Long-distance dispersal, ice sheet dynamics and mountaintop isolation underlie the genetic structure of glacier ice worms

• Published in: Proceedings of the Royal Society B: Biological Sciences
• Main Authors: Hotaling, Scott, Shain, Daniel H., Lang, Shirley A., Bagley, Robin K., Tronstad, Lusha M., Weisrock, David W., Kelley, Joanna L.
• Format: Text
• Language: English
• Published: The Royal Society 2019
• Subjects: Evolution; Pacific; glacier; glaciers; Ice Sheet; Alaska
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599980/; http://www.ncbi.nlm.nih.gov/pubmed/31213183; https://doi.org/10.1098/rspb.2019.0983

Disentangling the contemporary and historical factors underlying the spatial distributions of species is a central goal of biogeography. For species with broad distributions but little capacity to actively disperse, disconnected geographical distributions highlight the potential influence of passive, long-distance dispersal (LDD) on their evolutionary histories. However, dispersal alone cannot completely account for the biogeography of any species, and other factors—e.g. habitat suitability, life history—must also be considered. North American ice worms (Mesenchytraeus solifugus) are ice-obligate annelids that inhabit coastal glaciers from Oregon to Alaska. Previous studies identified a complex biogeographic history for ice worms, with evidence for genetic isolation, unexpectedly close relationships among geographically disjunct lineages, and contemporary migration across large (e.g. greater than 1500 km) areas of unsuitable habitat. In this study, we analysed genome-scale sequence data for individuals from most of the known ice worm range. We found clear support for divergence between populations along the Pacific Coast and the inland flanks of the Coast Mountains (mean F(ST) = 0.60), likely precipitated by episodic ice sheet expansion and contraction during the Pleistocene. We also found support for LDD of ice worms from Alaska to Vancouver Island, perhaps mediated by migrating birds. Our results highlight the power of genomic data for disentangling complex biogeographic patterns, including the presence of LDD.