Recent physical connections may explain weak genetic structure in western Alaskan chum salmon (<i>Oncorhynchus keta</i>) populations

Garvin, Michael R.; Kondzela, Christine M.; Martin, Patrick; Finney, Bruce P.; Guyon, Jeffrey R.; Templin, William D.; DeCovich, Nick; Gilk‐Baumer, Sara E.; Gharrett, Anthony J.

doi:10.1002/ece3.628

Cited by 15 publications

(26 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Populations from the lower Yukon, Kuskokwim, and Bristol Bay regions (Anvik River, Kogrukluk River, and Koktuli River) were least divergent, displaying pairwise F ST values < 0.01 for all population comparisons. The relatively small divergence we observed is consistent with other salmonids in the region (Olsen et al 2011;Garvin et al 2013) and is somewhat expected given the surrounding environment. Western Alaska is characterized by moisture-laden tundra and dynamic rivers that frequently change paths.…”

Section: Population Structuresupporting

confidence: 90%

Genotyping by sequencing resolves shallow population structure to inform conservation of Chinook salmon (Oncorhynchus tshawytscha)

Larson

Seeb

Everett

et al. 2014

Evolutionary Applications

Self Cite

189

213

View full text Add to dashboard Cite

Recent advances in population genomics have made it possible to detect previously unidentified structure, obtain more accurate estimates of demographic parameters, and explore adaptive divergence, potentially revolutionizing the way genetic data are used to manage wild populations. Here, we identified 10 944 single-nucleotide polymorphisms using restriction-site-associated DNA (RAD) sequencing to explore population structure, demography, and adaptive divergence in five populations of Chinook salmon (Oncorhynchus tshawytscha) from western Alaska. Patterns of population structure were similar to those of past studies, but our ability to assign individuals back to their region of origin was greatly improved (>90% accuracy for all populations). We also calculated effective size with and without removing physically linked loci identified from a linkage map, a novel method for nonmodel organisms. Estimates of effective size were generally above 1000 and were biased downward when physically linked loci were not removed. Outlier tests based on genetic differentiation identified 733 loci and three genomic regions under putative selection. These markers and genomic regions are excellent candidates for future research and can be used to create high-resolution panels for genetic monitoring and population assignment. This work demonstrates the utility of genomic data to inform conservation in highly exploited species with shallow population structure.

show abstract

Section: Population Structuresupporting

confidence: 90%

Genotyping by sequencing resolves shallow population structure to inform conservation of Chinook salmon (Oncorhynchus tshawytscha)

Larson

Seeb

Everett

et al. 2014

Evolutionary Applications

Self Cite

189

213

View full text Add to dashboard Cite

show abstract

“…) and chum salmon O. keta (Garvin et al . ). In terms of incorporating SNPs in GSI analyses, our results from scenarios that were intended to mimic these markers suggest that the estimation routines evaluated in our research exhibited similar levels of performance with respect to each other when compared to scenarios that mimicked other marker types.…”

Section: Discussionmentioning

confidence: 97%

Comparison of the accuracy and consistency of likelihood‐based estimation routines for genetic stock identification

