Data from: Noninvasive sampling reveals short-term genetic rescue in an insular red fox population
Quinn, Cate B.; Alden, Preston B.; Sacks, Benjamin N. (2019), Data from: Noninvasive sampling reveals short-term genetic rescue in an insular red fox population, Dryad, Dataset, https://doi.org/10.5061/dryad.5k8q374
Genetic factors in the decline of small populations are extremely difficult to study in nature. We leveraged a natural experiment to investigate evidence of inbreeding depression and genetic rescue in a remnant population of subalpine-specialized Sierra Nevada red foxes (Vulpes vulpes necator) using noninvasive genetic monitoring during 2010–2017. Only 7 individuals were detected in the first 2 years. These individuals assigned genetically to the historical population and exhibited genetic hallmarks of inbreeding and no evidence of reproduction. Two years into the study, we detected 2 first-generation immigrant males from a recently expanding population of red foxes in the Great Basin Desert. Through annual resampling of individuals (634 red fox DNA samples, 41 individuals) and molecular reconstruction of pedigrees, we documented 1–3 litters/yr for 5 years, all descended directly or indirectly from matings involving immigrant foxes. The observed heterozygosity and allelic richness of the population nearly doubled in 2 years. Abundance increased, indicative of a rapidly expanding population. Throughout the study, adult survival was high. Restoration of gene flow apparently improved the demographic trajectory of this population in the short term. Whether these benefits continue in the longer-term could depend on numerous factors, such as maintenance of any locally adapted alleles. This study highlights the value of noninvasive genetic monitoring to assess rapidly shifting conditions in small populations. Uncertainties about the longer-term trajectory of this population underscore the need to continue monitoring and to research potential for both negative and positive aspects of continued genetic infusion.
National Science Foundation, Award: 1650042