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.

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 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 Activity pattern of medium and large sized mammals and density estimates of Cuniculus paca (Rodentia: Cuniculidae) in the Brazilian Pampa

2018 ◽  
Vol 78 (4) ◽  
pp. 697-705 ◽  
Author(s):  
C. Leuchtenberger ◽  
Ê. S. de Oliveira ◽  
L. P. Cariolatto ◽  
C. B. Kasper
Keyword(s):  
Activity Pattern ◽  
Human Impacts ◽  
Riparian Forest ◽  
Activity Patterns ◽  
Camera Traps ◽  
Total Density ◽  
Circadian Activity ◽  
Density Estimates ◽  
Capture Recapture ◽  
Pampa Region

Abstract Between July 2014 and April 2015, we conducted weekly inventories of the circadian activity patterns of mammals in Passo Novo locality, municipality of Alegrete, southern Brazil. The vegetation is comprised by a grassy-woody steppe (grassland). We used two camera traps alternately located on one of four 1 km transects, each separated by 1 km. We classified the activity pattern of species by the percentage of photographic records taken in each daily period. We identify Cuniculus paca individuals by differences in the patterns of flank spots. We then estimate the density 1) considering the area of riparian forest present in the sampling area, and 2) through capture/recapture analysis. Cuniculus paca, Conepatus chinga and Hydrochoerus hydrochaeris were nocturnal, Cerdocyon thous had a crepuscular/nocturnal pattern, while Mazama gouazoubira was cathemeral. The patterns of circadian activity observed for medium and large mammals in this Pampa region (southern grasslands) may reflect not only evolutionary, biological and ecological affects, but also human impacts not assessed in this study. We identified ten individuals of C. paca through skin spot patterns during the study period, which were recorded in different transects and months. The minimum population density of C. paca was 3.5 individuals per km2 (resident animals only) and the total density estimates varied from 7.1 to 11.8 individuals per km2, when considering all individuals recorded or the result of the capture/recapture analysis, respectively.

scholarly journals Density estimates and conservation of Leopardus pardalis southernmost population of the Atlantic Forest

2015 ◽  
Vol 105 (3) ◽  
pp. 367-371 ◽  
Author(s):  
Carlos B. Kasper ◽  
Fábio D. Mazim ◽  
José B. G. Soares ◽  
Tadeu G. de Oliveira
Keyword(s):  
Camera Traps ◽  
Southern Brazil ◽  
Density Estimates ◽  
Leopardus Pardalis ◽  
Low Frequencies ◽  
Habitat Integrity ◽  
Capture Recapture ◽  
Green Corridor ◽  
Term Maintenance

ABSTRACT Using camera traps and capture/recapture analyses we recorded the presence and abundance of cat species at Turvo State Park, in southern Brazil. Ocelot [Leopardus pardalis (Linnaeus, 1758)] population density was estimated for two areas of the park, with differing management profiles. Density estimates varied from 0.14 to 0.26 indiv. km2. Another five cat species were recorded at very low frequencies, precluding more accurate analyses. We estimate 24 to 45 ocelots occur in the reserve, which is probably too small for long-term maintenance of the population, if isolated. However, if habitat integrity and connectivity between the Park and the Green Corridor of Misiones is maintained, an estimated ocelot population of 1,680 individuals should have long-term viability.

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 Double-observer approach with camera traps: Towards an unbiased density estimation of unmarked animal populations

2021 ◽  
Author(s):  
Yoshihiro Nakashima ◽  
Shun Hongo ◽  
Kaori Mizuno ◽  
Gota Yajima ◽  
Zeun’s C.B. Dzefck
Keyword(s):  
Density Estimation ◽  
Detection Probability ◽  
Camera Traps ◽  
Activity Levels ◽  
Focal Area ◽  
Wide Range ◽  
Animal Activity ◽  
Capture Recapture ◽  
Estimation Models ◽  
Double Observer

AbstractCamera traps are a powerful research tool with a wide range of applications in animal ecology, conservation, and management. However, camera traps may not always detect animals passing in front, and the probability of successfully detecting animals (i.e. camera sensitivity) may vary spatially and temporarily. This constraint may create a substantial bias in estimating critical parameters, such as the density of unmarked populations or animal activity levels.We applied the ‘double-observer approach’ to estimate detection probability and correct potentially imperfect detection. This involved two camera traps being set up at a camera station to monitor the same focal area. The detection probability and the number of animal passes were concurrently estimated with a hierarchal capture-recapture model for stratified populations using a Bayesian framework. Monte Carlo simulations were performed to test the reliability. We then estimated the detection probabilities of a camera model (Browning Strike Force Pro) within an equilateral-triangle focal area (1.56 m2) for 12 ground-dwelling mammals in Japan and Cameroon. We also evaluated the possible difference in detection probability between daytime and nighttime by incorporating it as a covariate.We found that the double-observer approach reliably quantifies camera sensitivity and provides unbiased estimates of the number of animal passes, even when the detection probability varies among animal passes or camera stations. The camera sensitivity did not change between daytime and nighttime either in Japan or Cameroon, providing the first evidence that the number of animal passes per unit time may be a viable index of animal activity levels. Nonetheless, the camera traps missed animals within the focal area by 4 %–36%. Current density estimation models relying on perfect detection may underestimate animal density by the same order of magnitude.Our results showed that the double-observer approach might be effective in correcting imperfect camera sensitivity. The hierarchical capture-recapture model used here can estimate the distribution of detection probability and the number of animals passing concurrently, and thus, it is easily incorporated in the current density estimation models. We believe that this approach could make a wide range of camera-trapping studies more accurate.

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 Estimating the density of a small population of leopards (Panthera pardus) in central Iran using multi-session photographic‐sampling data

2021 ◽  
Author(s):  
Mohammad S. Farhadinia ◽  
Pouyan Behnoud ◽  
Kaveh Hobeali ◽  
Seyed Jalal Mousavi ◽  
Fatemeh Hosseini-Zavarei ◽  
...  
Keyword(s):  
Population Density ◽  
Density Estimation ◽  
Animal Movement ◽  
Small Population ◽  
Central Iran ◽  
Large Carnivores ◽  
Panthera Pardus ◽  
Demographic Stochasticity ◽  
Density Estimates ◽  
Capture Recapture

AbstractWest Asian drylands host a number of threatened large carnivores, including the leopard (Panthera pardus) which is limited generally to areas with low primary productivity. While conservation efforts have focused on these areas for several decades, reliable population density estimates are missing for many of them. Spatially explicit capture–recapture (SECR) methodology is a widely accepted population density estimation tool to monitor populations of large carnivores and it incorporates animal movement in the statistical estimation process. We employed multi-session maximum-likelihood SECR modeling to estimate the density of a small population of leopard in a mountainous environment surrounded by deserts in central Iran. During 6724 camera trap nights, we detected 8 and 5 independent leopards in 2012 and 2016 sessions, respectively. The top-performing model produced density estimates of 1.6 (95% CI = 0.9–2.9) and 1.0 (95% CI = 0.6–1.6) independent leopards/100 km2 in 2012 and 2016, respectively. Both sex and season had substantial effects on spatial scale (σ), with larger movements recorded for males, and during winter. The estimates from our density estimation exercise represent some of the lowest densities across the leopard global range and strengthen the notion that arid habitats support low densities of the species. These small populations are vulnerable to demographic stochasticity, and monitoring temporal changes in their population density and composition is a critical tool in assisting conservation managers to better understand their population performance.

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.

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