Phylogenetic conservation of bacterial environmental responses predicts soil bacterial biogeographic patterns
Xia, M.; Isobe, K.; Martiny, J. B. H.
Show abstract
Soil bacterial communities exhibit biogeographic patterns along environmental gradients, yet why some environmental factors contribute more strongly to community turnover than others remains poorly understood. Here, we tested whether this variation can be explained by the phylogenetic depth at which bacterial responses to each environmental factor are conserved. Across 40 forest sites in Japan spanning multiple soil and climatic gradients, environmental factors whose bacterial responses were conserved at deeper phylogenetic levels contributed more strongly to bacterial community turnover. We further asked whether phylogenetic clades that share similar environmental responses represent ecologically meaningful units for understanding bacterial community responses. Using soil pH as a focal test case, we found that response-defined clades improved prediction of taxon-level abundance shifts and community-level compositional shifts compared with models that treated taxa as independent units. Together, these findings show that the phylogenetic depth of bacterial environmental responses links trait conservation, community turnover and soil bacterial biogeographic patterns. Significance StatementSoil bacterial communities form biogeographic patterns along environmental gradients, but it remains unclear why some environmental factors drive stronger community turnover than others. This study shows that the strength of bacterial community turnover can be predicted from the phylogenetic depth at which bacterial responses to environmental factors are conserved. Across forest soils in Japan, deeply conserved bacterial responses were linked to stronger community turnover, and clades sharing conserved responses improved prediction of both taxon- and community-level shifts. These findings identify phylogenetically conserved response structure as an organizing principle for understanding and predicting soil bacterial biogeographic patterns.
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