As the world burns and we barrel heedlessly into an ever-smaller and uglier future, predicting how species will respond to climate change will be critical for conservation planning. Intuition suggests most organisms will shift their ranges up in latitude or elevation in an attempt to track their thermal niche and its ecological covariates. Yet because other abiotic and biotic factors may be decoupled from mean temperature — e.g., precipitation, the presence of competitors, or habitat modification — “downslope” range shifts have also been observed. Moreover (and to the surprise of no one reading this website), the occurrence or severity of range shifts can be mediated by evolutionary responses. As a result, the amount and character of genetic variation in regions of the genome associated with climatic variables can help predict whether species will adapt quickly enough to track global warming.
In a paper published this week in Science, Rachel Bay and coauthors explored the link between adaptive potential and documented population trends in a migratory songbird (Yellow Warbler Setophaga petechia; hereafter “YEWA”). Using genome-wide SNP data from 229 individuals and 21 populations spanning YEWA’s breeding range, Bay et al. first asked if geographic and environmental distance predicted genetic variation. While variation was largely shaped through isolation-by-distance, a machine-learning approach found that smaller subsets of the genome are explained by environment, and that significant differences in environmentally-associated genetic variation are found across the species’ range.
With these subsets, the team next calculated the magnitude of allele frequency shift each population would require to keep pace with modeled genotype-environment relationships under future climate change scenarios — a metric they coin “genomic vulnerability.” If recent climate change is already affecting YEWA populations, they hypothesized, those with the highest genomic vulnerability will have suffered the most. Thanks to data from the North American Breeding Bird Surveys, they were able to confirm that this is indeed the case: a given population’s genomic vulnerability was a significant predictor of population decline. Because this is more empirical confirmation of a hot topic in global change biology, it’s a point that bears repeating: warbler populations without the raw genetic material to adapt to climate change are already facing
As you might expect, however, the functional link between this genomic vulnerability and real-world selective pressures is less clear. Bay et al. scanned for associations between genotype and climate with their data, finding that (among others) a SNP on chromosome 5 was strongly tied to their top three environmental variables. The SNP in question, located upstream of genes associated with dispersal and migratory behavior in birds (DRD4 and DEAF1), was most prevalent in wet areas with low seasonality. Though speculative, it’s not a huge leap to conclude this means that maybe — just maybe! — low genomic vulnerability indicates a propensity to disperse to more resilient, welcoming climes.
Of course, as the authors themselves caution, the polygenic nature of climate change adaptation (and the complexity of the global climate system itself) limit much in the way of causal inference. Still, it’s hard not to view the concept of genomic vulnerabilty and the relative ease of measuring it as an important advance for a forward-looking conservation biology — and a rich source of hypotheses for molecular ecologists studying the many links between genes, adaptation, and a changing planet.
Battey, C.J., et al. In prep. Why montane Puerto Rican lizards are moving downhill while the climate warms.
Bay, R.A., et al. 2018. Genomic signals of selection predict climate-driven population declines in a migratory bird. Science. DOI: 10.1126/science.aan4380
Ellis, N., et al. 2012. Gradient forests: calculating importance gradients on physical predictors. Ecology. DOI: 10.1890/11-0252.1
Lenoir, J., et al. 2010. Going against the flow: potential mechanisms for unexpected downslope range shifts in a warming climate. Ecography. DOI: 10.1111/j.1600-0587.2010.06279.x