Challenges of DNA-Based Mark-Recapture Studies of American Black Bears

Abstract: We explored whether genetic sampling would be feasible to provide a region-wide population estimate for American black bears (Ursus americanus) in the southern Appalachians, USA. Specifically, we determined whether adequate capture probabilities (p > 0.20) and population estimates with a low coefficient of variation (CV < 20%) could be achieved given typical agency budget and personnel constraints. We extracted DNA from hair collected from baited barbed-wire enclosures sampled over a 10-week period on 2 study areas: a high-density black bear population in a portion of Great Smoky Mountains National Park and a lower density population on National Forest lands in North Carolina, South Carolina, and Georgia. We identified individual bears by their unique genotypes obtained from 9 microsatellite loci. We sampled 129 and 60 different bears in the National Park and National Forest study areas, respectively, and applied closed mark-recapture models to estimate population abundance. Capture probabilities and precision of the population estimates were acceptable only for sampling scenarios for which we pooled weekly sampling periods. We detected capture heterogeneity biases, probably because of inadequate spatial coverage by the hair-trapping grid. The logistical challenges of establishing and checking a sufficiently high density of hair traps make DNA-based estimates of black bears impractical for the southern Appalachian region. Alternatives are to estimate population size for smaller areas, estimate population growth rates or survival using mark-recapture methods, or use independent marking and recapturing techniques to reduce capture heterogeneity.     

Factors associated with black bear density and implications for management

Wildlife density estimates are important to accurately formulate population management objectives and understand the relationship between habitat characteristics and a species’ abundance. Despite advances in density and abundance estimation methods, management of common game species continues to be challenged by a lack of reliable population estimates. In Washington, USA, statewide American black bear (Ursus americanus) abundance estimates are predicated on density estimates derived from research in the 1970s and are hypothesized to be a function of precipitation and vegetation, with higher densities in western Washington. To evaluate current black bear density and landscape relationships in Washington, we conducted a 4-year capture-recapture study in 2 areas of the North Cascade Mountains using 2 detection methods, non-invasive DNA collection and physical capture and deployment of global positioning system (GPS) collars. We integrated GPS telemetry from collared bears with spatial capture-recapture (SCR) data and created a SCR-resource selection model to estimate density as a function of spatial covariates and test the hypothesis that density is higher in areas with greater vegetative food resources. We captured and collared 118 bears 132 times and collected 7,863 hair samples at hair traps where we identified 537 bears from 1,237 detections via DNA. The most-supported model in the western North Cascades depicted a negative relationship between black bear density and an index of human development. We estimated bear density at 20.1 bears/100 km², but density varied from 13.5/100 km² to 27.8 bears/100 km² depending on degree of human development. The model best supported by the data in the eastern North Cascades estimated an average density of 19.2 bears/100 km², which was positively correlated with primary productivity, with resulting density estimates ranging from 7.1/100 km² to 33.6 bears/100 km². The hypothesis that greater precipitation and associated vegetative production in western Washington supports greater bear density compared to eastern Washington was not supported by our data. In western Washington, empirically derived average density estimates (including cubs) were nearly 50% lower than managers expected prior to our research. In eastern Washington average black bear density was predominantly as expected, but localized areas of high primary productivity supported greater than anticipated bear densities. Our findings underscore the importance that black bear density is not likely uniform and management risk may be increased if an average density is applied at too large a scale. Disparities between expected and empirically derived bear density illustrate the need for more rigorous monitoring to understand processes that affect population numbers throughout the jurisdiction, and suggest that management plans may need to be reevaluated to determine if current harvest strategies are achieving population objectives. © 2019 The Wildlife Society.     

