Article

Sergey S. Ogurtsov, Senior Researcher of the Central Forest State Nature Biosphere Reserve (172521, Russia, Tver Region, Nelidovo district, Zapovednyi settlement); Junior Researcher of the A.N. Severtsov Institute of Ecology and Evolution of the RAS (119071, Russia, Moscow, Leninsky Prospekt, 33); iD ORCID: https://orcid.org/0000-0002-0859-8954; e-mail: etundra@mail.ru

Ogurtsov S.S. 2023. Estimating brown bear population density and abundance using camera traps in the Central Forest State Nature Reserve (west of European Russia). Nature Conservation Research 8(2): 1–21. https://dx.doi.org/10.24189/ncr.2023.008

Electronic Supplement. Calibration of camera trap models, their deployments, and calculation of the activity level for REM building to estimate the brown bear population density in the Southern Forestry of the Central Forest State Nature Reserve, Russia (Link).

This paper presents the results of estimating the population density and abundance of Ursus arctos (hereinafter – brown bear) in the Southern Forestry of the Central Forest State Nature Biosphere Reserve (CFNR), West of European Russia, in 2021 based on the Random Encounter Model (REM) based upon data obtained from camera traps. Methods for obtaining parameters necessary for building a model are demonstrated. A total of 7970 camera trap nights were worked out at 46 stations, and 502 independent trap events were obtained. The average relative abundance index (RAI) was 6.28 ± 1.59. The total average brown bear population density was 0.086 ± 0.034 individuals per 1 km². The approximate estimated abundance was 18.98 ± 7.54 individuals. The coefficient of variation was 38%. Population density estimates had a pronounced seasonal dynamics. The minimum value was recorded for the period from 24 June to 23 July (individuals feeding on meadows and ants outside the CFNR core area), and the maximum for the period from 24 July to 22 August (brown bears feeding by berries in the CFNR core area). We found a strong significant correlation between brown bear population density and its relative abundance index (r = 0.81, p < 0.05). It was found that with an increase in the sampling period duration, the estimate of the population density noticeably decreases (r = -0.53, p < 0.05). Parameters of the average travel speed and activity level are a subject to the greatest variability, which determines the significant variability of the day range. In general, the method of population density estimation using REM is highly promising to carry out the brown bear population size estimation in forests and mountain forests, where visual estimations are difficult or impossible.

day range, large carnivores, population size, random encounter model, REM, unmarked species, Ursidae, Ursus arctos

Received: 08.08.2022. Revised: 28.10.2022. Accepted: 06.11.2022.

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