In Switzerland, the European wildcat (), a native felid, is protected by national law. In recent decades, the wildcat has slowly returned to much of its original range and may have even expanded into new areas that were not known to be occupied before. For the implementation of efficient conservation actions, reliable information about the status and trend of population size and density is crucial. But so far, only one reliable estimate of density in Switzerland was produced in the northern Swiss Jura Mountains. Wildcats are relatively rare and elusive, but camera trapping has proven to be an effective method for monitoring felids. We developed and tested a monitoring protocol using camera trapping in the northern Jura Mountains (cantons of Bern and Jura) in an area of 100 km. During 60 days, we obtained 105 pictures of phenotypical wildcats of which 98 were suitable for individual identification. We identified 13 individuals from both sides and, additionally, 5 single right-sided flanks and 3 single left-sided flanks that could not be matched to unique individuals. We analyzed the camera-trap data using the R package multimark, which has been extended to include a novel spatial capture-recapture model for encounter histories that include multiple "noninvasive" marks, such as bilaterally asymmetrical left- and right-sided flanks, that can be difficult (or impossible) to reliably match to individuals. Here, we present this model in detail for the first time. Based on a "semi-complete" data likelihood, the model is less computationally demanding than Bayesian alternatives that rely on a data-augmented complete data likelihood. The spatially explicit capture-recapture model estimated a wildcat density (95% credible interval) of 26 (17-36) per 100 km suitable habitat. Our integrated model produced higher abundance and density estimates with improved precision compared to single-sided analyses, suggesting spatially explicit capture-recapture methods with multiple "noninvasive" marks can improve our ability to monitor wildcat population status.
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http://dx.doi.org/10.1002/ece3.6990 | DOI Listing |
Animals (Basel)
January 2025
Ministry of Education Key Laboratory for Ecology of Tropical Islands, College of Life Sciences, Hainan Normal University, Haikou 571158, China.
Freshwater turtle species preservation relies on understanding their population dynamics and geographical distribution. Amur softshell turtles (ASTs []) are poorly protected due to insufficient awareness and the population in Northeastern China has experienced a steep decline compared to previous years. This study aims to investigate the population density and structure of ASTs in the Jewellery Island area of the Ussuri River in Northeast China using continuous-time capture-recapture methods in closed populations.
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January 2025
Government of Alberta, Forestry and Parks Canmore Alberta Canada.
Ecology
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School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, UK.
Data integration, the joint statistical analysis of data from different observation platforms, is pivotal for data-hungry disciplines such as spatial ecology. Pooled data types obtained from the same underlying process, analyzed jointly, can improve both precision and accuracy in models of species distributions and species-habitat associations. However, the integration of telemetry and spatial survey data has proved elusive because of the fundamentally different analytical approaches required by these two data types.
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Wildlife Counts, Nairobi, Kenya.
Regular population monitoring of imperilled charismatic species such as large carnivores is critical for conservation. However, the role of monitoring in conservation is frequently diminished due to: 1) surveys being implemented in isolation, 2) limited on-ground-capacity leading to infrequent monitoring, and 3) inappropriate methods being applied. Wildlife monitoring is often resource-intensive and the utility and cost of different field protocols is rarely reported.
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October 2024
Department of Biology and Centre d'Études Nordiques, Université Laval, 1045 Avenue de la Médecine, Québec, QC G1V 0A6, Canada.
Space use by small mammals should mirror their immediate needs for food and predator shelters but can also be influenced by seasonal changes in biotic and abiotic factors. Lemmings are keystone species of the tundra food web, but information on their spatial distribution in relation to habitat heterogeneity is still scant, especially at a fine scale. In this study, we used spatially explicit capture-recapture methods to determine how topography, hydrology, vegetation, and soil characteristics influence the fine-scale spatial variations in summer density of brown lemmings ().
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