Estimating day range from camera-trap data: the animals’ behaviour as a key parameter

Abstract

Day range (DR), the distance travelled by an individual during the day, is an important metric in movement ecology that recently gained interest by its relevance for estimating population density through the random encounter model (REM). Traditionally, DR has been estimated using GPS technology and considering raw straight-line distances between consecutive locations, which is an underestimation of the true path distance. In this work, we tested the accuracy of a new approach based on camera-trap data for the estimation of DR taking into account the animals’ behaviour. For this purpose, we considered wild boar (Sus scrofa) as a model species. We tagged 18 individuals with telemetry devices and then monitored the population with camera-traps (photo and video mode) to estimate the DR. In the case of telemetry, a straight-line DR was estimated and rescaled with a tortuosity-related correction factor. Using this camera-trap data, we revisited the procedure described by Rowcliffe et al. (Remote Sens. Ecol. Conserv. , 2, 2016, 84) to estimate the DR from the speed and activity information obtained from camera-trapsping. A new derivation of this approach was then developed, in which different animal behaviours were weighted to estimate the DR. The analysis showed no significant differences between the DR values obtained using telemetry data (corrected by the tortuosity-related correction factor) and those attained with the weighted approach. However, the original approach used to estimate the DR based on camera-trap data underestimated this parameter. The DR estimated with the weighted approach was 12.74 km·day⁻¹ ± (se) 1.89. Here, we showed that animals’ behaviour should be taken into account to estimate the DR when working with species that behave differently in front of cameras. These results may be relevant not only for REM, but also for movement ecology, disease dynamics and population monitoring methods.