Acta Sil va e et Ligni 131 (2023), 1–27 1 Izvirni znanstveni članek / Original scientific article ARE SLOVENIA’S FORESTS DEVIATING FROM SUST AINABLE DEVELOPMENT? ALI SE SLOVENSKI GOZDOVI ODMIKAJO OD TRAJNOSTNEGA RAZVOJA? Gal KUŠAR 1 , Marko KOVAČ 2 (1) Slovenian Forestry Institute, Department for Forest and Landscape Planning and Monitoring, gal.kusar@gozdis.si (2) Slovenian Forestry Institute, Department for Forest and Landscape Planning and Monitoring, marko.kovac@gozdis.si ABSTRACT This paper provides an overview of the sustainable development of Slovenian forests between 2000 and 2018. The state and development of Slovenian forests in terms of sustainability were examined using a set of variables and indicators of sustain- able forest management such as forest area, basal area, growing stock, stand density index, age structure/diameter distribu- tion, demographic balance, optimal growing stock, increment, felling, species diversity, species mixture, forest regeneration, naturalness and deadwood. We also assessed the suitability of the systematic 4 x 4 km sampling grid. All estimates were calcu- lated at the national, ecoregional and forest region levels. In 2018, forest cover was estimated at 60% and was slightly higher than that in 2012. Conversely, growing stock volume decreased and was estimated at 329.6 m 3 /ha. Young forests accounted for 29%, older forests for 68% and uneven-aged forests for 3% of the total forest area. Beech and spruce were the dominant tree species. The proportions of other species were less than 10%, and concerns were raised about their recruitment. Comparative analyses of the desired values of the indicators and the values reported by the Forest Europe process member states and some selected countries raised doubts about Slovenia’s progress towards sustainable forest development. Furthermore, the 2018 dataset does not fully support the indicators of sustainable forest management. Key words: sustainable forest management, indicators, temporal analysis, Slovenia IZVLEČEK Prispevek nas seznanja z osnovnimi informacijami o trajnostnem razvoju slovenskih gozdov med letoma 2000 in 2018. Stanje in razvoj slovenskih gozdov z vidika trajnosti smo preverili z nizom spremenljivk in kazalnikov trajnostnega gospodarjenja z gozdovi: površina gozdov, temeljnica, lesna zaloga, indeks sestojne gostote, starostna struktura/porazdelitev prsnih premerov, ravnotežje razvojnih faz, optimalna lesna zaloga, prirastek, posek, različnost drevesnih vrst, mešanost sestojev, pomlajevanje, naravnost in odmrla drevnina. Ocenili smo tudi ustreznosti sistematične mreže 4 x 4 km, ki se je uporabljala za velikoprostor- sko inventarizacijo. Vse vzorčne ocene so bile izračunane za raven države, ekoregije in za gozdnogospodarska območja. Leta 2018 je gozdnatost dosegala 60 % in je bila višja kot l. 2012. Nasprotno se je lesna zaloga zmanjšala in je bila ocenjena na 329,6 m 3 /ha. Površinski delež mlajših gozdov je znašal 29 %, starejših (sečno zrelih) 68 %, raznodobnih pa 3 %. Med drevesnimi vrstami je največji delež pripadal bukvi in smreki. Deleži drugih vrst niso presegli 10 %, posebej zaskrbljujoča je bila njihova vrast. Na osnovi primerjav z zaželenimi vrednostmi in vrednostmi kazalnikov v gozdovih držav članic procesa Forest Europe in nekaterimi izbranimi državami, je mogoče skleniti, da se razvoj slovenskih gozdov odmika od trajnostnega razvoja. Glede na razpoložljive podatke l. 2018 je tudi mogoče zaključiti, da velikoprostorska inventura MGGE l. 2018 s podatki ne zapolni vseh kazalnikov trajnostnega gospodarjenja z gozdovi. Ključne besede: trajnostno gospodarjenje z gozdovi, kazalniki, časovna analiza, Slovenija GDK GDK 901:611(497.4)=111 Prispelo / Received: 08. 05. 2023 DOI 10.20315/ASetL.131.2 Sprejeto / Accepted: 27. 06. 2023 1 INTRODUCTION 1 UVOD The concept of sustainability has been known in European forestry since Carlowitz (von Carlowitz, 1713) published his book on forestry. Although he likely believed that fixed forest resources were inex- haustible, he advocated for a balanced approach be- tween wood demand and wood supply. He claimed that the growing demand for wood could only be met by expanding wood production through silvicultural techniques (Warde, 2018), promoting coppicing and planned tree harvesting followed by systematic re- planting (Schmithüsen, 2013; Vollmuth, 2022). Since Carlowitz’s time, the idea of sustainable forest use has undergone many transformations and evolved into a complex development pattern that presently pervades forestry, many environmental sectors and industries (Schmithüsen, 2013; The European green …, 2019; Forest Europe, 2022). 2 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? Forests are currently perhaps the most heavily bur- dened by human demands of all natural renewable re- sources. They are vital for the forest sector, in which planners and managers with diverse knowledge and skills aim to conserve their ecological integrity as well as plant and animal inhabitants (Maurer, 1993), pro- tect soils, and ensure sustainable wood supply. Forests also play a crucial role in storing carbon, purifying wa- ter and enabling numerous human activities. Many of these forest contributions have been known for dec- ades (Dieterich, 1953; McArdle, 1953). What is new is the growing increase in demands presently affecting almost all forest services, generated primarily by en- vironmental sectors, energy-consuming industries and policies (e.g. EU biodiversity and forest strategies, EU Green Deal (Verkerk et al., 2022; The European Green …, 2019, EU biodiversity strategy …, 2020; Wolfslehner et al., 2020; New EU forest …, 2021)). These demands are not adequately prioritized or harmonized, leading to challenges in managing forests sustainably. To monitor changes and assess forest development and management status over time, a list of sustainable forest management (SFM) indicators has been devel- oped (Forest Europe, 2022). These indicators are used for forest reporting at the pan-European level and are often adopted and further developed by national forest sectors to support their policies and practices (Linser and Wolfslehner, 2022). However, measuring and as- sessing the status of sustainable forest development and management remains challenging due to the in- complete list of SFM indicators, including the attributes of forest ecosystem services (e.g. soil protection, ero- sion control, forest biodiversity (Kovač et al., 2017; Al- berdi et al., 2019)) and their undefined reference values (Linser and Wolfslehner, 2022). An additional dilemma arises from the ambiguous definition of SFM (Forest Europe, 2022), which does not explicitly state that a seminatural managed forest only functions in perpe- tuity if its tree population is at or near demographic equilibrium ((Schütz, 2006; Schütz et al., 2016), e.g. age classes/developmental phases, J-shaped curves). As this condition is not explicitly included, the definition allows for various interpretations, such as i) increasing wood (carbon) storage despite the surplus of overaged forests already saturated with wood biomass (Verkerk et al., 2022; Nabuurs et al., 2013) or ii) allowing large areas of already overaged forests to grow even older to improve species habitats, even though such actions un- dermine their stability and expose them to high risks (Brang et al., 2013; Albrich et al., 2018). As recently reported by Lier et al. (2022), a different political un- derstanding of the definition of SFM is also underway. SFM indicators are usually derived from data collected through field sampling, aerial photographs and other means. The data on forest development are usually pro- vided by national forest inventories (NFI) conducted in most EU 27 countries (Tomppo et al., 2009). The principle of sustainability was introduced to Slovenian forests (then part of the Austrian monarchy) with the Forest Act of 1852 (Johann, 2013; Perko et al., 2014; Perko, 2018) and has been applied nationwide since 1853. Presently, Slovenian forestry is commit- ted to SFM and participates in the Forest Europe proc- ess (Forest Europe, 2022). However, despite investing significant resources to improve near natural forest management (Diaci, 2006; Johann, 2007; Schütz et al., 2012) and develop an intensive forest planning system (Gašperšič, 1995; 2006), limited efforts have been de- voted to monitoring the outcomes of these practices at the national level. Consequently, some data and infor- mation on SFM are only available at the level of forest regions and forest management units (Pregledovalnik …, s. a.). Such statistical design makes the data unsuit- able for evaluating sustainable forest development and management at the national level or for shaping national forest policy. A better approach to assess forest conditions at the national level is provided by the national forest inven- tory named the “Forest and forest ecosystem survey” (hereafter FFECS), introduced in 1985 (Kušar et al., 2009). Unlike most NFIs, the FFECS provides a limited amount of data sufficient to derive only some of those SFM indicators that can be collected by the NFI. To im- prove the system of SFM indicators and the National Forest Program, the indicators have been revisited and an SFM-based set of indicators has been designed for simultaneous monitoring. However, no reference val- ues have been set for any of these indicators (Bončina, 2017; Kovač et al., 2019a). Apart from reporting for the needs of Forest Europe and occasional assessments of forest conditions (Kovač, 2014b; Veselič et al., 2014; Bončina, 2017; Poročilo o iz- vajanju …, 2021) , Slovenian forests have not yet been thoroughly analysed from a sustainable development perspective. This paper aims to introduce readers to the basic information about the development of forests at the national level between 2000 and 2018. Addition- ally, it provides some information about the suitabil- ity of the systematic grid used for data collection. The study also examines how many SFM indicators can be assessed using the 2018 FFECS data. Lastly, it compares the findings with information available for European forests and the forests of some selected countries and discusses them in the context of SFM. Acta Sil va e et Ligni 131 (2023), 1–27 3 2 METHODS 2 METODE DELA 2.1 Definition of sustainable forest development 2.1 Definicija trajnostnega gospodarjenja z goz- dovi This study defined SFM in the same way as Forest Europe (i.e. “… the stewardship and use of forests and forestlands in a way, and at a rate, that maintains their biodiversity, productivity, regeneration capacity, vital- ity and their potential to fulfil, now and in the future, relevant ecological, economic and social functions, at local, national and global levels, and that does not cause damage to other ecosystems” (Forest Europe, 2022)). The understanding of the definition was more rigid as it considered the development of semi-natu- ral forests to be sustainable only if their tree popula- tions were demographically balanced. Such an under- standing also suggested that the demographic balance should take precedence when searching for balance among the ecological, productional and social compo- nents of SFM. This condition stems from the idea that only forests at or near equilibrium can provide the ba- sic forest ecosystem services over long time horizons. 