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Genetically Informed Ecological Niche Models Improve Climate Change Predictions by Dana H. Ikeda; Tamara L. Max; Gerard J. Allan; Matthew K. Lau; Stephen M. Shuster; Thomas G. Whitham is a Environmental Science article available to read on EtoBox.

What is Genetically Informed Ecological Niche Models Improve Climate Change Predictions about?

We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on

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Author

Dana H. Ikeda; Tamara L. Max; Gerard J. Allan; Matthew K. Lau; Stephen M. Shuster; Thomas G. Whitham

Published

2016

Language

EN

Field

Environmental Science (Physical Sciences)