A fine-scale examination of parturition timing in temperate ungulates.

Parturition timing has long been a topic of interest in ungulate research. However, few studies have examined parturition timing at fine scale (e.g., <1 day). Predator activity and environmental conditions can vary considerably with diel timing, which may result in selective pressure for parturition to occur during diel times that maximize the likelihood of neonate survival. We monitored parturition events and early-life survival of elk (Cervus canadensis) and mule deer (Odocoileus hemionus) in Utah, USA to better understand diel timing of parturition in temperate ungulates. Diel timing of parturition was moderately synchronous among conspecifics and influenced by environmental variables on the date of parturition. For elk, parturition events were most common during the morning crepuscular period and generally occurred later (i.e., closer to 12:00) when a relatively large proportion of the moon was illuminated. For mule deer, parturition events were most common during the diurnal period and generally occurred later (i.e., closer to 15:00) on cold, wet dates. Diel timing of parturition did not influence neonate survival, but larger datasets may be required to verify the apparent lack of influence. Although additional work could evaluate alternative variables that might affect parturition timing, our data provide an improved and finer scale understanding of reproductive ecology and phenology in ungulates.

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore.

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat (Lynx rufus) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014-2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters (K) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation (F ST and GST″) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and GST″ values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

Sources of bias in applying close-kin mark-recapture to terrestrial game species with different life histories.

Close-kin mark-recapture (CKMR) is a method analogous to traditional mark-recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species' and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward-in-time, individual-based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent-offspring pairs and/or half-sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population-specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.

The first documented interaction between a long-tailed weasel (Mustela frenata) and a plains spotted skunk (Spilogale interrupta) carcass.

A novel interaction between a long-tailed weasel (Mustela frenata) and a plains spotted skunk (Spilogale interrupta) carcass is detailed. In November 2020, a farmer in Edmunds County in north-central South Dakota sent in a video recording of a long-tailed weasel with a spotted skunk carcass. Location of the event, carcass condition, and recorded behavior of the long-tailed weasel offer probable, but unconfirmed, evidence that the spotted skunk was killed by the long-tailed weasel.

Habitat amount or landscape configuration: Emerging HotSpot analysis reveals the importance of habitat amount for a grassland bird in South Dakota.

Habitat loss and fragmentation are two important drivers of biodiversity decline. Understanding how species respond to landscape composition and configuration in dynamic landscapes is of great importance for informing the conservation and management of grassland species. With limited conservation resources, prescribed management targeted at the appropriate landscape process is necessary for the effective management of species. We used pheasants (Phasianus colchicus) across South Dakota, USA as a model species to identify environmental factors driving spatiotemporal variation in population productivity. Using an emerging Hotspot analysis, we analyzed annual count data from 105 fixed pheasant brood routes over a 24-year period to identify high (HotSpot) and low (ColdSpot) pheasant population productivity areas. We then applied classification and regression tree modeling to evaluate landscape attributes associated with pheasant productivity among spatial scales (500 m and 1000 m). We found that the amount of grassland at a local spatial scale was the primary factor influencing an area being a HotSpot. Our results also demonstrated non-significant or weak effects of fragmentation per se on pheasant populations. These findings are in accordance with the habitat amount hypothesis highlighting the importance of habitat amount in the landscape for maintaining and increasing the pheasant population. We, therefore, recommend that managers should focus on increasing the total habitat area in the landscape and restoring degraded habitats. Our method of identifying areas of high productivity across the landscape can be applied to other species with count data.

Co-occurrence models fail to infer underlying patterns of avoidance and aggregation when closure is violated.

