Estimating Coyote Densities with Local,Discrete Bayesian Capture-Recapture Models

Recent advances in noninvasive genetic sampling and spatial capture-recapture (SCR) techniques are particularly useful for monitoring cryptic wildlife species such as carnivores. In southern Arizona, USA, coyotes (Canis latrans) are thought to negatively affect endangered Sonoran pronghorn (Antilocapra americana sonoriensis), although no estimates of coyote abundance or monitoring programs exist. Sonoran pronghorn are provided supplemental feed and water in this region, resulting in areas where pronghorn and other species are congregated. Because of the higher density of artificial water sources for Sonoran pronghorn on the Cabeza Prieta National Wildlife Refuge (CPNWR), we predicted that coyote density would be higher relative to the Barry M. Goldwater Range (BMGR), where artificial water sources are less dense. We used discrete Bayesian SCR models in a local evaluation approach to provide baseline estimates of coyote abundance and understand how coyote density varied between 2 contrasting areas of land use. We identified 106 individuals from scat samples across 3 sessions in 2013 and 2014 and achieved high genotyping and individual identification success rates (~78%). Encounter rates at water catchments were nearly 11 times higher compared to road and trail transects. As predicted, we found that coyote density was on average 2 times higher on the CPNWR (11.2 coyotes/100 km²) compared to the BMGR (5.3 coyotes/100 km²). The local evaluation approach significantly reduced computational time, making the discrete Bayesian approach more practical to implement across a large study area. Our study represents an important contribution towards developing a robust monitoring program for coyotes. We hope that our novel implementation of the local evaluation approach increases the ability of wildlife managers to understand the effects of land use and other ecological influences on large carnivore populations. © 2020 The Wildlife Society.     

Evaluation of Noninvasive Genetic Sampling Methods for Felid and Canid Populations

Abstract: Noninvasive sampling methods provide a means for studying species such as large mammalian carnivores that are difficult to survey using traditional techniques. Focusing on bobcat (Lynx rufus), we compared the effectiveness of noninvasive hair and scat genetic sampling in terms of field sample collection, species identification, and individual identification. We describe a novel hair-snare design and sampling protocol that successfully sampled 4 sympatric carnivore species, bobcat, mountain lion (Felis concolor), coyote (Canis latrans), and gray fox (Urocyon cinereoargenteus), in 3 habitat blocks in coastal southern California, USA. Scat surveys were also successful at sampling bobcats and other carnivores in the area. Hair and scat sampling methods had similar species identification success (81% and 87%, respectively) using mitochondrial DNA amplification and restriction enzyme digestion patterns. Therefore, for studies focused on the distribution and activity of a suite of carnivore species, we recommend a combination of noninvasive methodologies, for example, targeting hair and scat surveys toward species and sites where they are most effective. Because of a higher success rate for scat (85%) than for hair samples (10%) when using 4 microsatellite loci and a multiple-tubes approach to verify individual genotypes, we suggest scat sampling is a better choice for studies that require individual identification of bobcats.     

Density and population structure of the jaguar (<Emphasis Type="Italic">Panthera onca</Emphasis>) in a protected area of Los Llanos,Venezuela, from 1 year of camera trap monitoring

Density is crucial for understanding large carnivore ecology and conservation, but estimating it has proven methodologically difficult. We conducted 1 year of camera trapping to estimate jaguar (Panthera onca) density and population structure in the Los Llanos region of Venezuela on the Hato Piñero ranch, where hunting is prohibited and livestock are excluded from half of ranch lands. We identified 42 different jaguars and determined their sex, age class, and reproductive status. We estimated adult jaguar densities with spatial capture-recapture models, using sex/reproductive state and session as covariates. Models without temporal variation received more support than models that allowed variation between sessions. Males, reproductive females, and nonreproductive females differed in their density, baseline detectability, and movement. The best estimate of total adult jaguar population density was 4.44 individuals/100 km². Based on reproductive female density and mean number of offspring per female, we estimated cub density at 3.23 individuals/100 km² and an overall density of 7.67 jaguars/100 km². Estimated jaguar population structure was 21% males, 11% nonreproductive females, 26% reproductive females, and 42% cubs. We conclude that extending the sampling period to 1 year increases the detectability of females and cubs and makes density estimates more robust as compared to the more common short studies. Our results demonstrate that the Venezuelan Llanos represent important jaguar habitat, and further, they emphasize the importance of protected areas and hunting restrictions for carnivore conservation.     

Effects of Prey Presence and Scale on Bobcat Resource Selection during Winter

Factors relevant to resource selection in carnivores may vary across spatial and temporal scales, both in magnitude and rank. Understanding relationships among carnivore occupancy, prey presence, and habitat characteristics, as well as their interactions across multiple scales, is necessary to improve our understanding of resource selection and predict population changes. We used a multi-scale dynamic hierarchical co-occurrence model with camera data to study bobcat and snowshoe hare occupancy in the Upper Peninsula of Michigan during winter 2012–2013. Bobcat presence was influenced at the local scale by snowshoe hare presence, and by road density at the local and larger scale when hare were absent. Hare distribution was related primarily to vegetation cover types, and detectability varied in space and time. Bobcat occupancy dynamics were influenced by different factors depending on the spatial scale considered and the resource availability context. Moreover, considering observed co-occurrence, we suggest that bobcat presence had a greater effect on hare occupancy than hare presence on bobcat occupancy. Our results highlight the importance of studying carnivore distributions in the context of predator-prey relationships and its interactions with environmental covariates at multiple spatial scales. Our approach can be applied to other carnivore species to provide insights beneficial for management and conservation.     

The Effects of Landscape Characteristics on Northern Bobwhite Density

The northern bobwhite (Colinus virginianus) is an ecologically and economically valuable species in the United States. Managers rely on autumn density estimates to set harvest regulations, balancing the interests of hunters and long-term bobwhite population viability. Spatial capture-recapture (SCR) is a useful framework for estimating population size and modeling spatial variation in density. We used SCR to quantify the effect of landscape structure on spatial variation in density for a population of bobwhites on the Di-Lane Wildlife Management Area in Waynesboro, Georgia, USA. Without additional telemetry or nesting data, we were also able to estimate a spatially explicit metric of productivity. To sample the population, we deployed a fixed array of 395, 262, and 268 funnel traps in 2016, 2017, and 2018, respectively. We estimated age structure, with the highest density of juveniles (0.32 birds/ha, 95% CI = 0.28–0.37) and adults (0.10 birds/ha, 95% CI = 0.08–0.12) estimated in 2016. In our top model, density was negatively related to the proportion of closed canopy hardwoods. To increase bobwhite density on the landscape, managers should reduce the amount of closed canopy hardwood forest. Furthermore, the spatially explicit age ratio we estimated could be used to target management towards increasing the recruitment of chicks into the autumn population. An SCR approach may require additional logistical and financial resources relative to other data collection methods, but it makes modeling spatial variation in density straightforward and can be used to gather data to simultaneously understand population structure, vital rates, and movement. © 2021 The Wildlife Society.     

A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models

Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal’s home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786–1.071) for females, 0.844 (0.703–0.975) for males, and 0.882 (0.779–0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758–1.024) for females, 0.825 (0.700–0.948) for males, and 0.863 (0.771–0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth rates suggest that Banff National Park’s population of grizzly bears requires continued conservation-oriented management actions.     

Examining Temporal Sample Scale and Model Choice with Spatial Capture-Recapture Models in the Common Leopard Panthera pardus

Many large carnivores occupy a wide geographic distribution, and face threats from habitat loss and fragmentation, poaching, prey depletion, and human wildlife-conflicts. Conservation requires robust techniques for estimating population densities and trends, but the elusive nature and low densities of many large carnivores make them difficult to detect. Spatial capture-recapture (SCR) models provide a means for handling imperfect detectability, while linking population estimates to individual movement patterns to provide more accurate estimates than standard approaches. Within this framework, we investigate the effect of different sample interval lengths on density estimates, using simulations and a common leopard (Panthera pardus) model system. We apply Bayesian SCR methods to 89 simulated datasets and camera-trapping data from 22 leopards captured 82 times during winter 2010–2011 in Royal Manas National Park, Bhutan. We show that sample interval length from daily, weekly, monthly or quarterly periods did not appreciably affect median abundance or density, but did influence precision. We observed the largest gains in precision when moving from quarterly to shorter intervals. We therefore recommend daily sampling intervals for monitoring rare or elusive species where practicable, but note that monthly or quarterly sample periods can have similar informative value. We further develop a novel application of Bayes factors to select models where multiple ecological factors are integrated into density estimation. Our simulations demonstrate that these methods can help identify the “true” explanatory mechanisms underlying the data. Using this method, we found strong evidence for sex-specific movement distributions in leopards, suggesting that sexual patterns of space-use influence density. This model estimated a density of 10.0 leopards/100 km² (95% credibility interval: 6.25–15.93), comparable to contemporary estimates in Asia. These SCR methods provide a guide to monitor and observe the effect of management interventions on leopards and other species of conservation interest.     

Detection distance and environmental factors in conservation detection dog surveys

Surveys using conservation detection dogs have grown increasingly popular as an efficient means to gather monitoring data, particularly for elusive and low-density species such as carnivores. Working with dogs can greatly increase the area surveyed for wildlife and the detection rate of survey targets. Due to the confounding effects of scent dispersion and dog movement, however, it can be difficult to estimate the area searched in a survey. Additionally, although detection dogs have been used in studies under a wide range of air temperature, humidity, and wind conditions, little research has examined how environmental factors affect detection dogs' effectiveness for wildlife surveys. Between 2003 and 2005, we trained 2 dogs to assist us with surveys for mammalian carnivore scats in northern California. We conducted controlled search trials to assess how the dogs' scat detection rates were affected by the distance of scats from the transect search line, as well as variation in six environmental factors. Both dogs detected >75% of scats located within 10 m, and the dogs' detection rates decreased with increasing distance of scats from the transect line. Among environmental factors, precipitation was the most important variable explaining variation in scat detection rates for both dogs. Precipitation likely degrades or removes scats from the landscape over time, and detection rates increase as scat begins to accumulate following the last substantial (>5 mm) rain event of the year. If scat accumulation is not controlled for in ecosystems with a strong seasonal pattern of rainfall, it could lead to considerable bias in study results. We recommend that researchers report the conditions under which conservation detection dog surveys took place and analyze how detection rates vary as a function of distance, temperature, precipitation, humidity, wind, and other locally important environmental factors. © 2010 The Wildlife Society.     

Density estimates of two endangered nocturnal lemur species from northern Madagascar: new results and a comparison of commonly used methods

Very little information is known of the recently described Microcebus tavaratra and Lepilemur milanoii in the Daraina region, a restricted area in far northern Madagascar. Since their forest habitat is highly fragmented and expected to undergo significant changes in the future, rapid surveys are essential to determine conservation priorities. Using both distance sampling and capture-recapture methods, we estimated population densities in two forest fragments. Our results are the first known density and population size estimates for both nocturnal species. In parallel, we compare density results from four different approaches, which are widely used to estimate lemur densities and population sizes throughout Madagascar. Four approaches (King, Kelker, Muller and Buckland) are based on transect surveys and distance sampling, and they differ from each other by the way the effective strip width is estimated. The fifth method relies on a capture-mark-recapture (CMR) approach. Overall, we found that the King method produced density estimates that were significantly higher than other methods, suggesting that it generates overestimates and hence overly optimistic estimates of population sizes in endangered species. The other three distance sampling methods provided similar estimates. These estimates were similar to those obtained with the CMR approach when enough recapture data were available. Given that Microcebus species are often trapped for genetic or behavioral studies, our results suggest that existing data can be used to provide estimates of population density for that species across Madagascar.     

