An evolutionary perspective on the response‐effect framework

Abstract The response‐effect framework (REF) has provided a foundational approach in functional ecology, using traits to predict how species respond to environmental factors (‘response traits’) and influence ecosystem functioning (‘effect traits’). While highly valuable, the REF has largely overlooked evolutionary dynamics and transgenerational processes, despite growing evidence that these processes significantly shape species' responses to environmental changes and their subsequent ecosystem impacts. Addressing this gap by integrating evolutionary dynamics into the REF can substantially enhance our understanding of both short and long‐term biodiversity and ecosystem functioning relationships. Here, we build on recent advances to explore how evolutionary processes and eco‐evolutionary feedbacks can refine predictions of trait responses to environmental changes and their ecosystem‐level implications. We also highlight experimental evolution as a powerful tool to assess the role of eco‐evolutionary dynamics in improving the predictive capacity of the REF. We advocate for greater integration of evolutionary dynamics into the REF to reinforce the applicability of the framework in a rapidly changing world. Read the free Plain Language Summary for this article on the Journal blog.

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Publication Details

Journal
Functional Ecology
Published
2025-12-05
DOI
https://doi.org/10.1111/1365-2435.70236
Citations
1
Primary Topic
Animal Behavior and Reproduction
Type
article
Field-Weighted Citation Impact
3.03

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article

An evolutionary perspective on the response‐effect framework

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1 citations
Functional Ecology
Animal Behavior and Reproduction
3.03
article

An evolutionary perspective on the response‐effect framework

Denis Vile, Lucie Mahaut, J. F. Scheepens, François Vasseur, Moisés Expósito‐Alonso, Oliver Bossdorf, Elena Kazakou, Cyrille Violle, Maria Stefania Przybylska, Detlef Weigel, Xavier Le Roux, François Munoz
article en
1 citations

Abstract

Abstract The response‐effect framework (REF) has provided a foundational approach in functional ecology, using traits to predict how species respond to environmental factors (‘response traits’) and influence ecosystem functioning (‘effect traits’). While highly valuable, the REF has largely overlooked evolutionary dynamics and transgenerational processes, despite growing evidence that these processes significantly shape species' responses to environmental changes and their subsequent ecosystem impacts. Addressing this gap by integrating evolutionary dynamics into the REF can substantially enhance our understanding of both short and long‐term biodiversity and ecosystem functioning relationships. Here, we build on recent advances to explore how evolutionary processes and eco‐evolutionary feedbacks can refine predictions of trait responses to environmental changes and their ecosystem‐level implications. We also highlight experimental evolution as a powerful tool to assess the role of eco‐evolutionary dynamics in improving the predictive capacity of the REF. We advocate for greater integration of evolutionary dynamics into the REF to reinforce the applicability of the framework in a rapidly changing world. Read the free Plain Language Summary for this article on the Journal blog.

Functional EcologyVol. 40(2)
Université Claude Bernard Lyon 1 (FR), Goethe University Frankfurt (DE), Centre National de la Recherche Scientifique (FR), Howard Hughes Medical Institute (US), École Pratique des Hautes Études (FR), Université de Montpellier (FR), Institut Agro Montpellier (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Centre d'Écologie Fonctionnelle et Évolutive (FR), VetAgro Sup (FR), Laboratoire d'Ecophysiologie des Plantes sous Stress environnementaux (FR), Laboratoire de Biométrie et Biologie Evolutive (FR), Institut Agro Montpelier (FR), Max Planck Institute for Biology (DE), Institut de Recherche pour le Développement (FR), University of Tübingen (DE), University of California, Berkeley (US)
Deutsche Forschungsgemeinschaft, Agence Nationale de la Recherche
Openalex Percentile: Top 7%
Animal Behavior and Reproduction
3.03
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