Spatially explicit capture–recapture analysis of bobcat (Lynx rufus) density: implications for mesocarnivore monitoring

2015 ◽  
Vol 42 (5) ◽  
pp. 394 ◽  
Author(s):  
Daniel H. Thornton ◽  
Charles E. Pekins
Keyword(s):  
Density Estimation ◽  
Large Scale ◽  
Local Density ◽  
Camera Traps ◽  
Camera Trapping ◽  
Lynx Rufus ◽  
Spatially Explicit ◽  
Density Estimates ◽  
Capture Recapture ◽  
Study Sites

Context Accurate density estimation is crucial for conservation and management of elusive species. Camera-trapping may provide an efficient method for density estimation, particularly when analysed with recently developed spatially explicit capture–recapture (SECR) models. Although camera-traps are employed extensively to estimate large carnivore density, their use for smaller carnivores has been limited. Moreover, while camera-trapping studies are typically conducted at local scales, the utility of analysing larger-scale patterns by combining multiple camera studies remains poorly known. Aims The goal of the present study was to develop a better understanding of the utility of SECR models and camera-trapping for the estimation of density of small carnivores at local and regional scales. Methods Based on data collected from camera-traps, we used SECR to examine density of bobcats (Lynx rufus) at four study sites in north-central Texas. We then combined our density estimates with previous estimates (from multiple methodologies) across the bobcat’s geographic range, and used linear regression to examine drivers of range-wide density patterns. Key results Bobcat densities averaged 13.2 per 100 km2 across all four study sites, and were lowest at the site in the most heavily modified landscape. Bobcat capture probability was positively related to forest cover around camera-trap sites. At the range-wide scale, 53% of the variation in density was explained by just two factors: temperature and longitude. Conclusions Our results demonstrate the utility of camera-traps, combined with SECR, to generate precise density estimates for mesocarnivores, and reveal the negative effects of landscape disturbance on bobcat populations. The associations revealed in our range-wide analysis, despite variability in techniques used to estimate density, demonstrate how a combination of multiple density estimates for a species can be used for large-scale inference. However, improvement in our understanding of biogeographic density patterns for mesocarnivores could be obtained from a greater number of camera-based density estimates across the range of a species, combined with meta-analytic techniques. Implications Camera-trapping and SECR should be more widely applied to generate local density estimates for many small and medium-sized carnivores, where at least a portion of the individuals are identifiable. If such estimates are more widely obtained, meta-analytic techniques could be used to test biogeographic predictions or for large-scale monitoring efforts.

scholarly journals Spatially Explicit Capture-Recapture Through Camera Trapping: A Review of Benchmark Analyses for Wildlife Density Estimation

2020 ◽  
Vol 8 ◽  
Author(s):  
Austin M. Green ◽  
Mark W. Chynoweth ◽  
Çağan Hakkı Şekercioğlu
Keyword(s):  
Density Estimation ◽  
Study Design ◽  
New Technologies ◽  
Model Development ◽  
Population Monitoring ◽  
Camera Traps ◽  
Camera Trapping ◽  
Individual Identification ◽  
Spatially Explicit ◽  
Capture Recapture

Camera traps have become an important research tool for both conservation biologists and wildlife managers. Recent advances in spatially explicit capture-recapture (SECR) methods have increasingly put camera traps at the forefront of population monitoring programs. These methods allow for benchmark analysis of species density without the need for invasive fieldwork techniques. We conducted a review of SECR studies using camera traps to summarize the current focus of these investigations, as well as provide recommendations for future studies and identify areas in need of future investigation. Our analysis shows a strong bias in species preference, with a large proportion of studies focusing on large felids, many of which provide the only baseline estimates of population density for these species. Furthermore, we found that a majority of studies produced density estimates that may not be precise enough for long-term population monitoring. We recommend simulation and power analysis be conducted before initiating any particular study design and provide examples using readily available software. Furthermore, we show that precision can be increased by including a larger study area that will subsequently increase the number of individuals photo-captured. As many current studies lack the resources or manpower to accomplish such an increase in effort, we recommend that researchers incorporate new technologies such as machine-learning, web-based data entry, and online deployment management into their study design. We also cautiously recommend the potential of citizen science to help address these study design concerns. In addition, modifications in SECR model development to include species that have only a subset of individuals available for individual identification (often called mark-resight models), can extend the process of explicit density estimation through camera trapping to species not individually identifiable.

scholarly journals Abundance and density estimates for common leopard Panthera pardus and clouded leopard Neofelis nebulosa in Manas National Park, Assam, India

