Using Landscape Genomics to Conserve Adaptive Capacity: A Case Study with a Southern Appalachian Salamander
Landscape genomics is an emerging field that investigates how environmental features drive patterns of neutral and adaptive genetic variation across landscapes. Importantly, landscape genomics can provide insight into the adaptive potential of wild populations of non-model species, since these analyses do not require prior genomic information or the use of manipulative experiments such as reciprocal transplants. However, a fundamental challenge in landscape genomics is detecting genetic markers under selection from large genomic data sets. This analytical step is particularly important since partitioning these data into neutral and adaptive components of genetic diversity provides the information upon which management decisions are based.
Difficulties with the partitioning step include distinguishing neutral demographic signals from signals of selection, detecting selection across heterogeneous landscapes, and detecting signals of selection that are derived from multilocus adaptive processes. To address these issues, I used two different sets of landscape genetic simulations to test a suite of genotype-environment association (GEA) analyses across a range of landscape heterogeneities, selection strengths, dispersal abilities, demographic histories, sample sizes, sampling designs, and genetic architectures. I found that multivariate GEA methods showed a superior combination of low false positive and high true positive rates across simulation scenarios, providing a powerful tool for investigating the genetic basis of local adaptation and improving management actions.
I then applied a multivariate GEA approach to a reduced representation genomic data set for Weller's salamander (Plethodon welleri). This endemic, fully terrestrial, forest-dwelling salamander is a species of conservation concern across its small range in the Southern Appalachian Mountains. Its restriction to mountaintop habitats makes it particularly vulnerable to ongoing habitat fragmentation and climate change. I developed and illustrated the use of an “adaptive dissimilarity” index to characterize the scope of adaptive variation across the Weller’s salamander range. In combination with other metrics including neutral genetic variation, population differentiation, and effective population size, I addressed a series of conservation scenarios that were improved by the explicit consideration of differences in adaptive genetic variation among populations. These scenarios included: (1) site prioritization to ensure evolutionary resiliency across the species range; (2) genetic rescue to increase genetic diversity and population fitness while minimizing the risk of outbreeding depression; and (3) assisted gene flow to maximize adaptive potential in response to rapid climate change. These analyses are helping us better understand the capacity of species to adapt to changing conditions and what management actions will be most effective to conserve biodiversity under global change. These efforts must be part of the broader effort to stem the biodiversity crisis by conserving not just genetic diversity, but also the ecological and evolutionary processes that sustain it.
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