Move or adapt to changing climate? These chipmunks have had to do both

Tamias alpinus (Flickr: Eric Sonstroem)

Climate change threatens to land many, many species in conditions for which they’re not adapted — too warm, too dry, too stormy, too flood-prone — and traditionally the ways that living things might respond to this are framed as a choice between moving to more suitable habitat elsewhere, adapting to the new conditions in the current habitat, or dying out. These are a false choice, of course; it’s possible to move and adapt, and it’s possible that even doing both won’t be enough to avoid extinction. A new study of one rare chipmunk in the Sierra Nevada mountains pinpoints exactly such a case.

More than a decade ago now, Craig Mortiz led a project that compared historical field notes to contemporary distributions of small mammals in Yosemite National Park to point out species that have moved to new ranges or reduced the area they occupy over the course of a warming 20th century. The new study puts a genomic spin on that work, comparing population samples of chipmunks taken in the 2000s to museum specimens from the 1910s.

The authors, led by Ke Bi and Tyler Linderoth, used sequence capture to generate 9.4Mb of gene sequences for historic and contemporary samples of the alpine chipmunk, Tamias alpinus, in Yosemite National Park. Of the species in the 2008 study, Tamias alpinus had seen the one of the most dramatic contractions of its range, moving more than 600 meters (about 2000 feet) higher in elevation. For comparison, the authors also sequenced historic and contemporary samples of the lodgepole pine chipmunk, Tamias speciosus, which has maintained much more of its historic range in Yosemite; and historic/contemporary samples of T. alpinus from farther south in the Sierra Nevada mountains. They report very good performance of the sequence capture array, even given that more than half their material was dried museum specimens — over 90% of cleaned sequence reads aligned to targeted regions. The sequencing error rate was, however, about 4x higher in the historic samples.

Bi, Linderoth et al. first compared genetic variation and structure in the historic and contemporary datasets, which revealed substantial changes in the Yosemite alpine chipmunks. The time between sampling periods saw a substantial increase in global FST, from 0.03 to almost 0.06, and while a clustering analysis found two major subpopulations in the historic sample, it found six in the contemporary one. So even as the Yosemite alpine chipmunks’ range has contracted, the population has become more fragmented. In comparison, the Yosemite T. speciosus and southern T. alpinus maintained population structure largely similar to the early 20th century.

To formally analyze change in the chipmunk populations over time, the authors used approximate Bayesian computation to parameterize demographic models for each of the three populations they’d sequenced. For all three they found reduced migration rates among sites, but this was most striking in the Yosemite alpine chipmunks. There was not actually any signal of reduced effective population size for T. alpinus in Yosemite; and indeed globally that population hadn’t lost much diversity over time. The authors suggest that, if the major effect of alpine chipmunks’ range shifts has been population fragmentation rather than loss of diversity, assisted gene flow to reduce populations’ isolation might make sense as a conservation strategy.

Position of the verified selection candidates (A) within the overall distribution of historic-contemporary allele frequency difference (Fst) and (B) in the 2D site frequency spectrum (from Bi et al. 2019, Figure 4)

Finally, to identify SNPs that had undergone selection during the time between sampling periods, Bi et al. used outFLANK, which provides a suitably strict approach to finding loci that differ in frequency between two populations — in this case, the historic and contemporary samples —  given potentially confounding demographic differences. This found no SNPs showing sufficiently big frequency changes to be under selection in T. speciosus or the southern Sierra T. alpinus, but it did find a handful of sites in the T. alpinus data at which one allele had become so much more common that selection was likely. All of these sites were located in the gene coding for Arachidonate 15-Lipoxygenase, which is involved in immune inflammatory response and hypoxya.

The authors propose a strikingly direct link between climate change and selection affecting this gene: snowpack. Alpine chipmunks hibernate under snowpack, which provides insulation and shelter — but in Yosemite, winter snowpack has been steadily decreasing since the early 20th century. Shallower snowpack means hibernating chipmunks are more easily roused, which is physiologically stressful, particularly if it happens repeatedly. (This is also thought to be how white-nose fungus hurts hibernating bats.)

This study is really a template for what can be done with the right genomic resources (an annotated reference genome, a well-designed sequence capture array) and good population-level sampling in museum collections. I imagine that a pooled sequencing approach could have achieved a lot of the same results with somewhat simpler logistics; though presumably the authors have more work in mind for the individual-level sequences they’ve generated. Also, of course, as someone who works primarily in plants, I’m always keener on systems where you can directly study the historic population (say, though a seed bank). Still, there’s good biological insight to be drawn from genomic data in museum-based studies like this one, and the entire planet is covered in populations that have been adapting or migrating or both to cope with human activity. “Temporal genomics” have a lot of potential to show us what change we’ve already caused.

Reference

Bi K, T Linderoth, S Singhal, D Vanderpool, JL Patton, R Nielsen, C Mortiz, and JM Good. 2019. Temporal genomic contrasts reveal rapid evolutionary responses in an alpine mammal during recent climate change. PLoS Genetics 15(5): 1008119. doi: 10.1371/journal.pgen.1008119

Moritz C, JL Patton, CJ Conroy, JL Parra, GC White, and SR Beissinger. 2008. Impact of a century of climate change on small-mammal communities in Yosemite National Park, USA. Science 322: 261-264. doi: 10.1126/science.1163428

Whitlock MC and KE Lotterhos. 2015. Reliable detection of loci responsible for local adaptation: Inference of a null model through trimming the distribution of FST. The American Naturalist. 186(S1):S24-S36. doi: 10.1086/682949

About Jeremy Yoder

Jeremy Yoder is an Assistant Professor of Biology at California State University, Northridge. He also blogs at Denim and Tweed, and tweets under the handle @jbyoder.
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