2020). Na krasu glede na dominanten tip preperevanja locimo dva tipa pobocij. Na ak­tivnih pobocjih prevladujejo mehansko preperevanje in aktivni pobocni procesi, ki mehanski sediment premešcajo vzporedno s pobocjem navzdol. Na uravnoteženih pobocjih prevladujeta kemicno preperevanje in odnašanje kamnine v raztopini v kra­ški vodonosnik (Stepišnik, 2010). Slednja so znacilna za kraško površje, saj se zara­di odsotnosti pobocnih procesov njihova oblika, ukrivljenost in naklon bistveno ne spreminjajo. Zato se geomorfne oblike na uravnoteženih pobocjih in geomorfne ob­like, ki imajo uravnotežena pobocja, kot so na primer vrtace, lahko ohranijo izjemno dolgo (Stepišnik, Kosec, 2011). Gams (2004) je tipiziral kraška obmocja glede na gostote vrtac v šest tipov: izjemno visoka gostota (nad 200 vrtac/km2), zelo velika gostota (120–200 vrtac/km2), veli­ka gostota (50–120 vrtac/km2), zmerna gostota (15–50 vrtac/km2), majhna gostota (5–15 vrtac/km2) in neznatna gostota (pod 5 vrtac/km2). Izjemna gostota vrtac je bila proucena na zgornjekrednih apnencih na Divaškem krasu, kjer je 240 vrtac/km2 (Mihevc, 2001), in na severovzhodnem obrobju Planinskega polja s 352,5 vrtacami/km2 (Šušteršic, 1987) ter na mezozojskih apnencih in dolomitih na Skalcen kamnu z 260,8 vrtacami/km2 (Šušteršic, 1994) in Logaškem ravniku z 243,3 vrtacami/km2 (Mihevc, Mihevc, 2021). Nakloni pobocij in gostota vrtac so obratno sorazmerni (Gams, 2004; Kranjc, 1981). Kranjc (1981) je na podlagi diagrama izracunal regresijsko premico in koefi­cient korelacije, ki z vrednostjo -0,7638 nakazuje na mocno soodvisnost in obratno sorazmernost med naklonom površja in gostoto vrtac na apnencu. Enako korelacijo med naklonom površja in gostoto ter površino vrtac sta pri proucevanju jugozahod­nega dela Krasa dokazala tudi Ravbar in Zorn (2003). Frelih (2014) je najvecjo gosto­to vrtac ugotovila na naklonih površja med 2 in 5°. Vrtace so na površjih z naklonom do 24° (Frelih, 2014) oziroma 30–33° (Gams, 2000; Kranjc, 1972), 90 % pa jih je na površju z nakloni do 20° (Mihevc, Mihevc, 2021). Frelih (2014) navaja tudi, da so najvecje gostote vrtac na obmocjih, kjer so vrtace manjše in plitvejše. Analize vrtac so postale aktualne z razvojem GIS in dostopnostjo natancnejših pro­storskih podatkov (Frelih, 2014). Najvec analiz je bilo opravljenih z uporabo GIS in topografskih kart razlicnih meril (1 : 5.000–1 : 25.000), vedno bolj pa se uveljavljajo tudi (pol)avtomatizirani postopki zaznavanja kotanj, ki temeljijo na interpretaciji di­gitalnega modela višin (DMV) in iz njega izpeljanih podatkov (sencen relief, nakloni, indeks topografske pozicije) (Fuyuan, Yunan, 2013; Miao in sod., 2013; Mihevc, 2014; Rahimi, Alexander, 2013; Verbovšek, 2020) ter na modelu hidrološko pravilnega re­liefa z zapolnjevanjem kotanj (Ceru in sod., 2017; Gostincar, 2013; Grlj, 2014; 2020; Obu, 2011; Padro-Igúzquiza in sod., 2013; Telbisz in sod., 2016; Vrbovšek, 2020). 3 PROUCEVANA OBMOCJA Površje izbranih obmocij je razgibano, z razlicnimi nakloni pobocij, ter mocno razclenje­no z vrtacami. Poleg naklona pobocij je bil glavni dejavnik izbora obmocij enotna lito­loška sestava. Vsa obmocja namrec gradijo zgornjekredni apnenci (Plenicar, 1970; Šikic, Plenicar, 1975). Obenem imajo izbrana obmocja zmerno celinsko podnebje zahodne in južne Slovenije (Ogrin, 1996) in so brez stalnih izvirov in površinskih vodotokov. Na visoki kraški planoti Hrušice, južno in vzhodno od Podkraja, je prvo prouce­vano obmocje. Obsega 7,76 km2 površja in se razteza med 598 in 1108 m n. m. Na podlagi informacij o jamah v neposredni bližini obmocja, kjer je najgloblje brezno Brezno na liniji (kat. št. 4969) globoko 35 m, ocenjujemo, da je vadozna cona na ob­mocju razvita vsaj do te globine (Kataster jam, 2021). Drugo obmocje je na kraški planoti Snežnik, severno in severovzhodno od Leskove doline, na nadmorskih višinah med 729 in 936 m ter meri 5,03 km2. Na podlagi infor­macij o jamah na obmocju, kjer je najgloblje brezno Leskovo brezno 7 (kat. št. 3681) globoko 51 m, ocenjujemo, da je vadozna cona na obmocju razvita vsaj do te globine (Kataster jam, 2021). Tretje proucevano obmocje je v Slavniškem pogorju, vzhodno od vrha Slavnik. Meri 3,23 km2 in se razteza med 533 in 713 m n. m. Na podlagi informacij o jamah na ob­mocju, kjer je najgloblja jama Sk 20 (Skadanšcina) (kat. št. 8068) globoka 27 m, ocenju­jemo, da je vadozna cona na obmocju razvita vsaj do te globine (Kataster jam, 2021). 4 MATERIALI IN METODE Izbor obmocij proucevanja je potekal s prekrivanjem slojev prostorskih podatkov – DMV, geoloških kart in podatkov o povprecnih letnih temperaturah ter kolicinah pa­davin (ARSO, 2014; 2019a; 2019b; Osnovna geološka karta SFRJ, L 33–77 ..., 1967; Osnovna geološka karta SFRJ, L 33-89 ..., 1972). V raziskavi smo v prvem koraku uporabili kombinacijo avtomatiziranih metod in zaznali vrtace. Pridobljene rezultate smo nato rocno popravili na podlagi plastnic, sencnega reliefa in podatkovnega sloja naklonov, izracunanih iz DMV (ARSO, 2014), ter rezultati terenskega kartiranja. V drugem koraku smo izracunali izbrane mor­fometricne lastnosti zaznanih vrtac ter proucili vrednosti naklonov. Za zaznavanje vrtac, izracun lastnosti in analizo rezultatov smo uporabili programa ESRI ArcMap 10.2.2 ter IDLE. Vecji del postopka zaznavanja vrtac je bil opravljen z uporabo skripte, napisane v programskem jeziku Python 2.7.2 (Grlj, 2014), ki je bila za namen te raz­iskave popravljena v razlicici 2.7.5. Koncna statisticna analiza številcnih podatkov je bila opravljena s programom Excel. 4.1 Zaznavanje kotanj Izbor vrtac je bil izveden z uporabo skripte za iskanje kraških kotanj z daljinskim zaznavanjem na podlagi rastra – vhodnega DMV (Grlj, 2014). Za analizo je bil upora­bljen DMV s prostorsko locljivostjo 1 m (ARSO, 2014). Prvi korak v postopku je zapolnjevanje kotanj, ki ga skripta opravi z orodjem Fill. To zapolni kotanje v reliefu do višine iztoka (Pour Point), parameter Z-limit pa dolo­ca, katere kotanje bodo zapolnjene (Fill, 2021). Skripta ponovi uporabo tega orodja z razlicnimi vrednostmi Z-limit in na ta nacin zazna tudi kompleksnejše kotanje, kot so tiste, ki imajo v svojem dnu še manjše kotanje (Grlj, 2014). Za analizo smo uporabili prednastavljene parametre: zacetni Z-limit (Z-limit prve ponovitve) 0,5, koncni Z-li­mit (Z-limit prve ponovitve) pa 10. Skripta postopek zapolnjevanja ponovi dvajsetkrat z intervalom 0,5 (Grlj, 2014). V drugem koraku skripta zaznane kotanje izdvoji. To izvede na nacin, da od vsa­kega DMV z zapolnjenimi kotanjami odšteje vhodni DMV. Celice izhodnega DMV bodo imele vrednost, drugacno od nic, le na tistih obmocjih, kjer so bile kotanje za­polnjene (Grlj, 2014). Dobljene rastrske sloje nato skripta z orodjem Reclassify reklasificira in jim pripiše vrednost 1 povsod, kjer je vrednost celice višja od nic. To omogoca sledeco upora­bo orodja Raster to Polygon za pretvorbo v vektorske podatke (Grlj, 2014). V tem koraku smo skripto prilagodili, da dobljene poligone poenostavi (Simplify Poligons), saj zadostna prostorska locljivost vhodnih podatkov (1 m) omogoca dovolj natancno poenostavitev. V zadnjem koraku skripta z orodjem Merge v obratnem vrstnem redu združi vseh 20 vektorskih podatkovnih slojev v enega tako, da vecji poligoni ne zakrijejo manjših, zaznanih pri nižjih vrednostih Z-limit. Na koncu skripta z uporabo orodja Delete Identical izbriše dvojnike poligonov tistih kotanj, ki so bile zaznane pri vec kot eni vrednosti Z-limit, in z ukazom deleteRow izbriše poligone z vrednostjo 0, ki so bili ustvarjeni pri vektorizaciji podatkov (Grlj, 2014). Slika 1: Pojmovni model zaznavanja kotanj (vir: Grlj, 2014). Opisana skripta dobro deluje na uravnanem reliefu in pri nizkih naklonih površja, tocnost zaznavanja kotanj na pobocjih pa je omejena, saj so kotanje zapolnjene le do višine iztoka. Zaznani obod kotanje ima torej naklon 0°, dejanski obod pa ima enak naklon kot površje okoli njega in poteka nad zaznanim obodom, zato je posledicno tudi drugacne oblike. Da bi odpravili to napako, smo poligone, identificirane z upo­rabo zgoraj opisane skripte, naknadno rocno popravili. To smo naredili z vizualno interpretacijo rezultatov na podlagi sencnega reliefa, podatkovnega sloja naklonov ter plastnic z ekvidistanco 1 m (ARSO, 2014), ter terenskim pregledom. Poleg tega so bili izbrisani tudi tisti poligoni, ki predstavljajo napake pri zaznavanju. Te so se pojavile zaradi previsoke natancnosti nadmorskih višin uporabljenih podatkov, na primeru vrtac na poseljenih obmocjih, kjer je površje antropogeno preoblikovano, ter pri ne­popolnih poligonih na robovih proucevanih obmocij. 4.2 Izracun in analiza lastnosti zaznanih vrtac Na podlagi rezultatov, ki smo jih pridobili z zaznavanjem vrtac, smo za vsako vrtaco v programu ArcMap izracunali šest morfometricnih lastnosti: tlorisna površina, obseg oboda, indeks krožnosti, dolžina krajše in daljše osi ter globina. Tlorisno površino in obseg oboda vrtac smo izracunali z uporabo orodja Calculate Geometry, ki za vsak poligon izracuna omenjeni lastnosti v izbrani merski enoti (Calculate geometry attri­butes, 2021). Iz podatkov o površini in obsegu smo izracunali indeks krožnosti – raz­merje med površino vrtace in površino kroga z enakim obsegom, ki nam pove, koliko se oblika oboda posamezne vrtace približa krogu (vrednost 1). Za izracun dolžine osi smo uporabili orodje Minimum Bounding Geometry, ki za vsak poligon v izbranem sloju ustvari nov pravokotnik glede na širino (RECTAN­GLE_BY_WIDTH). Dolžina njegove daljše stranice predstavlja najvecjo dolžino dalj­še osi, dolžina njegove krajše stranice pa najvecjo dolžino njegove krajše osi (Mini­mum bounding geometry, 2021). Globino vrtac smo izracunali s pomocjo tock z najnižjo in najvišjo nadmorsko višino na obmocju poligona, ki smo jih dolocili z dvakratno ponovitvijo enakega postopka. Najprej smo z orodjem Zonal Statistics z izbiro funkcije MAXIMUM oziroma MINI­MUM identificirali vrednost najvišje oziroma najnižje ležece celice na obmocju poligo­na vrtace. Rezultat postopka je raster, ki vsem celicam na obmocju posameznega poli­gona pripiše najvišjo oziroma najnižjo vrednost z istega obmocja. Iz posameznega rastra smo nato identificirali tisto celico na DMV, ki ima omenjeno vrednost nadmorske višine s pogojnim izrazom v orodju Raster Calculator. Celica na sloju, ki je rezultat izracuna funkcije MAXIMUM oziroma MINIMUM, katere vrednost je enaka istoležeci celici iz­virnega DMV, obdrži svojo vrednost, ostalim celicam pa izraz pripiše vrednost NoData. Oba rastrska sloja, ki sta rezultat tega izracuna in vsebujeta celice z vrednostmi najnižjih in najvišjih tock vseh vrtac, smo z orodjem Raster to Point pretvorili v tockovni vek­torski format, pri cemer je lastnost posamezne tocke njena nadmorska višina. Globino vrtac od najvišjih tock njihovih obodov do njihovih dnov smo izracunali z odštevanjem vrednosti najnižjih tock od vrednosti najvišjih tock (How to: Create points …, 2021). Zaradi velike razclenjenosti površja proucevanih obmocij smo z uporabo orodja Focal Statistics izvorni DMV z locljivostjo 1 m najprej »zgladili«. Za sosešcino smo izbrali krog s polmerom 50 m (50 celic), za tip statistike pa MEAN (How focal statistics work, 2021). S tem smo odpravili razclenjenost zaradi vrtac, ohranili pa splošno obliko površja. Iz teh podatkov izracunane naklone površja smo reklasificirali v sedem naklonskih razredov 0–1,9°; 2–5,9°; 6–11,9°; 12–19,9°; 20–31,9°; 32–54,9° in vec kot 55°. Predmet prouceva­nja so vrtace na pobocjih, zato naklonski razredi temeljijo na razredih analiz pobocnih procesov (Komac, 2006; Natek, 1983), ki vplivajo na morfogenezo pobocij in oblik na njih. Vrednosti posameznih naklonskih razredov smo pretvorili v vektorske podatke. Nadaljnje analize so bile opravljene znotraj posameznega naklonskega razreda. Ce je vrtaca hkrati na obmocju vec naklonskih razredov, je bila obravnavana v okviru tistega, kjer je središcna tocka poligona, izracunana z orodjem Feature to Point. Za gostoto vrtac in vsako od šestih morfometricnih lastnosti (tlorisna površina, obseg oboda, indeks krožnosti, dolžina krajše in daljše osi ter globina) smo izracunali tudi Spearmanov koeficient korelacije v primerjavi z naklonom pobocja. Za vrednosti morfometricnih lastnosti smo uporabili aritmeticne sredine te lastnosti za posamezni naklonski razred, za vrednosti naklona pa srednje vrednosti posameznega naklonske­ga razreda, v katerem so vrtace: 1°, 4°, 9°, 16° in 26°. Izracun je bil narejen z uporabo funkcije CORREL v programu Excel. 5 REZULTATI Slika 2: Karta naklonskih razredov in vrtac, obravnavanih v posameznem razredu, na obmocju Hrušice. Slika 3: Karta naklonskih razredov in vrtac, obravnavanih v posameznem razredu, na obmocju Snežnika. Slika 4: Karta naklonskih razredov in vrtac, obravnavanih v posameznem razredu, na obmocju Slavnika. Izracunane vrednosti morfometricnih lastnosti smo proucili za celotno množico pro­ucevanih vrtac ter glede na njihovo pripadnost naklonskim razredom ter prouceva­nim obmocjem. Na vseh treh proucevanih obmocjih smo zaznali 2805 vrtac, od tega 1363 na ob­mocju Hrušice, 780 na obmocju Snežnika in 680 na obmocju Slavnika. Na vseh treh proucevanih obmocjih se nakloni pobocij razvrstijo v prvih petih naklonskih razre­dih do 31,9°, na Hrušici pa manjši del proucevanega obmocja pripada tudi naklonske­mu razredu 32–54,9°. Najvecjo gostoto vrtac na vseh obmocjih skupaj smo izracunali v prvih dveh naklonskih razredih med 0 in 1,9° (323,3 vrtac/km2) in med 2 in 5,9° (268,2 vrtac/km2). Sledi naklonski razred med 6 in 11,9° (188,6 vrtac/km2), zatem pa gostota znatno pade in je 67,5 vrtac/km2 (12–19,9°). Na naklonih med 20 in 31,9° smo vrtace zaznali le na obmocju Hrušice, vendar je tudi tu njihova gostota izjemno nizka (15,2 vrtac/km2). Koeficient korelacije med naklonom pobocja in gostoto vrtac je –0,9755, torej sta spremenljivki obratno sorazmerni. Slika 5: Gostota vrtac na proucevanih obmocjih glede na naklonske razrede. Povprecna vrtaca ima površino 552,7 m2, je globoka 6,5 m z obsegom oboda 78,4 m, dolžino krajše osi 21,1 m, dolžino daljše osi 27,5 m in indeksom krožnosti 0,88. Na Hrušici imajo vrtace najvišje vrednosti morfometricnih lastnosti, na Snežniku sre­dnje, na Slavniku pa najmanjše vrednosti. Povprecni obod vrtac na Hrušici (0,90) se najbolj približa pravilni krožni obliki, sledijo vrtace na Snežniku (0,89), v povprecju najmanj pravilne krožne oblike pa so vrtace na Slavniku (0,84). Preglednica 1: Povprecne vrednosti morfometricnih lastnosti vrtac glede na proucevano obmocje. Hrušica Snežnik Slavnik skupaj N 1363 762 680 2805 površina [m2] 597,0 570,0 444,7 552,7 globina [m] 7,0 6,7 5,2 6,5 krajša os [m] 22,4 21,6 17,8 21,1 daljša os [m] 29,2 27,6 24,1 27,5 obseg [m] 82,8 80,5 67,4 78,4 indeks krožnosti [/] 0,90 0,89 0,84 0,88 Vrednosti štirih morfometricnih lastnosti vrtac, ki temeljijo na tlorisu vrtace (po­vršina, obseg ter dolžini krajše in daljše osi), se zmanjšujejo z narašcanjem naklona pobocja. Kljub temu pa razmerje med krajšimi in daljšimi osmi in posledicno indeks krožnosti ostajata približno enaka pri vseh naklonih pobocij (0,88–0,89). Globina analiziranih vrtac se povecuje s povecevanjem naklona pobocja, povezanost teh dveh spremenljivk pa je zelo mocna (0,9766). Preglednica 2: Povprecne vrednosti morfometricnih lastnosti vrtac glede na naklon površja. 0–1,9° 2–5,9° 6–11,9° 12–19,9° 20–31,9° N 193 1085 1244 274 9 površina [m2] 645,1 601,4 515,0 479,0 252,7 globina [m] 6,2 6,3 6,5 7,4 7,9 krajša os [m] 22,9 22,2 20,4 18,9 14,4 daljša os [m] 29,9 29,0 26,5 25,1 19,6 obseg [m] 85,9 81,9 75,9 72,0 55,6 indeks krožnosti [/] 0,89 0,88 0,88 0,88 0,89 6 DISKUSIJA Vrtace so kot najbolj tipicne in pogoste površinske kraške reliefne oblike zmernih geo­grafskih širin (Sweeting, 1972) predmet številnih raziskav. Namen raziskave je bil prou­citi gostoto vrtac ter njihove morfometricne lastnosti v odvisnosti od naklona pobocja. Gostota vrtac na proucevanih obmocjih te raziskave je glede na opredelitev Gamsa (2004) v povprecju vseh naklonskih razredov zelo visoka (175,1 vrtac/km2), na naklonih pobocij do 5,9° pa celo izjemna (323,3 oziroma 268,2 vrtac/km2). To potrjuje ugoto­vitve Kranjca (1981) na Ribniški Mali gori, Ravbar in Zorna (2003) na jugozahodnem delu Krasa ter Frelih (2014) na razlicnih vrstah krasa na obmocju Slovenije. Ti so naj­vecje gostote vrtac na svojih proucevanih obmocjih izmerili na površju z nakloni do 5°. Na naklonih med 6 in 11,9° je gostota še zelo visoka (188,6 vrtac/km2), zatem pa znatno pade. Izracunani koeficient korelacije med naklonom pobocja in gostoto vrtac (–0,9755) potrjuje obratno sorazmerje med tema dvema spremenljivkama in kaže na še mocnejšo povezanost, kot jo je izracunal Kranjc (1981) na Ribniški Mali gori (-0,7638). Vrtace na naklonih med 20 in 31,9° smo izmed proucevanih obmocij zaznali le na Hrušici, tudi tam pa je njihova gostota zelo nizka (15,18 vrtac/km2). To potrjuje na­vedbe Kranjca (1981) in Gamsa (2000), da so v Sloveniji vrtace na pobocjih z nakloni do 30 oziroma 33°. Po podrobnejšem pregledu smo ugotovili, da so vse vrtace na po­bocjih z nakloni do 24°, s cimer smo nadalje potrdili enake ugotovitve Frelih (2014). Vrtace so torej oblikovane na uravnoteženih pobocjih, kjer se izenacita mehansko in kemicno preperevanje ali pa celo prevlada kemicno preperevanje kamnine. To omo­goca, da se geomorfne oblike tam ohranijo dlje (Stepišnik, Kosec, 2011). S primerjavo vrednosti gostote ter površine in globine vrtac lahko potrdimo ugo­tovitve Frelih (2014), da so najvecje gostote vrtac tam, kjer so vrtace najmanjše in najplitvejše. Povprecna gostota vrtac na Slavniku je namrec 210,5 vrtac/km2, kar je najvec izmed vseh treh proucevanih obmocij. Kljub temu pa ne moremo trditi, da obstaja obratno sorazmerje med gostoto in dimenzijami vrtac, kot trdi Frelih (2014), saj imajo drugo najvecjo gostoto vrtace na Hrušici, ki pa so v povprecju najvecje. Proucena literatura (Ford, Williams, 2007; Jennings, 1971) navaja, da lega vrtac na pobocjih povzroca asimetricno obliko vrtac. Te naj bi bile podaljšane v smeri pobocja, s položnejšim višjim pobocjem. Na podlagi naših rezultatov lahko to trditev ovrže­mo. Poleg ugotovitve, da se krožnost tlorisa vrtace ne spreminja z naklonom pobocja, smo ob zaznavanju vrtac ugotovili, da je višje pobocje vrtace praviloma tudi bolj str­mo. Med raziskavo smo opazili tudi, da med analiziranimi vrtacami ni prevladujoce usmeritve daljše osi vrtac v smeri padanja pobocja. Iz tega sklepamo, da ima vecji vpliv na njihovo orientacijo od naklona površja geološka struktura, ki jo izpostavljajo Bahun (1969), Car (1982) in Frelih (2014). Prouceni podatki globine vrtac, ki se spreminja premo sorazmerno z naklonom pobocja, nakazujejo na morebitno bolj intenzivno poglabljanje na pobocjih z višjim naklonom ter na širjenje vrtac na bolj položnih pobocjih oziroma uravnavah. Tega vseeno ne moremo trditi z gotovostjo, saj pri naši raziskavi nismo upoštevali struktur­nih elementov maticne podlage, ki vplivajo na hitrost kemicnega in mehanskega pre­perevanja kamnine, ter debeline prepereline. Habic (1978) sicer navaja, da so starejše vrtace navadno globlje, vendar tudi te trditve na podlagi naše analize ne moremo niti potrditi niti ovreci, saj podatkov o starosti vrtac na tem obmocju nimamo. Rezultati raziskave dajejo splošno sliko o odvisnosti gostote in morfologije vrtac od naklona površja, za natancnejše rezultate pa bi bilo treba odpraviti nekatere pomanjkljivosti, ki smo jih zaznali. Zaradi odsotnosti popolnoma avtomatizirane me­tode zaznavanja vrtac, ki izloci clovekovo presojo kot subjektivni dejavnik zaznavanja, bi ob ponovitvi raziskave verjetno prišli do drugacnih absolutnih vrednosti posame­znih lastnosti. Opiranje na vec razlicnih podatkovnih slojev v kombinaciji s terenskim delom to možnost zmanjšuje, vendar je ne odstrani popolnoma. Poleg tega smo zara­di razlicne velikosti posameznih proucevanih obmocij na njih zaznali razlicno število vrtac. Glede na to, da se vrtace po povprecnih dimenzijah na posameznih obmocjih nekoliko razlikujejo, bi bilo smiselno z uporabo uteži izenaciti njihov vpliv na izracun skupnih povprecnih vrednosti parametrov glede na površino obmocja. Kljub temu menimo, da so relativne vrednosti in povezave med posameznimi spremenljivkami dovolj tocne za argumentacijo naših ugotovitev. Natancnejšo obliko vrtac v živoskalni podlagi bi lahko dolocali z analizo elektricne prevodnosti tal, s cimer bi zmanjšali vpliv prepereline na dojemanje oblike vrtac. S temi podatki ter podrobnejšo analizo strukturnih lastnosti obmocja in usmerjenosti daljše osi vrtace glede na smer padanja pobocij bi lahko nadalje raziskali odvisnost asimetrije vrtac od razlicnih dejavnikov. Zakljucimo lahko, da se gostota in morfometricne lastnosti vrtac spreminjajo v odvisnosti od naklona pobocja. Vrtace so oblikovane na uravnoteženih pobocjih, v primeru naše raziskave do naklona 24°, njihova gostota pa pada obratno sorazmerno z narašcanjem naklona površja. Povprecna površina, obseg ter dolžini osi se z naraš­canjem naklona zmanjšujejo, globina pa se povecuje. Indeks krožnosti ostaja približ­no enak, ne glede na naklon pobocja. Zaznali smo tudi, da usmeritev daljše osi vrtace ni odvisna od usmeritve pobocja, kar pomeni, da nanjo bolj verjetno vpliva struktura maticne podlage. 7 SKLEPI Vrtace, najbolj tipicne in pogoste reliefne oblike kraškega površja zmernih geograf­skih širin, so kotanje z bolj ali manj pravilnim krožnim obodom in konkavnim profi­lom ter razlicnih dimenzij, znacilno pa je, da je premer njihovega oboda vecji od nji­hove globine (Gams, 2004; Sauro, 2012). V preteklih raziskavah je bilo ugotovljeno, da se vrtace ne nahajajo na pobocjih z naklonom nad 24° (Frelih, 2014) oziroma 30–33° (Gams, 2000; Kranjc, 1981) njihova gostota pa je najvecja na pobocjih z nakloni do 5°. DMV je osnova za analize vrtac z GIS orodji, ki tudi z razlicnimi izpeljavami, na pri­mer plastnicami, sencnim reliefom in nakloni, omogoca natancno zaznavo vrtac, GIS pa nam omogoca hitro obdelavo vecje kolicine podatkov in izracun morfometricnih lastnosti vrtac (Frelih, 2014). Na obmocju slovenskega krasa smo na podlagi primerljivih relevantnih fizicnogeo­grafskih znacilnosti izbrali tri obmocja proucevanja. Glavna kriterija sta bila litološka sestava in naklon površja. Prvi dve obmocji sta na pobocjih visokih kraških planot Hrušice in Snežnika, tretje pa v Slavniškem pogorju. Izbrana obmocja sestavljajo zgornjekredni apnenci (Plenicar, 1970; Šikic, Plenicar, 1975) in imajo zmerno celin­sko podnebje zahodne in južne Slovenije (Ogrin, 1996). Za zaznavanje vrtac smo uporabili kombinacijo avtomatiziranega daljinskega za­znavanja in vizualne interpretacije podatkov, pri cemer so bili rezultati prvega, avto­matiziranega postopka uporabljeni kot osnova za vizualno interpretacijo. Avtomati­zirani postopek je del metode, ki jo je z namenom zaznavanja brezstropih jam razvil Grlj (2014). Obsega ponavljajoce zapolnjevanje kotanj na DMV do višine iztoka in odštevanje novonastalega DMV od izvirnega. Raster, ki je rezultat tega odštevanja, vsebuje le obmocja vrtac. Tako zaznamo kotanje na vec nivojih (Grlj, 2014). Doblje­ne vektorske rezultate smo nato rocno popravili z vizualno interpretacijo površja na podlagi sloja plastnic, naklonov površja in sencnega modela reliefa, izpeljanih iz iz­virnega DMV, ter terenskega pregleda. Vsem tako zaznanim vrtacam smo nato izra­cunali vrednosti površine, globine, obsega, dolžine krajše in daljše osi ter indeks kro­žnosti. Za nekoliko generalizirano obliko površja smo izracunali vrednosti naklonov pobocij, ki smo jih razdelili v 7 razredov: 0–1,9°; 2–5,9°; 6–11,9°; 12–19,9°; 20–31,9°; 32–54,9° in vec kot 55°, vrtace pa smo sicer zaznali le na obmocju prvih petih. Z upo­rabo opisne statistike smo analizirali gostoto in morfometrijo vrtac znotraj vsakega od naklonskih razredov. V raziskavi smo analizirali morfometricne lastnosti 2805 vrtac. Skupna povprecna gostota vrtac je 175,1 vrtac/km2. Najvišja povprecna gostota vrtac je bila izmerjena na obmocjih z naklonom med 0 in 1,9° (323,3 vrtac/km2), najnižja pa na obmocjih z naklo­ni površja med 20 in 31,9° (12,58 vrtac/km2). Izjemno visoko gostoto vrtac smo izmerili tudi na obmocjih z nakloni med 2 in 5,9°. Koeficient korelacije med naklonom pobocja in gostoto vrtac je –0,9755 in nakazuje obratno sorazmerje med tema spremenljivkama. Za analizo morfometricnih lastnosti vrtac smo izbrali površino, globino, dolžino osi, indeks krožnosti in obseg oboda. Povprecna vrtaca ima površino 552,7 m2, je globoka 6,5 m z obsegom oboda 78,4 m, dolžino krajše osi 21,1 m, dolžino daljše osi 27,5 m in indeksom krožnosti 0,88. Površina, obseg ter dolžini krajše in daljše osi vrtace so zelo mocno obratno sorazmerni z naklonom pobocja, indeks krožnosti pa ne glede na na­klon ostaja približno enak (0,88–0,89). Globina analiziranih vrtac se spreminja premo sorazmerno z naklonom pobocja (koeficient korelacije 0,9766). Ugotavljamo, da se gostota in morfometricne lastnosti vrtac spreminjajo v odvi­snosti od naklona pobocja, na katerem se te vrtace nahajajo. Najvišje gostote vrtac so na pobocjih z nakloni do 5°. Vrtace so oblikovane na uravnoteženih pobocjih do naklona 24°, njihova gostota pa pada obratno sorazmerno z narašcanjem naklona površja. Povprecna površina, obseg ter dolžini osi se z narašcanjem naklona zmanjšu­jejo. Nasprotno se globina vrtac z vecanjem naklona povecuje. Indeks krožnosti ostaja približno enak, ne glede na naklon pobocja. Opazili smo tudi, da je višje pobocje vrta­ce praviloma bolj strmo in da usmeritev daljše osi vrtace ni odvisna od usmeritve po­bocja. Iz slednjega sklepamo, da nanjo bolj verjetno vpliva struktura maticne podlage. Literatura in viri ARSO [Agencija Republike Slovenije za okolje], 2014. Lidar. URL: http://gis.arso.gov.si/evode/profile.aspx?id=atlas_voda_Lidar@Arso (citirano 5. 4. 2019). ARSO, 2019a. Povprecna letna temperatura zraka 1971–2000. URL: http://gis.arso.gov.si/wfs_web/faces/WFSLayersList.jspx (citirano 21. 4. 2019). ARSO, 2019b. Povprecna letna višina korigiranih padavin 1971–2000. URL: http://gis.arso.gov.si/wfs_web/faces/WFSLayersList.jspx (citirano 21. 4. 2019). Bahun, S., 1969. On the formation of dolines. Geološki vjesnik, 22, str. 25–32. Calculate geometry attributes. ESRI. URL: https://pro.arcgis.com/en/pro-app/toolre­ference/data-management/calculate-geometry-attributes.htm (citirano 18. 9. 2021). Car, J., 1982. Geološka zgradba požiralnega obrobja Planinskega polja. 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Automatic detection and delinea­tion of karst terrain depressions and its application in geomorphological mapping and morphometric analysis. Acta Carsologica, 42, 1, str. 17–24. DOI: 10.3986/ac.v42i1.637. Plenicar, M., 1970. Tolmac za list Postojna. Beograd, Zvezni geološki zavod, 62 str. Radinja, D., 1969. Doberdobski kras. Morfogenetska problematika robne kraške pok­rajine. Geografski zbornik, 11, str. 225–278. Rahimi, M., Alexander, E. C., 2013. Locating sinkholes in lidar coverage of a glaci­ofluvial karst, Winona county, MN. V: Land, L., Doctor, H. D., Staphenson, J. B. (ur.). Sinkholes and the engineering and anvironmental impacts of karst. Carlsbad: National Cave and Karst Research Institute, str. 469–480. Ravbar, N., Zorn, M., 2003. Some characteristics of dolines on the Kras plateau in southwestern Slovenia. Geomorphologia Slovaca, 3, 2, str. 64–72. Sauro, U., 2012. Closed depressions in karst areas. V: White, W. B., Culved, D. C. (ur.). Encyclopedia of caves. 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DOI: 10.3986/ac.v45i1.4138. Verbovšek, T., 2020. Prostorska statistika globin vrtac na Matarskem podolju z meto­do Getis-Ord. V: Ciglic, R. in sod. (ur.). Modeliranje pokrajine. Ljubljana: Založba ZRC SAZU, str. 9–18. DOI: 10.3986/9789610504696. Waltham, A. C., Fookes, P. G., 2003. Engineering classification of karst ground conditi­ons. Quarterly Journal of Engineering Geology and Hydrogeology, 36, str. 101–118. MORPHOMETRY AND DENSITY OF DOLINES ON SLOPES OF SLOVENIAN KARST Summary A doline, the most typical and common surface form on mid-latitude karst, is a de­pression with a more or less regular circular perimeter and a concave profile that can have different dimensions, but typically the diameter of its perimeter is larger than its depth (Gams, 2004; Sauro, 2012). In addition to the genetic process, the shape and fre­quency of dolines are also influenced by various spatial factors – geological, climatic, and hydrological characteristics of the area, as well as relief, more specifically the slope of the surface on which they occur (Car, Šebela, 1998; Ford, Williams, 2007; Gams, 2000; 2004). Previous studies have shown that dolines do not occur on slopes with in­clinations greater than 24° (Frelih, 2014) or 30–33° (Gams, 2000; Kranjc, 1981). 90% of all dolines occur on slopes with the inclination up to 20° (Mihevc, Mihevc, 2021) and that they occur most densely on slopes with inclinations up to 5° (Frelih, 2014). The digital elevation model (DEM) provides the basis for doline analysis using GIS and enables accurate detection of dolines using various derivatives (e.g., contours, shaded relief, slope) as well as rapid processing of large amounts of data and calcula­tion of morphometric parameters. The accuracy of the detection depends mainly on the accuracy of the data, especially on the spatial resolution. Lidar data can be used to create DEM with spatial resolution of 1 metre, which was also done for the purpose of this research. Three areas in the Slovenian karst with comparable physical-geographical char­acteristics were selected for this study, the main criteria being lithology and surface slope inclination. The first two areas are located on the high karst plateaus of Hrušica and Snežnik, while the third is located on the Slavnik hill range. The areas lie between 533 and 1108 m above sea level and have a cumulative area of 16.02 km2. They consist of early Cretaceous limestones (Osnovna geološka karta SFRJ, L 33–77..., 1967; Os­novna geološka karta SFRJ, L 33-89..., 1972; Plenicar, 1970; Šikic, Plenicar, 1975) and have a temperate continental climate in western and southern Slovenia (Ogrin, 1996). A combination of automated detection and visual interpretation of the data was used to identify dolines on these plots, using the results of the first, automated process as the basis for the visual interpretation. The automated process is a part of a method, developed by Grlj (2014). It consists of the repetitive process of filling sinks on DEM up to the pour point and subtracting the new DEM from the original. The result con­tains only the areas of dolines. This method can be used to detected the depressions on many levels (Grlj, 2014). The results in vector format were then manually cor­rected with the visual interpretation of the surface, using contour, slope and shaded relief data derived from the original DEM, as well as the data obtained through a field survey. The area, depth, perimeter, shorter and longer axis length, and circularity index were calculated for all the identified dolines. The surface slope inclination was calculated using a slightly generalized surface model, and the values were divided into 7 classes: 0–1.9°; 2–5.9°; 6–11.9°; 12–19.9°; 20–31.9°; 32–54.9°; and more than 55°, with dolines occurring only in the first five. Descriptive statistics were used to analyse the occurrence and morphometry was analysed within each of the classes. A total of 2805 dolines were analysed in this study. The collective average density is 175.1 dolines/km2. The highest density was found in areas with slopes between 0 and 1.9° (323.3 dolines/km2) and the lowest in areas with slopes between 20 and 31.9° (12.6 dolines/km2). Exceptionally high densities were also documented in areas with slope between 2 and 5.9°, confirming the results of Kranjec (1981), Ravbar and Zorn (2003) and Frelih (2014), who found that doline density was the highest at slopes up to 5°. The correlation coefficient between slope inclination and doline density is –0.9755, which confirms the inverse proportionality between these two variables. Moreover, we found that dolines are not present on slopes with the inclination greater than 24°, which confirms that dolines occur on balanced slopes, where mechanical and chemical erosion balance each other or chemical erosion predominates, which enables the preservation of geomorphic forms (Frelih, 2014; Stepišnik, Kosec, 2011). The parameters chosen for morphometric analysis were the area, depth, axial length, circularity index and perimeter. The average doline has an area of 552.7 m2, is 6.5 m deep, its perimeter is 78.4 m, the length of the shorter axis is 21.1 m, the length of the longer axis is 27.5 m, and the circularity index is 0.88. On average, dolines on Hrušica are the largest, followed by dolines on Snežnik, and dolines on Slavnik are the smallest. We confirmed the finding of Frelih (2014) that doline density is the highest where dolines are the smallest. However, according to our research, the proportional­ity between density and doline dimensions is not inverse, as doline density is higher on Snežnik than on Hrušica. The area, perimeter and axis lengths of the dolines are very much inversely proportional to the slope gradient, which does not affect the relationship between the axes and thus the circularity index, which is 0.88–0.89 on average. We also found that the higher slope of the doline is usually steeper and that there is no dominant orientation of the longer axis with respect to the direction of the slope. Therefore, we can refute the claim that dolines on slopes are asymmetric due to the slope itself and that they are elongated in the direction of the slope as well as that their higher slope is supposedly less steep than their lower slope (Ford, Williams, 2007; Jennings, 1971). We assume that geological structure has a greater influence on the orientation of the longer axis than the direction of the slope (Bahun, 1969; Car, 1982; Frelih, 2014; Verbovšek, 2020). The depth of the studied slopes changes directly proportional to the slope inclination (correlation coefficient 0.9766), which could mean that deepening is more intense on slopes with higher inclination and widening on slopes with lower inclination. Nevertheless, we cannot assert this with certainty because the research did not analyse the shape of dolines in bedrock and did not include the analysis of geological structures. We also cannot refute Habic’s (1981) claim that older dolines are usually deeper, as we have no information on the age of the studied dolines. As the most important result of the study, we can confirm that the density and morphological characteristics of dolines change depending on the slope of the area where they occur. They occur on balanced slopes, in the case of this study up to gradient slope of 24°. Their density decreases inversely proportional to the in­crease in slope. The average area, perimeter and axis lengths decrease with increasing slope, while on the other hand their depth increases. The circularity index remains approximately the same regardless of the slope. We also found that the orientation of the longer axes does not depend on the direction of the slope, which means that it is more influenced by the geological structure. (Translated by the author) ORGANIZATIONAL EFFECTS OF SOCIAL CAPITAL IN THE OPERATION OF ORGANIZATIONS IN THE LITIJA ADMINISTRATIVE UNIT Abstract In this paper, we examine and evaluate the organizational effects of social capital in the Litija Administrative Unit. Social capital is a multifaceted and difficult to measure concept, so it is treated with a combination of step-by-step methods of the SCAT tool and used to evaluate the organizational effects of social capital (social capital of organizations, social network of organizations and spatial impact). As part of the research, a survey of societies, interviews with representatives of node organizations, and a focus group method were conducted. Through the analysis of the focus group research results, we evaluated the selected methods as appropriate for assessing the organizational effects of social capital. Based on the research, we find that social capi­tal is developed in the community and that there are possibilities for improving the structural dimension (networking, creating a bridging organization). Keywords: social capital, organizational effects, SCAT tool, societies, Litija Admini­trative Unit 1 UVOD Socialni kapital je eden izmed težje merljivih dejavnikov, ki pomembno vplivajo na ra­zvoj družbe in prostora. Pomembnost medsebojnih povezav med ljudmi, ki delujejo kot gradniki širše družbene strukture, so v okviru teorije socialnega kapitala v 80. letih 20. stoletja utemeljili Bourdieu (1986), Coleman (1988) in Putnam (1993). Teorija so­cialnega kapitala je postala scasoma vse prepoznavnejša, saj pojasnjuje vpliv odnosov med ljudmi na širšo družbeno strukturo (gospodarstvo, turizem, kakovost bivanja ...). Socialni kapital predstavlja vezivo, ki povezuje skupnost v samih osnovah družbene­ga življenja, kar pomeni podporo drug drugemu, zaupanje in solidarnost, kot rezultat takšnega družbenega delovanja pa lahko pricakujemo družbeni razvoj (Franklin, 2004). Ta pojasnjevalni vidik teorije socialnega kapitala pritegne k raziskovanju tudi geograf­sko stroko, saj predstavlja enega izmed dejavnikov pri preucevanju neskladnega razvoja regij. Svendsen in Bjřrnskov (2007) z meritvami socialnega kapitala dokažeta njegovo raznoliko stopnjo med 25 evropskimi državami. Stopnja socialnega kapitala je namrec pogojena z enakostjo med prebivalci, ki pogojuje ugodno socialno-ekonomsko stanje v državi (Svendsen, Bjřrnskov, 2007). Socialni kapital ima zato veliko pojasnjevalno moc pri preucevanju regionalnih razvojnih razlik, primerjanju uspešnosti politik in ostalih neenakosti družbenega življenja (Mohan, Mohan, 2002). V prispevku obravnavamo organizacijske ucinke socialnega kapitala pri delovanju organizacij v Upravni enoti (v nadaljevanju UE) Litija. Mednje sodijo socialni kapital organizacij, socialna mreža organizacij in ucinki v prostoru. Dinamika povezovanja in sodelovanja je namrec prepoznana kot izjemno pomembna pri tvorjenju pobud »od spodaj navzgor« znotraj razlicnih projektov in programov. Uspešnost crpanja razvojnih in financnih sredstev in uspešnost nadaljnjega razvoja sta torej pogojeni z visokim socialnim kapitalom v skupnosti. To pomeni, da lahko stopnja razvitosti socialnega kapitala pravzaprav vpliva na nastanek civilnih pobud, projektnega sode­lovanja in posledicno število razvojnih projektov. Nekatere programske sheme Evrop­ske unije, podrobneje izpostavljamo program LEADER, predvidevajo oblike združe­vanja, za katere je potreben visok socialni kapital. Za izvajanje programa se morajo vzpostaviti partnerstva, ki so posledica povezovanja in izkoristka potenciala mreže akterjev, ki so med seboj usklajeni glede skupne vizije bodocega razvoja. V povezani skupnosti dobro delujejo razlicne organizacije, predvsem društva, kjer se združujejo posamezniki s podobnimi interesi in so odgovorna za razvoj socialnega kapitala, zato jih v nadaljevanju obravnavamo kot izhodišce preucevanja (Potocnik Slavic, 2009). Z razvojem digitalne tehnologije se vse vec medsebojnih interakcij pojavlja tudi v virtu­alnem prostoru. Zanima nas, kako na preucevane organizacije vpliva socialni kapital, generiran v virtualnem prostoru. Socialni kapital je v slovenskem prostoru najbolj preucevan s strani sociologov (Iglic, 1988; Križan, 2012; Lenarcic, 2010), pojavljajo se tudi geografske raziskave. Z meritvami zalog socialnega kapitala se v svojih raziskavah ukvarjata Potocnik Slavic (2009) in Podmenik (2012), Logar (2015) utemelji gradnike socialnega kapitala, Cer­nic Istenic in Mavri (2014) pa preucita pomembnost socialnega kapitala v povezavi s podeželskim turizmom. V prispevku analiziramo znacilnosti organizacij v UE Litija, njihovo vozlišcnost in prispevek v prid akumulaciji socialnega kapitala. 