Assessing adaptive capacity in terrestrial salamanders threatened by climate change
Faced with climate change, organisms must adapt in place or move—or they go extinct. Relative to dispersal, adaptation in response to environmental change remains poorly understood. Fortunately the recent development of molecular techniques for detecting local adaptation in wild populations has made it easier to evaluate this response. These tools offer important benefits for conservation practice in a dynamic world, since conserving adaptive capacity and evolutionary potential can improve the capacity for species to persist under the synergistic effects of climate change and habitat fragmentation.
I am investigating the interaction of local adaptation and gene flow in two species of terrestrial salamanders (which lack lungs and breathe through their skin): Plethodon cinereus (top left, the red-backed salamander) and Plethodon welleri (bottom left, Weller's salamander, a species of conservation concern). Plethodontid salamanders have limited dispersal capabilities, narrow physiological tolerances, and are highly sensitive to changes in climate. In eastern North American forests, they are the dominant and most abundant vertebrate predators, where they play a fundamental role in ecosystem structure, function, and stability. These characteristics—environmental sensitivity and ecological importance—make them an excellent indicator taxon for climate change research.
My research quantifies how local adaptation and gene flow interact to affect the evolutionary potential of these species in fragmented and warming habitats. This work helps us better understand the capacity of species to adapt to climate change, and what actions will be most effective to conserve biodiversity under global change.
This is part of my current PhD research in collaboration with my advisor Dean Urban and committee members Tom Schultz (Duke Marine Lab), Jennifer Wernegreen (Duke Institute for Genome Sciences & Policy), and Rob Dunn (NC State University).
Detecting loci under selection using landscape genomics, ordination methods, and spatially explicit models
I am working with a group of colleagues to test the increasing number of statistical methods for detecting loci potentially under selection. Our focus is on their effectiveness in non-model species in a landscape genomic context.
We have a new pre-print testing multivariate and machine learning genotype-environment association (GEA) methods. These methods may be more effective at detecting important adaptive processes, such as selection on standing genetic variation, that result in weak, multilocus signatures.
We have a publication that investigates the role of landscape heterogeneity in generating patterns of local adaptation, and tests a suite of multivariate GEA methods.
Our previous paper combined spatial analyses with GEA methods, providing a powerful approach for identifying loci potentially under selection and explaining spatially complex interactions between species and their environment.
Projecting the impact of climate change on habitat availability for an arctic-alpine plant using ensemble species distribution modeling and statistical phylogeography
Species distribution models (SDMs) are commonly used to forecast
climate change impacts. These models, however, are subject to important assumptions and limitations. By integrating two independent but complementary methods, ensemble SDMs and statistical phylogeography, we addressed key assumptions and created robust assessments of climate change impacts on the arctic-alpine plant Rhodiola integrifolia, while improving the conservation value of these projections.
Integrating molecular approaches with spatial analyses has great potential to improve conservation decision-making. Molecular tools can support and improve current methods for understanding the vulnerability of species to climate change and provide additional data upon which to base conservation decisions, such as prioritizing the conservation of areas of high genetic diversity to build evolutionary resiliency within populations.
This research was part of my Master's degree thesis at the Huxley College of the Environment, Western Washington University, Bellingham, WA. I worked in collaboration with my advisor, Andy Bunn, and committee member Eric DeChaine, who conducted phylogeographic analyses.