Understanding habitat selection of range-expanding populations of large carnivores: 20 years of grey wolves (Canis lupus) recolonizing Germany ...

• Main Authors: Planillo, Aimara, Wenzler-Meya, Moritz, Reinhardt, Ilka, Kluth, Gesa, Michler, Frank-Uwe, Stier, Norman, Louvrier, Julie, Steyer, Katharina, Gillich, Benjamin, Rieger, Siegfried, Knauer, Felix, Kuemmerle, Tobias, Kramer-Schadt, Stephanie
• Format: Dataset
• Language: English
• Published: Dryad 2022
• Subjects: FOS Biological sciences; Germany; monitoring; large carnivore conservation; Colonization; data integration; expanding population; human disturbance; Species Distribution Modelling; Canis lupus
• Online Access: https://dx.doi.org/10.5061/dryad.m63xsj461; https://datadryad.org/stash/dataset/doi:10.5061/dryad.m63xsj461

Aim: The non-stationarity in habitat selection of expanding populations poses a significant challenge for spatial forecasting. Focusing on the grey wolf (Canis lupus) natural recolonization of Germany, we compared the performance of different distribution modelling approaches for predicting habitat suitability in unoccupied areas. Furthermore, we analysed whether grey wolf showed non-stationarity in habitat selection in newly colonized areas, which will impact the predictions for potential habitat. Location: Germany Methods: Using telemetry data as presence points, we compared the predictive performance of five modelling approaches based on combinations of distribution modelling algorithms –GLMM, MaxEnt, and ensemble modelling– and two background point selection strategies. We used a homogeneous Poisson point process to draw background points from either the minimum convex polygons derived from telemetry or the whole area known to be occupied by wolves. Models were fit to the data of the first years and ... : Our wolf data comprised two complementary datasets. Our first dataset consisted of GPS telemetry locations of 20 collared resident wolves from 2009 to 2018. This data is provided at a 50km resolution due to species conservation concerns. Our final telemetry dataset consisted of 3,841 locations from 21 home ranges (183 ± 104 locations per home range). Our second dataset consisted of centroids of known wolf territories monitored annually since 2000 (www.dbb-wolf.de/Wolfsvorkommen/territorien/karte-der-territorien). The centroids of the territories were assessed after the end of the monitoring year, as the central point of all activity signs (scats; camera trap images; telemetry data, when available; opportunistic sightings; hunt remains) that were assigned to the same territory. Territory areas for our study were delineated with a radius of 8 km around their centroids, resulting in territory sizes of approx. 200 km². ...