COMPARATION STUDY OF SOIL GENETIC DIVERSITY OF BACTERIA AND FUNGI IN DIFFERENT VEGETATION SUCCESSIONS IN A KARST OF GUIZHOU PROVINCE, CHINA PRIMERJALNA ŠTUDIJA GENETSKE RAZNOVRSTNOSTI TALNIH BAKTERIJ IN GLIV V RAZLIČNIH SUKCESIJAH VEGETACIJE NA KRASU V PROVINCI GUIZHOU, KITAJSKA Yidong MI 1,2 , Hongda FANG 3 , Peng TAO 4 , Min ZHOU 1,5 , Xinru LI 1 , Fanfan W ANG 1 , Haiyan CHEN 1 , Hailei SU 1 , Yuanrong ZHU 1 , Yuan WEI 1* & Lin XI 6* Abstract UDC 582.231:551.435.8(513) 582.28:551.435.8(513) Yidong Mi, Hongda Fang, Peng T ao, Min Zhou, Xinru Li, Fan- fan Wang, Haiyan Chen, Hailei Su, Yuanrong Zhu, Yuan Wei & Lin Xi: Comparation study of soil genetic diversity of bacte- ria and fungi in different vegetation successions in a karst of Guizhou province, China To study the soil genetic diversity of bacteria and fungi in dif- ferent vegetation successions (grassland, shrubbery, primary forest and secondary forest) from the karst area, the Poly- merase Chain Reaction-Denaturing Gradient Gel Electro- phoresis (PCR-DGGE) technology was applied. The results showed that: (1) the diversity of bacterial communities and the fungal communities in karst area were higher than non karst area in each vegetation succession. Compared with the survey from bacterial (the Shannon index was 2.97 in primary forest, 2.91 in secondary forest, 3.18 in shrubbery, 3.14 in grassland and 2.68 in non karst), fungal diversity between karst areas (the Shannon index was 3.56 in primary forest, 3.78 in second- ary forest, 3.73 in shrubbery and 3.70 in grassland) and non karst areas (the Shannon index was 3.08) was more evident, which may be related to the alterations of the composition of plant community and the source of carbon in soil with the vegetation succession of karst ecosystem; (2) The comparation of bacterial diversity index and the richness comprehensively Izvleček UDK 582.231:551.435.8(513) 582.28:551.435.8(513) Yidong Mi, Hongda Fang, Peng T ao, Min Zhou, Xinru Li, Fan- fan Wang, Haiyan Chen, Hailei Su, Yuanrong Zhu, Yuan Wei & Lin Xi: Primerjalna študija genetske raznovrstnosti talnih bakterij in gliv v različnih sukcesijah vegetacije na krasu v provinci Guizhou, Kitajska Za proučevanje genetske pestrosti talnih bakterij in gliv v različnih sukcesijah vegetacije (travišče, grmičevje, primarni gozd in sekundarni gozd) na krasu je bila uporabljena tehno- logija verižne reakcije s polimerazo-denaturirajoča gradientna gelska elektroforeza (PCR-DGGE). Rezultati raziskave so po- kazali, da: (1) je bila v vsaki sukcesiji vegetacije pestrost bak- terijskih in glivnih združb na kraškem območju višja kot na nekraškem. V primerjavi z bakterijsko raznovrstnostjo (Shan- nonov indeks je bil 2,97 v primarnem gozdu, 2,91 v sekundar- nem gozdu, 3,18 v tleh grmičevja, 3,14 v tleh travišč in 2,68 v nekraškem območju) je bila raznovrstnost gliv med kraškimi območji (Shannonov indeks je bil v primarnem gozdu 3,56, 3,78 v sekundarnem gozdu, 3,73 v tleh grmičevja in 3,70 v tleh travišč) in nekraškimi (Shannonov indeks je bil 3,08) jasneje izražena. To je lahko povezano s spremembami v sestavi rast- linske združbe in vira ogljika v tleh glede na stanje sukcesije v vegetaciji kraškega ekosistema. (2) Primerjava kazalnikov bakterijske raznovrstnosti in abundance je bila celostno ovred- 1 State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, P .R. China, e-mails: m18363974562@163.com, 15712975290@163.com, 18813145607@163.com, wwffaannaza@126.com, chenhy@craes.org.cn, suhailei666@163.com, zhuyuanrong07@mails.ucas.ac.cn, rbq-wy@163.com 2 School of Resources Environment and Chemical Engineering, Nanchang University, Nanchang 330031, P .R. China, e-mail: m18363974562@163.com 3 School of Port and Environmental Engineering, Jimei University, Xiamen 361021, P .R. China, e-mail: hdfang@jmu.edu.cn 4 State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, P .R. China, e-mail: pengtao@mails.gyig.ac.cn 5 College of Environment, Hohai university, Nanjing 210098, P .R. China, 15712905290@163.com 6 Department of Plant Systems Biology, University of Hohenheim, 70599 Stuttgart, Germany, e-mail: lin.xi.260@uni-hohenheim.de * Corresponding Author Received/Prejeto: 20. 11. 