Genomics-Enabled Mixed-Stock Analysis Uncovers Intraspecific Migratory Complexity and Detects Unsampled Populations in a Harvested Fish.

Abstract

The contributions of distinct populations to annual harvests provide key insights to conservation, especially in migratory species that return to specific reproductive areas. In this context, genetic stock identification (GSI) requires reference samples from source populations to assign harvested individuals, yet sampling might be challenging as reproductive areas could be remote and/or unknown. To investigate intraspecific variation in walleye (Sander vitreus) populations harvested in two large lakes in northern Quebec, we used genotyping-by-sequencing data to develop a panel of 303 filtered single-nucleotide polymorphisms. We then genotyped 1465 fish and assessed individual migration distances from GPS coordinates of capture locations. Samples were assigned to a source population using two methods, one requiring allele frequencies of known populations (RUBIAS) and the other without prior knowledge (STRUCTURE). Individual assignments to a known population reached 93% consistency between both methods in the main lake where we identified all five major source populations. However, the analyses also revealed up to three small unsampled populations. Furthermore, populations were characterised by large differences in average migration distance. In contrast, assignment consistency reached 99% in the neighbouring lake and walleye were assigned with high confidence to two populations having a similar distribution throughout the lake. The complex population structure and migration patterns in the main lake suggest a more heterogeneous habitat and thus, greater potential for local adaptation. This study highlights how combining analytical approaches can inform the robustness of GSI results in a given system and detect intraspecific diversity and complexity relevant for conservation.