2.2 Specific indicators and SFM indicators 2.2 Specifični kazalniki in kazalniki trajnost- nega gospodarjenja z gozdovi (TGG) All used data came from the FFECS database (GIS- NMGK, 1985–2018), collected between the years 2000 and 2018 on a 4 x 4 km systematic grid. Because this inventory provided a very small amount of data due to its irregular repetition and the exclusion of many vari- ables from regular assessments, some of the SFM indi- cators could not be included in this analysis. The number of concentric permanent sample plots in the observed period varied (582 in 2000; 724 in 2007; 760 in 2012; 759 in 2018) due to necessary in- ventory improvements (Kovač et al., 2014). Their num- bers stabilized in 2012 and since then have been de- pendant only on land use changes. The geo datasets of ecoregions and forest regions (Kutnar et al., 2002; Pre- gledovalnik …, s. a.) were used for post-stratifications. The evaluation of sustainable forest development was carried out with the data of a rather small number of simple and composite variables and available SFM indicators (Forest Europe, 2015), presented in Table 1. All analyses were performed using Microsoft 365, R- core team, Statistica v. 13, and ArcGIS v. 10.8.1 (R core …, s. a.; Statistica …, s. a.; ArcMap …, s. a.). 2.3 Computations 2.3 Izračuni 2.3.1 Forest area, basal area, growing stock, stand density index 2.3.1 Površina gozdov, temeljnica, lesna zaloga, indeks sestojne gostote Apart from the forest area, the plot values for basal area (BA), growing stock (GS) and stand density index Fig. 1: a) Ecoregions: Alp = Alpine; Poh = Pohorje; PPan = Prepannonian; Palp = Prealpine; Pdyn = Predinaric; Dyn = Dinaric; SMdt = Submediterranean, b) 14 Forest regions: To = Tolmin; Bl = Bled; Kr = Kranj; Lj = Ljubljana; Po = Postojna; Ko = Kočevje; NM = Novo mesto; Br = Brežice; Ce = Celje; Na = Nazarje; SG = Slovenj Gradec; Mb = Maribor; MS = Murska So- bota; Se = Sežana. Both figures show damaged forest areas by cause: bark beetles (violete; 2015–2018), ice storm (orange; 2014) and windthrows (green; 2017–2018) (Pregledovalnik …, s. a.). Slika 1: a) Ekoregije: Alp = Alpska; Poh = Pohorska; Ppan = Predpanonska; Palp = Predalpska; Pdyn = Preddinarska; Dyn = Dinarska; SMdt = Submediteranska, b) 14 Gozdnog- ospodarska območja: To = Tolmin; Bl = Bled; Kr = Kranj; Lj = Ljubljana; Po = Postojna; Ko = Kočevje; NM = Novo mesto; Br = Brežice; Ce = Celje; Na = Nazarje; SG = Slovenj Gradec; Mb = Maribor; MS = Murska Sobota; Se = Sežana. Obe sliki prikazujeta območja poškodovanosti gozdov zaradi: podlub- nikov (vijolično; 2015–2018), žledoloma (oranžno; 2014) in vetrolomov (zeleno; 2017–2018) (Pregledovalnik …, b. l.). 4 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? (SDI) were calculated using FFECS protocols (Kušar et al., 2010). Because the FFECS did not provide any infor- mation on forest types, forest areas available for wood supply and other wooded lands, all estimates referred to forests only. All density variables were calculated to values per hectare. The values of growing stock were calculated via the Kauffman approach (2001). Stand density index (SDI; Pretzsch, 2009) is sug- gested for the assessment of stocking at large scales (Woodall et al., 2005). Despite the large variability of tree diameters, the formula for evenly aged forests was used (SDI = N trees *(25/D) -1.605 ; D is mean diameter) because of the predominance of shelterwood stands (97% according to FFECS). To compare the SDI values, we derived the reference (“normal”) SDI line segments for spruce and beech (Fig. 7a, b, 8a). As suggested by Hladnik and Žižek Kulovec (2014), these reference values were calculated using the “average” site index values (SI) given in the Swiss (Badoux, 1966) and Slo- vak (Kotar, 2003) yield tables (Swiss tables: SI 50 for beech and mountain spruce = 18; Slovak tables: SI 100 for beech and mountain spruce = 28, productivity level = 2). Both tables are well known and widely used in Slovenian forest research. The SDI values represent the following forest densities: 0–400 = very low density; 400–600 = low density; 600–800 = normal density; 800–1200 = high density; and SDI > 1200 = very high density (Brassel, 2001). SFM indicator definition (For- est Europe) Original data Description Description (continuation) Used composite / auxiliary variables Source Concentric permanent sample plot R1: 3.09 m (small trees DBH < 10 cm, H ≥ 1.3 m) R2: 7.98 m (DBH ≥ 10 cm) R3: 13.82 m (DBH ≥ 30 cm) R4: 25.23 m (deadwood, site exposition, microrelief, …) FFECS 1.1 Forest area (by forest type* and OWL*) Forest area Forest area ≥ 0.25 ha FFECS 1.2 Growing stock (GS) (by forest type* and OWL*) DBH of a tree Alive: DBH ≥ 10 cm Standing dead: DBH ≥ 10 cm Ingrown: DBH ≥ 10 cm Cut: DBH ≥ 10 cm Basal area (BA), number of trees, stand density index (SDI), balanced and optimal growing stock FFECS 1.3 Age structure and/or diameter distribution Vertical struc- ture Evenly-aged Unevenly-aged Coppice, Multi-storey FFECS DBH of a tree Alive: DBH ≥ 10 cm Diameter distribution FFECS Even-aged stand Development phase Young stand = Yst; DBH < 10 cm Pole1 = DBH 10–19.9 cm Pole2 = DBH 20–29.9 cm Sawlog1 = Swl1: DBH 30–39.9 cm Sawlog2 = Swl2: DBH 40–49.9 cm Sawlog3 = Swl3: DBH ≥ 50 cm Current and normal shares of development phases FFECS Uneven-aged stand UnevA = all DBH ≥ 10 cm Taken as a whole, not classi- fied with respect to DBH FFECS 3.1 Increment and felling DBH of a tree Alive: DBH ≥ 10 cm Ingrown: DBH ≥ 10 cm Cut: DBH ≥ 10 cm Increment, felling (the ten- dency in increment in severely damaged stands) FFECS 4.1 Diversity of tree species Tree species Share in volume Species composition (the composition of ingrown trees) FFECS Ingrowth No. of ingrown trees (by DBH classes) Future species composition FFECS 4.2 Regenera- tion of forests Presence Yes, No Regeneration area by type FFECS Development phase Young forest Stand origin Natural regeneration Artificial regeneration Combined (natural + artificial) Unknown 4.3 Naturalness Naturalness Natural forest Seminatural forest Forest with exchanged tree spe- cies composition Share of naturalness FFECS 4.5 Deadwood Standing: DBH ≥ 10 cm Downed: DBH ≥ 10 cm Snag: DBH ≥ 10 cm, H ≥ 50 cm Stump: DBH ≥ 10 cm, H ≥ 20 cm Course woody debris: DBH ≥ 10 cm, L ≥ 50 cm Deadwood assessment (un- classified by type) FFECS * Forest type and other wooded lands (OWL) not assessed. Table 1: Original and calculated FFECS data and SFM indica- tors (Kovač, 2014a) Preglednica 1: Osnovni in izračunani podatki Monitoringa gozdov in gozdnih ekosistemov (MGGE) in kazalniki TGG (Kovač, 2014a) Acta Sil va e et Ligni 131 (2023), 1–27 5 2.3.2 Age structure and/or diameter distribution, balance of developmental phases, normal and optimal growing stock 2.3.2 Starostna struktura/porazdelitev prsnih pre- merov, ravnotežje razvojnih faz, normalna in optimalna lesna zaloga Instead of using the age-class approach (FFECS provided the data on stand age for most plots; the vari- able was not determined accurately, e.g. by drilling, but by visual assessments and by counting stump rings), we derived the demographic picture of evenly aged forests, managed by various forms of shelterwood sys- tems, by analysing the distributions of developmen- tal phases and constructing the normal forest model (von Gadow, 2005). Average transition periods were derived from the diameters of the same 9,032 trees, measured from 2000 to 2018. Because each plot be- longed to only one developmental phase, the average time for overgrowing each phase was calculated from all trees in that developmental phase. After the calcula- tion, the transition periods were modified, considering the results of specific forest growth and yield studies (Čokl, 1965; 1966; 1968; Kadunc, 2009; 2011) and the data of the Swiss and Slovak (Halay) yield tables. This modification was unavoidable because the calculated developmental phase transition times were overshad- owed by the unevenness of stands due to long regen- eration periods and delayed transitions, caused by a series of large-scale natural events. Another reason for this modification was the long production periods, often leading to tree over-maturity. In accordance with scientific suggestions for increas- ing the resilience of forests (Brang et al., 2013; Levanič et al., 2020), we set the average production period for all forests in the country at 125 years (for forests under 600 m a.s.l. at 110 years, and for forest above 600 m a.s.l. at 135 years). The normal growing stock was com- puted using the normal areas of developmental phases and their actual mean growing stocks. For the needs of future forest management (viz. carbon sequestration), we also derived the optimal growing stock using the aforementioned normal areas of developmental phas- es and the growing stocks suggested by the Swiss and Slovak yield tables. The same site index values were used as in the SDI calculations. Furthermore, to show that future forest management had many options, we also performed a simulation with the balanced grow- ing stock by using the mean growing stock values of developmental phases of the Swiss and the Burgen- land (AT) forests (Österreichische … s. a.; Swiss … s. a.). This Austrian region is ecologically very similar to the forest region of Murska Sobota and the Prepannonian ecoregion. Its forest composition is also comparable with Slovenian forests because of its larger share of broadleaves than in Carinthian and Styrian forests. 2.3.3 Increment and felling 2.3.3 Prirastek in sečnja The plot values of increment and felling were com- puted using FFECS protocols (Kušar et al., 2010). We computed i) the gross increment including ingrowth and half of the increment of felled trees and ii) the gross increment without ingrowth and the increment of felled trees (GI). The second option was used for com- parisons. Because of many natural disasters between 2012 and 2018 (ice storm, bark beetles, windthrows), the mean increment and felling were also separately evaluated for damaged areas (Fig. 1) (Pregledovalnik …, s. a.)). 2.3.4 Diversity of species, species mixture, forest regeneration, naturalness, deadwood 2.3.4 Različnost drevesnih vrst, mešanost sestojev, pomlajevanje, naravnost, odmrla drevnina The data on species proportions (forest mixture), naturalness and deadwood were collected using the FFECS protocol. Tree species proportions were pre- sented with volume proportions, and differences be- tween the observed years were examined with statis- tical tests. To show what species composition would prevail in the future, a more detailed analysis based on tree counts was carried out. To simplify the calcula- tions with different weights of circular plots, only the inner plot, determined by the R2 radius, was used. Tree species proportions were calculated using the 2018 dataset. Classes included trees with the diameters of 10–12 cm (this range was chosen for statistical pur- poses), 12.1–20 cm, 20.1–30 cm, 30.1–40 cm, 40.1–50 cm and over 50 cm. Apart from beech, fir and spruce, whose proportions were analysed at the ecoregional level, changes in the proportions of the other species were analysed solely at the national level. The rejuvenated area was estimated with the per- cent of area belonging to the young developmental phase. The FFECS estimate was also compared with the normal forest model value. 