Effect of Harvest on a Brown Bear Population in Alaska

There is a long and contentious history of brown bear (Ursus arctos) harvest management in Alaska, USA, the state that hosts the largest brown bear population in North America. In the mid-1990s, the Alaska Board of Game set the population objective for brown bears in Game Management Unit 13 A, located in interior southcentral Alaska, to be reduced by 50% to improve survival of moose (Alces alces) calves. The Board began further liberalizing brown bear harvest regulations for the unit beginning in regulatory year 1995, though adult females and their dependent offspring (i.e., cubs <2 yrs old) were protected. To evaluate progress toward this abundance objective, we captured and collared bears between 2006 and 2011 and conducted a capture-mark-resight density survey during summer 2011 for comparison to a similar baseline survey conducted in 1998. We report the results of the density survey and vital rates estimated from resight histories of collared bears and harvest information spanning from 1985 (10 years before establishment of the population objective) to 2012. There was a 25–40% reduction in abundance between 1998 and 2011. Population growth rates derived from density estimates and a matrix population projection model indicated that the population declined by 2.3–4.2% annually. We estimated harvest rates to be 8–15% annually, but harvest composition data indicated no changes in skull size, age distribution, or overall sex ratio. There was evidence of an increase in the proportion of older females in the harvest. Demographic analysis indicated high reproductive output and recruitment, potentially indicating a density-dependent compensatory response to reduced population size. Despite 13 years of harvest rates in excess of what had previously been considered to be sustainable for this population, the objective of reducing bear abundance by 50% had not been achieved as of 2011. The protection of females and dependent offspring in our study population appears to be a sufficient safeguard against a precipitous population decline while still permitting progress toward the population objective through high harvest on other segments of the population. © 2020 The Wildlife Society.     

Addressing challenges in non invasive capture-recapture based estimates of small populations: a pilot study on the Apennine brown bear

It is often difficult to determine optimal sampling design for non-invasive genetic sampling, especially when dealing with rare or elusive species depleted of genetic diversity. To address this problem, we ran a hair-snag pilot study on the remnant Apennine brown bear population. We used occupancy models to estimate the performance of an improved field protocol, a meta-analysis approach to indirectly model capture probability, and simulations to evaluate the effect of genotyping errors on the accuracy of capture-recapture population estimates. In spring 2007 we collected 70 bear hair samples in 15 5 × 5 km cells, using 5 10-day trapping sessions. Bear detectability was higher in 2007 than in a previous attempt on the same population in 2004, reflecting improved field protocols and sampling design. However, individual capture probability was 0.136 (95% CI = 0.120–0.152), still below the minimum requirements of capture-mark-recapture closed population models. We genotyped hair samples (n = 63) at 9 microsatellite loci, obtaining 94% Polymerase Chain Reaction success, and 13 bear genotypes. Estimated P_IDsib was 0.00594, and per-genotype error rate was 0.13, corresponding to a 99% probability of correct individual identification. Simulation studies showed that the effect of non-corrected or filtered genetic errors on the accuracy of population estimates was negligible only when individual capture probability was >0.2. Our results underline how the interaction among field protocols, sampling strategies and genotyping errors may affect the accuracy of DNA-based estimates of small and genetically depleted populations, and warned us about the feasibility of a survey using only traditional hair-snag sampling. In this and similar cases, indications from pilot studies can provide cost-effective means to evaluate the efficiency of designed sampling and modelling procedures.     

Estimation of capture probabilities using generalized estimating equations and mixed effects approaches

Modeling individual heterogeneity in capture probabilities has been one of the most challenging tasks in capture–recapture studies. Heterogeneity in capture probabilities can be modeled as a function of individual covariates, but correlation structure among capture occasions should be taking into account. A proposed generalized estimating equations (GEE) and generalized linear mixed modeling (GLMM) approaches can be used to estimate capture probabilities and population size for capture–recapture closed population models. An example is used for an illustrative application and for comparison with currently used methodology. A simulation study is also conducted to show the performance of the estimation procedures. Our simulation results show that the proposed quasi‐likelihood based on GEE approach provides lower SE than partial likelihood based on either generalized linear models (GLM) or GLMM approaches for estimating population size in a closed capture–recapture experiment. Estimator performance is good if a large proportion of individuals are captured. For cases where only a small proportion of individuals are captured, the estimates become unstable, but the GEE approach outperforms the other methods.     