Oryx ◽  
2013 ◽  
Vol 48 (1) ◽  
pp. 149-155 ◽  
Author(s):  
Jimmy Borah ◽  
Tridip Sharma ◽  
Dhritiman Das ◽  
Nilmani Rabha ◽  
Niraj Kakati ◽  
...  
Keyword(s):  
National Park ◽  
Camera Traps ◽  
Camera Trapping ◽  
Spatially Explicit ◽  
Panthera Pardus ◽  
Density Estimates ◽  
Clouded Leopard ◽  
Neofelis Nebulosa ◽  
Capture Recapture ◽  
The Common

AbstractEffective conservation of rare carnivores requires reliable estimates of population density for prioritizing investments and assessing the effectiveness of conservation interventions. We used camera traps and capture–recapture analysis to provide the first reliable abundance and density estimates for the common leopard Panthera pardus and clouded leopard Neofelis nebulosa in Manas National Park, India. In 57 days of camera trapping, with a total of 4,275 camera-trap days, we photo-captured 27 individually identified common leopards (11 males, 13 females and three unidentified), and 16 clouded leopards (four males, five females and seven unidentified). The abundance estimates using the Mh jackknife and Pledger model Mh were 47.0 and 35.6, respectively, for the common leopard, and 21.0 and 25.0, respectively, for the clouded leopard. Density estimates using maximum likelihood spatially-explicit capture–recapture were 3.4 ± SE 0.82 and 4.73 ± SE 1.43 per 100 km2 for the common and clouded leopards, respectively. Spatially-explicit capture–recapture provided more realistic density estimates compared with those obtained from conventional methods. Our data indicates that camera trapping using a capture–recapture framework is an effective tool for assessing population sizes of cryptic and elusive carnivores such as the common and clouded leopards. The study has established a baseline for the long-term monitoring programme for large carnivores in Manas National Park.

scholarly journals Density Estimates of Unmarked Large Mammals at Camera Traps Vary among Models, Species, and Years, Signalling Importance of Model Assumptions

2021 ◽  
Author(s):  
Jason Fisher ◽  
Joanna Burgar ◽  
Melanie Dickie ◽  
Cole Burton ◽  
Rob Serrouya
Keyword(s):  
Density Estimation ◽  
Black Bear ◽  
Camera Traps ◽  
Mammal Species ◽  
Density Estimates ◽  
Movement Rates ◽  
Social Species ◽  
Marked Variability ◽  
Capture Recapture ◽  
Best Fitting

Density estimation is a key goal in ecology but accurate estimates remain elusive, especially for unmarked animals. Data from camera-trap networks combined with new density estimation models can bridge this gap but recent research has shown marked variability in accuracy, precision, and concordance among estimators. We extend this work by comparing estimates from two different classes of models: unmarked spatial capture-recapture (spatial count, SC) models, and Time In Front of Camera (TIFC) models, a class of random encounter model. We estimated density for four large mammal species with different movement rates, behaviours, and sociality, as these traits directly relate to model assumptions. TIFC density estimates were typically higher than SC model estimates for all species. Black bear TIFC estimates were ~ 10-fold greater than SC estimates. Caribou TIFC estimates were 2-10 fold greater than SC estimates. White-tailed deer TIFC estimates were up to 100-fold greater than SC estimates. Differences of 2-5 fold were common for other species in other years. SC estimates were annually stable except for one social species; TIFC estimates were highly annually variable in some cases and consistent in others. Tests against densities obtained from DNA surveys and aerial surveys also showed variable concordance and divergence. For gregarious animals TIFC may outperform SC due to the latter model’s assumption of independent activity centres. For curious animals likely to investigate camera traps, SC may outperform TIFC, which assumes animal behavior is unaffected by cameras. Unmarked models offer great possibilities, but a pragmatic approach employs multiple estimators where possible, considers the ecological plausibility of assumptions, and uses an informed multi-inference approach to seek estimates from models with assumptions best fitting a species’ biology.

scholarly journals Identifying individual cougars (Puma concolor) in remote camera images – implications for population estimates

2018 ◽  
Vol 45 (3) ◽  
pp. 274 ◽  
Author(s):  
Peter D. Alexander ◽  
Eric M. Gese
Keyword(s):  
Puma Concolor ◽  
Camera Traps ◽  
Camera Trapping ◽  
Field Methods ◽  
Density Estimates ◽  
North West ◽  
Photo Identification ◽  
Matching Process ◽  
Capture Recapture ◽  
Remote Camera

