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Dryad

Data from: Harvest-associated size reductions and genomic changes within two generations in wild walleye populations

Cite this dataset

Bowles, Ella et al. (2020). Data from: Harvest-associated size reductions and genomic changes within two generations in wild walleye populations [Dataset]. Dryad. https://doi.org/10.5061/dryad.5tb2rbp1z

Abstract

The extent and rate of harvest-induced genetic changes in natural populations may impact population productivity, recovery and persistence. While there is substantial evidence for phenotypic changes in harvested fishes, knowledge of genetic change in the wild remains limited, as phenotypic and genetic data are seldom considered in tandem, and the number of generations needed for genetic changes to occur is not well understood. We quantified changes in size-at-age, sex-specific changes in body size, and genomic metrics in three harvested walleye (Sander vitreus) populations and a fourth reference population with low harvest levels over a 15-year period in Mistassini Lake, Quebec. We also collected Indigenous knowledge (IK) surrounding concerns about these populations over time. Using ~9000 SNPs, genomic metrics included changes in population structure, neutral genomic diversity, effective population size and signatures of selection. Indigenous knowledge revealed concerns about overall reductions in body size and number of fish caught. Smaller body size, smaller size-at-age, changing population structure (population differentiation within one river and homogenization between two others), and signatures of selection between historical and contemporary samples reflected coupled phenotypic and genomic change in the three harvested populations in both sexes, while no change occurred in the reference population. Sex-specific analyses revealed differences in both body size and genomic metrics but were inconclusive about whether one sex was disproportionately affected. Our results suggest that harvest-induced genetic changes may arise within 1-2.5 generations in long-lived wild fishes, demonstrating the need to investigate concerns about harvest-induced evolution quickly once they have been raised.

Methods

Walleye were captured via angling using the same lures and a combination of boats and shore fishing, from the same locations within rivers, for both historical and contemporary sampling (Table 1). From each walleye, we collected total and fork length (TL ± 1 mm), wet mass (± 50 g), sex (M, F, U (unknown, either spawned out or premature)) and a tissue sample for genetics; otoliths were collected from a random subsample. Opercular bones but not otoliths were collected for aging for historic samples (Table 1), and this was done before this study, for Dupont et al. (2007); 2015 and 2017 otoliths were aged at the Wisconsin Cooperative Fishery Unit, US Geological Service, University of Wisconsin, Stevens Point, USA. Otoliths were aged by two experienced readers; if they disagreed on an age they examined the structure together to agree upon one for that structure. No walleye were aged using both opercular bones and otoliths.

DNA was extracted using a modified Qiagen blood and tissue kit protocol (Qiagen Inc., Valencia, CA) (see Table 1 for sample sizes) and was sequenced using individual-based genotyping-by-sequencing (GBS). Libraries for Ion Proton GBS were prepared using the procedure described by Masher et al. (2013) at IBIS, Université Laval, Québec, Canada, with modifications described in Abed et al. (2018). Single-nucleotide polymorphisms (SNPs) were determined from raw sequence reads using the stacks pipeline v1.45 (Catchen et al. 2013), and de novo sequence alignment. 

Usage notes

For genomic data:

r12d files were made with a population map specifying each population and year separately, and includes outlier loci.

r12g files were made with a population map specifying Icon-Perch as a single population, and exclude outlier loci.

For body size data:

The all data file was used for body size modeling, while only the age data was used for the bayesian size-at-age models.