Estimating Detection Probabilities from Sign of Collared Peccary

ABSTRACT Determining presence or absence of collared peccaries (Pecari tajacu) from surveys of sign (tracks and feces) requires information on whether animals in sample units are detected. We estimated detection probabilities of collared peccary from sign surveys using occupancy models. Because it was unlikely that residence status of collared peccary in sampling units remained the same over a survey season, which is a primary assumption of occupancy models, we first determined the time interval for which to pool data. We then examined the influence of rainfall and peccary abundance on detection probabilities. We placed 90 sign stations (25-m-diam circular plots) throughout Chaparral Wildlife Management Area, south Texas, USA. We surveyed plots weekly for the presence or non-presence of collared peccary during 2 11-week sampling seasons in spring and fall 2003. We examined sign data weekly and we pooled the data in intervals from 2 weeks to 5 weeks. Estimates of detection probabilities increased from 1 week to 3 weeks of pooled data and leveled off thereafter. We needed a 3-week time interval to meet the assumption of unchanging residence status. Using sign data pooled in 3-week increments, detection probabilities were influenced by areas that differed in peccary abundance, but they were not influenced by rainfall. Estimates of detection probabilities ranged from 0.43 to 0.77 for 3-week time intervals. Sign surveys and occupancy modeling of data can be used to measure spatial patterns of collared peccary in south Texas as long as multiple 3-week time intervals are sampled.     

Capture, anesthesia, and disturbance of free-ranging brown bears (Ursus arctos) during hibernation

We conducted thirteen immobilizations of previously collared hibernating two- to four-year-old brown bears (Ursus arctos) weighing 21-66 kg in central Sweden in winter 2010 and 2011 for comparative physiology research. Here we report, for the first time, an effective protocol for the capture and anesthesia of free-ranging brown bears during hibernation and an assessment of the disturbance the captures caused. Bears were darted in anthill, soil, or uprooted tree dens on eleven occasions, but two bears in rock dens fled and were darted outside the den. We used medetomidine at 0.02-0.06 mg/kg and zolazepam-tiletamine at 0.9-2.8 mg/kg for anesthesia. In addition, ketamine at 1.5 mg/kg was hand-injected intramuscularly in four bears and in six it was included in the dart at 1.1-3.0 mg/kg. Once anesthetized, bears were removed from the dens. In nine bears, arterial blood samples were analyzed immediately with a portable blood gas analyzer. We corrected hypoxemia in seven bears (PaO(2) 57-74 mmHg) with supplemental oxygen. We placed the bears back into the dens and antagonized the effect of medetomidine with atipamezole. Capturing bears in the den significantly increased the risk of den abandonment. One of twelve collared bears that were captured remained at the original den until spring, and eleven, left their dens (mean ± standard deviation) 3.2±3.6 (range 0.5-10.5) days after capture. They used 1.9±0.9 intermediate resting sites, during 6.2±7.8 days before entering a new permanent den. The eleven new permanent dens were located 730±589 m from the original dens. We documented that it was feasible and safe to capture hibernating brown bears, although they behaved differently than black bears. When doing so, researchers should use 25% of the doses used for helicopter darting during the active period and should consider increased energetic costs associated with den abandonment.     

Estimating abundance and population trends when detection is low and highly variable: A comparison of three methods for the Hermann's tortoise

Assessing population trends is a basic prerequisite to carrying out adequate conservation strategies. Selecting an appropriate method to monitor animal populations can be challenging, particularly for low-detection species such as reptiles. This study compares 3 detection-corrected abundance methods (capture–recapture, distance sampling, and N-mixture) used to assess population size of the threatened Hermann's tortoise. We used a single dataset of 432 adult tortoise observations collected at 118 sampling sites in the Plaine des Maures, southeastern France. We also used a dataset of 520 tortoise observations based on radiotelemetry data collected from 10 adult females to estimate and model the availability (g0) needed for distance sampling. We evaluated bias for N-mixture and capture–recapture, by using simulations based on different values of detection probabilities. Finally, we conducted a power analysis to estimate the ability of the 3 methods to detect changes in Hermann's tortoise abundances. The abundance estimations we obtained using distance sampling and N-mixture models were respectively 1.75 and 2.19 times less than those obtained using the capture–recapture method. Our results indicated that g0 was influenced by temperature variations and can differ for the same temperature on different days. Simulations showed that the N-mixture models provide unstable estimations for species with detection probabilities <0.5, whereas capture–recapture estimations were unbiased. Power analysis showed that none of the 3 methods were precise enough to detect slow population changes. We recommend that great care should be taken when implementing monitoring designs for species with large variation in activity rates and low detection probabilities. Although N-mixture models are easy to implement, we would not recommend using them in situations where the detection probability is very low at the risk of providing biased estimates. Among the 3 methods allowing estimation of tortoise abundances, capture–recapture should be preferred to assess population trends. © 2013 The Wildlife Society.     