2019 DOI: https://doi.org/10.3986/ac.v50i2-3.7684 COBISS: 1.01 ACTA CARSOLOGICA 50/2-3, 329-342, POSTOJNA 2021 YIDONG MI, HONGDA FANG, PENG TAO, MIN ZHOU, XINRU LI, FANFAN W ANG, HAIYAN CHEN, HAILEI SU, YUANRONG ZHU, YUAN WEI & LIN XI INTRODUCTION Karst area in Southwest China is one of the most typical tropical-subtropical karst regions in the world (Y an et al., 2020). Karst topography is a result of geological action of soil erosion, which is dominated by chemical dissolution and supplemented by the mechanical actions of erosion or collapse (Zhou et al., 2020). This reflects in soil alka- linity, surface drought and nutrient deficiency (Wang et al., 2004; Zhang et al., 2015). One of the most harmful consequences of ecosystem degradation in karst regions is rocky desertification—development of a desert-like landscape with large-scale exposure of bedrock due to severe human disturbances (Liu et al., 2018). Southwest China is known as the ecological barrier of the Yangtze River because of its abundant ecological diversity, com- plex natural environment and ecological structure (Wu et al., 2018). Rocky desertification has tremendously threated the ecological security of this region, restricted sustainable economic development and consequently af- fected the whole Y angtze river ecological balance. There- fore, to study the ecological restoration of rocky deserti- fication is necessary for sustainable development and human survival (Hui et al., 2019). Although the rocky desertification process is partly due to its natural foundations (lithology, climate, etc.) and is influenced by different human social conditions (population, economy, etc.) (Ma et al., 2020), soil micro- organisms play a key role in this process (Wei et al., 2011; Jiang et al., 2014). Microorganisms are widely distributed in soil, and play an important role in the transformation and circulation of organic matter, nitrogen, phospho- rus, sulfur and other plant nutrients (Blagodatskaya & Kuzyakov, 2013; Chen et al., 2019). Soil microorganisms are crucial promoters of soil evolution, property change, soil fertility and biomass production, it has a profound influence on the disstribution and succession process of vegetation in different stages in karst areas. Soil mi- croorganisms are sensitive to environmental change, which can indicate the change of ecosystem (Kumar et al., 2015). Therefore, the study of microbial diversity in karst areas is conducive to in-depth karst formation fac- tors and provides supporting materials for karst ecologi- cal restoration. Meanwhile, microorganisms mainly feed on plant and animal secretion and organic matter, and the composition of plant species community in turn can significantly affect the community structure of soil mi- croorganisms (Carney & Matson, 2005; Fan et al., 2019). Zhao et al. (2014) have studied the soil microorganisms along a progressive succession of secondary vegetation in a karst area and found that microbial biomass and ratio of fungal to bacterial biomass decreased with the second- ary succession in the plant community. Li et al. (2013) found that vegetation changes from trees to shrubs and shrubs to grass might affect soil organic carbon contents particularly for organic carbon fractions, and alter soil microbial biomass, community structures and enzyme activities. Previous studies have provided that in karst area, different vegetation types give rise to the distinction on microbial community structure in soil in the aspect of the biomass (He et al., 2008; Zhu et al., 2012; Pan et al., 2018). However, there is a lack of discussion on genetic diversity of soil microorganisms. Thus characterization of soil microorganisms from different vegetation succes- sion types is needed. In this study, the soil bacterial and fungal genetic diversity of different vegetation successions in karst re- gion was studied using PCR and denaturing gradient gel electrophoresis (DGGE). The variation of soil microbial community structure in different vegetation succession stages was discussed. These results could definite the in- fluence of ecological succession on soil microbial com- munity structure and provided important scientific basis for the mechanism of rocky desertification of karst eco- system, protection and management. evaluated as follows: shrubbery > grassland > primary forest > secondary forest. The diversity index and the richness of fungal communities was as follows: secondary forest > shrubbery > grassland > primary forest. The results suggest that the fungal communities have been greatly changed via vegetation succes- sions, but the diversity index and the richness of the bacterial communities have not been seriously affected. The results pro - vide scientific basis for understanding karst surface ecosystem, which contributes to the future aim of protecting the karst from desertification. Keywords: karst; vegetation succession; bacteria; fungi; genetic diversity. notena in sledi takole: grmičevje > travišče > primarni gozd > sekundarni gozd. Kazalnika raznovrstnosti in abundance gliv- nih združb kažeta sledeči trend: sekundarni gozd > grmičevje > travišče > primarni gozd. Rezultati izkazujejo, da so se glivne združbe precej spremenile zaradi sukcesije v vegetaciji, vendar pa na drugi strani ni bilo bistvenega vpliva na kazalnika bakte- rijske raznovrstnosti in abundance. Rezultati med drugim daje- jo tudi znanstveno podlago za razumevanje delovanja kraškega površinskega ekosistema, kar ključno prispeva k cilju zaščite