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 (δ). 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.
Highlights
Capture–recapture (CR) methods are considered reference methods in population size estimates (Silvy, 2012)
The partial identification extension that we propose for general‐ ized spatial mark–resight is based on the (Whittington et al, 2017) model that included marking and resight‐ ing processes in the model, as well as the integration of telemetry data
We demonstrate the use of the Generalized spatial mark–resight (Gen‐Spatial mark–resight (SMR))‐ID model to deal with incomplete marked individual identification, using a red fox Vulpes vulpes empirical dataset
Summary
Capture–recapture (CR) methods are considered reference methods in population size estimates (Silvy, 2012). Some of the assumptions, such as homogeneity in capture probability of individuals are violated by the implicit heterogeneity derived from the location of the activity center of each animal in relation to each trap or detection device. Another limitation of stan‐ dard CR methods is that they cannot be used for density estimation because the effective sampling area is unknown (Otis, Burnham, White, & Anderson, 1978; Karanth & Nichols, 1998; Parmenter et al, 2003; Soisalo & Cavalcanti, 2006). In camera‐traps studies, the majority of detected species typically do not have individually recognizable natural or artificial marks, making it impossible to develop the capture histories required by SCR models
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