A local evaluation of the individual state‐space to scale up Bayesian spatial capture–recapture

Spatial capture–recapture models (SCR) are used to estimate animal density and to investigate a range of problems in spatial ecology that cannot be addressed with traditional nonspatial methods. Bayesian approaches in particular offer tremendous flexibility for SCR modeling. Increasingly, SCR data are being collected over very large spatial extents making analysis computational intensive, sometimes prohibitively so. To mitigate the computational burden of large‐scale SCR models, we developed an improved formulation of the Bayesian SCR model that uses local evaluation of the individual state‐space (LESS). Based on prior knowledge about a species’ home range size, we created square evaluation windows that restrict the spatial domain in which an individual's detection probability (detector window) and activity center location (AC window) are estimated. We used simulations and empirical data analyses to assess the performance and bias of SCR with LESS. LESS produced unbiased estimates of SCR parameters when the AC window width was ≥5σ (σ: the scale parameter of the half‐normal detection function), and when the detector window extended beyond the edge of the AC window by 2σ. Importantly, LESS considerably decreased the computation time needed for fitting SCR models. In our simulations, LESS increased the computation speed of SCR models up to 57‐fold. We demonstrate the power of this new approach by mapping the density of an elusive large carnivore—the wolverine (Gulo gulo)—with an unprecedented resolution and across the species’ entire range in Norway (> 200,000 km²). Our approach helps overcome a major computational obstacle to population and landscape‐level SCR analyses. The LESS implementation in a Bayesian framework makes the customization and fitting of SCR accessible for practitioners working at scales that are relevant for conservation and management.     

How Does Spatial Study Design Influence Density Estimates from Spatial Capture-Recapture Models?

When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR) models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2). Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.     

Human activity reduces niche partitioning among three widespread mesocarnivores

Anthropogenic disturbances can constrain the realized niche space of wildlife by inducing avoidance behaviors and altering community dynamics. Human activity might contribute to reduced partitioning of niche space by carnivores that consume similar resources, both by promoting tolerant species while also altering behavior of species (e.g. activity patterns). We investigated the influence of anthropogenic disturbance on habitat and dietary niche breadth and overlap among competing carnivores, and explored if altered resource partitioning could be explained by human‐induced activity shifts. To describe the diets of coyotes, bobcat, and gray foxes, we designed a citizen science program to collect carnivore scat samples in low‐ (‘wildland’) and high‐ (‘interface’) human‐use open space preserves, and obtained diet estimates using a DNA metabarcoding approach. Habitat use was determined at scat locations. We found that coyotes expanded habitat and dietary niche breadth in interface preserves, whereas bobcats and foxes narrowed both niche breadth measures. High human use was related to increased dietary niche overlap among all mesocarnivore pairs, increased coyote habitat overlap with bobcats and foxes, and a small reduction in habitat overlap between bobcats and foxes. The strongest increase in diet overlap was among coyotes and foxes, which was smaller in magnitude than their habitat overlap increase. Finally, coyote scats were more likely to contain nocturnal prey in interface preserves, whereas foxes appeared to reduce consumption of nocturnal prey. Our results suggest that dominant and generalist mesocarnivores may encroach on the niche space of subordinate mesocarnivores in areas with high human activity, and that patterns in resource use may be related to human‐induced activity shifts.     

Surveying carnivores at large spatial scales: a comparison of four broad-applied methods

Reliable methods to estimate species richness are very important to managers and conservationists because they provide key data to make the right decisions in conservation programmes. In the case of carnivore mammals, traditional methods, such as direct count censuses, are not useful since these animals are usually scarce, elusive and nocturnal. Difficulties in carnivore sampling are compounded when monitoring programmes are developed at large spatial scales, where high economic costs and field efforts are necessary to achieve reliable richness or abundance estimates. These problems have highlighted the need to find more effective carnivore survey methods, especially in regions with high rates of landscape change, such as the Mediterranean basin. The present study, performed in a typical Mediterranean area, was the first in Europe to test simultaneously the relative efficiencies of four broad-applied sampling methods to detect carnivore species at large spatial scales. Sign surveys based on scat detection, scent stations, camera-trapping and live-trapping were investigated. We compared efficiencies using biological parameters and by considering both the logistic and economic costs of each method. Overall, scent stations and sign surveys were the most efficient methods both in economic and logistic terms. In addition, the use of scent stations may be necessary to detect species rarely detected by scats. Detailed and extensive training programmes for conducting sign surveys and scent stations may overcome perceived problems thus enhancing the widespread use of both methods. Our results are applicable not only to other Mediterranean areas, but also to other habitats and regions of the world. More research into the suitability of these and other methods in relation to different landscapes, seasons and species is required.     

Assessing the homogeneity of individual scat detection probability using the bait-marking method on a monitored free-ranging carnivore population

Estimates of terrestrial carnivore populations are often based on information derived from scat collected during trail-based sampling. However, few attempts have been made to verify the homogeneity of individual scat detection probability because wild carnivore species seldom afford this opportunity. The present study aims to test this assumption on a free-ranging population of domestic cats (Felis silvestris catus), as this carnivore has ranging behaviours close enough to its wild ancestor to provide useful information for wild carnivore surveys. The homogeneity of scat detection probability was investigated using the bait-marking method on a previously monitored population of 142 individuals, composed of free-roaming house cats (43 %) and farm cats (57 %). An 11-km trail was walked twice a week over a 58-day period to individually feed cats with marked baits and to collect their faeces. From the 8,236 faeces expected to be dropped by cats over that period, less than 2 % were collected, and from the 215 baits distributed to 44 cats (31 % of the population), only 13.5 % of the expected marked faeces were found. Detectability of faeces producers did not differ between free-roaming house cats and farm cats, but faeces detection probability was linked with sex and reproductive status. This study, conducted on a monitored population of free-roaming carnivores, stresses that it is possible to make only cautious conclusions about population estimates supported by trail-based scat samplings, since only a few individuals may be responsible for many scat detections.     

Heterogeneous capture rates in low density populations and consequences for capture-recapture analysis of camera-trap data

Closed population capture-recapture analysis of camera-trap data has become the conventional method for estimating the abundance of individually recognisable cryptic species living at low densities, such as large felids. Often these estimates are the only information available to guide wildlife managers and conservation policy. Capture probability of the target species using camera traps is commonly heterogeneous and low. Published studies often report overall capture probabilities as low as 0.03 and fail to report on the level of heterogeneity in capture probability. We used simulations to study the effects of low and heterogeneous capture probability on the reliability of abundance estimates using the M_h jack-knife estimator within a closed-population capture-recapture framework. High heterogeneity in capture probability was associated with under- and over-estimates of true abundance. The use of biased abundance estimates could have serious conservation management consequences. We recommend that studies present capture frequencies of all sampled individuals so that policy makers can assess the reliability of the abundance estimates.     

Genetic sampling for estimating density of common species

Understanding population dynamics requires reliable estimates of population density, yet this basic information is often surprisingly difficult to obtain. With rare or difficult‐to‐capture species, genetic surveys from noninvasive collection of hair or scat has proved cost‐efficient for estimating densities. Here, we explored whether noninvasive genetic sampling (NGS) also offers promise for sampling a relatively common species, the snowshoe hare (Lepus americanus Erxleben, 1777), in comparison with traditional live trapping. We optimized a protocol for single‐session NGS sampling of hares. We compared spatial capture–recapture population estimates from live trapping to estimates derived from NGS, and assessed NGS costs. NGS provided population estimates similar to those derived from live trapping, but a higher density of sampling plots was required for NGS. The optimal NGS protocol for our study entailed deploying 160 sampling plots for 4 days and genotyping one pellet per plot. NGS laboratory costs ranged from approximately $670 to $3000 USD per field site. While live trapping does not incur laboratory costs, its field costs can be considerably higher than for NGS, especially when study sites are difficult to access. We conclude that NGS can work for common species, but that it will require field and laboratory pilot testing to develop cost‐effective sampling protocols.     

