Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study. (30th September 2019)

• Record Type: Journal Article
• Authors: Mahony, Colin R.; MacLachlan, Ian R.; Lind, Brandon M.; Yoder, Jeremy B.; Wang, Tongli; Aitken, Sally N.
• Is Part Of: Evolutionary applications. Volume 13:Number 1(2020)
• Page Start: 116
• Page End: 131
• Publication Date: 2019-09-30
• Subjects: assisted gene flow -- climate change adaptation -- ecological genetics -- genomic variation -- landscape genomics -- phenotypic variation; Evolution (Biology) -- Periodicals; Genetics -- Periodicals; Natural selection -- Periodicals; Ecology -- Periodicals; 576.8
• DOI: 10.1111/eva.12871
• Languages: English
• ISSNs: 1752-4571

Abstract

Abstract: We evaluate genomic data, relative to phenotypic and climatic data, as a basis for assisted gene flow and genetic conservation. Using a seedling common garden trial of 281 lodgepole pine ( Pinus contorta ) populations from across western Canada, we compare genomic data to phenotypic and climatic data to assess their effectiveness in characterizing the climatic drivers and spatial scale of local adaptation in this species. We find that phenotype‐associated loci are equivalent or slightly superior to climate data for describing local adaptation in seedling traits, but that climate data are superior to genomic data that have not been selected for phenotypic associations. We also find agreement between the climate variables associated with genomic variation and with 20‐year heights from a long‐term provenance trial, suggesting that genomic data may be a viable option for identifying climatic drivers of local adaptation where phenotypic data are unavailable. Genetic clines associated with the experimental traits occur at broad spatial scales, suggesting that standing variation of adaptive alleles for this and similar species does not require management at scales finer than those indicated by phenotypic data. This study demonstrates that genomic data are most useful when paired with phenotypic data, but can also fill some of the traditional roles of phenotypic data in management of species for which phenotypic trials are not feasible.