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Predictions of biodiversity are improved by integrating trait-based competition with abiotic filtering.

Published version
Peer-reviewed

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Authors

Chalmandrier, Loïc  ORCID logo  https://orcid.org/0000-0002-2631-0432
Purcell, Adam ST 
Tanentzap, Andrew J  ORCID logo  https://orcid.org/0000-0002-2883-1901

Abstract

All organisms must simultaneously tolerate the environment and access limiting resources if they are to persist. Approaches to understanding abiotic filtering and competitive interactions have generally been developed independently. Consequently, integrating those factors to predict species abundances and community structure remains an unresolved challenge. We introduce a new synthetic framework that models both abiotic filtering and competition by using functional traits. First, our framework estimates species carrying capacities along abiotic gradients. Second, it estimates pairwise competitive interactions as a function of species trait differences. Applied to the study of a complex wetland community, our combined approach more than doubles the explained variance of species abundances compared to a model of abiotic tolerances alone. Trait-based integration of competitive interactions and abiotic filtering improves our ability to predict species abundances, bringing us closer to more accurate predictions of biodiversity structure in a changing world.

Description

Funder: University of Canterbury; Id: http://dx.doi.org/10.13039/100008414


Funder: University of Waikato; Id: http://dx.doi.org/10.13039/100010061


Funder: University of Wyoming; Id: http://dx.doi.org/10.13039/100008106


Funder: Manaaki Whenua ‐ Landcare Research

Keywords

abiotic filtering, community modelling, competition, functional trait, plant ecology, species abundances, wetland, Biodiversity, Ecosystem, Phenotype

Journal Title

Ecol Lett

Conference Name

Journal ISSN

1461-023X
1461-0248

Volume Title

Publisher

Wiley
Sponsorship
H2020 Marie Skłodowska‐Curie Actions (840946)
New Zealand Government (16‐UOC‐008, RDF‐13‐UOC‐003)