Viewing soil systems from the top-down can make microbial ecology predictive for ecosystem functions
Johannes Rousk, Lettice Hicks
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80% confidenceInternational MES research in standard with focus on bioelectrochemical. Understanding the role of ecological communities in maintaining multiple ecosystem pro...
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Abstract
Understanding the role of ecological communities in maintaining multiple ecosystem processes is a central challenge in ecology. Soil microbial communities perform vital ecosystem functions, such as the decomposition of organic matter to provide plant nutrition. However, despite the functional importance of soil microorganisms, attribution of ecosystem function to particular constituents of the microbial community has been impeded by a lack of information linking microbial processes to community structure. Here, we propose a new conceptual framework to determine how microbial communities influence ecosystem processes, by applying a “top-down” approach. Looking from the “top”, we first view the microbial community associated with a specific function as a whole, and describe the dependence of microbial community processes on environmental factors (e.g. the intrinsic temperature dependence of bacterial growth rates), allowing us to define the aggregate functional response curve of the community. We then demonstrate that the whole community contribution to ecosystem function can be predicted, by parameterising the functional response curve with current environmental conditions. In a final step, we show how this functional information can be linked to the taxonomic community composition (amplicon assessments of microbial community composition) in order to identify “biomarker” taxa that capture microbial communities’ regulation of ecosystem processes and the susceptibility of microbial community structure and function to environmental change. Ultimately, these biomarkers may be used as a diagnostic tool, enabling predictions of ecosystem function from community composition information combined with environmental metadata.
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- Journal
- Unknown journal
- Year
- 2020