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Reconstructing Ecological Niche Evolution via Ancestral State Reconstruction with Uncertainty Incorporated
  • +8
  • Hannah Owens,
  • Vivian Ribeiro,
  • Erin Saupe,
  • Marlon E. Cobos,
  • Peter Hosner,
  • Jacob Cooper,
  • Abdallah Samy,
  • Vijay Barve,
  • Narayani Barve,
  • Carlos Muñoz,
  • A. Townsend Peterson
Hannah Owens
University of Copenhagen
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Vivian Ribeiro
Stockholm Environment Institute
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Erin Saupe
University of Oxford Department of Earth Sciences
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Marlon E. Cobos
University of Kansas
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Peter Hosner
University of Copenhagen
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Jacob Cooper
University of Chicago Committee on Evolutionary Biology
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Abdallah Samy
Ain Shams University Faculty of Science
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Vijay Barve
University of Florida
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Narayani Barve
University of Florida
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Carlos Muñoz
UNAM
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A. Townsend Peterson
University of Kansas
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Abstract

Study of species’ ecological niches through evolutionary history can elucidate speciation mechanisms, yet current comparative phylogenetic methods consistently overestimate niche evolution. Here we propose a method by which to characterize species’ fundamental ecological niches for comparative phylogenetic analysis using a bin-based approach that incorporates uncertainty in niche estimates. Simulation analysis using a traditional characterization method (median value calculated from species’ known occurrences) estimated a significantly higher rate of niche evolution than using our proposed method, and differences in rate estimates were consistent regardless of the number of simulated taxa in a phylogeny. We also demonstrate how to perform ancestral state reconstructions under the new coding system; reconstructions are performed for each bin individually, and ancestral fundamental niches inferred by smoothing each node’s reconstructions across all bins. Finally, we provide a worked empirical example of our method, investigating ecological niche evolution in 34 species of New World orioles (Icterus spp.). Ecological niches were generally conserved in the group, and only a few lineages appear to have experienced niche reduction and specialization.

Peer review status:ACCEPTED

20 Jan 2020Submitted to Ecology and Evolution
21 Jan 2020Submission Checks Completed
21 Jan 2020Assigned to Editor
27 Jan 2020Review(s) Completed, Editorial Evaluation Pending
04 Feb 2020Editorial Decision: Revise Minor
06 Apr 20201st Revision Received
08 Apr 2020Submission Checks Completed
08 Apr 2020Assigned to Editor
08 Apr 2020Review(s) Completed, Editorial Evaluation Pending
22 Apr 2020Editorial Decision: Accept