Toward a function-first framework to make soil microbial ecology predictive
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Toward a function-first framework to make soil microbial ecology predictive. / Hicks, Lettice C.; Frey, Beat; Kjøller, Rasmus; Lukac, Martin; Moora, Mari; Weedon, James T.; Rousk, Johannes.
In: Ecology, Vol. 103, No. 2, e03594, 2022.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Toward a function-first framework to make soil microbial ecology predictive
AU - Hicks, Lettice C.
AU - Frey, Beat
AU - Kjøller, Rasmus
AU - Lukac, Martin
AU - Moora, Mari
AU - Weedon, James T.
AU - Rousk, Johannes
N1 - Publisher Copyright: © 2021 The Authors. Ecology published by Wiley Periodicals LLC on behalf of Ecological Society of America.
PY - 2022
Y1 - 2022
N2 - 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 function to community composition and structure. Here, we propose a function-first framework to predict how microbial communities influence ecosystem functions. We first view the microbial community associated with a specific function as a whole and describe the dependence of microbial functions on environmental factors (e.g., the intrinsic temperature dependence of bacterial growth rates). This step defines the aggregate functional response curve of the community. Second, the contribution of the whole community to ecosystem function can be predicted, by combining the functional response curve with current environmental conditions. Functional response curves can then be linked with taxonomic data in order to identify sets of “biomarker” taxa that signal how microbial communities regulate ecosystem functions. Ultimately, such indicator taxa may be used as a diagnostic tool, enabling predictions of ecosystem function from community composition. In this paper, we provide three examples to illustrate the proposed framework, whereby the dependence of bacterial growth on environmental factors, including temperature, pH, and salinity, is defined as the functional response curve used to interlink soil bacterial community structure and function. Applying this framework will make it possible to predict ecosystem functions directly from microbial community composition.
AB - 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 function to community composition and structure. Here, we propose a function-first framework to predict how microbial communities influence ecosystem functions. We first view the microbial community associated with a specific function as a whole and describe the dependence of microbial functions on environmental factors (e.g., the intrinsic temperature dependence of bacterial growth rates). This step defines the aggregate functional response curve of the community. Second, the contribution of the whole community to ecosystem function can be predicted, by combining the functional response curve with current environmental conditions. Functional response curves can then be linked with taxonomic data in order to identify sets of “biomarker” taxa that signal how microbial communities regulate ecosystem functions. Ultimately, such indicator taxa may be used as a diagnostic tool, enabling predictions of ecosystem function from community composition. In this paper, we provide three examples to illustrate the proposed framework, whereby the dependence of bacterial growth on environmental factors, including temperature, pH, and salinity, is defined as the functional response curve used to interlink soil bacterial community structure and function. Applying this framework will make it possible to predict ecosystem functions directly from microbial community composition.
KW - biogeochemistry
KW - community ecology
KW - predictive ecology
KW - soil carbon
KW - soil microorganisms
KW - structure and function
U2 - 10.1002/ecy.3594
DO - 10.1002/ecy.3594
M3 - Journal article
C2 - 34807459
AN - SCOPUS:85121440233
VL - 103
JO - Ecology
JF - Ecology
SN - 0012-9658
IS - 2
M1 - e03594
ER -
ID: 288049984