Literature DB >> 36196546

Large genetic divergence underpins cryptic local adaptation across ecological and evolutionary gradients.

Morgan M Sparks1, Joshua C Kraft2, Kliffi M S Blackstone1, Gordon G McNickle2,3, Mark R Christie1,4.   

Abstract

Environmentally covarying local adaptation is a form of cryptic local adaptation in which the covariance of the genetic and environmental effects on a phenotype obscures the divergence between locally adapted genotypes. Here, we systematically document the magnitude and drivers of the genetic effect (VG) for two forms of environmentally covarying local adaptation: counter- and cogradient variation. Using a hierarchical Bayesian meta-analysis, we calculated the overall effect size of VG as 1.05 and 2.13 for populations exhibiting countergradient or cogradient variation, respectively. These results indicate that the genetic contribution to phenotypic variation represents a 1.05 to 2.13 s.d. change in trait value between the most disparate populations depending on if populations are expressing counter- or cogradient variation. We also found that while there was substantial variance among abiotic and biotic covariates, the covariates with the largest mean effects were temperature (2.41) and gamete size (2.81). Our results demonstrate the pervasiveness and large genetic effects underlying environmentally covarying local adaptation in wild populations and highlight the importance of accounting for these effects in future studies.

Entities:  

Keywords:  cogradient variation; countergradient variation; environmentally covarying local adaptation; genetic assimilation; maladaptive plasticity; perfect compensation

Mesh:

Year:  2022        PMID: 36196546      PMCID: PMC9533007          DOI: 10.1098/rspb.2022.1472

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.530


  27 in total

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Authors:  G C Trussell; R J Etter
Journal:  Genetica       Date:  2001       Impact factor: 1.082

2.  Countergradient vs. cogradient variation in growth and diapause in a lichen-feeding moth, Eilema depressum (Lepidoptera: Arctiidae).

Authors:  Heikki Pöykkö; T Tammaru
Journal:  J Evol Biol       Date:  2010-04-23       Impact factor: 2.411

3.  Phenotypic similarity and the evolutionary significance of countergradient variation.

Authors:  D O Conover; E T Schultz
Journal:  Trends Ecol Evol       Date:  1995-06       Impact factor: 17.712

4.  THE MEASUREMENT OF SELECTION ON CORRELATED CHARACTERS.

Authors:  Russell Lande; Stevan J Arnold
Journal:  Evolution       Date:  1983-11       Impact factor: 3.694

5.  The genetic basis of altitudinal variation in the wood frog Rana sylvatica II. An experimental analysis of larval development.

Authors:  Keith A Berven
Journal:  Oecologia       Date:  1982-01       Impact factor: 3.225

6.  Bergmann and converse bergmann latitudinal clines in arthropods: two ends of a continuum?

Authors:  W U Blanckenhorn; M Demont
Journal:  Integr Comp Biol       Date:  2004-12       Impact factor: 3.326

7.  A novel analytical framework to quantify co-gradient and countergradient variation.

Authors:  Molly A Albecker; Geoffrey C Trussell; Katie E Lotterhos
Journal:  Ecol Lett       Date:  2022-05-11       Impact factor: 9.492

8.  Large genetic divergence underpins cryptic local adaptation across ecological and evolutionary gradients.

Authors:  Morgan M Sparks; Joshua C Kraft; Kliffi M S Blackstone; Gordon G McNickle; Mark R Christie
Journal:  Proc Biol Sci       Date:  2022-10-05       Impact factor: 5.530

9.  COUNTERGRADIENT SELECTION IN THE GREEN FROG, RANA CLAMITANS.

Authors:  Keith A Berven; Douglas E Gill; Sandra J Smith-Gill
Journal:  Evolution       Date:  1979-06       Impact factor: 3.694

10.  Microgeographic countergradient variation in the wood frog, Rana sylvatica.

Authors:  David K Skelly
Journal:  Evolution       Date:  2004-01       Impact factor: 3.694

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  1 in total

1.  Large genetic divergence underpins cryptic local adaptation across ecological and evolutionary gradients.

Authors:  Morgan M Sparks; Joshua C Kraft; Kliffi M S Blackstone; Gordon G McNickle; Mark R Christie
Journal:  Proc Biol Sci       Date:  2022-10-05       Impact factor: 5.530

  1 in total

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