High habitat potential but limited connectivity for brown bears throughout Europe
Data files
Dec 01, 2025 version files 624.65 MB
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bearscript_revised.R
7.44 KB
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censored_10km.csv
995.24 KB
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convex_stack.grd
1.67 KB
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convex_stack.gri
237.20 MB
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fullarea_stack.grd
1.67 KB
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fullarea_stack.gri
386.44 MB
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README.md
2.98 KB
Abstract
Large carnivores worldwide have experienced substantial range contractions due to human activities. Using an ensemble species distribution model and occurrence data from all European brown bear (Ursus arctos) populations, we assessed current and potential bear habitat as well as habitat connectivity. Habitat suitability was strongly associated with low human development, high forest cover, and proximity to forest. Of our entire study area, 37% (4.09 million km2) is suitable for bears. Connectivity analyses identified corridors that could facilitate movement among southern European bear populations, though agriculture and human development limit connectivity between northern and southern European bear populations. Previous research estimated bears occupied 0.5 million km2 across the European Union, while our results estimate 1.82 million km2 of this area is potentially suitable for bears, though connectivity is limited. Our results inform conservation strategies and policy development for the future of brown bears in Europe, emphasizing the need for transboundary conservation efforts. Raw species presence data are not publicly available as the subject species (European brown bear) is listed under Annex IV of the EU Habitats Directive (Council Directive 92/43/EEC), which designates it as a species of community interest in need of strict protection. Article 12 of the directive prohibits deliberate disturbance, capture, or killing of individuals in the wild and includes protections for breeding sites and resting places. Presence data censored to a 10-km resolution are available from this repository, as is the code used to create the ensemble model.
Dataset DOI: 10.5061/dryad.83bk3jb48
Description of the data and file structure
We used brown bear data collected during 2000–2018 from various research projects and monitoring programs. Data were compiled as part of the BearConnect initiative (https://bearconnect.org), and sourced from research groups, government agencies, and non-government organizations. We created a dataset of bear occurrences including all ten European bear populations and Turkey using telemetry locations, genetic samples, remote camera images, direct observations, and other confirmed evidence of presence. All records of bear occurrences were verified by the respective research groups and government agencies.
Files and variables
File: bearscript_revised.R
Description: Script needed to run the species distribution model in R
File: censored_10km.csv
Description: Censored presence data for brown bears used for the model. The coordinates are presented in EPSG 3035.
Variables
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FID: ID number of the presence location
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Lon: Longitude
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Lat: Latitude
The environmental raster stacks in this dataset are provided in the .grd/.gri pair format commonly produced by the raster or terra packages in R:
.grd– A small metadata file containing information about the raster stack (number of layers, layer names, spatial extent, resolution, data type, etc.)..gri– The accompanying binary file that stores the actual raster cell values.
The accompanying R script loads the correct raster stacks when the working directory is set to the folder containing both the .grd and .gri of the same name.
How to use these files
File: convex_stack.gri
Description: Raster stack of environmental variables used in the model, clipped to the convex hull used for the species distribution model
File: fullarea_stack.gri
Description: Raster stack of environmental variables used in the model, for the entire study area the model was projected to.
File: convex_stack.grd
Description: Metadata for the raster stack of environmental variables used in the model, clipped to the convex hull used for the species distribution model
File: fullarea_stack.grd
Description: Metadata for the raster stack of environmental variables used in the model, for the entire study area the model was projected to.
Code/software
The species distribution model was created in R. Software packages necessary to run the analysis code are provided within the code script.
Access information
Data was derived from the following sources:
- Environmental covariates were derived from Copernicus Global Land Service (100-m resolution),
see https://land.copernicus.eu/en/products
