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phyr: An R package for phylogenetic species-distribution modelling in ecological communities

View ORCID ProfileDaijiang Li, View ORCID ProfileRussell Dinnage, View ORCID ProfileLucas Nell, View ORCID ProfileMatthew R. Helmus, Anthony Ives
doi: https://doi.org/10.1101/2020.02.17.952317
Daijiang Li
1Department of Wildlife Ecology & Conservation, University of Florida, Gainesville, FL 32611
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Russell Dinnage
2Research School of Biology, Australian National University, Acton ACT 2601, Australia
3Institute for Applied Ecology, University of Canberra, Bruce ACT 2617, Australia
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Lucas Nell
4Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI 53706
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Matthew R. Helmus
5Integrative Ecology Lab, Center for Biodiversity, Department of Biology, Temple University, Philadelphia, PA 19122
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Anthony Ives
4Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI 53706
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Summary

  1. Model-based approaches are increasingly popular in ecological studies. A good example of this trend is the use of joint species distribution models to ask questions about ecological communities. However, most current applications of model-based methods do not include phylogenies despite the well-known importance of phylogenetic relationships in shaping species distributions and community composition. In part, this is due to lack of accessible tools allowing ecologists to fit phylogenetic species distribution models easily.

  2. To fill this gap, the R package phyr (pronounced fire) implements a suite of metrics, comparative methods and mixed models that use phylogenies to understand and predict community composition and other ecological and evolutionary phenomena. The phyr workhorse functions are implemented in C++ making all calculations and model estimations fast.

  3. phyr can fit a variety of models such as phylogenetic joint-species distribution models, spatiotemporal-phylogenetic autocorrelation models, and phylogenetic trait-based bipartite network models. phyr also estimates phylogenetically independent trait correlations with measurement error to test for adaptive syndromes and performs fast calculations of common alpha and beta phylogenetic diversity metrics. All phyr methods are united under Brownian motion or Ornstein-Uhlenbeck models of evolution and phylogenetic terms are modelled as phylogenetic covariance matrices.

  4. The functions and model formula syntax we propose in phyr serves as a simple and unified framework that ignites the use of phylogenies to address a variety of ecological questions.

Footnotes

  • Emails: daijianglee{at}gmail.com; r.dinnage{at}gmail.com; lucas{at}lucasnell.com; mrhelmus{at}temple.edu;

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 February 18, 2020.
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phyr: An R package for phylogenetic species-distribution modelling in ecological communities
Daijiang Li, Russell Dinnage, Lucas Nell, Matthew R. Helmus, Anthony Ives
bioRxiv 2020.02.17.952317; doi: https://doi.org/10.1101/2020.02.17.952317
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phyr: An R package for phylogenetic species-distribution modelling in ecological communities
Daijiang Li, Russell Dinnage, Lucas Nell, Matthew R. Helmus, Anthony Ives
bioRxiv 2020.02.17.952317; doi: https://doi.org/10.1101/2020.02.17.952317

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