Ma Bin, Dai Zhongmin, Wang Haizhen, Dsouza Melissa, Liu Xingmei, He Yan, Wu Jianjun, Rodrigues Jorge L M, Gilbert Jack A, Brookes Philip C, Xu Jianming
Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou, China.
Department of Ecology and Evolution and Department of Surgery, University of Chicago, Chicago, Illinois, USA; The Marine Biological Laboratory, Woods Hole, Massachusetts, USA.
mSystems. 2017 Feb 7;2(1). doi: 10.1128/mSystems.00174-16. eCollection 2017 Jan-Feb.
The natural forest ecosystem in Eastern China, from tropical forest to boreal forest, has declined due to cropland development during the last 300 years, yet little is known about the historical biogeographic patterns and driving processes for the major domains of microorganisms along this continental-scale natural vegetation gradient. We predicted the biogeographic patterns of soil archaeal, bacterial, and fungal communities across 110 natural forest sites along a transect across four vegetation zones in Eastern China. The distance decay relationships demonstrated the distinct biogeographic patterns of archaeal, bacterial, and fungal communities. While historical processes mainly influenced bacterial community variations, spatially autocorrelated environmental variables mainly influenced the fungal community. did not display a distance decay pattern along the vegetation gradient. Bacterial community diversity and structure were correlated with the ratio of acid oxalate-soluble Fe to free Fe oxides (Feo/Fed ratio). Fungal community diversity and structure were influenced by dissolved organic carbon (DOC) and free aluminum (Ald), respectively. The role of these environmental variables was confirmed by the correlations between dominant operational taxonomic units (OTUs) and edaphic variables. However, most of the dominant OTUs were not correlated with the major driving variables for the entire communities. These results demonstrate that soil archaea, bacteria, and fungi have different biogeographic patterns and driving processes along this continental-scale natural vegetation gradient, implying different community assembly mechanisms and ecological functions for archaea, bacteria, and fungi in soil ecosystems. Understanding biogeographic patterns is a precursor to improving our knowledge of the function of microbiomes and to predicting ecosystem responses to environmental change. Using natural forest soil samples from 110 locations, this study is one of the largest attempts to comprehensively understand the different patterns of soil archaeal, bacterial, and fungal biogeography at the continental scale in eastern China. These patterns in natural forest sites could ascertain reliable soil microbial biogeographic patterns by eliminating anthropogenic influences. This information provides guidelines for monitoring the belowground ecosystem's decline and restoration. Meanwhile, the deviations in the soil microbial communities from corresponding natural forest states indicate the extent of degradation of the soil ecosystem. Moreover, given the association between vegetation type and the microbial community, this information could be used to predict the long-term response of the underground ecosystem to the vegetation distribution caused by global climate change.
在过去300年里,由于耕地开发,中国东部从热带森林到寒温带森林的天然森林生态系统已经衰退,但对于沿这个大陆尺度自然植被梯度的主要微生物类群的历史生物地理格局和驱动过程,人们了解甚少。我们预测了中国东部沿四个植被带的样带上110个天然森林站点土壤古菌、细菌和真菌群落的生物地理格局。距离衰减关系表明了古菌、细菌和真菌群落独特的生物地理格局。虽然历史过程主要影响细菌群落变异,但空间自相关环境变量主要影响真菌群落。沿植被梯度未呈现距离衰减模式。细菌群落多样性和结构与草酸溶性铁与游离铁氧化物的比率(Feo/Fed比率)相关。真菌群落多样性和结构分别受溶解有机碳(DOC)和游离铝(Ald)影响。这些环境变量的作用通过优势操作分类单元(OTU)与土壤变量之间的相关性得到证实。然而,大多数优势OTU与整个群落的主要驱动变量不相关。这些结果表明,土壤古菌、细菌和真菌沿这个大陆尺度自然植被梯度具有不同的生物地理格局和驱动过程,这意味着土壤生态系统中古菌、细菌和真菌具有不同的群落组装机制和生态功能。了解生物地理格局是增进我们对微生物群落功能的认识以及预测生态系统对环境变化响应的前提。本研究使用了来自110个地点的天然森林土壤样本,是在中国东部大陆尺度上全面了解土壤古菌、细菌和真菌生物地理学不同模式的最大规模尝试之一。天然森林站点的这些模式可以通过消除人为影响来确定可靠的土壤微生物生物地理模式。这些信息为监测地下生态系统的衰退和恢复提供了指导。同时,土壤微生物群落与相应天然森林状态的偏差表明了土壤生态系统的退化程度。此外,鉴于植被类型与微生物群落之间的关联,这些信息可用于预测地下生态系统对全球气候变化导致的植被分布的长期响应。