Bear historical ranges revisited: Documenting the increase of a once-extirpated population in Nevada

Black bears (Ursus americanus) were once abundant in Nevada and distributed throughout the state, yet recognition of the species' historical occurrence in the state is uncommon and has therefore been ignored in published distribution maps for North America. The lack of representation on distribution maps is likely due to the lack of any scientific data or research on bears in Nevada until 1987. Historical records dating back to the 1840s compiled by Nevada Department of Wildlife (NDOW) biologist Robert McQuivey indicate presence of black bears throughout the state in the 1800s through about 1930. The paucity of historical references after 1931 suggest extirpation of black bears from Nevada's interior mountain ranges by this time. We report on historical records of black bears in the state of Nevada and the results of a current population estimate of black bears derived from a sample of marked bears (n = 420) captured 707 times between 1997 and 2008. Using Pradel and Cormack–Jolly–Seber models in Program MARK, we estimated overall population size, finite rate of growth (λ = 1.16), quarterly and annual survival rates for males and females, seasonal capture probabilities, and recruitment rates. Our results indicate an overall population size of 262 ± 31 adult black bears in western Nevada. These results suggest that the once abundant, then extirpated population of black bears in Nevada is increasing at an annual average rate of 16%. Although the current distribution is limited to the western part of the state, our findings suggest possible expansion of the population into historical habitat within the interior and eastern portions of the state that have been absent of bears for >80 years. Finally, based on historical records, we present suggested revised historical distribution maps for black bears that include the Great Basin ranges in Nevada. © 2013 The Wildlife Society.     

Estimating abundance of mountain lions from unstructured spatial sampling

Mountain lions (Puma concolor) are often difficult to monitor because of their low capture probabilities, extensive movements, and large territories. Methods for estimating the abundance of this species are needed to assess population status, determine harvest levels, evaluate the impacts of management actions on populations, and derive conservation and management strategies. Traditional mark–recapture methods do not explicitly account for differences in individual capture probabilities due to the spatial distribution of individuals in relation to survey effort (or trap locations). However, recent advances in the analysis of capture–recapture data have produced methods estimating abundance and density of animals from spatially explicit capture–recapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capture–recapture models to estimate density and abundance of mountain lions in western Montana. Volunteers and state agency personnel collected mountain lion DNA samples in portions of the Blackfoot drainage (7,908 km²) in west-central Montana using 2 methods: snow back-tracking mountain lion tracks to collect hair samples and biopsy darting treed mountain lions to obtain tissue samples. Overall, we recorded 72 individual capture events, including captures both with and without tissue sample collection and hair samples resulting in the identification of 50 individual mountain lions (30 females, 19 males, and 1 unknown sex individual). We estimated lion densities from 8 models containing effects of distance, sex, and survey effort on detection probability. Our population density estimates ranged from a minimum of 3.7 mountain lions/100 km² (95% CI 2.3–5.7) under the distance only model (including only an effect of distance on detection probability) to 6.7 (95% CI 3.1–11.0) under the full model (including effects of distance, sex, survey effort, and distance × sex on detection probability). These numbers translate to a total estimate of 293 mountain lions (95% CI 182–451) to 529 (95% CI 245–870) within the Blackfoot drainage. Results from the distance model are similar to previous estimates of 3.6 mountain lions/100 km² for the study area; however, results from all other models indicated greater numbers of mountain lions. Our results indicate that unstructured spatial sampling combined with spatial capture–recapture analysis can be an effective method for estimating large carnivore densities. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.     