2.3.5 Evaluation of sustainability with the selected indicators of SFM 2.3.5 Presoja trajnosti gozdov z izbranimi kazalniki TGG The state of sustainability of selected SFM indica- tors is normally determined by evaluating the discrep- ancies between their current and target values. Be- 6 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? cause the target values have not yet been set (Bončina, 2017; Kovač et al., 2019a; Kovač et al., 2019b), the de- sired values (Bennetts and Bingham, 2007), represent- ed by the long-term averages, normal forest model val- ues, yield table values, and suggestions and evidence from the scientific literature, were used instead. The states of the current conditions were defined either as favourable or unfavourable. As mentioned, the list of SFM indicators used was incomplete. Nevertheless, with the exception of forest ecosystem health and vi- tality and soil indicators, the most pertinent ones char- acterizing forest development were included. • Forest area has become a notable indicator after being recognized as one of the carbon pools. The research of Žumer (1976) reveals that Slovenia’s forest cover has been increasing since 1875, when it was estimated at 36% (737,000 ha). For the sake of this study, a desired value for forest cover was defined subjectively, with a range. The range was compared with the forest areas of the EU27 Mem- ber states (Eurostat, 2022). • From an ecological point of view, the height of grow- ing stock volume is a less critical factor of forest eco- system development. However, its role becomes sig- nificant as soon as we begin dealing with mitigating climate change effects and with the national forest economy. To be able to evaluate its further develop- ment, we defined its desired value with the range of the possible values of the optimal growing stock. • Despite often being underestimated, age structure (demographic portrayal) is a notable factor in the development of seminatural forests. As this indi- cator has not been collected by the FFECS, it was replaced by the structure of developmental phases. Desired proportions for all developmental phases were defined with the normal forest model. • The ratio of felling and increment defines the inten- sity of forest management. Its desired value was set at a level that upholds a more intensive manage- ment and a faster improvement of the demographic portrayal. The ratio was checked with yield tables. • Along with the demographic portrayal of stands, tree species composition is an essential factor of near natural forest management. It helps deter- mine the degree of forest naturalness and the con- servation status of forest habitat types (Kovač et al., 2020). Because the definition of tree species com- position is meaningful at the forest habitat type lev- el, we defined desired values (viz. ranges) by means of vegetation models (Veselič, 2000) at the national level and evaluated their development trend. • The desired area of forest regeneration was defined by the normal forest model. This value was com- pared with the actual FFECS values between 2000 and 2018 and with some historical data. • Deadwood is suggested as one of the many biodi- versity indicators (Harmon et al., 1986). As the amounts for concrete species are generally un- known, the desired value was set by comparing the current national data and some of the EU27 data. 2.3.6 Suitability of the systematic sampling grid 2.3.6 Primernost sistematične vzorčne mreže The aim of this analysis was to investigate whether the estimates were influenced by periodicity in the population of Slovenian forests. We arranged the per- manent sample plots into 20 km wide strips (odd, even) and aligned them in four cardinal directions (north- south = a 1,2 , east-west = b 1,2 , northeast-southwest = c 1,2 , southeast-northwest = d 1,2 ; Fig. 2). We then tested the differences in variances and mean growing stocks of these eight combinations for the years 2012 and 2018. Additionally, we investigated (2018 data) the autocor- relation of the growing stock with four- and eight-km lags (Isaaks and Srivastava, 1989). Among the 37 west- east parallels with sample plots, 11 line segments with at least seven consecutive sample plots were selected. Because of the small number of segments and plots, we decided not to derive a correlation function. 2.3.7 Statistical computations 2.3.7 Statistični izračuni Familiar design-based statistics, such as sample to- tal, mean, ratio and variance were used (Table 2). The Fig. 2: Division of the country’s area into 20 km wide strips (N-S odd, even; E-W odd, even; NE-SW odd, even; SE-NW = odd, even) Slika 2: Razdelitev površine države na 20 km proge (S-J lihe, sode; V-Z lihe, sode; SV-JZ lihe, sode; JV-SZ = lihe, sode) Acta Sil va e et Ligni 131 (2023), 1–27 7 significance of differences over time was examined us- ing the strategies shown in Table 2. Because of exhaus- tive computations, significance tests were performed only for subjectively selected variables and those con- sidered relevant at the national or regional level. Time series were largely represented by frequency distribu- tions. 2.3.8 Completeness of indicators for the purpose of SFM analyses and reporting 2.3.8 Popolnost kazalnikov za potrebe presojanja TGG in poročanja The completeness of data needed for construct- ing the indicators of SFM was checked by a simple gap analysis. After the list of all sub-indicators was formed, we only determined which sub-indicators could be cal- culated either completely or partly. 3 RESUL TS 3 REZUL T ATI 3.1 Forest area, basal area, stand density index, growing stock 3.1 Površina gozdov, temeljnica, indeks sestojne gostote, lesna zaloga After long-lasting spontaneous afforestation of abandoned agricultural lands (Kobler et al., 2005), occasional reclamation of forest land, and land use conversions, the national forest area began to stabi- lize after 2000 (1,139,200 ± 55,348 ha; forest cover = 56%) and was estimated at 1,214,000 ± 54,663 ha in 2018 (forest cover = 60%). The change in proportions was insignificant (Z = 1.86 < 1.96; P = 0.0314 > α/2 = 0.025). Fifty-two per cent of forests were below 600 m a.s.l. and 48% were above this line. Forests were most abundant in the Dinaric, Alpine and Prealpine ecore- gions. The richest in forests were the forest regions of Tolmin (ca. 155,000 ha), Ljubljana (ca. 139,000 ha), Novo mesto (ca. 102,000 ha) and Kočevje (ca. 102,000 ha) (Fig. 3). The mean basal area increased from 29.4 m 2 /ha ± 1.1 m 2 /ha to 32.2 m 2 /ha ± 1.1 m 2 /ha between 2000 and Estimators/statistics Used for Estimation of totals, means, variances, confidence intervals Total forest area, mean growing stock and increment Estimation of ratios R = Σ (Y i / X i ) Felling/increment ratio Comparison of proportions: Z under H 0 : p 1 –p 2 = 0 Proportions of tree species in successive observations Comparison of two means: T/Z under H 0 : y 1 –y 2 ; pooled and separate (not- pooled) variance approaches Growing stock values, increment, felling Comparison of two means; t-test for independent and dependant samples Growing stock, increment, increment of damaged forests, deadwood comparison Comparison of means; one-way analysis of variance; H 0 : M 1 = M 2 =….. = M n SDI of different ecoregions, forest regions, development phases, grid analysis differences among the growing stock values in the 20 km wide strips, differences in deadwood among ecoregions Comparison of equality of variances: Levene test Comparison of variances in the 20 km wide strips Spatial continuity; autocorrelation Acor = Σ(Z i– Z i+h ) 2 /σ i σ i+h For the 4 km and the 8 km lags Table 2: Statistical techniques used Preglednica 2: Uporabljene statistične metode Fig. 3: Distribution of national forests (in % area = % A) by ecoregions (a) and forest regions (b). % A < > 600 m = % of area below/above 600 m a.s.l. See also Table 1 for abbrevia- tions. Slika 3: Porazdelitev slovenskih gozdov (v % površine = % A) po ekoregijah (a) in gozdnogospodarskih območjih (b). % A < > 600 m = % površine pod/nad 600 m nadmorske višine. Za okrajšave glej tudi Preglednico 1. 8 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? 2012 and then decreased to 30.7 m 2 /ha ± 1.1 m 2 /ha in 2018. The basal area of the forests above 600 m a.s.l. was ca. 17% higher than that of the lowland forests. Although the changes in basal areas over time were statistically significant (all phases from pole2–swl3; P = 0.000), the changes in basal areas within the particu- lar development phases were not (Fig. 4a). The highest basal areas occurred in the Pohorje ecoregion (40 m 2 / ha) and the lowest in the Submediterranean ecoregion (24 m 2 /ha). During the observed period, almost 50% of forestlands had basal areas lower than 30 m 2 /ha. Various analyses of stand density index (SDI) pro- vided detailed insights into stand structures. Between 2000 and 2012, the mean SDI grew steadily from 576 ± 21 to 619 ± 21 and then decreased to 592 ± 21 (2012– 2018); the differences between these means were statistically significant (P = 0.039). Conversely, the dif- ference in mean SDIs between 2000 and 2018 was not significant (P = 0.291). In 2018, the highest mean SDI values occurred in the forest regions of Slovenj Gradec (744 ± 112) and Kranj (701 ± 99) and the lowest in the regions of Sežana (512 ± 77) and Ljubljana (516 ± 55) (Fig. 5a). Its values within the developmental phases remained homogeneous (Fig. 5b). Similarly, the highest average SDIs were found in the Pohorje (615 ± 48) and the Alpine (653 ± 62) ecoregions and the lowest in the Submediterranean (494 ± 60) and Predinaric (552 ± 54) ecoregions. The distribution of forest areas, classified by the SDI class- es in ecoregions, showed that the area proportions with SDIs higher than 800 remained mostly below 20% (exceptions were in the Pohorje ecoregion and in the Alps; Fig. 6a). Additionally, a detailed examination of sawlog stands revealed that about 31% (ca. 261,000 ha) of them had SDIs lower than 500 and 24% of them had SDIs higher than 800 (Fig. 6b). Fig. 4: a) Distribution of mean basal area (BA; m 2 /ha) by devel- opment phases and in unevenly-aged forests between 2000 and 2018. The differences in BA within sawlog1 (P = 0.09) and sawlog2 (P = 0.45) were insignificant. Yst, Pole 1, 2, …, etc. see Table 1 for abbreviations; b) Distribution of forest areas A% by BA (m 2 /ha) classes between 2000 and 2018. Slika 4: a) Porazdelitev povprečne temeljnice (BA; m 2 /ha) po razvojnih fazah in v raznodobnih gozdovih med letoma 2000 in 2018. Razlike v BA znotraj Swl 1 (debeljak 1) (P = 0,09) in Swl 2 (debeljak 2) (P = 0,45) so bile neznačilne. Yst (mladovje), Pole 1, 2 (drogovnjak 1 in 2), … itd. glej Pregled- nico 1 za okrajšave; b) Porazdelitev gozdnih površin A% po razredih BA (m 2 /ha) med letoma 2000 in 2018. Fig. 5: a) Distribution of mean SDI by forest region; b) Distri- bution of mean SDI by development phase (young stands ex- cluded from analysis; within the individual phases, viz. Pole1, Pole2, … Swl3, differences in SDIs between years were insignif- icant; P values ranged between 0.08 and 0.78). Slika 5: a) Porazdelitev povprečnega SDI po gozdnih regijah; b): Porazdelitev povprečnih SDI po razvojnih fazah (mladi sestoji izvzeti iz analize; znotraj posameznih faz, tj. Pole1 (drogovnjak 1), Pole2 (drogovnjak 2), … Swl3 (debeljak 3), so bile razlike v SDI med leti neznačilne; vrednosti P so se gibale med 0,08 in 0,78). Acta Sil va e et Ligni 131 (2023), 1–27 9 As Fig. 7a shows, the spread of SDIs in pole (1, 2) and a sawlog1 stands was large. In a considerable pro- portion of stands, the SDIs were lower than their “nor- mal” values (line segment). The stand structures in the Pohorje and Dinaric ecoregions were quite different (Fig. 7b, 8b). While the stands in the Pohorje ecoregion were fully stocked, the stands in the Dinaric ecoregion were not (especially in sawlogs). The mean growing stock increased from 2000, when it amounted to 299.3 ± 13.8 m 3 /ha, to 2012, when it reached the value of 333.9 ± 13.7 m 3 /ha. It then de- creased to 329.6 ± 13.71 m 3 /ha in 2018 (Fig. 8b). The difference between 2000 and 2012 was significant (F = 4.80; P = 0.002), but the difference between 2012 and 2018 was not (unpaired; t = 0.437; P = 0.66). In 2018, the highest mean growing stocks were observed in the forest regions of Slovenj Gradec (450 ± 60 m 3 /ha) and Nazarje (422 ± 83 m 3 /ha), while the lowest were