Demographic modelling reveals a history of divergence with gene flow for a glacially tied stonefly in a changing post-Pleistocene landscape

• Published in: Journal of biogeography Vol. 45; no. 2; pp. 304 - 317
• Main Authors: Hotaling, Scott, Muhlfeld, Clint C., Giersch, J. Joseph, Ali, Omar A., Jordan, Steve, Miller, Michael R., Luikart, Gordon, Weisrock, David W.
• Format: Journal Article
• Language: English
• Published: Oxford John Wiley & Sons Ltd 01.02.2018; Wiley Subscription Services, Inc
• Subjects: Alpine environments; alpine stream ecology; Aquatic insects; Biological evolution; Climate change; Clusters; coalescent; conservation genetics; Demographics; Deoxyribonucleic acid; Divergence; Divergence with and without gene flow; DNA; DNA sequencing; Environmental changes; Evolutionary genetics; Filtration; Gene flow; Gene polymorphism; Genetic diversity; Genetic structure; Genomes; Geography; Glacial periods; Glaciation; Glacier National Park; Glaciers; Glaciohydrology; Glaciology; global climate change; Global warming; Ice accumulation; Ice sheets; Landscape; Lednia tumana; Missing data; Mountains; National parks; Parameter estimation; Parameter identification; phylogeography; Pleistocene; Polymorphism; Population; Population genetics; population genomics; Population structure; Populations; Recession; Scale (ratio); Single-nucleotide polymorphism; Species; Streams; Taxa
• ISSN: 0305-0270; 1365-2699
• DOI: 10.1111/jbi.13125

Aim: Climate warming is causing extensive loss of glaciers in mountainous regions, yet our understanding of how glacial recession influences evolutionary processes and genetic diversity is limited. Linking genetic structure with the influences shaping it can improve understanding of how species respond to environmental change. Here, we used genome-scale data and demographic modelling to resolve the evolutionary history of Lednia tumana, a rare, aquatic insect endemic to alpine streams. We also employed a range of widely used data filtering approaches to quantify how they influenced population structure results. Location: Alpine streams in the Rocky Mountains of Glacier National Park, Montana, USA. Taxon: Lednia tumana, a stonefly (Order Plecoptera) in the family Nemouridae. Methods: We generated single nucleotide polymorphism data through restriction-site associated DNA sequencing to assess contemporary patterns of genetic structure for 11 L. tumana populations. Using identified clusters, we assessed demographic history through model selection and parameter estimation in a coalescent framework. During population structure analyses, we filtered our data to assess the influence of singletons, missing data and total number of markers on results. Results: Contemporary patterns of population structure indicate that L. tumana exhibits a pattern of isolation-by-distance among populations within three genetic clusters that align with geography. Mean pairwise genetic differentiation (FST) among populations was 0.033. Coalescent-based demographic modelling supported divergence with gene flow among genetic clusters since the end of the Pleistocene (∼13-17 kya), likely reflecting the south-to-north recession of ice sheets that accumulated during the Wisconsin glaciation. Main conclusions: We identified a link between glacial retreat, evolutionary history and patterns of genetic diversity for a range-restricted stonefly imperiled by climate change. This finding included a history of divergence with gene flow, an unexpected conclusion for a mountaintop species. Beyond L. tumana, this study demonstrates the complexity of assessing genetic structure for weakly differentiated species, shows the degree to which rare alleles and missing data may influence results, and highlights the usefulness of genome-scale data to extend population genetic inquiry in non-model species.