Black bear spatial responses to the Wallow Wildfire in Arizona

The Wallow Fire, the largest wildfire in Arizona history, encompassed 2,170 km² and provided a rare opportunity to examine habitat selection and home ranges of American black bears (Ursus americanus) before and after a wildfire. We had fitted global positioning system (GPS) collars on 47 bears from 2005 to April 2011, and 10 of these were still collared when the fire started in May 2011. We captured and collared an additional 7 black bears within the fire perimeter post-fire (Jul–Sep 2011 and Jun 2012). To evaluate how black bears were affected by the fire, we fit a step selection function using a conditional mixed effects Poisson regression model to estimate the relative strength of black bear habitat selection in response to burn severity. Additionally, we estimated home range sizes using an autocorrelated kernel density estimator by means of a continuous-time movement model. We then used a generalized linear model with a negative binomial error distribution and mixed effects to estimate the effect of the burn severity on black bear home range size, while controlling for sex and drought. In spring and summer in years prior to the fire, bears selected areas that later burned in the fire. After the fire, bears used all burn severities, but their selection for high-severity burns decreased significantly in summer 2011 and fall 2012. Home range sizes were 3.06 times larger pre-fire than post-fire. Our study demonstrates that black bears continued to use all burn severities after a major wildfire, and that post-fire conditions did not result in expanded black bear home ranges.     

Estimating survival of a streamside salamander: importance of temporary emigration,capture response,and location

Estimating survival for highly secretive aquatic animals, such as stream salamanders, presents numerous challenges. Salamanders often spend a considerable time in refugia where they are difficult to capture. Few studies have calculated vital rates for stream salamanders, yet the need is substantial as they are threatened by a wide range of land-use stressors, especially urban development. In this study, we used 34 months of continuous field samples collected at an urban and undisturbed stream and robust design mark-recapture analysis to evaluate the importance of temporary emigration, capture response, and location on survival estimates of the salamander Desmognathus fuscus. We constructed a set of candidate models incorporating combinations of time- and location-varying capture and recapture probabilities, capture responses, temporary emigration, and survival estimates and ranked models using Akaike’s Information Criterion. We found strong support for month-specific capture probabilities, recapture probabilities, temporary emigration and a negative behavioral response to capture in the majority of months. We found no support for variation in capture probabilities, recapture probabilities, and temporary emigration between locations. However, we found that location strongly influenced survival estimates. Specifically, survival estimates were significantly higher at the undisturbed site than at the urban site. Our results emphasize the importance of estimating capture probabilities, recapture probabilities, capture response, and temporary emigration when evaluating survival in highly secretive aquatic animals. Failure to account for these population parameters will likely yield biased estimates of survival in freshwater animal populations.     

Erratum to: Using multistate capture–mark–recapture models to quantify effects of predation on age-specific survival and population growth in black-tailed deer

Effective species management and conservation relies on accurate estimates of vital rates and an understanding of their link to environmental variables. We used multistate capture–mark–recapture models to directly quantify effects of predation on age-specific survival of black-tailed deer Odocoileus hemionus columbianus in California, USA. Survival probabilities were derived from individual encounter histories of 136 fawns and 57 adults monitored over 4 years. Based on results from our survival analysis we parameterized a Lefkovitch matrix and used elasticity analyses to investigate contributions of mortality due to predation to changes in population growth. We found strong evidence for age-specific survival including senescence. Survival of females >1 year old was consistently low (0.56 ± 0.18 for yearlings, 0.77 ± 0.13 for prime-aged females, and 0.55 ± 0.08 for senescent individuals), primarily due to high puma Puma concolor predation during summer. Predation from black bears Ursus americanus and coyotes Canis latrans was the primary cause for low annual survival of fawns (0.24 ± 0.16). Resulting estimates of population growth rates were indicative of a strongly declining population (λ = 0.82 ± 0.13). Despite high sensitivity to changes in adult survival, results from a lower-level elasticity analysis suggested that predation on fawns was the most significant individual mortality component affecting population decline. Our results provide a rare, direct link between predation, age-specific survival and the predicted population decline of a common ungulate species. The magnitude of predation was unexpected and suggests that ungulates in multi-predator systems struggle to cope with simultaneous reductions in survival probabilities from predators targeting different age classes.     

