Data from: Applying landscape genomic tools to forest management and restoration of Hawaiian koa (Acacia koa) in a changing environment

Identifying and quantifying the importance of environmental variables in
structuring population genetic variation can help inform management
decisions for conservation, restoration, or reforestation purposes, both
in current and future environmental conditions. Landscape genomics offers
a powerful approach for understanding the environmental factors that
currently associate with genetic variation, and given those associations,
where populations may be most vulnerable under future environmental
change. Here, we applied genotyping by sequencing to generate over 11,000
single-nucleotide polymorphisms from 311 trees and then used nonlinear,
multivariate environmental association methods to examine spatial genetic
structure and its association with environmental variation in an
ecologically and economically important tree species endemic to Hawaii,
Acacia koa. Admixture and principal components analyses showed that trees
from different islands are genetically distinct in general, with the
exception of some genotypes that match other islands, likely as the result
of recent translocations. Gradient forest and generalized dissimilarity
models both revealed a strong association between genetic structure and
mean annual rainfall. Utilizing a model for projected future climate on
the island of Hawaii, we show that predicted changes in rainfall patterns
may result in genetic offset, such that trees no longer may be genetically
matched to their environment. These findings indicate that knowledge of
current and future rainfall gradients can provide valuable information for
the conservation of existing populations and also help refine seed
transfer guidelines for reforestation or replanting of koa throughout the
state.