Across much of North America, river otter (Lontra canadensis) populations were extirpated or greatly reduced by the early 20th century. More recently, reintroductions have resulted in restored populations and the recommencement of managed trapping. Perhaps the best example of these river otter reintroductions occurred in Missouri, regarded as one of the most successful carnivore recovery programs in history. However, abundance estimates for river otter populations are difficult to obtain and often contentious when used to underpin management activities. We assessed the value of latrine site monitoring as a mechanism for quantifying river otter abundance. Analyses of fecal DNA to identify individual animals may result in an improved population estimate and have been used for a variety of mammal species. We optimized laboratory protocols, redesigned existing microsatellite primers, and calculated genotyping error rates to enhance genotyping success for a large quantity of river otter scat samples. We also developed a method for molecular sexing. We then extracted DNA from 1,421 scat samples and anal sac secretions (anal jelly) collected during latrine site counts along 22–34‐km stretches representing 8–77% of 8 rivers in southern Missouri in 2009. Error rates were low for the redesigned microsatellites. We obtained genotypes at 7–10 microsatellite loci for 24% of samples, observing highest success for anal jelly samples (71%) and lowest for fresh samples (collected within 1 day of defecation). We identified 63 otters (41 M, 22 F) in the 8 rivers, ranging from 2 to 14 otters per river. Analyses using program CAPWIRE resulted in population estimates similar to the minimum genotyping estimate. Density estimates averaged 0.24 otters/km. We used linear regression to develop and contrast models predicting population size based on latrine site and scat count indices, which are easily collected in the field. Population size was best predicted by a combination of scats per latrine and latrines per kilometer. Our results provide methodological approaches to guide wildlife managers seeking to initiate similar river otter fecal genotyping studies, as well as to estimate and monitor river otter population sizes. © 2011 The Wildlife Society.

Reintroduction is an effective tool for restoring endangered populations. There is increasing concern, however, that demographic restoration may not equate with genetic restoration. We examine the demographic-genetic contrast in the context of one of the world's most successful carnivore population restorations. Beginning in 1982, a total of 835 river otters Lontra canadensis were reintroduced to Missouri, USA, more than 50 years after extirpation. Most otters were translocated from Louisiana, USA, and released at 43 sites across the state. An estimated population of 11 000-18 000 otters existed by 2000, and density estimates for Missouri otters are now similar to those reported for populations across the continent, indicating demographic recovery. We used microsatellite genotyping and mitochondrial sequence analysis of DNA extracted from fecal samples from eight southern Missouri rivers, in conjunction with mitochondrial DNA (mtDNA) analyses from several native Louisiana otter populations, to evaluate the genetic diversity and population structure of otters within Missouri as compared with Louisiana. The Missouri population showed moderate to high heterozygosity and allelic diversity, similar to that of the source populations, but low mtDNA haplotype diversity. We detected five distinct genetic clusters distributed throughout the eight rivers, with no evidence of isolation by distance. These data collectively suggest that 30 years after restoration efforts commenced, Missouri river otters have retained genetic diversity levels similar to those of the source populations, but that genetic structure has not reached an equilibrium between migration and genetic drift. Thus, the Missouri otter population has made a robust recovery despite retaining the genetic signature of the reintroduction.Restored otter genetic structure R. A. Mowry et al.

Monitoring rare and elusive carnivores is inherently challenging because they often occur at low densities and require more resources to effectively assess status and trend. The fisher (Pekania pennanti) is an elusive mesocarnivore endemic to North America; in its western populations it is classified as a species of greatest conservation need. During winter of 2018-2019, we deployed remotely triggered cameras in randomly selected, spatially balanced 7.5-km × 7.5-km grid cells across a broad study area in western Montana, Idaho, and eastern Washington, USA. As part of this large-scale, multistate monitoring effort, we conducted an occupancy assessment of the Northern Rocky Mountain fisher population at a range-wide scale. We used non-spatial occupancy models to determine the current extent of fisher occurrence in the Northern Rocky Mountains and to provide baseline occupancy estimates across a broad study area and a refined sampling frame for future monitoring. We used a spatial occupancy model to determine patterns in fisher occurrence across their Northern Rocky Mountain range while explicitly correcting for spatially induced overdispersion. Additionally, we assessed factors that influenced fisher occurrence through covariate occupancy modeling that considered predicted fisher habitat, site-level environmental characteristics, and the influence of available harvest records (incidental and regulated). We detected fishers in 32 out of 318 (10%) of our surveyed cells, and estimated that overall, 160 (14%; 95% CI = 115-218) of 1,143

