Density of American black bears in New Mexico

Pleistocene-Holocene vicariance, not Anthropocene landscape change, explains the genetic structure of American black bear (Ursus americanus) populations in the American Southwest and northern Mexico

The phylogeography of the American black bear (Ursus americanus) is characterized by isolation into glacial refugia, followed by population expansion and genetic admixture. Anthropogenic activities, including overharvest, habitat loss, and transportation infrastructure, have also influenced their landscape genetic structure. We describe the genetic structure of the American black bear in the American Southwest and northern Mexico and investigate how prehistoric and contemporary forces shaped genetic structure and influenced gene flow. Using a suite of microsatellites and a sample of 550 bears, we identified 14 subpopulations organized hierarchically following the distribution of ecoregions and mountain ranges containing black bear habitat. The pattern of subdivision we observed is more likely a product of postglacial habitat fragmentation during the Pleistocene and Holocene, rather than a consequence of contemporary anthropogenic barriers to movement during the Anthropocene. We used linear mixed‐effects models to quantify the relationship between landscape resistance and genetic distance among individuals, which indicated that both isolation by resistance and geographic distance govern gene flow. Gene flow was highest among subpopulations occupying large tracts of contiguous habitat, was reduced among subpopulations in the Madrean Sky Island Archipelago, where montane habitat exists within a lowland matrix of arid lands, and was essentially nonexistent between two isolated subpopulations. We found significant asymmetric gene flow supporting the hypothesis that bears expanded northward from a Pleistocene refugium located in the American Southwest and northern Mexico and that major highways were not yet affecting gene flow. The potential vulnerability of the species to climate change, transportation infrastructure, and the US–Mexico border wall highlights conservation challenges and opportunities for binational collaboration.

Precision and bias of spatial capture-recapture estimates: A multi-site, multi-year Utah black bear case study

Spatial capture-recapture (SCR) models are powerful analytical tools that have become the standard for estimating abundance and density of wild animal populations. When sampling populations to implement SCR, the number of unique individuals detected, total recaptures, and unique spatial relocations can be highly variable. These sample sizes influence the precision and accuracy of model parameter estimates. Testing the performance of SCR models with sparse empirical data sets typical of low-density, wide-ranging species can inform the threshold at which a more integrated modeling approach with additional data sources or additional years of monitoring may be required to achieve reliable, precise parameter estimates. Using a multi-site, multi-year Utah black bear (Ursus americanus) capture-recapture data set, we evaluated factors influencing the uncertainty of SCR structural parameter estimates, specifically density, detection, and the spatial scale parameter, sigma. We also provided some of the first SCR density estimates for Utah black bear populations, which ranged from 3.85 to 74.33 bears/100 km² . Increasing total detections decreased the uncertainty of density estimates, whereas an increasing number of total recaptures and individuals with recaptures decreased the uncertainty of detection and sigma estimates, respectively. In most cases, multiple years of data were required for precise density estimates (<0.2 coefficient of variation [CV]). Across study areas there was an average decline in CV of 0.07 with the addition of another year of data. One sampled population with very high estimated bear density had an atypically low number of spatial recaptures relative to total recaptures, apparently inflating density estimates. A complementary simulation study used to assess estimate bias suggested that when <30% of recaptured individuals were spatially recaptured, density estimates were unreliable and ranged widely, in some cases to >3 times the simulated density. Additional research could evaluate these requirements for other density scenarios. Large numbers of individuals detected, numbers of spatial recaptures, and precision alone may not be sufficient indicators of parameter estimate reliability. We provide an evaluation of simple summary statistics of capture-recapture data sets that can provide an early signal of the need to alter sampling design or collect auxiliary data before model implementation to improve estimate precision and accuracy.

Evaluating otter reintroduction outcomes using genetic spatial capture-recapture modified for dendritic networks

Monitoring the demographics and genetics of reintroduced populations is critical to evaluating reintroduction success, but species ecology and the landscapes that they inhabit often present challenges for accurate assessments. If suitable habitats are restricted to hierarchical dendritic networks, such as river systems, animal movements are typically constrained and may violate assumptions of methods commonly used to estimate demographic parameters. Using genetic detection data collected via fecal sampling at latrines, we demonstrate applicability of the spatial capture-recapture (SCR) network distance function for estimating the size and density of a recently reintroduced North American river otter (Lontra canadensis) population in the Upper Rio Grande River dendritic network in the southwestern United States, and we also evaluated the genetic outcomes of using a small founder group (n = 33 otters) for reintroduction. Estimated population density was 0.23-0.28 otter/km, or 1 otter/3.57-4.35 km, with weak evidence of density increasing with northerly latitude (β = 0.33). Estimated population size was 83-104 total otters in 359 km of riverine dendritic network, which corresponded to average annual exponential population growth of 1.12-1.15/year since reintroduction. Growth was ≥40% lower than most reintroduced river otter populations and strong evidence of a founder effect existed 8-10 years post-reintroduction, including 13-21% genetic diversity loss, 84%-87% genetic effective population size decline, and rapid divergence from the source population (F ST accumulation = 0.06/generation). Consequently, genetic restoration via translocation of additional otters from other populations may be necessary to mitigate deleterious genetic effects in this small, isolated population. Combined with non-invasive genetic sampling, the SCR network distance approach is likely widely applicable to demogenetic assessments of both reintroduced and established populations of multiple mustelid species that inhabit aquatic dendritic networks, many of which are regionally or globally imperiled and may warrant reintroduction or augmentation efforts.