Genetically informed ecological niche models improve climate change predictions

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

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
JournalGlobal Change Biology
DOIs
StateAccepted/In press - 2016

Fingerprint

Climate Change
Ecotype
Climate change
climate change
Genetic Structures
prediction
Climate
local adaptation
ecotype
Salicaceae
niche
Population
Populus
Genetic Models
Population Genetics
garden
Genetic Markers
Soil
niche breadth
genetic marker

Keywords

  • Climate change
  • Ecological niche models
  • Ecotypes
  • Foundation species
  • Genetic differentiation
  • Local adaptation
  • Niche divergence
  • Species distributions

ASJC Scopus subject areas

  • Global and Planetary Change
  • Environmental Chemistry
  • Medicine(all)
  • Ecology
  • Environmental Science(all)

Cite this

Genetically informed ecological niche models improve climate change predictions. / Ikeda, Dana H.; Max, Tamara L.; Allan, Gerard J; Lau, Matthew K.; Shuster, Stephen M; Whitham, Thomas G.

In: Global Change Biology, 2016.

Research output: Contribution to journalArticle

@article{583723f808b34936a012893095aaa0ae,
title = "Genetically informed ecological niche models improve climate change predictions",
abstract = "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.",
keywords = "Climate change, Ecological niche models, Ecotypes, Foundation species, Genetic differentiation, Local adaptation, Niche divergence, Species distributions",
author = "Ikeda, {Dana H.} and Max, {Tamara L.} and Allan, {Gerard J} and Lau, {Matthew K.} and Shuster, {Stephen M} and Whitham, {Thomas G}",
year = "2016",
doi = "10.1111/gcb.13470",
language = "English (US)",
journal = "Global Change Biology",
issn = "1354-1013",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Genetically informed ecological niche models improve climate change predictions

AU - Ikeda, Dana H.

AU - Max, Tamara L.

AU - Allan, Gerard J

AU - Lau, Matthew K.

AU - Shuster, Stephen M

AU - Whitham, Thomas G

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Climate change

KW - Ecological niche models

KW - Ecotypes

KW - Foundation species

KW - Genetic differentiation

KW - Local adaptation

KW - Niche divergence

KW - Species distributions

UR - http://www.scopus.com/inward/record.url?scp=84987660706&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84987660706&partnerID=8YFLogxK

U2 - 10.1111/gcb.13470

DO - 10.1111/gcb.13470

M3 - Article

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

ER -