Density and activity patterns of Pallas's cats, Otocolobus manul, in central Mongolia

Autor: Andrea Vendramin, Giovanni Bombieri, Claudio Augugliaro, Clayton K. Nielsen, Stefano Anile, Bariushaa Munkhtsog, Fabio Dartora
Přispěvatelé: Anile, S, Augugliaro, C, Munkhtsog, B, Dartora, F, Vendramin, A, Bombieri, G, Nielsen, CK
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Popis: Context. The ranges of many small, at-risk felid species occur almost entirely in unprotected areas, where research efforts are minimal; hence data on their density and activity patterns are scare. Aims. We estimated density and activity patterns of Pallas’s cats on unprotected lands in central Mongolia during two periods (May–August and September–November) in 2019. Methods. We used spatially explicit capture–recapture models to estimate population density at 15.2 ± 4.8 individuals per 100 km2. Key results. We obtained 484 Pallas’s cat images from 153 detections during 4266 camera-days. We identified Pallas’s cats using pelage markings and identified 16 individuals from 64 detections. Pallas’s cat activity was consistent between the two survey periods (~0.50), with cats mainly active during crepuscular hours in the first period and strictly diurnal in the second. Conclusions. We provide the first estimation of a Pallas’s cat population density using camera-trapping. Compared with other methods used, densities were high in our study area, which was likely to be due to a combination of highly suitable habitat and abundant prey. Seasonal shifts in the activity patterns of Pallas’s cats indicated a likely adaptive response to reduced risk of depredation by raptors. Implications. We recommend August to November as the best time for camera-trapping surveys for Pallas’s cats, given their high daily activity and the easiest interpretation of images used for individual identification collected during this time. We also suggest that future camera-trapping surveys of Pallas’s cat be mindful of potential camera-trap avoidance through time.
Databáze: OpenAIRE