et al. 2015

View full text Add to dashboard Cite

Summary1. Genetic stock identification (GSI) frequently is used to assess spawning/breeding population contributions to mixtures of individuals. Although multiple estimation routines are available for conducting GSI, their performance may vary depending on characteristics of assessed source populations and mixtures and of employed genetic markers. 2. We conducted simulations to compare performance of several likelihood-based GSI estimation routines. Estimation routines were implemented in SPAM, ONCOR and AD Model Builder (ADMB). Two ADMB routines were evaluated, one based on conditional maximum likelihood estimation (ADMB-MLE), similar to SPAM and ONCOR, and one based on conditional penalized maximum likelihood estimation (ADMB-PMLE). The simulations examined how performance varied by number of source populations, population divergence levels, number of evaluated loci, and source population and mixture sample sizes. Evaluations included scenarios with many loci with low levels of polymorphism for assessing performance when single nucleotide polymorphism (SNP) markers are incorporated in analyses. 3. Mixture sample size and source population genetic divergence accounted for most of the explained variability in simulation results. Overall, routines based on conditional maximum likelihood estimation (SPAM, ONCOR and ADMB-MLE) had similar levels of accuracy, including scenarios mimicking SNP markers, with SPAM having slightly better accuracy than ONCOR and ADMB-MLE. The accuracy of the ADMB-PMLE routine in many scenarios was noticeably poorer than the other routines, although in some instances accuracy of the ADMB-PMLE estimates approached the other routines with large mixture sample sizes. SPAM, ONCOR and ADMB-MLE also generally had similar levels of performance with respect to consistency, whereas ADMB-PMLE varied widely in consistency due in part to poor accuracy. 4. Because SPAM and ONCOR typically performed better than the ADMB-MLE routine, there appears to be little need for users to program their own likelihood-based estimation routines for standard GSI analyses, although for specialized applications (e.g. modelling contributions as functions of ecological or demographic features), it may be necessary for users to program their own routines. Given the performance of the ADMB-PMLE routine, additional research is needed to determine an appropriate configuration (e.g. penalty, optimization algorithm) for a penalized maximum likelihood GSI estimator.

show abstract

“…However, historic maps (U.S. Geological Survey, 1963) of the Chignik watershed indicate that Bearskin was formerly a tributary of the West Fork River. Channel migrations have occurred over the last several decades and Bearskin Creek now drains directly into Chignik Lake, highlighting the importance of historical geomorphology when interpreting contemporary population structure (Garvin et al 2013). Second, Hatchery Point Creek clusters between Black Lake, Chignik Lake and Westfork populations, although it drains directly into the middle of Chignik Lake.…”

Section: Discussionmentioning

confidence: 99%

Is isolation by adaptation driving genetic divergence among proximate Dolly Varden char populations?

Bond

Crane

Larson

et al. 2014

Ecology and Evolution

View full text Add to dashboard Cite

Numerous studies of population genetics in salmonids and other anadromous fishes have revealed that population structure is generally organized into geographic hierarchies (isolation by distance), but significant structure can exist in proximate populations due to varying selective pressures (isolation by adaptation). In Chignik Lakes, Alaska, anadromous Dolly Varden char (Salvelinus malma) spawn in nearly all accessible streams throughout the watershed, including those draining directly to an estuary, Chignik Lagoon, into larger rivers, and into lakes. Collections of Dolly Varden fry from 13 streams throughout the system revealed low levels of population structure among streams emptying into freshwater. However, much stronger genetic differentiation was detected between streams emptying into freshwater and streams flowing directly into estuarine environments. This fine-scale reproductive isolation without any physical barriers to migration is likely driven by differences in selection pressures across freshwater and estuarine environments. Estuary tributaries had fewer larger, older juveniles, suggesting an alternative life history of smolting and migration to the marine environment at a much smaller size than occurs in the other populations. Therefore, genetic data were consistent with a scenario where isolation by adaptation occurs between populations of Dolly Varden in the study system, and ecological data suggest that this isolation may partially be a result of a novel Dolly Varden life history of seawater tolerance at a smaller size than previously recognized.

show abstract

Recent physical connections may explain weak genetic structure in western Alaskan chum salmon (Oncorhynchus keta) populations

Cited by 15 publications

References 48 publications

Genotyping by sequencing resolves shallow population structure to inform conservation of Chinook salmon (Oncorhynchus tshawytscha)

Genotyping by sequencing resolves shallow population structure to inform conservation of Chinook salmon (Oncorhynchus tshawytscha)

Comparison of the accuracy and consistency of likelihood‐based estimation routines for genetic stock identification

Is isolation by adaptation driving genetic divergence among proximate Dolly Varden char populations?

Contact Info

Product

Resources

About