Context Several studies have estimated cougar (Puma concolor) abundance using remote camera trapping in conjunction with capture–mark–recapture (CMR) type analyses. However, this methodology (photo-CMR) requires that photo-captured individuals are individually recognisable (photo identification). Photo identification is generally achieved using naturally occurring marks (e.g. stripes or spots) that are unique to each individual. Cougars, however, are uniformly pelaged, and photo identification must be based on subtler attributes such as scars, ear nicks or body morphology. There is some debate as to whether these types of features are sufficient for photo-CMR, but there is little research directly evaluating its feasibility with cougars. Aim We aimed to examine researchers’ ability to reliably identify individual cougars in photographs taken from a camera-trapping survey, in order to evaluate the appropriateness of photo-CMR for estimating cougar abundance or CMR-derived parameters. Methods We collected cougar photo detections using a grid of 55 remote camera traps in north-west Wyoming, USA. The photo detections were distributed to professional biologists working in cougar research, who independently attempted to identify individuals in a pairwise matching process. We assessed the level to which their results agreed, using simple percentage agreement and Fleiss’s kappa. We also generated and compared spatially explicit capture–recapture (SECR) density estimates using their resultant detection histories. Key results There were no cases where participants were in full agreement on a cougar’s ID. Agreement in photo identification among participants was low (n = 7; simple agreement = 46.7%; Fleiss’s kappa = 0.183). The resultant SECR density estimates ranged from 0.7 to 13.5 cougars per 100 km2 (n = 4; s.d. = 6.11). Conclusion We were unable to produce reliable estimates of cougar density using photo-CMR, due to our inability to accurately photo-tag detected individuals. Abundance estimators that do not require complete photo-tagging (i.e. mark–resight) were also infeasible, given the lack of agreement on any single cougar’s ID. Implications This research suggested that there are substantial problems with the application of photo-CMR to estimate the size of cougar populations. Although improvements in camera technology or field methods may resolve these issues, researchers attempting to use this method on cougars should be cautious.

scholarly journals Leopard Density Estimation within an Enclosed Reserve, Namibia Using Spatially Explicit Capture-Recapture Models

Animals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 724
Author(s):  
Noack ◽  
Heyns ◽  
Rodenwoldt ◽  
Edwards
Keyword(s):  
Management Strategies ◽  
Camera Traps ◽  
Spatially Explicit ◽  
Conservation Areas ◽  
Term Survival ◽  
New Class ◽  
Capture Recapture ◽  
Wildlife Populations ◽  
Effective Conservation

The establishment of enclosed conservation areas are claimed to be the driving force for the long-term survival of wildlife populations. Whilst fencing provides an important tool in conservation, it simultaneously represents a controversial matter as it stops natural migration processes, which could ultimately lead to inbreeding, a decline in genetic diversity and local extinction if not managed correctly. Thus, wildlife residing in enclosed reserves requires effective conservation and management strategies, which are strongly reliant on robust population estimates. Here, we used camera traps combined with the relatively new class of spatially explicit capture-recaptured models (SECR) to produce the first reliable leopard population estimate for an enclosed reserve in Namibia. Leopard density was estimated at 14.51 leopards/100 km2, the highest recorded density in Namibia to date. A combination of high prey abundance, the absence of human persecution and a lack of top-down control are believed to be the main drivers of the recorded high leopard population. Our results add to the growing body of literature which suggests enclosed reserves have the potential to harbour high densities and highlight the importance of such reserves for the survival of threatened species in the future.

scholarly journals A Spatially Explicit Capture–Recapture Model for Partially Identified Individuals When Trap Detection Rate Is Less than One

2019 ◽  
Vol 71 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Soumen Dey ◽  
Mohan Delampady ◽  
K. Ullas Karanth ◽  
Arjun M. Gopalaswamy
Keyword(s):  
Detection Probability ◽  
Credible Interval ◽  
Camera Traps ◽  
Spatially Explicit ◽  
Panthera Tigris ◽  
Partial Identity ◽  
Proposed Model ◽  
Estimation Problems ◽  
Capture Recapture ◽  
Future Work

Spatially explicit capture–recapture (SECR) models have gained enormous popularity to solve abundance estimation problems in ecology. In this study, we develop a novel Bayesian SECR model that disentangles two processes: one is the process of animal arrival within a detection region, and the other is the process of recording this arrival by a given set of detectors. We integrate this complexity into an advanced version of a recent SECR model involving partially identified individuals (Royle JA. Spatial capture-recapture with partial identity. arXiv preprint arXiv:1503.06873, 2015). We assess the performance of our model over a range of realistic simulation scenarios and demonstrate that estimates of population size N improve when we utilize the proposed model relative to the model that does not explicitly estimate trap detection probability (Royle JA. Spatial capture-recapture with partial identity. arXiv preprint arXiv:1503.06873, 2015). We confront and investigate the proposed model with a spatial capture–recapture dataset from a camera trapping survey of tigers (Panthera tigris) in Nagarahole study area of southern India. Detection probability is estimated at 0.489 (with 95% credible interval (CI) [0.430, 0.543]) which implies that the camera traps are performing imperfectly and thus justifying the use of our model in real world applications. We discuss possible extensions, future work and relevance of our model to other statistical applications beyond ecology. AMS classification codes: 62F15, 92D40

