广西环江喀斯特常绿落叶阔叶林土壤微生物类群的空间格局
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摘要
运用地理统计学和Illumina 16S rRNA基因测序等手段,研究广西环江木论国家自然保护区25 hm~2喀斯特常绿落叶阔叶林土壤主要门级微生物类群的空间分布。结果表明:广西环江木论国家自然保护区喀斯特森林土壤中优势菌门为变形菌门(Protebacteria,34.5%)、放线菌门(Actinobacteria,30.7%)和酸杆菌门(Acidobacteria,12.2%);土壤细菌类群显示空间相关性的自相关范围为44.4～841.4m,其中大部分细菌类群的变程在研究区域范围(500 m)内;在研究区内,变形菌门的相对丰度从北到南逐渐升高,而放线菌门和厚壁菌门(Firmicutes)的相对丰度则从北到南逐渐降低,绿弯菌门(Chloroflexi)、酸杆菌门、奇古菌门(Thaumarchaeota)、拟杆菌门(Bacteroidetes)、芽单胞菌门(Gemmatimonadetes)、疣微菌门(Verrucomicrobia)的相对丰度呈斑片状分布,硝化螺旋菌门(Nitrospirae)的相对丰度呈单峰型分布,WS3(Latescibacteria)的相对丰度则呈间歇性的低值条带和高值条带状分布。可见,喀斯特土壤主要微生物类群相对丰度呈现不同的空间分布格局。
To understand the spatial pattern of soil microbial communities at the phyla level in Mulun National Natural Reserve in Huangjiang of Guangxi, we used geostatistical modeling and Illumina sequencing of 16 S rRNA genes to the soils in a 25 hm~2 karst evergreen deciduous broadleaf forest. The results showed that the dominant bacterial phyla in the karst forest soils were Protebacteria(34.5%), Actinobacteria(30.7%) and Acidobacteria(12.2%). Soil bacterial taxa showed spatial dependence with an autocorrelation range of 44.4-841.4 m, and most of them were within the scope of the study plot(500 m). An increasing trend was observed for Proteobacteria from north to south in the studied area, but an opposite trend for Actinobacteria and Firmicutes was observed. The spatial pattern for Chloroflexi, Acidobacteira, Thaumarchaeota, Bacteroidetes, Gemmatimonadetes and Verrucomicrobia could be characterized as patchy, and the spatial pattern for Nitrospirae could be unimodal. In addition, the spatial pattern for Latescibacteria could be intermittent with low and high value strips. Overall, our results demonstrated that the spatial distribution of soil microbial communities differs among various taxa in karst forest.
To understand the spatial pattern of soil microbial communities at the phyla level in Mulun National Natural Reserve in Huangjiang of Guangxi, we used geostatistical modeling and Illumina sequencing of 16 S rRNA genes to the soils in a 25 hm~2 karst evergreen deciduous broadleaf forest. The results showed that the dominant bacterial phyla in the karst forest soils were Protebacteria(34.5%), Actinobacteria(30.7%) and Acidobacteria(12.2%). Soil bacterial taxa showed spatial dependence with an autocorrelation range of 44.4-841.4 m, and most of them were within the scope of the study plot(500 m). An increasing trend was observed for Proteobacteria from north to south in the studied area, but an opposite trend for Actinobacteria and Firmicutes was observed. The spatial pattern for Chloroflexi, Acidobacteira, Thaumarchaeota, Bacteroidetes, Gemmatimonadetes and Verrucomicrobia could be characterized as patchy, and the spatial pattern for Nitrospirae could be unimodal. In addition, the spatial pattern for Latescibacteria could be intermittent with low and high value strips. Overall, our results demonstrated that the spatial distribution of soil microbial communities differs among various taxa in karst forest.
引文
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[2] REN C J,ZHANG W,ZHONG Z K,et al.Differential responses of soil microbial biomass, diversity, and compositions to altitudinal gradients depend on plant and soil characteristics[J].Science of the Total Environment,2018,610/611:750–758.
[3] BARDGETT R D, VAN DER PUTTEN W H.Belowground biodiversity and ecosystem functioning[J].Nature,2014,515:505–511.
[4] BELL T,NEWMAN J A,SILVERMAN B W,et al.The contribution of species richness and composition to bacterial services[J].Nature,2005,436:1157–1160.