in the regions of Sežana (199 ± 35 m 3 /ha) and Ljubljana (275 ± 33 m 3 /ha). Similarly, the Pohorje ecoregion had the highest mean growing stock (469 ± 54 m 3 /ha) and the Submediterranean ecoregion the lowest (199 ± 28 m 3 /ha; Fig. 9a). These two ecoregions also made the differences in growing stocks statistically significant (P = 0.000). With the exception of the Prepannonian and Submediterranean lowlands, mean growing stocks Fig. 6: a) Distribution of SDI classes (relative area %) by ecoregions; b) Distribution of area % (A %) by SDI and de- velopmental phase over time. Slika 6: a) Porazdelitev razredov SDI (relativna površina %) po ekoregijah; b) Porazdelitev % površine (A %) po SDI in razvojnih fazah po letih. Fig. 7: a) Relationship between the Dg and N/ha in national forests. Slovenia (n = 744, 2018; missing inaccessible plots without field data). Dots: yellow = young stands; light green = pole1; dark green = pole2; light blue = sawlog1, dark blue = sawlog2, black = sawlog3; Normal line segments: blue = spruce (mountain sites), Slovak tables (SI 100 = 28, productiv- ity level = 2); red = beech (mountain sites), Halay tables (SI 100 = 28, productivity level = 2); dashed blue = spruce, Swiss tables (SI 50 = 18); dashed red = beech, Swiss tables (SI 50 = 18). Swiss tables provide lower values than Slovak (Halay) tables. X-axis: Dg (cm) = middle basal area tree; b) Relation- ship between the Dg and N/ha in the Pohorje ecoregion (n = 51, 2018). Slika 7: a) Razmerje med Dg in N/ha v slovenskih gozdovih. Slovenija (n = 744, 2018; manjkajo nedostopne ploskve brez terenskih podatkov). Točke: rumena = mladovje; svetlo ze- lena = drogovnjak 1; temno zelena = drogovnjak 2; svetlo modra = debeljak1, temno modra = debeljak2, črna = debel- jak3; črte: modra = smreka (gorska rastišča), slovaške tablice (SI 100 = 28, raven produktivnosti = 2); rdeča = bukev (gorska rastišča), Halayeve tablice (SI 100 = 28, stopnja produktivnosti = 2); črtkana modra = smreka, švicarske tablice (SI 50 = 18); črtkana rdeča = bukev, švicarske tablice (SI 50 = 18). Švicarske tablice dajejo nižje vrednosti kot slovaške (Halayeve) tablice. Os X: Dg (cm) = srednje temeljnično drevo; b) Razmerje med Dg in N/ha v ekoregiji Pohorje (n = 51, 2018). 10 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? were higher above the 600 m a.s.l. line (by ca. 20%). Between 2012 and 2018, the growing stock decreased in all developmental phases, except for young stands and unevenly-aged stands (Fig. 9b). 3.2 Age structure and/or diameter distribution, balance of developmental phases, optimal growing stock 3.2 Starostna struktura/porazdelitev prsnih premerov, ravnotežje razvojnih faz, optimal- na lesna zaloga Until the end of 2018, shelterwood and irregular shelterwood were the predominant stand forms of na- tional forests (97%). Their demographic portrayal be- tween 2000 and 2012 was stable (Fig. 10a; first three columns within each phase). However, after 2012 it began to change because of a series of natural events, such as the 2014 ice storm (Kobler et al., 2015), sub- sequent bark-beetle infestations, and occasional snow and wind storms. Although these large-scale events affected forests in various ways, overall changes at the national level were not large; the proportion of younger stands (i.e. Ystd + Pole1,2) decreased from 32% in 2000 to 30% in 2018, while the proportion of older stands (Swl 1,2,3) increased from 68% to 70% (Z Ystd = 0.398 < 1.96; Z Swl = 1.294 < 1.96 => P in both cases > α/2 = 0.025) (Fig. 10a). The distribution of the developmental phases in the altitudinal belts was simi- lar. The diameters of trees (Fig. 10b) were positively skewed in all developmental phases, indicating their large uneveness. Regarding the differences in the area shares of developmental phases among the ecoregions or for- est regions, the 2018 dataset showed that they were large and statistically significant (see details: Fig. 11a, b). The Dinaric, Pohorje and Prealpine ecoregions har- boured more than 70% of older stands. Conversely, a much more favourable ratio between young and older stands was exhibited by the forests in the Submediter- ranean ecoregion (ca. 50% of sawlogs). Similarly, old- er forests accounted for more than 75% of the forest regions of Kranj, Kočevje, Nazarje and Maribor, while they amounted to about 53% in the regions of Tolmin and Sežana. The demography of shelterwood stands was ana- lysed with the normal forest model (Fig. 10a). The mod- Fig. 8: a) Relationship between the Dg and N/ha in the Di- naric ecoregion (n = 157, 2018); b) Mean GS (m 3 /ha) in for- est regions. Slika 8: a) Razmerje med Dg in N/ha v dinarski ekoregiji (n = 157, 2018); b) Povprečna lesna zaloga (GS, m 3 /ha) v gozd- nogospodarskih območjih. Fig. 9: a) Mean growing stock by ecoregions and altitude belts in ecoregions; b) Mean growing stock in developmen- tal phases (both 2018). Large differences in growing stock in unevenly-aged stands are due to the transition of some plots from evenly aged into unevenly aged. Slika 9: a) Povprečna lesna zaloga po ekoregijah in višinskih pasovih v ekoregijah; b) Povprečna lesna zaloga v razvojnih fazah (oboje 2018). Velike razlike v lesni zalogi v raznodob- nih sestojih so posledica prehoda nekaterih ploskev iz eno- dobnih v raznodobne sestoje. Acta Sil va e et Ligni 131 (2023), 1–27 11 el revealed shortages of young and surpluses of older stands. The following findings are worth mentioning: • In 2018, Slovenian forests lacked 169,152 ha of young stands (110,835 ha of young stands, approx. the area of the whole forest region of Postojna, and 58,417 ha of pole stands, approx. the area of all for- ests in the region of Bled). At the same time, there was a surplus of older stands in the same amount. • The balanced growing stock was set at 296 m 3 /ha (only shelterwood) and at 297 m 3 /ha combined with unevenly-aged stands. A value of 276 m 3 /ha was computed for the forests below the 600 m a.s.l. line and 303 m 3 /ha for forests above this line. • The balanced growing stock was lower than the optimal growing stocks (derived with the Swiss and Slovak yield tables) that were set at 319 m 3 /ha and 421 m 3 /ha, respectively. Similarly, a simulation with the balanced growing stock, computed with the values of the Burgenland and Swiss developmental phases (Österreichische … s. a; WSL, 2022), amount- ed to 347 m 3 /ha and 322 m 3 /ha, respectively. 3.3 Increment and felling 3.3 Prirastek in sečnja The 2012–2018 gross increment without ingrowth and half increment of cut trees (GI) was estimated at 6.85 ± 0.30 m 3 /ha and was lower than the value be- tween 2000 and 2007, which was 7.92 ± 0.32 m 3 /ha (the 2018 gross increment with ingrowth and half in- crement of cut trees equalled 7.86 ± 0.32 m 3 /ha, while the 2012 value was 8.60 ± 0.33 m 3 /ha). With the ex- ception of the Alpine ecoregion, gross increment first Fig. 10: a) Distribution of the developmental phase areas (in %) between 2000 and 2018 (first four columns). The fifth column (% A_Model) represents the areas derived by the normal forest model (Area = 1,180,800 ha, production peri- od/rotation = 125 years); b) Distribution of DBH classes (in % of trees of each developmental phase) by developmental phases in 2018. An exponentially decaying curve is signifi- cant for most developmental phases. Slika 10: a) Porazdelitev površin razvojnih faz (v %) med letoma 2000 in 2018 (prvi štirje stolpci). Peti stolpec (% A_ Model) predstavlja površine, izračunane z modelom normal- nega gozda (površina = 1.180.800 ha, proizvodna doba = 125 let); b) Porazdelitev razredov DBH (v % dreves posamezne razvojne faze) po razvojnih fazah v letu 2018. Za večino raz- vojnih faz je značilna eksponentno padajoča krivulja. Fig. 11: a) Distribution of developmental phase area shares by ecoregions. Significance of differences in the shares of sawlogs: Dinaric vs Submediterranean–significant: Z = 4.96 > 1.96 at P = α/2 = 0.975; Dinaric vs Pohorje–insignificant: Z = 0.74 < 1.96 at P = α/2 = 0.975); b) Distribution of develop- mental phase area shares by forest regions. Slika 11: a) Porazdelitev deležev površin razvojnih faz po ekoregijah. Značilnost razlik v deležih debeljakov: dinarska proti submediteranski – značilno: Z = 4,96 > 1,96 pri P = α/2 = 0,975; dinarska proti pohorski–neznačilno: Z = 0,74 < 1,96 pri P = α/2 = 0,975); b) Porazdelitev deležev površin razvo- jnih faz po gozdnogospodarskih območjih. 12 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? increased and then decreased in all other ecoregions (Fig. 12a). A similar trend was observed in forest re- gions (Fig. 13a). Quite a different trend was observed in the Bled forest region, where gross increment was continuously decreasing and in Murska Sobota, where it was constantly increasing. In the forest region of Tol- min, gross increment remained stable over the period. Between 2012 and 2018, the mean annual felling without half increment of cut trees was estimated to be 5.94 ± 1.18 m 3 /ha (with half increment 6.27 ± 1.2 m 3 /ha) and was higher than that between 2007 and 2012, which equalled 4.03 ± 0.80 m 3 /ha. Since 2000, the mean annual felling increased in all regions except the Pre-Pannonian, where it decreased (Fig. 12b, 13b). During the 2000–2007, 2007–2012 and 2012–2018 periods, gross increment and annual felling developed with different trends. While gross increment first in- creased in most ecoregions and forest regions despite increasing annual felling, this direction reversed after 2012. This fact is noteworthy because not all ecore- gions and forest regions were impacted by hazardous events and increased felling. From 2000 to 2012, the mean annual felling in the developmental phases was lower than the gross incre- ment (GI) (Fig. 14a). From 2000 to 2007, the ratio of felling and increment (R ACGI ) was 47% and increased to 52% between the years 2007 to 2012. However, after 2012, a series of consecutive hazardous events struck forests, leading to a significant change in trend, and the R ACGI increased to 88% (Fig. 14b, see SLO). Fig. 12: a) Mean gross increment (GI) by ecoregions between 2000 and 2018. In 2018, differences in gross increment be- tween ecoregions and forest regions (Fig. 13a) were signifi- cant (in both cases P = 0.0000). The difference in average annual increment (SLO) between 2000 and 2018 was insig- nificant (t = -0.089; df > 1000 => t => Z << 1.96, P = 0.0975); b) Mean annual cut (AC) by ecoregions between 2000 and 2018. In 2018, differences in felling between ecoregions and forest regions were insignificant. The difference in average annual felling (SLO) between 2007 and 2018 was significant (t = -4.01 < -1.96; df unpooled = 382 => t = 1.96 for α/2 = 0.025). Slika 12: a) Povprečni bruto prirastek (GI) po ekoregijah med letoma 2000 in 2018. V letu 2018 so bile razlike v bruto prirastku med ekoregijami in gozdnogospodarskimi območji (slika 13a) značilne (v obeh primerih P = 0,0000). Razlika v povprečnem letnem prirastku (SLO) med letoma 2000 in 2018 je bila neznačilna (t = -0,089; df > 1000 => t => Z << 1,96, P = 0,0975); b) Povprečni letni posek (AC) po ekore- gijah med letoma 2000 in 2018. V letu 2018 so bile razlike v poseku med ekoregijami in gozdnogospodarskimi območji neznačilne. Razlika v povprečnem letnem poseku (SLO) med letoma 2007 in 2018 je bila značilna (t = -4,01 < -1,96; df un- pooled = 382 => t = 1,96 za α/2 = 0,025). Fig. 13: a) Mean gross increment (GI) by forest re- gions between 2000 and 2018; b) Mean annual felling (AC) by forest regions between 2000 and 2018. Slika 13: a) Povprečni bruto prirastek (GI) po gozdnog- ospodarskih območjih med 2000 in 2018; b) Povprečni letni posek (AC) po gozdnogospodarskih območjih med 2000 in 