Advances in multi-species monitoring have prompted an increase in the use of multi-species occupancy analyses to assess patterns of co-occurrence among species, even when data were collected at scales likely violating the assumption that sites were closed to changes in the occupancy state for the target species. Violating the closure assumption may lead to erroneous conclusions related to patterns of co-occurrence among species. Occurrence for two hypothetical species was simulated under patterns of avoidance, aggregation, or independence, when the closure assumption was either met or not. Simulated populations were sampled at two levels (N = 250 or 100 sites) and two scales of temporal resolution for surveys. Sample data were analyzed with conditional two-species occupancy models, and performance was assessed based on the proportion of simulations recovering the true pattern of co-occurrence. Estimates of occupancy were unbiased when closure was met, but biased when closure violations occurred; bias increased when sample size was small and encounter histories were collapsed to a large-scale temporal resolution. When closure was met and patterns of avoidance and aggregation were simulated, conditional two-species models tended to correctly find support for non-independence, and estimated species interaction factors (SIF) aligned with predicted values. By contrast, when closure was violated, models tended to incorrectly infer a pattern of independence and power to detect simulated patterns of avoidance or aggregation that decreased with smaller sample size. Results suggest that when the closure assumption is violated, co-occurrence models often fail to detect underlying patterns of avoidance or aggregation, and incorrectly identify a pattern of independence among species, which could have negative consequences for our understanding of species interactions and conservation efforts. Thus, when closure is violated, inferred patterns of independence from multi-species occupancy should be interpreted cautiously, and evidence of avoidance or aggregation is likely a conservative estimate of true pattern or interaction.

Detection criteria and post-field sample processing influence results and cost efficiency of occupancy-based monitoring.

Optimization of occupancy-based monitoring has focused on balancing the number of sites and surveys to minimize field efforts and costs. When survey techniques require post-field processing of samples to confirm species detections, there may be opportunities to further improve efficiency. We used scat-based noninvasive genetic sampling for kit foxes (Vulpes macrotis) in Utah, USA, as a model system to assess post-field data processing strategies, evaluate the impacts of these strategies on estimates of occupancy and associations between parameters and predictors, and identify the most cost-effective approach. We identified scats with three criteria that varied in costs and reliability: (1) field-based identification (expert opinion), (2) statistical-based morphological identification, and (3) genetic-based identification (mitochondrial DNA). We also considered four novel post-field sample processing strategies that integrated statistical and genetic identifications to reduce costly genetic procedures, including (4) a combined statistical-genetic identification, (5) a genetic removal design, (6) a within-survey conditional-replicate design, and (7) a single-genetic-replicate with false-positive modeling design. We considered results based on genetic identification as the best approximation of truth and used this to evaluate the performance of alternatives. Field-based and statistical-based criteria prone to misidentification produced estimates of occupancy that were biased high (˜1.8 and 2.1 times higher than estimates without misidentifications, respectively). These criteria failed to recover associations between parameters and predictors consistent with genetic identification. The genetic removal design performed poorly, with limited detections leading to estimates that were biased high with poor precision and patterns inconsistent with genetic identification. Both statistical-genetic identification and the conditional-replicate design produced occupancy estimates comparable to genetic identification, while recovering the same model structure and associations at cost reductions of 67% and 74%, respectively. The false-positive design had the lowest cost (88% reduction) and recovered patterns consistent with genetic identification but had occupancy estimates that were ˜32% lower than estimated occupancy based on genetic identification. Our results demonstrate that careful consideration of detection criteria and post-field data processing can reduce costs without significantly altering resulting inferences. Combined with earlier guidance on sampling designs for occupancy modeling, these findings can aid managers in optimizing occupancy-based monitoring.

Evaluating effective population size and genetic diversity of a declining kit fox population using contemporary and historical specimens.

Loss of genetic diversity has serious conservation consequences (e.g., loss of adaptive potential, reduced population viability), but is difficult to evaluate without developing long-term, multigenerational datasets. Alternatively, historical samples can provide insights into changes in genetic diversity and effective population size (N e). Kit foxes (Vulpes macrotis) are a species of conservation concern across much of their range. In western Utah, kit fox abundance has declined precipitously from historical levels, causing concern about population persistence. We analyzed genetic samples from museum specimens and contemporary scats to evaluate temporal changes in (a) genetic diversity and (b) N e for kit foxes in western Utah, and (c) discuss our findings with respect to population risk and conservation. The N e of kit foxes in western Utah has decreased substantially. When compared to established conservation thresholds for N e (e.g., the 50/500 rule), observed levels suggest the population may be at risk of inbreeding depression and local extinction. In contrast, we found no significant decrease in genetic diversity associated with declining N e. We detected evidence of low levels of immigration into the population and suspect genetic diversity may have been maintained by this previously undescribed gene flow from adjacent populations. Low or intermittent immigration may serve to temper the potential short-term negative consequences of low N e. We recommend that kit fox conservation efforts focus on evaluating and maintaining landscape connectivity. We demonstrate how historical specimens can provide a baseline of comparison for contemporary populations, highlighting the importance of natural history collections to conservation during a period of declining funding and support.

