Combining Harvest and Genetics to Estimate Reproduction in Wolves

• Published in: The Journal of Wildlife Management
• Main Authors: Clendenin, Heather R., Adams, Jennifer R., Ausband, David E., Hayden, James A., Hohenlohe, Paul A., Waits, Lisette P.
• Other Authors: Idaho Department of Fish and Game
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: Canis lupus; gray wolf
• Online Access: http://dx.doi.org/10.1002/jwmg.21820; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjwmg.21820; https://onlinelibrary.wiley.com/doi/pdf/10.1002/jwmg.21820; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/jwmg.21820

ABSTRACT Parameters of reproductive success are important to the management of wildlife populations. Genetic monitoring can be an effective approach for acquiring this important demographic information when traditional methods are unsuccessful, inefficient, or too expensive. This study demonstrates a novel application of genetic data opportunistically collected from harvested game to estimate a minimum annual count of breeding packs of gray wolves ( Canis lupus ) and to provide a coarse index of harvest vulnerability of young of the year (YOY) across packs. We used 18 microsatellite loci to genotype 98 gray wolf YOY from 2014 and 105 from 2015 harvested in Idaho, USA. Using this genotype data, we reconstructed sibling groups for each cohort using the program COLONY and treated full‐sibling litters as proxies for unique packs. In addition to evaluating our marker panel using simulations, we assessed the accuracy of empirical relationship assignments by adding YOY of known relationship from long‐term study packs to the dataset (27 individuals from 2014 and 61 from 2015) and tracking correctly reconstructed relationships. We varied COLONY input parameters to evaluate the power of relationship assignments under conditions that may be encountered when working with empirical data. We also compared COLONY's estimates of effective number of breeders based on sibship frequency to estimates based on a commonly used linkage‐disequilibrium method. All COLONY runs for both cohorts correctly identified the known sibling relationships. Among the other individuals, changes in the geographic clustering of putative siblings, probabilities of inclusion and exclusion for reconstructed sibling groups, and consistency of relationship assignments across COLONY runs suggested that marker number had a larger effect on accuracy than access to population‐level genetic data. Our estimates of breeding packs subjected to harvest within the state (52 for 2014 and 63 for 2015) differed from estimates reported by Idaho Department of Fish and ...