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Acknowledging uncertainty in evolutionary reconstructions of ecological niches [Image: see text]

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; an...

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Detalles Bibliográficos
Autores principales: Owens, Hannah L., Ribeiro, Vivian, Saupe, Erin E., Cobos, Marlon E., Hosner, Peter A., Cooper, Jacob C., Samy, Abdallah M., Barve, Vijay, Barve, Narayani, Muñoz‐R., Carlos J., Peterson, A. Townsend
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391559/
https://www.ncbi.nlm.nih.gov/pubmed/32760505
http://dx.doi.org/10.1002/ece3.6359
Descripción
Sumario:Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol.