Game species monitoring using road-based distance sampling in association with thermal imagers: a covariate analysis

Abstract

Monitoring of game species populations is necessary to adequately assess culling by hunters in areas where natural large predators are absent. However, game managers have to control several species and they often lack of an efficient and convenient survey design method. Monitoring several species at that same time over large areas could thus be cost– and time–effective. We tested the influence of several factors during monitoring of three common game species, (wild boar, roe deer and red fox, using road–based distance sampling in association with thermal imagers. This pilot survey based on 20 night counts in five contrasting sites studied the effect of several covariates (species, thermal imaging, observer, group size, and habitat type) on the detection probabilities (= dp). No differences were observed between thermal imagers (dp_JENOPTIK: 0.186, dp_FLIR: 0.193) and group sizes (dp_1ind.: 0.243, dp_2ind.: 0.259, dp_{> 2ind.}: 0.223), but we found differences between observers (dp_obs1: 0.207, dp_obs2: 0.274, dp_obs3: 0.159). Expected differences were also observed between species (dp_{wild boar}: 0.22, dp_{roe deer}: 0.35, dp_{red fox}: 0.32) and between habitat type (dp_forest: 0.27, dp_edge: 0.74, dp_open: 0.35). Our results show that the detectability of low cost thermal imaging equipment is similar to that of more expensive methods, highlighting new possibilities for the use of thermal imagery by game managers. Although adjustments should be made to the study design our findings suggest that large–scale multi–species monitoring could be an efficient method for common game species.