2 METODE Za celostno obravnavo organizacijskih ucinkov socialnega kapitala je treba metodo­loško zajeti vse njegove elemente, ki so: socialna omrežja, norme, zaupanje (Putnam, 1995), reciprocnost (Lenarcic, 2010), skupna identiteta, kultura, vizija, vrednote in jezik (Claridge, 2018). Po naštetih gradnikih dosedanje raziskave (Fukuyama, 2000; Kühn, Koch, 2012; Larsen, Ellersgaard, 2017; Nardone in sod., 2010; Teilmann, 2012 idr.) raz­licno vrednotijo socialni kapital, zato v prispevku celostno obravnavamo vse elemen­te s pomocjo orodja za vrednotenje socialnega kapitala (v nadaljevanju orodje SCAT, angl. Social Capital Assesment Tool). Orodje je predlog s strani Svetovne banke, avtorjev Krishne in Shraderja (1999) in metodološko uokvirja pristop preucevanja socialnega kapitala s predlaganimi metodami v posameznih korakih. Njegov glaven namen je po­enoteno preucevanje, zato je z manjšimi prilagoditvami široko rabljen v raziskavah v razlicnih regijah sveta (npr. Agampodi in sod., 2019; Berwal, 2016; Muco, 2021). Slika 1: Koraki orodja SCAT. Vir podatkov: Krishna, Shrader, 1999. Slika 1 prikazuje korake orodja SCAT, po katerih smo izvedli analize. Orodje pred­postavlja preucevanje socialnega kapitala na treh ravneh: na ravni skupnosti, gospo­dinjstev in organizacij. Ker se v prispevku osredotocamo predvsem na organizacije, smo postopek prilagodili. Za našo raziskavo vprašalnik za gospodinjstva ni relevan­ten, saj meri individualno raven socialnega kapitala v gospodinjstvih in njihov dostop do socialnega kapitala. Ker se v prispevku ne osredotocamo na individualni aspekt socialnega kapitala, smo ta del izpustili. Pri analizi skupnosti smo, poleg pilotnih intervjujev zaradi vecje objektivnosti rezultatov, dodatno izvedli kvantitativno mre­žno analizo, s katero smo prikazali socialno mrežo organizacij v UE Litija. Orodje SCAT izhodišcno vkljucuje dve razsežnosti, tj. strukturne in kognitivne, ker pa smo želeli organizacijske ucinke socialnega kapitala preuciti kar se da celostno, smo vklju­cili še relacijsko razsežnost, ki vkljucuje razlicne vidike zaupanja, zato smo intervjuju v sklopu analize organiziranosti dodali dodatna vprašanja (stopnja zaupanja ostalim organizacijam, skupnosti, medsebojnega zaupanja in zaupanja lokalnim oblastem). Prvi korak je analiza preucevane skupnosti, kjer ugotovimo njene bistvene znacil­nosti. V sklopu analize smo opredelili raziskovano skupino in obmocje preucevanja. Upravna enota Litija je bila izbrana kot preucevano obmocje zato, ker se obmocje kaže kot homogena enota s skupno identiteto, velikost obmocja tudi ustreza mezo ravni preucevanja, kjer se najbolje kažejo znacilnosti socialnih skupin (organizacij). Razlicne organizacije, deležniki, akterji in posamezniki lahko tvorijo socialni kapital na mikro (lokalna skupnost), mezo (obcina) ali makro (država in mednarodno delo­vanje) ravni (Mavri, Cernic Istenic, 2014). V naslednjem koraku smo zbrali vse javno dostopne podatke o organizacijah na raziskovanem obmocju, ustvarili smo bazo dru­štev s kontaktnimi podatki, pridobili javno dostopne podatke o financiranju društev (obcinski in nacionalni javni razpisi, razpisi LAS), preverili smo clanstvo v LAS in število zaposlenih v društvih. Ostale podatke, ki niso javno dostopni, smo pridobili s spletnim anketnim vprašalnikom (N = 107) poslanim vsem predstavnikom društev na obmocju. Za anketiranje predstavnikov društev smo se odlocili predvsem zato, ker se društva že od Putnama (1993) dalje pojavljajo kot eden kljucnih indikatorjev za­log povezovalnega in premostitvenega socialnega kapitala. Tudi raziskava socialnega kapitala Potocnik Slavic (2009) na izbranih podeželskih obmocjih je pokazala, da so lokalna društva pomemben dejavnik lokalnega razvoja oz. merilo razvitosti socialne­ga kapitala, zato tovrstno obliko združenja tudi v prispevku vzamemo kot izhodišce za preucevanje. V nadaljevanju analize upoštevamo tudi druge oblike združevanj, tako formalne kot neformalne (javni zavodi, obcine, šole, zveze, krajevne skupnosti ...), saj na podlagi anketiranja društev gradimo socialno mrežo vseh organizacij po principu snežene kepe. Pojem organizacija uporabljamo kot nadpomenko vseh organizacijskih oblik v socialni mreži. Anketiranje je potekalo v spletnem okolju 1ka.si, kjer smo ob­javili strukturirani anketni vprašalnik. K izpolnjevanju so bili pozvani predsedniki društev in aktivni clani upravnega odbora. Anketni vprašalnik smo razdelili v tri dele: splošni podatki o društvu (število clanov, aktivnih clanov, cas opravljanja funkcije), delovanje društva (število letno organiziranih dogodkov in dogodkov v partnerstvu, povezovanje z organizacijami) in delovanje društva v virtualnem okolju (aktiven upo­rabniški profil, nacin komunikacije, virtualna podpora ostalim organizacijam). Preglednica 1: Število društev v uradnih evidencah, število aktivnih društev na podlagi prejetih odgovorov in število in odstotek društev, ki so se odzvala na anketo. Tip društva Število vseh društev (vir: MNZ, 2020) Število aktivnih društev (vir: anketiranje društev 2021) Število anketiranih društev (vir: anketiranje društev, 2021) Delež rešenih anket glede na število aktivnih društev [%] društva in pobude civilne družbe 2 2 1 50 društva za duhovno življenje 4 2 0 0 društva podeželskih žena in deklet 5 5 3 60 gasilska združenja 25 25 14 56 generacijska združenja 15 15 9 60 kulturna in umetniška društva 36 36 17 47,2 strokovna združenja 32 31 17 54,8 športna in rekreativna društva 63 61 35 57,4 turisticno-etnografska društva 11 10 5 50 zdravstveno-humanitarne organizacije 8 8 6 75 skupaj 201 195 107 Vir podatkov: Ministrstvo za notranje zadeve, 2020; Anketiranje društev v UE Litija, 2021. Glavne znacilnosti delovanja društev smo ugotavljali s statisticno analizo s pomoc­jo programa IBM SPSS. S korelacijsko analizo (Pearsonov in Spearmanov koeficient) smo preverili statisticno povezanost spremenljivk, torej povezanost znacilnosti dru­štev in njihovega delovanja, z multiplo regresijsko analizo pa smo preverili, katere spremenljivke najbolj vplivajo na število dogodkov, ki jih društvo izvede. pove, kolikokrat je bila ista organizacija navedena s strani ostalih. Pomembnejši vi­dik povezanosti so vhodne vezi, saj so tiste, ki nakazujejo pomembnost posameznega vozlišca v mreži. Mera središcnosti glede na dostopnost nam pove, kakšna je središc­nost opazovanih vozlišc glede na število vseh vezi, središcnost lastnega vektorja (angl. Eigenvector centraility) pa pove, koliko vplivnih povezav imajo opazovana vozlišca (Markovic, 2015). Višje vrednosti indeksa dosegajo tiste organizacije, ki so povezane z bolj središcnimi organizacijami. Drugi korak orodja SCAT je analiza organiziranosti. Na podlagi mer središcnosti smo dolocili vozlišcne organizacije, katerih predstavnike smo povabili na intervju (N = 13). Izvedli smo poglobljene polstrukturirane intervjuje, katere smo analizirali z metodo kodiranja v programu Atlas.ti. Polstrukturirani intervju je bil sestavljen iz vprašanj glede na teme pogovora: organizacijski ucinki socialnega kapitala (struktur­na, relacijska in kognitivna razsežnost), uporaba virtualnega socialnega kapitala in izkušnje s projekti LAS. Intervjuvane organizacije so navedene v preglednici 2. Preglednica 2: Organizacije v UE Litija, sodelujoce pri intervjuju. Zaporedna številka Naziv organizacije 1 Javni zavod za kulturo, mladino in šport Litija 2 Klub litijskih in šmarskih študentov 3 Društvo za razvoj podeželja Laz 4 Društvo za razvoj in varovanje Geossa 5 Društvo upokojencev Litija 6 Društvo Univerza za tretje življenjsko obdobje Litija in Šmartno 7 Društvo Lojtra 8 Medgeneracijsko glasbeno društvo Litija 9 Pevsko društvo Lipa Litija 10 Planinsko društvo Litija 12 Vinogradniško društvo Štuc Šmartno 13 Prostovoljno gasilsko društvo Liberga 14 Društvo podeželskih žena in deklet Polšnik V okviru analize organiziranosti je bila izvedena tudi fokusna skupina, na kateri so bili zbrani kljucni deležniki, ki jih tematika zadeva (N = 7). Na fokusno skupino so bili povabljeni deležniki, ki so kot vozlišcni izstopali v socialni mreži organizacij (najvišja stopnja središcnosti). Pet od sedmih sodelujocih je bilo že vkljucenih v predhodne faze (anketa, intervju), dodatno sta bili povabljeni še predstavnici Obcine Litija in LAS Srce Slovenije. Rezultate vseh izvedenih analiz smo ovrednotili na štiristopenjski lestvici. Stopnje smo po razsežnostih smiselno poimenovali, predvsem zaradi lažje povezave z od­govori intervjuvancev (npr. dobro, srednje, zadovoljivo, slabo). Rezultate, ki prika­zujejo stopnjo socialnega kapitala glede na organizacijske ucinke po treh razsežno­stih (strukturni, relacijski in kognitivni) smo prikazali v razpredelnici. Relacijsko in kognitivno razsežnost organizacijskih ucinkov socialnega kapitala smo vrednotili na podlagi analize intervjujev, medtem ko smo pri strukturni razsežnosti poleg odgo­vorov intervjuvancev upoštevali še rezultate mrežne analize in analize anketiranja. Stopnjo na lestvici od 1 do 4 smo pri posameznem kazalniku izracunali s povprecjem glede na odgovore intervjuvancev, pri strukturni razsežnosti pa povprecje rezultatov intervjuja, anketnih odgovorov in mrežne analize. 3 REZULTATI IN RAZPRAVA 3.1. Analiza skupnosti UE Litija V UE Litija je registriranih 201 neprofitnih društev. Najvec društev ima sedež v Litiji in njeni okolici. Litija je središcno naselje, za katerega je znacilna gosta poselitev in posledicno zgošcevanje dejavnosti, tudi društvene (Potocnik Slavic, Rebernik, 2011). Organizacijski ucinki socialnega kapitala se po tipih društev razlikujejo, zato smo vsa društva, ki delujejo v UE Litija, najprej tipizirali. Podlaga tipizacije je bil Pravilnik o registru društev, registru podružnic tujih društev in evidenci društev v javnem inte­resu (2007), kot pomoc pri poimenovanju skupin smo uporabili tudi kategorizacijo Potocnik Slaviceve (2009), uporabljeno pri preucevanju socialnega kapitala na sloven­skem podeželju. Društva na obmocju smo razdelili v 10 tipov (Slika 3). Iz analize javno dostopnih podatkov ugotavljamo, da neprofitna društva financne vire za izvedbo razlicnih projektov pridobijo iz clanarin, sponzorstev, donacij in preko razpisov razlicnih organov. Vecina društev se prijavlja na obstojece obcinske razpise: razpis za šport in kulturo, za mlade, za socialno varstvo in dejavnosti društev na podro­cju kmetijstva. Najvišji delež društev se na obcinske razpise prijavlja v tipu društva po­deželskih žena in deklet (100 %), generacijskih združenj (67 %) in kulturno-umetniških društev (58 %). Najvec društev, ki crpajo financna sredstva tudi iz drugih virov je v tipu zdravstveno-humanitarnih organizacij in turisticno-etnografskih društev, v vsakem tipu po tri. Zanimala nas je tudi zaposljivost nevladnega sektorja v UE Litija. Najvec zaposlenih je v tipu generacijskih združenj, kjer so zaposlene osebe v treh razlicnih dru­štvih. Sledijo turisticno-etnografska društva in zdravstveno-humanitarne organizacije, ki imajo vsaka po dva zaposlena (Ajpes, 2019). Kljub temu da je najvec zaposlenih v tipu generacijskih združenj, ta delovna mesta niso stalna in so projektno vezana. Posledica avtonomnosti delovanja društev so razlike v notranji organizaciji. Notra­nja organizacija društva vpliva na njegov socialni kapital in na aktivnost povezovanja z ostalimi društvi. Društva v UE Litija so razmeroma velika, saj jih je vec kot 45 % odgovorilo, da imajo od 50 do 200 clanov in v povprecju vec kot 20 aktivnih clanov. Anketiranci razlicno dolgo opravljajo svojo funkcijo, povprecna doba predsedovanja je 10,6 let. Rezultati analize anketiranja kažejo na najvecjo dovzetnost zdravstveno­-humanitarnih organizacij za sodelovanje in povezovanje. Te organizacije izvedejo najvecje relativno število dogodkov v partnerstvu (število vseh izvedenih dogodkov glede na število društev v tipu) in imajo najvec partnerjev (povprecno 4,3). Zdravstve­no-humanitarnim organizacijam sledijo generacijska (2,5 partnerja) in gasilska zdru­ženja (2,3 partnerja) Vecina društev posveca pozornost tudi medsebojnemu druženju clanov, saj je 43 % predstavnikov društev odgovorilo, da veckrat letno organizirajo dogodke z druženjem, 14 % društev pa organizira dogodke za medsebojno druženje clanov skoraj vsak teden. Analiza virtualnega socialnega kapitala kaže, da društva slabše izkorišcajo virtualni socialni kapital. Kljub temu da ima 82 % društev aktiven profil na socialnem omrežju Facebook, ga vecina uporablja predvsem za promocijo, manj za komunikacijo. 40 % društev ne deli objav drugih organizacij, ali jih kako drugace podpira, 26 % vprašanih pa to stori povprecno enkrat mesecno. K tvorbi socialnega kapitala v veliki meri prispeva aktivnost društev in organi­zacija dogodkov, ki omogoca interakcije in spodbuja mreženje. Analize korelacije s Pearsonovim koeficientom kaže na to, da je spremenljivka št. partnerjev statisticno znacilno povezana s spremenljivkama št. dogodkov in št. dogodkov v partnerstvu. Ko­relacija števila dogodkov in števila partnerjev je šibka, medtem ko vrednost Pearso­novega koeficienta potrdi zmerno povezanost števila partnerjev in števila dogodkov v partnerstvu. Spremenljivki št. dogodkov in št. dogodkov v partnerstvu sta srednje mocno povezani, ce organizacija organizira vec dogodkov, je vecja možnost, da orga­nizira tudi dogodke v partnerstvu. S Spearmanovim koeficientom povezanosti nismo mogli dokazati mocne ali zelo mocne povezanosti pri nobeni spremenljivki. Spear­manov koeficient 0,528 pomeni zmerno povezanost, kar izkazujeta spremenljivki po­membnost socialnega omrežja Facebook in pomembnost socialnega omrežja Instagram. Tisti uporabniki, ki pripisujejo vecjo pomembnost Facebooku, bolj verjetno vidijo prednosti tudi pri uporabi družbenega omrežja Instagram. Zmerno povezanost izka­zujeta tudi spremenljivki pomembnost socialnega omrežja Instagram in pomembnost socialnega omrežja Twitter. Vec objav ostalih uporabnikov delijo tisti, ki dajejo vecjo težo socialnima omrežjema Facebook in Instagram v primerjavi z ostalimi. Na podlagi izracunane korelacije predpostavljamo, da v kolikor je društvo bolj ak­tivno in organizira vec dogodkov, vecja je verjetnost, da se društvo tudi povezuje in vkljucuje v projektna partnerstva. S statisticno analizo smo želeli preveriti, katere spremenljivke najbolj vplivajo na spremenljivko število dogodkov. Neodvisne spremenljivke, ki so bile vkljucene v na­daljnjo analizo, so: število organiziranih dogodkov v partnerstvu, število aktivnih cla­nov in število clanov. Gre za številske spremenljivke, ki so bile izbrane na podlagi kore­lacijske analize. Navedene neodvisne spremenljivke z odvisno izkazujejo vsaj zmerno povezanost (Pearsonov koeficient višji od 0,4). Preglednica 4: Koeficienti povezanosti izbranih spremenljivk po metodi Enter. Nestan­dardiziran regresijski koeficient B Standardna napaka ocene Stn Standardni regresijski koeficient Beta Koeficient T-vrednosti t Statisticna znacilnost t-testa p število dogodkov v partnerstvu 0,417 0,092 0,406 4,538 0,000 število aktivnih clanov 0,604 0,222 0,236 2,725 0,008 število clanov 0,117 0,046 0,201 2,529 0,013 število partnerjev 0,124 0,101 0,100 1,227 0,223 Vir podatkov: Anketiranje društev v UE Litija, 2021. Standardizirani regresijski koeficient beta je najvišji pri spremenljivki število do­godkov v partnerstvu, kar pomeni, da ima na odvisno spremenljivko vecji vpliv in posledicno vecjo pojasnjevalno moc. Število dogodkov, ki se v društvu odvijejo v soorganizaciji z ostalimi partnerji, pozitivno prispeva h koncnemu številu dogod­kov v društvu, kar pa ne pomeni, da nadomešcajo stalne dogodke. Metoda Enter nam ponudi model, kjer multipli korelacijski koeficient R znaša 0,69. Delež celotne variance spremenljivke število dogodkov lahko z vkljucenimi spremenljivkami po­jasnimo v 47 %. Standardna napaka znaša 0,33, model je glede na analizo variance (ANOVA) statisticno znacilen (F-test: p = 0). Metoda Stepwise nam ponudi tri mo­žne modele, ki pojasnjujejo podoben ali manjši delež variance odvisne spremenljivke število dogodkov, odvisno od števila vkljucenih spremenljivk. V predlaganih modelih je nestandardiziran regresijski koeficient beta vecji pri spremenljivki število organi­ziranih dogodkov v partnerstvu. Da društvo deluje in širi svoj nabor aktivnosti, je torej kljucnega pomena, da je vkljucenih vec clanov (predvsem aktivnih clanov), ki izpeljejo dogodke tudi v partnerstvu. Preglednica 5: Kazalci multiplega regresijskega modela za napovedovanje števila dogodkov po metodi Stepwise. Model Mutipli regresijski koeficient R Determinacijski koeficient Rsq Standardna napaka modela Stm Statisticna znacilnost F-testa p 1 0,594 0,353 0,35532 0,000 2 0,652 0,425 0,33667 0,001 3 0,680 0,463 0,32713 0,011 Vir podatkov: Anketiranje društev v UE Litija, 2021. S kvantitativno mrežno analizo organizacij v UE Litija smo prikazali znacilnosti strukturne razsežnosti organizacijskih ucinkov socialnega kapitala. Za izracun vpetosti organizacij v socialno mrežo smo izracunali mere središcnosti s pomocjo programa R. Premer socialnega omrežja organizacij v UE Litija znaša 8 korakov (med skraj­nimi vozlišci), kar kaže na redke povezave in zato daljšo pot, da preckamo mrežo. Število vezi je v mreži 321 in število vozlišc 149. Vozlišca so vse organizacije, zajete v mrežno analizo, vezi pa predstavljajo vse medsebojne povezave med vozlišci. So­cialno omrežje je glede na vezi in vozlišca veliko, hkrati pa je razvejano, na kar kaže vecja velikost premera (vec kot je korakov, vecja je razvejanost). Posledica tovrstne strukture je nizka gostota povezav in lokacijsko povezovanje v posameznih skupinah (predvsem strokovno mreženje in povezovanje s skupnimi interesi). V širšo socialno mrežo se na obmocju vkljucuje približno 20 društev, ostala društva so slabše poveza­na, v vecini z eno ali dvema drugima organizacijama. Stopnja prehodnosti v mreži je 0,1, kar kaže na nizko prehodnost. Stopnja prehodnosti je socialni mehanizem, kjer lahko opazujemo povezanost vozlišc. Bolj kot so ta med seboj povezana, vecja je pre­hodnost (podatkov, dobrin, itd.) v socialni mreži. Ce je prehodnost mreže enaka 1, je mreža popolnoma prehodna (Markovic, 2015). Socialna mreža organizacij prav tako nima mocnega jedra, temvec mocne povezovalne organizacije (generacijska združe­nja, turisticno-etnografske organizacije in strokovna združenja). Na sliki 4 z veliko­stjo krogov prikazujemo število vseh povezav za posamezno organizacijo, z rumeno barvo pa tiste, ki imajo vec kot tri vhodne povezave. Te so z vidika analize središcnosti pomembnejše, saj ne predstavljajo le anketiranih društev, temvec vse organizacijske enote, ki so bile v anketi najveckrat omenjene. Slika 4: Socialna mreža organizacij v UE Litija (izsek). 3.2 Analiza organiziranosti Analizo transkribiranih pogovorov intervjujev smo izvedli s pomocjo kodiranja v pro­gramu Atlas.ti. Analiza relacijske razsežnosti kaže na visoko stopnjo medsebojnega zau­panja tako med clani, organizacijami, skupnostjo in obcino. Na podlagi analize sklepa­mo, da vecina društev zaupa lokalnim organizacijam in podpori skupnosti. V nasprotju s splošnim zaupanjem organizacijam, se zaupanje clanom najveckrat pokriva s koncen­tricnimi krogi aktivnosti, kar pomeni, da predstavniki društev najbolj zaupajo svojemu upravnemu odboru, nato aktivnim clanom in najmanj clanom, ki so manj aktivni. Pred­stavniki društev opažajo, da so njihove glavne ovire pri napredku društva staranje clan­stva in pomanjkanje notranjih virov za ucinkovitejše udejstvovanje v skupnosti. Manjša povezanost v socialni mreži se odraža tudi pri udejstvovanju organizacij v Programu za razvoj podeželja. Izmed 201 društva v UE Litija se v projektna partner­stva LAS povezuje 10 društev. Predstavniki društev kot glavne težave navajajo nekom­petentnost za vodenje tovrstnih projektov, pomanjkanje kadra, zapleteno birokracijo in težave v povezavi s financiranjem. Deležniki na fokusni skupini ugotavljajo, da na preucevanem obmocju manjka podporna organizacija, ki bi društvom nudila podpo­ro in pomoc pri tovrstnih projektih. Analiza kognitivne razsežnosti kaže, da clani z vclanitvijo prevzamejo identiteto društva, aktivni clani pa redno dajejo pobude in si želijo biti vkljuceni v proces dela. Osebnostni razvoj clani dosegajo z razlicnimi oblikami neformalnega izobraževa­nja, lokalni razvoj pa predvsem z izvajanjem razvojno naravnanih projektov. Kljucne težave v povezavi z delovanjem organizacij, ki jih navajajo predstavniki društev, so predvsem pomanjkanje notranjih virov: clanov za izvajanje projektov, pomanjkljivo znanje in staranje clanstva. Kot možnost za nadgradnjo trenutnega stanja deležniki na fokusni skupini ugotavljajo, da je potrebna vzpostavitev podporne organizacije, ki bi nudila podporo društvom pri zapolnjevanju potreb pri izgubi notranjih virov in vzpostavitev premostitvene organizacije, ki bi spodbujala mreženje na preucevanem obmocju. Trenutni primanjkljaj se namrec kaže tudi v možnostih mreženja, saj sami zaznavajo, da v projektih sodelujejo vedno ista društva. Analiza zaznavanja virtualnega socialnega kapitala s strani predstavnikov organi­zacij kaže na to, da so virtualni socialni mediji razumljeni le kot kanal za komunikaci­jo s splošno javnostjo, ali pa kot virtualna izkaznica o delovanju drugih organizacij, le redkokdaj kot medij za navezovanje in ohranjanje stikov (s clani, ostalimi organizaci­jami). Virtualni socialni kapital bolje izkorišcajo mlajše generacije (študentski klub), ki jim je uporaba socialnih omrežij blizu. Vecina intervjuvanih (11) bi zaupala osebno nepoznani organizaciji na spletu in navezala stik v primeru potrebe po informacijah, partnerjih pri dogodkih in podobno, vendar do sedaj še niso imeli potrebe po tem. Deležniki, prisotni na fokusni skupini, ugotavljajo, da virtualno udejstvovanje ni pri­marni namen društev, saj že samo ime daje poudarek druženju (družba/društvo), za kar je potreben fizicen prostor. 3.3 Vrednotenje prispevka organizacij k akumulaciji socialnega kapitala Po korakih orodja SCAT smo iz posameznih analiz povzeli kljucne ugotovitve o raz­sežnostih socialnega kapitala in jih sintezno vrednotili v preglednici 7. Virtualni soci­alni kapital smo upoštevali znotraj strukturne in relacijske razsežnosti, saj je virtualna oblika socialnega kapitala dopolnjujoca fizicni in je zaradi tega nismo locevali. Vrednotenje organizacijskih ucinkov po štiristopenjski lestvici kaže na razvit soci­alni kapital v UE Litija. Glede na dolocene kazalnike se kaže najvec pomanjkljivosti in prostora za napredek pri strukturni razsežnosti, kjer je skupna ocena socialnega kapitala srednja (3. stopnja). Ocena socialnega kapitala pri relacijski razsežnosti in pri kognitivni je visoka (4. stopnja). Vrednotenje kaže na dobro medsebojno povezanost, kar je posledica dolge tradicije delovanja društev in zaupanja društvenim strukturam, medtem ko je zunanje povezovanje in sodelovanje slabše razvito. 4 SKLEP Organizacije v UE Litija na podlagi preucevanja organizacijskih ucinkov izkazujejo razvit socialni kapital. Ugotavljamo, da je v Upravni enoti Litija veliko število društev (201) z dolgo društveno tradicijo (povprecje delovanja je 28,5 let). Znotraj socialne mreže organizacij je desetina društev medsebojno zelo dobro povezana (približno 20 društev), ta se kot vozlišcne organizacije aktivno vkljucujejo v socialno mrežo in or­ganizirajo najvec dogodkov. Konkretni ucinki v prostoru, ki se kažejo kot posledica razvitega organizacijskega socialnega kapitala, so dogodki in projekti, ki hkrati omo­gocajo nove interakcije in posledicno nadaljnji razvoj socialnega kapitala v skupnosti. Ugotavljamo, da za razvoj virtualnega socialnega kapitala obstaja prostor in interes. Na podlagi rezultatov sklepamo, da vecina društev virtualnega socialnega kapitala ne uporablja zaradi pomanjkanja notranjih virov (predvsem mladih clanov), ki bi uprav­ljali socialna omrežja. Deležniki, ki so zastopali mnenja organizacij, so bili skupnega mnenja, da so virtualna omrežja pomemben vidik ohranjanja stikov, vendar je bistvo društev druženje v fizicnem okolju. Za ohranjanje in razvoj stopnje socialnega kapitala glede na organizacijske ucinke moramo društva ohranjati aktivna. Korelacijska analiza je pokazala, da ce je društvo aktivnejše, organizira vec dogodkov in se bolj verjetno povezuje v projektna partner­stva, ki so za razvoj organizacij in lokalnega okolja kljucna. Zaupanje je prav tako po­gojeno z aktivnostjo, saj so clani veckrat v medsebojni interakciji, se med seboj bolje poznajo in tako formirajo skupine z vec in mocnejšimi povezavami. Enako velja za zaupanje organizacijam, saj je za društva znacilno, da imajo dolgorocna partnerstva, ki temeljijo izkljucno na zaupanju. Za vecjo povezanost socialne mreže v UE Litija je treba ustvariti nove povezave, ki bi povecale gostoto mreže in njeno prehodnost. To bi lahko dosegli z novimi lokalnimi projekti, ki spodbujajo nove povezave in nove prilož­nosti za lokalni razvoj. Priložnost za rast socialnega kapitala in dvig usposobljenosti organizacij za prispevek k razvoju lokalnega obmocja je profesionalizacija nevladnega sektorja. Društva, ki nastopajo kot vozlišcne organizacije v socialni mreži UE Litija, imajo obicajno zaposleno vsaj eno osebo, ki poskrbi za zahtevnejšo administracijo in vodenje obsežnejših projektov. Vozlišcne organizacije s svojimi aktivnostmi v skup­nosti izstopajo in dosegajo najvišje vrednosti kazalnikov središcnosti. Te organizacije so nosilci razvoja in najvec prispevajo k akumulaciji socialnega kapitala na preuce­vanem obmocju. Premostitvene organizacije imajo v socialni mreži posebno mesto, saj zagotavljajo pretok informacij in imajo možnost vpliva na ostale organizacije. V socialni mreži organizacij UE Litija premostitvene organizacije ni, kar smo dokazali z izracunom mere središcnosti glede na dostopnost, kjer ne izstopa nobena izmed or­ganizacij. Takšna organizacija ima sicer pomembno vlogo, saj nastopa kot moderator, ki organizacije na obmocju med seboj povezuje, koordinira medsebojne stike in jih usmerja v skladu s skupnimi cilji in vizijo razvoja obmocja. V prispevku so obravnavani le organizacijski ucinki socialnega kapitala. Za celostno vrednotenje stopnje socialnega kapitala bi bilo treba izvesti še analizo gospodinjstev, ki bi prispevala pogled posameznikov in njihovega individualnega prispevka k skup­nosti in k akumulaciji socialnega kapitala. Literatura in viri Agampodi, T., Agampodi, S. B., Glozier, N., Lelwala, T. A., Sirisena, K., Siribadda­na, S., 2019. 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Jou­rnal of Rural Studies, 28, str. 458–465. DOI: 10.1016/j.jrurstud.2012.10.002. Zhang, J., Luo, Y., 2017. Degree centrality, betweenness centrality, and closeness cen­trality in social network. Advances in Intelligent Systems Research, 132, str. 300–303. DOI: 10.2991/msam-17.2017.68. ORGANIZATIONAL EFFECTS OF SOCIAL CAPITAL IN THE OPERATION OF ORGANIZATIONS IN THE LITIJA ADMINISTRATIVE UNIT Summary Social capital is a product of reciprocal connections among individuals that are based on trust, mutual support and solidarity. The most basic division of social capital in­cludes three dimensions: structural, relational and cognitive. The construction of a personal network or a network of organizations does not happen only in the physical environment, but also in the virtual one. It predominantly means the development of weak connections (bridging social capital) which can be established or maintained with the presence and activity on social media. Due to the interlacement of relation­ships in the physical and virtual environment we also dedicate special attention to the virtual social capital. The SCAT tool, which is developed for the standardised evalu­ation of the social capital, logically includes combinations of methods that are meant for an effective analysis of all three dimensions of the social capital. Its virtual char­acteristics were also reasonably included. The adapted SCAT tool predicts two steps: community profile and organizational profile. In the first step we carried out analysis of public sources (employment rate, application for public grants, contact data) and a survey for societies. In the second step we interviewed node organizations (identified from quantitative network analysis) and carried out one focus group. In our research we analyse the entire network of organizations in the Litija Administrative Unit with emphasis on organizations, which enables networking of the participating local ac­tors, information flow; it represents a possibility for information growth, innovations and identity construction. The social tradition in the Litija Administrative Unit area is long; due to that there are many associations in this area which have a high number of members and active members. That is also confirmed by the quantitative network analysis that serves as a basis for our findings which point out that the social network of organizations in Litija Administrative Unit is large and branched. The most active type of societies, which execute most events and events in partnerships in ratio with the number of societies, are the health-humanitarian organizations. A fifth of all soci­eties in the social network is reciprocally very well connected. The evaluation of organizational effects with a four-degree scale showed that social capital is present in the Litija Administrative Unit. The analysis of relational dimension points to a high degree of mutual trust among members, organizations and also in the community; the cognitive analysis shows good knowledge of the goals and the achieve­ment of them. The structural dimension is evaluated as the weakest one; meaning the characteristic of social network organizations that requires improvement to function properly. organizations in the area use the virtual social capital in smaller extents. De­spite the expressed interest and the trust in online organizations, societies do not devel­op their social capital on virtual platforms. 40 % of societies do not share posts that are made by other organizations or support them in any other way. Associations perceive social capital developed in physical environment more important as virtual. When establishing and maintaining the social capital, the social activity is crucial. The formation of new connections is conditioned by constant activity and event organi­zation; meanwhile trust is conditioned by long-lasting partnership and collaboration during a longer period of time. For a better connectedness of the social network in the Litija Administrative Unit, we need to create new connections that would increase the density of the network and its transitivity. An important contribution to the non-governmental sector, which would consequently cause a higher participation rate of societies in the local community and a qualified activity, is also the professionalization of occupations in bigger associations. An important contribution could also be made by a strong bridging organization which would offer support to the societies, and at the same time act as a connective link, moderator and organizer of the social network. IS THE NEW REGULATION OF CONSTITUENCIES FOR PARLIAMENTARY ELECTIONS IN SLOVENIA CONSTITUTIONAL? Abstract In February 2021, the National Assembly of the Republic of Slovenia adopted an amendment to the law determining the electoral districts used for parliamentary elec­tions in Slovenia. The amendment minimally changes the system of electorates, which the Constitutional Court of the Republic of Slovenia found to be unconstitutional in 2018. For this paper, we examined the extent to which the new system meets the legal criteria and remedies the unconstitutional situation. The comparative analysis, which includes the old and the new systems as well as two proposals formed by an expert group in 2019, has highlighted several shortcomings of the new system. The new sys­tem eliminates the vast differences in district sizes but does not solve the problem of geographically inconsistent constituencies. As a result, the new system may again be subject to constitutional review. Keywords: electoral geography, electoral districts, Slovenia, National Assembly of the Republic of Slovenia 1 UVOD Volilne enote so eden najpomembnejših elementov volilnega sistema (Lijphart, 1994). V volilni sistem so navadno vkljucene zaradi želje po enakomernejši prostorski po­razdelitvi mandatov, tesnejši povezanosti volivcev in poslancev ter lažji organizaciji in izvedbi volitev (Kras.ovec, 2007; Norris, 2004). Ureditev volilnih enot enako kot drugi elementi volilnega sistema pripomore k legitimnosti volilnega sistema. Ureditev, ki del volilnega telesa postavlja v neenakopraven položaj oziroma ga diskriminira, lahko vodi v odtujenost volivcev in volilno neaktivnost. Ta se navadno kaže v nizki volilni udeležbi ali vecjem deležu neveljavnih glasovnic (McAllister, Makkai, 1993; Power, Garand, 2007). Oba dejavnika spodkopavata legitimnost izvoljenih oblasti, s tem pa se zmanjšuje tudi stopnja sprejemanja vladnih odlocitev (Hadjar, Beck, 2010). Državni zbor RS je februarja 2021 po vec kot dveletni razpravi sprejel novelo Zako­na o dolocitvi volilnih enot za volitve poslancev v državni zbor (v nadaljnjem besedilu ZDVEDZ). Sprejetje novele je koncni rezultat reforme volilne zakonodaje, ki jo je sproži­la odlocba Ustavnega sodišca o neustavnosti ureditve volilnih okrajev iz leta 2018. Ustav­ni sodniki so ugotovili, da so problematicne tako velike razlike v številu volivcev med volilnimi okraji kot tudi njihova geografska nezaokroženost (Ustavno sodišce RS, 2018). Odlocitev Ustavnega sodišca RS je sprožila reformo volilne zakonodaje, v okviru katere sta se oblikovala dva predloga. Prvi je predvideval temeljitejšo spremembo vo­lilnega sistema z uvedbo relativnega prednostnega glasu in odpravo volilnih okrajev. Drugi je predvideval le preoblikovanje meja volilnih okrajev. Ministrstvo za javno upravo je za pripravo drugega predloga oblikovalo strokovno delovno skupino, ki je v letu 2019 pripravila tri predloge nove ureditve volilnih okrajev (Rogelj in sod., 2019a; 2019b). Po zamenjavi vlade marca 2020 je pripravo nove zakonodaje prevzela nova vladna koalicija pod vodstvom Slovenske demokratske stranke (SDS). Medtem ko je strokovna skupina zagovarjala temeljito preoblikovanje ureditve volilnih okrajev, je stranka SDS zagovarjala minimalne spremembe (MMC RTV SLO, 2021). Predstav­niki SDS-a so trdili, da je veljavna ureditev v vecji meri ustrezna, problematicna naj bi bila le pešcica velikostno (glede na število volivcev) mocno odstopajocih volilnih okrajev. Skladno z omenjenim stališcem je Ministrstvo za javno upravo (MJU) v za­cetku leta 2021 pripravilo predlog, ki je predvidel spremembo meja štirinajstih volil­nih okrajev in tri popravke meja volilnih enot. V središcu raziskave je ocena ustavnosti sprejete ureditve. Zanima nas, ali ta od­pravlja neustavno stanje oziroma v kolikšni meri izpolnjuje zakonska dolocila o ve­likosti in geografski zaokroženosti volilnih okrajev. V ta namen smo izvedli primer­jalno prostorsko in statisticno analizo, v kateri smo novo ureditev primerjali s staro ureditvijo in z dvema predlogoma, ki ju je pripravila strokovna skupina. 2 VOLILNI OKRAJI V DRŽAVNOZBORSKEM VOLILNEM SISTEMU Ozemlje države je za potrebe državnozborskih volitev razdeljeno na osem volilnih enot (slika 2). Vsaka od njih je razdeljena na 11 volilnih okrajev (skupaj je država razdeljena na 88 volilnih okrajev). Medtem ko v volilnih enotah poteka primarna medstrankarska delitev mandatov, so volilni okraji uporabljeni za znotrajstrankarsko delitev mandatov (Grad, 2004). Zakon o volitvah v državni zbor (v nadaljnjem besedilu ZVDZ) doloca, da morajo imeti volilni okraji približno enako število prebivalcev in da je pri njihovem obliko­vanju treba upoštevati geografsko zaokroženost ter skupne kulturne in druge znacil­nosti (Zakon o volitvah ..., 2017). Pri tem je pomembno, da zakon nikjer ne doloca maksimalno dovoljenega odstopanja v številu prebivalcev. Prav tako ne doloca, katera merila je treba upoštevati, da bi zadostili merilu geografske zaokroženosti. Prvi osnutek ZDVEDZ iz leta 1992 je predvideval oblikovanje približno enako ve­likih volilnih okrajev (predlog je predvideval najvec 10-odstotno odstopanje). Politika je omenjenemu predlogu zaradi delitve vecine obcin mocno nasprotovala in v parla­mentarni postopek vložila dopolnilo, na podlagi katerega so se pri oblikovanju volilnih okrajev upoštevale geografska zaokroženost in skupne znacilnosti ozemlja. V praksi je to pomenilo, da so meje volilnih okrajev, ce je bilo to mogoce, uskladili z mejami takra­tnih obcin (Rogelj, 2011, str. 92). S tem so ustvarili geografsko relativno homogene in kompaktne, velikostno pa zelo heterogene volilne okraje (preglednica 1, slika 1). Ureditev volilnih enot in volilnih okrajev je bila od vsega zacetka deležna številnih kritik (Gaber, 1996; Pogorelec, 1998; Ribic.ic., 1996). Kljub temu vse od sprejetja obeh temeljnih zakonov leta 1992 ni doživela vecjih sprememb. Nekaj manjših popravkov je bilo narejenih leta 2004, ko so meje nekaterih okrajev uskladili z novimi obcinskimi mejami (najvecje spremembe so bile na obmocju obcin Železniki in Novo mesto). O ustavnosti ureditve je trikrat presojalo tudi Ustavno sodišce RS. V prvih dveh primerih (v letih 1992 in 2003) so sodniki presodili, da ureditev ni neustavna (Ustavno sodišce RS, 2003; 1992), v tretjem so presodili, da je 4. clen ZDVEDZ neskladen z Ustavo RS. K omenjeni odlocitvi sta pripomogla predvsem dva dejavnika. Prvi so spremembe v prostorski razporeditvi prebivalstva, zaradi katerih so se razlike v številu prebivalcev/volivcev med volilnimi okraji še dodatno povecale (preglednica 1, slika 1). Številne re­forme lokalne samouprave po letu 1992 so drugi pomemben dejavnik. Zaradi njih je v številnih primerih prišlo do neusklajenosti meja volilnih okrajev z obcinskimi mejami. Preglednica 1: Velikost volilnih okrajev v letih 1992 in 2019 (vir podatkov: MNZ, 2019; ZRSS, 1994). 