Beyond variance: Simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure

Girard-Tercieux Camille, Vieilledent Ghislain, Clark Adam T., Clark Adam T., Courbaud Benoît, Fortunel Claire, Kunstler Georges, Pélissier Raphaël, Rüger Nadja, Marechaux Isabelle. 2024. Beyond variance: Simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure. Peer Community Journal, 4:e28, 19 p.

Url - autre : https://doi.org/10.24072/pci.ecology.100466 / Url - autres données associées : https://doi.org/10.5281/zenodo.6929042 / Url - autres données associées : https://doi.org/10.5281/zenodo.10616716

Résumé : The role of intraspecific variability (IV) in shaping community dynamics and species coexistence has been intensively discussed over the past decade and modelling studies have played an important role in that respect. However, these studies often implicitly assume that IV can be represented by independent random draws around species-specific mean parameters. This major assumption has largely remained undiscussed, although a great part of observed IV is structured in space or time, in particular when environmental dimensions that influence individual performance are imperfectly characterised or unobserved in the field. To test the impact of this strong assumption on the outcome of community dynamics models, we designed a simulation experiment where we varied the level of knowledge of the environment in virtual communities, resulting in different relative importance of explained vs unexplained spatial individual variation in performance. We used a community dynamics simulator to generate communities where the unexplained individual variation is, or is not, added as an unstructured random noise. Communities simulated with unstructured IV never reached the community diversity and composition of those where all the variation was explained and structured (perfect knowledge model). This highlights that incorporating unstructured IV (i.e. a random noise) to account for unexplained (but structured) variation can lead to incorrect simulations of community dynamics. In addition, the effects of unstructured IV on community diversity and composition depended on the relative importance of structured vs unstructured IV, i.e. on the level of knowledge of the environment, which may partly explain the contrasting results of previous studies on the effect of IV on species coexistence. In particular, the effect of unstructured IV on community diversity was positive when the proportion of structured IV vs unstructured IV in the model was low, but negative when this proportion was high. This is because unstructured random noise can either limit the competitive exclusion of inferior competitors in low dimensions or destabilise tight niche partitioning in high dimension. Our study suggests that it is crucial to account for the sources and structure of observed IV in real communities to better understand its effect on community assembly and properly include it in community dynamics models.

Mots-clés Agrovoc : modèle de simulation, modélisation environnementale, modèle mathématique, impact sur l'environnement, variation génétique, dynamique des populations

Mots-clés libres : Species coexistence, Intraspecific variability, Micro-environment, Multidimensional species niche, Theoretical ecology

Classification Agris : U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 7 (2019-) - Hors champs stratégiques

Agences de financement hors UE : Centre de synthèse et d'analyse sur la biodiversité, Fondation pour la Recherche sur la Biodiversite, Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig, Agence Nationale de la Recherche

Projets sur financement : (FRA) CEnter of the study of Biodiversity in Amazonia

Auteurs et affiliations

• Girard-Tercieux Camille, Université de Montpellier (FRA) - auteur correspondant
• Vieilledent Ghislain, CIRAD-BIOS-UMR AMAP (FRA) ORCID: 0000-0002-1685-4997
• Clark Adam T., Karl-Franzens-Universität Graz (AUT)
• Clark Adam T., Karl-Franzens-Universität Graz (AUT)
• Courbaud Benoît, Université Grenoble Alpes (FRA)
• Fortunel Claire, IRD (FRA)
• Kunstler Georges, Université Grenoble Alpes (FRA)
• Pélissier Raphaël, IRD (FRA)
• Rüger Nadja, University of Leipzig (DEU)
• Marechaux Isabelle, CNRS (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/609110/)

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