Data and code from: Evaluating genomic offset predictions in a forest tree with high population genetic structure

Genomic offset models are increasingly popular tools for identifying
populations at risk of maladaptation under climate change. These models
estimate the extent of genetic change required for populations to remain
adapted under future climate change scenarios, but face strong limitations
and still lack broad empirical testing. Using 9,817 single nucleotide
polymorphisms (SNPs) genotyped in 454 trees from 34 populations of
maritime pine, a species with a marked population genetic structure, we
found substantial variability across genomic offset predictions from
different methods, SNP sets, and general circulation models. Using five
common gardens, we mostly found positive associations between genomic
offset predictions and mortality, as expected. However, contrary to our
expectations, we observed very few negative monotonic associations between
genomic offset predictions and height. Higher mortality rates were also
observed in national forest inventory plots with high genomic offset, but
only for some methods and SNP sets. The differing genomic offset patterns
produced by the best-validated methods across the maritime pine range
hindered drawing definitive conclusions for the species. Our study
demonstrates the imperative of employing different methods and validating
genomic offset predictions with independent data sources before using them
as reliable metrics to inform conservation or management.