1992 2019 Povprecna velikost volilnega okraja (št. volivcev) 16.970 19.358 Velikost najmanjšega volilnega okraja (št. volivcev) 8.313 Hrastnik 7.945 Hrastnik Odstopanje najmanjšega volilnega okraja od povprecja –51,0 % –59,0 % Velikost najvecjega volilnega okraja (št. volivcev) 25.383 Murska Sobota I 31.694 Grosuplje Odstopanje najvecjega volilnega okraja od povprecja +49,9 % +63,7 % Razlika med najvecjim in najmanjšim volilnim okrajem (št. volivcev) 17.070 23.749 Število volilnih okrajev, ki od povprecja odstopajo za manj kot 15 % (–/+ 15 %) 45 40 3 METODOLOGIJA DELA Analiza temelji na podatkih Centralnega registra prebivalstva (CRP) o številu volivcev po hišnih številkah, ki ga vodi Ministrstvo za notranje zadeve RS (MNZ, 2019), prostor­skih podatkovnih slojih Registra prostorskih enot (RPE), ki ga vodi Geodetska uprava RS (GURS, 2021), in prostorskih podatkovnih slojih, ki jih je pripravila strokovna de­lovna skupina (Rogelj in sod., 2019a; 2019b). Podatki o volivcih odražajo stanje aprila 2019 (povprecni volilni okraj je takrat štel 19.358 volivcev), prostorski podatkovni sloji pa stanje leta 2019 (podatki strokovne delovne skupine) oziroma 2021 (podatki Registra prostorskih enot). Za potrebe raziskave smo podatke o volivcih agregirali na ravni raz­licnih prostorskih enot (prostorski okoliši, naselja, obcine, volilni okraji). Na tem mestu velja opozoriti, da so oblikovalci nove ureditve volilnih okrajev operirali z novejšimi podatki o številu volivcev (verjetno iz druge polovice leta 2020). Zaradi intenzivnih me­dobcinskih selitev v prvem obdobju epidemije COVID-a (Razpotnik, 2020) se omenje­ni podatki nekoliko razlikujejo od podatkov, uporabljenih v analizi. Analizirali smo štiri ureditve volilnih okrajev: • ureditev, ki je veljala od leta 2004 do leta 2021 (stara ureditev); • ureditev, ki velja od leta 2021 (nova ureditev); • ureditev, ki jo je predlagala strokovna skupina leta 2019 (predlog strokovne sku­pine); • alternativno ureditev, ki jo je predlagala strokovna skupina leta 2019 (alternativ­ni predlog strokovne skupine). S pomocjo izbranih kvantitativnih kazalcev (uporabili smo razlicne mere razprše­nosti, razmerja in indekse) smo preverili, v kolikšni meri posamezna ureditev sledi zakonskemu dolocilu, da naj bi imeli volilni okraji približno enako število prebival­cev/volivcev. Oceno geografske zaokroženosti volilnih okrajev smo naredili na podla­gi prostorske analize usklajenosti njihovih meja z mejami obstojecih upravno-terito­rialnih enot (mestnih cetrti, krajevnih skupnosti, naselij in obcin). 4 GLAVNE ZNACILNOSTI NOVE UREDITVE VOLILNIH OKRAJEV (2021) Državni zbor RS je 16. februarja 2021 sprejel novelo ZDVEDZ. Z njo so bile spreme­njene meje štirinajstih volilnih okrajev (VO) in petih volilnih enot (VE). Spremembe meja volilnih enot (Zakon o spremembah in dopolnitvah ..., 2021): 1. VE 4: iz nje se izloci obmocje volilnega okraja Litija, ki obsega obcini Litija in Šmartno pri Litiji, ter naselji Ravne nad Šentrupertom in Kostanjevica v obcini Šentrupert in naselja Pusti Javor, Radanja vas, Sela pri Sobracah, Sobrace in Vrh pri Sobracah v obcini Ivancna Gorica; 2. VE 5: iz nje se izloci del naselij Knezdol in Vrhe v obcini Trbovlje; 3. VE 6: prikljuci se ji obcini Litija in Šmartno pri Litiji, naselji Ravne nad Šentru­pertom in Kostanjevica v obcini Šentrupert ter naselja Pusti Javor, Radanja vas, Sela pri Sobracah, Sobrace, Vrh pri Sobracah v obcini Ivancna Gorica ter dela naselij Knezdol in Vrhe v obcini Trbovlje; 4. VE 7: izloci se del obcine Pesnica, ki obsega naselja Dragucova, Ložana, Pernica, Vosek in Vukovje ter del naselja Kušernik; 5. VE 8: prikljuci se ji del obcine Pesnica, ki obsega naselja Dragucova, Ložana, Pernica, Vosek in Vukovje ter del naselja Kušernik. Volilni okraj Litija je bil iz VE 4 prestavljen v VE 6, ker je bilo treba zmanjšati raz­liko v velikosti volilnih enot. Zaradi razlicnih demografskih trendov se je razlika med najvecjo (VE 4) in najmanjšo (VE 6) volilno enoto v zadnjih dveh desetletjih mocno povecala (leta 2019 je znašala že 11 odstotnih tock). Posledicno je bila ogrožena enaka volilna pravica, skladno s katero mora enega poslanca voliti približno enako število volivcev. S premikom volilnega okraja Litija se je omenjena razlika obcutno zmanjšala (na 4,4 odstotne tocke). Preostale spremembe so posledica uskladitve meja volilnih enot z obcinskimi me­jami. Pri tem pa je zanimivo, da je nova ureditev povzrocila novo neskladje, saj je obcina Ivancna Gorica po novem razdeljena med VE 4 in VE 6. V slednjo spada kra­jevna skupnost Sobrace, ki je bila v preteklosti del obcine Litija, z reformo lokalne samouprave pa je bila prikljucena obcini Ivancna Gorica. Spremembe volilnih okrajev (Zakon o spremembah in dopolnitvah ..., 2021): 1. VO 4002 (Ribnica): se poveca za obmocje obcine Dobrepolje; 2. VO 4003 (Grosuplje): se zmanjša na obmocje obcine Grosuplje; 3. oblikuje se nov VO 4004 (Ivancna Gorica): ki obsega del obcine Ivancna Gorica (brez naselij Pusti Javor, Radanja vas, Sela pri Sobracah, Sobrace, Vrh pri Sobracah); 4. VO 5005 (Žalec II) se zmanjša za majhen del obcine Trbovlje (del naselij Knez­dol in Vrhe); 5. VO 6002 (Novo mesto I): se zmanjša za obmocje obcine Škocjan; 6. VO 6004 (Trebnje): se poveca za del obcine Šentrupert (naselja Ravne nad Šen­trupertom in Kostanjevica ter Mali Cirnik pri Šentjanžu); 7. VO 6007 (Sevnica): se poveca za obcino Škocjan ter zmanjša za del obcine Šen­trupert (naselje Mali Cirnik pri Šentjanžu); 8. VO 6009 (Litija): se zmanjša za del obcine Šentrupert (naselji Ravne nad Šen­trupertom in Kostanjevica); 9. VO 6010 (Trbovlje-Hrastnik): se poveca za obmocje obcine Hrastnik, hkrati se mu doda del naselij Knezdol in Vrhe v obcini Trbovlje; 10. nekdanji VO 6009 (Hrastnik) se ukine; 11. VO 7002 (Slovenska Bistrica): se zmanjša za del obcine Slovenska Bistrica (kra­jevni skupnosti Pragersko ter Spodnja in Zgornja Polskava); 12. VO 7005 (Maribor I): se poveca za del obcine Slovenska Bistrica (krajevne skupnosti Pragersko ter Spodnja in Zgornja Polskava); 13. VO 7007 (Maribor III): se zmanjša za del obcine Pesnica (naselja Dragucova, Ložana, Pernica, Vosek in Vukovje ter del naselja Kušernik); 14. VO 8008 (Pesnica): se poveca za del obcine Pesnica (naselja Dragucova, Loža­na, Pernica, Vosek in Vukovje ter del naselja Kušernik). V grobem lahko spremembe meja volilnih okrajev razdelimo v dve skupini. V prvi so spremembe, ki so nastale zaradi želje po zmanjševanju velikih razlik v velikos­ti volilnih okrajev. Z razkosanjem VO 4003 (Grosuplje) in zmanjšanjem VO 7002 (Slovenska Bistrica) sta se obcutno zmanjšala dva najvecja volilna okraja v državi. Z oblikovanjem VO 6010 (Trbovlje-Hrastnik) in povecanjem VO 4002 Ribnica sta se povecala najmanjša okraja v državi. V drugo skupino spadajo spremembe, ki so nastale zaradi uskladitve meja volilnih okrajev z obcinskimi mejami. Pri tem velja opozoriti, da je bila odpravljena le pešcica neskladij. Pred spremembo ureditve je bilo v državi 24 obcin, katerih meje niso bile usklajene z mejami volilnih okrajev (Rogelj, 2012). Nova ureditev je odpravila le tri neskladja, in sicer na obmocju obcin Pesnica, Trbovlje in Šentrupert. Poseben primer je premik obcine Škocjan iz VO 6002 (Novo mesto I) v VO 6007 (Sevnica). Razlogi zanj niso jasni. Res je, da so z omenjeno potezo uravnotežili veli­kost obeh (prvi je spadal med vecje, drugi pa med manjše okraje), toda dejstvo, da ne­kateri bolj izstopajoci volilni okraji niso bili preoblikovani, kaže na to, da je bil premik verjetno povezan s partikularnimi interesi najvecje koalicijske stranke. 5 GLAVNE ZNACILNOSTI PREDLOGA STROKOVNE SKUPINE (2019) Strokovna skupina je v casu delovanja (leta 2019) pripravila tri predloge nove ureditve volilnih okrajev. Prvotni predlog je predvideval relativno majhna (-/+15 %) odstopanja v številu volivcev in uskladitev meja volilnih okrajev z mejami uveljavljenih prostorskih enot (obcin, naselij, cetrtnih/krajevnih/vaških skupnosti). Politicne stranke nad predlo­gom niso bile navdušene, saj je predvideval temeljito preoblikovanje takrat veljavne ure­ditve. V okviru pogajanj o spremembi volilnega sistema pod okriljem predsednika države je bilo sklenjeno, da se oblikuje nov predlog, ki bo dovoljeval vecja odstopanja v velikosti. Strokovna skupina je pripravila dva predloga, ki sta temeljila na enakih izhodišcih: • Velikost volilnih okrajev je bila dolocena na podlagi števila volivcev. • Velikost volilnega okraja naj ne bi odstopala od povprecnega volilnega okraja za vec kot 25 %. V izjemnih primerih se zaradi spoštovanja nacela geografske zaokroženosti dovolijo tudi vecja odstopanja v velikosti. • Meje volilnih okrajev se dolocajo na podlagi meja obcin. V primeru delitve ob­cin se upoštevajo meje naselij. Pri naseljih z vec kot 24.197 volivci (Celje, Kranj, Ljubljana in Maribor) se meje volilnih okrajev uskladijo z mejami krajevnih/mestnih/cetrtnih skupnosti. • V mestni obcini Ljubljana se pri oblikovanju volilnih okrajev v izjemnih prime­rih upoštevajo meje prostorskih okolišev. Oba predloga sta vkljucevala spremembo meja volilnih enot. Poleg sprememb, vkljucenih v novelo Zakona o dolocitvi volilnih enot za volitve poslancev v DZ, sta predvidevala še dve manjši spremembi. V mestni obcini Ljubljana bi bilo celotno ob­mocje cetrtne skupnosti Posavje vkljuceno v VE 4. V omenjeno volilno enoto bi bilo vkljuceno tudi celotno obmocje obcine Ivancna Gorica. Predloga sta se razlikovala v dovoljenih velikostnih odstopanjih in stopnji spošto­vanja nacela geografske zaokroženosti. Po prvem predlogu (v primerjalni analizi ime­novan predlog strokovne skupine) bi le sedem volilnih okrajev za vec kot 25 % odsto­palo od velikosti povprecnega volilnega okraja (le eden bi odstopal za vec kot 30 %). Predlog je predvideval delitev trinajstih obcin, med katerimi bi bile štiri (Brezovica, Grosuplje, Slovenska Bistrica in Vrhnika) manjše od velikosti najvecjega dovoljenega volilnega okraja. Drugi predlog (v primerjalni analizi imenovan alternativni predlog strokovne skupine) je odpravil delitev omenjenih obcin z oblikovanjem vecjega števila velikostno bolj izstopajocih volilnih okrajev (dvanajst okrajev bi odstopalo za vec kot 25 %, od tega šest za vec kot 30 %). Pri obeh predlogih bi na obmocju vecjih mestnih obcin (Ljubljana, Maribor, Celje, Kranj in Velenje) meje volilnih okrajev sledile me­jam naselij ter cetrtnih, mestnih in krajevnih skupnosti. 6 REZULTATI PRIMERJALNE ANALIZE Izbrani kvantitativni kazalci in graficne predstavitve (preglednica 2, slike 1, 4, 6, 8 in 9), s katerimi smo preverili spoštovanje zakonskega dolocila, po katerem naj bi imeli volilni okraji približno enako število prebivalcev/volivcev, kažejo na velike razlike med analiziranimi ureditvami. Predvsem med staro in novo ureditvijo ter obema predlogo­ma strokovne skupine. Nova ureditev je s preoblikovanjem dveh najmanjših in dveh najvecjih volilnih okrajev obcutno zmanjšala razliko med najbolj odstopajocima volil­nima okrajema, zelo malo pa je pripomogla k odpravi velike velikostne razpršenosti. Iz slik 4 in 9 je razvidno, da nova ureditev ohranja veliko volilnih okrajev, ki za vec kot 25 % odstopajo od povprecja, in da jih le slaba polovica od povprecja odstopa za manj kot 15 %. Iz rezultatov je razvidno, da so tako za staro kot novo ureditev veliki odmiki od povprecne velikosti prej pravilo kot izjema. Nasprotno lahko trdimo za oba predloga strokovne skupine, ki sta poleg velikih velikostnih razlik odpravila tudi veliko veliko­stno razpršenost (slike 6, 8 in 9). Osnovni predlog je predvidel le sedem okrajev, ki bi za vec kot 25 % odstopali od povprecja, od tega le eden (Šmarje pri Jelšah) za vec kot 30 %. Skoraj dve tretjini okrajev bi od povprecja odstopalo za manj kot 15 %. Alternativni predlog je predvidel nekoliko vecja odstopanja, saj bi ohranil oziroma ustvaril nekaj zelo majhnih volilnih okrajev (Ribnica, Rogaška Slatina, Izola in Ivancna Gorica). Posledic­no so izracunani kazalci razpršenosti slabši kot za osnovni predlog, vendar še vedno bistveno boljši kot pri stari oziroma novi ureditvi (preglednica 2). Preglednica 2: Izbrani kazalci velikostne razpršenosti volilnih okrajev v analiziranih ureditvah (vir: lastni izracuni na podlagi podatkov GURS, 2021; MNZ, 2019; Rogelj in sod., 2019a; 2019b). Kazalec Stara ureditev Nova ureditev Predlog strokovne skupine Alternativni predlog strokovne skupine Povprecna velikost 19.358 19.358 19.358 19.358 Mediana 18.569,5 18.562,5 19.384,5 19.539,5 Standardni odklon 4.704,7 4.171,3 3.029,8 3.410,6 Koeficient variacije 24,3 21,5 15,7 17,6 5 kvantil 12.806 12.942 14.433 13.334 95 kvantil 27.844 26.076 23.828 24.115 Interkvartilni razmik 6.629 6.503 4.276 5.253 Variacijski razmik (razlika med najvecjim in najmanjšim volilnim okrajem) 23.749 17.045 14.086 15.082 Najvecji volilni okraj 4003 – Grosuplje 5001 – Celje 1 7001 – Šmarje pri Jelšah 7004 – Slovenska Bistrica 1 Velikost najvecjega volilnega okraja 31.694 29.705 27.706 26.631 Odstopanje najvecjega volilnega okraja od povprecja 63,7 53,5 43,1 37,6 Najmanjši volilni okraj 6009 – Hrastnik 1007 – Tržic 1011 – Idrija 4002 – Ribnica Kazalec Stara ureditev Nova ureditev Predlog strokovne skupine Alternativni predlog strokovne skupine Velikost najmanjšega volilnega okraja 7.945 12.660 13.620 11.549 Odstopanje najmanjšega volilnega okraja od povprecja (v %) 59,0 34,6 29,6 40,3 Razmerje med najvecjim in najmanjšim volilnim okrajem 4:1 2,3:1 2,0:1 2,3:1 Število volilnih okrajev, ki od povprecja odstopajo za manj kot 15 % (–/+ 15 %) 40 41 55 51 Število volilnih okrajev, ki od povprecja odstopajo za manj kot 25 % (–/+ 25 %) 60 63 81 76 Število volilnih okrajev, ki od povprecja odstopajo za vec kot 25 % (–/+ 25 %) 28 25 7 12 Slika 9: Histogrami števila volivcev v volilnih okrajih v analiziranih ureditvah (GURS, 2021; MNZ, 2019; Rogelj in sod., 2019a; 2019b). Ocena geografske zaokroženosti je bila narejena s pomocjo prostorske analize uskla­jenosti meja volilnih okrajev z mejami obstojecih upravno-teritorialnih enot. Stara ure­ditev je temeljila na mejah obcin in krajevnih skupnosti iz leta 1992. Z reformami lokal­ne samouprave med letoma 1994 in 2012 sta se spremenila tako število kot prostorski obseg obcin in krajevnih skupnosti (slednje so bile ponekod odpravljene oziroma nado­mešcene s cetrtnimi/mestnimi/vaškimi skupnostmi). V stari ureditvi volilnih okrajev je bilo kar štiriindvajset obcin razdeljenih na dva ali vec okrajev. Pri devetih je bila delitev potrebna, saj je število volivcev v njih za vec kot 25 % presegalo velikost povprecnega volilnega okraja, pri preostalih je bila delitev nepotrebna (preglednica 3). Zaradi minimalisticnega pristopa k preoblikovanju volilnih okrajev je nova uredi­tev odpravila le tri delitve volilnih okrajev (Trbovlje, Šentrupert in Pesnica) (pregle­dnica 3, slika 10). Za odpravo vecine drugih bi bil potreben korenitejši poseg v ustroj volilnih okrajev. Izjema so tri obcine. Uskladitev obcinskih in okrajnih meja na ob­mocju obcin Bohinj, Ivancna Gorica in Zrece bi zahtevala minimalne spremembe. Še posebno nesmiselna je delitev obcine Ivancna Gorica, ki je v novi ureditvi razdeljena celo na dve volilni enoti (medtem ko je vecji del obcine v VE 4, so bila naselja Pusti Javor, Radanja vas, Sela pri Sobracah, Sobrace in Vrh pri Sobracah skupaj z obcino Litija in Šmartno pri Litiji prestavljena v VE 6). Predloga strokovne skupine v vecji meri odpravljata nepotrebne delitve obcin. Prvi predlog je predvidel odpravo enajstih, alternativni pa kar štirinajstih delitev. V stari ureditvi so bila poleg obcin razdeljena tudi nekatera naselja in krajevne skupnosti (preglednica 3). Medtem ko je delitev štirih najvecjih naselij (Ljubljana, Maribor, Celje in Kranj) nujna zaradi njihove velikosti, je delitev preostalih popol­noma nepotrebna in nesmiselna. V Ljubljani, Mariboru in Kranju je stara ureditev delila celo nekatere mestne/cetrtne/krajevne skupnosti (v Ljubljani je razdeljenih kar 13 od 17 cetrtnih skupnosti). Nova ureditev je odpravila le štiri delitve naselij, ohra­nja pa vse delitve mestnih/cetrtnih/krajevnih skupnosti. Nasprotno sta oba predloga strokovne komisije predvidela odpravo vseh delitev naselij (ohranila bi se le delitev naselja Vinarje pri Mariboru, ki je razdeljeno na dve mestni cetrti) in vecine mestnih/cetrtnih/krajevnih skupnosti (v Ljubljani bi se ohranila delitev mestnih cetrti Fužine, Šiška in Bežigrad, ki za vec kot 25 % presegajo velikost povprecnega volilnega okraja). Posledicno bi bili volilni okraji na obmocju Ljubljane in Maribora bolj homogeni, saj bi obsegali le obmocja mestnih naselij in neposrednega sosedstva (slika 11). Preglednica 3: Izbrani kazalci geografske zaokroženosti volilnih okrajev v analiziranih ureditvah (vir: GURS, 2021; MNZ, 2019; Rogelj in sod., 2019a; 2019b). Kazalec Stara ureditev Nova ureditev Predlog stro­kovne skupine Alternativni predlog stro­kovne skupine Število obcin, ki so razdeljene na dva ali vec volil­nih okrajev 24 21 13 10 Število razde­ljenih obcin, ki za vec kot 25 % presegajo veli­kost povprecnega volilnega okraja 9 9 9 99 Celje, Domžale, Ko­per, Kranj, Ljubljana, Maribor, Nova Go­rica, Novo mesto, Velenje Celje, Domžale, Koper, Kranj, Ljubljana, Mari­bor, Nova Gori­ca, Novo mesto, Velenje Celje, Dom­žale, Koper, Kranj, Ljublja­na, Maribor, Nova Gorica, Novo mesto, Velenje Celje, Dom­žale, Koper, Kranj, Ljublja­na, Maribor, Nova Gorica, Novo mesto, Velenje Število razdelje­nih obcin, ki za manj kot 25 % presegajo veli­kost povprecnega volilnega okraja 15 12 4 1 Bohinj, Brezovica, Dol pri Ljubljani, Hoce-Slivnica, Ivancna Gorica, Mo­ravske Toplice, Mur­ska Sobota, Pesnica, Ptuj, Rence-Vogrsko, Šentrupert, Škofljica, Trbovlje, Velenje, Zrece in Žalec Bohinj, Bre­zovica, Dol pri Ljubljani, Hoce-Slivnica, Ivancna Gorica, Moravske To­plice, Murska Sobota, Ptuj, Rence-Vogrsko, Škofljica, Velenje, Zrece in Žalec Brezovica, Grosuplje, Slo­venska Bistri­ca, Vrhnika Brezovica Število razde­ljenih naselij, ki za vec kot 25 % presegajo veli­kost povprecnega volilnega okraja 4 4 4 4 Ljubljana, Maribor, Celje, Kranj Ljubljana, Mari­bor, Celje, Kranj Ljubljana, Maribor, Celje, Kranj Ljubljana, Maribor, Celje, Kranj Število razdelje­nih naselij, ki za manj kot 25 % presegajo veli­kost povprecnega volilnega okraja 14 10 1 1 Domžale, Knezdol, Koper, Križe, Kušer­nik, Nemški Rovt, Pivola, Ptuj, Spodnje Hoce, Sveta Gora, Velenje, Vinarje, Vrhe, Zgornje Hoce Domžale, Koper, Križe, Nemški Rovt, Pivola, Ptuj, Sveta Gora, Velenje, Vinarje, Zgornje Hoce Vinarje Vinarje Število krajevnih/cetrtnih/mestnih skupnosti v najvecjih naseljih, ki so razdeljene na vec volilnih okrajev Ljubljana (skupaj 17 cetrtnih skup­nosti) 13 13 3 2 Maribor (skupaj 17 krajevnih skupnosti in mestnih cetrti) 6 6 0 0 Kranj (skupaj 26 krajevnih skup­nosti) 1 1 0 0 Celje (skupaj 19 krajevnih skup­nosti in mestnih cetrti) 0 0 0 0 Slika 10: Nova ureditev - obcine, ki so razdeljene na dva ali vec volilnih okrajev. Slika 11: Ureditev volilnih okrajev na obmocju mestne obcine Ljubljana: a) nova ureditev; b) predlog strokovne skupine. 7 SKLEP Iz rezultatov analize je razvidno, da nova ureditev volilnih okrajev temelji na minimal­nih spremembah stare ureditve. Posledicno ohranja vecino njenih problematicnih in nesmiselnih rešitev. Ali to pomeni, da je tudi nova ureditev neskladna z ustavo? Odgo­vor na to vprašanje je odvisen od interpretacije ZVDZ-ja in preteklih odlocitev Ustav­nega sodišca. Že prej smo opozorili, da zakonodaja nikjer ne doloca, kakšno je »približ­no enako število prebivalcev«, prav tako ne definira, kaj je »geografska zaokroženost«. Zagovorniki minimalnih sprememb zagovarjajo tezo, da mora ureditev volilnih okrajev izpolnjevati vsaj eno merilo 20. clena ZVDZ (tisto o enaki velikosti ali tisto o geografski zaokroženosti). Po njihovem mnenju so neustavne le velike razlike med najmanjšim in najvecjim volilnim okrajem, pri cemer naj bi zakonodaja dovoljevala celo 50-% odstopanja od velikosti povprecnega volilnega okraja. Svoje mnenje opi­rajo na odlocitev Ustavnega sodišca RS iz leta 1992, v kateri velike razlike v velikosti volilnih okrajev niso bile oznacene za protiustavne (Ustavno sodišce RS, 1992). Nova ureditev je zelo podobna ureditvi iz leta 1992. Enaka oziroma zelo podobna sta tako prostorski obseg kot velikost volilnih okrajev. Zagovorniki temeljitih sprememb nasprotno trdijo, da mora ureditev volilnih okrajev v cim vecji meri zadostiti obema zakonskima meriloma. Stara ureditev je bila problematicna tako zaradi velikih razlik v velikosti kot zaradi neusklajenosti meja volilnih okrajev z mejami preostalih upravno-teritorialnih enot. Po njihovem mnenju bi morala nova ureditev odpraviti obe pomanjkljivosti, vecja odstopanja v velikosti pa naj bi bila dovoljena le zaradi ohranjanja geografske zaokroženosti volilnih okrajev. Ce sledimo interpretaciji zagovornikov minimalnih sprememb, potem je nova ure­ditev ustrezna in skladna z ustavo. Ce sledimo interpretaciji zagovornikov temeljitih sprememb, pa je nova ureditev neustavna. Kateri interpretaciji bodo sledili ustavni sodniki ob morebitni prihodnji presoji ustavnosti ZDVEDZ-ja, je težko napovedati. Predloga strokovne skupine dokazujeta, da je v okviru zakonskih omejitev mogoce oblikovati velikostno primerljive in hkrati geografsko zaokrožene volilne okraje. Dosedanje reforme volilnega sistema v Sloveniji so pokazale, da je koncni rezultat reformnega procesa v vecini primerov odvisen od specificnih politicnih razmer in partikularnih interesov najmocnejših politicnih strank (Rogelj, 2011). Omenjena de­javnika sta odlocilno vplivala tudi na zadnjo reformo. Volilni okraji so zelo pomemb­ni pri delitvi poslanskih mandatov (mandati, ki jih stranka osvoji na ravni volilnih enot, se dodelijo strankarskim kandidatom z najvecjim deležem glasov v volilnem okraju). Izkušnje kažejo, da je obstojeci volilni sistem relativno predvidljiv. Predvsem vecje politicne stranke z daljšo tradicijo zelo dobro vedo, v katerih volilnih okrajih je možnost za izvolitev njihovih kandidatov velika, v katerih pa ne. Vodstva strank lahko z razporeditvijo izbranih kandidatov v »izvoljive« volilne okraje odlocilno vplivajo na dodelitev poslanskih mandatov. Vecje spremembe v ureditvi volilnih okrajev bi vsaj zacasno ustvarile razmere, v katerih bi bila izvoljivost posameznih kandidatov veliko bolj negotova. Zato ni presenetljivo, da so se nekatere stranke (predvsem SDS in De­SUS) z vsemi sredstvi borile za minimalne spremembe sistema. Na koncu velja opozoriti, da so bili volilni okraji vkljuceni v volilni sistem zato, da bi volivci odlocilno vplivali na dodelitev poslanskih mandatov. Dosedanje volitve so pokazale, da ni tako. Ce bi politiki resnicno želeli, da bi imeli volivci odlocilen vpliv na dodelitev poslanskih mandatov, potem bi bilo smiselno volilne okraje v celoti odpraviti oziroma jih nadomestiti z uvedbo prednostnega glasu. S tem volivec ne bi bil prisiljen voliti kandidata, ki mu ga vsili vodstvo politicne stranke. Literatura in viri Gaber, S., 1996. Volilni sistemi : zbornik. Ljubljana: Krtina. Grad, F., 2004. Volitve in volilni sistem. Ljubljana: Uradni list Republike Slovenije. GURS, 2019. Register prostorskih enot. URL: https://www.e-prostor.gov.si/brezplac­ni-podatki/ (citirano 25. 4. 2019). GURS, 2021. Register prostorskih enot. URL: https://www.e-prostor.gov.si/brezplac­ni-podatki/ (citirano 30. 11. 2021). Hadjar, A., Beck, M., 2010. Who does not participate in elections in Europe and why is this?: A multilevel analysis of social mechanisms behind non-voting. European Societies, 12, 4, str. 521–542. DOI: 10.1080/14616696.2010.483007. Kras.ovec, A., 2007. Volilne s.tudije. Ljubljana: Fakulteta za druz.bene vede. Lijphart, A., 1994. Electoral systems and party systems : a study of twenty-seven de­mocracies, 1945–1990. Oxford: Oxford University Press. McAllister, I., Makkai, T., 1993. Institutions, society or protest? Explaining invalid vo­tes in Australian elections. Electoral Studies, 12, 1, str. 23–40. DOI: 10.1016/0261-3794(93)90004-4. MMC RTV SLO, 2021. Zelena luc poskusu uskladitve glede volilne zakonodaje. URL: https://www.rtvslo.si/slovenija/zelena-luc-poskusu-uskladitve-glede-volilne-zako­nodaje/568786 (citirano 11. 2. 2021). MNZ, 2019. Centralni register prebivalstva – število volivcev po hišnih številkah. Norris, P., 2004. Electoral engineering voting rules and political behavior. Cambridge: Cambridge University Press. Pogorelec, J., 1998. Sistem volitev v Drz.avni zbor : nekaj predlogov za njegovo iz­boljs.anje. Pravna praksa. Power, T. J., Garand, J. C., 2007. Determinants of invalid voting in Latin America. Electoral Studies, 26, 2, str. 432–444. DOI: 10.1016/j.electstud.2006.11.001. Razpotnik, B., 2020. V prvem polletju 2020 dve tretjini vec medobcinskih selitev kot v istem obdobju leta 2019. URL: https://www.stat.si/StatWeb/news/Index/9232 (ci­tirano 6. 12. 2021). Ribic.ic., C., 1996. Osebnost kandidatov in sorazmerna zastopanost strank. V: Gaber, S. (ur.). Volilni sistemi. Ljubljana: Krtina, str. 283–303. Rogelj, B., 2011. Politic.nogeografska analiza volilnega sistema volitev v Drz.avni zbor Republike Slovenije. Doktorska disertacija. Ljubljana: Univerza v Ljubljani. Rogelj, B., 2012. Ureditev volilnih enot v državnozborskem volilnem sistemu. Dela, 37, str. 107–128. Rogelj, B., Krevs, M., Veršic, A., Prešern, M., 2019a. Predlog sprememb obmocij vo­lilnih enot in volilnih okrajev (Porocilo Medresorske delovne skupine za pripravo sprememb in dopolnitev ZVDZ). Ljubljana. Rogelj, B., Krevs, M., Veršic, A., Prešern, M., 2019b. Dopolnjen predlog sprememb obmocij volilnih enot in volilnih okrajev (Porocilo Medresorske delovne skupine za pripravo sprememb in dopolnitev ZVDZ). Ljubljana. Ustavno sodišce RS, 1992. Odlocba U-I-128/92. Ljubljana. Ustavno sodišce RS, 2003. Odlocba U-I-226/00. Ljubljana. Ustavno sodišce RS, 2018. Odlocba U-I-32/15-56. Ljubljana. Zakon o spremembah in dopolnitvah Zakona o dolocitvi volilnih enot za volitve po­slancev v državni zbor – ZDVEDZ-B. 2021. Uradni list RS, 29/21. Ljubljana. Zakon o volitvah v državni zbor. 2017. Uradni list RS, 23/17. Ljubljana. ZRSS [Zavod Republike Slovenije za statistiko], 1994. Rezultati raziskovanj – volitve 1992 (št. 600). Ljubljana. IS THE NEW REGULATION OF CONSTITUENCIES FOR PARLIAMENTARY ELECTIONS IN SLOVENIA CONSTITUTIONAL? Summary In national elections the territory of the Republic of Slovenia is divided into eight electoral districts (volilna enota). Each of them is subdivided into 11 constituencies (volilni okraj). In total, the country comprises 88 constituencies. Constituencies are very important for the division of parliamentary seats. The seats won by a party at the district level are allocated to the party candidates with the highest share of the vote in the constituency. The law stipulates that constituencies must have approximately the same number of inhabitants and that their creation must take into account geographical consistency as well as common cultural and other characteristics. It is important to note that no­where does the law set a maximum variation in the number of inhabitants. Nor does it specify which criteria must be taken into account in order to satisfy the criterion of geographical consistency. In 2018, the Constitutional Court of the Republic of Slovenia ruled that the system of constituencies was not compatible with the Constitution. The large differences in the number of voters between constituencies, as well as their geographic inconsist­ency, were considered problematic. The latter was most directly manifested in the mismatch between constituency and municipal boundaries. This decision triggered a reform of the electoral legislation, as part of which several proposals for a new elec­toral district system were put forth. The Ministry of Public Administration formed an expert working group which in 2019 prepared three proposals for a new system of constituencies (Figure 5, 6, 7 and 8) (Rogelj et al., 2019a; 2019b). Following the change of government in March 2020, the expert group was disbanded, and the drafting of new legislation was taken over by the new government coalition led by the Slovenian Democratic Party (SDS). While the ex­pert group advocated a radical overhaul of the constituency system, the SDS advocated minimal changes (MMC RTV SLO, 2021). The SDS representatives argued that the ex­isting system was mostly adequate, contending that there were only a handful of prob­lematic constituencies varying significantly in size (in terms of the number of voters). In line with this position, the Ministry of Public Administration prepared a pro­posal at the beginning of 2021, which foresaw a change in the boundaries of 14 con­stituencies and three revisions to the boundaries of electoral districts (Figures 2, 3 and 4). The proposal was voted through despite a number of concerns about its suitability and constitutionality and without broad political consensus. Our research focused on the constitutionality of the adopted system. We wanted to know whether it remedies the unconstitutional situation and to what extent it com­plies with the legal provisions on the size and geographical consistency of constituen­cies. To this end, we carried out a comparative spatial and statistical analysis, compar­ing the new system with the previous one and with the two proposals put forth by the expert working group. The analysis (Table 2, Figures 4, 6, 8 and 9) shows that the new system has signifi­cantly reduced the difference between the two most outlying constituencies but has done very little to eliminate the substantial variability in constituency size. Figures 4 and 9 show that the new system still features a large number of constituencies that deviate by more than 25% from the average, while there are only around half of all consistencies deviating from the average by less than 15%. In contrast, both propos­als of the expert group have not only eliminated the large size differences, but also the large variability in size (Figures 6, 8 and 9). The basic proposal envisaged only seven constituencies deviating by more than 25% from the average, of which only one (Šmarje pri Jelšah) deviated by more than 30%. The alternative proposal envisaged slightly larger deviations, as it would have maintained or created some very small constituencies (Ribnica, Rogaška Slatina, Izola and Ivancna Gorica). Assessments of the geographical consistency of constituencies were made through a spatial analysis of the alignment of constituencies with the boundaries of exist­ing administrative-territorial units (Table 3, Figures 10 and 11). The old system was based on the 1992 municipal and local authority boundaries. The reform of local self-government has led to a number of discrepancies between constituency and mu­nicipal boundaries. Under the old system, as many as twenty-four municipalities were divided into two or more constituencies. In nine of them, the division was necessary because the number of voters in them exceeded the size of the average electoral dis­trict by more than 25%, while in the others the division was unnecessary. Given the minimalist approach to constituency redistricting, the new system has abolished only three constituencies (Trbovlje, Šentrupert and Pesnica). The proposals of the expert group foresaw the abolition of most of the unnecessary municipal divi­sions. The first proposal would have entailed the abolition of eleven divisions, while the alternative proposal foresaw the abolition of as many as fourteen divisions. Under the old system, divisions occurred not only in municipalities but also in some settlements and local communities (Table 3, Figure 10). While the division of the four largest settlements (Ljubljana, Maribor, Celje and Kranj) is necessary because of their size, the division of others is completely unnecessary and pointless. In Ljublja­na, Maribor and Kranj, the old system even divided some of the city/borough/local districts. The new system has abolished only four divisions of settlements but retains all the divisions of city/borough/local districts. In contrast, both proposals of the ex­pert group foresaw the abolition of all unnecessary divisions of settlements and most among city/borough/local wards. Thus, under these proposals the electoral districts in Ljubljana (Figure 11) and Maribor would be more homogeneous, as they would cover only the areas of the urban settlements and the immediate neighbourhood. The results of the analysis show that the new system of constituencies is based on the old system with minimal changes. As a result, it retains most of its problematic and nonsensical outcomes. Does this mean that the new system is also incompatible with the Constitution? The answer to this question depends on the interpretation of the legislation and past decisions of the Constitutional Court. If we follow the interpretation of the advocates of minimum changes, then the new system is appropriate and compatible with the Constitution. If we follow the interpreta­tion of the advocates of more fundamental changes, the new system is unconstitutional. It is difficult to predict which interpretation the constitutional judges will follow in any future review of the constitutionality of the system. The proposals of the expert group demonstrate that it is possible to create constituencies that are comparable in size and at the same time geographically consistent, within the confines of the law. The results of the analysis show that both proposals of the expert group meet the legal criteria to a much greater extent than the new system of constituency. Why did members of Parliament decide to adopt the minimum changes? The reasons for this can be traced back to political calculation on the part of the government parties. The existing electoral system is relatively predictable. Especially the larger political parties with a longer tradition know very well in which constituencies their candidates are likely to be elected and in which they are not. By allocating their preferred candidates to ‘electable’ constituencies, party leaderships can decisively influence the allocation of parliamentary seats. Major changes in the system of constituencies would, at least temporarily, create a situation in which the electability of individual candidates would be much more uncertain. It is therefore not surprising that some parties have fought by all means for minimal changes to the system. Finally, it should be noted that constituencies were included in the electoral system in order to give voters a decisive influence on the allocation of parliamentary seats. Elections to date have shown that this is not the case. If politicians really wanted the electorate to have a decisive influence on the allocation of parliamentary seats, then it would make sense to abolish constituencies altogether, or to replace them with the in­troduction of preferential voting. This would prevent the electorate from being forced to vote for a candidate imposed by the leadership of a political party. ODNOS KMETOV DO VARSTVA NARAVE NA IZBRANIH OBMOCJIH SUHIH TRAVIŠC V VZHODNI SLOVENIJI Izvlecek Gorjanci, Haloze, Kum in Pohorje so štiri slovenska obmocja, na katerih se v okviru omrežja Natura 2000 skuša ohranjati evropsko pomembne habitatne tipe travišc ter njihove rastlinske in živalske vrste. Clanek predstavlja rezultate anketiranja o odnosu do varstva narave in obmocij Natura 2000 med kmeti, ki so na teh obmocjih v obdob­ju 2015–2020 aktivno sodelovali v LIFE projektu, namenjenem upravljanju in ohra­njanju suhih travišc. V primerjavi z drugimi prebivalci Slovenije so v projektu sode­lujoci kmetje bolj ozavešceni o Natura 2000 obmocjih in imajo do njih bolj pozitiven odnos, zaradi projekta pa je pomemben delež kmetov spremenil pogled na pomen ohranjanja vrstno pestrih travišc (58 %) oziroma na kmetijske prakse na njih (43 %). Kljucne besede: Natura 2000, suha travišca, kmetijstvo, ozavešcenost, regionalni ra­zvoj, Slovenija 1 INTRODUCTION This article presents the results of a survey of attitudes towards nature conservation and Natura 2000 sites among local farmers who previously participated actively in the LIFE project aimed at preserving dry grasslands in four Natura 2000 sites in Eastern Slovenia. In the survey we attempted to ascertain the extent to which the project in­fluenced changes in farmers’ attitudes towards dry grasslands and farming on them, and their opinion of Natura 2000 was further compared with the results of Slovenian public opinion polls. A positive attitude of the local population is crucial for the suc­cessful management of protected areas. Therefore, it is useful to evaluate the scope and approaches of nature conservation projects in this regard. In the selected Natura 2000 areas – Haloze, Pohorje, Kum and Gorjanci – in the period 2015–2020 the LIFE project Conservation and management of dry grasslands in Eastern Slovenia (Life to Grasslands) took place with the aim of long-term conser­vation of selected important European habitat types of grasslands and the plant and animal species dependent on them. The primary criterion for the selection of project areas was therefore the presence of dry grasslands, and in order to determine the results of the project, a study of the broader impacts of project activities, particularly their socioeconomic aspects, on the local population and economy was conducted. Part of this study also focused on identifying the positive and negative impacts of the project on farms that were involved in carrying out specific project activities. To this end they were surveyed in the final, fifth year of the project not only regarding their experience related to project participation, but also regarding their attitude towards nature conservation. The successfully implemented LIFE project was also the basis for the establishment of a new agriculture, environment and climate payments intervention (conservation of dry grasslands) (MKGP, 2021), which will include all four selected Natura 2000 sites in the next programming period. Although the Life to Grasslands project was primarily focused on nature conserva­tion campaigns, an important part of the project partners’ activities was also related to education and raising awareness of the local population about the importance of dry grasslands, Natura 2000 sites and nature conservation more generally. Our study is therefore based on the assumption that participating farmers in the project for conservation and management of dry grasslands show a higher level of awareness of Natura 2000 sites and have a more positive attitude towards them compared to other residents of Slovenia. 