Substantial Red Wolf Genetic Ancestry Persists in Wild Canids of Southwestern Louisiana

Concerns over red wolf (Canis rufus) extinction caused by hybridization with coyotes (C. latrans) led to the capture and removal of remnant wild wolves from southwestern Louisiana and southeastern Texas, United States, during the 1970s. Here we show that despite decades of unmitigated hybridization, and declaration of endangered red wolves as functionally extinct in the wild, red wolf mitochondrial or nuclear DNA ancestry persists in ∼55% of contemporary wild canids sampled in southwestern Louisiana. Surprisingly, one individual had 78–100% red wolf ancestry, which is within the range for 75% red wolf, red wolf backcross, or putative red wolf, depending on estimation method. Our findings bolster support for designation of red wolves as a distinct species, demonstrate a critical need for the United States Government to consider adopting an existing but unimplemented hybrid policy, and suggest that immediate reassessment of canid management and taxonomic designation in southwestern Louisiana may be warranted

Evaluating the Reliability of Field Identification and Morphometric Classifications for Carnivore Scats Confirmed with Genetic Analysis

Scat surveys are commonly used to monitor carnivore populations. Scats of sympatric carnivores can be difficult to differentiate and field-based identification can be misleading. We evaluated the success of field-based species identification for scats of 2 sympatric carnivores—coyotes (Canis latrans) and kit foxes (Vulpes macrotis). We conducted scat surveys in the Great Basin desert of Utah, USA, during the winter and summer of 2013, and we detected 1,680 carnivore scats. We classified scats based on field identification, recorded morphometricmeasurements, and collected fecalDNA samples for molecular species identification. We subsequently evaluated the classification success of field identification and the predictive power of 2 nonparametric classification techniques—k-nearest neighbors and classification trees—based on scat measurements. Overall, 12.2% of scats were misclassified by field identification, but misclassifications were not equitable between species. Only 7.1% of the scats identified as coyote with field identification were misclassified, compared with 22.9% of scats identified as kit fox. Results from both k-nearest neighbor and classification-tree analyses suggest that morphometric measurements provided an objective alternative to field identification that improved classification of rarer species. Overall misclassification rates for k-nearest neighbor and classification-tree analyses were 11.7% and 7.5%, respectively. Using classification trees, misclassification was reduced for kit foxes (8.5%) and remained similar for coyotes (7.2%), relative to field identification. Although molecular techniques provide unambiguous species identification, classification approaches may offer a cost-effective alternative. We recommend that monitoring programs employing scat surveys utilize molecular species identification to develop training data sets and evaluate the accuracy of field based and statistical classification approaches

Evaluating the Reliability of Field Identification and Morphometric Classifications for Carnivore Scats Confirmed with Genetic Analysis

Scat surveys are commonly used to monitor carnivore populations. Scats of sympatric carnivores can be difficult to differentiate and field-based identification can be misleading. We evaluated the success of field-based species identification for scats of 2 sympatric carnivores—coyotes (Canis latrans) and kit foxes (Vulpes macrotis). We conducted scat surveys in the Great Basin desert of Utah, USA, during the winter and summer of 2013, and we detected 1,680 carnivore scats. We classified scats based on field identification, recorded morphometricmeasurements, and collected fecalDNA samples for molecular species identification. We subsequently evaluated the classification success of field identification and the predictive power of 2 nonparametric classification techniques—k-nearest neighbors and classification trees—based on scat measurements. Overall, 12.2% of scats were misclassified by field identification, but misclassifications were not equitable between species. Only 7.1% of the scats identified as coyote with field identification were misclassified, compared with 22.9% of scats identified as kit fox. Results from both k-nearest neighbor and classification-tree analyses suggest that morphometric measurements provided an objective alternative to field identification that improved classification of rarer species. Overall misclassification rates for k-nearest neighbor and classification-tree analyses were 11.7% and 7.5%, respectively. Using classification trees, misclassification was reduced for kit foxes (8.5%) and remained similar for coyotes (7.2%), relative to field identification. Although molecular techniques provide unambiguous species identification, classification approaches may offer a cost-effective alternative. We recommend that monitoring programs employing scat surveys utilize molecular species identification to develop training data sets and evaluate the accuracy of field based and statistical classification approaches

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 (FST 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