Leopard density in post-conflict landscape,Cambodia: Evidence from spatially explicit capture–recapture

Effective conservation of large carnivores requires reliable estimates of population density, often obtained through capture–recapture analysis, in order to prioritize investments and assess conservation intervention effectiveness. Recent statistical advances and development of user-friendly software for spatially explicit capture–recapture (SECR) circumvent the difficulties in estimating effective survey area, and hence density, from capture–recapture data. We conducted a camera-trapping study on leopards (Panthera pardus) in Mondulkiri Protected Forest, Cambodia. We compared density estimates using SECR with those obtained from conventional approaches in which the effective survey area is estimated using a boundary strip width based on observed animal movements. Density estimates from Chao heterogeneity models (3.8 ± SE 1.9 individuals/100 km²) and Pledger heterogeneity models and models accounting for gender-specific capture and recapture rates (model-averaged density 3.9 ± SE 2.9 individuals/100 km²) were similar to those from SECR in program DENSITY (3.6 ± SE 1.0/100 km²) but higher than estimates from Jack-knife heterogeneity models (2.9 ± SE 0.9 individuals/100 km²). Capture probabilities differed between male and female leopards probably resulting from differences in the use of human-made trails between sexes. Given that there are a number of biologically plausible reasons to expect gender-specific variation in capture probabilities of large carnivores, we recommend exploratory analysis of data using models in which gender can be included as a covariate affecting capture probabilities particularly given the demographic importance of breeding females for population recovery of threatened carnivores. © 2011 The Wildlife Society.     

Noninvasive Estimation of Black Bear Abundance Incorporating Genotyping Errors and Harvested Bear

ABSTRACT Estimating black bear (Ursus americanus) population size is a difficult but important requirement when justifying harvest quotas and managing populations. Advancements in genetic techniques provide a means to identify individual bears using DNA contained in tissue and hair samples, thereby permitting estimates of population abundance based on established mark-capture-recapture methodology. We expand on previous noninvasive population-estimation work by geographically extending sampling areas (36,848 km²) to include the entire Northern Lower Peninsula (NLP) of Michigan, USA. We selected sampling locations randomly within biologically relevant bear habitat and used barbed wire hair snares to collect hair samples. Unlike previous noninvasive studies, we used tissue samples from harvested bears as an additional sampling occasion to increase recapture probabilities. We developed subsampling protocols to account for both spatial and temporal variance in sample distribution and variation in sample quality using recently published quality control protocols using 5 microsatellite loci. We quantified genotyping errors using samples from harvested bears and estimated abundance using statistical models that accounted for genotyping error. We estimated the population of yearling and adult black bears in the NLP to be 1,882 bears (95% CI = 1,389-2,551 bears). The derived population estimate with a 15% coefficient of variation was used by wildlife managers to examine the sustainability of harvest over a large geographic area.     

Smoothing population size estimates for time-stratified mark-recapture experiments using Bayesian P-splines

Petersen-type mark-recapture experiments are often used to estimate the number of fish or other animals in a population moving along a set migration route. A first sample of individuals is captured at one location, marked, and returned to the population. A second sample is then captured farther along the route, and inferences are derived from the numbers of marked and unmarked fish found in this second sample. Data from such experiments are often stratified by time (day or week) to allow for possible changes in the capture probabilities, and previous methods of analysis fail to take advantage of the temporal relationships in the stratified data. We present a Bayesian, semiparametric method that explicitly models the expected number of fish in each stratum as a smooth function of time. Results from the analysis of historical data from the migration of young Atlantic salmon (Salmo salar) along the Conne River, Newfoundland, and from a simulation study indicate that the new method provides more precise estimates of the population size and more accurate estimates of uncertainty than the currently available methods.     

Characteristics of Asian black bears stripping bark from coniferous trees

Stripping of conifer tree bark by Asian black bears (Ursus thibetanus) has been observed in parts of Japan. To identify and characterize the bears exhibiting this behavior, we performed a genetic analysis using DNA extracted from the hairs left on damaged trees. We analyzed 219 samples of bear hair collected from damaged trees at 33 sites and 64 tissue samples from captured bears as controls by using ten microsatellite DNA loci, ca. 706 bp of the mitochondrial DNA d-loop region, and the amelogenin locus. Sixteen bears were identified; some of them had damaged trees at more than one site. bark-stripping and the captured bears. Spatial autocorrelation analysis for increasing distance class revealed a significantly positive genetic correlation coefficient within 40 km among the bark-stripping bears (P < 0.05). Relatedness among the bark-stripping bears was higher than among the captured bears when the distance between bears was within 25 km. We concluded that bark-stripping behavior is associated with relatedness.     