2018. Acta Sil va e et Ligni 131 (2023), 1–27 13 Apart from the forests in the Prepannonian ecore- gion (R ACGI = 0.29), the events affected all forests. In the Dinaric, Submediterranean and Pohorje ecoregions, the ratios reached 1.12, 1.12 and 1.05, respectively. In the other regions they ranged from 0.83 to 0.97. Of all forest regions, the largest increase in felling took place in the forest regions of Postojna (by a factor of 2.20), Ljubljana (1.50), Nazarje (1.29) and Kranj (1.07). Of 702 paired plots (viz. measured consecutively) between 2007 and 2018, 143 plots were affected by the hazardous events (131 by one event, 12 by two) (Fig. 15a, b, Table 3). • Before the events, the growing stock of affected plots was above average compared to all meas- ured plots (∆ = + 10.3 m 3 /ha = 354.1 m 3 /ha–343.8 m 3 /ha). In 2018, these plots fell below the average (∆ = -35.5 m 3 /ha = 336.5 m 3 /ha–301.0 m 3 /ha). • In the period 2012–2018, the change in growing stock on the damaged plots was estimated to be -53.1 m 3 /ha. The difference was 7 times greater than the mean of all plots measured consecutively (702 plots), whose difference was -7.3 m 3 /ha. Because of nega- tive differences on all plots, the overall growing stock decrease was estimated at -4.3 m 3 /ha (2012–2018). • Similarly, the decrease in the increment on affected plots was much larger (increment difference -2.04 m 3 /ha year) compared to unaffected plots. During the period 2012–2018, the increment decreased everywhere. • The felling on the damaged plots doubled com- pared to the plots without damage. The average felling was almost 2 m 3 /ha higher in the period 2012–2018 than in the period 2007–2012. Fig. 14: a) Gross increment (GI) and annual felling (AC) by developmental phases between 2000 and 2018 (both in m 3 / ha/y); b) R ACGI : Ratio of annual felling and gross increment in developmental phases between 2000 and 2018, in uneven- aged stands and Slovenia (the ratio for young stands not shown; its values were 19.42 between 2007 and 2000, 15.45 between 2007 and 2000 and 10.35 between 2018 and 2012). Slika 14: a) Bruto prirastek (GI) in letni posek (AC) po raz- vojnih fazah med letoma 2000 in 2018 (oboje v m 3 /ha/leto); b) R ACGI : Razmerje med letnim posekom in bruto prirastkom v razvojnih fazah med letoma 2000 in 2018, v raznodobnih sestojih in Sloveniji (razmerje za mlade sestoje ni prikazano; njegove vrednosti so bile med letoma 2007 in 2000 19,42, med leti 2007 in 2000 15,45 oz. 10,35 med letoma 2018 in 2012). Fig. 15: Growing stock changes (D–difference from the mean growing stock) between 2012 and 2018 and damaged areas (ice storm, bark beetles, windthrows; Pregledovalnik …, s. a.) by ecoregions (a) and by forest regions (b) Slika 15: Spremembe lesne zaloge (D–razlika od povprečne lesne zaloge) med letoma 2012 in 2018 ter prizadete površine (žledolom, podlubniki, vetrolom; Pregledovalnik …, b. l.) po ekoregijah (a) in po gozdnogospodarskih območjih (b) 14 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? • A general increase in felling and the decrease in in- crement should be considered the main reasons for the average growing stock decrease. 3.4 Diversity of tree species, species mixtures, forest regeneration, naturalness and dead- wood 3.4 Različnost drevesnih vrst, mešanost sestojev, pomlajevanje, naravnost in odmrla drevnina The most abundant (in volume) tree species in 2018 were beech (33.4%) and spruce (28.6%), fol- lowed by fir, sessile oak and all others with substan- tially lower volume shares (Fig. 16a, b). While beech’s share increased, the share spruce and fir decreased. All changes were significant (Z spruce = 6.94; Z beech = 3.27; Z fir = 3.73; all Z values > 1.96 => P < α/2 = 0.025). In general, between 2000 and 2018, the tree composition of Slovenian forests changed slowly. While the share of beech increased only recently, the share of spruce began declining between 2000 and 2007 and again after 2012. The dynamics of the change for fir were less clear. In the case of all other species, the changes were small. A detailed data analysis revealed that the shares of fir, pine sp., sessile oak, sycamore maple, and many species with much smaller shares (e.g. larch, ash, wych elm, part of Ocon and Obrdl) have not increased despite their ecological, economic and environmen- tal significance (Dakskobler et al., 2013a; Dakskobler et al., 2013b; Dakskobler et al., 2016). Conversely, the share of other broadleaves (Obrdl) increased. The 2018 distributions of species count by diam- eter classes were more informative. As shown in Fig. 17a, b, only the distribution of beech individuals was balanced, while fir, sycamore maple, sessile oak and Event n 1 Growing stock Growing stock difference Gross increment 2 Felling 3 Ingrowth Mortality 2007 2012 2018 2007/12 2012/18 2007/12 2012/18 2007/12 2012/18 2007/12 2012/18 2007/12 2012/18 m 3 /ha m 3 /ha m 3 /ha m 3 /ha m 3 /ha m 3 /ha y m 3 /ha y m 3 /ha y m 3 /ha y m 3 /ha y m 3 /ha y m 3 /ha y m 3 /ha y NO 559 311.6 341.1 345.6 29.5 4.7 7.90 7.04 4.15 5.05 0.40 0.33 0.99 1.78 O 143 318.8 354.1 301.0 35.3 -53.1 8.03 5.99 3.55 10.41 0.32 0.21 1.03 4.07 (NO+O) 4 702 313.1 343.8 336.5 30.7 -7.3 7.93 6.83 4.02 6.14 0.38 0.31 1.00 2.25 SLO 313.7 333.9 329.6 20.2 -4.3 7.92 6.85 4.10 5.94 0.38 0.33 0.99 2.23 Remark: 1 n = 724 in 2007, n = 760 in 2012, n = 759 in 2018; NO = event did not occur; O = event did occur; 2 growing stock gross increment (without ingrowth and half increment of cut trees); 3 felling (without half increment of cut trees); 4 all plots measured consecutively. Opomba: 1 n = 724 leta 2007, n = 760 leta 2012, n = 759 leta 2018; NO = dogodek se ni zgodil; O = dogodek se je zgodil; 2 bruto prirastek lesne zaloge (brez prirastka in polovice prirastka posekanih dreves); 3 posek (brez polovice prirastka posekanih dreves); 4 vse ploskve izmerjene zaporedno. Table 3: Data for the plots measured consecutively (2007–2012–2018) Preglednica 3: Podatki za zaporedno izmerjene ploskve (2007–2012–2018) Fig. 16: a) Tree species abundance in SLO forests expressed in volume shares (% GS) between 2000 and 2018. PicA = Pi- cea abies, AbA = Abies alba, Pine = Pinus sp., Ocon = other conifers, FagS = Fagus sylvatica, Quercus = Quercus sp., Ac- erP = Acer pseudoplatanus, CarpB = Carpinus betulus, OBrdl = other broadleaves; b) Tree species abundance by ecoregions. Slika 16: a) Številčnost drevesnih vrst v slovenskih gozdovih izražena v prostorninskih deležih lesne zaloge (% GS) med letoma 2000 in 2018. PicA = Picea abies, AbA = Abies alba, Bor = Pinus sp., Ocon = drugi iglavci, FagS = Fagus sylvatica , Quercus = Quercus sp., AcerP = Acer pseudoplatanus, CarpB = Carpinus betulus, OBrdl = drugi listavci; b) Številčnost drevesnih vrst po ekoregijah. Acta Sil va e et Ligni 131 (2023), 1–27 15 Scotch pine lacked saplings (ingrowth) and trees with diameters below 30 cm. Conversely, hornbeam, sweet chestnut and some other species exhibited shortages in larger diameter classes. The counts of spruce trees also differed, with the reduction in ingrowth largely at- tributed to hazardous events and an intentional reduc- tion in share. The distributions of the proportions of beech, fir and spruce by diameter classes in ecoregions (Fig. 18a, b) were even more insightful. Beech exhibited higher ingrowth rates of over 20% in all ecoregions except the Submediterranean. On the other hand, the ingrowth of fir remained balanced and retained significant shares only in the Pohorje ecoregion. The largest decline in fir occurred in the Dinaric ecoregion, where its share was sustained by the presence of abundant large trees. In the Alpine ecoregion, the share of fir also was relatively stable, maintaining an average share of 5% across all DBH classes. The percentage of spruce in diameter classes also varied greatly. In contrast to the species mentioned earlier, this variation is not worrisome, as spruce in Slovenia largely inhabits secondary forest sites (Levanič et al., 2020). Forests were primarily classified as seminatural (Forest Europe, 2020). Forest regeneration was mostly natural and lagged behind the required demographic shares. Given that i) the average share of regenerated area between 2000–2018 was 45,300 ha (3.85%) and that ii) young growth needs ca. 20 years to overgrow the first developmental phase, it would take more than 500 years to regenerate all shelterwood forests in the country. In 2018, the volume of deadwood amounted to 24.2 ± 2.39 m 3 /ha. It increased significantly after 2012 (P = 0.0002) when it was estimated at 19.83 ± 1.93 m 3 /ha. The 2018 deadwood volume also differed significantly between ecoregions (P = 0.003). The highest mean Fig. 17: a) Percentages of tree species (based on counts) by diameter classes (every DBH class is 100%). Of all ingrown trees in 2018, the percentage of fir trees was 3.8%. FagS = Fagus sylvatica, PicA = Picea abies, CarpB = Carpinus betulus, OstryC = Ostrya carpinifolia, AbA = Abies alba, AcerP = Acer pseudoplatanus, QuerS = Quercus sp., PinS = Pinus sp., CastS = Castanea sativa, FraxO = Fraxinus ornus; b) Relative percent- ages of beech trees by diameter classes in ecoregions (ex: No. of beech species with DBH = 10–12 cm / all species with DBH = 10–12 cm). Slika 17: a) Odstotki drevesnih vrst (na podlagi števila) po razredih premera (vsak razred DBH je 100 %). Od vseh vras- lih dreves v letu 2018 je bil delež jelk 3,8 %. FagS = Fagus sylvatica, PicA = Picea abies, CarpB = Carpinus betulus, OstryC = Ostrya carpinifolia, AbA = Abies alba, AcerP = Acer pseudo- platanus, QuerS = Quercus sp., PinS = Pinus sp., CastS = Cas- tanea sativa, FraxO = Fraxinus ornus; b) Relativni odstotki bukev po razredih premera v ekoregijah (npr.: št. vrst bukve z DBH = 10–12 cm / vse vrste z DBH = 10–12 cm). Fig. 18: Relative percentages of fir (a) and spruce (b) trees by diameter classes in ecoregions. The peak of fir in the Di- naric ecoregion (36%, DBH > 50 cm) serves as a reminder of once common fir-beech forests. Slika 18: Relativni deleži jelke (a) in smreke (b) po razredih premera v ekoregijah. Izrazit vrh jelke v dinarski ekoregiji (36 %, DBH > 50 cm) spominja na nekoč pogoste jelovo-bu- kove gozdove. 16 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? volumes were found in the Alpine (31.4 m 3 /ha) and the Dinaric ecoregions (30.5 m 3 /ha), while the lowest were in the Prepannonian (18.5 m 3 /ha) and Submedi- terranean (20.4 m 3 /ha) ecoregions. The increased mean values reflected the intensity of disturbances and were the largest in the Dinaric (7.9 m 3 /ha), Alpine (5.7 m 3 /ha) and Pohorje ecoregions (4.7 m 3 /ha). It is worth noting that, according to the 2020 Forest Condi- tion report (Forest Europe, 2020), Slovenia belongs to the group of countries with the highest average dead- wood volume in its forests. 