Evidence for \u3cem\u3eBombus Occidentalis\u3c/em\u3e (Hymenoptera: Apidae) Populations in the Olympic Peninsula, the Palouse Prairie, and Forests of Northern Idaho

Since the mid-1990s, Bombus occidentalis (Green) has declined from being one of the most common to one of the rarest bumble bee species in the Pacific Northwest of the United States. Although its conservation status is unresolved, a petition to list this species as endangered or threatened was recently submitted to the U.S. Fish and Wildlife Service. To shed light on the conservation situation and inform the U.S. Fish and Wildlife Service decision, we report on the detection and abundance of B. occidentalis following bumble bee collection between 2012 and 2014 across the Pacific Northwest. Collection occurred from the San Juan Islands and Olympic peninsula east to northern Idaho and northeastern Oregon, excluding the arid region in central Washington. B. occidentalis was observed at 23 collection sites out of a total of 234. With the exception of three sites on the Olympic peninsula, all of these were in the southeastern portion of the collection range

Developing a Monitoring Framework to Estimate Wolf Distribution and Abundance in Southwest Alberta

Gray wolf (Canis lupus) populations are difficult to monitor because wolves can be elusive and occur in low densities.  Traditional radiotelemetry-based monitoring methods have limited application when turnover is high within the wolf population and resources to maintain long-term collaring programs are limited.  We worked collaboratively with Alberta Environmental Sustainable Resource Development between 2012 and 2014 to develop techniques for monitoring gray wolf populations in the absence of radiotelemetry in southwest Alberta.  We surveyed potential rendezvous sites and collected DNA samples from wolf scats for genetic analysis and surveyed hunters for wolf sightings made during the hunting seasons. We fit false-positive occupancy models to annual detection data derived from genetic results and hunter surveys with Program PRESENCE.  We found percent forest cover and human density positively influenced pack occupancy whereas detection probabilities varied by survey method, sampling effort, and sampling season.  The model predicted wolf pack occupancy well and distribution and abundance estimates were consistent with agency predictions.  While developing the monitoring framework, questions arose regarding pack turnover and population growth under widespread human harvest.  Previous studies have focused on population recovery following wolf control actions but little emphasis is put on populations that exist under regular harvest.  We will use genetic data to determine how immigration contributes to wolf population trends under a long-term harvest regime and tie this into pack occupancy through colonization and local extinction probabilities.  This will expand the application of our occupancy model and will further clarify how wolf populations respond to long-term regulated harvest

Immigration as a Compensatory Mechanism to Offset Harvest Mortality in Harvested Wolf Populations

In less than a decade the U.S. Northern Rocky Mountain gray wolf (Canis lupus) population has experienced large shifts in management practices, from federal protection under the Endangered Species Act to increasingly liberal hunting and trapping seasons in many portions of their range after delisting.  As a result, there is interest in how current wolf management practices will affect this population over time.  Recent research suggests wolf pup recruitment in central Idaho has declined since harvest was initiated, yet wolf densities appear stable in many regions of the state, suggesting other compensatory mechanisms are offsetting the effects of harvest mortality.  Our objective was to evaluate immigration as a compensatory mechanism that may offset the effects of harvest mortality and facilitate population persistence in a heavily harvested wolf population.  Using noninvasively sampled DNA we identified dispersers into two focal study areas in central Idaho prior to and after harvest was initiated.  We measured genetic relatedness within and among wolf packs using three different metrics to assess how immigration has changed with changing management practices.  Our results suggest that at current harvest rates immigration is not acting as a compensatory mechanism to offset the effects of harvest mortality.  Local dispersal may be unaffected by harvest pressure whereas harvest has negative effects on long-distance dispersal.  Our research can help managers consider the effects of immigration on local wolf populations when making harvest management decisions