Genetic mark–recapture population estimation in black bears and issues of scale

Abundance estimates for black bears (Ursus americanus) are important for effective management. Recently, DNA technology has resulted in widespread use of noninvasive, genetic capture–mark–recapture (CMR) approaches to estimate populations. Few studies have compared the genetic CMR methods to other estimation methods. We used genetic CMR to estimate the bear population at 2 study sites in northern New Hampshire (Pittsburg and Milan) in 2 consecutive years. We compared these estimates to those derived from traditional methods used by the New Hampshire Fish and Game Department (NHFG) using hunter harvest and mortality data. Density estimates produced with genetic CMR methods were similar both years and were comparable to those derived from traditional methods. In 2006, the estimated number of bears in Pittsburg was 79 (95% CI = 60–98) corresponding to a density of 15–24 (95% CI) bears/100 km²; the 2007 estimate was 83 (95% CI = 67–99; density = 16–24 bears/100 km²). In 2006, the estimated number of bears in Milan was 95 (95% CI = 74–117; density = 16–25 bears/100 km²); the 2007 estimate was 96 (95% CI = 77–114; density = 17–25 bears/100 km²). We found that genetic CMR methods were able to identify demographic variation at a local scale, including a strongly skewed sex ratio (2 M:1 F) in the Milan population. Genetic CMR is a useful tool for wildlife managers to monitor populations of local concern, where abundance or demographic characteristics may deviate from regional estimates. Future monitoring of the Milan population with genetic CMR is recommended to determine if the sex ratio bias continues, possibly warranting a change in local harvest regimes. © 2011 The Wildlife Society.     

Estimating Black Bear Density Using DNA Data From Hair Snares

ABSTRACT DNA-based mark-recapture has become a methodological cornerstone of research focused on bear species. The objective of such studies is often to estimate population size; however, doing so is frequently complicated by movement of individual bears. Movement affects the probability of detection and the assumption of closure of the population required in most models. To mitigate the bias caused by movement of individuals, population size and density estimates are often adjusted using ad hoc methods, including buffering the minimum polygon of the trapping array. We used a hierarchical, spatial capture-recapture model that contains explicit components for the spatial-point process that governs the distribution of individuals and their exposure to (via movement), and detection by, traps. We modeled detection probability as a function of each individual's distance to the trap and an indicator variable for previous capture to account for possible behavioral responses. We applied our model to a 2006 hair-snare study of a black bear (Ursus americanus) population in northern New York, USA. Based on the microsatellite marker analysis of collected hair samples, 47 individuals were identified. We estimated mean density at 0.20 bears/km². A positive estimate of the indicator variable suggests that bears are attracted to baited sites; therefore, including a trap-dependence covariate is important when using bait to attract individuals. Bayesian analysis of the model was implemented in WinBUGS, and we provide the model specification. The model can be applied to any spatially organized trapping array (hair snares, camera traps, mist nests, etc.) to estimate density and can also account for heterogeneity and covariate information at the trap or individual level.     

Comparing clustered sampling designs for spatially explicit estimation of population density

Spatially explicit capture–recapture methods do not assume that animals have equal access to sampling devices (e.g., detectors), which allows for gaps in the sampling extent and nonuniform (e.g., clustered) sampling designs. However, the performance (i.e., relative root mean squared error [RRMSE], confidence interval coverage, relative bias and relative standard error) of clustered detector arrays has not been thoroughly evaluated. I used simulations to evaluate the performance of various detector and cluster spacings, cluster configurations (i.e., number of detectors arranged in a square grid), sampling extents and number of sampling occasions for estimating population density, the relationship between detection rate and distance to a detector from the animal's center of activity (σ) and base detection rates, using American black bears (Ursus americanus) as a case study. My simulations indicated that a wide range of detector configurations can provide reliable estimates if spacing between detectors in clusters is ≥1σ and ≤3σ. A number of cluster configurations and occasion lengths produced estimates that were unbiased, resulted in good spatial coverage, and were relatively precise. Moreover, increasing the duration of sampling, establishing large study areas, increasing detection rates and spacing clusters so that cross-cluster sampling of individuals can occur could help ameliorate deficiencies in the detector layout. These results have application for a wide array of species and sampling methods (e.g., DNA sampling, camera trapping, mark-resight and search-encounter) and suggest that clustered sampling can significantly reduce the effort necessary to provide reliable estimates of population density across large spatial extents that previously would have been infeasible with nonclustered sampling designs.