Dataset Information

Generalized spatial mark-resight models with incomplete identification: An application to red fox density estimates.

ABSTRACT: The estimation of abundance of wildlife populations is an essential part of ecological research and monitoring. Spatially explicit capture-recapture (SCR) models are widely used for abundance and density estimation, frequently through individual identification of target species using camera-trap sampling.Generalized spatial mark-resight (Gen-SMR) is a recently developed SCR extension that allows for abundance estimation when only a subset of the population is recognizable by artificial or natural marks. However, in many cases, it is not possible to read the marks in camera-trap pictures, even though individuals can be recognized as marked. We present a new extension of Gen-SMR that allows for this type of incomplete identification.We used simulation to assess how the number of marked individuals and the individual identification rate influenced bias and precision. We demonstrate the model's performance in estimating red fox (Vulpes vulpes) density with two empirical datasets characterized by contrasting densities and rates of identification of marked individuals. According to the simulations, accuracy increases with the number of marked individuals (m), but is less sensitive to changes in individual identification rate (?). In our case studies of red fox density estimation, we obtained a posterior mean of 1.60 (standard deviation SD: 0.32) and 0.28 (SD: 0.06) individuals/km², in high and low density, with an identification rate of 0.21 and 0.91, respectively.This extension of Gen-SMR is broadly applicable as it addresses the common problem of incomplete identification of marked individuals during resighting surveys.

SUBMITTER: Jimenez J

PROVIDER: S-EPMC6476752 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Generalized spatial mark-resight models with incomplete identification: An application to red fox density estimates.

Jimenez Jose J Chandler Richard R Tobajas Jorge J Descalzo Esther E Mateo Rafael R Ferreras Pablo P

Ecology and evolution 20190322 8

The estimation of abundance of wildlife populations is an essential part of ecological research and monitoring. Spatially explicit capture-recapture (SCR) models are widely used for abundance and density estimation, frequently through individual identification of target species using camera-trap sampling.Generalized spatial mark-resight (Gen-SMR) is a recently developed SCR extension that allows for abundance estimation when only a subset of the population is recognizable by artificial or natura ...[more]

PMID: 31031940

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Project description:Camera traps are used increasingly to estimate population density for elusive and difficult to observe species. A standard practice for mammalian surveys is to place cameras on roads, trails, and paths to maximize detections and/or increase efficiency in the field. However, for many species it is unclear whether track-based camera surveys provide reliable estimates of population density.Understanding how the spatial arrangement of camera traps affects population density estimates is of key interest to contemporary conservationists and managers given the rapid increase in camera-based wildlife surveys.We evaluated the effect of camera-trap placement, using several survey designs, on density estimates of a widespread mesopredator, the red fox Vulpes vulpes, over a two-year period in a semi-arid conservation reserve in south-eastern Australia. Further, we used the certainty in the identity and whereabouts of individuals (via GPS collars) to assess how resighting rates of marked foxes affect density estimates using maximum likelihood spatially explicit mark-resight methods.Fox detection rates were much higher at cameras placed on tracks compared with off-track cameras, yet in the majority of sessions, camera placement had relatively little effect on point estimates of density. However, for each survey design, the precision of density estimates varied considerably across sessions, influenced heavily by the absolute number of marked foxes detected, the number of times marked foxes was resighted, and the number of detection events of unmarked foxes.Our research demonstrates that the precision of population density estimates using spatially explicit mark-resight models is sensitive to resighting rates of identifiable individuals. Nonetheless, camera surveys based either on- or off-track can provide reliable estimates of population density using spatially explicit mark-resight models. This underscores the importance of incorporating information on the spatial behavior of the subject species when planning camera-trap surveys.

Project description:Abundance estimation of carnivore populations is difficult and has prompted the use of non-invasive detection methods, such as remotely-triggered cameras, to collect data. To analyze photo data, studies focusing on carnivores with unique pelage patterns have utilized a mark-recapture framework and studies of carnivores without unique pelage patterns have used a mark-resight framework. We compared mark-resight and mark-recapture estimation methods to estimate bobcat (Lynx rufus) population sizes, which motivated the development of a new "hybrid" mark-resight model as an alternative to traditional methods. We deployed a sampling grid of 30 cameras throughout the urban southern California study area. Additionally, we physically captured and marked a subset of the bobcat population with GPS telemetry collars. Since we could identify individual bobcats with photos of unique pelage patterns and a subset of the population was physically marked, we were able to use traditional mark-recapture and mark-resight methods, as well as the new "hybrid" mark-resight model we developed to estimate bobcat abundance. We recorded 109 bobcat photos during 4,669 camera nights and physically marked 27 bobcats with GPS telemetry collars. Abundance estimates produced by the traditional mark-recapture, traditional mark-resight, and "hybrid" mark-resight methods were similar, however precision differed depending on the models used. Traditional mark-recapture and mark-resight estimates were relatively imprecise with percent confidence interval lengths exceeding 100% of point estimates. Hybrid mark-resight models produced better precision with percent confidence intervals not exceeding 57%. The increased precision of the hybrid mark-resight method stems from utilizing the complete encounter histories of physically marked individuals (including those never detected by a camera trap) and the encounter histories of naturally marked individuals detected at camera traps. This new estimator may be particularly useful for estimating abundance of uniquely identifiable species that are difficult to sample using camera traps alone.

Dataset Information

Generalized spatial mark-resight models with incomplete identification: An application to red fox density estimates.

Publications

Generalized spatial mark-resight models with incomplete identification: An application to red fox density estimates.

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