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Journal article

Reconstructing ecological niche evolution when niches are incompletely characterized

Abstract:
Evolutionary dynamics of abiotic ecological niches across phylogenetic history can shed light on large-scale biogeographic patterns, macroevolutionary rate shifts, and the relative ability of lineages to respond to global change. An unresolved question is how best to represent and reconstruct evolution of these complex traits at coarse spatial scales through time. Studies have approached this question by integrating phylogenetic comparative methods with niche estimates inferred from correlative and other models. However, methods for estimating niches often produce incomplete characterizations, as they are inferred from present-day distributions that may be limited in full expression of the fundamental ecological niche by biotic interactions, dispersal limitations, and the existing set of environmental conditions. Here, we test whether incomplete niche characterizations inherent in most estimates of species’ niches bias phylogenetic reconstructions of niche evolution, using simulations of virtual species with known niches. Results establish that incompletely-characterized niches inflate estimates of evolutionary change and lead to error in ancestral state reconstructions. Our analyses also provide a potential mechanism to explain the frequent observation that maximum thermal tolerances are more conserved than minimum thermal tolerances: populations and species experience more spatial variation in minimum temperature than in maximum temperature across their distributions, and consequently may experience stronger diversifying selection for cold tolerance.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/sysbio/syx084

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Earth Sciences
Oxford college:
St Hugh's College
Role:
Author


More from this funder
Funding agency for:
Saupe, E
Grant:
G0601617


Publisher:
Oxford University Press
Journal:
Systematic Biology More from this journal
Volume:
67
Issue:
3
Pages:
428-438
Publication date:
2017-10-27
Acceptance date:
2017-10-24
DOI:
EISSN:
1076-836X
ISSN:
1063-5157


Pubs id:
pubs:739243
UUID:
uuid:173ee443-61b9-46f4-8402-d1372fa8d1af
Local pid:
pubs:739243
Source identifiers:
739243
Deposit date:
2017-10-31

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