Evaluating the current condition of a threatened marine mammal population: Estimating northern sea otter (Enhydra lutris kenyoni) abundance in southwest Alaska

We estimated density and abundance of the threatened southwest Alaska distinct population segment of northern sea otters (Enhydra lutris kenyoni) in two management units. We conducted aerial surveys in Bristol Bay and South Alaska Peninsula management units in 2016, and modeled sea otter density and abundance with Bayesian hierarchical distance sampling models and spatial environmental covariates (depth, distance to shore, depth × distance to shore). Spatial environmental covariates substantially impacted sea otter group density in both management units, but effects sizes differed between the two management units. Abundance (9,733 otters, 95% CrI 6,412–17,819) and density (0.82 otters/km², 95% CrI 0.54–1.49) estimates for Bristol Bay indicated a moderate population size. In contrast, abundance (546 otters, 95% CrI 322–879) and density (0.06 otters/km², 95% CrI 0.03–0.09) estimates indicated a relatively low population size in South Alaska Peninsula. Overall, our results highlight the importance of accounting for the detection process in monitoring at-risk species to reduce the uncertainty associated with making conclusions about population declines.     

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.     

Using density surface models to estimate spatio-temporal changes in population densities and trend

Precise measures of population abundance and trend are needed for species conservation; these are most difficult to obtain for rare and rapidly changing populations. We compare uncertainty in densities estimated from spatio–temporal models with that from standard design-based methods. Spatio–temporal models allow us to target priority areas where, and at times when, a population may most benefit. Generalised additive models were fitted to a 31-year time series of point-transect surveys of an endangered Hawaiian forest bird, the Hawai‘i ‘ākepa Loxops coccineus. This allowed us to estimate bird densities over space and time. We used two methods to quantify uncertainty in density estimates from the spatio–temporal model: the delta method (which assumes independence between detection and distribution parameters) and a variance propagation method. With the delta method we observed a 52% decrease in the width of the design-based 95% confidence interval (CI), while we observed a 37% decrease in CI width when propagating the variance. We mapped bird densities as they changed across space and time, allowing managers to evaluate management actions. Integrating detection function modelling with spatio–temporal modelling exploits survey data more efficiently by producing finer-grained abundance estimates than are possible with design-based methods as well as producing more precise abundance estimates. Model-based approaches require switching from making assumptions about the survey design to assumptions about bird distribution. Such a switch warrants consideration. In this case the model-based approach benefits conservation planning through improved management efficiency and reduced costs by taking into account both spatial shifts and temporal changes in population abundance and distribution.     

Evaluation of an Aerial Survey to Estimate Abundance of Wintering Ducks in Mississippi

Abstract: Researchers have successfully designed aerial surveys that provided precise estimates of wintering populations of ducks over large physiographic regions, yet few conservation agencies have adopted these probability-based sampling designs for their surveys. We designed and evaluated an aerial survey to estimate abundance of wintering mallards (Anas platyrhynchos), dabbling ducks (tribe Anatini) other than mallards, diving ducks (tribes Aythini, Mergini, and Oxyurini), and total ducks in western Mississippi, USA. We used design-based sampling of fixed width transects to estimate population indices (Ǐ), and we used model-based methods to correct population indices for visibility bias and estimate population abundance (Ň) for 14 surveys during winters 2002–2004. Correcting for bias increased estimates of mallards, other dabbling ducks, and diving ducks by an average of 40–48% among all surveys and contributed 48–61% of the estimated variance of Ň. However, mean-squared errors were consistently less for Ň than Ǐ. Estimates of Ň met our goals for precision (CV ≤ 15%) in 7 of 14 surveys for mallards, 5 surveys for other dabbling ducks, no surveys for diving ducks, and 10 surveys for total ducks. Generally, we estimated more mallards and other dabbling ducks in mid- and late winter (Jan-Feb) than early winter (Nov-Dec) and determined that population indices from the late 1980s were nearly 3 times greater than those from our study. We developed a method to display relative densities of ducks spatially as an additional application of survey data. Our study advanced methods of estimating abundance of wintering waterfowl, and we recommend this design for continued monitoring of wintering ducks in western Mississippi and similar physiographic regions.     

Distribution of mountain hares Lepus timidus in Scotland: results from a questionnaire

A questionnaire survey of land owners, managers and gamekeepers was conducted in order to assess the distribution of mountain hares in Scotland, assess their current management, collate numbers harvested in 2006–07 and estimate distribution change by comparing with similar data collected in 1995–96. The land area covered by returned questionnaires was 71098km² (90% of Scotland). Mountain hares were reported as present on 34359km² (48%) and absent from 36739km² (52%). Mountain hare presence was strongly associated with heather moorland managed for red grouse shooting. Moorland managed for driven grouse shooting had the highest percentage area of mountain hare presence (median 64%) followed by moorland managed for walked‐up grouse shooting (median 9%) and moorland with no grouse shooting (median 0%). Approximately 25000 mountain hares were harvested in 2006–07. Based on the estimated UK population in 1995 of 350000 (range ±50%), this represents around 7% of the population (range 5–14%). Reasons given by respondents for harvesting hares were tick control (50%), sport (40%) and forestry or crop protection (10%). Comparison of the estates surveyed in both 2006–07 and 1995–96 (a total area of 20462km²) indicated no net gain or loss in hare distribution. Furthermore, there was no evidence that levels of harvest had reduced the range of mountain hares in this area. It is not possible to comment on any distribution change outside this area (58737km²). Similarly, as no data were collected on abundance, it is not possible to draw conclusions on changes in density. Regular monitoring of mountain hare distribution within Scotland is required to identify any distribution changes. Measures of abundance throughout the range are necessary to estimate the population size, investigate the relationship between harvest intensity and changes in abundance and further assess the conservation status of this UK Biodiversity Action Plan species.     

Focusing Conservation Efforts for the Critically Endangered Brown-headed Spider Monkey (<Emphasis Type="Italic">Ateles fusciceps</Emphasis>) Using Remote Sensing,Modeling, and Playback Survey Methods

Brown-headed spider monkeys (Ateles fusciceps), endemic to the Choco-Darien forests and lower Andean forests of NW Ecuador, are considered critically endangered. Unfortunately, scientific data regarding the actual status of populations is lacking. We combined satellite image analysis, species-specific habitat assessment, and a field survey technique using playback to focus conservation efforts for this species. First, we identified remaining forest via a LANDSAT mosaic and then applied species-specific criteria to delineate remaining forest with potential to hold populations. By combining this with the historical distribution from ecological niche modeling and predicted hunting intensity we generated a species-specific landscape map. Within our study area, forest capable of sustaining Ateles fusciceps covers 5872 km², of which 2172 km² (40%) is protected. Unprotected forest considered suitable for Ateles fusciceps extends to 3700 km² but within this only 989 km² (23%) is under low hunting pressure and likely to maintain healthy populations of Ateles fusciceps. To overcome problems of sampling at low primate density and in difficult mountain terrain we developed a field survey technique to determine presence and estimate abundance using acoustic sampling. For sites under low hunting pressure density of primates varied with altitude. Densities decreased from 7.49 individuals/km² at 332 masl to 0.9 individuals/km² at 1570 masl. Based on combining data sets in a gap analysis, we recommend conservation action focus on unprotected lowland forest to the south and west of the Cotacachi-Cayapas Ecological Reserve where hunting pressure is low and population densities of Ateles fusciceps are greatest.     

Response of native ungulates to drought in semi‐arid Kenyan rangeland

The distribution and abundance of native ungulates were measured on commercially managed, semi‐arid rangeland in central Kenya over a 3‐year period that encompassed severe drought and above‐average rainfall. Native ungulate biomass density averaged 5282 kg km^?2 over the study and was dominated by elephant (Loxodonta africana), impala (Aepyceros melampus) and dik‐dik (Madoqua kirkii). Biomass density of domestic cattle (Bos taurus) averaged 2280 kg km^?2 during the study. Responses of native ungulates to severe drought were variable. Impala densities were similar to or greater than densities for similar habitat in protected areas, and varied from 12 to 16 km^?2 during and following the drought to 24–29 km^?2 following above‐average rainfall. Dik‐dik densities were also greater than densities reported for protected areas and were surprisingly stable throughout the study despite the wide annual fluctuations in rainfall. Elephant migrated out of the region during drought but were present at high densities (2.9–5.2 km^?2) during wet seasons, consistent with telemetry studies emphasizing the importance of Acacia bushland habitat on commercial rangelands for the migratory portion of the Laikipia–Samburu elephant population. Results show that substantial densities of native browsing and mixed‐feeding ungulates can occur on rangeland managed for commercial beef production and suggest that the capacity for ungulates to move over large spatial scales (>100 km²) and to shift distributions in response to locally variable thunderstorms may be important for sustaining these populations.     

Integrating sign surveys and telemetry data for estimating brown bear (Ursus arctos) density in the Romanian Carpathians

Accurate population size estimates are important information for sustainable wildlife management. The Romanian Carpathians harbor the largest brown bear (Ursus arctos) population in Europe, yet current management relies on estimates of density that lack statistical oversight and ignore uncertainty deriving from track surveys. In this study, we investigate an alternative approach to estimate brown bear density using sign surveys along transects within a novel integration of occupancy models and home range methods. We performed repeated surveys along 2‐km segments of forest roads during three distinct seasons: spring 2011, fall‐winter 2011, and spring 2012, within three game management units and a Natura 2000 site. We estimated bears abundances along transects using the number of unique tracks observed per survey occasion via N‐mixture hierarchical models, which account for imperfect detection. To obtain brown bear densities, we combined these abundances with the effective sampling area of the transects, that is, estimated as a function of the median (± bootstrapped SE) of the core home range (5.58 ± 1.08 km²) based on telemetry data from 17 bears tracked for 1‐month periods overlapping our surveys windows. Our analyses yielded average brown bear densities (and 95% confidence intervals) for the three seasons of: 11.5 (7.8–15.3), 11.3 (7.4–15.2), and 12.4 (8.6–16.3) individuals/100 km². Across game management units, mean densities ranged between 7.5 and 14.8 individuals/100 km². Our method incorporates multiple sources of uncertainty (e.g., effective sampling area, imperfect detection) to estimate brown bear density, but the inference fundamentally relies on unmarked individuals only. While useful as a temporary approach to monitor brown bears, we urge implementing DNA capture–recapture methods regionally to inform brown bear management and recommend increasing resources for GPS collars to improve estimates of effective sampling area.     

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 abundance of Sitka black-tailed deer using DNA from fecal pellets

Densely vegetated environments have hindered collection of basic population parameters on forest-dwelling ungulates. Our objective was to develop a mark–recapture technique that used DNA from fecal pellets to overcome constraints associated with estimating abundance of ungulates in landscapes where direct observation is difficult. We tested our technique on Sitka black-tailed deer (Odocoileus hemionus sitkensis) in the temperate coastal rainforest of Southeast Alaska. During 2006–2008, we sampled fecal pellets of deer along trail transects in 3 intensively logged watersheds on Prince of Wales Island, Alaska. We extracted DNA from the surface of fecal pellets and used microsatellite markers to identify individual deer. With genotypes of individual deer, we estimated abundance of deer with moderate precision (±20%) using mark–recapture models. Combining all study sites, we identified a 30% (SE = 5.1%) decline in abundance during our 3-year study, which we attributed to 3 consecutive severe winters. We determined that deer densities in managed land logged >30 years ago (7 deer/km², SE = 1.3) supported fewer deer compared to both managed land logged <30 years ago (10 deer/km², SE = 1.5) and unmanaged land (12 deer/km², SE = 1.4). Our study provides the first estimates of abundance (based on individually identified deer) for Sitka black-tailed deer and the first estimates of abundance of an unenclosed ungulate population using DNA from fecal pellets. Our tool enables managers to accurately and precisely estimate the abundance of deer in densely vegetated habitats using a non-invasive approach. © 2011 The Wildlife Society.     

Censusing rainforest game species with communal net hunts

This paper presents a method to address two wildlife management problems in central African rainforests: the need for local communities to take responsibility for wildlife management, and the lack of simple and appropriate wildlife monitoring techniques. The method uses encounters of game species during net hunts to calculate abundance indices as well as to estimate population densities for the four principal game species in the Dzanga–Sangha region: the duikers Cephalophus monticola (10.7–20.4 km^?2), C. dorsalis (1.2–2.0 km^?2), and C. callipygus (0.9–1.2 km^?2), and the brush-tailed porcupine Atherurus africanus (2.7–5.3 km^?2). Game species behaviour, the hunting practice, and comparisons with results from other research across central Africa suggest that the method can provide valid density estimates for C. monticola and C. dorsalis, but only abundance indices for C. callipygus and A. africanus. Nevertheless, the method can be applied by hunters in the course of their normal activities, and is adapted to the local habitat types and game species. As such, it can be an important tool for local communities in developing sustainable wildlife management programmes.     