2 THEORETICAL AND METHODOLOGICAL FRAMEWORK OF THE STUDY The project and the study took place in four areas in the eastern part of Slovenia that are home to important European habitat types of dry grasslands, which are protected in the European Union under Natura 2000. Natura 2000 is the largest network of pro­tected areas in the world, whose aim is the protection of rare and endangered species as well as habitats and their long-term conservation, but which does not exclude human activities within them (The European environment…, 2019). There are a total of 355 Natura 2000 sites in Slovenia, covering 7,682 km2 or 37.9% of the country’s territory, the highest share in the European Union countries, where Natura 2000 averages 18.5% of a country’s territory (EEA, 2021). In the areas of Haloze, Kum and Gorjanci, the habitat type 6230 – Species-rich Nardus grasslands is protected under Natura 2000, and in Pohorje the habitat type 6210 – Semi-natural dry grasslands and scrubland fa­cies on calcareous substrates (Festuco-Brometalia). The presence of both important European habitat types is linked to extensive agriculture or grazing and is threatened on the one hand by intensification of agriculture (increased input of nutrients, mow­ing that is too frequent, additional sowing of mixed grasses, overgrazing, introduction of invasive species) or land use change (plowing of fields, construction of tourist and other infrastructure), and on the other hand due to the abandonment of meadows and pastures that used to be regularly mown or grazed, resulting in the land becom­ing overgrown (Calaciura, Spinelli, 2008; Debeljak et al., 2020; Galvánek, Janák, 2008). Fragmentation of grasslands hinders pollination as well as seed dispersal and cross-fertilization (Peterken, 2013), while intensification of agriculture leads to erosion of farmers’ knowledge about their grasslands. Mowing, hay spreading, turning and rak­ing have recently become fully mechanized (Zwitter, Rasran, 2022). Close observation of grasslands during the growing season greatly improves farmers’ understanding of grassland ecology, but young farmers have lost touch with grasslands and the changes caused by intensification are no longer properly perceived (Zwitter, Rasran, 2022). In Slovenia, each habitat type (6230 and 6210) is present in less than 2% of Natura 2000 sites, and grasslands occur mostly in higher lying areas, on diverse soils that are poor in nutrients and have developed on siliceous or calcareous rocks. In addition to maintaining biodiversity (herbs, orchids, butterflies, birds, grazing animals, etc.), grassland conservation is also important for erosion prevention, runoff regulation and many other ecosystem services (Calaciura, Spinelli, 2008; Debeljak et al., 2020; Galvánek, Janák, 2008). (Late) mowing and extensive grazing are recommended for the conservation of dry grasslands in Slovenia, but threats must also be prevented, among which intensive use, eutrophication, abandonment of grasslands and high-trunk orchards, overgrowth, fragmented ownership, erosion, pressures from other economic activities, and aging of the local population and its low level of environ­mental awareness have been identified (Debeljak et al., 2020; Life Conservation…, 2021). In general, grassland habitat types are among those in the worst condition in Slovenia. In 2019, according to experts, only 27% of grassland habitat types had a favorable conservation status (Petkovšek, 2020). As part of the Life to Grasslands project, efforts are being made to establish a fa­vorable condition and preserve selected dry grasslands, as well as convince farmers that farming and ensuring food security are possible while still protecting nature, for which cooperation between experts and local residents is essential (IRSNC, 2020). The Slovenian local population in protected areas usually perceives nature protection as a development barrier and not as an opportunity, and for the most part declines to play an active role in the development of their areas (Lampic, Mrak, 2007; Lampic, Mrak, 2008; Rodela, Torkar, 2011). However, an attractive landscape, which is shaped significantly by among other things the presence of species-rich grasslands, is a key factor in the choice of holiday location (Potocnik Slavic et al., 2016). Studies in other countries also show that environmental awareness does not always lead to active par­ticipation in solving environmental problems in protected areas (Dimitrakopoulos et al., 2010), so efforts are being made to increase the involvement of diverse stakehold­ers in the planning and management of protected areas, from experts in various fields to landowners, businesses, and entire local communities (Chan et al., 2007; Kam­phorst et al., 2017; Magda et al., 2015; Pietrzyk-Kaszynska et al., 2012). A positive attitude of the population is key to the successful functioning of nature conservation areas and can promote protection and sustainable management activities (Brankov et al., 2019). The most important precondition was the belief of the local population that living in a nature conservation area adds to the quality of life and that the activities have financial support (Nastran, Cernic Istenic, 2015; Šorgo et al., 2016). Table 1: Basic characteristics of project areas and farms surveyed. Number of settle­ments Area (km2) Population, 2020 Number of farms in the project Surveyed farms number share Gorjanci 27 75.9 3,829 18 12 66.7 Haloze 83 276.2 12,527 100 67 67.0 Kum 21 75.6 4,372 30 20 66.7 Pohorje 10 198.5 3,506 13 8 61.5 Total 141 626.2 24,234 161 107 66.5 Sources of data: SURS, 2020; Vintar Mally et al., 2020. The areas in which the project activities took place included 141 settlements with a total area of 626.2 km2 and 24,234 inhabitants (Table 1). In terms of area as well as in terms of population, the largest project area was Haloze (Figure 1). In this Pannonian region, low tertiary hills predominate, but the relief is extremely varied, so steeper slopes, especially in the western part, are an important limiting factor for agriculture. The eastern part of Haloze has traditionally been more oriented towards viticulture, while the higher and steeper western part has remained predominantly forested (Pak, 2012). Of all the project areas, Haloze has the largest share of overgrown agricultural land. As a result of this process, land use has changed significantly in recent decades and now more than half of the project area is covered by forests and about a quarter by grassland, while permanent crops (vineyards and orchards) cover only about 5% (MGKP, 2016). The project also included the central part of Gorjanci, a plateau and the easternmost Slovenian Dinaric Karst region (Perko, 1999). The central part of Gorjanci studied is relatively sparsely populated, and the area has greater than av­erage forest cover for Slovenian conditions (with forest covering about two-thirds of the area). Among agricultural areas, meadows predominate (around 17%), while fields and gardens account for less than 6%, and permanent crops around 5% (MGKP, 2016). The smallest area included is Kum, which is also the most densely populated. Kum is a Prealpine region, dominated by forest (71% of the area), amidst which sparse settlement consisting of isolated farms and hamlets has been preserved in the cleared areas. The surrounding valleys are significantly more attractive for settlement and the economy. Most of the area is karstic, so the central areas of Kum have no surface river network, and meadows predominate among agricultural land (ARSO, 2020; MGKP, 2016). The fourth project area covered only the western part of the Slovenian Pre­alpine region of Pohorje. It is the least populated (under 18 inhabitants per km2), and large swathes lie above 1000 meters in elevation, which significantly affects the conditions for agriculture, since highland climate features predominate in the high­est places. The most common form of settlement in the area is dispersed settlements and isolated farms (ARSO, 2020; Žiberna, 1999), and as much as 86% of the area is covered by forest, with occasional grassland areas scattered within (10% of the area) (MGKP, 2016). Figure 1: Project areas and survey response of farms. In all four project areas (hereinafter referred to as Haloze, Pohorje, Kum and Gor­janci for those parts of the Slovenian regions of the same name that were included in the project), we conducted a survey among all farms whose land was involved in the activities of the Life to Grasslands project over the previous four and a half years. Activities for the conservation of dry grasslands that took place on the land holdings of the participating farmers included removing overgrowth, preparing new mead­ows and pastures for extensive use, restoring or rejuvenating high-trunk orchards and similar. Local farmers and residents were thus not only exposed to education and awareness raising but were also actively involved in the project with their land and labor, and in return the project financed the purchase of agricultural equipment for their use and the assistance of third parties (e.g. for clearing brush from land) (Debel­jak et al., 2020). Due to the COVID-19 pandemic, the originally planned field survey was conducted entirely by telephone in the second half of May and the first half of June 2020, by a single interviewer, in order to ensure maximum uniformity in asking questions and comparability of answers. We invited all 161 farms who were actively involved in the project and for whom we had contact information to participate in the survey. Two-thirds of them, or 107 farms, agreed to take part, on whose behalf the farmers themselves (74.8%) or their closest family members who were familiar with the project activities responded (Table 1). Haloze has the greatest influence on the overall results, as more than 60% of farms that participated in the project and the survey are from this area. All farms surveyed had land included in the project in one of the project areas, although the location of the respondent’s residence and farm address may be outside the area (Figure 1). Due to the high response rate, the sample is representative of the entire set of farms that participated in the project. In addition to the attitude towards nature conservation and Natura 2000 sites, the survey also determined the degree of satisfaction with participation in the project and perception of the socioeconomic and environmental effects of project activities. This article does not give particular attention to the broader topic of the socioeconomic effects of the project, though it should be noted that these effects can also have a significant impact on the attitude of residents. In this particular case, we primarily investigated changes in farmers’ views on the importance of preserving species-rich grasslands and their farming methods as well as respondents’ views of Natura 2000. Two survey questions were identical to those in a national public opinion poll on Natura 2000 in Slovenia (Raziskava…, 2019), which enables a direct comparison of the results of both surveys. Although numerous studies on nature protection areas have been published, we found almost none that allowed direct comparison of results, while comparisons with national surveys in Slovenia are also limited by the fact that their results are not reported at the level of regions or smaller areas. The majority of respondents were men (74.8%), as heads of the agricultural hold­ings were predominantly male. It is important to note that the respondents are a soci­oeconomically diverse group. They include elderly farmers, new entrants to farming, subsistence farmers, farmers with registered supplementary activities, organic farm­ers and also those who are not interested in switching to organic farming at all. 3 RESULTS AND DISCUSSION The Life to Grasslands project took place in existing Natura 2000 areas in which the farmers surveyed cultivate at least part of their agricultural land. In the introductory question, we were therefore interested in whether respondents had already heard of Natura 2000. Of the 107 respondents, 95.3% stated that they had heard of it; only four respondents in Haloze and one in Kum answered in the negative. These results are extremely favorable, especially in comparison with the national public opinion survey (Raziskava…, 2019), according to which fewer than two-thirds of respondents (63.7%) knew of Natura 2000 in Slovenia. Given the intensive cooperation of project the statement, as this was 13.6 percentage points higher in the national survey, at the expense of the share of the undecided. The third statement asserted that farmers and forest owners in the Natura 2000 area could receive subsidies. In the project areas, 77% of respondents agreed with this, and only four disagreed. Farmers without this kind of knowledge or experience mostly opted for the response “I don’t know”. Compared to the national survey, a greater share of respondents in the project areas were convinced of the possibility of obtaining a subsidy for agriculture or forestry in the project areas – the difference was 18.9 percentage points. Almost a fifth of the Slovenian population was convinced that such subsidies could not be obtained. The differences in responses are under­standable, as farms have considerably more experience in obtaining subsidies than the general public. In the national survey, only 22.4% of respondents were engaged in farming, and 30.3% of respondents owned forest land. Table 2: Agreement with statements about Natura 2000 in Slovenia and in the project areas. Project areas (N=102) Slovenia (N=1007) Statement Agree Disagree Don’t know Agree Disagree Don’t know Natura 2000 signifies nature conservation. 88.2 5.9 5.9 97.1 2.1 0.8 Various human activities are allowed in Natura 2000. 48.0 29.4 22.5 48.7 43.0 8.3 If you have forest or if you farm in Natura 2000, you can receive subsidies 77.4 3.9 18.6 58.5 18.5 23.0 People living in Natura 2000 can take pride in that.* 85.3 5.9 8.8 79.5 10.4 10.1 Natura 2000 restricts farming. 31.4 59.8 8.8 68.0 23.0 9.0 Sources of data: Raziskava…, 2019; Survey, 2020. Note: *In the national public opinion survey the statement was: If I lived in a Natura 2000 area, I would be proud. A longitudinal study on social values of space and the environment in Slovenia (Hocevar et al., 2018) showed that in the period 2004–2018, support for the protection of natural areas increased in the country. As many as 81.4% of respondents believed that the state should consistently protect all areas of preserved nature, even in the face of lo­cal opposition. Moreover, in the same opinion poll in 2018, the population of Slovenia most often cited the proximity of nature (61.0%) and a clean (unpolluted) environment (55.6%) among the five most important features of a place to live, immediately after security with a low crime rate (77.5% of respondents), which shows how highly valued nature is in the country. The results of the national survey from 2019, in which almost 80% of respondents agreed with the statement that they would be proud to live in a Natura 2000 area, can also be understood in this context. Only a tenth saw no reason to be proud. In the project areas in 2020, respondents were even more convinced that inhabitants of Natura 2000 areas can take pride in this. All respondents in Pohorje and about 84% of respondents from other areas agreed with the statement. The greatest differences in the results of the two surveys could be seen regarding the statement that Natura 2000 restricts farming. Fewer than a third of the respond­ents in the project areas agreed with the statement, whereas more than two-thirds of the respondents in the national survey did (68.0%). Significant differences also ex­ist between project areas, as no one in Pohorje agreed with the statement, while in Haloze 36.5% of respondents regarded Natura 2000 as a restriction for agriculture. In general, project areas where the majority of the population live in the Natura 2000 area and are also engaged in farming have been shown to be more aware of the practi­cal consequences of nature protection measures, and surprisingly less aware of what Natura 2000 is primarily intended for. We also found that almost half of all respondents, thanks to this primarily na­ture conservation project, have begun to identify new development opportunities for agriculture in their area, from new farming practices to opportunities to engage in supplementary activities on farms and generate additional income. In this way, the project has clearly succeeded in linking environmental efforts in their local environ­ments with the search for opportunities for progress in the social and economic fields, which is also extremely important for achieving the long-term goals of sustainable development. 4 CONCLUSIONS A survey of the attitudes of participating farms in the LIFE project Life to Grass­lands, which took place between 2015 and 2020 in four dry grassland areas in Slove­nia, showed that respondents display a more positive attitude towards Natura 2000 sites compared to other Slovenian residents. To a greater extent, they expressed pride in living in Natura 2000 areas, and to a lesser extent they saw this form of nature conservation as an impediment to agriculture or other human activities, and were much more aware of the possibilities for financial support that they can receive for their agricultural activities. 95.3% of respondents were familiar with Natura 2000, significantly above the national average (63.7%). The only deviation is the finding that respondents from the project areas equated Natura 2000 with the conservation of nature to a somewhat lesser extent. This could also be the result of project activities aimed at raising awareness of economic opportunities in areas where special attention needs to be paid to nature conservation efforts. Nevertheless, we can confirm the ini­tial assumption that farmers participating in the project of conservation and manage­ment of dry grasslands are more aware of Natura 2000 sites than other inhabitants of Slovenia and have a more positive attitude towards them. We also found that the project helped to identify new development opportuni­ties for agriculture and significantly changed the view of farmers on the importance of preserving species-rich grasslands, especially concerning greater awareness and knowledge of plants, grassland diversity and the importance of maintaining dry grass­lands. However, we noticed a significant gap between the higher level of awareness of the farmers involved in the project and the actual implementation of new farming practices. In just under half of the participating farmers, the project also influenced changes in certain agricultural practices, most often in grazing and methods of mow­ing meadows. However, farmers have remained relatively reluctant to make more rad­ical changes to farming (e.g. switching to organic production), although many have shown readiness for them in principle and over time. As a result, additional education of farmers will be needed, as well as efforts from various stakeholders in the field of environmental protection and the promotion of sustainable agriculture, in order to transfer awareness into regular agricultural practices to a greater extent. The success of the project is reflected not only in the way of thinking of the sur­veyed farmers, but also in the new agriculture, environment and climate payments scheme as a “conservation of dry grasslands” intervention, which is included in the strategic plan of the upcoming programming period (MKGP, 2021). This is the only intervention in a scheme that is entirely results-oriented. Since it has already been tested in the field at the time of the project implementation, it is expected to be more successful than past agri-environment measures related to grasslands, which have been identified as highly ineffective (Kaligaric et al., 2019). In interpreting the results of the survey, it should be noted that the attitudes of the respondents during their lives are shaped by many factors and thus project activities could only influence them to a limited extent. Also, the farms involved in the project represented only a minority of all those who farm in the project areas, so their opin­ions cannot be generalized to the entire areas of Gorjanci, Haloze, Kum or Pohorje. Nevertheless, it is these farms that have gained knowledge and experience in the LIFE project that can be an important driving force in their local communities in the fu­ture. Through following established good practices, the effects of projects can spill over to other stakeholders (Magda et al., 2015) who have not participated actively in the project, and positive experiences with the project also open the door to other similar approaches. Acknowledgment The study (Vintar Mally et al., 2020) was carried out by a project team from the Depart­ment of Geography, Faculty of Arts, University of Ljubljana. The authors give special thanks to their colleague Doroteja Penko for meticulous administration of the survey. 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In: Nared, J., Perko, D., Razpotnik Viskovic, N. (eds.). Razvoj zavarovanih obmocij v Sloveniji. Ljubljana: Založba ZRC, pp. 187–192. SURS [Statistical Office of the Republic of Slovenia], 2020. SiStat database. URL: https://pxweb.stat.si/SiStat (accessed 16.07.2020). Šorgo, A., Špur, N., Škornik, S., 2016. Public attitudes and opinions as dimensions of efficient management with extensive meadows in Natura 2000 area. Journal of En­vironmental Management, 183, pp. 637–646. DOI: 10.1016/j.jenvman.2016.09.024. The European environment – state and outlook 2020. Knowledge for transition to a sustainable Europe. 2019. Luxembourg: Publications Office of the European Union. Vintar Mally, K., Bobovnik, N., Lampic, B., Kušar, S., 2020. Analiza socialno-eko­nomskih vplivov projektnih aktivnosti na lokalno gospodarstvo in prebivalstvo. Koncno porocilo. Ljubljana: Univerza v Ljubljani, Filozofska fakulteta, Oddelek za geografijo. Zwitter, Ž., Rasran, L., 2022. Species-rich grasslands in the Alps in the last millennium: Environmental history and historical ecology. Vienna: Austrian Academy of Scien­ces (in press). Žiberna, I., 1999. Strojna, Kozjak in Pohorje. In: Perko, D., Orožen Adamic, M. (eds.). Slovenija. Pokrajine in ljudje. Ljubljana: Mladinska knjiga, pp. 143–154. ODNOS KMETOV DO VARSTVA NARAVE NA IZBRANIH OBMOCJIH SUHIH TRAVIŠC V VZHODNI SLOVENIJI Povzetek V clanku so predstavljeni rezultati raziskave odnosa do varstva narave in obmocij Natura 2000 med kmeti, ki so v obdobju 2015–2020 sodelovali v LIFE projektu Life to grasslands. LIFE projekt je bil namenjen ohranjanju suhih travišc na štirih Natura 2000 obmocjih v vzhodni Sloveniji; Haloze, Pohorje, Kum in Gorjanci. V zadnjem letu trajanja projekta (2020) smo z anketiranjem sodelujocih kmetijskih gospodarstev skušali ugotoviti, v kolikšni meri je projekt vplival na spremembo stališc kmetov o suhih travišcih in kmetovanju na njih, njihovo mnenje o Naturi 2000 pa smo dodat­no primerjali z rezultati slovenskih javnomnenjskih raziskav. Ceprav je bil projekt primarno usmerjen v doseganje naravovarstvenih ciljev, se je pomemben del aktiv­nosti projektnih partnerjev navezoval tudi na izobraževanje in ozavešcanje lokalnega prebivalstva o pomenu suhih travišc, obmocij Natura 2000 in varstva narave nasploh. Posledicno je preucitev izhajala iz predpostavke, da bodo v projektu ohranjanja in upravljanja suhih travišc sodelujoci kmeti v primerjavi z drugimi prebivalci Slovenije izkazovali višjo stopnjo ozavešcenosti o obmocjih Natura 2000 in imeli do njih bolj pozitiven odnos. V preucevanih predelih Haloz, Kuma in Gorjancev se v okviru Nature 2000 varuje habitatni tip 6230 – vrstno bogata travišca s prevladujocim navadnim volkom (Nar­dus stricta), na Pohorju pa habitatni tip 6210 – polnaravna suha travišca in grmišcne faze na karbonatnih tleh (Festuco-Brometalia). Obstoj obeh evropsko pomembnih ha­bitatnih tipov je vezan na ekstenzivno kmetijstvo ali pašo in je v Evropi ogrožen na eni strani zaradi intenziviranja kmetijstva, na drugi strani pa zaradi opušcanja rabe v preteklosti košenih travnikov in pašnikov, kar vodi v zarašcanje. S projektom Life to grasslands so tako skušali predvsem vzpostavljati ugodno stanje in ohranjanje suhih travišc, vzporedno pa v praksi dokazovati, da je možno kmetovanje oziroma zagota­vljanje prehranske varnosti ob socasnem varovanju narave (IRSCN, 2020). Domace in tuje študije namrec kažejo, da sta odnos in vkljucenost lokalnih kmetov izjemnega pomena za uspešno upravljanje naravovarstvenih obmocij, cetudi okoljska ozavešce­nost kmetov oziroma lokalnih prebivalcev ne vodi nujno v njihovo aktivno udeležbo. Aktivnosti za ohranjanje suhih travišc, ki so potekale na zemljišcih sodelujocih kmetov, so vkljucevale odstranjevanje zarasti, urejanje novih travnikov in pašnikov za ekstenzivno rabo, obnavljanje ali pomlajevanje visokodebelnih sadovnjakov in podob­no. Lokalni kmeti in prebivalci torej niso bili deležni le ozavešcanja in izobraževanja, temvec so bili v projekt aktivno vkljuceni s svojimi zemljišci in opravljenimi urami dela, v zameno pa so se iz projekta financirali nakupi kmetijske opreme, ki so jo prejeli v upo­rabo, ter pomoc tretjih oseb (npr. za cišcenje zemljišc) (Debeljak et al., 2020). K sodelovanju v raziskavi o ucinkih projekta je bilo povabljenih vseh 161 kmetij­skih gospodarstev, ki so bila v projekt vkljucena z zemljišci na enem izmed projektnih obmocij, odzvali pa sta se dve tretjini oziroma 107 kmetijskih gospodarstev. Anketi­ranci so v primerjavi z drugimi prebivalci Slovenije izkazovali bolj pozitiven odnos do Natura 2000 obmocij in bili o njih tudi bolj ozavešceni. V vecji meri so izrazili obcutek ponosa na življenje v Natura 2000 obmocjih, v manjši meri so v tej obliki varstva narave videli oviro za kmetijstvo oziroma druge dejavnosti ter se bistveno bolje zave­dali možnosti financnih podpor, ki so jih lahko deležni za svoje kmetijske dejavnosti. Naturo 2000 je poznalo 95,3 % anketirancev, kar je bistveno nad nacionalnim povpre­cjem (63,7 %). Odstopa le ugotovitev, da so anketiranci s projektnih obmocij v Naturi 2000 v nekoliko manjši meri prepoznali varstvo narave. To bi lahko bila tudi posledica projektnih aktivnosti, ki so bile usmerjene v ozavešcanje gospodarskih priložnosti na obmocjih, kjer je treba posebej paziti na naravovarstvena prizadevanja. Projekt je pripomogel k prepoznavanju novih razvojnih priložnosti za kmetijstvo, od novih praks kmetovanja pa do možnosti ukvarjanja z dopolnilnimi dejavnostmi na kmetijah in ustvarjanja dodatnega zaslužka, kar je potrdila skoraj polovica vseh anketiranih. S tem je projekt ocitno uspel doseci, da so se okoljevarstvena prizadeva­nja v njihovih lokalnih okoljih povezala z iskanjem možnosti napredka na socialnem in ekonomskem podrocju, kar je izjemnega pomena tudi za doseganje dolgorocnih ciljev trajnostnega razvoja. Projekt je pomembno spremenil pogled kmetovalcev na pomen ohranjanja vrstno pestrih travišc, predvsem v smeri vecje ozavešcenosti in poznavanja rastlin, pestrosti travišc in pomembnosti vzdrževanja suhih travnikov. Rezultati kažejo na veliko vlogo ozavešcanja lokalnega prebivalstva o biotski pestrosti in pomenu njenega ohranjanja tudi v primerih, ko gre za podeželsko prebivalstvo, ki se tradicionalno ukvarja s kme­tijstvom, in od katerega bi pricakovali, da je že prek stika z naravo visoko ozavešceno o dobrih kmetijskih praksah, prilagojenih na specificne lokalne razmere. Zaznali smo tudi znaten razkorak med višjo stopnjo ozavešcenosti v projekt vkljucenih kmetov in njihovim dejanskim uresnicevanjem novih praks kmetovanja. Ceprav anketiranci cenijo pridobljeno znanje, so bili v bistveno manjši meri preprica­ni, da bo to vplivalo na njihov nacin kmetovanja. Le slaba polovica (43 %) sodelujocih kmetov je porocala, da je projekt vplival tudi na spremembo dolocenih kmetijskih praks, najveckrat pri paši in nacinu košnje travnikov. Do bolj korenitih sprememb kmetovanja (npr. preusmeritev v ekološko pridelavo) pa so bili kmetje še razmeroma zadržani, ceprav so mnogi na nacelni ravni in v daljšem casovnem obdobju zanje izkazali pripravljenost. Posledicno bodo potrebna še dodatna izobraževanja kmetov ter napori razlicnih deležnikov s podrocja varstva okolja in spodbujanja trajnostnega kmetijstva, da se bo ozavešcenost v vecji meri prenesla v redno kmetijsko prakso. UCITELJI GEOGRAFIJE IN MATEMATIKE V IZOBRAŽEVANJU NA DALJAVO V CASU PANDEMIJE COVIDA-19 V ALBANIJI Izvlecek Pandemija COVID-19 je povzrocila hitre spremembe v poklicni rutini uciteljev po vsem svetu. Raziskava, v katero je bila vkljucena vzorcna skupina 155 uciteljev geogra­fije in matematike v Albaniji v zacetnih obdobjih pandemije COVID-19, predstavlja oceno izzivov ucenja na daljavo. Rezultati raziskave so pokazali, da je pomanjkanje predhodne priprave bistveno vplivalo na izbiro in uporabo spletnih platform, primer­nih za ucenje na daljavo. Ucitelji se srecujejo s težavami na podrocju kartografske, graficne in simbolne semantike, manj pa s težavami na podrocju verbalne semantike. Na zacetku pandemije je poucevanje vecinoma potekalo preko aplikacije WhatsApp, nadalje s televizijskimi kanali RTSH, sledilo je poucevanje v okoljih Google Classro­om in Zoom. Ucitelji so potrebe po tehnološkem usposabljanju spopolnjevali s so­delovanjem s kolegi in samoizobraževanjem. V prispevku je poudarjeno, da ucitelji potrebujejo strokovno spopolnjevanje, zlasti na podrocju programskih sistemov in metod spletnega poucevanja. Kljucne besede: ucitelji geografije in matematike, poucevanje na daljavo, COVID-19, IKT, strokovno spopolnjevanje uciteljev 1 INTRODUCTION On March 8, 2020, the first two cases of COVID-19 coronavirus were confirmed in Albania, and on the same day the government closed schools for two weeks. In ad­dition, schools remained physically closed during this academic year and reopened only in September 2020, in 3 scenarios according to ASCAP (Pre-university Quality Assurance Agency), “Guidelines for the beginning of the academic year 2020-2021”. This reopening depended on the Albanian regions, the evolution of the number of in­fected and deaths due to the pandemic. In June 2020, the schools opened only for the final year students in high school, in the pre-university system and for the final year students in the bachelor’s and master’s degree system at the university. Pre-university education and teachers were in anything but a suitable state. Teach­ing and learning no longer had to be practised face-to-face, but digitally in online distance learning systems. Daniel (2020) states, “Most governments played catch-up to the exponential spread of COVID-19, so institutions had very little time to prepare for a remote-teaching regime.” Although the use of ICT in teaching was embedded in some university curricula, most teachers were not accustomed to distance teaching and the lack of adequate infrastructure in schools had left both them and students unprepared. Several difficulties arose at the beginning of online teaching, which were firmly linked to the conversion of subjects to the online format and the lack of meth­ods and pedagogical plans suitable for e-learning platforms. Teachers were confront­ed with certain situations, with little pedagogical or technical knowledge, that had to be implemented immediately. Often accompanied by stress, teachers had to adapt, increase collaboration among colleagues, and strictly follow the instructions given by local and central educational leaders. On the other hand, the MASR (Ministry of Education, Sports and Youth) provided maximum assistance in various instructions in schools, in accordance with the announcement of the Health Technical Committee. This Committee evaluated the progress of the pandemic and made recommendations for teaching. This was essential for the students and the pedagogical staff. There were no differences between primary and secondary schools. 1.1 Literature review In distance learning, the figure of the teacher is still indispensable, even though his function changes in comparison with traditional teaching. He/she changes from lec­turer to facilitator of the teaching process, contributing to the preparation of the teach­ing material and supervising the interactive activities. Students should be encouraged to have more autonomy, participation, and responsibility for their learning process (Elliot, 2008; Trentin, 2014). Daniel (2020) says: “Teachers should work with what they know. Giving full attention to reassuring students is more important than trying to learn new pedagogy or technology on the fly”. The WHO advised educators and students to use alternative learning due to the COVID -19 outbreak to mitigate the loss of instruction by providing a resource list from the World Bank’s Edtech teams to provide some online materials that could be used during the pandemic. The programme aimed to reduce learning loss and provide distance learning op­portunities while schools were closed (Alea et al., 2020). Currently, the forms of professional development for teachers according to Direc­tive No. 1 of 20.01.2017 (MASR, 2017) are internal professional development, train­ing, professional networks, counseling, long-term and short-term courses. Educa­tional institutions that deal with the professional development of teaching staff aim, among other things, to provide teachers, especially those in service, with the neces­sary adaptability to maximize the fulfillment of needs and their adaptation to the task of developing the competencies of today’s students. A sustainable element of today’s educational system is closely related to teacher training, both in terms of instrumental use of e-learning resources and various di­dactic-formative approaches related to their didactic continuity (Trentin, 2014). Since teachers nowadays, although they are constantly evolving, use traditional teaching methods (Chu et al., 2016), the need for modern professional development (Brysch, Boehm, 2014) arises with the use of technology in teaching and learning. Moreover, this professional development becomes an absolute priority (Chu et al., 2016), espe­cially in the current learning situation under pandemic conditions. The crucial role of traditional learning is by no means underestimated, even though we now have many successful e-learning methods (Brysch, Boehm, 2014; Dash et al., 2012) in various areas of mathematics and other sciences. Technology also helps in online professional development where space and time can be fully manipulated by us, according to one’s own financial costs. When it comes to integrating web technologies into didactic practice, one cannot ignore the gap that exists between students’ personal and daily use of these technolo­gies and the way teachers present them for research activities (Trentin, 2014). Moreo­ver, teachers tend to present a use based on the methods and practices of “convention­al” study and linked to the old teaching schemes, while instead it would be necessary to use new methodological presentations inspired by the so-called e-pedagogy (Elliot, 2008), able to fully exploit the potential of communication technologies both for so­cial interaction and for access to knowledge. Information technology is one of the key skills needed by today’s teachers, as schol­arly research and information organization are greatly supported by technology, e.g., in media creation and use (Boehm et al., 2012; Safar, Alkhezzi, 2013), digital storytell­ing (Chu et al., 2016), and especially e-learning platforms, where various software can be tightly integrated with their respective subjects. There is a growing trend of tech­nology integration in the classroom that requires teachers to incorporate technology into their pedagogy. In particular, the Technological Pedagogical Content Knowledge (TPACK) model proposed by Mishra and Koehler (2006) is a frame of reference that helps teachers, including geography teachers (Trigueros, 2018), integrate technology into their teaching. The positive side is that scientific research has given teachers the ability and confi­dence to teach using technology, but on the other hand, there are teachers who have difficulty implementing it in the classroom and even have little confidence in it (Chu et al., 2016; Kopcha, 2012). The technological infrastructure must be reliable and nec­essary to serve teachers’ purposes. If using the technology is time consuming or does not contribute to the learning process, then this will discourage teachers from using it (Kopcha 2012). The availability of a technological infrastructure both at school and at home increases teachers’ confidence in using ICT professionally (Chu et al., 2016). If teachers do not feel comfortable using technological tools or fear they are not skilled enough to learn how to use ICT, then they are less likely to incorporate technology into their teaching and even affect the little interaction students have with technology (Chu et al., 2016). However, the tools need to be carefully crafted: Content, methods for delivering content, and methods for teaching and learning, as well as methods for assessing student progress (Ohlin, 2019). There are difficulties in changing the way of teaching (Trentin, 2014): irregular use of the network in interaction with students; inability to enter into the logic of CMC (computer-mediated communication); lack of use of technologies. In general, teachers at all school levels indicated that their experience with online instruction was moderate to low (Lucisano et al., 2020). Teachers should provide high-quality profes­sional development in flexible, effective formats that address their individual needs. 2 METHODOLOGY The purpose of this study is to identify and analyze the challenges and needs of in-service teachers of geography and mathematics during the pandemic outbreak. Firstly a literature review on online learning was made and secondly a research with the participation of 155 geography and mathematics teachers working in several schools in Albania, both in rural and urban areas, was conducted. The applied aspect of the study is based on a survey. The analyzes were carried out in two dimensions: qual­itative and quantitative. The questionnaire was distributed randomly based on the snowball technique. The instrument used for data collection is a Google Forms type questionnaire and consists of open and closed questions with predefined answers to allow qualitative analysis. The teachers who participated in this study were informed about the purpose of the study. In addition, ethical aspects were considered in the use of the questionnaires, ensuring that anonymity, confidentiality, and fair treatment of the participants were maintained. The questionnaire focused on: defining the difficul­ties encountered; the possibility of using online learning; the most common forms of communication with students before and at the beginning of the pandemic; the assessment of common needs as part of their professional development. Some ques­tions used the Likert scale, which allowed the observation and analysis of frequencies of the variables, the analysis of cross-tabulations, especially between the variables and the teachers’ work experience. Other analyzes focused on correlations and tests per­formed with the SPSS version 20 program. It is practical to apply the method of opin­ion analysis to collect important qualitative data (Albanese, 2020). Sentiment analysis was used to identify the platforms and applications most used by teachers. 