Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite Toad (Anaxyrus canorus)

An essential goal in conservation biology is delineating population units
that maximize the probability of species persisting into the future and
adapting to future environmental change. However, future-facing
conservation concerns are often addressed using retrospective patterns
that could be irrelevant. We recommend a novel landscape genomics
framework for delineating future “Geminate Evolutionary Units” (GEUs) in a
focal species: (1) identify loci under environmental selection, (2) model
and map adaptive conservation units that may spawn future lineages, (3)
forecast relative selection pressures on each future lineage, and (4)
estimate their fitness and likelihood of persistence using geo-genomic
simulations. Using this process, we delineated conservation units for the
Yosemite toad (Anaxyrus canorus), a U.S. federally threatened species that
is highly vulnerable to climate change. We used a genome-wide dataset,
redundancy analysis, and Bayesian association methods to identify 24
candidate loci responding to climatic selection (R2 ranging from
0.09–0.52), after controlling for demographic structure. Candidate loci
included genes such as MAP3K5, involved in cellular response to
environmental change. We then forecasted future genomic response to
climate change using the multivariate machine learning algorithm Gradient
Forests. Based on all available evidence, we found three GEUs in Yosemite
National Park, reflecting contrasting adaptive optima: YF-North (high
winter snowpack with moderate summer rainfall), YF-East (low to moderate
snowpack with high summer rainfall), and YF-Low-Elevation (low snowpack
and rainfall). Simulations under the RCP 8.5 climate change scenario
suggest that the species will decline by 29% over 90 years, but the highly
diverse YF-East lineage will be least impacted for two reasons: (1)
geographically it will be sheltered from the largest climatic selection
pressures, (2) its standing genetic diversity will promote a faster
adaptive response. Our approach provides a comprehensive strategy for
protecting imperiled non-model species with genomic data alone and has
wide applicability to other declining species.