3.5 Evaluation of sustainability with selected indicators 3.5 Ocena trajnostnega razvoja z izbranimi ka- zalniki Apart from forest area and deadwood, the statuses of the other indicators were found to be unfavourable (Table 4). The most critical issues were the demo- graphic portrayal of stands and tree species compo- sition. Both factors also affect forest biodiversity and the conservation status of forest habitat types (Kutnar and Dakskobler, 2014; Grošelj et al., 2015; Kovač and Grošelj, 2018). Another concern in the long run was the felling/increment ratio. While underharvesting helped raise growing stocks, it contributed to forest ageing. As already shown (Ch. 3.1), ca. 29% of sawlogs 2,3 had considerably low SDIs (< 500; low stocked stands) and could be treated similarly to overaged stands. Tree spe- cies and regeneration also were determined to be unfa- vourable. The shares of spruce were quite high, while the shares of pine and fir declined (Dinaric, Predinaric ecoregion). By contrast, the data for beech clearly indi- cated that this species was making a comeback, while the share of fir declined (only ca. 4% in ingrowth; Fig. 18a, SLO). Lastly, the regenerated forest area was low and should have amounted to about three times the size of its current area. The differences in factors between the current and desired values of indicators range from 0.33 for regen- eration area (min.) to 1.6 for deadwood (min). In the case of tree species, the factors range between 0.05 for Austrian pine (current = ingrowth), 0.075 for oak and 0.9 for beech. The future outlook seems especially discouraging when the discrepancies between the cur- rent and the desired values are expressed in the time in years needed to reach the desired states. Consider- ing the current change dynamics, it may take decades to significantly improve the present forest conditions (e.g. regeneration; if increased by 33% every 10 years, it would take more than 60 years). Based on the pre- sented facts, the current direction of national forest de- velopment is discouraging and may be considered as a departure from sustainable forest development. 3.6 Estimation of the suitability of the 4 x 4 km systematic sampling grid 3.6 Ocena primernosti sistematične vzorčne mreže 4 x 4 km The mean growing stock values of differently ori- Indicator Current value Desired value Condition Reference/compared values Forest area 1,214,400 ha (60%) 50–60% Favourable The EU27 forest cover is ca. 40%. Growing stock (GS) Unbalanced = 329.6 m 3 /ha 325–350 m 3 /ha Unfavourable Current normal = 297 m 3 /ha, optimal = 325–350 m 3 /ha. Area Young/ swl 1,2,3 /uneven aged 29% : 68% : 3% 41% : 52% : 7% Unfavourable Lack of young stands, many sawlogs ove- raged; ca. 40 years needed to improve the portrayal. Felling/increment 2018/2000 average R = 63% R 2018 = 88% 90–110% Unfavourable Beech SI 28 = increment 7.2 and felling 7.2 m 3 / ha; R = 100% Spruce SI 28 = increment 7.7 and felling 7.7 m 3 / ha; R = 100% Tree species 1 Spruce 28.6% (20.4%) Fir 7.9% (3.8%) Pine (0.3%) 5.5% Beech 33.3% (29.5%) Oak 7.5% (0.6%) Maple 3.7% (2.5%) Other 13.5% (15.8%) 2 Spruce 25–29% Fir 8–15% Pine 6–10% Beech 33–40% Oak 8–15% Noble brdl. 4–10% Other 10–15% 3 Unfavourable Unfavourable Unfavourable Favourable Unfavourable Unfavourable Favourable 1 Values in brackets refer to ingrowth 2 All desired values refer to the total share. 3 Reference values in Fig. 17 and 18. Apart from beech and spruce, the shares of the other tree species in the ingrowth are unfavo- urable. Regenerated area Area ca. 4% 12–14% Unfavourable Deadwood 24 m 3 /ha 15–25 m 3 /ha Favourable Table 4: Assessment of sustainability (current values as of 2018) Preglednica 4: Ocena trajnosti (sedanje vrednosti iz leta 2018) Acta Sil va e et Ligni 131 (2023), 1–27 17 ented odd and even data strips from 2018 ranged be- tween 320.19 and 339.39 m 3 /ha and differed from the national mean growing stock (329.63 m 3 /ha; 2018) by less than 3% (Table 5). While the differences between the variances in the strips were significant (Levene; df = 7, F = 2.53, P = 0.0134), the differences between the mean growing stocks were not significant (4 cardi- nal directions x 2 strips; ANOVA; df = 7, F = 0.416, P = 0.893; Fig. 19a). Conversely, the same analysis carried out with the 2012 data revealed no significant differ- ences between the variances or means (Levene; df = 7, F = 1.82, P = 0.078; min-max. differences in s.d. = ± 1.5 % to ± 8.3 %; ANOVA; df = 7, F = 0.25, P = 0.971). An erratic pattern was also exhibited in the spatial continuity. Instead of showing decreasing correlations by distance, the correlations of the four km lags of se- lected west-east segments were in the range of + 0.39 to -0.78, while the values of the eight km lags were in the range of +0.57 to -0.74. Considering all the means and variances, we concluded that the estimates were not affected by cyclic periodicity. As shown, the differ- ences between the variances in 2018 were due to the hazardous events. 3.7 Completeness of indicators for the purpose of SFM analyses and reporting 3.7 Popolnost kazalnikov za potrebe presojanja TGG in poročanja o njem Out of the 34 complex indicators of SFM (Forest Eu- rope, 2022), between 15 and 19 of them are supposed to be collected by NFIs. Considering the many possi- ble combinations generated by stratification factors such as other wooded lands and forests available for wood supply, the number of sub-indicators increases significantly. Regarding the available data in 2018, we conclude that the FFECS database made it possible to derive incomplete estimates on eight SFM indicators. It also did not allow for estimates to be derived for dif- ferent reporting processes, which differ in area thresh- olds and indicator definitions (e.g. national vs Forest Europe definitions). stripp 1 Combination a 1, 2 2 Combination b 1, 2 Combination c1, 2 Combination d1, 2 n mean GS m 3 /ha n mean GS m 3 /ha n mean GS m 3 /ha n mean GS m 3 /ha N-S odd N-S even E-W odd E-W even NE-SW odd NE-SW even SE-NW odd SE-NW even Odd 386 320.90 376 333.06 367 325.92 361 334.92 Even 373 339.39 383 326.25 392 333.10 398 324.83 All 759 329.63 759 329.63 759 329.63 759 329.63 Remark: n = number of plots; GS = growing stock; Combination (see Fig. 2); 1 = largest differences; 2 = smallest differences Opomba: n = število ploskev; GS = lesna zaloga; kombinacija (glej Sliko 2); 1 = največje razlike; 2 = najmanjše razlike Table 5: Mean growing stock values of differently ori- ented odd and even 20 km wide strips Preglednica 5: Povprečne lesne zaloge izračunane iz ploskev ležečih na lihih in sodih 20 km širokih različno orientiranih pasovih Fig. 19: a) Growing stock 2018 (m 3 /ha) in 20 km wide strips; b) Average correlations for the 4 km and 8 km lag for 11 seg- ments (each dot pair viz. orange and grey, represents one line segment). Slika 19: a) Lesna zaloga 2018 (m 3 /ha) v pasovih širine 20 km; b) Povprečne korelacije za razpon 4 km in 8 km za 11 segmentov (vsak par pik, tj. oranžna in siva, predstavlja en segment črte). 18 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? SFM Indicator name (shortened) Availability of estimates Demanded Source 1.1 Area of forest and other wooded land, classified by… A: forest area FE + LU NFI N/A: AWS, OWL, PFL, FTy, OLWT 1.2 Growing stock (GS) …, classified by… A: GS of forest area FE + LU NFI N/A: GS of OWL, AWS, PFL, FTy and OLWT 1.3 Age structure and/or diameter distribution of, by … A: diameter distribution, developmental phases; forest area FE NFI N/A: diameter distribution, developmental phases; OWL, OLWT P/A: age structure; different methods, inconsistent data 1.4 Carbon stock and carbon stock changes in … A: carbon pools (living wood biomass, litter, deadwood, soil) for forest area FE + LU NFI N/A: PFL, OWL, OLWT, change 2.1 Deposition and concentration of air pollutants on forest and … Not NFI FE ICP 2.2 Chemical soil properties (pH, CEC, C/N, organic C, base sat.) A: forest area (pH, C/Nm organic C) FE NFI N/A: CEC and base saturation, change, soil type, OWL, OLWT 2.3 Defoliation of one or more main tree species on … N/A: FTy, FPL, OWL FE NFI-ICP 2.4 Forest and other wooded land with damage classified by … N/A: tree level, PFL, FTy, OWL, FTy FE NFI N/A: damaged area of PFL, FTy, OWL, FTy 2.5 Trends in forest land degradation ... NEW FE NFI 3.1 Balance between … Increment/felling of wood … A: forest area FE + LU NFI N/A: PFL/AWS, OWL, OLWT 3.2 Quantity and market value of roundwood Not NFI FE FSTAT 3.3 Quantity/market value non-wood A: game; P/A: honey; not collected by NFI FE FSTAT N/A: quantity in forests, OWL 3.4 Value of marketed services N/A: services in forest area, OWL FE FSTAT 4.1 Tree species A: share in GS in forest area FE NFI N/A: species area in forests, OWL; exotic, invasive, other species in forests and OWL Table 6: Completeness of SFM indicators (as of 2018) Preglednica 6: Popolnost kazalnikov TGG (stanje leta 2018) Acta Sil va e et Ligni 131 (2023), 1–27 19 4.2 Forest regeneration/expansion A: forest regeneration in even-aged forests (determined as developmental phase) FE NFI N/A: forest expansion, regenerated patches in uneven-aged stands and older sawlogs (2 and 3), regenerated patches in OWL, composition and sapling densities of regenerated patches, damage on saplings 4.3 Area of forest and other wooded land by class of naturalness A: forest area FE NFI N/A: OWL 4.4 Area of forest and other wooded land dominated by introduced tree species. … N/A (sparse grid): forest area FE NFI N/A: OWL, density of species, % of area 4.5 Volume of standing and lying deadwood A: forest area FE + LU NFI N/A: OLWT, change in OWL 4.6 Genetic resources Not NFI FE EUFORGEN 4.7 Area of continuous forest and patches of forest separated by NEW FE NFI N/A: forest area, OWL, forest habitat type 4.8 Number of threatened forest species, classified Not NFI FE BM 4.9 Area of forest and other wooded land protected to conserve ... N/A: forest area, OWL FE BM-NFI 4.10 Common breeding bird species NEW FE BM-NFI 5.1 Protective forests–soil, water and other ecosystem functions N/A: forest area, OWL FE NFI Not NFI 6.1-9 Maintenance of other socioeconomic functions and conditions Not NFI FE FSTAT 6.10 The use of forests and other wooded land for recreation in .. N/A: forest area FE NFI, FSTAT Remark: SFM = No. of SFM indicator; A = estimate available; N/A = estimate non-available; P/A = estimate partly available (for some variables); AWS = area available for wood supply; OWL = other wooded lands; PFL = productive forest land; FTy = forest type; OLWT = other lands with trees; GS = growing stock; CEC = cation exchange capacity; FE = Forest Europe; LU = LULUCF = land use, land use change and forestry; EUFORGEN = Forest genetics monitoring; BM = biodiversity monitoring; FSTAT = forest statistics. Opomba: SFM = št. indikatorja TGG; A = ocena na voljo; N/A = ocena ni na voljo; P/A = ocena delno na voljo (za nekatere spremenljivke); AWS = območje, ki je na voljo za oskrbo z lesom; SOVA = druga gozdnata zemljišča; PFL = produktivno gozdno zemljišče; FTy = vrsta gozda; OLWT = druga zemljišča porasla z drevesi; GS = lesna zaloga; CEC = kapaciteta kationske izmenjave; FE = Gozdovi Evrope; LU = LULUCF = raba zemljišč, sprememba rabe zemljišč in gozdarstvo; EUFORGEN = Forest genetics monitoring; BM = spremljanje biotske raznovrstnosti; FSTAT = gozdna statistika. 20 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? 4 DISCUSSION 4 RAZPRAVA Slovenia’s forest area is stable and Slovenia ranks third in the EU 27 (Forest Europe, 2020). The average growing stock is also the third highest at approx. 