3 RESULTS AND DISCUSSIONS The survey was completed by 155 in-service teachers. A look at the demographic profile of the respondents shows that most of the respondents were female (117, i.e. 75.5%) and 38 (24.5%) were male. 51% of the teachers worked in rural areas and 49% in urban areas. In the sample group, 145 (93.5%) of the teachers worked in public schools and 10 (6.5%) worked in private schools. Evaluating the highest diploma obtained by the survey participants and the professional categories, we find that teachers with university diplomas of 4 years of study (97 teachers) dominate, of which 73 (75.2%) are subject teachers and highly qualified teachers. In-service teachers are graded based on their teaching experience. Each grade is reached by passing an examination, which can be taken after a certain length of professional experience. Teachers with less than 5 years of professional experience are classified as unclassified teachers; those with 5 to 10 years of professional experience are classified as qualified teachers; 10-20 years of professional experience are qualified specialist teachers; and those with more than 20 belong to the category of highly qualified teachers. In short, a considerable number of teachers with considerable teaching experience participated in the study. The second group of teachers includes those with bachelor’s and MPM (Profes­sional Master for Geography Teachers) degrees with 64 teachers, 67.45% of whom have less than 5 years of professional experience. According to the professional years of teachers, the dominance of the specialist teachers can be seen (62 teachers, 40%), followed by unclassified teachers (39 teach­ers, 25.2%) of the whole sample. Highly qualified teachers account for 16.8%. Table 1: Crosstabulation between: “Which is your highest diploma” and “Which professional categories do you own”. Which professional categories do you own? Total Unclassi­fied teacher Quali­fied teacher Spe­cialist teacher Highly qualified teacher Which is your highest diplo­ma? Teacher Diploma 4 years studies Count 6 18 52 21 97 % 6.2% 18.6% 53.6% 21.6% 100.0% Teacher diploma Bachelor and MPM Count 31 9 2 4 46 % 67.4% 19.6% 4.3% 8.7% 100.0% Doctorate Count 1 0 4 1 6 % 16.7% 0.0% 66.7% 16.7% 100.0% Other Count 1 1 4 0 6 % 16.7% 16.7% 66.7% 0.0% 100.0% Total Count 39 28 62 26 155 % 25.2% 18.1% 40.0% 16.8% 100.0% 108 teachers (69.7%) are teachers in the Geography profile and 47 teachers (30.3%) are teachers in the Mathematics profile; 83 teachers (53.5%) teach in the AMU (Low Middle Education) system, where the age of students is 11–15; 53 teachers (34.2%) teach in the AML (High Middle Education) system, where the age of students is 11–18; and 19 teachers teach in common schools where the age of students is 11–18. The results of the study show that most teachers did not engage in the development of distance education before the COVID-19 pandemic (65%) and the rest used ap­plications according to their specific needs (Figure 1). Figure 1: Teachers and how they used online learning before the COVID-19 pandemic outbreak (number of responses). Teachers were asked to name 2 of the platforms or applications they used most fre­quently during the pandemic (Figure 2). Using the opinion mining analysis technique as software in semantic studies, a predominance of the words WhatsApp (155 times, i.e. 100%), RTSH TV channels (84 times, 54.2%), and Google Classroom, Google Meet (65 times, 41.9%), Zoom (44 times, 28.4%), etc. was found. Figure 2: The platforms or applications most commonly used by teachers during the pandemic. It was found that some of the solutions are part of UNESCO 2020’s recommended solutions for distance education during the pandemic. A paired sample t-test (Table 2) was estimated for two questions: A) How pre­pared do you feel for digital work in distance education? The variables were: 1) none, 2) a little, 3) not well, 4) well, 5) very well; and B) How was digital learning used before the pandemic? 1) Applications 2) Platforms 3) Use of applications and platforms was not required 4) Required but not used. Null hypothesis (H0): there is no significant difference between the means of ques­tion A and B. The difference in means is equal to 0. The way how the teachers have performed digital learning before pandemic does not affect how prepared they feel to work in distance teaching. Alternative Hypothesis (Ha): There is a significant difference between the means of questions A and B, and the difference in the means is not equal to 0. The way teachers have conducted digital learning before the pandemic has an impact on how prepared they feel for working in distance teaching. Table 2: Paired sample t-test. Paired Differences t df Sig. (2-tailed) Mean Std. Devi­ation Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 Q A. Which has been the way you have teaching in distance learn­ing before pandemic? Q B. How prepared do you feel to work digitally in distance teaching? -1.355 1.440 .116 -1.583 -1.126 -11.711 154 .000 Interpretation of test results: Observed t-value = -11.711; Statistical significance (p-value) = 0.0005. A p-value of (0.0005) < 0.05 means that the null hypothesis is rejected and the alternative hypothesis is accepted. The test results show that there is a significant difference between the mean scores of questions A and B. The results indicate that how teachers used digital learning prior to the pandemic has an impact on how prepared they feel to work in distance teaching during the pandemic. One-sample t-test (Table 3). Question: how prepared do you feel for digital work in distance teaching? 1) none 2) a little 3) not well 4) well 5) very well. Pre-deter­mined test score: t=4. Null hypothesis (H0): population mean is significantly equal to 4. Teachers feel well prepared to work digitally in distance teaching. Alternative hypothesis (Ha): The population mean is significantly different from 4. Teachers do not feel well prepared to work digitally in distance learning. Table 3: One-sample t-test. Test Value = 4 t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference Lower Upper How prepared do you feel for digital work in distance teaching? -2.739 154 .007 -.155 -.27 -.04 Interpretation of test results: T-criterion 1.64; observed t-value = -2.739. Statistical significance (p-value) = 0.007. A p-value of (0.007) < 0.05 means that the null hypoth­esis is rejected and the alternative hypothesis is accepted. In summary, the test shows that the population mean is statistically significantly different from 4. Specifically, the results show that teachers do not feel well prepared for digital work in distance teaching. Teachers show a great interest in their professional development by considering training in technological teaching and, in particular, specialised technological train­ing in 91.6% of the responses. The rest of the responses correspond to: I have no comment 5.8% and I disagree 2.6%. Teachers are aware that technological training is necessary for their work, especially in the conditions of theCOVID-19 pandemic . Teachers were asked how they should develop digital skills in their work at the beginning of the pandemic by selecting two options from the 5 offered: I do not de­velop, communication with colleagues, self-training through tutorials, participation in training provided by others (Figure 3). The answers showed that teachers prefer to develop their digital skills in their work mainly through self-training (118 of them), communication with colleagues (103 of them) and, in addition, through trainings offered by other trainers (75 of them). In Albania, self-directed learning served as a form of professional development for teachers. Lucisano et al. (2020) found in their study that collaboration with colleagues was considered effective – both for sharing teaching practices and for realizing interdisciplinary didactic pathways. Dhimitri et al. (2021), in their study conducted in 2020 and during a pandemic, estimated that self-directed learning enriches teachers with the competence to learn by gaining knowledge, attitudes, values for their professional and personal growth. They saw that teachers themselves were educated on issues of learning on platforms, online teaching, use of ICT software and hardware, Google classrooms, etc. In the didactic dimension, they preferred topics such as online teaching and learning techniques, assessment methods, ethical issues, competency-based learning, didactic use of the globe, maps, and so on. Meanwhile, Chang (2020) points out, “While online learning becomes prevalent, it also provides opportunities for teachers’ professional develop­ment, such as the ability to observe each other’s lessons through recorded video con­ferencing functionalities”. Figure 3: Teachers and development of digital skills in teachers’ work in the first period of the COVID-19 pandemic (number of responses). Teachers were asked about the support they need regarding distance education. Their answers showed that 51.6% of them asked for support in software applications (programmes), 37.4% asked for support in online learning methods, and the rest asked for technical support (34.2%) In regard to the question “which semiotic systems have you encountered more dif­ficulties with online services” teachers had to name two main difficulties for them. The answers showed that 95 (61.35%) teachers had difficulties with cartographic uses, 86 (55.5%) of them had difficulties with pictorial representations and 88 (56.8%) teachers had difficulties with notes through symbols e.g. equation, meteorological symbols etc. Figure 4: Teachers and semiotic systems and the most frequently encountered difficulties in online services (number of responses). Table 4 is a correlation matrix that shows the correlation coefficients between differ­ent variables, the strength and the direction of this relationship. It shows that the cor­relations are statistically significant at p < 0.01. The correlations between variables are positive. They appear as moderate relationship (Salkind, 2000) especially in the cases where students interact with digital teaching lessons and learning and the estimation of the digital level of your school and moreover in digital work in distance education. A weak relationship exists between student interaction with digital lessons and learn­ing and the platforms that allow teachers to decide and use the didactic activities. The most effective practice in response to teaching in an online environment is directed at students. Often students can become isolated in a virtual environment and feel helpless when challenged in a class. They need support and they need to feel that there is a hu­man being present behind the computer screen (Schultz, DeMersb, 2022). Table 4: Pearson correlations among issues on remote teaching and learning in the COVID-19 pandemic. How do you estimate the digital level of your school? How pre­pared do you feel to work digitally in distance teaching? How does the platform allow you to find and use the didactic activities? How do the students interact with digital lessons and learning? How do you estimate the digital level of your school? Pearson Correlation 1 .441** .522** .509** Sig. (2-tailed) .000 .000 .000 N 155 155 155 155 How prepared do you feel to work digitally in distance teaching? Pearson Correlation .441** 1 .413** .430** Sig. (2-tailed) .000 .000 .000 N 155 155 155 155 How does the platform allow you to find and use the didactic activities? Pearson Correlation .522** .413** 1 .399** Sig. (2-tailed) .000 .000 .000 N 155 155 155 155 How do the students interact with digital lessons and learning? Pearson Correlation .509** .430** .399** 1 Sig. (2-tailed) .000 .000 .000 N 155 155 155 155 **Correlation is significant at the 0.01 level (2-tailed). 4 CONCLUSIONS The purpose of this study was to provide a general snapshot of geography and mathe­matics teachers’ online learning experiences during the COVID-19 outbreak. Compli­cations in coping with the pandemic also occurred in pre-university education. How­ever, teachers never stopped working to ensure children’s right to education, albeit under unusual circumstances and with immediate change. Decision makers turned their attention in this direction by directing, planning, and aligning educational insti­tutions. Although the current curriculum was introduced in 2015, in which teachers’ digital literacy is a key part, the study shows that most teachers did not fully possess this literacy when the pandemic broke out. The lack of digital literacy among teachers is also evident in the applications used during the pandemic. The use of applications that are not intended for didactic purposes is striking. At this stage, the use of low synchronous learning is striking. The results of the paired samples t-test show that the nature of teaching during the pandemic is strongly dependent on pre-pandemic teacher preparation. The results of the one sample t-test show that teachers do not feel adequately prepared for distance learning. They tend to show a great need in their professional development in terms of technology training in teaching and especially in professional technology training. However, the study showed that teachers could respond professionally. Although they were instructed or often autonomous, they were able to respond to their needs by self-training, interacting with colleagues, or through multiple tutorials. Interaction among teachers to respond to their professional needs became increasingly evident. We can distinguish different software, platforms or applications suitable for dis­tance learning, such as Mathematica, Geogebra, Google Earth, Mind Mapper, Google Workspace for Education, Excalidraw virtual whiteboard, ZoomTM, virtual tours to assist in field research, etc. However, virtual reality fieldwork will not be able to rep­licate the senses of touch and smell, which are important experiences of fieldwork (Chang, 2020). Our teachers have not yet overcome the technocentric stage. Many theoretical models have been developed that aim to evaluate the readiness to use technology through the acceptance and use of technology in different areas of life. TAM (Tech­nology Acceptance Model) is one of them. After several modifications, this model was proposed by Davis (1989), which evaluates perceived usefulness (PU) and perceived ease of use (PE) to predict teachers’ attitudes toward technology use (Wang, 2021). The model assumes that when users are presented with a modern technology, a num­ber of factors influence users’ decisions about how and when they will use a modern technology (Silva, 2015). Technology was an important component of professional practise during the COV­ID-19 pandemic. Under post-pandemic conditions and the school’s return to pre-pan­demic learning conditions for the 2021-2022 school year, but due to health limitations, the role of technology is no longer the same. It is no longer mandatory or necessary for teachers as it was for distance learning. However, we propose the use of a large-scale ap­plication TAM for teachers, administrators, etc. as individual adoption and use of inno­vative technologies in the work context. Teachers’ desire and professional commitment to technology, based on the perceived usefulness and perceived ease of use of the TAM technology, would provide the technological foundation for the didactics of geography, mathematics, and other subjects. Although this model may be influenced by a number of personal factors, such as: socioeconomic, technical, etc., we propose that it be inte­grated into the professional aspects of the teacher’s work. Professional networks are part of teachers’ CPD. They can provide individuals, ex­clusively teachers, with a comprehensive awareness of how to use and integrate tech­nology into the teaching process. Through this study, more ideas and opportunities of professional networks that need to address digital literacy are created. In addition, the study proposes professional development trainings and seminars on various peda­gogical approaches and methods that are appropriate for online learning. By strength­ening the foundations of technology as a tool for providing didactic solutions, we can create a desire for its professional use in schools. Because the study was conducted during COVID-19, the available time and scope were limited. We propose to conduct future studies involving a larger group of teach­ers-in-training and teachers of other subjects at the country level. Acknowledgments This study was conducted at the initiative of the authors, experts in geography and math­ematics education. It is not supported by any funding source. The authors would like to thank the teachers who participated in the survey. References Albanese, V., 2020. La sentiment analysis a supporto della ricerca geografica. Un esem­pio applicativo per il turismo salentino. URL: https://www.researchgate.net/publi­ cation/ 345179579_La_sentiment_analysis_a_supporto_della_ricerca_geografica_Un_esempio_applicativo_per_il_turismo_salentino/stats (accessed 21.07.2021). Alea, L., Fabrea, M., Roldan, R., Farooqi, A., 2020. Teachers’ Covid-19 awareness, dis­tance learning education experiences and perceptions towards institutional readi­ness and challenges. International Journal of Learning, Teaching and Educational Research. 19, 6, pp. 127–144. URL: 10.26803/ijlter.19.6.8. ASCAP, 2020. URL: https://www.ascap.edu.al/wp-content/uploads/2020/09/Udhe­ zuesi-per-fillimin-e-vitit-shkollor-2020-2021.pdf (accessed 25.07.2021). Boehm, R. G., Brysch, C. P., Mohan, A., Backler, A., 2012. A new pathway: Video-based professional development in geography. Journal of Geography, 11, 2, pp. 41–53. Brysch, C. P., Boehm, R. G., 2014. Online professional development in geography: the learning cluster method and teacher leader. European Journal of Geography, 5, 1, pp. 62–69. Chang, Ch., 2020. Teaching and learning geography in pandemic and post-pandem­ic realities. J-READING, Journal of research and didactics in geography, 2, 9, pp. 31–39. URL: http://j-reading.org/index.php/geography/article/view/267/214 (ac­cessed 02.01.2022). Chu, S., Reynolds, R., Notari, M., Taveres, N., Lee, C., 2016. 21st century skills develop­ment through inquiry based learning from theory to practice. Springer Science. Daniel, S. J., 2020. Education and the COVID-19 pandemic. Prospects, 49, pp. 91–96. URL: DOI: 10.1007/ s11125-020-09464-3. Dash, S., de Kramer, R. M., O’Dwyer, L. M., Masters, J., Russell, M., 2012. Impact of online professional development on teacher quality and student achievement in fifth grade mathematics. Journal of Research on Technology in Education, 45, 1, pp. 1–26. Davis, F. D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of infor­mation technology. MIS Quarterly, 13, 3, pp. 319–340. DOI: 10.2307/249008. Dhimitri, J., Karaguni, M., Bardhoshi S., 2021. Self-directed learning dimensions and in-service geography teachers in Albania. Journal of Educational Research, 3, 5-6, pp. 30–38. URL: https://eprints.unite.edu.mk/848/1/EDUCATION%202021-30-38.pdf (accessed 02.01.2022). Elliot, 2008. E-pedagogy: does e-learning require a new approach to teaching and learning? URL: http://www.scribd.com/doc/932164/E-Pedagogy (24.07.2021). Kopcha, T. J., 2012. Teachers’ perceptions of the barriers to technology integration and 20 practices with technology under situated professional development. Com­puters & Education, 59, 4, pp. 1109–1121. Lucisano, P., Girelli, C., Becilacqua A., Virdia, S., 2020. Didattica in emergenza du­rante la pandemia Covid-19. Uno sguardo all’esperienza locale e nazionale degli insegnanti. RicercAzione, Research and innovation in Education, 12, 2, pp. 23–46 DOI: 10.32076/RA12 208. MASR, 2017, Guideline No. 1, date 20.01.2017. URL: https://ascap.edu.al/Biblioteka/Zhvilli mi%20Profesional%20i%20M%C3%ABsuesit/Udhezimi%20zhvillimi%20profesional%20-%20Janar%202017.pdf (accessed 24.07.2021). Mishra, P., Koehler, M. J., 2006. Technological pedagogical content knowledge: A new framework for teacher knowledge. Teachers College Record, 108, 6, pp. 1017–1054. Ohlin, C., 2019. Information and communication technology in a global world: Teachers’ perceptions of continuing professional development. Research in Social Sciences and Technology, 4, 2, pp. 41–57. Safar, A. H., Alkhezzi, F. A., 2013. Beyond computer literacy: Technology integration and curriculum transformation. College Student Journal. 47, 4, pp. 614–626. Salkind, J. N., 2000. Statistics for people who (think they) hate statistics. Sage publica­tion. Schultz, R., DeMersb, M., 2020. Transitioning from Emergency Remote Learning to Deep Online Learning Experiences in Geography Education. Journal of Geogra­phy, 119, 5, pp. 142–146. DOI: 10.1080/00221341.2020.1813791. Silva, P., 2015. Davis’ Technology Acceptance Model (TAM) (1989). URL: https://www.igi-global.com/viewtitlesample.aspx?id=127133&ptid=120225&t=Davis%27%20Technology%20Acceptance%20Model%20(TAM)%20(1989)&isxn=978146668 (accessed 03.01.2022). Trentin, G., 2014. Formazione degli insegnanti: tra formale, informale e digitale. In M.E. Cadeddu (a cura di) Il CNR e la Scuola. Roma: Edizioni CNR. Trigueros, I., 2018. New learning of geography with technology: the TPACK model. European Journal of Geography, 9, 1, pp. 38–48. UNESCO, 2020. Distance learning solutions, URL: https://en.unesco.org/covid19/education response/solutions (accessed 30.07.2021). Wang, Y., 2021. In-service teachers’ perceptions of technology integration and prac­tices in a Japanese university context, The JALT CALL Journal, 17, 1, pp. 45–71. DOI: 10.29 140/jaltcall.v17n1.377. UCITELJI GEOGRAFIJE IN MATEMATIKE V IZOBRAŽEVANJU NA DALJAVO V CASU PANDEMIJE COVIDA-19 V ALBANIJI Povzetek Albanija je 8. marca 2020 potrdila prva dva primera koronavirusa COVID-19, še isti dan pa je vlada zaprla šole za dva tedna. Šole so v tem šolskem letu ostale fizicno za­prte, ponovno pa so jih odprli septembra 2020, in sicer po treh scenarijih v skladu z ASCAP 2020, »Smernicami za zacetek šolskega leta 2020–2021«. Ponovno odprtje je bilo odvisno od števila okuženih in žrtev v razlicnih regijah Albanije. Preduniverzite­tno izobraževanje in zlasti ucitelji so se znašli v povsem neprimernih razmerah. Poucevanje in ucenje je bilo treba nemudoma prilagoditi digitalnemu nacinu v spletnih sistemih ucenja na daljavo. Že na zacetku spletnega poucevanja in ucenja so se pokazale številne težave. Predmeti so se izvajali v spletni obliki, pri tem pa niso bile uporabljene metodologije, primerne za platforme e-ucenja. Ucitelji so se pogosto soocali s stresom, saj so se morali sami usposabljati, povecati sodelovanje s sodelavci ter dosledno upoštevati navodila lokalnih in osrednjih vodij izobraževanja. Didakticna raba informacijske tehnologije je ena od kljucnih kompetenc današnjih uciteljev. Od uciteljev se vse bolj pricakuje, da tehnologijo vkljucijo v svoje pouce­vanje. Zlasti model tehnološko-pedagoškega vsebinskega znanja (TPACK), ki sta ga predlagala Mishra in Koehler (2006), je referencni okvir za pomoc uciteljem (Isabel 2018) pri vkljucevanju tehnologije v pouk. Namen raziskave je bil identificirati in analizirati izzive in potrebe uciteljev geo­grafije in matematike v casu nastopa pandemije. V njej je sodelovalo 155 uciteljev, zaposlenih na razlicnih šolah v Albaniji. Aplikativni vidik študije temelji na izvedeni anketi. Analize so bile opravljene v dveh metodoloških razsežnostih: kvalitativni in kvantitativni. Orodje, uporabljeno za zbiranje podatkov, je vprašalnik tipa Google for­ms, ki je sestavljen iz vprašanj zaprtega in odprtega tipa, kar omogoca tudi kvalitativ­no analizo. Namen vprašalnika je bil: opredeliti težave, s katerimi se srecujejo ucitelji; možnost uporabe spletnega ucenja; najpogostejše oblike komunikacije z ucenci pred zacetkom pandemije in po njem; oceniti najpogostejše potrebe v okviru njihovega strokovnega razvoja. Pogled v demografski profil anketirancev kaže, da je bila med 155 udeleženci raziskave vecina žensk, in sicer 117 (75,5 %), 38 (24,5 %) pa moških. 51 % uciteljev je delalo na podeželju, 49 % pa v mestih. 145 (93,5 %) uciteljev je delalo v javnih, 10 (6,5 %) pa v zasebnih šolah. 56,8 % uciteljev je uvršcenih med ucitelje specialiste in visokokvalificirane ucitelje, saj imajo vec kot 10 let delovnih izkušenj kot ucitelji. 108 anketirancev (69,7 %) je uciteljev geografije, 47 uciteljev (30,3 %) pa je uciteljev matematike. Vecina uciteljev se pred pandemijo ni posvecala poucevanju na daljavo (65 %), ostali pa so uporabljali aplikacije glede na svoje specificne potrebe. Ucitelji so bili naprošeni, da izpostavijo dve od platform ali aplikacij, ki so jih med pandemijo naj­bolj uporabljali. S tehniko analize “Opinion mining” kot programske opreme v se­manticnih študijah je bila ugotovljena prevlada besed WhatsApp (155-krat), RTSH TV kanali (84-krat), Google Classroom in Google Meet (65-krat), Zoom (44-krat) itd. Ucitelji (91,6 % odgovorov) kažejo veliko zanimanje za svoj strokovni razvoj v zve­zi s tehnološkim usposabljanjem pri pouku in še posebej za predmetno tehnološko usposabljanje. Odgovori so pokazali, da ucitelji pri svojem delu najveckrat razvijajo digitalne spretnosti s pomocjo samoizobraževanja (118) in komunikacije med kolegi (103), pa tudi z usposabljanji, ki jih izvajajo drugi (75). (Prevod Arsim Ejupi) VPLIV BLAŽA KOCENA (BLASIUSA KOZENNA) IN NJEGOVEGA GEOGRAFSKEGA ATLASA NA RAZVOJ HRVAŠKE ŠOLSKE KARTOGRAFIJE Izvlecek V prispevku analiziramo pomen Kocenovih atlasov za razvoj hrvaške šolske karto­grafije. S primerjavo nemških in hrvaških izdaj v obdobju med letoma 1887 in 1943 spremljamo razvoj na podrocju tiskanja zemljevidov, kartografskih tehnik, jezikov­nih redakcij toponimije in vkljucevanja tematskih kart ter vpliv politicnega diskurza (nemški centralizem proti slovanskim nacionalizmom) na geografski obseg in vsebi­no zemljevidov, ki so jih uporabljali v izobraževalnem procesu. Kljucne besede: hrvaška šolska kartografija, poucevanje geografije, nacionalna iden­titeta, Blaž Kocen (Blasius Kozenn) 1 INTRODUCTION Blaž Kocen, also known as Blasius Kozenn (1821, Hotunje near Ponikva – 1871, Vien­na) is one of the most prominent Slovene geographers and cartographers who worked at the turbulent times marked by the modernization of education system in the coun­tries of the Austrian Empire, i.e. Austro-Hungarian Monarchy (since 1867). Initially trained as a priest and then educated in mathematics, physic, and natural sciences, he distinguished himself in teaching of geography, advocating the use of more advanced teaching tools. In order to improve teaching process Kocen wrote several geography textbooks and compiled numerous wall and table maps. No doubt, Kocen’s crowning accomplishment was his school geographical atlas. After its first edition in 1861, Kocen’s atlas continued to improve and adapt to new historical circumstances even after author’s untimely death, leaving a lasting mark in the school cartography of all Central European countries. Based on Kocen’s template, adapted editions soon followed published in Cro­atian, Czech, Hungarian and Polish language, making it the most important geographi­cal school atlas within Austro-Hungary. Since then, atlas that saw at least 278 editions on six languages, still represents a synonym for a high quality school atlas. When the first edition of Kocen’s Geographischer Schul-Atlas für die Gymnasien, Real- und Handels-Schulen appeared in 1861 as the first school geographical atlas pre­pared for the use in countries of the Austrian Empire, it was a scientific and didactic sensation. For the first time, teachers of geography received a manual in the form of an atlas that was harmonized with the curriculum of the countries of the Empire. This was also true for Croatia, where the Croatian language became the official language in that same year, and the curriculum and all textbooks had to be adapted to this new situation. Until 1861, the teaching of geography as well as the development of Croatian cartography in the local language was prevented by the use of German as the official language. In fact, except for the short period of 1847–1853, teaching, as well as all manuals, including maps, were exclusively in German. Reconvened in 1861, the Croatian Parliament reintroduced the use of Croatian as the official language in Croatia and Slavonia (however, not in the territories of the Military Frontier, Dal­matia and Istria!), and brought a series of modernization reforms that had a strong impact on education, science and culture. It adopted laws on elementary and second­ary schools, as well as on teacher training colleges. The matters discussed were further reconstruction of the University, the establishment of the Yugoslav Academy of Arts and Sciences, and the organizational structure of the National Museum, founded in 1846. Such intensive legislative work of the Parliament laid the foundations for the modernization of local administration and judiciary, as well as for the educational reorganization of Croatia. Particularly important was a decision on the independence and territorial integrity of the Triune Kingdom, that is to say, the entitlement of Croa­tia to the Croatian Military Frontier and Dalmatia, as well as Croatian independence in matters of internal affairs, justice, religion, and education that was subsequently confirmed by the ruler himself (Stancic, 2002, p. 183). The political changes that took place in 1860/1861 had powerful reverberations in the educational and scientific system, which also boosted development of national cartog­raphy. The development of geography had a particularly strong influence, in both the school system and the field of scientific research. The advances in the geography as a sci­entific discipline were directly reflected in the content and quality of local cartographic production. In 1866, the Yugoslav Academy of Arts and Sciences was founded while in 1874, a modern university was founded in Zagreb (Gross, Szabo, 1992, p. 415). These institutions were the main instigators of modernization processes, creating precondi­tions for the development of modern civil society in the fields of science and education. The significant changes initiated in the school system were to additionally en­courage the development of so-called national sciences. School books, which until 1862 were exclusively printed by the educational publisher K.u.k. Schulbuchverlag in Vienna, after 1862 started being printed in Zagreb (Cuvaj, 1910, V, p. 139; Modric Blivajz, 2007, p. 782). This especially boosted the domestic production of textbooks on geography. In the 1860s, Croatia saw the emergence of a pleiad of distinguished geographers. They had studied at prestigious German universities, but published their books in Croatian. As early as 1861, Václav Záboj Marik, published his book Kratak opis Carevine Austrijanske [A Brief Description of the Austrian Empire]. Soon other books followed; in 1865 Marik wrote Zemljopis Trojedne Kraljevine [The Geography of the Triune Kingdom], Petar Zoricic prepared Zemljopis za niže realke i niže gimna­zije [Geography for Lower Secondary Schools and Lower Grammar Schools], while in 1867 the Slovene pedagogue Franjo Bradaška published Sravnjivajuci zemljopis za više razrede srednjih ucionah [Geography for Higher Grades of Secondary Schools]. In addition to Marik and Bradaška, another geographer who started his scientific career around the same time was Petar Matkovic, the first university professor of geography in Croatia. As founder of the Department of Geography at the Faculty of Philosophy in Zagreb and its first professor, he was considered the founder of geographical sci­ence in Croatia. Having started his scientific work in 1866, Matkovic published a book entitled Statistika Austrijske Carevine [The Statistics of the Austrian Empire]. In 1874, it was followed by a book titled Geografsko-statisticki nacrt Austro-Ugarske Monarhije [A Geographical and Statistical Review of the Austro-Hungarian Monarchy], which underwent numerous editions (Altic, 2019, pp. 104–105). Of great significance for the development of geography and the geographic knowledge of the Croatian lands was also Vinko Sabljar’s book Miestopisni riecnik kraljevinah Dalmacije, Hervatske i Slavonije [The Toponymic Dictionary of the Kingdoms of Dalmatia, Croatia and Slavonia], published in Zagreb in 1866. On the other hand, Bogoslav Šulek had a particular influence on the development of professional geographic terminology. He published the Hrvatsko-njemacko-talijanski rjecnik znanstvenog nazivlja [The Croatian-German-Italian Dictionary of Scientific Terminology] in Zagreb in 1874. Toponymy recording in the native language, the development of professional geo­graphical terminology, and the progress in the geographic knowledge of the Croatian lands in general were also reflected in the advances in national cartographic efforts, which increasingly relied on recent achievements of local geographers as well. The ap­pearance of the abovementioned textbooks played an important role in the midst of the Croatian national movement and the struggle for its own cultural identity within the Austro-Hungarian Monarchy. Geography and cartography were recognized as an important expression of national identity, especially in their educational dimension. 2 USE OF GERMAN EDITIONS OF KOCEN'S ATLAS IN CROATIAN SCHOOLS The development of production of school textbooks in the Croatian language, which especially took place in the 1870s and 1880s, highlighted the problem of the lack of school maps in the Croatian language. A rather clumsy map of the Triune Kingdom made in 1861 by Franjo Kružic as the first school map of Croatia in the native lan­guage1, or a bilingual (Croatian-German) map of Croatia and Slavonia by Michael Katzenschläger (numerous editions from 1855 onwards)2, which left out many Cro­atian countries, caused great difficulties for teachers (Cuvaj, 1910, IV, p. 119). It is interesting that cartography in public schools was then taught not only through the teaching of geography but also through the teaching of drawing, where the skill of the so-called surveying drawing was taught.3 In the absence of school atlases in the Croatian language, the use of Kocen’s geographical atlas was allowed in secondary schools and high schools since 1861. Although published in German and modeled on German models of school atlases, Kocen’s editing and gradual supplementation of each new edition managed to move the atlas somewhat away from traditional Ger­manocentric school atlases and create an original content adapted to a multicultural monarchy such as Austro-Hungary. In the early editions (until the creation of Austro-Hungary), the Croatian lands were shown on several maps: Dalmatia and the Military Frontier were shown on a map of the Austrian Empire (1:5,000,000), Croatia and Slavonia were included in the map of Hungary (1:2,000,000) which was later replaced by a map of the Carpathian countries as well as on a map of the South Slavic country inhabited by Croats and Serbs (1:2,000,000), which in 1862 was replaced by a map of European Turkey, Dalmatia, and the Military Frontier (1:4,000,000) (Dörflinger, Hühnel, 1995, II, pp. 519–521). Germanocentrism in Kocen’s early editions was still very pronounced. The geographical focus on the German lands is obvious (in the 1865 edition there were no less than four maps of Germany), and the absence of the­matic maps especially those on linguistic and ethnographic issues speaking in favor of strongly expressed centralism of the then European monarchies. This is a reflection of the use of German templates such as school atlases by Emil von Sydow, Adolf Stieler, Joseph Marx von Lichenstern, Karl Christian Ludwig Adami, and Heinrich Kiepert (Kocen himself cites them as the source in the introduction to his first edition). Nevertheless, Kocen made some important steps forward. In addition to maps of political entities, he included in his atlas maps of individual natural geographical units (Central Europe, the Carpathian region, the Alpine countries, the Mediterranean), which was extremely innovative at the time (Bratec Mrvar, 2011, p. 94). He also drew the Slovene language border in the map of the Alpine countries,4 and added a comparative index of German and Slovenian geographical names for Slovenian settlements, which was omitted in editions published after Kocen’s death (Bratec Mrvar, 2011, p. 40). After 1868, the atlas was supplemented with new maps that did not focus on Germany but on the Austro-Hungarian Monarchy and its countries, so several maps of individual countries of the Austrian and Hungarian crowns appeared such as Bohemia and Mora­via, Galicia, Carniola, Istria and Goritz, etc. After Kocen’s retirement in 1870, his suc­cessors Konrad Jarc, Friedrich Umlauft (since 1877), Vincenz von Haardt (since 1880), and Wilhelm Schmidt (since 1896) continued completing and adapting the atlas to new political circumstances within the Monarchy. From 1875, the first thematic maps began to appear in the atlas, which at least somewhat moved away from the strictly physical geographical aspect of space, and touched on some issues of social and economic ge­ography.5 Nevertheless, despite the obvious progress, the Croatian countries in the atlas are still shown exclusively within larger geographical units (Croatia and Slavonia as part of the map of the Hungarian crown countries and Dalmatia together with Bosnia and Military Border, as well as, from 1877, together with Istria, Crain, and Goritz (and after 1880 again with Bosnia). This way of presenting the Croatian lands was in contradic­tion with the school curriculum of geography and history, which insisted on the unity of the Triune Kingdom (Croatia, Slavonia, Dalmatia). Also, a special problem was the geographical nomenclature that was Germanized or Italianized (in Istria and Dalmatia). 3 CROATIAN EDITIONS OF KOCEN’S ATLAS AND THEIR DISTINCTIVE FEATURES In order to improve the teaching of geography and history, and harmonize curricula with teaching aids, Augustin Dobrilovic, professor of geography and history and prin­cipal of the gymnasium in Kotor, decided in 1887 to compile a set of Croatian text­books and atlases for Croatian schools.6 After he had published Zemljopis za niže raz­rede srednjih škola [Geography for the Lower Grades of Secondary Schools] (Zadar, 1887; Zagreb, 1892), he prepared two Croatian school atlases in the same year. First he translated and adapted Putzgers’ historical atlas (F. W. Putzgers Historischer Schul-Atlas) into Croatian7, and then, in collaboration with Petar Matkovic,8 the Croatian edition of Kocen’s geographical atlas for secondary schools, which was published in Zagreb in 1887. More precisely, two editions of the abovementioned geographical at­las were published that year. First, an atlas with a set of 12 maps of Austro-Hungary was published as a separate volume in Vienna9, and then republished in Zagreb as a complete edition of the atlas with 37 maps covering the whole world, including previously published maps of Austro-Hungary10. All maps of Croatian editions were made as more or less literal translations of German editions. It is interesting that both Croatian editions of the geographical atlas from 1887 omit thematic maps that were already present in the German edition from 1887: a map of the Austro-Hungarian railway network and an ethnographic and linguistic map of the Monarchy. 