Feeding ecological knowledge: the underutilised power of faecal DNA approaches for carnivore diet analysis

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Non-invasively determined multi-site variation in pine marten <Emphasis Type="Italic">Martes martes</Emphasis> density,a recovering carnivore in Europe

Pine martens (Martes martes) are subject to national and international conservation legislation throughout most of their European range. Yet population density and abundance estimates, which are a key component of effective conservation management, are lacking in many countries. In this study, a large-scale non-invasive survey was undertaken in 14 forested study sites throughout Ireland to assess variation in pine marten density and abundance. Pine marten hair samples were collected in each study site and analysed using genetic techniques to determine individual identity data. Density and abundance estimates were obtained using spatially explicit capture-recapture models and CAPWIRE. Across all study sites, a total of 93 individual pine marten were identified and captured 217 times. Estimated pine marten density varied from 0 to 2.60 individuals per km² of forested habitat, with all but a single site having estimated densities of ≤1 pine marten per km² of forest habitat. Mean population abundance estimates across all study sites ranged from 0 to 27 individuals. Spatially explicit capture-recapture models on combined data across all 14 study sites provided a mean density estimate of 0.64 (95% CI 0.49–0.81). Combining this with data on the current distribution and estimated area of forest habitat occupied by the species in Ireland, the total pine marten population abundance of pine marten in Ireland was estimated at 3043 (95% CI 2330–3852) individuals. This research has conducted the largest scale investigation of pine marten density and abundance in any part of its global distribution and provided an improved basis for future population assessment and monitoring of this species.     

Landscape Analysis of Bobcat Habitat in the Northern Lower Peninsula of Michigan

ABSTRACT Controversy over bobcat (Lynx rufus) management in the northern Lower Peninsula of Michigan (NLP), USA, stimulated a need for information on the distribution of Michigan bobcats. From March 2003 to October 2004, we conducted a radiotelemetry and scentstation survey study of bobcats in the NLP. We developed a spatial model to predict bobcat distribution throughout the NLP based on bobcat area requirements, habitat and landscape variables derived from remotely sensed land-cover data, and a multivariate distance statistic. Bobcat 50% minimum convex polygon core areas were comprised of more lowland forest (51%), nonforested wetlands (9%), and streams (3%) than the surrounding NLP. The NLP was comprised primarily of upland forest (44%) and field (32%). Habitat in the northeast and central regions of the NLP was most similar to the habitat composition of bobcat core areas. This model will be useful in aiding Michigan wildlife management agencies with assessing the status and distribution of the NLP bobcat population by identifying areas important to bobcats and supporting the development of regional strategies for carnivore conservation.     

Population density and abundance of sympatric large carnivores in the lowland tropical evergreen forest of Indian Eastern Himalayas

Low density occurrence of large carnivore species and direct hunting of predators and prey make carnivore conservation complex. Vital baseline information on population status of large carnivores is still deficient in most forests of eastern Himalaya, which are known to be the biodiversity hotspots. To fill this information gap, we estimated the large carnivore population status and abundance in an intricate eastern Himalayan lowland tropical forest in Pakke Tiger Reserve, Arunachal Pradesh. Population status and abundance estimates of tigers and leopards were made through individual identification using closed capture-recapture sampling. To estimate the dhole abundance photographic encounter rate was used. For individually non-identifiable species photographic rate seemed to correlate well with animal abundance. The estimated tiger and leopard density through 1/2 MMDM was 2.14 ± 0.04/100 km² and 2.99 ± 1.13/100 km² respectively. Maximum likelihood estimates shows density of tiger 1.86 ± 0.7 and for leopard 2.82 ± 1.2.The estimated dhole abundance was (N) 10.6 ± 0.94, and density 6.62 ± 0.58 individuals in 100 km². Further, occupancy estimation of large carnivores may be tried along with assessing the comparative efficacy of other population estimation methods to establish better monitoring methods for this region.