Evaluation of Scat Deposition Transects versus Radio Telemetry for Developing a Species Distribution Model for a Rare Desert Carnivore, the Kit Fox.

Development and evaluation of noninvasive methods for monitoring species distribution and abundance is a growing area of ecological research. While noninvasive methods have the advantage of reduced risk of negative factors associated with capture, comparisons to methods using more traditional invasive sampling is lacking. Historically kit foxes (Vulpes macrotis) occupied the desert and semi-arid regions of southwestern North America. Once the most abundant carnivore in the Great Basin Desert of Utah, the species is now considered rare. In recent decades, attempts have been made to model the environmental variables influencing kit fox distribution. Using noninvasive scat deposition surveys for determination of kit fox presence, we modeled resource selection functions to predict kit fox distribution using three popular techniques (Maxent, fixed-effects, and mixed-effects generalized linear models) and compared these with similar models developed from invasive sampling (telemetry locations from radio-collared foxes). Resource selection functions were developed using a combination of landscape variables including elevation, slope, aspect, vegetation height, and soil type. All models were tested against subsequent scat collections as a method of model validation. We demonstrate the importance of comparing multiple model types for development of resource selection functions used to predict a species distribution, and evaluating the importance of environmental variables on species distribution. All models we examined showed a large effect of elevation on kit fox presence, followed by slope and vegetation height. However, the invasive sampling method (i.e., radio-telemetry) appeared to be better at determining resource selection, and therefore may be more robust in predicting kit fox distribution. In contrast, the distribution maps created from the noninvasive sampling (i.e., scat transects) were significantly different than the invasive method, thus scat transects may be appropriate when used in an occupancy framework to predict species distribution. We concluded that while scat deposition transects may be useful for monitoring kit fox abundance and possibly occupancy, they do not appear to be appropriate for determining resource selection. On our study area, scat transects were biased to roadways, while data collected using radio-telemetry was dictated by movements of the kit foxes themselves. We recommend that future studies applying noninvasive scat sampling should consider a more robust random sampling design across the landscape (e.g., random transects or more complete road coverage) that would then provide a more accurate and unbiased depiction of resource selection useful to predict kit fox distribution.

Balancing sample accumulation and DNA degradation rates to optimize noninvasive genetic sampling of sympatric carnivores.

Noninvasive genetic sampling, or noninvasive DNA sampling (NDS), can be an effective monitoring approach for elusive, wide-ranging species at low densities. However, few studies have attempted to maximize sampling efficiency. We present a model for combining sample accumulation and DNA degradation to identify the most efficient (i.e. minimal cost per successful sample) NDS temporal design for capture-recapture analyses. We use scat accumulation and faecal DNA degradation rates for two sympatric carnivores, kit fox (Vulpes macrotis) and coyote (Canis latrans) across two seasons (summer and winter) in Utah, USA, to demonstrate implementation of this approach. We estimated scat accumulation rates by clearing and surveying transects for scats. We evaluated mitochondrial (mtDNA) and nuclear (nDNA) DNA amplification success for faecal DNA samples under natural field conditions for 20 fresh scats/species/season from <1-112 days. Mean accumulation rates were nearly three times greater for coyotes (0.076 scats/km/day) than foxes (0.029 scats/km/day) across seasons. Across species and seasons, mtDNA amplification success was ≥95% through day 21. Fox nDNA amplification success was ≥70% through day 21 across seasons. Coyote nDNA success was ≥70% through day 21 in winter, but declined to <50% by day 7 in summer. We identified a common temporal sampling frame of approximately 14 days that allowed species to be monitored simultaneously, further reducing time, survey effort and costs. Our results suggest that when conducting repeated surveys for capture-recapture analyses, overall cost-efficiency for NDS may be improved with a temporal design that balances field and laboratory costs along with deposition and degradation rates.