How useful is genomic data for predicting maladaptation to future climate?

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Description:

Methods using genomic information to forecast potential population maladaptation to climate change or new environments are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods – Gradient Forests (GF_offset) and the Risk Of Non-Adaptedness (RONA) – using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against two-year and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GF_offset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use.

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Auteur(s) :

Lind, Brandon

Lind, Brandon

University of British Columbia

, Candido-Ribeiro, Rafael

Candido-Ribeiro, Rafael

University of British Columbia

, Singh, Pooja

Singh, Pooja

University of Calgary

, Lu, Mengmeng

Lu, Mengmeng

University of Calgary

, Obreht Vidakovic, Dragana

Obreht Vidakovic, Dragana

University of British Columbia

, Booker, Tom

Booker, Tom

University of British Columbia

, Whitlock, Michael

Whitlock, Michael

University of British Columbia

, Yeaman, Sam

Yeaman, Sam

University of Calgary

, Isabel, Nathalie

Isabel, Nathalie

Université Laval

et Aitken, Sally

Aitken, Sally

University of British Columbia

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Dépôt source:

Dryad

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URL:

https://doi.org/10.5061/dryad.sxksn039h

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Date de publication:

2024-04-17

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Mots-clés (en):

Conifers, Douglas-fir, jack pine, banksiana, menziesii, et genomic offset

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Citation selon les normes APA:

How useful is genomic data for predicting maladaptation to future climate? (2024). [Data set]. Dryad. https://doi.org/10.5061/dryad.sxksn039h

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