Estimating jaguar (Panthera onca) density in a preserved coastal area of French Guiana

Mammalia ◽  
2018 ◽  
Vol 82 (2) ◽  
pp. 188-192 ◽  
Author(s):  
Matthis Petit ◽  
Thomas Denis ◽  
Ondine Rux ◽  
Cécile Richard-Hansen ◽  
Rachel Berzins
Keyword(s):  
Home Range ◽  
Coastal Area ◽  
French Guiana ◽  
Scale Parameter ◽  
Local Density ◽  
Home Range Size ◽  
Range Size ◽  
Spatially Explicit ◽  
Panthera Onca ◽  
Capture Recapture

AbstractKnowledge of the jaguar population is needed in French Guiana that faces an increase of human-jaguar conflicts. We carried out a camera trap survey to assess jaguar local density and home range size in a preserved coastal area of French Guiana. We ran spatially explicit capture recapture (SECR) models. In our model, the scale parameterσ, that is linked to the home range size, was larger for males (σ=3.87±0.59 SE km) than for females (σ=2.33±0.30 SE km). The assessed jaguar density was 3.22±0.87 SE ind. 100 km−2, which should be considered as an optimal density in a French Guiana coastal area.

scholarly journals Bringing clarity to the clouded leopard Neofelis diardi: first density estimates from Sumatra

Oryx ◽  
2014 ◽  
Vol 48 (4) ◽  
pp. 536-539 ◽  
Author(s):  
Rahel Sollmann ◽  
Matthew Linkie ◽  
Iding A. Haidir ◽  
David W. Macdonald
Keyword(s):  
Mixed Forest ◽  
Camera Trap ◽  
Forest Loss ◽  
Data Sets ◽  
Panthera Tigris ◽  
Density Estimates ◽  
Clouded Leopard ◽  
Data Limitations ◽  
Capture Recapture ◽  
Study Sites

AbstractWe use data from camera-trap surveys for tigers Panthera tigris in combination with spatial capture–recapture models to provide the first density estimates for the Sunda clouded leopard Neofelis diardi on Sumatra. Surveys took place during 2004–2007 in the Kerinci landscape. Densities were 0.385–1.278 per 100 km2. We found no statistically significant differences in density among four study sites or between primary and mixed forest. Because the data sets are too small to account for differences in detection parameters between sexes, density is probably underestimated. Estimates are comparable to previous estimates of 1–2 per 100 km2 from the lowlands of central Sabah, on Borneo. Data limitations suggest that camera-trap surveys for Sunda clouded leopards require traps spaced more closely, to increase the chance of recaptures at different traps. Nevertheless, these first density estimates for clouded leopards on Sumatra provide a benchmark for measuring future conservation impact on an island that is undergoing rapid forest loss.

scholarly journals The use of camera traps for estimating jaguar Panthera onca abundance and density using capture/recapture analysis

Oryx ◽  
2004 ◽  
Vol 38 (2) ◽  
pp. 148-154 ◽  
Author(s):  
Scott C. Silver ◽  
Linde E. T. Ostro ◽  
Laura K. Marsh ◽  
Leonardo Maffei ◽  
Andrew J. Noss ◽  
...  
Keyword(s):  
Economic Value ◽  
Sampling Technique ◽  
Camera Traps ◽  
Dry Forest ◽  
Panthera Onca ◽  
Survey Technique ◽  
Capture Recapture ◽  
Amazonian Rainforest ◽  
Study Sites

Across their range jaguars Panthera onca are important conservation icons for several reasons: their important role in ecosystems as top carnivores, their cultural and economic value, and their potential conflicts with livestock. However, jaguars have historically been difficult to monitor. This paper outlines the first application of a systematic camera trapping methodology for abundance estimation of jaguars. The methodology was initially developed to estimate tiger abundance in India. We used a grid of camera traps deployed for 2 months, identified individual animals from their pelage patterns, and estimated population abundance using capture-recapture statistical models. We applied this methodology in a total of five study sites in the Mayan rainforest of Belize, the Chaco dry forest of Bolivia, and the Amazonian rainforest of Bolivia. Densities were 2.4–8.8 adult individuals per 100 km2, based on 7–11 observed animals, 16–37 combined ‘captures’ and ‘recaptures’, 486–2,280 trap nights, and sample areas of 107–458 km2. The sampling technique will be used to continue long-term monitoring of jaguar populations at the same sites, to compare with further sites, and to develop population models. This method is currently the only systematic population survey technique for jaguars, and has the potential to be applied to other species with individually recognizable markings.

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