krasa pred dezertifikacijo (širjenjem puščav). Ključne besede: kras, sukcesija vegetacije, bakterije, glive, ge- netska pestrost. ACTA CARSOLOGICA 50/2-3 – 2021 330 COMPARATION STUDY OF SOIL GENETIC DIVERSITY OF BACTERIA AND FUNGI IN DIFFERENT VEGETATION SUCCESSIONS IN A KARST OF GUIZHOU PROVINCE, CHINA GEOLOGICAL AND GEOGRAPHICAL SETTING Maolan national nature reserve is located in Libo, Guizhou province, with an average altitude of 758.8 m. This region has a typical subtropical monsoon humid cli- mate, and the karst landform is very developed in this area (Wei et al., 2012). The mean annual air temperature at Maolan is about 17 o C. Long-term mean annual pre- cipitation of this region is around 1752 mm, about 81% of which falls in the monsoon season from April to Sep- tember (Liu et al., 2015a). There are vegetation succes- sion communities with different degrees of degradation in this area, and the vegetation communities are relative- ly complete under each degree of degradation, which are conducive to the comparative study of different vegeta- tion types in the same area. The study was conducted at Laqiao W atershed, Y aogu Village, Yongkang Township (25°18 ′00 ″–25°18 ′50 ″N, 107°56 ′10 ″–107°58 ′10″E), Maolan National Natural Pre- serve, Guizhou province in southwest China (Figure 1) in August. According to the main characteristic of karst vegetation succession, four representative types of vegeta- tion succession (grassland, shrubbery, primary forest and secondary forest) were selected. Grassland was dominated by herbaceous plants, the height of herbaceous layer was between 0.5-1 m, and the coverage rate was above 90%, the dominant species were Heteropogon contortus, Pteridium revolutum, Dicranopteris linearis, Miscanthus floridulus, etc. Shrubbery was mainly shrub layers with a height of 2.5-3 m and a coverage rate of more than 80%, with a few trees, the vertical structure of the stand was simple, the dominant species were Nandina domestica, Lindera com- munis, Damnacanthus indicus, Clausena dunniana, Cy- clobalanopsis multinervis, Rosa cymosa, etc. Primary for- est was dominated by the arbor layer, which was 10-20 m high, the arbor layer covered more than 80%, and the hi- erarchical structure was relatively complete, the dominant species were Pittosporum brevicalyx, Machilus microcarpa, Pteroceltis tatarinowii, Pittosporum glabratum, Euonymus dielsianus, Castanopsis fargesii, Mahonia fortunei, Ficus Figure 1: Descriptive map of the study area and the samples plots. ACTA CARSOLOGICA 50/2-3 – 2021 331 YIDONG MI, HONGDA FANG, PENG TAO, MIN ZHOU, XINRU LI, FANFAN W ANG, HAIYAN CHEN, HAILEI SU, YUANRONG ZHU, YUAN WEI & LIN XI erecta, etc. Secondary forest has developed arbor layer and shrub layer, with obvious differentiation of stand hierar- chy structure, 5-12 m high, and tree layer coverage rate of more than 80%, the dominant species were Carpinus pu- bescens, Cyclobalanopsis glauca, Castanopsis fargesii, Pinus massoniana, Pittosporum crispulum, Lindera communis, etc. Vegetation characteristics of different vegetation suc- cessions are shown in Table 1. Slope inclination measured with a forest compass, rock exposure rate and vegeta- tion coverage were estimated by naked eye. Three typical sample plots of each vegetation succession were selected according to the principle of random distributed with lo- cal control (including density, slope direction and slope position), and the size of each sample plot was 20–30 m. In addition, three sample plots in a non karst vegetation succession of size 20–30 m in Libo country (107°53 ′26 ″E, 25°28 ′46 ″N) was chosen. The sample plots were divided into the types of de- fined microhabitats (soil surface, stone ditch, stone seam and stone surface), the litters covering layer was removed, the weighted sampling method was adopted to collect the topsoil at 3-5 points (0-15 cm), and then the soil was screened at 2 mm to ensure sufficient mixing, and the samples were preserved at -20 o C (Wang et al., 2007). The soil here is rich in Ca 2+ , Mg 2+ , and HCO 3 - , with a pH of 7.5 to 8.0, an organic matter content of 75.5 to 380 g/kg, and a total nitrogen content of 6.06 g/kg (Zhou, 1987; Wang et al., 2007). METHODS DNA EXTRACTION AND PCR AMPLIFICATION OF 16S rDNA GENES Total DNA was extracted from 0.5 g sample using Power Soil TM DNA isolation kit (MO BIO laboratories, USA). DNA was finally preserved at -80 o C for later use. The extracted DNA was used as templates for PCR. The amplification of bacterial DNA was performed using the universal 16S rDNA primers F338-GC (5’-CGCCC- GCCGCGCGCGGCGGGCGGGGCGGGGGCAC- GGGGGGCCTACGGAGGCAGCAG-3’) and R518 (5’-ATTACCGCGGCTGCTGG-3’). PCR was performed in a total volume of 25 μL, containing 1 μL template solu- tion, 12.5 μL Master mix (Promega, M712B), 10 pmol of each primer (1 μL), 9.5 μL ddH 2 O. The PCR