The dimensionality and structure of species trait spaces.

Autor: Mouillot D; MARBEC, University of Montpellier, CNRS, IFREMER, IRD, Montpellier, France.; Institut Universitaire de France, IUF, Paris, France., Loiseau N; MARBEC, University of Montpellier, CNRS, IFREMER, IRD, Montpellier, France., Grenié M; Centre d'Ecologie Fonctionnelle et Evolutive-UMR 5175 CEFE, University of Montpellier, CNRS, EPHE, University of Paul Valéry, IRD, Montpellier, France., Algar AC; Department of Biology, Lakehead University, Thunder Bay, ON, Canada., Allegra M; Institut de Neurosciences de la Timone, Aix Marseille Université, UMR 7289, CNRS, Marseille, France., Cadotte MW; Department of Biological Sciences, University of Toronto-Scarborough, Toronto, ON, Canada., Casajus N; FRB-CESAB, Institut Bouisson Bertrand, Montpellier, France., Denelle P; Biodiversity, Macroecology & Biogeography, University of Goettingen, Göttingen, Germany., Guéguen M; Laboratoire d'Ecologie Alpine, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France., Maire A; EDF R&D, LNHE (Laboratoire National d'Hydraulique et Environnement), Chatou, France., Maitner B; Department of Ecology and Evolutionary Biology, University of Connecticut, Mansfield, CT, USA., McGill BJ; School of Biology and Ecology and Mitchell Center for Sustainability Solutions, University of Maine, Orono, ME, USA., McLean M; Department of Biology, Dalhousie University, Halifax, Nova Scotia, Canada., Mouquet N; MARBEC, University of Montpellier, CNRS, IFREMER, IRD, Montpellier, France.; FRB-CESAB, Institut Bouisson Bertrand, Montpellier, France., Munoz F; LiPhy (Laboratoire Interdisciplinaire de Physique), Université Grenoble Alpes, Grenoble, France., Thuiller W; Laboratoire d'Ecologie Alpine, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France., Villéger S; MARBEC, University of Montpellier, CNRS, IFREMER, IRD, Montpellier, France., Violle C; Centre d'Ecologie Fonctionnelle et Evolutive-UMR 5175 CEFE, University of Montpellier, CNRS, EPHE, University of Paul Valéry, IRD, Montpellier, France., Auber A; IFREMER, Unité Halieutique Manche Mer du Nord, Laboratoire Ressources Halieutiques, Boulogne-sur-Mer, France.
Jazyk: angličtina
Zdroj: Ecology letters [Ecol Lett] 2021 Sep; Vol. 24 (9), pp. 1988-2009. Date of Electronic Publication: 2021 May 20.
DOI: 10.1111/ele.13778
Abstrakt: Trait-based ecology aims to understand the processes that generate the overarching diversity of organismal traits and their influence on ecosystem functioning. Achieving this goal requires simplifying this complexity in synthetic axes defining a trait space and to cluster species based on their traits while identifying those with unique combinations of traits. However, so far, we know little about the dimensionality, the robustness to trait omission and the structure of these trait spaces. Here, we propose a unified framework and a synthesis across 30 trait datasets representing a broad variety of taxa, ecosystems and spatial scales to show that a common trade-off between trait space quality and operationality appears between three and six dimensions. The robustness to trait omission is generally low but highly variable among datasets. We also highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, whereas species tend to disproportionately pack in the richest cluster. Based on these results, we propose some rules of thumb to build species trait spaces and estimate subsequent functional diversity indices.
(© 2021 John Wiley & Sons Ltd.)
Databáze: MEDLINE
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