Toward a function-first framework to make soil microbial ecology predictive
(2022) In Ecology 103(e03594).- Abstract
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).... (More)
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.
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- author
- Hicks, Lettice C. LU ; Frey, Beat ; Kjøller, Rasmus ; Lukac, Martin ; Moora, Mari ; Weedon, James T. and Rousk, Johannes LU
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- biogeochemistry, community ecology, predictive ecology, soil carbon, soil microorganisms, structure and function
- in
- Ecology
- volume
- 103
- issue
- e03594
- publisher
- Ecological Society of America
- external identifiers
-
- pmid:34807459
- scopus:85121440233
- ISSN
- 0012-9658
- DOI
- 10.1002/ecy.3594
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2021 The Authors. Ecology published by Wiley Periodicals LLC on behalf of Ecological Society of America.
- id
- 34d34faa-7b63-4737-b002-6ba3da4cf4e9
- date added to LUP
- 2022-01-12 08:49:33
- date last changed
- 2024-06-15 23:46:50
@article{34d34faa-7b63-4737-b002-6ba3da4cf4e9,
abstract = {{<p>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.</p>}},
author = {{Hicks, Lettice C. and Frey, Beat and Kjøller, Rasmus and Lukac, Martin and Moora, Mari and Weedon, James T. and Rousk, Johannes}},
issn = {{0012-9658}},
keywords = {{biogeochemistry; community ecology; predictive ecology; soil carbon; soil microorganisms; structure and function}},
language = {{eng}},
number = {{e03594}},
publisher = {{Ecological Society of America}},
series = {{Ecology}},
title = {{Toward a function-first framework to make soil microbial ecology predictive}},
url = {{http://dx.doi.org/10.1002/ecy.3594}},
doi = {{10.1002/ecy.3594}},
volume = {{103}},
year = {{2022}},
}