Genetic and spatial structure within a swift fox population

1. We incorporated spatial data on swift foxes (Vulpes velox) with genetic analysis to assess the influence of relatedness between individuals on their social and spatial ecology. We recorded the space use patterns of 188 radio-collared swift foxes in southeastern Colorado from January 1997 to December 2000. One hundred and sixty-seven foxes were also genotyped at 11 microsatellite DNA loci and the degree of relatedness between individuals was estimated. 2. We described the genetic structure of the population by examining the relatedness of neighbors and the relationship between the spatial and genetic distance of all individuals. We found that close kin appeared to cluster within the population. Neighbors were significantly more related (mean R= 0.089 ± 0.01) than non-neighbors (mean R = 0.003 ± 0.01; randomization test, P \u3c 0.0002). Female clusters were more extensive than male clusters. 3. The degree of genetic relatedness among foxes was useful in explaining why foxes tolerated encroachment of their home ranges by neighbors; the more closely related neighbors were, the more home-range overlap they tolerated (Mantel test, P = 0.0004). Foxes did not appear to orientate their home ranges to avoid neighbors and home ranges overlapped by as much as 54.77% (x = 14.13% ± 0.41). Neighbors also occasionally engaged in concurrent den sharing. 4. Relatedness influenced the likelihood that an individual would inherit a newly vacated home range, with a mean relatedness of range inheritors to previous owners of 0.333 ±&#;0.074. Thus, the genetic structure of the population and interactions between kin were interrelated to space-use patterns and social ecology of the swift fox

Wolf Pack Distribution in Relation to Heavy Harvest in Southwest Alberta

Gray wolf (Canis lupus) populations are difficult to monitor because wolves can be elusive and occur in low densities.  Harvest can further complicate wolf monitoring by affecting wolf behavior, altering pack structure, and potentially reducing probability of detection.  Currently, Montana and Idaho use patch occupancy models to monitor wolves at state-wide scales.  These models were originally developed prior to the initiation of wolf harvest and there is growing concern that current occupancy estimates are becoming less reliable as harvest continues.  Our objectives were to determine whether we could estimate wolf distribution for a heavily harvested wolf population and assess how harvest may be affecting that distribution.  We surveyed potential rendezvous sites and collected DNA samples from wolf scats for genetic analysis and surveyed hunters for wolf sightings in southwestern Alberta from 2012 to 2014. We used a Bayesian approach to fit dynamic occupancy models to the encounter histories while accounting for false-positive detections using JAGS and Program R.  We found both habitat and anthropogenic factors influenced wolf occupancy parameters in southwestern Alberta and detection probability varied by survey method.  Our preliminary results suggest wolf pack distribution is fairly consistent but that source-sink dynamics may be occurring in certain regions of the study area.  Despite heavy harvest pressure, southwestern Alberta appears to maintain a stable wolf population, although this is possibly due to immigration from nearby regions

Determination of polar bear (Ursus maritimus) individual genotype and sex based on DNA extracted from paw-prints in snow

Polar bears rely upon sea ice to hunt, travel, and reproduce. Declining sea ice extent and duration has led polar bears to be designated as “threatened” (ESA). Population monitoring is vital to polar bear conservation; but recently, poor sea ice has made traditional aircraft-based methods less viable. These methods largely rely upon the capture and handling of polar bears, and have been criticized over animal welfare concerns. Monitoring polar bears via DNA sampling is a promising option. One common method utilizes biopsy darts delivered from a helicopter to collect DNA, a method that faces similar ice associated challenges to those described above. However, epidermal cells shed from the foot pads of a polar bear into its paw-prints in snow are a source of “environmental DNA” (e-DNA) that can be collected non-invasively on the sea ice or on land for potential use in population monitoring. Mitochondrial DNA (mt-DNA) is used to assess whether polar bear DNA is present within a snow sample, and nuclear DNA (n-DNA) can identify individuals and their sex. The goal of this investigation was to assess the viability of using e-DNA collected from paw-prints in the snow to identify individual polar bears and their sex. Snow was sampled from 13 polar bear trails (10 paw-prints per trail) on the sea ice in the Chukchi and Beaufort seas along the North Slope of Alaska. Species verification was based on a mt-DNA PCR fragment analysis test. Identification of individuals was accomplished by amplifying a multiplex of seven n-DNA microsatellite loci, and sex was determined by the amelogenin gene sex ID marker. Six of the 13 bear trails sampled (46%) yielded consensus genotypes for five unique males and one female. To our knowledge, this is the first time that polar bears have been individually identified by genotype and sex using e-DNA collected from snow. This method is non-invasive, could be integrated into genetic mark-recapture sampling designs, and addresses some of the current challenges arising from poor sea ice conditions. It also can involve, engage, and empower Indigenous communities in the Arctic, which are greatly affected by polar bear management decisions