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Title of the item:

Theory of temperature-dependent consumer-resource interactions.

Title :
Theory of temperature-dependent consumer-resource interactions.
Authors :
Synodinos AD; Theoretical and Experimental Ecology Station, CNRS, Moulis, France.
Haegeman B; Theoretical and Experimental Ecology Station, CNRS, Moulis, France.
Sentis A; INRAE, Aix Marseille University, UMR RECOVER, Aix-en-Provence, France.
Montoya JM; Theoretical and Experimental Ecology Station, CNRS, Moulis, France.
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Source :
Ecology letters [Ecol Lett] 2021 Aug; Vol. 24 (8), pp. 1539-1555. Date of Electronic Publication: 2021 Jun 13.
Publication Type :
Journal Article
Language :
Imprint Name(s) :
Publication: Oxford, UK : Blackwell Publishing
Original Publication: Oxford, UK : [Paris, France] : Blackwell Science ; Centre national de la recherche scientifique, c1998-
MeSH Terms :
Food Chain*
Biomass ; Temperature
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Grant Information :
726176 H2020 European Research Council; ANR-10-LABX-41 Agence Nationale de la Recherche
Contributed Indexing :
Keywords: biomass distributions; climate change; community stability; consumer; food webs; interaction strength; resource dynamics; temperature dependence
Entry Date(s) :
Date Created: 20210613 Date Completed: 20210713 Latest Revision: 20210713
Update Code :
Academic Journal
Changes in temperature affect consumer-resource interactions, which underpin the functioning of ecosystems. However, existing studies report contrasting predictions regarding the impacts of warming on biological rates and community dynamics. To improve prediction accuracy and comparability, we develop an approach that combines sensitivity analysis and aggregate parameters. The former determines which biological parameters impact the community most strongly. The use of aggregate parameters (i.e., maximal energetic efficiency, ρ, and interaction strength, κ), that combine multiple biological parameters, increases explanatory power and reduces the complexity of theoretical analyses. We illustrate the approach using empirically derived thermal dependence curves of biological rates and applying it to consumer-resource biomass ratio and community stability. Based on our analyses, we generate four predictions: (1) resource growth rate regulates biomass distributions at mild temperatures, (2) interaction strength alone determines the thermal boundaries of the community, (3) warming destabilises dynamics at low and mild temperatures only and (4) interactions strength must decrease faster than maximal energetic efficiency for warming to stabilise dynamics. We argue for the potential benefits of directly working with the aggregate parameters to increase the accuracy of predictions on warming impacts on food webs and promote cross-system comparisons.
(© 2021 John Wiley & Sons Ltd.)

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