cycling pa- rameters were 5 min at 94°C (the annealing temperature of each cycle decreased by 0.5 °C), and the last 100 cycles of 1 min at 94°C, 1 min at 65-55°C, and 3 min at 72°C, with a final extension phase of 7 min at 72°C (Muyzer et al., 1993). The amplification of fungal DNA was per - formed using the universal 18S rDNA primers U1 (5’-GACTCCTTGGTCCGTGTT-3’) and U2-GC (5’-CGCCCGCCGCGCGCGGCGGGCGGGGC- GGGGGCACGGGGGG-3’). PCR was performed in a total volume of 25 μL, containing 1 μL template solution, 12.5 μL Master mix (Promega, M712B), 1 μL of each primer, 9.5 μL ddH 2 O. The PCR cycling parameters were 3 min at 94°C, followed by 35 cycles of 0.5 min at 94°C, 0.5 min at 53°C, and 1 min at 72°C, with a final extension phase of 10 min at 72°C. DENATURING GRADIENT GEL ELECTROPHORESIS (DGGE) ANALYSIS The type 475 gradient irrigation system (Bio-Rad) was used to conduct the DGGE analysis. The PCR product of bacterial sample was analyzed on 8% polyacrylamide gels containing gradients of 30% to 60% denaturants. Elec- trophoresis was run at a constant voltage of 75 V for 10 h at 60°C in 1×TAE running buffer. The gels were then stained with silver nitrate and scanned with an laser im- age analyzer (Bassam et al., 1991). Table 1: The vegetation characteristic of different vegetation succession. Vegetation succession Slope inclination Rock exposure rate Vegetation coverage Vegetation characteristic Primary forest 30-40° 60-90% 90-100% The hierarchical structure is complete, and the differentiation between layers is distinct, mainly arbor layer, the dominant species are arbor. Secondary forest 30-40° 50-80% 90-100% The hierarchical structure is obviously, and the arbor layer and shrub layer are relatively developed. Shrubbery 20-30° 70-80% 80-100% The hierarchical structure is simple, the dominant species are shrub. Grassland 30-40° 50-70% 90-100% The dominant species are herbage. Non karst 30-40° 0 90-100% The dominant species are arbor. ACTA CARSOLOGICA 50/2-3 – 2021 332 COMPARATION STUDY OF SOIL GENETIC DIVERSITY OF BACTERIA AND FUNGI IN DIFFERENT VEGETATION SUCCESSIONS IN A KARST OF GUIZHOU PROVINCE, CHINA The PCR product of fungal sample was analyzed on 8% polyacrylamide gels containing gradients of 30% to 70% denaturants. Electrophoresis was run at a constant voltage of 100 V for 10 h at 60°C in 1× TAE running buffer. The gels were then stained with silver nitrate and scanned with a laser image analyzer. DATA ANALYSIS DGGE profiles from different samples were analyzed using Bio-Rad Quantity One 4.4.0 software (BIO-RAD, Hercules, CA, USA). Comparisons of banding profiles were performed by calculating the DICE correlation co- efficient (Cs) using the unweighted pair group method with arithmetic mean (UPGMA) algorithm (Equation 1). [1] j, indicates bands in common; a, indicates bands in sam- ple A; b, indicates band in sample B. Richness (S) is the total bands number of each sam- ple. Shannon’s index (H) and evenness (Eh) were used to characterize microbial diversity, using the equations 2 & 3: [2] [3] H, Shannon ’ s index; S, total bands number of each sample; Pi, relative abundance of i th band of each sample (Luo et al., 2004). Data statistics was performed using Excel and SPSS v.17.1 software (SPSS Inc., Chicago, IL,USA). RESULTS GENETIC DIVERSITY OF SOIL BACTERIA UNDER DIFFERENT VEGETATION SUCCESSIONS DGGE spectrum analysis Bacterial communities associated with different soil samples were analysed by the DGGE profile (Figure 2). DGGE analysis revealed that each sample contained several number of bands, each band represents differ- ent DNA sequence (Wei et al., 2012). It was obvious that some of the bands (bands no. 20, 24, 30 and 34) were detected across all samples, which suggested certain bac- terial taxa were present in different karst areas and non Figure 2: DGGE profile of amplified bacterial communities in different vegetation succession samples. (A) DGGE page; (B) Comparison of bands pattern (Horizontal numbers: 1-3 secondary forest; 4-6 shrub; 7-9 primary forest; 10-12 grassland; 13 non karst; Vertical numbers: 20, 24, 30 and 34 mark the positions of different bands.). ACTA CARSOLOGICA 50/2-3 – 2021 333 YIDONG MI, HONGDA FANG, PENG TAO, MIN ZHOU, XINRU LI, FANFAN W ANG, HAIYAN CHEN, HAILEI SU, YUANRONG ZHU, YUAN WEI & LIN XI karst area. Despite this, it showed much more specific electrophoretic bands in karst samples (sample 1-12) compared with non karst sample (sample 13). It indi- cated that soil bacterial species were more abundant and diverse in karst vegetation successions. From the DGGE profile, the shrub (sample 4, 5 and 6) and the grassland (sample 10, 11 and 12) exhibited the most abundant bands, an average of 25 bands out of 39 compared with others. Except the sample 13 (18 bands out of 39) from the non karst had the lowest quantity of bands, the sec- ondary