330 m 3 /ha (Forest Europe, 2020). The balanced growing stock is slightly lower at 297 m 3 /ha, a value similar to the calculation from 2012, which was 290 m 3 /ha (Bončina, 2017). However, after several years of continuous growth, the average growing stock started to decrease after 2012 in all developmental phases. These phases re- mained relatively homogeneous and were character- ized by unsuitable tree densities and average growing stocks. Compared to neighbouring Austrian (of Carin- thia, Styria and Burgenland states only) and the Swiss forests, our developmental phases had lower mean growing stocks (viz. sawlogs1 by 10–30%; sawlogs2 by 10–70%; sawlogs3 by 19–90% (Österreichische … s. a; WSL, 2022)). The Slovak yield tables (Kotar, 2003) also predict a more distinctive stand heterogeneity. Several decades of an inadequate felling increment ratio affected the developmental phase structure, leading to a deficit of young forests. While the ratio of young and older stands in our forests was estimated at R SLO = 0.29:0.71, the same ratio in the forests of the Austrian states is R AT = 0.45:0.55, and in the Swiss for- ests it is R CH = 0.34:0.66 (Österreichische … s. a; WSL, 2022). Based on the results and these comparisons, we argue that only demographically balanced seminatural forests can develop sustainably and provide essential ecological ecosystem services (e.g. erosion protection, water purification, wood) to societies. In our view, SFM should always seek a balance between forest structure and the diverse ecosystem services it provides, without undermining the forest structure itself. While search- ing for acceptable options, shifts from the demographic balance are possible and often necessary (e.g., planned increase of the growing stock, restoration of damaged areas, addressing imbalances in the market). However, such shifts should be spatially and temporally limited, justified and agreed upon with forest owners. The felling/increment ratio between 2000 and 2018 was estimated at 0.63, the lowest among the three compared nations and quite low in Europe (For- est Europe, 2020). The gross increment decreased in all ecoregions and in most forest regions, apart from Tolmin, Sežana and Murska Sobota. Similarly, a de- crease in growing stock was observed. Both facts, part- ly affected by the natural events, play a significant role in carbon management. The decrease in increment and growing stock, along with a non-optimal SDI (Hladnik and Žižek Kulovec, 2014), suggest that the present Slovenian forests, at given stand densities, are already saturated with wood (carbon) biomass, similar to Eu- ropean forests (Nabuurs et al., 2013). Consequently, as the country cannot increase the carbon sink by es- tablishing new forest areas, it must regulate it within existing forest boundaries. As a result, alternatives for a higher carbon sink should be sought in newly estab- lished stands (future generations) and prompt forest management capable of performing timely manage- ment actions. If these new stands have site-suitable tree species compositions (Pardos et al., 2021) and balanced demographic portrayals, they will also be more resilient to disturbances and less risky to manage (Brang et al., 2013; Thom and Seidl, 2016; Levanič et al., 2020; Kauppi et al., 2022). There is a larger poten- tial for storing carbon in optimal developmental phase stocking (higher SDIs) and a more balanced felling-in- crement ratio. Notably, recent simulations suggest that optimal carbon storage can only be achieved through sustainable felling (Thürig and Kaufmann, 2008; 2010; Jevšenak et al., 2020). Similarly, our simulation with balanced growing stocks shows that if the develop- mental phases of Slovenian forests had growing stocks as high as the forests of Burgenland or Switzerland, the Slovenian balanced growing stock would amount to 347 m 3 /ha and 322 m 3 /ha, respectively. However, if the areas of developmental phases remained unbalanced (as they are), the unbalanced growing stock would reach 408 m 3 /ha or 356 m 3 /ha. The existing tree species composition is facing many challenges. Among the three main species, the share of spruce has declined due to many hazardous events. Regardless, the share of spruce continues to remain high in the ecoregions of Pohorje and the Alps and in the lowlands. The future of fir is much more questionable. Although its current share is still signifi- cant due to many large trees (Fig.19b) in the stands, its proportion in the ingrowth does not exceed 4%. Fir regenerates normally only in the Pohorje ecoregion, and its share is declining in the Dinaric and Predinaric regions, where it once formed large-scale fir-beech- spruce forests. Although the FFECS has not provided evidence about the drivers of its low share, it is very likely that the carrying capacities of fir-mixed and some other forests are undermined by game browsing (Klopčič et al., 2010). Beech, the third dominant spe- cies, is slowly reclaiming sites from which it was once wiped out and is becoming the dominant species on many sites where it was previously admixed (Poljanec et al., 2010; Gozdnogospodarski načrt …, 2012; Kovač et al., 2018). This process has also been observed in Acta Sil va e et Ligni 131 (2023), 1–27 21 some other EU countries (Mölder et al., 2014). The shares of other tree species such as pine sp., noble broadleaves, larch, willow, alder and poplars continue to remain very low and should be increased in differ- ent forest types to improve the general forest and their forest habitat type biodiversity. Also insufficiently large is the average regenerated forest area, totalling ca. 4%. In neighbouring Austrian forests, the regeneration area totals ca. 21–26 %, while in Swiss forests it is 9% (Österreichische … s. a; WSL, 2022). The share of regenerated forests ranks Slovenia among the countries with the lowest share of regener- ation in Europe (Forest Europe, 2020). The problem of extremely slow forest rejuvenation has been observed for a long time. Pipan, who attributed this issue to great inertia in the state forest management, reported that ca. 1,873 ha of forests were regenerated annually between 1947 and 1967 (Pipan, 1967). Alongside for- est rejuvenation, some beneficial actions such as the local reduction of game and stand fencing need to be considered to improve the conservation status of for- est habitat types. Many of them (some covering large areas, e.g., 91K0-Illyrian beech forests, 91L0–Illyrian oak-common hornbeam forests) are changing their portrayals and slowly turning into homogenous stands due to the suppression of their dominant species such as fir, sessile (and pedunculate) oak, maple and ash, causing the depletion of their natural biodiversity (Kutnar and Dakskobler, 2014; Kovač et al., 2016) Regarding very limited possibilities for deriving the complete set of SFM indicators and suggestions for im- provements (Bončina, 2017; Kovač et al., 2019a; Kovač et al., 2019b), the Slovenian national forest inventory- ing should undergo significant improvements, espe- cially in terms of the amount of collected variables and inventory integration. 5 CONCLUSIONS – HOW TO MOVE FORWARD 5 SKLEPI – POGLED V PRIHODNOST As assumed, the intensive regeneration of forests, coupled with prompt management in existing stands, is a reliable approach for Slovenian forestry to break free from management standstill. The series of consecutive and connected hazardous events between 2000–2018, and especially since 2012 (salvage cutting in some re- gions reached 70% or more; (Zbirka osnutkov …, s. a), should be considered a wake-up call and a warning that sustainable forest development and management cannot tolerate insufficient management activity or delays in the execution of actions. If natural processes are disregarded for an extended period, forest devel- opment may spiral into a management crisis, with economic consequences potentially amounting to tens of millions of euros. Additionally, because many of the earlier highlighted issues (e.g. stand homogenization, undermined demographic structure, felling increment ratio, long rotation periods) cannot be explained solely by natural disturbances and the knowledge and recom- mendations of forest science, nor can credit for some SFM indicators (e.g. high average growing stock due to low felling) be attributed to successfully planned and executed forest management actions, the forest sector as a whole should engage in a wide-ranging discussion about the appropriateness of the present management strategies. This discussion should also address the suit- ability of the present, highly rigid state forest planning and forest management system (GIS, 2006–2016). The basic idea that all national forests must be regulated by a set of forest management plans, designed exclusively by governmental institutions, originates from the early 1960s, when Slovenia was still part of the Socialist Fed- eral Republic of Yugoslavia (Kovač, 2018). Therefore, a comprehensive discussion is necessary given the pre- dominance of private forests whose owners must have a say about whether the present forest management concept should be continued or modified. These forest owners will also play an important role in the imple- mentation of future forest conservation actions. Close collaboration among forest owners, forest practitioners, forest science and the administration in resolving such issues is also envisioned by the new EU forest strategy (New EU Forest …, 2021). This collaborative effort will be essential in shaping a sustainable and resilient forest management approach for Slovenia’s future. 6 SUMMARY 6 POVZETEK V prispevku smo predstavili stanje in razvoj slo- venskih gozdov, ocenjena s podatki velikoprostorskega Monitoringa gozdov in gozdnih ekosistemov (MGGE), pridobljenimi na sistematični vzorčni mreži 4 x 4 km. Meritve so bile opravljene v letih 2000, 2007, 2012 in 2018, na ca. 760 trajnih vzorčnih ploskvah. Stanje in razvoj slovenskih gozdov z vidika trajnosti smo preverili z naslednjimi kazalci trajnostnega gospo- darjenja z gozdovi (TGG): površina gozdov, temeljnica, lesna zaloga, indeks sestojne gostote (SDI), starostna struktura/porazdelitev prsnih premerov, ravnotežje razvojnih faz, optimalna lesna zaloga, prirastek, sečnja, različnost drevesnih vrst, mešanost sestojev, pomlaje- vanje, naravnost in odmrla drevnina. Obračuni so bili izdelani na ravni države, dveh višinskih pasov (pod/ nad 600 m nmv), sedmih ekoregij ter štirinajstih goz- dnogospodarskih območij (GGO). 22 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? Površina gozdov je od l. 2012 stabilna in znaša ca. 1.214.000 ± 54.663 ha (gozdnatost 60 %). Pod 600 m nmv je bilo 52 % gozdov, nad to mejo pa 48 %. Med ekoregijami so bile z gozdovi najbogatejše Dinarska, Alpska in Predalpska, med GGO pa Tolmin, Ljubljana, Novo mesto in Kočevje. Povprečna temeljnica je med l. 2000 in 2012 nara- sla z 29,4 m 2 /ha (± 1,1 m 2 /ha) na 32,2 m 2 /ha (± 1,1 m 2 /ha), se potem znižala in je l. 2018 znašala 30,7 m 2 / ha (± 1,1 m 2 /ha). V pasu nad 600 m nmv so bile njene povprečne vrednosti za ca. 17 % višje od temeljnic v nižinskem pasu. Razslojevanje temeljnice po razvojnih fazah je neizrazito. Najvišje temeljnice so v Pohorski ekoregiji (40 m 2 /ha), najnižje pa v Submediteranski (24 m 2 /ha). V opazovanem obdobju ima skoraj 50 % gozdov temeljnice nižje od 30 m 2 /ha. V istem času pa je delež površin z visokimi temeljnicami (nad 40 m 2 / ha) narastel. Zarast sestojev smo ocenili z indeksom sestojnih gostot (SDI), ki nam omogoča podroben vpogled v se- stojno strukturo. V opazovanem obdobju je povprečni SDI naraščal od 576 ± 21 v letu 2000, na 619 ± 21 v letu 2012, nato pa se do l. 2018 zmanjšal na 592 ± 21. V l. 2018 sta najvišja povprečna SDI v GGO Slovenj Gradec (744 ± 112) in Kranj (701 ± 99), najnižji pa v Sežana (512 ± 77) in Ljubljana (516 ± 55). Podobno so najviš- ji povprečni SDI v Pohorski (615 ± 48) in Alpski (653 ± 62) ekoregiji, najnižji pa v Submediteranski (494 ± 60) in Preddinarski (552 ± 54). Razporeditev gozdnih površin, razvrščenih po razredih SDI v ekoregijah, je pokazal, da deleži površin s SDI nad 800 ostajajo ve- činoma pod 20 % (izjemi sta bili Pohorska in Alpska ekoregija). Poleg tega je podroben pregled debeljakov pokazal, da ima približno 31 % (pribl. 