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  5. Population density of European wildcats in a pre-alpine area (northeast Italy) and an assessment of estimate robustness

Population density of European wildcats in a pre-alpine area (northeast Italy) and an assessment of estimate robustness

Author(s)
Fonda, Federica
Bacaro, Giovanni
Battistella, Silvia
Chiatante, Gianpasquale  
Pecorella, Stefano
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Date Issued
2022
Type
article
Volume
67
Issue
1
Start Page
9
End Page
20
DOI
10.1007/s13364-021-00609-z
Journal
MAMMAL RESEARCH  
Abstract
While population density is a basic demographic parameter, it is rarely available for the elusive European wildcat, despite its wide distribution. Italy hosts at least five different wildcat populations, and little information is available for the wildcats inhabiting the northeast of the Italian peninsula. With the aim to provide the first report on European wildcat population density, we used spatially explicit capture-recapture models applied to camera trapping data in a pre-alpine area in NE Italy. The survey was carried out from May 18th to September 14th, 2015, using 31 camera traps distributed within a 1 × 1 km grid, placing a single camera per km2. We collected 32 videos of wildcats, corresponding to a total of eleven individuals. Density ± SE estimate was 0.35 ± 0.12 individuals per km2, with the encounter probability (g0) equal to 0.10 ± 0.03, and the spatial scale (σ) equal to 461 ± 62 m, corresponding to a mean home range size of 3.36 km2. In addition, to evaluate our sampling design and the robustness of our estimates, we simulated data generation and fitted SECR models under several realistic combinations of number and spacing of detectors, and sampling efforts. Considering the relative standard errors and relative bias, our sampling design produced robust estimates, whereas in scenarios with short sampling periods or greater spacing of detectors, the estimates were inadequate. Our study provides previously unavailable data on the biology of the European wildcat from NE Italy and some important considerations concerning sampling design to plan future research.
Handle
http://hdl.handle.net/2067/49788
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