3.1 Geographical scope, content, and source maps The first Croatian edition of Kocen’s atlas brings 12 maps relating to Austro-Hungary and its components, of which only two refer exclusively to Croatian lands. Maps refer­ring to the entire Austro-Hungarian Monarchy (physical with a longitudinal section of the relief and a political-administrative map) were taken from a recently published Ger­man or Czech edition. Physical maps, Alpine countries (Upper and Lower Austria, Salz­burg, Styria, Carinthia, Tyrol, Voralberg, Carniola, and Primorje), Carpathian countries (Hungary, Galicia, Bukovina), and Sudetenland (Czech Republic, Moravia, Silesia) that appeared in the German edition, in Croatian edition are supplemented with a politi­cal map for each of the above areas, which were adopted from the Czech edition. A particularly important intervention was the inclusion of a map Austrian Karst Regions and Occupied Lands (Bosnia and Herzegovina, Novi Pazar) at a scale of 1:2,000,000 through two maps, physical and political. It was a revision of a political map Dalmatia and the Occupied Territories that appeared in the 1880 German edition with the exactly same geographical coverage and content. For the Croatian countries, which are pre­dominantly located on karst terrains, this map certainly had great significance. How­ever, the inclusion of this map had a much greater political significance, and reflects the geopolitical changes that occurred after the Berlin Congress of 1878 and the Austrian occupation of Bosnia and Sanjak. The Austrian presence in Bosnia as well as the grow­ing political pressures from Budapest encouraged the growth of Croatian nationalism and the increasingly common perception of Bosnia as a predominantly Croatian coun­try.11 The inclusion of this map was a politically inconspicuous way to find all Croa­tian countries on one map, those under the Austrian (Istria, Dalmatia) and Hungarian crowns (Croatia and Slavonia), as well as Bosnia and Herzegovina. Due to the Austrian suppression of the South Slavic question, those countries rarely found places on the same map. Nonetheless, this map also maintained a specific Austrian discourse, which appropriated Croatia and Slavonia as Austrian (karst) countries. Certainly the most important novelty of Dobrilovic’s edition was the inclusion of two maps of Croatia and Slavonia at a scale of 1:1,500,000 (political and physical) (Figure 1). These were the first single geographical maps of Croatia and Slavonia in a school atlas. Interestingly, in 1876, a physical map of Croatia, Slavonia and Dalmatia at a scale of 1:2,500,000 appeared in Czech and German editions12. However, the Croatian edition of the physical and administrative maps of Croatia and Slavonia only partially relied on existing maps from Kocen’s atlas. Given the much larger scale that required signifi­cant refinement of the geographical content, it is clear that other templates were used in the preparation of Croatian maps. Considering the geographical content, geographical nomenclature and the way the relief is presented, some of the recent editions of Katzen­schläger’s map of Croatia and Slavonia at a scale of 1:500,000, which was used in schools, stand out as the most probable template.13 Dobrilovic’s presentation of relief by hatching and detailed administrative-territorial division largely coincides with Katzenschläger’s map. Dobrilovic and Matkovic played a particularly important role in adapting geo­graphical nomenclature to the Croatian language, which was otherwise the weakest link on earlier maps of Croatian countries. This is especially reflected in the Croatian terminology for mountains (oronyms), islands (nesonyms), and certain mareonyms, which now were significantly improved. As a supplement for oronyms, mareonyms, and hypsometric data, they used a 1878 physical map of Croatia and Slavonia prepared by Karl Herdliczka and printed by Friedrich Köke, a close associate of Hölzel (Altic, 2019, p. 114).14 Thus, to designate Podvelebitski kanal, which until then had been commonly called the Morlacki kanal [Morlach’s Channel] (according to the Italian name Morlacco for the Vlachs) he introduced the Croatian name Planinski kanal [Mountain Channel] under the influence of Herdliczka, Dobrilovic, and Matkovic. Echoes of the geographi­cal nomenclature of Herdliczka’s map can be clearly seen in Dobrilovic’s edition of the map of the Austrian karst regions as well, where a number of new Croatian mareonyms (for sea passages and channels) and nesonyms were adopted, which until then were listed exclusively in Italianized form. Figure 1: Physical map of Croatia and Slavonia prepared by Augustin Dobrilovic and Petar Matkovic for first Croatian edition of Kocen’s geographical atlas (Zagreb, 1887). This is the first single geographical map of Croatia and Slavonia in a school atlas (Croatian School Museum). 3.2 Map production and geographic elements of maps Publisher of the Croatian editions was the Lavoslav Hartman Bookstore. Yet, the maps prepared by Croatian editors were technically finalized and printed in Vienna by Eduard Hölzel. In this sense, there is no difference in the technique and quality of printing between the identical Zagreb and Viennese editions. Both were executed by the lithographer Friedrich Köke (1823–1882), the head of the Geographical Depart­ment of the Hölzel Institute. Croatian editions were printed in multicolored lithog­raphy and mostly published in hardcover. The technique of multicolor lithography was improved in later editions, which was especially reflected in the more detailed elaboration of the hypsometric scale and in the stronger contrast of colors, which improved the legibility of maps. Progress in the quality and manner of presentation of certain geographical ele­ments on the maps of Croatian editions mainly coincides with the progress in Ger­man editions (sometimes with a time lag). All maps in the early Croatian editions were constructed according to Ferro prime meridian. From the early 20th century, Croatian editions started to refer to Greenwich (the same as German editions).15 Al­though the metric system was introduced as the official unit of measurement in Aus­tria-Hungary from 1871, the scale of maps was expressed by a double scale in meters and geographical miles. Due to excessive generalization and the inadequacy of the hypsometric scale, the presentation of relief was the weakest element of the maps (this also applies to Ger­man editions). The relief is shown by hatching on both physical and political maps. On physical maps, the presentation of the relief was supplemented with a hypsometric scale, which in the first Croatian editions was not adjusted to the altitude range of Croatian lands, so that the whole of Croatia and Slavonia falls into only two catego­ries: lowlands and highlands. In the editions from 1900 onwards, the hypsometric scale was better defined (0–200 m, 200–500 m, 500–1000 m), so the presentation of the terrain was more credible, and was supplemented with height points. Another significant step forward in the quality of relief presentation was made when Milan Šenoa took over the editing of the atlas. He introduces the hypsometric scale with an equidistance of 100 meters, supplemented with numerous height points. Administrative and political maps of Croatia and Slavonia are accompanied by more abundant socio-geographical elements like numerous settlements, traffic network, and borders of the counties (these contents are excluded from the physical map).16 The symbolization (circular signatures) and classification of settlements according to the number of inhabitants are identical to those in the German editions. In the 1887 Croatian edition, the fortresses were designated by a special symbol and the capitals of provinces underlined (in later editions fortresses were excluded). Kocen’s approach not to rely only on the size of a settlement, but also on its historical significance when choosing which place names should be labeled on the map, particularly advanced the educational process. The same approach was adopted in Croatian editions. Thanks to the selection of toponyms based on both population and their historical significance, the Croatian maps also included many smaller settlements important for Croatian history, such as Bužim, Cetin, or Stolni Biograd (in Hungary). 3.3 Language redaction The most significant contribution of Croatian editors certainly relates to the linguis­tic redaction of geographical terminology. All map titles, explanation keys, texts on mathematical cartography, as well as the overall geographical nomenclature of maps (including diacritics) were translated into Croatian. Thus, the atlases had been adapt­ed for the teaching in the Croatian language, as well as harmonized with valid geog­raphy textbooks. This was especially important for place names which in previous editions of school atlases were given in Germanized or Italianized forms. Slovenian, Montenegrin, Bosnian-Herzegovinian, and Serbian nomenclature was also given in their original forms. Not only Croatian toponyms were given in Croatian language. Some of the geo­graphical nomenclature of foreign countries is also translated into Croatian (exoto­ponyms). This refers equally to settlements (Wien – Bec, Graz – Gradac, Bratislava – Požun, Pécs – Pecuh, Venezia – Mletci, Eisenstadt – Željezni grad), oronyms (Bay­erisches Alpenvorland – Bavarska visocina, Stredo ceská vrchovina – Srednja ceska stupnjevina, Ceško-moravska vrchovina – Ceško-moravsko pogorje, Schweizer Jura – Švicarska jura, Erdélyi-érchegység – Erdeljsko rudogorje, Kisalföld – Mala ugar­ska nizina), as well as to the names of countries (Scotland – Škotska, Steiermark – Štajerska, Schwaben – Švabska). Hydronyms are most often left with their original names except in the case of minor phonetic adaptations (e.g., Dija – Dyje, Adiža – Adige). Exceptions were made with large rivers such as the Danube, the Rhine, the Po, and the Thames, which are written as Croatian exonyms (Dunav, Rajna, Pad, Temza). The names of foreign lakes are usually set in the original language and only appella­tions are translated (e.g., lake – jezero). The exception is Lake Balaton in Hungary, which is designated by its Croatian name (Mutno jezero). Aware of the unusualness of Croatian forms of certain foreign place names, the Croatian editors labeled some of those toponyms with double names – in Croatian and in its original language, e.g., Monakov (Munich), Rezno (Regensburg), Draždjan (Dresden), Pasov (Passau). In later editions, the tendency of translating foreign nomenclature is less pronounced, so most of the foreign place names are given in their language of origin, including appel­lations (e.g. Boden See instead of Bodensko jezero). The longest-lived exotoponyms in Croatian atlas editions refer to names of neighboring countries with which Croatia had the strongest historical ties (Hungary, Austria, Italy). In 1934 and 1943 editions, most of the geographical nomenclature was written in the original languages. The only excep­tions are the names of the seas and countries that had been retained in the Croatian version, and which, in accordance with international conventions, are still written as they are read in the language of the publisher (Jordan, 2005). Strange enough, Croatian editions of Kocen’s atlas were not equipped with an index of foreign geographical names with their pronunciation (sprachliche Erläuterungen) that regularly appeared in German editions. The first such addition to Croatian editions appeared in 1934. 4. CROATIAN EDITIONS OF KOCEN'S ATLAS AFTER 1887 4.1 Early Hranilovic's editions The publication of the 1887 edition was followed by two editions, from 1889 and 1894, which remained unchanged from the complete 1887 edition (Dörflinger and Hühnel, 1995, II, pp. 612–613).17 After Vincenz von Haardt, in collaboration with Wilhelm Schmidt, revised the German edition in 1897, supplementing it with new thematic maps of Austro-Hungary (maps of soil, relief, climate, forests, density of population, languages, urban network) these thematic maps were for the first time included in the Croatian edition that was published in 1900.18 From that edition onward, the editing of Kocen’s atlas was taken over by Hinko Hranilovic,19 who included 12 maps related to Austro-Hungary, two more than the German edition.20 Moreover, for the first time all the maps refer to the Greenwich prime meridian. In addition to the maps that can be found in the German edition, Hranilovic kept two maps of Croatia and Slavo­nia (physical and political) according to Dobrilovic’s earlier template, which he now supplemented with new contents (primarily in terms of administrative division and railway network). The maps of Croatia and Slavonia are now at a scale of 1:1,200,000, which is an enlargement in scale compared to 1887. Apart of the larger scale maps have been supplemented with many new toponyms. In addition, the physical map of Croatia and Slavonia was accompanied by an auxiliary map of Plitvice Lakes and longitudinal sections of the Croatian relief. Furthermore, Hranilovic improved the physical map of the karst countries (1:2,000,000) whose old Germanocentric title (Austrian karst countries) was now revised (Karst regions. Croatia, Slavonia, Dalmatia, Bosnia and Herzegovina, Istria, and Carniola). In addition, the first Croatian edition of the thematic maps of Aus­tria-Hungary that appeared in this edition (which also refers to Croatian countries) made a significant advance in geography teaching. In addition to the abovementioned maps, Hranilovic implemented several other innovations. In the introductory part of the atlas, he included the sheet titled Osnove kartografije [Basics of Cartography], which explains cartographic methods of presentation of different types of terrain. Al­though a similar sheet appears in the German edition, in the Croatian edition all examples of terrain are taken from Croatian maps so the sheet also contains five city maps of Zagreb of different scales. Hranilovic also supplemented some maps taken from the German edition. E.g., he introduced isobaths on the maps of the northern and southern hemispheres and marked the depths of the sea with a color scale, which enabled an insight into the relief of the seabed. The good reception of Hranilovic’s edition was confirmed in professional circles, so in 1903 a very positive review of the atlas was made in the Gazette of the Croatian Natural History Society, which praises the atlas and its innovations in teaching geography (Mandic, 1903, pp. 178–179). 4.2 Second enlarged edition prepared by Hranilovic and Modestin The Croatian edition of 1900 would be reissued more or less unchanged in 1903, 1906, and 1909. When Josip Modestin21 joined Hinko Hranilovic in the editorial office of Kocen’s atlas, together they prepared a new (second) enlarged Croatian edition in 191022. Although the atlas had not been significantly revised in terms of content and number of maps (the content of the atlas is almost identical to the 1900 edition), this edition represents a qualitative leap in production. Instead of the previous 57, the atlas now contains 78 maps on 51 sheets. There are 11 sheets on Austro-Hungary (one less than before). The biggest novelties in this edition are the geological map of Austria-Hungary at a scale of 1:4,000,000, the improved toponymy of maps, and a much better representation of relief on physical map of Croatia and Slavonia (Figure 2). The politi­cal map of Croatia and Slavonia is now supplemented with auxiliary maps of Zagreb at four different scales and two aerial views of Zagreb taken from the Turul balloon in 1905 (Figure 3). This small but important acknowledgment to the city of Zagreb gave the atlas a stronger national note, emphasizing the Croatian capital. A physical map of the karst countries was also supplemented with an auxiliary map of Carniola and the Austrian Littoral at a scale of 1:1,250,000 which was of particular importance for the geography of Istria, which is here shown together with its Slovenian and Croatian hinterland (Figure 4). This 51-page edition would be reissued more or less unchanged several more times: in 1911, 1912, 1914, and 1918. Figure 2: Physical map of Croatia and Slavonia prepared by Josip Modestin and Hinko Hranilovic published in the second enlarged Croatian edition (Vienna, 1910). Toponymy and representation of relief are greatly improved (Library of Department of Geography, Faculty of Science University of Zagreb). Figure 3: Auxiliary maps of Zagreb at four different scales and two aerial views of Zagreb taken from the Turul balloon in 1905 included in second enlarged Croatian edition of 1910 (Library of Department of Geography, Faculty of Science University of Zagreb). Figure 4: Auxiliary map of Carniola and Austrian Littoral showing Istria together with its Slovenian and Croatian hinterland. This is copy from 1914 edition (Croatian School Museum). 4.3 Third enlarged edition prepared by Augustin Šenoa After 1918, the links between the German and other European editions of Kocen’s atlas weakened. Although still united under the name of Blaž Kocen, national editions after 1918 became increasingly independent of German templates. This is primarily reflected in the changed geographical scope of the maps. The maps of the Austro-Hungarian area are now disappearing, and are replaced by maps of the newly formed nation-states or their parts. However, this would not happen immediately in 1918. Due to the war, even the German editions from 1918 and 1920 still do not reflect the geopolitical changes caused by the collapse of the Monarchy (Kretschmer, 1995, p. 219). Thus, the Croatian editions from 1918 and 1919 remain unchanged as well. The first supplemented German edition that brings significant changes regarding the former Austro-Hungarian space appears from 1921/1922. This edition also contains a new physical map of the Kingdom of Serbs, Croats and Slovenes at a scale of 1:2,500,000 (Kretschmer, 1995, p. 220). As early as 1922, under the leadership of Milan Šenoa, a new (third) revised edition of Ko­cen’s atlas was prepared in Croatia, which would contain the same map of the Kingdom in the Croatian edition23. At that time, Milan Šenoa was one of the leading Croatian geographers and head of the Department of Geography at the Faculty of Philosophy, University of Zagreb.24 His most significant contribution to Croatian cartography is definitely his work on Croatian editions of Kocen’s atlas published from 1922 to 1943. Hinko Hranilovic and Josip Modestin still participated in the preparation of this edi­tion. Although marked as the third revised edition, the only significant change was the inclusion of a physical map of the Kingdom of Serbs, Croats and Slovenes (1:2,500,000) adopted from German edition. In this edition, the physical map Croatia and Slavonia was retained, while the administrative map of the same area was omitted. The atlas under the leadership of Milan Šenoa underwent significant changes only in 1934, when it changed its title to Kocenov geografski atlas.25 In this edition, Šenoa has new associates, the Croatian geography professor Ivo Juras26 and the Slovene ge­ographer and cartographer Valter Bohinec.27 The inclusion of Bohinec in the editorial board of the Croatian edition was especially beneficial due to his dual role. Bohinec was an experienced and skilled cartographer, especially in making hypsometric maps, who helped Šenoa to compile new physical maps. In addition, the Croatian edition from 1934 (as well as the later one from 1939) was also prepared in the Slovene lan­guage for the needs of Slovene schools. Although in the Slovene version only the in­troductory pages were finally translated into Slovene while the maps and geographi­cal terminology remained in the Croatian language, Bohinec’s participation certainly contributed to the quality of both the Slovene and Croatian editions. The Croatian 1934 edition is equipped with an index of foreign geographical names and their pronunciation, as well as with an explanation key. The world map and the celestial map are followed by a set of thematic maps of the world. Earlier chapters on mathematical geography with accompanying maps are omitted here. The volume of the atlas has now been reduced compared to some previous editions (48 pages), but the share of maps relating to Yugoslavia has increased significantly (as many as ten). Thus, immediately after the physical, the political, and the ethnographic map of Europe a whole set of maps on Yugoslavia are inserted. The physical map of the Kingdom of Serbs, Croats and Slovenes has now been renamed Yugoslavia, and supplemented with ancillary city maps of Belgrade, Zagreb, and Ljubljana. In addition to the physical map of the country, an administrative map with a division into counties (containing ancil­lary maps of the Sarajevo, Split, and Dubrovnik areas) is included as well. This is fol­lowed by two more detailed maps of Yugoslavia at a scale of 1:2,000,000: the southern counties (Banovinas) and the northwestern counties. Yugoslavia is also shown by a series of thematic maps at a scale of 1:5,000,000 which are also an original work of the editors: type of soil, distribution of forests and arable land, population density, traffic map, geological map by Kosta Petkovic, confessional map, and language map. Clearly outlined on the latter is Yugoslav unitarism, in which the only South Slavic language is Yugoslav. Due to the detailed hypsometric scale (undoubtedly the merit of Bohinec!), all physical maps in this edition are characterized by an extremely plastic and concise presentation of the relief. An interesting phenomenon is the appearance of small ancil­lary maps of Yugoslavia inserted into the political maps of North and South America and Australia, respectively. Although the didactic goal was to compare the size of the territories, linking the territories of Yugoslavia with the states in the Americas and Australia certainly had the goal of emphasizing the migrant ties between Yugoslavia and the abovementioned countries. This edition was reprinted twice more in 1938 and 1939 (in Croatian and Slovene) without significant changes. A new edition of 1943, compiled after the establishment of the Independent State of Croatia (NDH) faithfully reflected all the changes in the educational and cultural policy of the new state.28 Symptomatically, Valter Bohinec and Ivo Juras disappeared from the editorial board. No less important, Milan Šenoa, who prepared the adapted edition for the needs of the Independent State of Croatia, was already retired at the time of preparing the atlas. Probably the relative security of his pension (he could not lose his position) allowed him to accept a job, and try to protect the geographical and didactic principles applied in this edition within the framework of his profession and his abilities. The introductory part of the atlas was now supplemented. In addition to the list of foreign geographical names with their pronunciation, for the first time, the atlas also contains a classic geographical index of all geographical names (domestic and foreign) with an indication of their position on the map. The 1943 edition under­went a significant linguistic revision. With the establishment of the Independent State of Croatia, the obligatory application of etymological spelling was introduced into the education system. As this required major interventions in the atlas, the new spelling was applied only in the index of geographical names while the geographical names according to the old spelling remained on the maps (this was the reason why the atlas received only a temporary use permit). Exceptions are maps of the Independent State of Croatia where the terminology is harmonized with the etymological spelling (e.g., Priedor instead of Prijedor). Šenoa wrote foreign geographical names in their original language, but there where they were forcibly replaced by German names he tried to avoid those names or possibly add them only in brackets, keeping the original place name in the first place such as Celje (Cilli), Warszawa (Warschau). In some places he completely avoided it. For example, in the annexed Sudetenland, he does not mention the German name Karlsbad for Karlovy Vary at all. For Ljubljana, he preferred to cite the etymological version of Lubiana in parentheses to avoid mentioning the German name Laibach. He did the same with Croatian town of Rijeka, which he mentions in the index as Rieka, avoiding to mention its official Italian name Fiume. The sheet with the explanation key and the cartographic techniques used in the presentation of the terrain remained identical to those in the 1934 edition. In the introductory part, now included is one sheet of mathematical geography (taken from earlier Croatian editions). Although maps changed their order, being updated with new state borders, differences between the 1934 and 1943 editions were relatively small. As expected, the largest interventions were carried out on maps of Croatia. From the former map of Yugoslavia at a scale of 1:2,500,000, an overview map of the NDH at the same scale was now made, and by doubling it, what was obtained was a more detailed physical map of the NDH at a scale of 1:1,250,000 (Figure 5). The abovementioned maps of Croatia are now significantly improved. The relief is pre­sented through a detailed and well-adapted hypsometric scale, which is supplemented with isohypses. This significantly improves the impression of three-dimensionality of the terrain, and increases the legibility of maps. The larger scale enabled a sig­nificant addition to the geographical nomenclature. In the Croatian territory annexed by Italy (Istria, Kvarner, part of Dalmatia) Šenoa retains Croatian place names (the only Italianized name he adopted in political map of Croatia was Fiume). In addition to numerous place names, the maps are supplemented with the names of numerous mountain peaks that are now appearing for the first time (in previous editions, the peaks were only indicated with height markings). In addition to the physical map, an administrative-territorial map of the Independent State of Croatia and four thematic maps of the same state were compiled. The language and confessional maps that ap­pear in the 1934 edition are now omitted. The map of Central Europe is now renamed the Great German Reich (the new title is just pasted over the old one). The rest of the atlas relating to Europe and other continents, remained identical to the 1934 edition though with minor changes (borders). 5 CONCLUDING REMARKS Kocen’s geographical atlas played a key role in both the development of Croatian school cartography and the development of geography teaching. Its Croatian editions from 1887 were the first school geographical atlas in the Croatian language that was used as a didactic tool in teaching from 1887 onward until the end of the Second World War. About twenty Croatian editions published between 1887 and 1943 maintain the devel­opment of the geography curriculum, but also the political changes that the Croatian countries underwent at the end of the 19th and the beginning of the 20th centuries. Its appearance during the national movement and the struggle for the affirmation of the Croatian language in education and science gave it an important role in awakening national consciousness and building a common cultural identity of Croatian peoples. The creation of the first Croatian edition of Kocen’s atlas was also encouraged by the founding of the Department of Geography at the Faculty of Philosophy, which began in 1883 under the leadership of Petar Matkovic. Its later editors were also the distinguished university professors of geography at the University of Zagreb, such as Hinko Hranilovic and Milan Šenoa, who, in cooperation with high school teachers, adapted the atlas to the school curriculum and new didactic standards in teaching of geography. Its good adaptation to historical changes and national ideologies from Austrian centralism, Cro­atian nationalism to Yugoslav unitarism enabled its long-lasting use.29 The appearance of Dobrilovic’s edition of Kocen’s atlas was an announcement of a new era, and had far-reaching consequences for the development of Croatian school cartography and the manner of teaching geography. The introduction of school atlases and wall maps as teaching aids gained momentum in the 1880s. Around 1890 began a larger production of Croatian wall maps under the leadership of Ivan Steklasa who (according to Hungarian templates) prepared not only a large wall map of Croatia and Slavonia, but also school maps of each county for the use in teaching local geography. Last but not least, Steklasa edited Rothaug’s geographical atlas, which was supposed to compete with Kocen’s, but was not very successful30. Almost at the same time the first wall map of Dalmatia, which was prepared at the Hölzel Institute in Vienna and published in Zadar in 1892 appeared in the schools (Altic, 2019, pp. 122–123).31 Only a year after the appearance of the Croatian edition of Kocen’s atlas, the first school atlas of Croatian history prepared by Vjekoslav Klaic32 was published, soon followed by the first wall maps of Croatian history.33 Changes in the Croatian editions of Kocen’s atlas were most often associated with changes in German (sometimes Czech) editions. The early Croatian editions show a very high correlation with the simultaneous German editions, so the Croatian edition primarily referred to a language edition of the geographical nomenclature. Greater in­dependence in editorial policy can only be noticed after 1918. The geographical scope of the maps, which sustains new political changes, is beginning to change significant­ly. In addition to increasing number of maps of national areas, their order changes, so that maps of nation-states move from the end of the atlas (where they represented the periphery of the Empire) to the beginning of the atlas, placing national territory at the center of interest. The diversification of maps by type is also obvious in the editions from the end of the 19th and the beginning of the 20th centuries. Apart from physical and political maps, there are more and more thematic maps. Types of thematic maps, on the other hand, maintain changes in geographical theory, which, in studying the geography of countries, no longer relies predominantly on the physical characteristics of the country (environmentalism typical of German scientific thought), but increas­ingly respects socio-geographical processes as a factor of geographical development (Black, 2000, p. 111). The 1943 edition was the last edition of Kocen’s atlas in the Croatian language. After the end of the Second World War, a new network of institutions was established in Croatia that were specialized in production of school atlases. In 1948, the pub­lishing house Ucila specializing in the production of didactic aids, including school atlases, wall maps, and globes was established. In 1983, this organization grew into Kartografija-Ucila, from which emerged the public institution Croatian School Car­tography, which still operates today. Notes 1 Krajobraz Trojedne Kraljevine Dalmatinsko-Hérvatsko-Slavonske i pripadajucih delah Vojnicke krajine kao što i pridnadležecih pokrajinah sa Turskom Hérvatskom, Hercego­vinom, Cérnogorom i Bosnom narisan i preuzvišenomu, presvetlomu i precastnomu gos­podinu Josipu Jurju Strossmajeru Franjo Vjekoslav Kružic. 1:288,000. Zagreb: Dragutin Albrecht, 1861. Color lithograph in 9 sheets; 215 x 148 cm. 2 Zemljovid Hérvatske i Slavonije s Krajinom vojnickom sastavljen i dubokim strahopoštovanjem posvetjen nj. preuzvišenosti gospodinu grofu Josipu Jellacicu Bužimskomu banu... = Karte von Croatien und Slavonien nebst der k.k. Militär Gränze entworfen und sr. exellenz herrn grafen Josef Jellacic von Bužim… / Michael Katzenschläger. 1:504,000. Vienna: Reiffenstein und Rosch, 1855. Color lithograph; 112 x 65 cm. 3 A special textbook was published in 1867 for the purpose of educating children in drawing maps. Ljudevit Modec, Rukovodnik u risanju zemljovida [A Guide in Drawing Maps] (Cuvaj, 1910, V, p. 469). 4 As a source he probably used the Ethnographische Karte der Oesterreichischen Monarchie by Karl von Czoernig from 1857. 5 The first thematic maps were included in the 1875 edition (a map of the Austro-Hungar­ian railway network and a map of the Central European railway). From 1887 a linguistic and ethnographic map of Austro-Hungary appeared as well. 6 Augustin Dobrilovic (1843–ca 1907?) was a professor of history and geography and prin­cipal at the Gymnasium and associated Naval school in Kotor. Apart from being the au­thor of the geography textbook, he stood out most as an editor of Croatian editions of historical and geographical school atlases. 7 Atlas antiquus: Historijsko-geografski školski atlas / izradili F. W. Schubert i W. Schmidt, za hrvacke škole udesio A. Dobrilovic. Vienna: Eduard Hölzel, 1887. Atlas on 22 sheets. 8 Petar Matkovic (1830–1898) studied geography in Vienna, Prague and Berlin, where he at­tended the lectures of the historian Theodor Mommsen and geographer Eduard Ritter. Ini­tially, he worked as a secondary school professor, and then taught geography at the University of Zagreb (1883–1893). Also, he was the founder of the Statistical Office for the Kingdoms of Croatia and Slavonia (1875), and member of the Yugoslav Academy of Arts and Sciences. 9 Kozennov školski atlas, hrvatski priredio A. Dobrilovic, ravnatelj C.k. državne velike gim­nazije u Kotoru. I dio Austro-Ugarska. Vienna: Eduard Hölzel, 1887. Atlas with 12 maps in color; 17x25 cm. 10 Kozennov geografijski atlas za srednje škole sa hrvatskim naukovnim jezikom / pripredio Augustin Dobrilovic, ravnatelj c. k. državne gimnazije u Kotoru, uz reviziju dra. Petra Matkovica. Zagreb: Akademicka knjižara Lavoslava Hartmana (Kugli & Deutsch), 1887. Atlas with 37 maps. 11 The work of Vjekoslav Klaic, who in 1878 published his book about the geography of Bos­nia and Herzegovina, describing them as predominantly Croatian countries, had a special influence on the development of this idea (Altic, 2019, p. 115). 12 Chorvatsko, Slavonie i Dalmacie. Blaž Kozennuv zemepisný atlas pro školy strední. Vien­na: Eduard Hölzel, 1876. Map Collection of the Faculty of Sciences, Charles University in Prague. Strangely enough, this map appeared only in the 1876 edition (Czech and German). 13 According to current knowledge, the map was published in 1855, and reissued in 1856, 1857, 1870, 1871, 1879, 1881, 1882, 1889, 1893, 1895, 1898, 1907, 1910, 1913, 1916, 1918, 1919, and 1920. From 1871 onwards, the map publication was continued by Vi­enna’s publishing house Artaria & Comp. 14 Fizikalna karta Hrvatske, Slavonije i Dalmacije/ Karlo Herdliczka. 1:864,000. Vienna: F. Köke Lithographer, 1878. Color lithograph: 56 x 56 cm. 15 This is quite atypical given that the then official Austrian cartography still relied on Ferro. In fact, although Greenwich was introduced as the official meridian in 1884, the Austro-Hungarian Monarchy kept Ferro as the initial meridian on its official topographic maps until 1918. 16 In early Croatian editions of physical maps of Croatia and Slavonia, the positions of settle­ments are marked by the usual circular symbol and only the initial letter of the place name. 17 It should be noted that the dates of the Croatian editions for 1889 and 1894 are based on an estimate of two atlases with no original date. Not a single specimen from those years has been found in Croatia. Dörflinger and Hühnel dated these two undated Croatian editions accord­ing to the administrative-territorial structure and construction of the railway network. 18 Kozennov geograficki atlas izraden po V.v. Hardtu i W. Schmidtu za srednje škole sa hr­vatskim nastavnim jezikom priredio i upotpunio dr. Hinko pl. Hranilovic, kr. Sveucilišni profesor, sadržaje 57 listova i 85 karata. Bec: Ed. Hölzel, Zagreb: glavno skladište za Hrvatsku, Slavoniju, Dalmaciju, Bosnu i Hercegovinu, knjižara L. Hartmana (Kugli & Deutsch), 1900. 19 Hinko Hranilovic (1860–1922) was a Croatian geographer. He studied geography, history, and philosophy at the Universities of Graz, Vienna, Berlin, and Oxford. In 1887, he was awarded a Doctorate in Physical Geography by the University of Graz. A secondary school teacher of geography at first, in 1892 he became an assistant to Professor Petar Matkovic at the Department of Geography of the Faculty of Philosophy, University of Zagreb. Full profes­sor since 1908. One of the founders of the Geography Society in Zagreb (1897). He special­ized in geographical theory, geographical methods, regional geography, and karst geography. 20 The German edition does not include two maps of Croatia and Slavonia. 21 Josip Modestin (1866–?) studied history and geography at the University of Zagreb. He worked as a high school teacher and principal of the Gymnasium in Rijeka. Author of two prominent geography textbooks in the Croatian language: Zemljopis i statistika Austro-Ugarske Monarhije za srednja ucilišta [Geography and Statistics of the Austro-Hungarian Monarchy for Secondary Schools] (1903, 1905, 1916), Zemljopis za srednje škole po knjizi Dr Eduarda Richtera [Geography for Secondary Schools based on a book by Dr. Eduard Richter] (1905, 1908). He participated in the work on the Croatian edition of Kocen’s atlas from 1910 to 1922. 22 Kozennov geograficki atlas za srednje škole (gimnazije, realke, trgovacke i uciteljske škole i slicne zavode), obradili i upotpunili za škole sa hrvatskim nastavnim jezikom Dr. Hinko pl. Hranilovic i Dr. Josip Modestin. 78 karata sa 199 sporednih karata na 51 listu po njemackom izdanju koje obradiše dr. F. Heiderich i dr. F. Schmidt. Drugo prošireno i preradeno hrvatsko izdanje. Vienna: Ed. Hölzel, 1910. 23 Kozennov geografic.ki atlas za srednje s.kole sa 78 karata sa 199 sporednih karata na 51 listu. Obradili i potpunili Hinko Hranilovic´, Josip Modestin i Milan S.enoa; po njemac.kom izdanju F. Heidericha i W. Schmidta 3. pros.ireno i preradeno hrvatsko izdanje. Zagreb: St. Kugli, 1922. 24 Milan Šenoa (1869–1961), Croatian geographer and writer. He graduated and received his PhD from the Faculty of Philosophy in Zagreb. At first he taught geography at the classical gymnasium in Zagreb and from 1910 started teaching at the Faculty. In 1918, he took over the position from Hranilovic as a head of the Department of Geography at the Faculty of Philosophy in Zagreb. From 1922 to 1940, when he retired, he was the head of the Geographical Institute, and from 1927 head of the Department of Regional and Social Geography (anthropogeography). He published about fifty papers on physical, regional and social geography, many travelogues, and popular geographical articles. 