DOI: 10.5061/dryad.c014p
title: Data from: Applying landscape genomic tools to forest management and restoration of Hawaiian koa (Acacia koa) in a changing environment

description: 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.
description: SNP calls for all
 samples in VCF format (before filtering)SNP call data for all
 samples across all Hawaiian islands, produced by Stacks in VCF format,
 before final filtering steps.KoaSNP_ALL.vcfSNP calls for island of Hawaii in VCF format (before filtering)SNP call data for samples from the island of Hawaii, produced by Stacks in VCF format, before final filtering steps.KoaSNP_Hawaii.vcfSNP calls for island of Hawaii, final in table formatSNP calls in tab-separated format with rows as individual samples and columns as loci as inferred from Stacks. These are the final data that were filtered such that the minor allele frequency is greater than 0.05 and there is no more than 30% missing data at a locus. This file contains both Acacia koa and A. koaia samples; the latter were removed prior to environmental association analyses.KoaSNP_Hawaii_maf5mis30.tsvSNP calls for all samples, final in table formatSNP calls in tab-separated format with rows as individual samples and columns as loci as inferred from Stacks. These are the final data that were filtered such that the minor allele frequency is greater than 0.05 and there is no more than 30% missing data at a locus. This file contains both Acacia koa and A. koaia samples.KoaSNP_ALL_maf5mis30.tsv