Comparison of Population Density Estimation Methods for Roe Deer (Capreolus capreolus)

Author:

Tóth Gergely1,Katona Krisztián1ORCID

Affiliation:

1. Department of Wildlife Biology and Management, Institute for Wildlife Management and Nature Conservation, Hungarian University of Agriculture and Life Sciences, Páter Károly Street 1, 2100 Gödöllő, Hungary

Abstract

Roe deer (Capreolus capreolus) populations have been increasing in Europe in the last decades. Without reliable methods, game managers frequently underestimate the population size, leading to underharvesting. The aim of this research was to identify the most suitable method for roe deer density estimation in lowland, sparsely forested, high-visibility flat areas in Hungary. The census data of the total counting in the daytime strip transect and the night spotlight strip transect, as the total counting of the sample areas with a thermal camera from observation points within 0–250 m and 0–500 m ranges, were compared in seven hunting areas. It was revealed that using the thermal camera within 0–250 m and the spotlight method in the same range gave the statistically highest population density values. There was no significant difference between the two methods. The smallest mean was revealed in the case of the daytime strip transect data. The thermal imaging method gave significantly lower values for the greater distance (250–500 m) than for the range of spotlighting (250 m). The night spotlight strip transect method and the counting from observation points with a thermal camera, both to 250 m, provided the highest values; thus, they are recommended to determine the roe deer population density in open flat areas. They require the same amount of human resources and time, but due to the high cost of the thermal camera, the spotlight is also perfectly suited for widespread use by hunting companies. The results supported the underestimation of roe deer populations.

Funder

Doctoral School of Animal Biotechnology and Animal Science of the Hungarian University of Agriculture and Life Sciences

Publisher

MDPI AG

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