forest sample 1 and the primary forest sample 7 had relatively less bands, which were 21 bands out of 39 and 20 bands out of 39, respectively. It could be possible that soil bacterial communities from the shrub and the grassland exhibited the highest diversity compared with other karst samples. At the same time, there are some common bands among the samples. For example band no. 20, 24, 30 and 34 were commonly shared. In spite of that, the strong bands were commonly shared across the lanes suggested that the differences of dominant soil bacterial community among these karst vegetation suc- cessions were indistinctive (Yu et al., 2012). In general, the bacterial diversity in karst areas was obviously much higher than that in non karst area. There were some dis- tinction in soil bacterial communities among karst veg- etation successions, but the dominant population was relatively stable. Cluster analysis Based on the similarity of bacterial communities in dif- ferent vegetation succession samples, cluster analysis was shown by a dendrogram (Figure 3), along with the simi- larity index between samples (Table 2). The dendrogram gave rise to two main branches of clusters and shared a similarity of 0.47. One branch of cluster contains the sec- Table 2: The similarity index (Cs) between different vegetation succession samples lanes of microbial communities (%). (1-3 secondary for- est; 4-6 shrub; 7-9 primary forest; 10-12 grassland; 13 non karst). Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 1 100.0 78.0 68.5 49.5 40.0 44.0 60.5 61.2 57.5 62.9 46.2 46.0 59.5 2 78.0 100.0 68.3 46.8 41.9 45.0 56.6 56.0 55.9 53.9 54.6 55.8 52.4 3 68.5 68.3 100.0 64.5 52.0 54.6 61.0 63.1 59.9 57.7 48.7 51.0 57.8 4 49.5 46.8 64.5 100.0 61.1 69.8 65.4 55.4 49.5 53.1 49.5 51.5 52.7 5 40.9 41.9 52.0 61.1 100.0 72.9 67.8 57.3 51.9 42.8 40.8 44.7 47.7 6 44.0 45.0 54.6 69.8 72.9 100.0 66.4 54.9 56.7 49.4 44.6 47.5 47.6 7 60.5 56.6 61.0 65.4 67.8 66.4 100.0 69.8 71.4 58.9 53.7 55.3 47.2 8 61.2 56.0 63.1 55.4 57.3 54.9 69.8 100.0 74.2 69.0 54.4 58.5 43.5 9 57.5 55.9 59.9 49.5 51.9 56.7 71.4 74.2 100.0 59.5 52.2 52.1 39.0 10 62.9 53.9 57.7 53.1 42.8 49.4 58.9 69.0 59.5 100.0 71.6 66.2 40.3 11 46.2 54.6 48.7 49.5 40.8 44.6 53.7 54.4 52.2 71.6 100.0 64.5 30.1 12 46.0 55.8 51.0 51.5 44.7 47.5 55.3 58.5 52.1 66.2 64.5 100.0 26.3 13 59.5 52.4 57.8 52.7 47.7 47.6 47.2 43.5 39.0 40.3 30.1 26.3 100.0 Figure 3: Cluster analysis of microbial communities between dif- ferent vegetation succession samples. Numbers above the branches represent the Cs index. (1-3 secondary forest; 4-6 shrub; 7-9 pri- mary forest; 10-12 grassland; 13 non karst). ondary forest and non karst, with the similarity of 0.57. The other cluster covered the primary forest, shrub and the grassland. The bacterial communities between pri- mary forest and shrub stayed closer with a similarity of 0.60. The bacterial community of the grassland shared ACTA CARSOLOGICA 50/2-3 – 2021 334 COMPARATION STUDY OF SOIL GENETIC DIVERSITY OF BACTERIA AND FUNGI IN DIFFERENT VEGETATION SUCCESSIONS IN A KARST OF GUIZHOU PROVINCE, CHINA the similarly with the others of 0.52. From the similarity index, non karst 13 had high correlation with secondary forest 1 (59.5%), 2 (52.6%) and 3 (57.8%) and the low- est correlation with grassland samples 11 (30.1%) and 12 (26.3%). Therefore it is possible that bacterial commu- nity distinguish significantly at different vegetation suc- cessions. Diversity and Richness analysis We calculated the diversity index of soil bacterial com- munities in different vegetation succession samples, us- ing Shannon index, richness and evenness (Table 3). Ac- cording to Table 3, the Shannon index and richness of shrub were the highest among all karst areas, which were 3.18 and 25, respectively. The second highest index val- ues were from the grassland, which were 3.14 and 24 re- spectively. The primary forest and secondary forest were 2.97 and 21, 2.91 and 22, respectively, and significantly lower than that of other karst areas. The Shannon index and richness of non karst plot were only 2.68 and 18, which were the lowest, and the mean difference in bacte- rial Shannon index between karst areas (3.05) and non karst area (2.68) was 0.37 (Figure 4). In terms of evenness index, non karst plot exhibited the lowest value, only 0.93 while the shrub and the grassland gave the highest value of 0.99, secondary forest had a value of 0.95 and primary forest had a value of 0.98. Thus it suggested that when the vegetation succession getting changed from grassland to secondary forest, the diversity of soil bacterial communi- ties increased firstly and then decreased. Shrub seemed to own the highest bacterial diversity. GENETIC DIVERSITY OF SOIL FUNGAL UNDER DIFFERENT VEGETATION SUCCESSIONS DGGE spectrum analysis Similar as bacterial study, fungal communities