The Abundance and Distribution of Wolverines in British Columbia,Canada

ABSTRACT The abundance and distribution of carnivores and their habitat are key information needed for status assessment, conservation planning, population management, and assessment of the effects of human development on their habitat and populations. We developed a habitat quality rating system, using existing wolverine (Gulo gulo) distribution, wolverine food, ecosystem mapping, and human development data. We used this and empirically derived estimates of wolverine density to predict wolverine distribution and abundance at a provincial scale. Density estimates for wolverines in high-quality habitat averaged 6.2 wolverines/1,000 km² (95% CI = 4.2–9.5). We predicted mean densities ranging from 0.3/1,000 km² in rare-quality habitat to 4.1/1,000 km² in moderate-quality habitat. Our predicted population estimate for wolverines in British Columbia was 3,530 (95% CI = 2,700-4,760). We predicted highest densities of wolverines in interior mountainous regions, moderate densities in interior plateau and boreal forest regions, and low densities in mainland coastal regions and drier interior plateaus. We predicted that wolverines would be rare on Vancouver Island, along the outer mainland coast, and in the dry interior forests, and absent from the Queen Charlotte Islands, interior grassland environments, and areas of intensive urban development.     

Trends in bowhead whales in West Greenland: Aerial surveys vs. genetic capture‐recapture analyses

We contrast two methods for estimating the trends of bowhead whales (Balaena mysticetus) in West Greenland: (1) double platform visual aerial survey, corrected for missed sightings and the time the whales are available at the surface; and (2) a genetic capture‐recapture approach based on a 14‐yr‐long biopsy sampling program in Disko Bay. The aerial survey covered 39,000 km² and resulted in 58 sightings, yielding an abundance estimate of 744 whales (CV = 0.34, 95% CI: 357–1,461). The genetic method relied on determining sex, mitochondrial haplotypes and genotypes of nine microsatellite markers. Based on samples from a total of 427 individuals, with 11 recaptures from previous years in 2013, this resulted in an estimate of 1,538 whales (CV = 0.24, 95% CI: 827–2,249). While the aerial survey is considered a snapshot of the local spring aggregation in Disko Bay, the genetic approach estimates the abundance of the source of this aggregation. As the whales in Disko Bay primarily are adult females that do not visit the bay annually, the genetic method would presumably yield higher estimates. The studies indicate that an increase in abundance observed between 1998 and 2006 has leveled off.     

Evidence of a large carnivore population recovery: Counting bears in Greece

Reliable population and density estimates are the cornerstone of effective conservation and management planning, as conservation priorities often arise in relation to population numbers. Despite increased public interest and costly conservation programs limited information on brown bear (Ursus arctos, Linnaeus, 1758) abundance and density in Greece exists. We carried out systematic non-invasive genetic sampling using hair traps on power poles, as part of a capture-mark-recapture study design in order to rigorously estimate abundance and density of the Pindos bear population in Greece. From 2007–2010 we identified 211 and estimated a mean of 182.3 individuals in four sampling areas; bear densities ranged from 10.0 to 54 bears/1000 km². These results indicate an important population recovery of this large carnivore in Greece in recent years; a conservative population estimate would place the population size in the entire country >450 individuals. Considering the results of the study and the increased negative interactions between humans and bears recorded currently in Greece, we suggest that systematic genetic monitoring using power poles should continue in order to collect the necessary information that will enable the definition of an effective Action Plan for the long-term conservation of this species.     

Estimating mountain goat abundance using DNA from fecal pellets

Non-invasive collection of tissue samples to obtain DNA for microsatellite genotyping required to estimate population size has been used for many wildlife species but rarely for ungulates. We estimated mountain goat (Oreamnos americanus) population size on a mountain complex in southwestern British Columbia by identification of individuals using DNA obtained from fecal pellet and hair samples collected during 3 sampling sessions. We identified 55 individuals from 170 samples that were successfully genotyped, and estimated a population of 77 mountain goats (SE = 7.4). Mean capture probability was 0.38 (SE = 0.037) per session. Our technique provides one of the first statistically rigorous estimates of abundance of an ungulate species using DNA derived primarily from fecal pellets. Our technique enables managers to obtain minimum counts or population estimates of ungulates in areas of low sightability that can be used for conservation and management. © 2011 The Wildlife Society.     

