Automated Author Profile

Kirk, Stephanie L

University of British Columbia

Current S-Index

2.8

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.4

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

65.4%

Average FAIR Score per dataset

Total Citations

1

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Detection of outlier loci and their utility for fisheries management

AbstractGenetics-based approaches have informed fisheries management for decades, yet remain challenging to implement within systems involving recently diverged stocks or where gene flow persists. In such cases, genetic markers exhibiting locus-specific (“outlier”) effects associated with divergent selection may provide promising alternatives to loci that reflect genome-wide (“neutral”) effects for guiding fisheries management. Okanagan Lake kokanee (Oncorhynchus nerka), a fishery of conservation concern, exhibits two sympatric ecotypes adapted to different reproductive environments, however, previous research demonstrated the limited utility of neutral microsatellites for assigning individuals. Here, we investigated the efficacy of an outlier-based approach to fisheries management by screening >11,000 expressed sequence tags for linked microsatellites and conducting genomic scans for kokanee sampled across seven spawning sites. We identified eight outliers among 52 polymorphic loci that detected ecotype-level divergence, whereas there was no evidence of divergence at neutral loci. Outlier loci exhibited the highest self-assignment accuracy to ecotype (92.1%), substantially outperforming 44 neutral loci (71.8%). Results were robust among-sampling years, with assignment and mixed composition estimates for individuals sampled in 2010 mirroring baseline results. Overall, outlier loci constitute promising alternatives for informing fisheries management involving recently diverged stocks, with potential applications for designating management units across a broad range of taxa.

Authors

  • Russello, Michael A ;
  • Kirk, Stephanie L ;
  • Frazer, Karen K ;
  • Askey, Paul J
0 Citations0 Mentions54% FAIR0.6 Dataset Index
10.5683/sp2/c3icamJanuary 2021

Data from: Detection of outlier loci and their utility for fisheries management (Version: 1)

Genetics-based approaches have informed fisheries management for decades, yet remain challenging to implement within systems involving recently diverged stocks or where gene flow persists. In such cases, genetic markers exhibiting locus-specific (“outlier”) effects associated with divergent selection may provide promising alternatives to loci that reflect genome-wide (“neutral”) effects for guiding fisheries management. Okanagan Lake kokanee (Oncorhynchus nerka), a fishery of conservation concern, exhibits two sympatric ecotypes adapted to different reproductive environments, however, previous research demonstrated the limited utility of neutral microsatellites for assigning individuals. Here, we investigated the efficacy of an outlier-based approach to fisheries management by screening >11,000 expressed sequence tags for linked microsatellites and conducting genomic scans for kokanee sampled across seven spawning sites. We identified eight outliers among 52 polymorphic loci that detected ecotype-level divergence, whereas there was no evidence of divergence at neutral loci. Outlier loci exhibited the highest self-assignment accuracy to ecotype (92.1%), substantially outperforming 44 neutral loci (71.8%). Results were robust among-sampling years, with assignment and mixed composition estimates for individuals sampled in 2010 mirroring baseline results. Overall, outlier loci constitute promising alternatives for informing fisheries management involving recently diverged stocks, with potential applications for designating management units across a broad range of taxa.

Authors

  • Russello, Michael A ;
  • Kirk, Stephanie L ;
  • Frazer, Karen K ;
  • Askey, Paul J
1 Citation0 Mentions77% FAIR2.2 Dataset Index
10.5061/dryad.5bk66August 2011