261.000 ha) SDI nižje od 500 in 24 % višje od 800. Raztros SDI v drogovnjakih in tanjših debeljakih je velik. V precej- šnjem deležu sestojev so bili SDI nižji od normalnih vrednosti. Precej drugačne so bile strukture sestojev v Pohorski in Dinarski ekoregiji. Medtem ko so bili se- stoji v Pohorski ekoregiji polnozarasli, je v sestojih v Dinarski ekoregiji primanjkovalo dreves (predvsem v debeljakih). Lesna zaloga je od l. 2000, ko je znašala 299,3 ± 13,8 m 3 /ha, naraščala. Najvišjo vrednost je dosegla l. 2012, in sicer 333,9 ± 13,7 m 3 /ha, zatem se je l. 2018 znižala na 329,6 ± 13,71 m 3 /ha. L. 2018 so bile najvišje zaloge v GGO Slovenj Gradec (450 ± 60 m 3 /ha), Nazarje (422 ± 83 m 3 /ha), najnižje pa v Sežani (199 ± 35 m 3 /ha) in Ljubljani (275 ± 33 m 3 /ha). Izmed ekoregij je imela najvišjo povprečno zalogo Pohorska (469 ± 54 m 3 /ha), najnižjo pa Submediteranska (199 ± 28 m 3 /h). Razen v Predpanonski in Submediteranski, so bile v vseh pre- ostalih lesne zaloge v zgornjem višinskem pasu višje (največ za ca. 20 %). Med l. 2012 in 2018 se je lesna zaloga zmanjšala v vseh razvojnih fazah. Do l. 2018 so bile prevladujoče oblike sestojev (97 %) skupinsko postopno gospodarjeni in raznodobni gozdovi. Njihovo demografsko stanje med l. 2000 in 2012 je bilo stabilno. Prehode med razvojnimi fazami, ki so postali izrazitejši po l. 2012, je v veliki meri spro- žil niz naravnih dogodkov, kot so žledolom leta 2014, kasnejši napadi podlubnikov ter občasni snego- in ve- trolomi. Čeprav so ti obsežni naravni dogodki vplivali na gozdne strukture, so bile spremembe na nacional- ni ravni nepomembne; majhen delež mlajših sestojev (mladovje in drogovnjaka) je l. 2000 znašal 32 %, l. 2018 pa je padel na 29 %, medtem ko se je delež zrelih sestojev (debeljaki) povečal z 68 % na 70 %. Podobna je bila tudi porazdelitev razvojnih faz v višinskih paso- vih. Premeri dreves so bili pozitivno zamaknjeni v vseh razvojnih fazah in so kazali na njihovo pomembno ne- enakomernost. Kar zadeva razlike v površinskih deležih razvojnih faz med ekoregijami ali GGO, je nabor podatkov za l. 2018 pokazal, da so velike in pomembne. V Dinarski, Pohorski in Predalpski ekoregiji je bilo več kot 70 % zrelih sestojev. Nasprotno pa so precej ugodnejšo, če- prav neuravnoteženo, demografsko podobo izkazovali gozdovi v Submediteranski ekoregiji (ca. 50 % debelja- kov). Podobno je bilo v GGO Kranj, Kočevje, Nazarje in Maribor več kot 75 % zrelih gozdov, v Tolminskem in Sežanskem pa približno 53 %. Neuravnotežena demografija sestojev je bila prika- zana z modelom normalnega gozda za skupinsko po- stopno gospodarjenje. Model je razkril pomanjkanje mladih in presežke zrelih sestojev. Čeprav je ta demo- grafski problem poznan že nekaj časa, se je stanje po l. 2012 poslabšalo. Omeniti velja naslednje ugotovitve: Slovenskim gozdovom je v l. 2018 primanjkovalo 169.152 ha mladih sestojev (110.835 ha mladovij in 58.417 ha drogovnjakov). Hkrati je bil v enaki količini presežek zrelih sestojev. Neuravnotežene razvojne faze in njihove povpreč- ne lesne zaloge so povzročile uravnoteženo lesno za- logo 296 m 3 /ha (skupinsko postopno gospodarjenje) in 297 m 3 /ha v kombinaciji z raznodobnimi sestoji. Za gozdove pod 600 m nadmorske višine je bila izračuna- na vrednost 276 m 3 /ha in 303 m 3 /ha za gozdove nad njo. Uravnotežene vrednosti so bile bistveno nižje od optimalnih lesnih zalog, izpeljanih iz švicarskih in slo- vaških donosnih tablic, ki so bile postavljene na 319 m 3 /ha oziroma 421 m 3 /ha. Nižje so bile tudi od vre- dnosti, izračunanih s simuliranjem adekvatnih vredno- Acta Sil va e et Ligni 131 (2023), 1–27 23 sti gozdov dežele Gradiščanske in Švice, ki so znašale 347 m 3 /ha oz. 322 m 3 /ha. Bruto prirastek z vrastjo in polovičnim prirastkom posekanih dreves je l. 2018 znašal 7,86 ± 0,32 m 3 /ha in se je v primerjavi z l. 2012 (8,60 m 3 /ha) zmanjšal. Bru- to prirastek brez vrasti in polovičnega prirastka po- sekanega drevja je bil med l. 2012 in 2018 ocenjen na 6,85 ± 0,30 m 3 /ha in je nižji od vrednosti med l. 2000 in 2007, ki je znašala 7,92 ± 0,32 m 3 /ha (bruto prirastek z vrastjo in polovičnim prirastkom posekanih dreves je v l. 2018 znašal 7,86 ± 0,32 m 3 /ha, v l. 2012 pa 8,60 ± 0,33 m 3 /ha). Z izjemo Alpske ekoregije se je v vseh drugih ekore- gijah bruto prirastek najprej povečal, nato pa zmanjšal. Podoben trend je mogoče zaslediti v GGO. Precej dru- gačen trend je bil v GGO Bled, kjer se je bruto prirastek stalno zmanjševal, in v Murski Soboti, kjer se je stalno povečeval. V GGO Tolmin je bruto prirastek skozi leta ostal stabilen. Med l. 2012 in 2018 je bil povprečni letni posek brez polovičnega prirastka posekanih dreves ocenjen na 5,94 ± 1,18 m 3 /ha (s polovičnim prirastkom 6,27 ± 1,2 m 3 /ha) in je bil višji kot med l. 2007 in 2012, ko je znašal 4,03 ± 0,80 m 3 /ha. Od l. 2000 je povprečni letni posek naraščal v vseh ekoregijah, razen v Predpanon- ski, kjer se je zmanjšal. V obdobjih 2000–2007, 2007–2012 in 2012–2018 sta se bruto prirastek in letni posek razvijala z različ- nimi trendi. Medtem ko se je bruto prirastek najprej povečal v večini ekoregij in tudi GGO kljub naraščajo- čemu letnemu poseku, se je ta smer po l. 2012 obrnila. To dejstvo je omembe vredno, ker naravni dogodki in povečani posek niso prizadeli vseh ekoregij in GGO. Od l. 2000 do 2012 je povprečni letni posek v ra- zvojnih fazah v veliki meri zaostajal za bruto prirast- kom. Od l. 2000 do 2007 je bilo razmerje med posekom in prirastkom 47 % in je med l. 2007 in 2012 doseglo 52 %. Njegova nizka vrednost se je obrnila po l. 2012, ko je vrsta zaporednih naravnih dogodkov prizadela gozdove in ga potisnila na 88 %. Razen gozdov v Subpanonski ekoregiji (R = 0,29) so naravni dogodki prizadeli vse gozdove. V Dinarski, Submediteranski in Pohorski ekoregiji je razmerje do- seglo 1,05 oziroma 1,12. V drugih ekoregijah se je gi- balo med 0,83–0,97. Od vseh GGO se je posek najbolj povečal v Postojni (za faktor 2,20), Ljubljani (1,50), Nazarjah (1,29) in Kranju (1,07). L. 2018 sta bili v gozdovih najpogostejši drevesni vrsti bukev (33,4 %) in smreka (28,6 %), ki so jima z bistveno nižjimi volumenskimi deleži sledile druge vr- ste. Deleža smreke in jelke sta se med l. 2000 in 2018 znižala. V zadnjem obdobju je izrazito narasel delež bukve. Na splošno se je v zadnjih 18 letih drevesna se- stava slovenskih gozdov počasi spreminjala. Medtem ko je delež bukve močno narasel šele v zadnjem času, je delež smreke začel upadati že med l. 2000 in 2007 ter ponovno po l. 2012. Manj jasno dinamiko spremi- njanja je zaznati pri jelki. Pri vseh drugih vrstah so bile spremembe majhne. Podrobna analiza podatkov je pokazala, da se deleži jelke, rdečega bora, macesna, gorskega javorja in velikega jesena kljub njihovemu ekološkemu, gospodarskemu in okoljskemu pomenu niso močno povečali. Spremenila se je tudi mešanost sestojev. Več informacij nam da porazdelitev drevesnih vrst po debelinskih stopnjah l. 2018, kjer je bila uravnote- žena le porazdelitev osebkov bukve, medtem ko jelka, gorski javor, hrast in rdeči bor nimajo zadostnega šte- vila mladik (vrasti) in dreves s premerom pod 30 cm. Nasprotno pa pri belem gabru in velikem jesenu pri- manjkuje dreves večjih premerov. Neuravnotežena po- razdelitev je tudi pri smreki, do te spremembe je prišlo zaradi naravnih dogodkov in morebitnega namenske- ga zmanjšanja deleža smreke. Še lepše se to vidi na porazdelitvi deležev bukve, jelke in smreke po debelinskih razredih v ekoregijah. Medtem ko je bil delež bukve v vseh ekoregijah višji od 20 %, se je v Submediteranski ekoregiji delež jelke zmanjšal in je ostal uravnotežen le v Pohorski ekore- giji. Največji upad je bil zabeležen v Dinarski ekoregiji, kjer je jelka obdržala svoj delež (v lesni zalogi) zaradi še vedno velikega števila debelih dreves. Kljub temu pa je od vseh jelk le 5 % takšnih, ki jih je mogoče šteti za vrasle. Tudi delež smreke v debelinskih razredih je bil zelo različen. V nasprotju s prej omenjenimi vrstami ta variabilnost ni zaskrbljujoča, saj smreka v Sloveniji ve- činoma raste na sekundarnih rastiščih. Večina sestojev je polnaravnega nastanka. Obnova gozdov je pretežno naravna in zaostaja za potrebnimi demografskimi deleži. Če upoštevamo, da je povprečni delež površin v obnovi v obdobju 2000–2018 znašal 45.300 ha (3,85 %) in da potrebujejo sadike najmanj 20 let, da prerastejo prvo razvojno fazo, bi bilo potreb- nih več kot 500 let, da bi obnovili vse gozdove v državi. V l. 2018 je količina odmrle drevnine znašala 24,2 ± 2,39 m 3 /ha. Znatno se je povečala po l. 2012, ko je bila ocenjena na 19,83 ± 1,93 m 3 /ha. Tudi količina od- mrlega lesa v l. 2018 se je med ekoregijami pomemb- no razlikovala. Največje količine so bile ugotovljene v Alpski in Dinarski ekoregiji (> 30 m 3 /ha), najmanjše pa v Predpanonski in Submediteranski (> 18,5 m 3 /ha). Povečane vrednosti so kazale na intenzivnost narav- nih motenj in so bile največje v Dinarski (7,9 m 3 /ha), Alpski (5,7 m 3 /ha) in Pohorski ekoregiji (4,7 m 3 /ha). 24 K ušar G., K o va č M.: Ar e Sl o v enia ’ s f or ests de v ia t ing f r om sustainabl e de v el opment? Glede na poročilo o stanju gozdov 2020 (Forest Eu- rope, 2020) sodi Slovenija v skupino držav z največjo povprečno količino odmrle drevnine v svojih gozdovih. Razen kazalcev površine gozdov in odmrle drevnine so bila stanja drugih kazalnikov z vidika trajnostnega razvoja ocenjena kot neugodna. Najbolj kritična sta bila neuravnotežena zgradba razvojnih faz (demografska podoba) sestojev in drevesna (vrstna) sestava. Oboje vpliva tudi na biotsko raznovrstnost gozdov, predvsem na stanje ohranjenosti gozdnih habitatnih tipov. Dolgo- ročno neugodno je bilo tudi razmerje posek/prirastek. Čeprav je premajhna sečnja pomagala povečati lesne zaloge, je prispevala tudi k zastaranju gozdov. Neugodno sta bila ocenjena tudi znaka drevesna (vrstna) sestave in obnova. Previsoki so bili deleži smreke, upadajo pa deleži rdečega bora in jelke (Dinar- ska, Preddinarska ekoregija). Nasprotno pa je podatek za bukev jasno pokazal, da je ta vrsta ponovno zavzela svojo površino, jelka pa jo izgubila. Razlike faktorjev velikosti med ocenjenimi in že- lenimi vrednostmi indikatorjev so se gibale med 0,33 (pomladitvene površine) in 1,2 (odmrla drevnina), v primeru drevesnih vrst pa med 0,08 (hrast) in 0,8 (bu- kev). Stanje postane zelo nespodbudno takoj, ko se iz- razi v času, ki je potreben, da se gozdovi vrnejo ali pri- bližajo normalnemu stanju. Glede na sedanjo dinamiko sprememb bo potrebnih več desetletij za približanje zaželenim vrednostim kazalnikov. Na podlagi dejstev in predpostavk lahko sedanjo usmeritev razvoja naci- onalnih gozdov štejemo za odmik od trajnostnega ra- zvoja gozdov. Ocenili smo tudi ustreznosti sistematične mreže 4 x 4 km, ki se je uporabljala do l. 2018, in ugotovili, da periodičnost v populaciji ni bila zaznana. Od 34 kompleksnih kazalnikov SFM (Forest Euro- pe, 2022) naj bi jih ca. –5 - 19 pridobivali z nacionalno inventuro. Ob upoštevanju številnih možnih kombina- cij (ki jih ustvarjajo stratifikacijske spremenljivke, kot so druga gozdnata zemljišča, gozdovi, ki so na voljo za oskrbo z lesom), se število podrejenih kazalnikov moč- no poveča. Glede na razpoložljive podatke v letu 2018 ugotavljamo, da je zbirka podatkov MGGE omogočila izpeljavo nepopolnih ocen osmih kazalnikov SFM. Prav tako ni omogočila izpeljave ločenih ocen za različne postopke poročanja, ki se razlikujejo glede na mejne vrednosti območij in v nekaterih drugih definicijah ka- zalnikov. ACKNOWLEDGEMENTS ZAHVALA This study was prepared within the framework of the JGS 4 assignment “Development and execution of the national forest inventory”, financed by Ministry for Agriculture, Forestry and Food, and the “Forest biology, ecology, and technology” (P4-0107) Program group, financially supported by the Slovenian Research and Innovation Agency. We are grateful to Andrej Grah, who prepared the temporal data series for processing. We also extend our thanks to two anonymous review- ers who provided valuable feedback, greatly improv- ing this paper. Many thanks also to Philip Jan Nagel for proofreading and improving the readability of the paper. 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