[5] VAN DER HEIJDEN M G A,BARDGETT R D,VAN STRAALEN N M.The unseen majority:soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems[J].Ecology Letters,2008,11(3):296–310.
[6] JING X,SANDERS N J,SHI Y,et al.The links between ecosystem multifunctionality and above-and belowground biodiversity are mediated by climate[J]. Nature Communications,2015,6:8159.
[7] CORREA-GALEOTE D,MARCO D E,TORTOSA G,et al.Spatial distribution of N-cycling microbial communities showed complex patterns in constructed wetland sediments[J].FEMS Microbiology Ecology,2013,83(2):340–351.
[8] HORNER-DEVINE M C,CARNEY K M,BOHANNAN B J M.An ecological perspective on bacterial biodiversity[J].Proceedings of the Royal Society of London Series B:Biological Sciences,2004,271:113–122.
[9] MARTINY J B H,BOHANNAN B J M,BROWN J H,et al.Microbial biogeography:putting microorganisms on the map[J].Nature Reviews Microbiology,2006,4:102–112.
[10] RANJARD L, DEQUIEDT S, JOLIVET C, et al.Biogeography of soil microbial communities:a review and a description of the ongoing French national initiative[J].Agronomy for Sustainable Development,2010,30:359–365.
[11] DE VRIES F T,MANNING P,TALLOWIN J R B,et al.Abiotic drivers and plant traits explain landscape-scale patterns in soil microbial communities[J]. Ecology Letters,2012,15(11):1230–1239.
[12] PENG W X,SONG T Q,ZENG F P,et al.Spatial distribution of surface soil water content under different vegetation types in northwest Guangxi, China[J].Environmental Earth Sciences,2013,69(8):2699–2708.
[13]彭晚霞，王克林，宋同清，等．喀斯特脆弱生态系统复合退化控制与重建模式[J]．生态学报，2008,28(2):811–820.
[14] ZHANG Z H,HU G,ZHU J D,et al.Spatial patterns and interspecific associations of dominant tree species in two old-growth karst forests,SW China[J].Ecological Research,2010,25(6):1151–1160.
[15] ZHOU Y C,WANG S J,LU H M,et al.Forest soil heterogeneity and soil sampling protocols on limestone outcrops:example from SW China[J].Acta Carsologica,2010,39(1):115–122.
[16] DU H,HU F,ZENG F P,et al.Spatial distribution of tree species in evergreen-deciduous broadleaf karst forests in southwest China[J].Scientific Reports,2017,7:15664.
[17] MORI H,MARUYAMA F,KATO H,et al.Design and experimental application of a novel non-degenerate universal primer set that amplifies prokaryotic 16S rRNA genes with a low possibility to amplify eukaryotic rRNA genes[J].DNA Research,2014,21(2):217–227.
[18] SUN W M,XIAO E Z,XIAO T F,et al.Response of soil microbial communities to elevated antimony and arsenic contamination indicates the relationship between the innate microbiota and contaminant fractions[J].Environmental Science&Technology,2017,51(16):9165–9175.
[19] CAPORASO J G,KUCZYNSKI J,STOMBAUGH J,et al. QIIME allows analysis of high-throughput community sequencing data[J].Nature Methods,2010,7(5):335–336.
[20]王政权．地统计学及在生态学中的应用[M]．北京：科学出版社，1999.
[21] GOOVAERTS P.Geostatistical tools for characterizing the spatial variability of microbiological and physicochemical soil properties[J]. Biology and Fertility of Soils,1998,27(4):315–334.
[22]邬建国．景观生态学：格局、过程、尺度与等级[M]．北京：高等教育出版社，2000.
[23] LIU J J,SUI Y Y,YU Z H,et al.High throughput sequencing analysis of biogeographical distribution of bacterial communities in the black soils of northeast China[J].Soil Biology and Biochemistry,2014,70:113–122.
[24] REN C J,SUN P S,KANG D,et al.Responsiveness of soil nitrogen fractions and bacterial communities to afforestation in the Loess Hilly Region(LHR)of China[J].Scientific Reports,2016,6:1–11.
[25] CHU H Y,FIERER N,LAUBER C L,et al.Soil bacterial diversity in the Arctic is not fundamentally different from that found in other biomes[J].Environmental Microbiology,2010,12(11):2998–3006.
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