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

View ORCID ProfileLoïc Chalmandrier, View ORCID ProfileDaniel B. Stouffer, Adam S. T. Purcell, William G. Lee, View ORCID ProfileAndrew J. Tanentzap, View ORCID ProfileDaniel C. Laughlin
doi: https://doi.org/10.1101/2021.07.12.448750
Loïc Chalmandrier
1Department of Botany, University of Wyoming, Laramie, Wyoming, USA
2Centre for Integrative Ecology, School of Biological Sciences, Univ. of Canterbury, Christchurch, New Zealand
3Theoretical Ecology, Faculty of Biology and Pre-Clinical Medicine, University of Regensburg, Regensburg, Germany
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  • For correspondence: loic.chalmandrier@canterbury.ac.nz
Daniel B. Stouffer
2Centre for Integrative Ecology, School of Biological Sciences, Univ. of Canterbury, Christchurch, New Zealand
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Adam S. T. Purcell
4Tonkin + Taylor, Hamilton, New Zealand
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William G. Lee
5Landcare Research, Private Bag 1930, Dunedin 9054, New Zealand
6School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
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Andrew J. Tanentzap
7Ecosystems and Global Change Group, University of Cambridge, Cambridge, UK CB2 3EA
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Daniel C. Laughlin
1Department of Botany, University of Wyoming, Laramie, Wyoming, USA
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Abstract

All organisms must simultaneously tolerate the environment and access limiting resources if they are to persist. Otherwise they go extinct. Approaches to understanding environmental tolerance and resource competition have generally been developed independently. Consequently, integrating the factors that determine abiotic tolerance with those that affect competitive interactions to model species abundances and community structure remains an unresolved challenge. This is likely the reason why current models of community assembly do not accurately predict species abundances and dynamics. Here, we introduce a new synthetic framework that models both abiotic tolerance and biotic competition by using functional traits, which are phenotypic attributes that influence organism fitness. First, our framework estimates species carrying capacities that vary along abiotic gradients based on whether the phenotype tolerates the local environment. Second, it estimates pairwise competitive interactions as a function of multidimensional trait differences between species and determines which trait combinations produce the most competitive phenotypes. We demonstrate that our combined approach more than doubles the explained variance of species covers in a wetland community compared to the model of abiotic tolerances alone. Trait-based integration of competitive interactions and abiotic filtering improves our ability to predict species abundances across space, bringing us closer to more accurate predictions of biodiversity structure in a changing world.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/LoicChr/Banquo

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 13, 2021.
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Predictions of biodiversity are improved by integrating trait-based competition with abiotic filtering
Loïc Chalmandrier, Daniel B. Stouffer, Adam S. T. Purcell, William G. Lee, Andrew J. Tanentzap, Daniel C. Laughlin
bioRxiv 2021.07.12.448750; doi: https://doi.org/10.1101/2021.07.12.448750
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Predictions of biodiversity are improved by integrating trait-based competition with abiotic filtering
Loïc Chalmandrier, Daniel B. Stouffer, Adam S. T. Purcell, William G. Lee, Andrew J. Tanentzap, Daniel C. Laughlin
bioRxiv 2021.07.12.448750; doi: https://doi.org/10.1101/2021.07.12.448750

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