in dif- ferent vegetation succession samples were compared by DGGE (Figure 5). There were both the conserved and specific bands from samples 1 to 12, which indicated that there were both common and specific fungal pop- ulations in the soil at different vegetation successions Table 3: Shannon index, richness and evenness of bacterial communities in different vegetation succession stage samples. Vegetation succession Shannon index (H) Richness (S) Evenness (E H ) Primary forest 2.97±0.04 a 21 0.98±0.00 Secondary forest 2.91±0.16 b 22 0.95±0.03 Shrub 3.18±0.04 c 25 0.99±0.00 Grassland 3.14±0.08 c 24 0.99±0.00 Non karst 2.68±0.00 d 18 0.93±0.00 Note: Data are the means ± SD (Different letters “a, b, c, ” in the same column indicate significant differences at P < 0.05 with Tukey test for multiple comparisons.). Figure 4: Shannon index from bac- terial community between karst and non-karst area. ACTA CARSOLOGICA 50/2-3 – 2021 335 YIDONG MI, HONGDA FANG, PENG TAO, MIN ZHOU, XINRU LI, FANFAN W ANG, HAIYAN CHEN, HAILEI SU, YUANRONG ZHU, YUAN WEI & LIN XI in karst soil. Samples 2 and 3 from the secondary for- est showed the most abundant bands, which suggested that secondary forest had the highest fungal diversity. Samples 13, 14 and 15 from the non karst shared the minimum amount of bands compared with samples 1-12, which indicated that the diversity of fungi in non karst areas was lower than that in karst areas. It was worth to note that the specific bands from the soil fun- gal community of each succession varied greatly among different samples. For example in shrub samples 4, 5 and 6, a specific band no. 12 were not present while in the secondary forest (sample 1, 2 and 3) both bands no. 12 and 13 could be seen. This kind of variation was more extravagant than that from the bacterial survey, which was possibly due to more bands detected in fungi DGGE page (96 bands detected in total). In general, the results indicated that the structure of fungal communi- ty has distinguished components within the vegetation succession process. CLUSTER ANALYSIS We performed the similarity clustering. As shown in Fig- ure 6, the fungal communities from the shrub (sample 4-6) and primary forest (sample 7-9) were classified within the same branch of cluster, with a similarity of 0.35. The fungal communities of sample 2 and 3 from the secondary forest were grouped with sample 12 from the grassland, and they stayed close with the above cluster on Figure 5: DGGE profile of amplified fungal communities in different vegetation succession samples. (A) DGGE page; (B) Comparison of bands pattern (Horizontal numbers: 1-3 secondary forest; 4-6 shrub; 7-9 primary forest; 10-12 grassland; 13-15 non karst; Vertical num- bers: 12 and 13 mark the positions of different bands.). Figure 6: Similarity of fungal communities between different veg- etation succession samples. Numbers above the branches represent the index. (1-3 secondary forest; 4-6 shrub; 7-9 primary forest; 10- 12 grassland; 13-15 non karst). ACTA CARSOLOGICA 50/2-3 – 2021 336 COMPARATION STUDY OF SOIL GENETIC DIVERSITY OF BACTERIA AND FUNGI IN DIFFERENT VEGETATION SUCCESSIONS IN A KARST OF GUIZHOU PROVINCE, CHINA a separate branch. Besides, sample 10 and 11 from grass- land, they stayed closer (a similarity of 0.42) and they to- gether shared a similarity of 0.32 with the non karst sam- ple 13. It was obviously that the similarity was diffused along with the succession process. From the similarity Cs index (Table 4), overall within same vegetation succes- sion, samples had higher index correlation. For example, the sample 7, 8 and 9 were from the same cluster branch and the Cs index between them were 82.1%, 83.1% and 86.1%. But compared the sample 7 with others than 8 and 9, it showed values of index correlation ranging from 20.9% (v.s sample 13) to 42.4% (v.s sample 6). This pat- tern can be found in other samples as well. Therefore the fungal communities along with different vegetation suc- cessions had significant distinction. Diversity and Richness analysis Soil fungal communities Shannon index, richness and evenness in different vegetation succession samples were shown in Table 5. It can be seen that the lowest Shannon index and richness index of soil fungi in karst vegetation succession were the primary forest (3.56 and 35). In addi- tion to the primary forest, the difference of fungal Shan- non index and richness in karst vegetation succession was Table 4: The similarity index () between different vegetation succession samples of fungal communities (%). (1-3 secondary forest; 4-6 shrub; 7-9 primary forest; 10-12 grassland; 13-15 non karst). Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 100.0 31.0 29.9 41.2 37.1 40.8 39.0 34.6 37.8 27.9 33.0 24.7 24.9 13.4 28.4 2 31.0 100.0 53.9 38.1 36.2 29.9 33.7 32.4 33.2 27.3 36.8 32.9 25.8 28.5 24.8 3 29.9 53.9 100.0 41.9 40.1 29.9 21.3 23.1 22.5 33.3 28.5 29.6 19.6 21.2 26.9 4 41.2 38.1 41.9 100.0 69.9 53.2 29.2 28.2 25.4 30.3 39.3 37.7 22.6 29.1 26.1 5 37.1 36.2 40.1 69.9 100.0 73.4 33.2 33.0 34.2 28.8 39.3 33.9 18.1 25.3 30.0 6 40.8 29.9 29.9 53.2 73.4 100.0 42.4 40.6 42.8 26.3 30.6 27.1 14.9 18.9 24.1 7 39.0 33.7 21.3 29.2 33.2 42.4 100.0 82.1 83.1 28.1 34.9 25.2 20.9 24.7 25.4 8 34.6 32.4 23.1 28.2 33.0 40.6 82.1 100.0 86.1 31.5 35.8 23.7 16.2 22.3 22.9 9 37.8 33.2 22.5 25.4 34.2 42.8 83.1 86.1 100.0 27.2 33.2 27.8 13.9 21.3 21.5 10 27.9 27.3 33.3 30.3 28.8 26.3 28.1 31.5 27.2 100.0 42.3 20.8 31.1 23.9 20.8 11 33.0 36.8 28.5 39.3 39.3 30.6 34.9 35.8 33.2 42.3 100.0 37.7 32.5 22.4 28.8 12 24.7 32.9 29.6 37.7 33.9 27.1 25.2 23.7 27.8 20.8 37.7 100.0 22.0 26.1 12.5 13 24.9 25.8 19.6 22.6 18.1 14.9 20.9 16.2 13.9 31.1 32.5 22.0 100.0 30.9 21.0 14 13.4 28.5 21.2 29.1 25.3 18.9 24.7 22.3 21.3 23.9 22.4 26.1 30.9 100.0 18.5 15 28.4 24.8 26.9 26.1 30.0 24.1 25.4 22.9 21.5 20.8 28.8 12.5 21.0 18.5 100.0 Figure 7: Shannon index from fun- gal community between karst and non-karst area. ACTA CARSOLOGICA 50/2-3 – 2021 337 YIDONG MI, HONGDA FANG, PENG TAO, MIN ZHOU, XINRU LI, FANFAN W ANG, HAIYAN CHEN, HAILEI SU, YUANRONG ZHU, YUAN WEI & LIN XI not significant. The Shannon index and richness in sec- ondary forest, shrub and grassland were 3.78 and 45, 3.73 and 42, 3.70 and 40, respectively. Besides, the Shannon index and richness of non karst samples were 3.08 and 22, which were significantly lower than the levels of karst vegetation succession. The mean difference in fungal Shannon index between karst areas (3.70) and non karst areas (3.08) was 0.62 (Figure 7), significantly greater than that in bacterial Shannon index (0.37) (Figure 4), which indicated that the difference of fungal diversity between karst areas and non karst areas was more significant than bacterial diversity. The trends of fungal Shannon index and the richness was compared as follows: secondary for- est > shrubbery > grassland > primary forest. There was no difference between the evenness index values from each ecological succession. DISCUSSION In the present research, the diversity of bacteria and fun- gi in karst vegetation succession was studied using PCR- DGGE technology, and the results showed that abundant species of bacteria and fungi can be detected from karst vegetation succession areas. The ecological environment in karst areas is complex and diverse, species must adapt to this environment to survive. The abundant microbial diversity in karst is the result of long-term selection of ecological environment, which is conducive to maintain- ing the continuity and comprehensiveness of its func- tions ( Zhu et al., 2012; Tang et al., 2017). In this study, similarity cluster analysis for both bacteria and fungi communities provided that the con- servation and diversity behavior were distinguished in karst vegetation succession, which indicated that the soil microorganism community structure changed greatly with the conversion of vegetation succession. Pan et al. (2018) investigated litter and soil nutrients on soil en- zyme activities and microbial biomass along vegetation successions in karst region, and indicated that the litter nutrients and quantities had direct positive effect on soil nutrients, which had direct effect on enzyme activities and microbial biomass. Nutrient could be one of the key factors affecting the structure of microbial community. Meanwhile, plant community structure changing lead to alteration of microbial community structure, which have a significant impact on the decomposers (Lamb et al., 2010). Previous studies also support our view that plant communities are important factors affecting microbial diversity (Schlatter et al., 2015). Compared with the results from bacteria study, the differences of fungal diversity between karst areas and non karst areas were more obvious. Soil fungi partici- pate in the decomposition of plant and animal remains, which is the most indispensable source in the soil car- bon and nitrogen cycle, especially in the early stage of plant remains decomposition, fungi are more active than bacteria (Clemmensen et al., 2013). With the succession of vegetation, the composition of plant community and the source of carbon in soil changed significantly, which leads to alterations of the fungal community structure in soil (Wang et al., 2013). Besides, both fungi and bacteria in karst areas have high diversity in our result. Previous study reported that bacteria and fungi have great com- plementarity in ecological function to form healthy karst soil microbiota (Liang et al., 2016). Abundant microbial diversity may determine the rate of material cycling in a karst ecosystem thereby affects plant community diver- sity and productivity (Li et al., 2014). The Shannon