25 Kocenov geografski atlas. Priredio ga Dr. Milan Šenoa, prof. universiteta uz suradnju prof. Ive Jurasa i prof. dra V. Bohinca. Zagreb: St. Kugli, knjižara kralj. Sveucilišta i Jugoslaven­ske akademije, Zagreb, 1934. Atlas with 48 pages in color. 26 Ivo Juras (1866–1948), was born in Zadar. From 1905 to 1906 he studied geography and history in Zagreb, continuing his studies in Graz (1906–1907) and Vienna (1907–1909). He worked as a high school teacher in Zadar and Split. In 1942 he became the director of the Teachers’ School in Zagreb, retiring in 1944. He was the author of numerous high school text­books on geography, especially on Dalmatia. Apart from his work on Kocen’s atlas, he is best known as the author of Pregled gospodarstva i trgovine u Dalmaciji [Review of the Economy and Trade in Dalmatia] (1910) and Zemljopis Jugoslavije, Kraljevine Srba, Hrvata i Sloven­aca [Geography of Yugoslavia, the Kingdom of Serbs, Croats and Slovenes] (1922). 27 Valter Bohinec (1898–1984) was one of the first Slovene doctors of geography. He studied in Vienna, Naples, Zagreb, and Ljubljana. He received his doctorate in 1921 under the mentorship of Arthur Gavazzi. He worked at the Institute of Geography, as a high school teacher, and then for three decades as a map librarian at the National Library of Slovenia. He was one of the leading karstologists between the two world wars in Slovenia. He was also a prominent author of a number of school maps. 28 Kozenov zemljopisni atlas, priredio prof. dr. Milan Šenoa. Zagreb: St. Hugli, 1943. Atlas with 46 sheets, Lithographs in color. 29 This was not the case with the historical school atlas that Augustin Dobrilovic also pre­pared in 1887. It was the F. W. Putzgers Historischer Schul-Atlas that Dobrilovic trans­lated into Croatian. However, its distinct Germanocentrism as well as the lack of historical maps relating to Croatian history did not leave it in use for long. The following year it was overshadowed by Klaic’s Atlas za hrvatsku povijestnicu [Atlas of Croatian History]. 30 Školski atlas na temelju metodike sastavljen po Ivanu Gj. Rothaugu, hrvatski priredio Ivan Steklasa, prof. kr. Uciteljske škole u Zagrebu. Zagreb: Lav. Hartman (Kugli i Deutsch), 1892. 31 Zemljovid Kraljevine Dalmacije = Carta del Regno di Dalmazia / Vinko plemeniti Haardt. 1:350 000. Wien, Zadar: Eduard Holzel, Komisiona naklada knjižare H. pl. Schönfelda,1892. – Lithograph in color; 165x125 cm. 32 Atlas za hrvatsku povjestnicu/ sastavio ga Vjekoslav Klaic. U Zagrebu, litografija i štampa Carla Albrechta, 1888. Atlas with 6 maps: lithograph in color; 18x24 cm. 33 Historicki zemljovid Hrvatske (sa Slavonijom i Dalmacijom), Bosnom, Istrom i susjednim srpskim i slovenskim zemljama / zasnovao ga Vjekoslav Klaic, crtao Anton Jiroušek. 1:400 000. Zagreb, tipografija Margetic i drug, 1899. Lithograph in color; 168x148 cm. References Altic, M., 2003. Povijesna kartografija: kartografski izvori u povijesnim znanostima [Historical Cartography: Cartographic Sources in Historical Sciences]. Zagreb: Publishing house Meridijani. Altic, M., 2019. Cartography between imperial politics and national movements: 19th century mapping of Croatia. Special issue of Cartographica 54/4, monograph 55, Toronto: University of Toronto Press. Black, J., 2000. Maps and history, constructing images of the past. New Haven and London: Yale University Press. Bradaška, F., 1867. Sravnjivajuci zemljopis za više razrede srednjih ucionah [Geogra­phy for the Higher Grades of Secondary Schools], Zagreb: Ljudevit Gaj. Bratec Mrvar, R., Lukas B., Fridl, J., Kladnik, D., Kunaver J., 2011. Kocenov srednjes.olski atlas kot didaktic.na prelomnica. Ljubljana: Zaloz.ba ZRC. Cuvaj, A., 1910. Grada za povijest školstva: sv. IV od 31. prosinca 1851. do 20. listo­pada 1860. [Sources for the History of Education: Volume IV for Period Decem­ber 31, 1851 - 20 October, 1860]. Zagreb: Kr. hrv.-slav.-dalm. zem. vlada, Odjelaza bogošt. i nastavu. Cuvaj, A., 1910. Grada za povijest školstva: sv. V od 20. listopada 1860. do 20. travnja 1868. [Sources for the History of Education: Volume V for Period October 20, 1860 - 20 April 20, 1868]. Zagreb: Kr. hrv.-slav.-dalm. zem. vlada, Odjela za bogošt. i nastavu. Dobrilovic, A., 1887. Zemljopis za niže razrede srednjih škola [Geography for Lower Grades of Secondary School]. Zadar: Brzotiskom Narodnog lista. Dörflinger, J., Hühnel, H., 1995. Atlantes Austriaci, Österreichische Atlanten 1. Band 1561-1918, 2 Teilband. Wien: Böhlau Verlag. Gross, M., Szabo, A., 1992. Prema hrvatskome gradanskom društvu. [Towards the Croatian Bourgeois Society]. Zagreb: Nakladni zavod Globus. Jelavich, C., 1992. Južnoslavenski nacionalizmi, jugoslavensko ujedinjenje i udžbenici prije 1914 [South Slav Nationalisms, Texbooks and Yugoslav Union before 1914]. Zagreb: Nakladni zavod Globus i Školska knjiga. Klaic, V., 1888. Atlas za hrvatsku povjestnicu, sastavio ga Vjekoslav Klaic. Zagreb: Carl Albrecht. Kretschmer, I., 1995. Atlantes Austriaci, Österreichische Atlanten 2. Band 1919-1994. Wien: Böhlau Verlag. Mandic, D., 1903. Kozennov geograficki atlas izraden po V. v. Hardtz i W.Schmidrtu. Za srednje škole s hrvatski nastavnim jezikom priredio i upotpunio dr. Hinko pl. Hranilovic. Glasnik hrvatskoga naravoslovnog društva, XIV, pp. 178–179. Marik, V., 1861. Kratak opis Carevine Austrijanske [A Brief Description on the Aus­trian Empire]. Zagreb: Dragutin Albrecht. Marik, V., 1865. Zemljopis Trojedne Kraljevine [Geography of the Triune Kingdom]. Zagreb: Dragutin Albrecht. Matkovic, P., 1866. Statistika Austrijske Carevine [The Statistics of the Austrian Em­pire]. Zagreb: Narodna tiskarnica Ljudevita Gaja. Matkovic, P., 1874. Geografsko-statisticki pregled Austro-Ugarske Monarhije [Geo­graphical and Statistical Review of the Austro-Hungarian Monarchy]. Zagreb: Narodna tiskara dra. Ljudevita Gaja. Modec, Lj., 1867. Rukovodnik u risanju zemljovida [A Guide in Drawing Maps]. Za­greb: [s.n.]. Modric Blivajs, D., 2007. Kakvi su bili povijesni srednjoškolski udžbenici u banskoj Hrvatskoj u razdoblju Khuenova banovanja? [What’s like the history textbooks in Croatia during the Era of Ban Khuen were?]. Casopis za suvremenu povijest, 3, pp. 777–849. Sabljar, V., 1866. Miestopisni rjecnik kraljevinah Dalmacije, Hervatske i Slavonije [The Toponymic Dictionary of the Kingdoms of Dalmatia, Croatia and Slavonia]. Zagreb: Antun Jakic. Stancic, N., 2002. Hrvatska nacija i nacionalizam u 19. i 20. stoljecu [Croatian Nation and Nationalism in the 19th and 20th Centuries]. Zagreb: Barbat. Zoricic, P., 1865. Zemljopis za niže gimnazije i realke. Zagreb: Narodna tiskarna dra. Ljudevita Gaja. VPLIV BLAŽA KOCENA (BLASIUSA KOZENNA) IN NJEGOVEGA GEOGRAFSKEGA ATLASA NA RAZVOJ HRVAŠKE ŠOLSKE KARTOGRAFIJE Povzetek Blaž Kocen, poznan tudi kot Blasius Kozenn (1821, Hotunje pri Ponikvi–1871, Du­naj), je eden najbolj znanih slovenskih geografov in kartografov. Deloval je v raz­burkanih casih, ki jih je zaznamovala tudi modernizacija izobraževalnega sistema v deželah Avstrijskega cesarstva oz. Avstro-Ogrske (od l. 1867). Sprva je študiral za duhovnika, potem pa se je izobrazil na podrocju matematike, fizike in naravoslovja; odlikoval se je pri pouku geografije, pri cemer je zagovarjal uporabo bolj naprednih ucnih orodij, Da bi izboljšal proces poucevanja je Kocen napisal nekaj geografskih ucbenikov in zbral razlicne stenske in namizne karte. Nedvomno je Kocenov glavni dosežek njegov šolski geografski atlas. Ko je l. 1861 izšla prva izdaja njegovega atlasa (Kocen's Geographischer Schul-Atlas für die Gymnasien, Real- und Handels-Schulen) kot prvega šolskega geografskega atlasa za uporabo v deželah Avstrijskega cesarstva, je bil znanstvena in didakticna senzacija. Prvic so ucitelji geografije dobili prirocnik v obliki atlasa, ki je bil usklajen z ucnim nacrtom dežel cesarstva. Po prvi izdaji je bil atlas deležen številnih izboljšav in prilagoditev novim zgodovinskim okolišcinam, tudi po avtorjevi prezgodnji smrti, in je tako pustil trajen pecat na šolski geografi­ji v vseh srednjeevropskih državah. Na temelju Kocenove predloge so kmalu sledile prilagojene izdaje v hrvašcini, cešcini, madžaršcini in poljšcini. Tako je ta atlas postaj najpomembnejši geografski šolski atlas v Avstro-Ogrski. V 19. stoletju sta bili geografija in kartografija prepoznani kot pomembno orodje hrvaške kulturne nacionalne identitete, še posebej v izobraževalni razsežnosti. V skladu s tem je sedemdeseta in osemdeseta leta 19. stoletja zaznamoval pojav prvih geografskih ucbenikov in prirocnikov v hrvaškem jeziku. V okviru prilagajanja šolskih programov novim okolišcinam se je zacela razvijati hrvaška šolska kartografija, pri cemer je ime Blaža Kocena igralo še posebej pomembno vlogo. Kocenov šolski atlas, ki ga je leta 1887 prevedel in prilagodil hrvaškemu šolskemu programu Augustin Dobrilovic, je bil prvi zemljepisni atlas v hrvaškem jeziku. V obdobju med letoma 1887 in 1943 je izšlo okoli dvajset hrvaških izdaj, njihovi uredniki pa so bili najvidnejši profesorji geografije, kot npr. Petar Matkovic, Hinko Hranilovic, Josip Modestin, Milan Šenoa, pri pripravljanju izdaj v letih 1934, 1838 in 1939 pa je sodeloval tudi slovenski geograf Valter Bohinec. Kocenovi atlasi so imeli kljucno vlogo pri pouku geografije in so bili poleg ucbenikov najpomembnejše sredstvo geografskega izobraževanja na Hrvaškem. V prispevku smo analizirali pomen Kocenovih atlasov za razvoj hrvaške šolske kartografije. S primerjavo nemških in hrvaških izdaj med letoma 1887 in 1943 smo predstavili razvoj na podrocju tiskanja zemljevidov, kartografskih tehnik, jezikovnih redakcij toponimike in vkljucevanja tematskih kart ter vpliv politicnega diskurza (nemški centralizem proti slovanskim nacionalizmom) na geografski obseg in vsebi­no zemljevidov, ki so jih uporabljali v izobraževalnem procesu. KRAJEVNA SKUPNOST POD DROBNOGLEDOM V PROSTORU IN CASU Matjaž Geršic: Krajevna skupnost Lesce: V prostoru in casu. Lesce, Krajevna skupnost Lesce, 2021, 247 strani. Obravnava manjših prostorskih enot – naselij, vaških in krajevnih skupnosti, obcin – se obicajno povezuje z obletnicami pomembnih dogodkov, rojstev in smrti. Lesce vecina prebivalcev Slovenije pozna kot središce športnega in jadralnega letenja ter po slikovitih panoramskih preletih Dežele in Blejskega kota. Manj pa je znano, da so bile v pisnih virih (Nantwnova listina) prvic omenjene pred 900 leti. Obeleženje castitljive obletnice pa ni bil edini razlog, da se je geograf Matjaž Geršic lotil obsežne analize krajevne skup­nosti, v kateri živi. Že v preteklih desetletjih (1984, 1987, 1998, 1999, 2012) so razlicni avtorji osvetlili razvoj šolstva, pregledali kulturno in cerkveno zgodovino, izdali obsežen zbornik ali drobne knjižice za turisticne namene ipd. Geršicevo delo pa tem posame­znim študijam dodaja celovit pregled obstojecih virov, pri cemer izstopata zgodovinski in geografski vidik. Kot takšno je delo uporabno za izobraževalne namene, služi pa tudi kot izjemno vsebinsko in slikovno bogat vir informacij tako domacinom kot obiskovalcem. V devetih vsebinskih poglavjih je predstavljena zanimiva in bogato ilustrirana zgodba krajevne skupnosti v prostoru in casu. Uvodoma avtor predstavi razlicna ze­mljepisna in ledinska imena, tudi imena ulic in domacij, s katerimi je povezano preu­cevano obmocje (na primer Lesce so bile v toku zgodovine poznane kot: Lezeza, Lez, Lescz, Lescha, Less, Losch, Leess itd.). Logicno sledi poglavje o administrativni ure­ditvi in njenem razvoju. Osrednji vsebinski del sistematicno sledi Hettnerjevi shemi geografske znanosti. Geršic najprej predstavi naravno- (kamnine in površje, vodovje, podnebje, prsti, rastlinstvo in živalstvo), nato pa družbenogeografske znacilnosti (po­selitev, prebivalstvo, gospodarstvo – kmetijstvo, obrt, trgovina, industrija, turizem, promet in komunikacije) preucevane krajevne skupnosti. Obsežno je tudi peto pog­lavje, namenjeno pregledu splošne zgodovine, ki vkljucuje podrobnejši pregled po zgodovinskih dobah (antika, srednji vek, novi vek, 1. svetovna vojna in obdobje po njej, 2. svetovna vojna in obdobje po njej). Bogata sakralna dedišcina župnije Lesce je predstavljena v šestem poglavju. Sledi krajše poglavje o razvoju in razvejanem delova­nju društev. Posebno pozornost je avtor namenil razvoju šolstva, otroškega varstva in kratkemu opisu nekaterih najpomembnejših izobražencev iz krajevne skupnosti (npr. pomembni sodniki, cerkveni dostojanstveniki, meceni, pravniki). Vse, ki si predstave o prostoru najbolje oblikujete s pomocjo slikovnega gradiva, bo razveselilo zadnje poglavje (str. 206–229), ki s pregledom obstojecega kartografskega in drugega slikov­nega gradiva (razglednice, fotografije) bralcu nudi še vizualno pridobivanje informa­cij. Vsebinskim poglavjem sledi tudi navedba virov in literature. V delu je veliko zanimivosti, ki so nedomacinom verjetno manj poznane: izstopa izjemen prometni položaj Dežele, pa nekdanja pivovarna, številne prigode, povezane s prihodom pomembnih ljudi na leško železniško postajo ipd. Monografija je izjemno pregledna, lepo in skladno oblikovana, odlikuje jo skrb za lep in jasen jezik, kar je posledica avtorjevega vecletnega skrbnega dela v arhivih, pa tudi kontinuiranega terenskega dela – od pogovorov z domacini, do fotografiranja in natancnega dokumentiranja. Kot je zapisal poet in geograf Oton Župancic, a bomo malce preoblikovali v: »Veš, geograf, svoj dolg?!« – kolega Geršic je to nalogo vec kot odlicno opravil, pricujoce delo pa je vsem nam za vzgled in spodbudo. Irma Potocnik Slavic PREGLED ZGODOVINE SLOVENSKE SKUPNOSTI V ELYJU, MINNESOTA/POLITICNA PARTICIPACIJA SLOVENSKIH ETNICNIH SKUPNOSTI V ZDA. ŠTUDIJA PRIMEROV V CLEVELANDU, OHIO, IN ELYJU, MINNESOTA Matjaž Klemencic, Tadej Šeruga: Pregled zgodovine slovenske skupnosti v Elyju, Minnesota. Maribor, Univerzitetna založba Univerze, 2019, 426 str. Matjaž Klemencic, Tadej Šeruga, Milan Mrdenovic: Politicna participacija slovenskih etnicnih skupnosti v ZDA. Študija primerov v Clevelandu, Ohio, in Elyju, Minnesota. Maribor, Univerzitetna založba Univerze, 2020, 486 str. Matjaž Klemencic sodi med ustvarjalne avtorje s podrocja izseljevanja Slovencev in slovenskega izseljenstva v ZDA. Kar tu razgrinjam bralcem in bralkam je le deloma »klasika« Klemencicevega ustvarjanja, ker v marsicem presega (sploh po vsebini) do­sedanje (prav tako zajetne) podrobne opise ameriške kulturne pokrajine skozi konte­kste slovenske ameriške priseljenske zgodovine. Obe deli (izšli sta v letih 2019 in 2020 pri mariborski univerzitetni založbi v zbirki Zora) zajemata obmocje Velikih jezer in podrobneje obravnavata zgodovinsko usodo dveh zelo razlicnih geografskih okolij, katerima je skupna navzocnost slovenskih priseljencev. Tako Ely kakor Cleveland sta zapisana med »velikimi« slovenskimi etnicnimi naselbinami v ZDA. Med krajema so velike razlike že po legi, velikosti in vplivu. Ely je majhna rudarska kolonija v zakotju severne Minnesote. V življenje ga je priklicalo izkorišcanje bogatih zalog odlicne že­lezove rude v Mesabi Range. Po ambientu deluje nekako severnjaško; nizka in v gro­bem uravnana pokrajina s številnimi jezeri in barji mocno spominja na slovito finsko jezersko pokrajino. Ne cudi, da je bilo prav Fincev med priseljenci zelo veliko. A ni jih bilo vselej najvec. Najštevilcnejšo etnicno skupnost so oblikovali Slovenci. Klemencic zato v delu upraviceno govori o »najbolj slovenskem« naselju v ZDA. Cleveland pa je druga, starejša ameriško-slovenska zgodba. Milijonsko mesto (urbano obmocje) ob jezeru Erie je srkalo vase malodane vse, kar se je prek Ellis Islanda (in drugih ame­riških pristanišc) zgrinjalo proti predelom ameriške sredine in dalje proti zahodu, išcoc delo v rudarstvu in industriji. Tudi Slovenci so bili med njimi. Tam so oblikovali nesporno najvecjo slovensko zgostitev v ZDA. Številcna razmerja so pozneje omogo­cila slovensko angažiranje tudi na politicnem podrocju. Usodi obeh mest postaneta ob vseh razlikah presenetljivo povezani, ne pa tudi cisto zares podobni. Da bi laže razumeli kontekst in povezanost obeh mest, je treba seci v zacetke Kle­mencicevega raziskovalnega opusa. Sredi osemdesetih let prejšnjega stoletja je pri­cel z raziskovanjem zgodovine ameriških Slovencev. Poglavitna metoda, pravzaprav pristop, je bil temeljito terensko in arhivsko delo, ki je vkljucevalo analizo popisnih podatkov, imenikov, poslovnih imenikov, župnijskih arhivov in drugih možnih vzpo­rednih evidenc (poleg seveda uradnih), ki so dovoljevale in omogocile rekonstrukci­jo slovenskih priseljenskih skupnosti v njihovem novem toposu. Te je imenoval kar (slovenske) etnicne naselbine. Dobrih 800 jih je širom ZDA in vsaka ima svojo zgo­dovino in številne zgodbe. Klemencic se je usmeril k rekonstrukciji naselbin, ki so po pravilu pozneje ostale le skupnost, lokacije pa razen nekaj materialnih ostalin ter imen – ter seveda zgodb – zgodovina. V takem pristopu vidim veliko elementov his­toricne geografije, za katero je razumevanje zgodovinskih tokov in vodilnih procesov prav tako kljucno kakor natancna razclenitev in kriticna analiza omenjenih arhivskih virov. Poseben šarm je seveda odkritje sedanje skupnosti slovenskih Americanov ter njihova socialno-prostorska evolucija. Clevelandu so sledile analize še mnogih krajev; od pensilvanskih rudarskih kolonij do (prav tako rudarskih) predelov onstran prerije do Pacifika: Leadville, Rock Springs, St. Louis, Pueblo, Denver, San Francisco, Jolliet pa Barberton in Bethlehem ter še nekateri. Ely je prišel na vrsto bolj na koncu, zato so sistematika dela, metode in pristopi za avtorja (in soavtorje, njegove doktorske študente) že v dobršni meri preizkušena rutina, predhodne izkušnje pa priložnost za primerjavo ter teoreticna ter metodološka razglabljanja. »Ely« je zato po mojem najbolj geografizirano delo, ki ga je pripravil kak zgodovinar. Za razliko od Clevelanda, Minneapolisa, Denverja, San Francisca, Leadvilla ali Pu­ebla, kjer so bile »slovenske naselbine« sorazmerno manjši del pestrega priseljenskega mozaika vecinoma velikih mest, je Ely majhen in odmaknjen kraj, a »slovenski« za­radi relativno zelo mocne slovenske lokalne skupnosti. Avtorjema (Klemencic, Šeru­ga) je Ely lahko ponudil izjemno priliko ugotavljanja družbeno-prostorskega vedenja lokalne skupnosti v pogojih relativne številcnosti. Ely je »slovenski Ely«, a obenem tipicno ameriški, ce ga opazujemo z gledišca družbenega razvoja in kulture. V tem se kaže ne le ucinkovitost ameriškega talilnega lonca, temvec tudi trdoživost etnicnih diaspor, ki lahko ohranjajo svoj etnicni substrat prav zaradi tega, ker jih je amerikani­zacija sprejela v svoj populacijski kontingent na podlagi svobodne volje in z nudenjem vrste individualnih prednosti. Po drugi strani je geografska izolacija redko naseljene Minnesote faktor utrjevanja lokalne skupnosti in posredno s tem tudi njene (ocitno vecplastne) identitete. To, kar imenujemo slovenska diaspora, ima v knjigi upravice­no skoraj ves cas naziv »slovenski Americani«. Posebno težo pa dajejo delu natancni prikazi gospodarske in politicne zgodovine severovzhodne Minnesote, v kateri so slo­venski kolonisti vsaj v Elyju odigrali zelo pomembno vlogo. Knjigo sestavlja devet poglavij. Uvodni del vsebuje poleg orisa nacina dela, pristo­pov oziroma metodologije še ocene raziskovalne uporabnosti terenskih in arhivskih virov. Ta del je še posebej primeren za študente in raziskovalce, z vrsto koristnih iz­kušenj in napotkov v zvezi z rabo virov. Drugo, tretje in cetrto poglavje vsebujejo širši prikaz zgodovine Elyja in Minnesote. Morda bi bil videti tako širok in obsežen pristop skoraj pleonazem, ce ne bi bila zgodovina slovenskih Americanov tako moc­no vezana na silovit vzpon ameriškega rudarstva (in industrije) v casu glavnega vala slovenske imigracije na ameriško celino (in je v tem pogledu Ely pac skoraj vzorcna »zgodba«), na njegov zaton in posledicno krizo teh okolij, v tem primeru pa tudi na ponovno oživljanje v terciarni paradigmi. Vmes sta avtorja podrobneje prikazala še posebnost: prizadevanje lokalne skupnosti za zašcito okolja. Podrobno je opisana dol­ga pot razglasitve nekaterih zavarovanih obmocij v vzhodnih delih Minnesote in skrbi za zašcito voda Gornjega jezera. Kolonizacijska zgodovina teh predelov se je zacela nekako z nastopom »zlate mrzlice« v drugi polovici 19. stoletja. Iskalci niso našli ple­menite kovine, pac pa bogate zaloge železove rude. Rudarstvo in nekaj še metalurgija sta postala gonilna gospodarska panoga za dobrega pol stoletja. Avtorja sta prika­zala vzpon te panoge zelo natancno in v povezavi še z drugimi kraji v ZDA. Bralec dobi zelo veliko informacij o tem burnem ameriškem obdobju. V teh procesih so sodelovali tudi Slovenci. Posebej je prikazan številcni razvoj slovenskih naseljencev v Minnesoti glede na ameriške statisticne vire. Zadnje poglavje predstavlja zelo podro­ben prikaz politicnega življenja, organizacije in delovanja slovenskih Americanov. Ely, kraj z rudarsko-industrijsko popotnico nosi med vsemi slovenskimi »naselbinami« v ZDA primat glede na dolgotrajno in ucinkovito politicno delovanje lokalne slovenske diaspore. Dolgo je bila številcno najmocnejša skupnost v kraju in to se je poznalo tudi pri uspešnem politicnem delovanju, kljub relativno skromni ekonomski moci slovenske skupnosti. Toliko bolj pa so izstopali nekateri posamezniki, ki so dosegli zelo pomembne položaje v ameriškem kongresu in senatu. Druga knjiga (Politicna participacija slovenskih etnicnih skupnosti v ZDA) je smisel­no nadaljevanje in poglobitev »Elyja« in mnogih predhodnih monografij pri obravna­vi te tematike, obenem pa specializacija, poglobitev in na nek nacin tudi teoretizacija Klemencicevega raziskovanja slovenskega izseljenstva v ZDA. Na ta vidik opominja termin slovenski Americani in s tem jasno izpostavi identitetne premene demosa, ki se je v medgeneracijskih premenah preoblikoval podobno, kot so se druge etnicne skupnosti, ki so ob prvi naselitvi prav tako kot slovenske oblikovale lokalno zaokrože­ne, a nikakor ne zaprte skupnosti. Druga knjiga razgrinja politicno participacijo slovenskih Americanov v dveh zelo razlicnih okoljih: v Clevelandu v Ohiu ter v Elyju v Minnesoti. Izbira krajev je omogocila paralelno sledenje socialnim spremembam, znacilnostim družbenih oko­lij, gospodarski zgodovini in angažiranju ameriških Slovencev na polju politicnega de­lovanja. Slovenski kolonisti so se v medgeneracijskem asociiranju v ameriško družbo »amerikanizirali« v slovenske Americane. Integracijski okvir je sicer zelo širok, a prav politicno delo prica o uspešnosti integracije, o identifikaciji z okoljem in prevzemom zavesti, da je smiselno (ce ne nujno) vsakomur poiskati svoj modus operandi po ame­riško in s tem vstopati v sfere priložnosti, ki jih nudi ameriška družba. Delo podrobno analizira politicno angažiranje v Elyju in Clevelandu in poleg že nekaterih znanih ob­razov (od Lauscheja, pa Blatnika, Oberstarja ali sedaj Amy Klobuchar) razkriva dolgo vrsto oseb, ki so dale politicni pecat svojemu okolju, nekatere pa so segle tudi bistve­no višje. Poznejši razvoj jih je iz pretežno delavskega razreda profiliral (oziroma so se sami) v znacilne poklice srednjega sloja, s tem pa posameznikom omogocil plezanje po družbeni lestvici. Politika je postala možnost šele potem, ko so posamezniki (pa tudi posameznice) že dokazali zmožnosti preboja v ameriški družbi. Politicno življenje je ekskluziven dokaz sinhronizacije slovenskega etnicnega elementa v ameriški miselni tok, tradicijo, vrednote in identiteto. Zgodi se lahko, ko je koncan prehod iz evropske etnicne tradicije, naslonjene na jezik in ožja teritorialna okolja, pojmovana kot »domo­vina«, in se preoblikuje v konglomeratno ameriško družbo, za katero je znacilna identi­tetna enotnost izvorno razlicnih Americanov. Znacilnost te etnicno-kulturne evolucije je, da se z integracijo posamezni fragmenti izvorne etnicne identitete nadaljujejo zato, ker je to ameriški slog identifikacije. Zunanji izraz tega procesa je sprošcena vpetost v dinamicno ameriško okolje. Izvorni (v našem primeru) slovenski vidiki organizacije v domove, društva, klube in druge oblike paternalisticnih organizacij so posameznikom, ki so se lotili politicnih karier, izjemno dragoceno izhodišce in tvorijo bazicno družbeno omrežje, v nekaterih primerih pa tudi volilno bazo. Tu sta si Ely in Cleveland dokaj raz­licna. V majhnem Elyju je slovenski etnos ocitno zaradi mrežne organiziranosti lahko racunal na svoje lastno zaledje, a je moral za prepricljivo zmago poseci po interpretaciji skupnih lokalnih problemov in perspektiv; zgolj »slovenskost« kandidata ni bila dovolj. V multikulturnem clevelandskem okolju tak pristop ne deluje in tisti, ki so v politiki videli karierno opcijo, so morali skrbno preracunati zlasti socialne in prostorske pro­bleme, iskati kompromise in bistveno preseci miljeje nekdanjega etnicnega izvora. A nic manj ni bilo pomembno, da so v svojem izvorno-etnicnem (sedaj znacilno ameriškem) socialnem okolju dobili prvo potrditev in zaslombo, kar je omogocilo njihovo profilira­nje v obeh kljucnih politicnih strankah v ZDA in s tem odprlo pot na politicne položaje. Izkušnje kažejo, da je slovenski volivec iskal svoje mesto pretežno v Demokratski stran­ki. Drugi, morda še bolj prepricljiv modus je bilo delavsko izvorno okolje. Demokratska stranka še sedaj racuna tudi na to, ce je soditi po npr. novejših predstavnikih slovenskih korenin v sodobni ameriški politiki. Jernej Zupancic PRIROCNIK ZA PREPOZNAVANJE IN NACRTOVANJE ZELENE INFRASTRUKTURE Mitja Bricelj (urednik): Prirocnik za prepoznavanje in nacrtovanje zelene infrastrukture. Ljubljana, Inštitut za vode Republike Slovenije, Ministrstvo za okolje in prostor, 2021, 96 strani. Prirocnik za prepoznavanje in nacrtovanje zelene infrastrukture (Prirocnik) je rezul­tat vecletnih strokovnih prizadevanj Ministrstva za okolje in prostor ter Inštituta za vode Republike Slovenije za implementacijo koncepta zelene infrastrukture v Sloveni­ji, pa tudi doprinos k razvoju samega koncepta in njegove vloge na podrocju regional­nega planiranja. Urednik Prirocnika je dr. Mitja Bricelj (Ministrstvo za okolje in pros­tor), avtorji pa so sodelavci Inštituta za vode Republike Slovenije ter zunanji sodelavci. Namen strokovnega prirocnika je spodbuditi in okrepiti rabo koncepta zelene infrastrukture kot okvira za sodelovanje razlicnih sektorjev, ki posegajo v prostor, predvsem sektorjev ohranjanja narave, urejanja prostora in upravljanja voda. Cilj Prirocnika je »izboljšati vkljucevanje ekoloških sistemov in naravnih zeleno-vodnih obmocij, ki jih predstavljajo gozdovi, celinske vode, morje ipd. v procesih nacrtova­nja« (str. 13). Prirocnik je namenjen vsem, ki so kakor koli soudeleženi v postopkih nacrtovanja in urejanja prostora, predstavlja pa tudi strokovno gradivo za ozavešcanje in izobraževanje strokovne in laicne javnosti. Opredelitev koncepta zelene infrastrukture sledi pogledom Evropske komisije iz leta 2013. Zelena infrastruktura je zato opredeljena kot strateško nacrtovana mreža visokokakovostnih naravnih in polnaravnih obmocij, ki je zasnovana in upravljana tako, da zagotavlja široko paleto ekosistemskih storitev in šciti biotsko raznovrstnost tako v podeželskih kot mestnih okoljih. Zelena infrastruktura se tako nanaša na pro­storsko strukturo, ki omogoca ljudem koristi narave in je namenjena povecanju spo­sobnosti narave za zagotavljanje vec dragocenih dobrin in storitev ekosistema. Prirocnik je osredinjen okrog štirih temeljnih poglavij. V uvodu je opredeljen širši kontekst, v katerega je umešcen koncept zelene infrastrukture kot pristop k doseganju trajnostnega razvoja s kljucnim sporocilom: »ohranjanje in nacrtovanje zelene infra­strukture je koristno ne le za biotsko raznovrstnost, temvec tudi za cloveka in njegovo dolgorocno blaginjo« (str. 11). Avtorji Prirocnika se torej zavedajo, da je varovanje biot­ske raznovrstnosti, ugodnega stanja ekosistemov ter ohranjanje pokrajinskih in ekosi­stemskih storitev kljucnega pomena za cloveka – za njegov obstoj in za razvoj cloveške družbe v kontekstu trajnostnega razvoja. V nadaljevanju uvodnega poglavja so prika­zani zacetki, razvoj in uporaba termina »zelena infrastruktura«, izpostavljene so dileme pri njegovi uporabi in razlicna razumevanja. Sklep uvodnega poglavja opisuje postopek nastanka prirocnika, namen in cilje ter ciljno strokovno (in politicno) javnost. V drugem poglavju so natancno opredeljena strokovna izhodišca: od opredelitve zelene infrastrukture, s terminom nelocljivo povezan koncept ekosistemskih storitev, pa tudi znacilnosti in vloga koncepta zelene infrastrukture na razlicnih prostorskih ravneh. Prikazani so pomembnejši elementi, ki opredeljujejo zeleno infrastrukturo, tehnicno-metodološka izhodišca (postopek prepoznavanja zelene infrastrukture), pa tudi pravna izhodišca. Posebno dragoceno je tretje poglavje, ki prikazuje dosedanje izkušnje in dobre pra­kse implementacije koncepta zelene infrastrukture na razlicnih prostorskih ravneh, s cimer Prirocnik dokazuje široko poznavanje samega koncepta, hkrati pa prepoznava veliko uporabnost in še ne izkorišcene potenciale za uporabo koncepta pri nacrto­vanju razvoja v prostoru na razlicnih prostorskih ravneh in v razlicnih normativnih okoljih (prekomejno, makroregionalno). Cetrto poglavje prikazuje poglede avtorjev Prirocnika o vsebinski vrednosti in prakticni uporabnosti koncepta. Pri tem se sklicujejo na obstojeco zakonodajo v Slo­veniji, kar Prirocniku daje veliko aplikativno vrednost. V nadaljevanju Prirocnika so podrobnejše opredeljene metodološke in pravno­-normativne vsebine, ki so za uporabnika prirocnika pomembna dodatna informa­cija, s katero lahko metodološko in pravno utemelji nove inovativne nacine uporabe zelene infrastrukture kot okvira za reševanje navzkrižij v prostoru in naslavljanje ak­tualnih razvojnih izzivov. Prirocnik v dodatku z metodološkimi podlagami ponuja kot orodje za pripravo strokovnih podlag za nacrtovanje v kontekstu koncepta zelene infrastrukture me­todo, ki pomaga prepoznavati »zelenost« prostora oziroma prepoznavanje, koliko je elementov v prostoru, ki opredeljujejo zeleno infrastrukturo. Gre za model, ki na podlagi logicnega postopka opredelitve osnovne prostorske enote, izbora kriterijev, ocenjevanja pomembnosti izbranih kriterijev analizira prostor z vidika prisotnosti posameznih kategorij, ki so podlaga za opredelitev zelene infrastrukture na obrav­navanem prostoru. Ker izhaja iz pravnih režimov, je neposredno uporabna predvsem na podrocju podrobnejše analize prostora ter ocene prisotnosti in vrzeli elementov, ki opredeljujejo zeleno infrastrukturo v kontekstu prostorskega nacrtovanja na lokalni ravni. Z ustrezno prilagoditvijo metode je mogoce analizo zelene infrastrukture opra­viti tudi na višjih prostorskih ravneh. Besedila so kljub dolocenim dilemam in razlicnim razumevanjem terminov in konceptov med strokami poenotena in razcišcena do te mere, da je Prirocnik razum­ljiv tudi manj poucenemu bralcu in uporabniku, a hkrati ostaja strokovno korekten. Uporabljene opredelitve in definicije namrec izhajajo iz dokumentov, ki so objavljeni na ravni celotne Evropske unije, hkrati pa išcejo najmanjši skupen imenovalec med sektorji, ki prav tako izhajajo iz konceptov ekosistemskih storitev in zelene infrastruk­ture pri nacrtovanju razvoja v prostoru. Jasnost in nazornost Prirocnika povecujejo tudi številne sheme in kartografski prikazi ter ilustrativni primeri v blokih. Slednji spremljajo Prirocnik od opredelitve koncepta do njegove implementacije. Kljucni doprinos Prirocnika je temeljno izhodišce – kompleksni pogled na prostor, ki je nujna predpostavka za iskanje odgovorov na številne aktualne izzive prostorske­ga in regionalnega razvoja ter doseganje trajnostnega (prostorskega) razvoja. Po svoji vsebini in strukturi gre za inovativen regionalno-planerski pristop na podrocju zelene infrastrukture in njene vloge pri razvoju v prostoru ter doseganja ciljev na podrocju varstva okolja v kontekstu zagotavljanja ekosistemskih storitev. Prirocnik je pomem­ben doprinos k uveljavljanju potencialov, ki jih prinaša zelena infrastruktura na nižjih prostorskih ravneh v Sloveniji, in koristno gradivo za vse, ki (strateško) nacrtujejo prostorski razvoj v bolj trajnostno in zeleno smer. Prirocnik je primerno izhodišce za nadaljnji razvoj pristopa, predvsem v smeri nadgradnje metodološke podpore za prepoznavanje in nacrtovanje zelene infrastruk­ture, na primer z zasnovo novih orodij za strateško nacrtovanje zelene infrastrukture (analize prostora skozi koncepte jedrnih obmocij, stopalnih kamnov in koridorjev) na razlicnih prostorskih ravneh (lokalna, regionalna, prekomejna, nacionalna), vkljucno s podrobnejšimi usmeritvami/preucitvijo možnosti za dejansko umešcanje elementov zelene infrastrukture v prostor v dialogu z drugimi strokami, nosilci urejanja prostora in predstavniki naravovarstvenikov. Prirocnik je bil izdan tudi v angleškem jeziku, kar bo prispevalo k prepoznavanju koncepta tudi v širšem prostoru. Simon Kušar NOVI PRISTOPNIKI V KMETIJSTVO: UPORABA IN UCINKI REZULTATOV PROJEKTA NEWBIE Raziskovalci in praktiki širom držav EU že dalj casa opažamo skromno izmenjavo znanja (med univerzami in razlicnimi ciljnimi skupinami), šibko inovativnost ter pomanjkljivo sodelovanje med razlicnimi deležniki in akterji na podeželju. Zato je programsko obdobje 2014–2020 na ravni Evropske unije v vec programih (npr. Ob­zorje 2020, Program razvoja podeželja, Erasmus Knowledge Alliance, Interreg itd.) in preko razpisanih tem naslavljalo navedena vsebinska težišca. Sodelavci Oddelka za geografijo FF UL smo se preko fokusne skupine, ki jo je odlic­no organiziralo Evropsko partnerstvo za inovacije (pri DG-AGRI) v letu 2015, pove­zali z vec raziskovalnimi ustanovami in deležniki na podeželju iz razlicnih evropskih držav. Ugotovili smo, da se kmetijski sektor sooca s prepocasno revitalizacijo znotraj družinskih kmetij, hkrati pa se pojavljajo raznovrstni akterji, ki bi radi kmetovali, a se morajo pogosto soocati z zelo zahtevnimi ovirami. V letu 2018 je konzorciju desetih partnerjev iz devetih držav (Irska, Združeno kra­ljestvo, Bolgarija, Nizozemska, Portugalska, Belgija, Nemcija, Francija, Slovenija) uspelo na razpisu Obzorje 2020 s projektno prijavo NEWBIE: New Entrant netWork: Business models for Innovation, entrepreneurship and resilience in European agriculture pridobiti 2 milijona EUR sredstev (za tematske mreže; št. pogodbe: 772835). O štiriletnem projektu smo vas uvodoma že informirali v reviji Dela (Dela 50, 2019, str. 153–156), ker pa se je projekt 31. 12. 