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

Abstract

Identifying and quantifying the importance of environmental variables in structuring population genetic variation can help inform management decisions for conservation, restoration, or reforestation purposes, in both 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.

Landscape genomics provides evidence of climate‐associated genetic variation in Mexican populations ofQuercus rugosa

“…For example, Fitzpatrick and Keller () found a graduate gradient in their GF models for P. balsamifera and Gugger et al. () found very strong spatial structure in Hawaii Island populations of Acacia koa , respectively. The strong spatial influence explains the similarity among GF models observed in the maps of Procrustes residuals.…”

“…For samples that produced final products with coloration, presumably due to unremoved secondary compounds, we repeated the extractions applying a prewash protocol (Gaddis, Zukin, Dieterich, Braker, & Sork, 2014;Li, Yang, Chen, Zhang, & Tang, 2007). Total genomic DNA was prepared for sequencing using an efficient restriction enzyme-based approach, genotyping by sequencing (GBS) (Elshire et al, 2011), which we have modified and used for other tree species in our lab (Gugger, Liang, Sork, Hodgskiss, & Wright, 2018). Briefly, DNA was digested with a restriction enzyme, common and unique barcoded adapters with overhangs complementary to the cut site were ligated to each sample, samples were pooled in equimolar ratios, and the pooled library was PCR-amplified and sent for Illumina sequencing.…”

Conservation of adaptive potential and functional diversity: integrating old and new approaches

“…For example, even closely related species inhabiting the same environments can show differences in genetic variation and adaptive potential at fine local scales (Lobo et al 2018), which should be accounted for in multi-species based conservation. Landscape genomics, combining phylogeographic patterns with detailed environmental data (Gugger et al 2018) also could aid in the restoration and preservation of either particular threatened species or larger communities (Montalvo et al 1997;Funk et al 2008), by informing practical decisions about what to preserve, how and over what geographic scales (McKay et al 2005). Relating genomic variation to critical phenotypic responses to environmental stress (Bustos-Salazar et al 2017;Vangestel et al 2018) can be used to inform selection of individuals to use for restoration or breeding programmes for sustainably harvested populations.…”

Guidelines for planning genomic assessment and monitoring of locally adaptive variation to inform species conservation

“…While appropriate source and recipient populations could be selected based on climatic and other ecological data (a “best guess” approach), such efforts would be better informed by knowledge of adaptive variation and climatic drivers of local adaptation. Assisted gene flow is expected to be especially beneficial in dispersal‐limited, long‐lived species such as trees (Aitken & Bemmels, 2016; Gugger, Liang, Sork, Hodgskiss, & Wright, 2017; Steane et al., 2014). …”