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法国土壤细菌丰富度的图谱绘制与预测变化

Mapping and predictive variations of soil bacterial richness across France.

作者信息

Terrat Sébastien, Horrigue Walid, Dequiedt Samuel, Saby Nicolas P A, Lelièvre Mélanie, Nowak Virginie, Tripied Julie, Régnier Tiffanie, Jolivet Claudy, Arrouays Dominique, Wincker Patrick, Cruaud Corinne, Karimi Battle, Bispo Antonio, Maron Pierre Alain, Chemidlin Prévost-Bouré Nicolas, Ranjard Lionel

机构信息

Agroécologie, AgroSup Dijon, INRA, Univ. Bourgogne Franche-Comté, Dijon, France.

INRA Orléans - US 1106, Unité INFOSOL, Orleans, France.

出版信息

PLoS One. 2017 Oct 23;12(10):e0186766. doi: 10.1371/journal.pone.0186766. eCollection 2017.

Abstract

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

摘要

尽管众多研究已证明细菌多样性在土壤功能和生态系统服务中发挥着关键作用,但在全国范围内,对于这种多样性的变化及其决定因素却知之甚少。本研究的总体目标是:(i)描述法国各地细菌分类丰富度的变化;(ii)确定影响这种分布的生态过程(即环境选择和扩散限制);(iii)建立土壤细菌丰富度的统计预测模型。我们利用了法国土壤质量监测网络(RMQS),该网络覆盖法国全境,有2173个站点。通过对16S rRNA基因进行焦磷酸测序来确定土壤细菌丰富度(即OTU数量),并将其与土壤特征、气候条件、地貌、土地利用和空间相关联。细菌丰富度的地图显示出一种异质的空间分布,形成了约111公里的斑块,其中主要驱动因素是土壤理化性质(解释方差的18%)、空间描述符(细、中、粗尺度分别为5.25%、1.89%和1.02%)以及土地利用(1.4%)。基于这些驱动因素,开发了一个预测模型,该模型能够很好地预测细菌丰富度(调整后的R2为0.56),并为给定的土壤气候条件提供参考值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14ad/5653302/0640ad0139e5/pone.0186766.g001.jpg

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