Climate change is expected to disproportionately affect species occupying ecosystems with relatively hard boundaries, such as alpine ecosystems. Wildlife managers must identify actions to conserve and manage alpine species into the future, while considering other issues and uncertainties. Climate change and respiratory pathogens associated with widespread pneumonia epidemics in bighorn sheep (Ovis canadensis) may negatively affect mountain goat (Oreamnos americanus) populations. Mountain goat demographic and population data are challenging to collect and sparsely available, making population management decisions difficult. We developed predictive models incorporating these uncertainties and analyzed results within a structured decision making framework to make management recommendations and identify priority information needs in Montana, USA. We built resource selection models to forecast occupied mountain goat habitat and account for uncertainty in effects of climate change, and a Leslie matrix projection model to predict population trends while accounting for uncertainty in population demographics and dynamics. We predicted disease risks while accounting for uncertainty about presence of pneumonia pathogens and risk tolerance for mixing populations during translocations. Our analysis predicted that new introductions would produce more area occupied by mountain goats at mid‐century, regardless of the effects of climate change. Population augmentations, carnivore management, and harvest management may improve population trends, although this was associated with considerable uncertainty. Tolerance for risk of disease transmission affected optimal management choices because translocations are expected to increase disease risks for mountain goats and sympatric bighorn sheep. Expected value of information analyses revealed that reducing uncertainty related to population dynamics would affect the optimal choice among management strategies to improve mountain goat trends. Reducing uncertainty related to the presence of pneumonia‐associated pathogens and consequences of mixing microbial communities should reduce disease risks if translocations are included in future management strategies. We recommend managers determine tolerance for disease risks associated with translocations that they and constituents are willing to accept. From this, an adaptive management program can be constructed wherein a portfolio of management actions are chosen based on risk tolerance in each population range, combined with the amount that uncertainty is reduced when paired with monitoring, to ultimately improve achievement of fundamental objectives.

Extirpated from Missouri by the 1930s, river otters (Lontra canadensis) were reintroduced by the Missouri Department of Conservation (MDC) between1982 and 1992. Since the reintroductions, concerns over the legitimacy of otter trapping and the predator's effects on sport fish populations have sparked controversy.The MDC responded by increasing efforts to monitor river otter populations, using latrine site counts to measure relative abundance across several rivers in Missouri. However, the actual number of otters represented by these counts was unknown. To address this question, I extracted DNA present on the surface of scat samples collected along 8 rivers in southern Missouri in the winter and spring of 2009. I used a panel of 10 microsatellite markers (segments of DNA containing repeated base pairs, the number of which varies between individuals) plus sexing markers to genotype (or fingerprint) and sex individual otters to determine the population size and sex ratio. I identified 63 otters (41 males, 22 females) across the 8 rivers, with population sizes ranging from 2 in the Niangua River (density 0.069 otters/km) to 14 in the Big Piney River (density 0.511 otters/km). I then developed a model to estimate population size from latrine site index variables, observing that the number of scats per latrine and the density of active latrines across the river best predicted population size. I then used the genotypes to calculate the genetic diversity of the otter populations, evaluate the distribution of genotype clusters across the landscape, and track individual otter movements between latrines. Unexpected genetic similarities in geographically distant rivers indicated that otters translocated to different areas may have come from the same source populations, and have not yet developed population substructure related to their current Missouri environments. Overall, this project has demonstrated the utility of genetic methods for estimating otter abundance, provided insight into the genetic diversity of the populations, and presented a model for inexpensive monitoring of river otter populations in the future.