Data from: A literature-based framework for anticipating golden jackal (Canis aureus) colonisation: Insights from Europe and a Swiss case study
Data files
Apr 30, 2026 version files 123.21 MB
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README.md
3.13 KB
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S1_Balanced.tif
30.80 MB
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S2_ClimateWater.tif
30.80 MB
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S3_Landscape.tif
30.80 MB
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S4_PredatorAvoidance.tif
30.80 MB
Abstract
The expansion of the golden jackal (Canis aureus) in Europe, caused mainly by habitat fragmentation, climate change, and the decline of large carnivores until half a century ago, poses emerging challenges for newly colonised regions. With the arrival of a new species, potential effects on local animal communities, hunting, livestock husbandry, or the transfer of diseases need to be addressed. Therefore, anticipating probable areas for colonisation is crucial to allow early monitoring and targeted management strategies and thus mitigate potential conflicts from the beginning of the recolonisation. In this study, we therefore conducted a literature review on the golden jackal’s habitat use and diet on a European scale to identify ecological factors that influence its local distribution. We then used this information to model habitat suitability for the golden jackal in Switzerland, where increasing detections indicate the imminent colonisation. We modelled four scenarios with different weights for the ecological factors: land cover, mosaicity, proximity to water, snow cover duration, and wolf presence. All models show that Switzerland provides a suitable habitat over a large surface area, particularly the Swiss Plateau and the northern Jura Mountains. These regions are characterized by a high prevalence of mosaic environments with plenty of access to water-related habitats, are generally low in elevation with shorter winters, less snow, and are so far largely unoccupied by grey wolves (Canis lupus). The models were validated using confirmed locations of dispersing golden jackals in Switzerland. The results show that golden jackals were found at locations with a significantly higher habitat suitability than at points generated randomly. Our modelling approach provides a transferable framework for guiding early monitoring efforts, focusing information campaigns, and early mitigation measures for potential conflicts with stakeholder groups in regions undergoing golden jackal colonisation, and could be easily applied to other species.
Dataset DOI: 10.5061/dryad.ghx3ffc49
Description of the data and file structure
This dataset was developed using a literature-based approach to model potential habitat suitability for the golden jackal (Canis aureus) in Switzerland. Ecological factors were assigned varying weights across four distinct scenarios, resulting in suitability layers ranging from 1 (highly suitable) to 0 (unsuitable). The dataset is georeferenced to the CH1903+ LV95 coordinate system.
It includes four habitat suitability scenarios derived from literature on Canis aureus and applied to the environmental conditions of Switzerland.
Files and variables
File: S4_PredatorAvoidance.tif
Description: Habitat suitability for golden jackal: 0 (unsuitable) to 1 (highly suitable). The dataset was created using following weights on the defined ecological variables: 0.15 x Mosaicity + 0.35 x WolfPresence + 0.15 x SnowCover + 0.20 x LandCover + 0.15 x WaterProximity. Predator avoidance: higher weight assigned to wolf presence in a scenario where the golden jackal would mostly avoid core areas of wolf territories.
File: S1_Balanced.tif
Description: Habitat suitability for golden jackal: 0 (unsuitable) to 1 (highly suitable). The dataset was created using following weights on the defined ecological variables: 0.2 x Mosaicity + 0.2 x WolfPresence + 0.2 x SnowCover + 0.2 x LandCover + 0.2 x WaterProximity. Balanced: weights assigned equally in a scenario where each ecological factor has the same importance.
File: S2_ClimateWater.tif
Description: Habitat suitability for golden jackal: 0 (unsuitable) to 1 (highly suitable). The dataset was created using the following weights on the defined ecological variables: 0.1 x Mosaicity + 0.1 x WolfPresence + 0.4 x SnowCover + 0.1 x LandCover + 0.3 x WaterProximity. Climatic/water adaptation: higher weights assigned to climatic or water related variables (water proximity and snow cover duration).
File: S3_Landscape.tif
Description: Habitat suitability for golden jackal: 0 (unsuitable) to 1 (highly suitable). The dataset was created using the following weights on the defined ecological variables: 0.25 x Mosaicity + 0.1 x WolfPresence + 0.15 x SnowCover + 0.25 x LandCover + 0.25 x WaterProximity. Landscape-driven: higher weights assigned to landscape variables (Habitat mosaicity, land cover and water-proximity).
Code/software
Data can be viewed using any GIS program or picture view on the local machine
Access information
Other publicly accessible locations of the data:
- None
Data was derived from the following sources:
For the calculation of the weights for the single layers, following data sources were used:
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Corine Land Cover (CLC) 2018 dataset (European Environment Agency (EEA), 2020)
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Swisstopo Federal Office of Topography, 2022
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CHELSA V2.1 climatology dataset (Karger et al. 2021)
