DOI: 10.1111/gcb.13470
论文题名: Genetically informed ecological niche models improve climate change predictions
作者: Ikeda D.H. ; Max T.L. ; Allan G.J. ; Lau M.K. ; Shuster S.M. ; Whitham T.G.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2017
卷: 23, 期: 1 起始页码: 164
结束页码: 176
语种: 英语
英文关键词: climate change
; ecological niche models
; ecotypes
; foundation species
; genetic differentiation
; local adaptation
; niche divergence
; species distributions
Scopus关键词: adaptation
; climate change
; climate prediction
; ecotype
; environmental change
; genetic differentiation
; genetic structure
; genetic variation
; geographical distribution
; modeling
; niche
; population distribution
; population genetics
; Populus fremontii
; Salicaceae
英文摘要: 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 the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change. © 2016 John Wiley & Sons Ltd 资助项目: We thank the Cottonwood Ecology Group for their valuable feedback, in addition to GA O'Neill, AV Whipple, HM Bothwell, HF Cooper and BJ Butterfield. P Heinrich provided technical assistance. We also thank two anonymous reviewers for their valuable suggestions and comments. This research was supported by an NSF IGERT fellowship, NSF FIBR grant DEB-0425908, NSF MacroSystems grant DEB-1340852 and NSF DBI-1126840 for establishing the Southwest Experimental Garden Array.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/61163
Appears in Collections: 影响、适应和脆弱性
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作者单位: Department of Biological Science, Northern Arizona University, Flagstaff, AZ, United States; Merriam-Powell Center for Environmental Research, Northern Arizona University, Flagstaff, AZ, United States; Division of Biological Sciences, University of Montana, Missoula, MT, United States; Harvard Forest, Harvard University, Petersham, MA, United States
Recommended Citation:
Ikeda D.H.,Max T.L.,Allan G.J.,et al. Genetically informed ecological niche models improve climate change predictions[J]. Global Change Biology,2017-01-01,23(1)