Unveiling ecological assembly rules from commonalities in trait distributions

Gross, Nicolas; Le Bagousse‐Pinguet, Yoann; Liancourt, Pierre; Saiz, Hugo; Violle, Cyrille; Munoz, François (2021). Unveiling ecological assembly rules from commonalities in trait distributions. Ecology Letters, 24(8), pp. 1668-1680. Wiley-Blackwell Publishing 10.1111/ele.13789

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Deciphering the effect of neutral and deterministic processes on community assembly is critical to understand and predict diversity patterns. The information held in community trait distributions is commonly assumed as a signature of these processes, but empirical and modelling attempts have most often failed to untangle their confounding, sometimes opposing, impacts. Here, we simulated the assembly of trait distributions through stochastic (dispersal limitation) and/or deterministic scenarios (environmental filtering and niche differentiation). We characterized the shape of trait distributions using the skewness–kurtosis relationship. We identified commonalities in the co-variation between the skewness and the kurtosis of trait distributions with a unique signature for each simulated assembly scenario. Our findings were robust to variation in the composition of regional species pools, dispersal limitation and environmental conditions. While ecological communities can exhibit a high degree of idiosyncrasy, identification of commonalities across multiple communities can help to unveil ecological assembly rules in real-world ecosystems.

Item Type:

Journal Article (Original Article)


08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS)
08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS) > Biodiversity

UniBE Contributor:

Saiz Bustamante, Hugo


500 Science > 580 Plants (Botany)




Wiley-Blackwell Publishing




Peter Alfred von Ballmoos-Haas

Date Deposited:

15 Jul 2021 13:23

Last Modified:

05 Dec 2022 15:51

Publisher DOI:


Uncontrolled Keywords:

community assembly rules; dispersal; environmental filtering; functional diversity, niche differentiation; skewness–kurtosis relationship; stochasticity, trait distributions





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