The genetic legacy of 50 years of desert bighorn sheep translocations. (16th October 2018) - Jahner, Joshua P.
Abstract: Conservation biologists have increasingly used translocations to mitigate population declines and restore locally extirpated populations. Genetic data can guide the selection of source populations for translocations and help evaluate restoration success. Bighorn sheep ( Ovis canadensis ) are a managed big game species that suffered widespread population extirpations across western North America throughout the early 1900s. Subsequent translocation programs have successfully re‐established many formally extirpated bighorn herds, but most of these programs pre‐date genetically informed management practices. The state of Nevada presents a particularly well‐documented case of decline followed by restoration of extirpated herds. Desert bighorn sheep ( O. c. nelsoni ) populations declined to less than 3, 000 individuals restricted to remnant herds in the Mojave Desert and a few locations in the Great Basin Desert. Beginning in 1968, the Nevada Department of Wildlife translocated ~2, 000 individuals from remnant populations to restore previously extirpated areas, possibly establishing herds with mixed ancestries. Here, we examined genetic diversity and structure among remnant herds and the genetic consequences of translocation from these herds using a genotyping‐by‐sequencing approach to genotype 17, 095 loci in 303 desert bighorn sheep. We found a signal of population genetic structure among remnant Mojave Desert populations, even across geographically proximate mountain ranges. Further, we found evidence of a genetically distinct, potential relict herd from a previously hypothesized Great Basin lineage of desert bighorn sheep. The genetic structure of source herds was clearly reflected in translocated populations. In most cases, herds retained genetic evidence of multiple translocation events and subsequent admixture when founded from multiple remnant source herds. Our results add to a growing literature on how population genomic data can be used to guide and monitor restoration programs.