Estimating abundances,densities, and interspecific associations in a carnivore community

Estimating population abundances, densities, and interspecific interactions are common goals in wildlife management. Camera traps have been used to estimate the abundance and density of a single species, and are useful for carnivores that occur at low densities. Spatial capture–recapture (SCR) models can be used to estimate abundance and density from a camera trap array when all, some, or no individuals in the population can be uniquely identified. These SCR models also estimate locations of individual activity centers, the spatial patterning of which could provide important information about interspecific interactions. We used SCR models to estimate abundances, densities, and activity centers of each of 3 carnivore species (i.e., dingo [Canis familiaris], red fox [Vulpes vulpes], and feral cat) using photographs from 1 camera trap array in southeastern Australia during September to November 2015. Some dingoes and feral cats were uniquely identifiable and therefore, we used a spatial mark–resight model for these species. We could not uniquely identify fox individuals, however, so we used a spatial unmarked (SUN) model for this species. Our estimated dingo density was 0.06/km². The fox (0.25/km²) and feral cat (0.16/km²) densities are within the ranges previously reported for these species in Australia. We obtained a relatively imprecise fox density estimate because we did not have detections of uniquely identifiable individuals; hence, the SUN model should be used as a last resort. We next modeled spatial dependence among the estimated activity centers for the 3 species using a spatial pair correlation function for a marked point process. Consistent with our expectations, the activity centers of dingoes and foxes were strongly negatively associated at distances of <1,000 m. Foxes and feral cats were also negatively associated at distances of <1,500 m. Surprisingly, dingoes and feral cats were positively associated at distances of >500 m, with no association evident at distances of <500 m. Our study extends the inferences that can be made from using a camera trap array and SCR methods to include spatial patterning and interspecific interactions, and provides new insights into the carnivore community of dingoes, foxes, and feral cats in southeastern Australia. © 2019 The Authors. The Journal of Wildlife Management Published by Wiley Periodicals, Inc.     

A noninvasive and integrative approach for improving density and abundance estimates of moose

Acquiring demographic data for moose (Alces alces) can be difficult because they are solitary in nature, they prefer densely vegetated and mountainous habitats, and they often occur at low density. Such data, however, are essential for long-term population monitoring, evaluating management practices, and effective conservation. Winter aerial surveys are the standard method for estimating moose population parameters, but they can be logistically challenging, expensive, and subject to sightability correction, which necessitates the capture of study animals for initial model development. Herein, we demonstrate a noninvasive alternative approach for estimating population parameters of moose in northern Yellowstone National Park, where aerial surveys were attempted but proved ineffective. We determined individual moose genotype and sex using microsatellite polymerase chain reaction amplification of DNA extracted from fecal pellets, integrated ancillary pellet sample data (i.e., metadata) in genotype analysis to aid in the identification of matching genotypes, and used spatially explicit capture-recapture (SECR) modeling to estimate sex-specific density and abundance. We collected 616 samples over 3 consecutive winters (Dec 2013–Apr 2016) and within 2 sampling occasions each winter. We recorded 514 captures of 142 individual moose (69 males, 73 females). Overall density ranged between 0.062 moose/km² and 0.076 moose/km² and averaged 0.034/km² for females and 0.033/km² for males. Abundance estimates were 150 moose in 2013 (female = 76, 95% CI = 55–105; male = 74, 95% CI = 54–103), 186 in 2014 (female = 95, 95% CI = 63–142; male = 91, 95% CI = 60–138), and 160 in 2015 (female = 79, 95% CI = 58–108; male = 81, 95% CI = 59–110). Average population sex ratio was 0.99 males/female. We demonstrate that SECR analysis of fecal DNA genotypes, using metadata in genotype analysis to help identify matching moose genotypes, is a promising alternative method for estimating sex-specific density and abundance of a low-density moose population in a mountainous and forested landscape.     

