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Soil Biology and Biochemistry
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Disentangling drivers of soil microbial potential enzyme activity across rain regimes: An approach based on the functional trait framework

Authors: Pedro Martins da Silva; Jean-Christophe Clément; José Paulo Sousa; Laura B. Martínez-García; Nicolas Legay; Eduardo Nascimento; Arnaud Foulquier; +6 Authors

Disentangling drivers of soil microbial potential enzyme activity across rain regimes: An approach based on the functional trait framework

Abstract

The functional trait framework provides a powerful corpus of integrated concepts and theories to assess how environmental factors influence ecosystem functioning through community assembly. While common in plant ecology, this approach is under-used in microbial ecology. After an introduction of this framework in the context of microbial ecology and enzymology, we propose an approach 1) to elucidate new links between soil microbial community composition and microbial traits; and 2) to disentangle mechanisms underlying “total” potential enzyme activity in soil (sum of 7 hydrolase potential activities). We address these objectives using a terrestrial grassland ecosystem model experiment with intact soil monoliths from three European countries (Switzerland, France and Portugal) and two management types (Conventional-intensive and Ecological-intensive), subjected to 4 rain regimes (Dry, Wet, Intermittent and Normal) under controlled conditions in a common climate chamber. We found tight associations between proxies of microbial ecoenzymatic community-weighted mean traits (enzymatic stoichiometry and biomass-specific activity) and community composition, bringing new information on resource acquisition strategy associated with fungi, Gram positive and Gram negative bacteria. We demonstrate that microbial biomass explained most of the total enzyme activity before altered rain regimes, whereas adjustments in biomass-specific activity (enzyme activity per unit of microbial biomass) explained most variation under altered rain regime scenarios. Furthermore, structural equation models revealed that the variation of community composition was the main driver of the variation in biomass-specific enzyme activity prior to rain perturbation, whereas physiological acclimation or evolutionary adaptation became an important driver only under altered rain regimes. This study presents a promising trait-based approach to investigate soil microbial community response to environmental changes and potential consequences for ecosystem functioning. We argue that the functional trait framework should be further implemented in microbial ecology to guide experimental and analytical design.

Countries
France, Netherlands
Keywords

[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 550, Bacteria, Fungi, Enzymatic stoichiometry, Structural equation mode, Structural equation model, PLFA, Climate change

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    Top 10%
    influence
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    impulse
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Average
Top 10%
Green
bronze