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Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modeling approach

View ORCID ProfileChristopher P. Weiss-Lehman, View ORCID ProfileChhaya M. Werner, View ORCID ProfileCatherine H. Bowler, View ORCID ProfileLauren M. Hallett, View ORCID ProfileMargaret M. Mayfield, View ORCID ProfileOscar Godoy, View ORCID ProfileLina Aoyama, View ORCID ProfileGyörgy Barabás, Chengjin Chu, View ORCID ProfileEmma Ladouceur, View ORCID ProfileLoralee Larios, View ORCID ProfileLauren G. Shoemaker
doi: https://doi.org/10.1101/2021.07.23.453227
Christopher P. Weiss-Lehman
1Botany Department, University of Wyoming, Laramie, Wyoming 82071 USA
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  • ORCID record for Christopher P. Weiss-Lehman
  • For correspondence: cweissle@uwyo.edu
Chhaya M. Werner
1Botany Department, University of Wyoming, Laramie, Wyoming 82071 USA
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Catherine H. Bowler
2School of Biological Sciences University of Queensland, Brisbane, QLD, 4072, Australia
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Lauren M. Hallett
3Biology Department, University of Oregon, Eugene, OR 97403, USA
4Environmental Studies Program, University of Oregon, Eugene, OR 97403, USA
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Margaret M. Mayfield
2School of Biological Sciences University of Queensland, Brisbane, QLD, 4072, Australia
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  • ORCID record for Margaret M. Mayfield
Oscar Godoy
5Departamento de Biología, Instituto Universitario de Investigación Marina (INMAR), Universidad de Cádiz, E-11510 Puerto Real, Spain
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Lina Aoyama
3Biology Department, University of Oregon, Eugene, OR 97403, USA
4Environmental Studies Program, University of Oregon, Eugene, OR 97403, USA
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György Barabás
6Division of Theoretical Biology, Dept. IFM, Linköping University, SE-58183 Linköping, Sweeden
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  • ORCID record for György Barabás
Chengjin Chu
7Department of Ecology, State Key Laboratory of Biocontrol and School of Life Sciences, Sun Yat-sen University, 510275 Guangzhou, Guangdong, China
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Emma Ladouceur
8German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena,Puschstraße 4, 04103 Leipzig, Germany
9Department of Physiological Diversity, Helmholtz Centre for Environmental Research -UFZ, Permoserstrasse 15, 04318 Leipzig, Germany
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Loralee Larios
10Department of Botany and Plant Sciences, University of Callifornia Riverside, Riverside, CA 92521
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Lauren G. Shoemaker
1Botany Department, University of Wyoming, Laramie, Wyoming 82071 USA
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1 Abstract

Modeling species interactions in diverse communities traditionally requires a prohibitively large number of species-interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity-inducing priors on non-linear species abundance models to determine which species-interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out-of-sample predictive accuracy and parameter recovery across different input sample sizes. We applied our method to a diverse empirical community, allowing us to disentangle the direct role of environmental gradients on species’ intrinsic growth rates from indirect effects via competitive interactions. We also identified a few neighboring species from the diverse community that had non-generic interactions with our focal species. This sparse modeling approach facilitates exploration of species-interactions in diverse communities while maintaining a manageable number of parameters.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Data accessibility statement: Upon acceptance, all data will be archived on Dryad and the data DOI will be included at the end of the article. Model code is available on GitHub, with the URL included in the manuscript. Upon acceptance, model code with be archived on Zenodo and the URL will be updated with the Zenodo link.

  • https://github.com/tpweiss06/SparseInteractions

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted July 26, 2021.
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Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modeling approach
Christopher P. Weiss-Lehman, Chhaya M. Werner, Catherine H. Bowler, Lauren M. Hallett, Margaret M. Mayfield, Oscar Godoy, Lina Aoyama, György Barabás, Chengjin Chu, Emma Ladouceur, Loralee Larios, Lauren G. Shoemaker
bioRxiv 2021.07.23.453227; doi: https://doi.org/10.1101/2021.07.23.453227
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Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modeling approach
Christopher P. Weiss-Lehman, Chhaya M. Werner, Catherine H. Bowler, Lauren M. Hallett, Margaret M. Mayfield, Oscar Godoy, Lina Aoyama, György Barabás, Chengjin Chu, Emma Ladouceur, Loralee Larios, Lauren G. Shoemaker
bioRxiv 2021.07.23.453227; doi: https://doi.org/10.1101/2021.07.23.453227

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