Evaluating Methods for Counting Cryptic Carnivores

ABSTRACT Numerous techniques have been proposed to estimate carnivore abundance and density, but few have been validated against populations of known size. We used a density estimate established by intensive monitoring of a population of radiotagged leopards (Panthera pardus) with a detection probability of 1.0 to evaluate efficacy of track counts and camera-trap surveys as population estimators. We calculated densities from track counts using 2 methods and compared performance of 10 methods for calculating the effectively sampled area for camera-trapping data. Compared to our reference density (7.33 ± 0.44 leopards/100 km²), camera-trapping generally produced more accurate but less precise estimates than did track counts. The most accurate result (6.97 ± 1.88 leopards/100 km²) came from camera-trap data with a sampled area buffered by a boundary strip representing the mean maximum distance moved by leopards outside the survey area (MMDMOSA) established by telemetry. However, contrary to recent suggestions, the traditional method of using half the mean maximum distance moved from photographic recaptures did not result in gross overestimates of population density (6.56 ± 1.92 leopards/100 km²) but rather displayed the next best performance after MMDMOSA. The only track-count method comparable to reference density employed a capture-recapture framework applied to data when individuals were identified from their tracks (6.45 ± 1.43 leopards/100 km²) but the underlying assumptions of this technique limit more widespread application. Our results demonstrate that if applied correctly, camera-trap surveys represent the best balance of rigor and cost-effectiveness for estimating abundance and density of cryptic carnivore species that can be identified individually.     

Estimation of Black Bear Abundance Using a Discrete DNA Sampling Device

Abstract We developed a snare for collection of black bear (Ursus americanus) hair that obtained a unique hair sample at each snare site, improved the quantity of collected hair compared to barbed-wire corrals, and was easy to deploy over a wide range of topographical features and habitat conditions. This device allowed us to implement intensive sampling methodology needed in mark-recapture experiments with minimal effort. By improving the quantity of hair collected, we also lowered the potential for bear identification errors at the lab. During 2003–2004, bears in 2 study areas triggered snares 1,104 times, which resulted in the collection of 981 hair samples. Of the samples we collected, 79% (775) produced valid genetic data. In 2003, 454 samples identified 79 genetically distinct individuals, and 321 samples identified 86 genetically distinct individuals in 2004. Analysis of capture-recapture data indicated that capture probabilities were affected by heterogeneity among individuals and behavioral responses, but showed little evidence of time effects. Consequently, we used the Pollock and Otto (1983) estimator for model M_bh to estimate abundance with reasonably good precision (CV: 12–14%). Density on the Steamboat and Toketee, Oregon, USA, study areas over the 2-year period averaged 19 bears/100 km² and 22 bears/100 km², respectively. Average capture and recapture probabilities over the 2 years of the study were 30% and 63%, respectively, indicating a trap-prone behavioral response. Knowledge of bear densities on the Steamboat and Toketee study areas will enable managers to set hunting quotas, advise land management agencies on habitat issues, and create a baseline database to assist in the long-term monitoring of bear trends in a changing landscape.     

Territory size of wolves Canis lupus: linking local (Białowieża Primeval Forest, Poland) and Holarctic-scale patterns

Factors affecting territory size in wolves Canis lupus were studied at 2 scales, the local population (Bia?owie?a Primeval Forest (BPF), eastern Poland) and the geographic range of species (literature review from 14 localities in the Holarctic). Four packs of wolves were studied by radio‐tracking in BPF from 1994 to 1999. The annual territories of packs (Minimum convex polygons with 95% of locations) averaged 201 km² (SD 63, range 116–310). Core areas of territories (50% MCP) covered from 14 to 78 km² (mean 35). Territory sizes and core areas both were negatively correlated to the encounter rates of ungulates (mean number of ungulates seen per unit time spent in the forest by human observers). Pack size (3–8 wolves) did not influence territory size. Home ranges of individual wolves from the same pack varied with season as well as the age, sex, and reproductive status of the wolf. Review of literature from North America and Europe (42–66^oN), showed that latitude and prey biomass were essential factors shaping the biogeographic variation in wolf territory size. Territories increased with latitude and declined with growing biomass of prey. The analysis showed that latitude acted partly independently of the south–north gradient in prey abundance. At similar standing crop of ungulate biomass (100 kg km^?2), wolf territories would average 140 km² at 40^oN, 370 km² at 50^oN, and 950 km² at 60^oN. Pack size was larger at northern latitudes, but the increase did not keep pace with enlargement of territories. Within‐territory density of wolves declined from 2.5–3 wolves 100 km^?2 at 40–45^oN to 0.7 wolves 100 km^?2 at 60^oN. Our analyses documented similarities regarding the role of prey resources in shaping wolf territoriality at the different scales. Furthermore, a macroecological approach revealed additional factors affecting wolf territory size that were not emergent from knowledge of local population.