index, richness and evenness of bac- teria and fungi in different vegetation succession stages were analyzed in this study. The patterns identified from the bacterial survey for Shannon diversity index and the richness comprehensively was evaluated as follows: Table 5: Shannon index, richness and evenness of fungal communities in different vegetation succession stage samples. Vegetation succession Shannon index (H) Richness (S) Evenness (EH) Primary forest 3.56±0.02b 35b 1.00±0.00a Secondary forest 3.78±0.25a 45a 1.00±0.00a Shrub 3.73±0.10a 42a 1.00±0.00a Grassland 3.70±0.13a 40a 1.00±0.00a Non karst 3.08±0.04c 22c 1.00±0.00a Note: Data are the means ± SD (Different letters “a, b, c, ” in the same column indicate significant differences at P < 0.05 with Tukey test for multiple comparisons.) ACTA CARSOLOGICA 50/2-3 – 2021 338 COMPARATION STUDY OF SOIL GENETIC DIVERSITY OF BACTERIA AND FUNGI IN DIFFERENT VEGETATION SUCCESSIONS IN A KARST OF GUIZHOU PROVINCE, CHINA shrub > grassland > primary forest > secondary forest > non karst, bacterial diversity tends to increase firstly from grassland to shrub and then decrease gradually to be stable with the positive succession of vegetation from shrub to secondary forest. This result is consistent with the latest research of using high-throughput sequencing technology to study the structure of soil bacterial com- munity in karst areas (Liu et al., 2015a). The main reason is that soil fertility is low and soil heterogeneity increased in the early stage of vegetation succession, which in- creased the diversity of soil bacterial community (Liu et al., 2015b). Based on our result, with the positive succes- sion of the ecosystem, the composition and structure of the ecosystem tended to be complete and stable (Loreau & de Mazancourt, 2013), and some bacteria in the inter- mediate of succession are eliminated. It has been known that there is a positive correlation between soil microbial metabolic diversities and plant taxonomic diversity (He et al., 2008). The trends of fungal Shannon index and the rich- ness were identified as follows: secondary forest > shrub- bery > grassland > primary forest > non karst. At the same time, through the comprehensive analysis of the Shannon index, richness and evenness of fungi in differ- ent vegetation successions, the karst ecological succes- sion had a significant impact on the fungal community structure. Bastias et al. (2007) studied the effect of forest type conversion on soil fungal diversity by PCR-TFLP and DGGE technology, and found that the change of for- est type affected the diversity of soil fungal community greatly, which supported our results (Harpole & Tilman, 2007). Unlike the pattern from the bacteria survey, in fungal communities, Shannon index and the richness showed that the secondary forest showed the highest val- ues. Zhu et al. (2012) found that the Shannon indexes of fungi was positively correlated with the contents of soil organic carbon, total nitrogen and cation exchange capacity. With the vegetation succession (from farming system to tussock, shrub and secondary forest), soil or- ganic carbon, total nitrogen and physical conditions were significantly improved, which resulted in the increases of soil fungal phylogenetic diversity (Zhu et al., 2012). Soil fungal communities are often strongly influenced by soil nutrient (Gomez-Brandon et al., 2020; Xu et al., 2021). Numerous studies have demonstrated that vegetation succession could alter and gradually restore soil nutri- ents (Jiao et al., 2011; Zhang et al., 2021). The plants in secondary forests in the study area include leguminous plants and non-leguminous plants, leguminous plants have the ability to enter into symbiosis with nitrogen-fix- ing bacteria (Liang et al., 2016), which can increased soil nutrients (Zhang et al., 2020b). This may be the reason for the high fungal diversity in secondary forests. Studies have shown that fungi in the upper layer of soil are often associated with the decomposition of lit- ter (Kubartova et al., 2009; Zhang et al., 2020a). With the positive succession of vegetation in karst, the com- position and quantity of litters change greatly (Pan et al., 2018). It is obvious that different succession required dif- ferent fungal communities to play their important eco- logical functions. This study mainly collected topsoil, which indicated that litters could be the main reason for the great changes in the fungal community. ACKNOWLEDGMENT This work was funded by the National Natural Sci- ence Foundation of China (41977294), Ministry of Sci- ence and Technology of the People's Republic of China (2016R1A6A1A05011910). REFERENCES Bassam, B.J., Caetano-Anollés, G., Gresshoff, P.M., 1991. Fast and sensitive silver staining of DNA in polyacrylamide gels. 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