Comparing capture-recapture, mark-resight, and spatial mark-resight models for estimating puma densities via camera traps

Rich, Lindsey N.; Kelly, Marcella J.; Sollmann, Rahel; Noss, Andrew J.; Maffei, Leonardo; Arispe, Rosario; Paviolo, Agustin Javier; Angelo, Carlos De; Blanco, Yamil Edgardo Di; Bitetti, Mario S. Di

doi:10.1644/13-mamm-a-126

Cited by 87 publications

(102 citation statements)

References 32 publications

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“…The second strategy uses alternative modelling, such as mark-resight models that do not require all detected animals to be tagged (Rich et al 2014). As implemented by Rich et al (2014), only those detections for which independent observers fully agreed on ID would be categorised as marked.…”

Section: Discussionmentioning

confidence: 99%

“…As implemented by Rich et al (2014), only those detections for which independent observers fully agreed on ID would be categorised as marked. Critically, we had no cases of complete agreement on any single assigned ID, thus precluding mark-resight analysis.…”

Section: Discussionmentioning

confidence: 99%

“…Both analytical methods and field techniques have been proposed to deal with this potential issue. Rich et al (2014) proposed mark-resight analyses (Arnason et al 1991), which required that only a subset of detected individuals are assigned an ID. This method is potentially ideal, assuming at least some subset of cougars in a population has distinguishing features that allow for reliable photo identification.…”

Section: Introductionmentioning

confidence: 99%

“…Despite this, studies have continued to report photo-CMR estimates of cougar abundance or density, and there has been little research that directly addresses the method's potential problems or evaluates its proposed solutions. Our goals were to (1) evaluate researcher ability to individually identify cougars in remote camera images following the Kelly et al (2008) approach, (2) examine the effects that differing detection histories may have on density estimates and (3) examine the practicality of some proposed methods such as mark-resight (Rich et al 2014) and increasing photos per detection (McBride and Sensor 2015).…”

Section: Introductionmentioning

confidence: 99%

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

Alexander

Gese

2018

Wildl. Res.

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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 km 2 (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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Alexander

Gese

2018

Wildl. Res.

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“…Any feature that uniquely identifies an animal, allowing previous captured animals to be recognized, can be used to "mark" the animal. Examples of such "natural" marks include DNA fingerprinting (Puechmaille and Petit 2007), dorsal fin contours (Currey et al 2008), fur patterns (Rich et al 2014) or distinctive scars or other marks. We use "traps" and "detectors" somewhat interchangeably, preferring "detectors" to convey the idea that animals do not need to be physically trapped.…”

Section: Modelling Frameworkmentioning

confidence: 99%

From distance sampling to spatial capture–recapture

Borchers

Marques

2017

AStA Adv Stat Anal

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Distance sampling and capture-recapture are the two most widely used wildlife abundance estimation methods. capture-recapture methods have only recently incorporated models for spatial distribution and there is an increasing tendency for distance sampling methods to incorporated spatial models rather than to rely on partly design-based spatial inference. In this overview we show how spatial models are central to modern distance sampling and that spatial capture-recapture models arise as an extension of distance sampling methods. Depending on the type of data recorded, they can be viewed as particular kinds of hierarchical binary regression, Poisson regression, survival or time-to-event models, with individuals' locations as latent variables and a spatial model as the latent variable distribution. Incorporation of spatial models in these two methods provides new opportunities for drawing explicitly spatial inferences. Areas of likely future development include more sophisticated spatial and spatio-temporal modelling of individuals' locations and movements, new methods for integrating spatial capture-recapture and other kinds of ecological survey data, and methods for dealing with the recapture uncertainty that often arise when "capture" consists of detection by a remote device like a camera trap or microphone.

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Sampling bias in snow leopard population estimation studies

et al. 2019

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Accurate assessments of the status of threatened species and their conservation planning require reliable estimation of their global populations and robust monitoring of local population trends. We assessed the adequacy and suitability of studies in reliably estimating the global snow leopard (Panthera uncia) population. We compiled a dataset of all the peer-reviewed published literature on snow leopard population estimation. Metadata analysis showed estimates of snow leopard density to be a negative exponential function of area, suggesting that study areas have generally been too small for accurate density estimation, and sampling has often been biased towards the best habitats. Published studies are restricted to six of the 12 range countries, covering only 0.3-0.9% of the presumed global range of the species. Re-sampling of camera trap data from a relatively large study site (c.1684 km 2 ) showed that small-sized study areas together with a bias towards good quality habitats in existing studies may have overestimated densities by up to five times. We conclude that current information is biased and inadequate for generating a reliable global population estimate of snow leopards. To develop a rigorous and useful baseline and to avoid pitfalls, there is an urgent need for (a) refinement of sampling and analytical protocols for population estimation of snow leopards (b) agreement and coordinated use of standardized sampling protocols amongst researchers and governments across the range, and (c) sampling larger and under-represented areas of the snow leopard's global range.

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Comparing capture-recapture, mark-resight, and spatial mark-resight models for estimating puma densities via camera traps

Cited by 87 publications

References 32 publications

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

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

From distance sampling to spatial capture–recapture

Sampling bias in snow leopard population estimation studies

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