DigitalAngewandte InformatikTC Freyung
Beitrag (Sammelband oder Tagungsband)
C. Hoermann, Raphaela Pagany, K. Kirchner, Wolfgang Dorner, M. Heurich, I. Storch
Predicting the risk of deer-vehicle collisions by inferring rules learnt from deer experience and movement patterns in the vicinity of roads
Proceedings of the 2020 10th International Conference on Advanced Computer Information Technologies (ACIT) [September 6-8, 2020; Deggendorf]
Estimates of annual deer-vehicle collisions exceed one million incidences in Europe. Consequently, we were analyzing whether an animal’s experience and movement pattern close to roads can provide crucial information for accident prevention and mitigation measures. We applied an innovative approach using machine learning and step selection analyses to find rules and patterns in deer movement data for a better understanding of the spatio-temporal dynamics in wildlife-vehicle collisions. The rule tree indicated highest collision probabilities when the mean distance to a road of a roe deer tracking path was shorter than 192 meters and the roe deer crossed in more unfamiliar areas of its home range. The step selection function analysis revealed no obvious road avoidance and more road crossings in areas with less understory vegetation. Our results demonstrate the power of learned threshold values and step selection functions modelling results for a better understanding of the factors driving deer behavior in the vicinity of roads.
C. Dupke, C. Bonenfant, B. Reineking, Robert Hable, T. Zeppenfeld, M. Ewald, M. Heurich
Habitat selection by a large herbivore at multiple spatial and temporal scales is primarily governed by food resources
Ecography - Pattern and Process in Ecology, vol. 40, no. 8, pp. 1014-1027
Habitat selection can be considered as a hierarchical process in which animals satisfy their habitat requirements at different ecological scales. Theory predicts that spatial and temporal scales should co‐vary in most ecological processes and that the most limiting factors should drive habitat selection at coarse ecological scales, but be less influential at finer scales. Using detailed location data on roe deer Capreolus capreolus inhabiting the Bavarian Forest National Park, Germany, we investigated habitat selection at several spatial and temporal scales. We tested 1) whether time‐varying patterns were governed by factors reported as having the largest effects on fitness, 2) whether the trade‐off between forage and predation risks differed among spatial and temporal scales and 3) if spatial and temporal scales are positively associated. We analysed the variation in habitat selection within the landscape and within home ranges at monthly intervals, with respect to land‐cover type and proxys of food and cover over seasonal and diurnal temporal scales. The fine‐scale temporal variation follows a nycthemeral cycle linked to diurnal variation in human disturbance. The large‐scale variation matches seasonal plant phenology, suggesting food resources being a greater limiting factor than lynx predation risk. The trade‐off between selection for food and cover was similar on seasonal and diurnal scale. Habitat selection at the different scales may be the consequence of the temporal variation and predictability of the limiting factors as much as its association with fitness. The landscape of fear might have less importance at the studied scale of habitat selection than generally accepted because of the predator hunting strategy. Finally, seasonal variation in habitat selection was similar at the large and small spatial scales, which may arise because of the marked philopatry of roe deer. The difference is supposed to be greater for wider ranging herbivores.