2021 zakljucil, želimo predstaviti glavne projektne rezultate. V projektu NEWBIE smo preucevali nove pristopnike v kmetijstvo: mednje pri­števamo novince (vsakdo, ki se povsem na novo vkljuci v kmetijsko dejavnost) in naslednike (se vkljuci v obstojeco kmetijo in vpelje nov poslovni model). Novi pris­topniki so razlicnih starosti, z raznolikimi izkušnjami v kmetijstvu in z raznovrstnim dostopom do virov. Dejstvo je, da se novi pristopniki soocajo s številnimi in razlicni­mi ovirami, kot so: dostop do kmetijske zemlje, dostop do kapitala, dostop do pravih informacij, dostop do trgov ipd. Pri novih pristopnikih nas je zanimalo dvoje: njihov vstopni (nacini vstopanja v kmetijstvo) in poslovni model (njegov razvoj in širjenje), saj obicajno v kmetijski sektor prinašajo nove vešcine, znanja in mreže ter prispevajo k širjenju inovacij. Rdeca nit celotnega projekta je »pristop NEWBIE«, ki je vodil k sooblikovanju podpornega okolja za nove pristopnike v kmetijstvo in je vkljuceval: 1. prepoznavanje novih pristopnikov na terenu: posneli smo 90 kratkih videozgodb, ki predstavljajo njihove vstopne in poslovne modele (povezava: www.youtube.com/channel/UCLMxm12dGFJuNdYtYzrWNeg/videos, do sedaj imajo vec kot 60.000 ogledov); pri tem prevladujejo modeli, ki so mocno vpeti v lokalno okolje in družbo (naslavljanje proizvodnih in tržnih vrzeli, ekološko kmetijstvo, kratke oskrbne verige, neposredna prodaja, diverzifikacija na kmetiji – pedagoške kme­tije, socialno varstvo na kmetijah, rekreacija in turizem, CSA – angl. Community supported agriculture ipd.); 2. oblikovanje in vkljucevanje v mreže, ki novim pristopnikom nudijo podporo: v sklopu projekta smo zasnovali Mrežo NEWBIE, v kateri sodelujejo novi pristopni­ki, obstojeci in bodoci kmetje, kmetijski svetovalci, ucitelji, raziskovalci, odloceval­ci in snovalci politik itd. (ima vec kot 700 clanov); obenem pa smo tudi evidentirali mreže, v katere so vkljuceni novi pristopniki v posameznih državah partnericah (npr. povezovanje francoskih novincev v mrežo podeželskih inkubatorjev); 3. mednarodno zbiranje podatkov o novih pristopnikih: s poglobljenimi intervjuji smo pridobili mednarodno primerljive podatke novih pristopnikov iz razlicnih kmetijskih panog, zlasti o tem, kako se sami, s partnerji oziroma družino lotevajo poslovnih modelov in najrazlicnejših ovir (90 intervjujev); 4. zasnovo nagrade NEWBIE, s katero se je povecala prepoznavnost novih pristop­nikov v družbi: 27 NEWBIE nagrajencev je v devetih državah potrdilo, da so novi pristopniki vrelec inovacij, ki pomembno (tako z gospodarskega kot širšega druž­benega vidika) vpliva na širjenje informacij in širšo promocijo kmetijskega sektorja kot zanimivega za zaposlovanje; 5. pripravo orodij (angl. toolkitov), ki so namenjena tako novim pristopnikom kot tudi odlocevalcem in snovalcem politik: sodelavci projekta NEWBIE smo izdela­li 11 orodij, ki pomagajo novim pristopnikom in njihovemu podpornemu okolju pri premagovanju ovir (kako priti do informacij, financ, kako vzpostaviti in razviti poslovni model, vkljucitev v podeželski inkubator, dostop do kmetijskih zemljišc, kako sprejeti odlocitev, da boš postal/a kmet/ica, odlocitev za diverzifikacijo na kmetiji, kako tržiti, vkljucitev v mreže – npr. pobuda km0 itd.). Kljucnega pomena pri tematskih mrežah pa je, na kakšen nacin prihaja do izme­njave znanja in v tem pogledu je projekt NEWBIE s svojim delovanjem spretno po­vezoval lokalne, regionalne, državne in mednarodne izkušnje novih pristopnikov v kmetijstvo, in sicer: • z organizacijo osmih nacionalnih diskusijskih krožkov v vsaki partnerski državi, ki so zainteresirani javnosti (mladi prevzemniki, novinci, obstojeci kmetje, študenti razlicnih smeri, kmetijski svetovalci, samostojni podjetniki, odlocevalci, ucitelji in raziskovalci itd.) predstavili, na kakšen nacin se je možno lotiti premagovanja ovir za nove pristopnike; v Sloveniji smo tako posebno pozornost namenili dostopu do kmetijskih zemljišc, financ, znanja in informacij ter trga; v okviru celotnega pro­jekta je bilo organiziranih vec kot 100 nacionalnih diskusijskih krožkov z vec kot 5000 udeleženci; • z oblikovanjem nacionalne usmerjevalne skupine v vsaki državi clanici: v Sloveniji je bila sestavljena iz desetih clanov (osem razlicnih ustanov in predstavnika novih pristopnikov), ki je predlagala, katere tematike in govorce/ke je smiselno vkljuci­ti v nacionalne diskusijske krožke, ocenjevala kandidate/ke za nagrado NEWBIE, skrbela za promocijo projekta v njihovem delovnem in širšem okolju ter spremljala projektne aktivnosti in rezultate; • z bilateralno (ali multilateralno) izmenjavo med državami partnericami: projektni partnerji, ki so razvili zanimive rešitve za premagovanje ovir (npr. podeželski in­kubatorji v Franciji, prenos kmetije na Irskem, razlicni nacini dostopanja do kme­tijskih zemljišc na Nizozemskem, okrepljeno tržno pozicioniranje novih pristop­nikov v lokalnem okolju na Portugalskem ipd.), so le-te predstavili gostom (novi pristopniki, kmetijski svetovalci, odlocevalci, raziskovalci, NEWBIE nagrajenci itd.) iz partnerskih držav sklopu enotedenskega obiska; • s ciljno naravnano promocijo NEWBIE nagrajencev (npr. na sejmih, strokovnih dogodkih, podeželskem parlamentu itd.), ki so prejeli prakticno financno nagrado, katero so lahko uporabili ali za snemanje samopromocijskega videa ali za izobraže­vanje v sklopu projekta NEWBIE ali za udeležbo na izobraževanju in usposabljanju po svoji izbiri; • z zasnovo t. i. transnacionalne dinamicne ucne agende, v sklopu katere je prišlo do redne in aktivne izmenjave izkušenj, znanj in informacij med državami partnerica­mi, ki imajo že razvite dolocene rešitve za nove pristopnike, in tistimi, ki še išcejo primerne rešitve za nove pristopnike v svojem okolju; • z organizacijo dveh odmevnih mednarodnih konferenc s tematiko novih pristopni­kov, in sicer v Ljubljani (februar 2020, 120 udeležencev) in Montpellierju (oktober 2021, 80 udeležencev v živo, 40 udeležencev je dogodku prisostvovalo na daljavo); • z izdelavo prosto dostopnih pedagoških gradiv (v angleškem jeziku, besedilo v Word in PPT formatu ter z glasovno podlago), ki so primerna tako za delo kme­tijskih svetovalcev kot tudi za poucevanje dijakov in študentov ter naslavljajo štiri kljucne tematike, ki so jih kot nujno potrebne izpostavili novi pristopniki in so se pokazale kot manjkajoce pri analizi obstojecega kmetijskega izobraževanja na srednjih, višjih in visokih šolah v državah partnericah (podjetništvo, tehnološke in družbene inovacije, proizvodne in tržne vrzeli, vešcine novih pristopnikov: diver­zifikacija v nekmetijske dejavnosti na kmetiji); • s pripravo priporocil za odlocevalce na lokalni, regionalni, državni in evropski rav­ni ter za financni sektor; izdelali smo tudi izjemno zanimivo ter obsežno zbirko 120 kratkih zapisov (angl. practice abstracts), ki na zgošcen nacin prikazujejo rešitev, ki jo je novi pristopnik ali njegovo podporno okolje preskusil/o, ko je reševal/o dolo­ceno oviro; objavljeni so tudi na spletni strani EIP DG Agri. Terenski del mednarodne konference v Montpellierju, ki je bila oktobra 2021 (foto: B. Lampic). Kaj je prinesel projekt NEWBIE slovenskim novim pristopnikom v kmetijstvo? Med ukrepi Programa razvoja podeželja je precej sredstev in besed namenjenih mla­dim prevzemnikom, v javnosti je zelo odmevna nagrada Inovativni mladi kmet. O popolnih novincih v kmetijstvo pa pred projektom NEWBIE v Sloveniji ni bilo go­vora, ceprav so se obdobno (obicajno v casu vecjih gospodarskih kriz) pojavljali. S tematskimi razpravami in predvsem z opozarjanjem na ovire, na katere trcijo tako novinci kot nasledniki, smo spodbudili tako razpravo, pa tudi iskanje rešitev – npr. kako bi tisti, ki bi želeli obdelovati kmetijska zemljišca in imajo dober poslovni nacrt, lahko prišli do kmetijskih zemljišc; kako si novi pristopniki išcejo, oblikujejo in razvi­jajo tržišce; katera znanja in informacije bi novi pristopniki v kmetijstvo nujno potre­bovali itd. Tako smo v Sloveniji izdelali pregledovalnik opušcenih kmetijskih zemljišc, ki je bil kot orodje predstavljen odlocevalcu (Ministrstvo za kmetijstvo, gozdarstvo in prehrano). Z izborom treh NEWBIE nagrajencev (Kmetija Zlate misli – družina Turinek, Kmetija pr´Ropet – Domen Virant in Kmetija pr´Andreco – Tilen Soklic) smo pomembno posegli tudi v medijski prostor in omogocili nagrajencem vecjo prepoznavnost ter s financiranjem izobraževanja ali bilateralnih obiskov predvsem pridobivanje novih informacij. Zelo smo zadovoljni tudi z razpravami v nacionalnih diskusijskih krožkih in angažiranim delom clanov slovenske usmerjevalne skupine. V casu priprave Strateškega nacrta skupne kmetijske politike za obdobje 2023–2027 smo z oblikovalci politike pripravili tudi predlog posebnega ukrepa za nove pristopni­ke, ki bi bili lahko starejši tudi od 40 let. Žal ta ukrep ni bil vkljucen v zakljucno verzijo dokumenta, ceprav so bili novi pristopniki prepoznani kot pomembna skupina na ravni EU (Farmers of the Future, junij 2019) in vkljuceni v slovenski Akcijski nacrt za ekološko kmetijstvo. Predvsem pa smo veseli, da so se vzpostavile številne nove pove­zave med samimi novimi pristopniki, razvile so se tudi že ideje za poslovno sodelova­nje, da so se povezali razlicni deležniki in akterji, ki sestavljajo podporno okolje novih pristopnikov. Oddelek za geografijo FF UL bo z raziskovanjem novincev nadaljeval tudi v prihodnje, in sicer v sklopu doktorske disertacije in bilateralnega raziskovalne­ga projekta z Belgijo. Veseli nas tudi, da je Univerza v Ljubljani prepoznala tematiko kot pomembno in so bila zato projektu dodeljena tudi sredstva Razvojnega sklada UL. Mednarodno odmevnost pa je dosegla tudi prva konferenca o novih pristopnikih (New entrants and their enviroments for dialogues) v Ljubljani, za katero je organizacij­ska ekipa prejela priznanje »Kongresni ambasador Slovenije za leto 2021«. Podrobnejši zapis o aktivnostih, rezultatih in nadaljevanju naših aktivnosti, pove­zanih z novimi pristopniki v kmetijstvo, si lahko preberete na spletni strani projekta NEWBIE: www.newbie-academy.eu. Irma Potocnik Slavic, Barbara Lampic in Sara Mikolic POROCILO DELAVNICE PROJEKTA SYSTEM (SHARE YOUR SOILS) V ESTREMADURI UVOD Oddelek za geografijo Filozofske fakultete Univerze v Ljubljani je eden od partnerjev mednarodnega projekta Share Your Soils (SYStem), ki ga financira Evropska unija v sklopu programa Erasmus+. Projekt, v katerega je vkljucenih 10 institucij iz Ceške, Estonije, Madžarske, Italije, Latvije, Poljske, Slovenije in Španije, se izvaja od 1. 10. 2019 do 31. 8. 2022. V tem obdobju se na obmocjih držav partneric zvrstijo eno­tedenske delavnice. Prvenstveno so namenjene preizkušanju mobilne aplikacije, ki služi kot orodje za zbiranje podatkov o prsteh na podlagi mednarodnega klasifika­cijskega sistema za poimenovanje tal (ang. World Reference Base for Soil Resources oz. WRB) (Mednarodni klasifikacijski ..., 2018). Poleg tega so delavnice namenjene tudi poglabljanju znanja o prsteh in pridobivanju izkušenj s podrocja njihove pravilne klasifikacije po WRB. Med 7. in 13. novembrom 2021 se je ena od delavnic odvila na obmocju španske Estremadure, kjer je bil glavni organizator oddelek za geografijo s Fakultete za filozofijo in književnost Univerze v Estremaduri, ki se nahaja v Caceresu. Pod mentorstvom doc. dr. Blaža Repeta smo se je iz Slovenije udeležili štirje študenti geografije: Tinkara Mazej, Tim Gregorcic, Sašo Stefanovski in Job Stopar. AKTIVNOSTI PO DNEVIH Prvi terenski dan Prvi dan smo priceli s sprejemom na Fakulteti za filozofijo in književnost, kjer nam je glavni organizator prof. Pulido Fernández predstavil osnovne naravnogeografske in družbenogeografske znacilnosti Estremadure ter okviren potek delavnice. Sledila je razporeditev v štiri mednarodne delovne skupine. Vsaka skupina je na terenski dan izkopala eno profilno jamo in nato dolocila tip prsti glede na WRB klasifikacijo. Uvodno terensko delo je potekalo v neposredni bližini fakultete. Maticno podlago na obmocju tvori skrilavec. Izkopali smo štiri profilne jame, eno na konveksnem površju, dve na pobocju in eno na dnu erozijskega jarka. V lokalno najvišji legi smo identifici­rali Dystric Skeletic Epiprotostagnic Leptic Regosol (Clayic, Ohric). Regosol je tip prsti, ki je slabo razvit in nima diagnosticnih horizontov ter se tako nahaja na repu WRB kljuca. Nižje smo tip prsti oznacili za Dystric Cambic Stagnosol (Loamic, Ochric), saj smo zaznali znake obcasnega zastajanja vode. Še malenkost nižje smo ponovno nale­teli na regosol. Ta je bil tokrat Dystric Skeletic Stagnic Leptic Regosol (Loamic, Ochric). Najnižje ležeca profilna jama je bila zasicena in pri dnu že zalita z vodo. Prst smo pre­poznali kot Dystric Endoskeletic Stagnic Gleyic Cambisol (Pantosiltic, Colluvic, Humic) zaradi diagnosticnega kambicnega horizonta. Dan smo zakljucili z obiskom srednje­veškega jedra Caceresa. Profilna jama 1: Dystric Endoskeletic Stagnic Gleyic Cambisol (Pantosiltic, Colluvic, Humic) (foto: M. Switoniak, 2021). Drugi terenski dan Drugi terenski dan smo priceli z obiskom vasi Cabańas del Castillo v osrcju UNESCO geoparka Villuercas Ibores Jara. Povzpeli smo se na vzpetino, kjer stojijo ruševine gradu iz casa islamske nadvlade nad Iberskim polotokom, in si ogledali monumental­ne kvarcitne izdanke, ki se vijejo v smeri SZ–JV. Pot smo nato nadaljevali proti kraju Navezuelas, kjer se je v okoliškem nasadu pravega kostanja (Castanea sativa) nahajalo naše drugo obmocje preucevanja. Nasad, ki je že sam po sebi nakazoval nizko efektiv­no nasicenost prsti z bazami ter kisle prsti, se je nahajal na jugozahodno orientiranem kvarcitnem pobocju na n. v. 980 m. Delovne skupine so izkopale 5 profilnih jam. Najvišji sta se nahajali nad nasadom, na najvišjem delu pobocja, kjer je erozija gradiva intenzivnejša od pedogeneze, zato so prsti tam najplitvejše (do 12 cm) in skeletne. Po WRB so bile klasificirane kot Umbric Hyperskeletic Leptosol (Humic, Siltic) in Distric Lithic Leptosol (Ochric, Siltic) ter vsebovale zgolj dva profila: humusni Ah in R oz. A in R. S spušcanjem vzdolž pobocja je globina prsti narašcala. Glede na ugotovitve iz tretje profilne jame se je nižje nahajal Dystric Cambic Skeletic Leptosol (Siltic). Ta ni vseboval erodiranega humusnega horizonta, je pa bil prisoten kambicni Bw, kar prst uvršca v genetsko starejši tip od prvih dveh. Kljub temu, da je kambicni hori­zont bil prisoten, ta ni bil dovolj razvit, da bi lahko prst klasificirali kot Cambisol. Na obmocju cetrte profilne jame se je nahajal Dystric Skeletic Leptic Cambisol (Loamic, Ochric) z dobro razvitim diagnosticnim kambicnim Bw horizontom. Najnižje se je z najvecjo globino (95 cm) nahajala peta profilna jama, kjer je bil prisoten Endoleptic Endostagnic Cambic Umbrisol (Epiloamic, Endosiltic) z diagnosticnim umbricnim ho­rizontom. Po koncanem terenskem delu smo si ogledali še samostan Guadalupe, del svetovne kulturne dedišcine UNESCO, kjer je bilo na enem mestu mogoce opaziti vec razlicnih zgodovinskih arhitekturnih slogov. Tretji terenski dan Tretji terenski dan je potekal v vinogradniški okolici Méride, ki leži v južnem delu Estre­madure. Kamninska podlaga obmocja je konglomerat terciarne starosti. Ponovno smo izkopali štiri profilne jame na razlicnih topografskih legah. Najvišje smo prepoznali Cal­caric Katoskeletic Leptic Regosol (Aric, Loamic, Ochric). Šlo je za edino profilno jamo, kjer smo dosegli preperelo maticno podlago. Nižje je profilna jama pokazala Cambic Mollic Umbrisol (Aric, Endoclayic, Colluvic, Epiloamic). Tukaj in nižje so bile profilne jame precej globlje, saj gre za obmocja akumulacije gradiva. Sledila je profilna jama s tipom prsti Haplic Luvic Calcisol (Loamic, Protovertic) zaradi vsebnosti karbonatov. Najnižje na obmocju, ki je bilo pred kratkim poplavljeno, smo identificirali Luvic En­docalcaric Phaeozem (Siltic, Colluvic, Hiperhumic, Pachic) zaradi molicnega horizonta in nasicenosti z bazami globlje pod površjem. Po klasifikaciji izkopanih profilnih jam je sledil ogled pridelave oljcnega olja in njegova degustacija skupaj z lokalnimi kozjim ter ovcjim sirom, vinom in jamonom. Terenski dan smo zakljucili z ogledom Méride, nekdanje prestolnice rimske Lusitanie, kjer smo si ogledali cudovito ohranjene ostanke amfiteatra in teatra, ki so v rabi še danes. Mesto je znano tudi po rimskem mostu, ki je dolg kar 790 metrov in je najdaljši ohranjen most svojega casa. Cetrti terenski dan Cetrti dan smo terensko delo izvedli na Portugalskem, na posestvu kmetije Defesin­has v bližini mesta Elvas. Na kmetiji prakticirajo ekstenzivno pašno živinorejo, kjer se živali nekaj mesecev prosto pasejo na dolocenem delu posestva, nato se premaknejo na drug del. Pokrajina je travnata in porasla z drevesi vrste hrast crnika (Quercus ilex) na n. v. okoli 230 m. Tri profilne jame smo izkopali na vrhu pobocja, eno v srednjem delu pobocja in zadnjo na dnu pobocja. Prst prve profilne jame na vrhu pobocja smo klasificirali kot Dystric Lithic Leptosols (Loamic), drugo pa kot Dystric Leptosols (Lo­amic). V obeh primerih gre torej za izredno plitve prsti z izraženo bazicnostjo. Hu­mozni A horizont je pri obeh zelo plitev (do 3 cm), kljub temu, da bi objektivne oko­lišcine nakazovale na možnost razvoja globljega humoznega horizonta. To bi lahko bila posledica intenzivnejše erozije prsti v preteklosti zaradi drugacne rabe tal. Glavni kvalifikator Lithic v prvem primeru nakazuje na zvezno kamnino, ki se je pojavila na globini 8 cm. Le nekaj metrov od prve profilne jame smo identificirali prst Dystric Stagnic Cambisols (Ochric, Siltic), pri kateri se globina prsti poveca na 45 cm, prst pa je uvršcena med kambisole. Tako je opazna velika variabilnost prsti na zelo majhnem obmocju. V osrednjem delu pobocja smo prst klasificirali kot Dystric Leptic Cambi­sols (Loamic, Ochric, Epichromic). Globina prsti se tu znatno poveca in doseže okoli 45 cm. Cambisols veljajo za zmerno razvite prsti. Ponovno je bila izražena bazicnost. Klasifikator Leptic nakazuje na zvezno kamnino, ki se je v profilu pojavila na globini 45 cm. Prst izraža teksturni razred meljasto-glinaste ilovice, kar oznacuje klasifikator loamic. Na dnu pobocja smo klasificirali prst kot Dystric Cambisol (Colluvic, Ochric, Siltic). Ponovno gre za zmerno razvite prsti. Globina prsti na dnu pobocja doseže 60 cm. V prsti smo zaznali koluvialno gradivo, ki je posledica premešcanja po pobocju navzdol. Po zakljucenem terenskem delu smo si ogledali portugalsko mesto Elvas, ki je umešceno tudi na seznam UNESCO in velja za enega lepših primerov utrjenih obrambnih mest novega veka z akvaduktom, ki je mestu nekoc dovajal vodo. Peti dan Zadnji dan smo se zjutraj povzpeli na razgledno tocko nad mestom Caceres, kjer se nam je odprl pogled na mesto in uravnano okoliško pokrajino. Po povratku v prostore fa­kultete je sledilo delo po skupinah. Pripravili smo koncne predstavitve terenskega dela, opisali vse opisane profile prsti in predstavili njihove kljucne znacilnosti. Prav tako smo profile vnesli v aplikacijo Share your soils, ki predstavlja glavni produkt projekta. Gre za izobraževalno družbeno omrežje, namenjeno opisovanju in klasifikaciji prsti po siste­mu WRB (About the project – SYStem, 2021). Aplikacija uporabniku omogoca deljenje profilov prsti, ki jih opremi s pripadajoco fotografijo, imenom, kot ga glede na kriterije doloca klasifikacija WRB, in lastnostmi prsti. Pred javno objavo primera prsti vnesene podatke pregleda in potrdi urednik strani. Uporabniki si med seboj lahko vnesene po­datke tudi komentirajo, kar omogoca izmenjavo mnenj. Sledila je koncna predstavitev, kjer je vsaka skupina predstavila glavne znacilnosti prsti na posameznih obmocjih, kjer smo izvedli terensko delo. Sledil je povzetek vseh ugotovitev, na koncu pa še razdelitev diplom udeležencem za uspešno opravljeno delo na projektni delavnici. ZAKLJUCEK Na koncu lahko sklenemo, da je enotedenski terenski seminar v Španiji služil kot odlicna nadgradnja našega dosedanjega znanja s podrocja pedogeografije, ki smo ga lahko v veliki meri uporabili tudi v praksi. V tednu smo se temeljito seznanili s te­renskim delom in pridobili kopico novega prakticnega znanja. Za nekatere od nas je bilo to še posebej dobrodošlo, saj je mnogo terenskega dela v letih pred tem (2020 in 2021, op. avt.) žal odpadlo. Izkušnja je bila še bolj kvalitetna zaradi edinstvenih fizicnogeografskih razmer in posledicno pedogenetskih dejavnikov, ki jih v Sloveniji in bližnji okolici ne moremo preucevati. Dejstvo, da smo pri klasifikaciji prsti uspešno sodelovali študentje iz razlicnih držav in iz razlicnih znanstvenih strok, le še poudarja in krepi pomembnost enotne svetovne klasifikacije prsti WRB ter uporabnost priroc­nika (Mednarodni klasifikacijski ..., 2018), ki se je za koristnega izkazal tudi v tem delu Evrope. Aplikacija bo uporabo omenjenega prirocnika le še dopolnila in izbolj­šala pravilnost rezultatov, ugotovljenih na terenu, kar bomo lahko s pridom izkoristili pri svojem nadaljnjem delu s prstmi. Literatura in viri About the project – SYStem [Share Your Soils]. URL: https://sites.google.com/site/sha­ reyoursoils/home (citirano 19. 11. 2021). Mednarodni klasifikacijski sistem za poimenovanje tal 2014: Mednarodni klasifikacijski sistem za poimenovanje tal in izdelavo legend na zemljevidih tal, posodobitev 2015. 2018. Prevod: Repe, B. Ljubljana: Znanstvena založba Filozofske fakultete Univer­ze v Ljubljani, Rim: Food and agriculture organization of the United Nations. DOI: 10.4312/9789610601159. Tim Gregorcic, Tinkara Mazej, Sašo Stefanovski, Job Stopar in Blaž Repe NAVODILA AVTORJEM ZA PRIPRAVO PRISPEVKOV V ZNANSTVENI REVIJI DELA 1. Znanstvena revija DELA je periodicna publikacija Oddelka za geografijo Filozofske fakultete Univerze v Ljubljani. Izhaja od leta 1985. Namenjena je predstavitvi znan­stvenih in strokovnih dosežkov z vseh podrocij geografije in sorodnih strok. Od leta 2000 izhaja dvakrat letno v tiskani in elektronski obliki (http://revije.ff.uni-lj.si/Dela). Revija je uvršcena v mednarodne baze (Scopus, CGP – Current Geographical Pu­blications, DOAJ, ERIH PLUS, GEOBASE, Central and Eastern European Academic Source, GeoRef, Russian Academy of Sciences Bibliographies, dLib.si, International Bibliography of the Social Sciences) in ima mednarodni uredniški odbor. 2. V prvem delu so objavljeni znanstveni clanki (1.01 in 1.02 po kategorizaciji COBISS). V drugem delu se objavljajo informativni prispevki v rubriki POROCILA, in sicer bi­ografski prispevki (obletnice, nekrologi), predstavitve geografskih monografij in revij, pomembnejše geografske prireditve in drugi dogodki idr. 3. Znanstveni clanki so lahko objavljeni v treh jezikovnih razlicicah: dvojezicno slo­vensko-angleško, samo v slovenskem jeziku, samo v angleškem jeziku. Prispevki mo­rajo imeti naslednje sestavine: • naslov clanka; • ime in priimek avtorja/avtorjev; • avtorjev poštni naslov (npr. Oddelek za geografijo Filozofske fakultete Univerze v Ljubljani, Aškerceva cesta 2, SI-1000 Ljubljana); • avtorjev elektronski naslov; • izvlecek (skupaj s presledki do 500 znakov); • kljucne besede (do 8 besed); • besedilo clanka (skupaj s presledki do 30.000 znakov; v primeru daljših prispev­kov naj se avtor predhodno posvetuje z urednikom); • v primeru enojezicnih clankov tudi povzetek/summary v drugem jeziku (skupaj s presledki od 5000 do 8000 znakov) ter prevod izvlecka in kljucnih besed v drugi jezik; • ime prevajalca. 4. Clanek naj ima naslove poglavij in naslove podpoglavij, oznacene z arabskimi šte­vilkami v obliki desetiške klasifikacije (npr. 1 Uvod, 2 Metode, 3 Rezultati in razprava, 4 Sklep, Literatura in viri ipd.). Razdelitev clanka na poglavja je obvezna, podpoglavja naj avtor uporabi le izjemoma. 5. Avtorji naj prispevke pošljejo v digitalni obliki v formatih *.doc, *.docx ali *.odt. Digitalni zapis besedila naj bo povsem enostaven, brez slogov in drugega zapletenega oblikovanja, brez deljenja besed, podcrtavanja in podobnega. Avtorji naj oznacijo le krepki in ležeci tisk. Besedilo naj bo v celoti izpisano z malimi tiskanimi crkami (velja tudi za naslove in podnaslove, razen velikih zacetnic), brez nepotrebnih krajšav, ok­rajšav in kratic. 6. Zemljevidi, graficne priloge in fotografije morajo upoštevati najvecjo velikost v ob­javljenem delu, to je 125 x 180 mm. Rastrski formati (*.tiff ali *.jpg) morajo biti odda­ni v digitalni obliki z locljivostjo najmanj 300 pik na palec (dpi). Zemljevidi in druge graficne priloge v vektorski obliki (*.ai, *.pdf, *.cdr) morajo vsebovati fonte, vecje od 6 pt. Grafikoni morajo biti izdelani s programom Excel ali sorodnim programom (av­torji jih oddajo skupaj s podatki v izvorni datoteki, npr. Excelovi preglednici). Ce avtorji ne morejo oddati prispevkov in graficnih prilog v navedenih oblikah, naj se predhodno posvetujejo z urednikom. Za graficne priloge, za katere avtorji nimajo avtorskih pravic, morajo priložiti fotokopijo dovoljenja za objavo, ki so ga pridobili od lastnika avtorskih pravic. 7. Avtorji so dolžni upoštevati nacin citiranja v clanku ter oblikovanje seznama virov in literature, preglednic in ostalega graficnega gradiva, kot je to navedeno v podrob­nejših navodilih za pripravo clankov na povezavi http://revije.ff.uni-lj.si/Dela/about/ submissions#authorGuidelines. Za dela, ki jih je avtor uporabil v elektronski obliki, naj poleg bibliografskih podatkov navede še elektronski naslov, na katerem je delo dostopno bralcem, in datum citiranja. Za znanstvene clanke s številko DOI avtorji navedejo DOI številko. 8. Znanstveni clanki bodo recenzirani. Recenzentski postopek je praviloma ano­nimen, opravita ga dva kompetentna recenzenta. Recenzenta prejmeta clanek brez navedbe avtorja clanka, avtor clanka pa prejme recenzentove pripombe brez navedbe recenzentovega imena. Ce recenziji ne zahtevata popravka ali dopolnitve clanka, se avtorju clanka recenzij ne pošlje. Uredniški odbor lahko na predlog recenzentov za­vrne objavo prispevka. 9. Avtorji, ki želijo, da se njihov clanek objavi v reviji, se strinjajo z naslednjimi pogoji: • Pisci besedila z imenom in priimkom avtorstva potrjujejo, da so avtorji odda­nega clanka, ki bo predvidoma izšel v reviji DELA v okviru Znanstvene založbe Filozofske fakultete Univerze v Ljubljani (Univerza v Ljubljani, Filozofska fakul­teta, Aškerceva 2, 1000 Ljubljana). O likovno-graficni in tehnicni opremi dela ter o pogojih njegovega trženja odloca založnik. • Avtorji jamcijo, da je delo njihova avtorska stvaritev, da na njem ne obstajajo pravice tretjih oseb in da z njim niso kršene kakšne druge pravice. V primeru zahtevkov tretjih oseb se avtorji zavezujejo, da bodo varovali interese založnika ter mu povrnili škodo in stroške. • Avtorji obdržijo materialne avtorske pravice ter založniku priznajo pravico do prve izdaje clanka z licenco Creative Commons Attribution-ShareAlike 4.0 In­ternational License (priznanje avtorstva in deljenje pod istimi pogoji). To pome­ni, da se lahko besedilo, slike, grafi in druge sestavine dela prosto distribuirajo, reproducirajo, uporabljajo, priobcujejo javnosti in predelujejo, pod pogojem, da se jasno in vidno navede avtorja in naslov tega dela in da se v primeru spremem­be, preoblikovanja ali uporabe tega dela v svojem delu, lahko predelava distribu­ira le pod licenco, ki je enaka tej. • Avtorji lahko sklenejo dodatne locene pogodbene dogovore za neizkljucno dis­tribucijo razlicice dela, objavljene v reviji (npr. oddaja v institucionalni repozi­torij ali objava v knjigi), z navedbo, da je bilo delo prvic objavljeno v tej reviji. • Pred postopkom pošiljanja ali med njim lahko avtorji delo objavijo na spletu (npr. v institucionalnih repozitorijih ali na svojih spletnih straneh), k cemur jih tudi spodbujamo, saj lahko to prispeva k plodnim izmenjavam ter hitrejšemu in obsežnejšemu navajanju objavljenega dela. 10. Avtor sam poskrbi za jezikovno ustreznost svojega besedila in prevoda (vkljucno z izvleckom, kljucnimi besedami in povzetkom clanka). Ce je besedilo jezikovno ne­ustrezno, ga uredništvo vrne avtorju, ki mora poskrbeti za lektorski pregled besedila. Ce obseg avtorskega dela ni v skladu z navodili za objavo, avtor dovoljuje izdajatelju, da ga po svoji presoji ustrezno prilagodi. 11. Izdajatelj poskrbi, da bodo vsi prispevki s pozitivno recenzijo objavljeni, ce bo imel zagotovljena sredstva za tisk. O razporeditvi prispevkov odloca uredniški odbor. Vsakemu avtorju pripada en brezplacen tiskan izvod publikacije. 12. Avtorji naj prispevke pošljejo na elektronski naslov dela_geo@ff.uni-lj.si. INSTRUCTIONS FOR AUTHORS PREPARING ARTICLES FOR THE SCIENTIFIC JOURNAL DELA 1. The scientific journal DELA is a periodical publication of the Department of Ge­ography, Faculty of Arts, University of Ljubljana. It has been published since 1985. It is dedicated to presenting scientific and technical achievements in all fields of geo­graphy and related disciplines. Since 2000 it has been published twice yearly in print and electronic form (http://revije.ff.uni-lj.si/Dela). The magazine is included in the international databases (Scopus, CGP – Current Geographical Publications, DOAJ, ERIH PLUS, GEOBASE, Central and Eastern European Academic Source, GeoRef, Russian Academy of Sciences Bibliographies, dLib.si, International Bibliography of the Social Sciences) and has an international Editorial Board. 2. Published in the first part are scientific articles (1.01 and 1.02 by COBISS catego­risation). Published in the second part are informative articles categorised as RE­PORTS as well as biographical contributions (anniversaries, obituaries), reviews of geographical monographs and journals, major events in the field of geography and other events, etc. 3. Scientific articles may be published in one of three language configurations: bilin­gual Slovene-English, entirely in Slovene or entirely in English Articles must have the following components: • Article title; • Name and surname of author/authors; • Author’s address (eg. Department of Geography, Faculty of Arts, University of Ljubljana, Aškerceva cesta 2, 1000 Ljubljana, Slovenia); • Author’s email; • Abstract (up to 500 characters with spaces); • Keywords (up to eight); • Article text (up to 30,000 characters with spaces; for longer articles authors should consult with the editor before submitting); • In cases of articles written in one language, these must also include a summa­ry in the other language (between 5,000 and 8,000 characters with spaces) and translations of the abstract and keywords; • Name of translator. 4. The article should have chapter headings and subheadings identified with Arabic numerals in the form of decimal classification (e.g. 1 Introduction, 2 Methods, 3 Re­sults and discussion, 4 Conclusion, References etc.). Structuring the article in chapters is mandatory, authors may use sub-chapters only in exceptional cases. 5. Authors should submit their articles as digital copies – format may be *.doc, *.docx or *.odt. The digital version of the text should be completely clean, without styles and other sophisticated design, without line break hyphenation nor underlining, and so forth. Authors may mark using only bold and italic text. The text should be written entirely in lowercase (including in the title and subtitle, with the exception of capitali­sed words) without unnecessary contractions, acronyms and abbreviations. 6. Maps and other graphic materials must conform to the format of the journal. Ful­lpage figures need to be sized 125 x 170 mm, while smaller figures are restricted to a maximum width of 125 mm. Font size must be at least 6pt. All graphic materials must be submitted as individual files (i.e. not as part of the file with the text). Graphics (maps, etc.) should be in AI, CDR, PDF, TIFF or JPG file formats. Those in raster formats (e.g. *.tiff or *.jpg) must have a resolution of at least 300 dots per inch (dpi). Charts must be prepared in Excel or a similar programme (authors should submit them together with the data in the source file, e.g. Excel spreadsheet). If authors are unable to submit articles and graphic materials in the mentioned forms, they should consult with the editor. If an author is not the copyright holder of graphic materials then they must attach a photocopy of the approval for publication, which they have obtained from the copyright owner. 7. In articles authors are obliged to comply with the citation style and produce a re­ference list, tables and other graphic materials, as outlined in the detailed guidelines for the preparation of articles – available at http://revije.ff.uni-lj.si/Dela/about/Sub­missions#authorGuidelines. In instances where the author used electronic resources, in addition to the bibliographic details they should also provide a URL where readers can access the resources, and note the date it was accessed. For scientific articles with a DOI number, authors should provide the DOI number. 8. Scientific and professional articles will be peer reviewed. The peer-review process is anonymous, carried out by two competent reviewers. Reviewers receive an article without the author’s name being revealed, the author of the article receives the re­viewer's comments, without being given any reviewers’ names. If reviewers do not demand corrections or amendments be made to the article, the reviewers do not send the author the reviewed article. Based on recommendations from the reviewers the Editorial Board may refuse to publish the article. 9. Authors wishing to have their article published in the journal agree to the following conditions: • Listed authors (name and surname) confirm that they are the authors of the sub­mitted article, intended for publication in the journal DELA, a publication of the Ljubljana University Press, Faculty of Arts [Znanstvena založba Filozofske fakul­tete Univerze v Ljubljani] (University of Ljubljana, Faculty of Arts, Aškerceva 2, 1000 Ljubljana). Decisions concerning graphic design and technical production of the work and the conditions of its marketing are at the discretion of the publisher. • Authors guarantee that the work is their own original composition, that no third parties have rights to the work, and that the article does not violate any other rights. In the case of third-party claims authors undertake to protect the inte­rests of the publisher and cover the publisher’s damages and costs. • Authors retain copyright and recognise the publisher’s right of first publication; the article will be licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (attribution of authorship and shared authorship are covered by the same conditions). This means that text, pictures, graphs and other components of the work can be freely distributed, reproduced, used, communi­cated to the public and processed, provided that author’s name and the article title are clearly and prominently indicated, and that in cases where changes or modifications are made or the work is used in other work, it can be distributed only under a license identical to this one. • Authors may enter into additional separate contractual arrangements for non­-exclusive distribution of the version of the work, published in the journal (e.g. submit it to an institutional repository or publish it in a book), with an ac­knowledgement that the work was first published in this journal. • Before the submission process or during it authors can publish work on the in­ternet (e.g. in institutional repositories or on their own websites), which we also encourage, as this can contribute to a fruitful exchange as well as rapid and wi­despread referencing of the published work. 10. Authors themselves ensure that the language used in their text is appropriate and that acceptable translations are provided (including of the abstract, keywords and su­mmary of the article). If the language is inappropriate the Editorial Board will return it to the author, who must arrange for a professional proofreader to review the text. If the author’s work is not in accordance with the instructions for publication, the author allows the publisher at their discretion to make appropriate adjustments. 11. The publisher shall ensure that all articles that are positively reviewed are published, provided it has funds available for printing. The sequence of articles is decided by the Editorial Board. Each author is entitled to one free copy of the printed publication. 12. Authors should send articles to e-mail address dela_geo@ff.uni-lj.si. Slika 1: Dobro strukturirane mejice zaradi zastopanosti vseh treh slojev rastlinstva (dreves, grmovja in zelišc) opravljajo najvec funkcij (Vipavska dolina) (foto: A. Kastelic). Figure 1: Well-structured hedgerows perform the most functions due to the representation of all three layers of vegetation (trees, shrubs and herbs) (Vipava Valley) (photo: A. Kastelic). ORODJE SCAT ANALIZA SKUPNOSTI 1. opredelitev raziskovane skupine in obmocja 2. zbiranje in obdelava kvantitativno zbranih podatkov 3. statisticna analiza: korelacijska analiza in multipla regresijska analiza (SPSS) 4. kvantitaitvna mrežna analiza: socialna mreža organizacij in mere središcnosti (R) ANALIZA ORGANIZIRANOSTI 5. opredelitev vzorca 6. izvedba poglobljenih polstrukturiranih intervjujev 7. analiza intervjujev s kodiranjem (Atlas.ti) 8. metoda fokusne skupine vrednotenje organizacijskih ucinkov socialnega kapitala Zasnova in oblikovanje: Jasna Sitar Oddelek za geografijo, FF UL, 2021 Slika 3: Registrirana društva v UE Litija, število in tipi društev. Preglednica 3: Korelacijska koeficienta (Pearson in Spearman), ki nakazujeta povezanost spremenljivk. Legenda: Pearsonov koeficient 0,40–0,69 (zmerna povezanost)   Pearsonov koeficient 0,20–0,39 (šibka povezanost) * p < 0,05, statisticno znacilno na ravni 5 % ** p < 0,01, statisticno znacilno na ravni 1 % Trajanje funkcije Št. dogodkov Št. dogodkov v partner­stvu Št. part­nerjev Št. let delo­vanja Sode­lovanje na regional­ni in nacional­ni ravni Pomem­bnost so­cialnega omrežja FB Pomem­bnost so­cialnega omrežja Insta­gram Pomem­bnost social­nega omrežja Twitter Pomem­bnost e-mail komu­niciranja Št. organ­iziranih dogod­kov prek spleta Št. deljenih objav na mesec Št. clanov Št. akt. clanov Trajanje funkcije Št. dogodkov 0,17 Št. dogodkov v partnerstvu 0,16 0,521** Št. partnerjev –0,02 0,297** 0,457** let delovanja 0,219* 0,239* 0,269** 0,01 Sodelovanje na regionalnem/nacionalnem nivoju –0,04 –0,415** –0,343** –0,364** –0,18 Pomembnost socialnega om­režja FB –0,236* 0,04 –0,06 0,20 –0,226* –0,06 Pomembnost so­cialnega omrežja Instagram –0,16 –0,01 –0,11 0,07 –0,238* 0,00 0,528** Pomembnost socialnega om­režja Twitter –0,12 –0,11 –0,11 0,07 –0,21 0,04 0,288** 0,523** Pomembnost e-mail komu­niciranja –0,10 0,14 0,268* 0,263* 0,05 –0,17 0,14 –0,04 0,16 Št. organizir­anih dogodkov prek spleta –0,18 0,235* 0,17 0,13 –0,03 –0,17 0,268* 0,270* 0,11 0,09 Št. deljenih ob­jav na mesec –0,04 0,00 –0,12 –0,20 0,07 0,218* –0,376** –0,295** –0,04 –0,05 –0,15 Št. clanov 0,12 0,336** 0,210* 0,15 0,263** –0,244* 0,10 0,11 –0,12 0,02 0,10 –0,15 Št. aktivnih clanov 0,06 0,467** 0,404** 0,210* 0,324** –0,330** 0,17 0,09 0,00 0,14 0,215* –0,08 0,382** Vir podatkov: Anketiranje društev v UE Litija, 2021. Preglednica 6: Znacilnosti socialne mreže organizacij v UE Litija. Znacilnosti mreže Mere Znacilnosti 1. povezanost vozlišc gostota 0,15 (nizka gostota) 2. povprecna dolžina poti 3,9 koraka (nizka povezanost) 3. prehodnost 0,1 (nizka povezanost) 4. verjetnost porazdelitve povezav 34 % verjetnosti, da ima nakljucno vozlišce dve povezavi, tretjina vozlišc dobro povezana (s 3, 5 ali 6 vozlišci). 5. položaj vozlišc stopnja središcnosti Vozlišcne organizacije. 6. mera središcnosti glede na dostopnost Šibka povezanost omrežja brez mocnega jedra. 7. mera središcnosti glede na vmesnost Prepoznanih 5 organizacij, ki vplivajo na ostale. 8. središcnost lastnega vektorja Obstoj dobro omreženih organizacij, ki med seboj niso povezane (povezovalne organizacije). Preglednica 7: Štiristopenjska lestvica vrednotenja organizacijskih ucinkov socialnega kapitala po treh razsežnostih. Organizacijski ucinki Vrednotenje Skupna ocena Razsežnost Kazalnik 4. stopnja 3. stopnja 2. stopnja 1. stopnja 1 strukturna razsežnost notranje sodelovanje dobro srednje zadovoljivo slabo srednja (3. stopnja) zunanje sodelovanje dobro srednje zadovoljivo slabo notranja povezanost dobra srednja zadovoljiva slaba zunanja povezanost dobra srednja zadovoljiva slaba virtualna povezanost dobra srednja zadovoljiva slaba 2 relacijska razsežnost medsebojno zaupanje (clani) visoko srednje nizko ne zaupam visoka (4. stopnja) zaupanje lokalnim organom visoko srednje nizko ne zaupam zaupanje ostalim organizacijam visoko srednje nizko ne zaupam zaupanje skup­nosti visoko srednje nizko ne zaupam virtualno zaupanje visoko srednje nizko ne zaupam 3 kognitivna razsežnost poznavan­je vizije, strateških ciljev visoko srednje nizko ne poznam visoka (4. stopnja) pomen ciljev dobro srednje zadovoljivo slabo/ni zastavljenih ciljev doseganje ciljev dobro srednje zadovoljivo slabo/ni zastavljenih ciljev Opomba: Ocena vrednotenja kazalnika je prikazana z zeleno obarvanim poljem. Slika 1: Stara ureditev (2004-2021) - Indeks velikosti volilnih okrajev glede na velikost povprecnega volilnega okraja (19.358 volivcev). Slika 2: Nova ureditev volilnih enot (2021). Slika 3: Nova ureditev volilnih okrajev (2021). Slika 4: Nova ureditev volilnih okrajev (2021) - Indeks velikosti volilnih okrajev glede na velikost povprecnega volilnega okraja (19.358 volivcev). Slika 5: Predlog ureditve volilnih okrajev, ki ga je pripravila strokovna skupina (2019). Slika 6: Predlog strokovne skupine (2019): Indeks velikosti volilnih okrajev glede na velikost povprecnega volilnega okraja (19.358 volivcev). Slika 7: Alternativni predlog ureditve volilnih okrajev, ki ga je pripravila strokovna skupina (2019). Slika 8: Alternativni predlog strokovne skupine (2019): Indeks velikosti volilnih okrajev glede na velikost povprecnega volilnega okraja (19.358 volivcev). Figure 5: Part of the map of Croatia with original Croatian and Slovene toponymies kept. Map was prepared by Milan Šenoa for edition of 1943 (Library of Department of Geography, Faculty of Science University of Zagreb. Pristop NEWBIE. Vir infografike: Freepik, Projekt NEWBIE, 2021. Profilna jama 2: Endoleptic Endostagnic Cambic Umbrisol (Epiloamic, Endosiltic) (foto: M. Switoniak, 2021). Profilna jama 3: Luvic Endocalcaric Phaeozem (Siltic, Colluvic, Hiperhumic, Pachic) (foto: M. Switoniak, 2021). Profilna jama 4: Dystric Leptic Cambisols (Loamic, Ochric, Epichromic) (foto: M. Switoniak, 2021). NAVODILA AVTORJEM NAVODILA AVTORJEM NAVODILA AVTORJEM DELA 56 Oddelek za geografijo, Filozofska fakulteta Univerze v Ljubljani Department of Geography, Faculty of Arts, University of Ljubljana Založnik – Published by Znanstvena založba Filozofske fakultete Univerze v Ljubljani Izdajatelj — Issued by Oddelek za geografijo, Filozofska fakulteta Univerze v Ljubljani Za založbo — For the Publisher Mojca Schlamberger Brezar, dekanja Filozofske fakultete Upravnik — Editorial Secretary Nejc Bobovnik Narocila – Orders Oddelek za geografijo, Filozofska fakulteta Aškerceva 2, p.p. 580, SI-1001 Ljubljana, Slovenija e-mail: nejc.bobovnik@ff.uni-lj.si Cena — Price 15 € Fotografija na naslovnici/Cover photo: Za Slovenijo je zaradi raznolikih geografskih razmer in dolge tradicije kultiviranja zemljišc znacilna mozaicna pokrajina, katere sestavni deli so tudi mejice. Na sliki so strukturirane mejice na Ljubljanskem barju (foto: B. Lampic). For Slovenia, due to the diverse geographical conditions and the long tradition of land cultivation, a mosaic landscape is characteristic. A part of it are also hedgerows. The picture shows structured hedgerows in the Ljubljana Marshes (photo: B. Lampic).