Data and code from: How to stay wild in a highly domesticated landscape? Spatiotemporal behaviour of wolves in Germany
Data files
Apr 10, 2026 version files 33.58 MB
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Activity_vs_Light.Habitat_Distances_clean.R
12.80 KB
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fulldata_clean.csv
31.76 MB
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Hab_Act_Combined_clean.csv
1.76 MB
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Habitat_model_WolfGermany_clean.R
43.36 KB
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README.md
2.72 KB
Abstract
Wild animals can adapt to the increasing presence of humans by either becoming accustomed to it or avoiding humans by spatiotemporal separation. The return of the wolf to the German lowlands raised the opportunity to study wolf behaviour in one of the most densely populated and fragmented countries in Europe, in an area where topography offers no retreat from human disturbance. We analysed telemetry data of 18 wolves from five federal states in Germany to study how wolves adjust their movements and activity in relation to anthropogenic structures. We found no evidence that wolves in Germany got accustomed to humans or human infrastructure. Our results show that wolves adapted their spatiotemporal behaviour in a way that minimized encounters with humans: 1) Wolves were mostly inactive during the day when humans are most active, 2) they showed a high preference for habitats that provide cover, especially during daylight, and 3) they strongly avoided human infrastructures, especially during daylight. This study shows that land-sharing between wolves and humans does not appear to have resulted in a loss of strong spatial avoidance of humans, particularly during daytime when human activity is highest. It reaffirms that coexistence in landscapes heavily impacted by humans is possible.
Dataset DOI: 10.5061/dryad.brv15dvqj
Description of the data and file structure
Files and variables
File: Hab_Act_Combined_clean.csv
Description: A data set containing combined habitat and activity data from wolves for which activity data were available. X-and Y-coordinates are not provided because of sensitivity reasons. The file contains the following variables:
Variables
- ID: ID
- Wolf_ID: ID of the wolf unit
- Territory: wolf territory
- Terr_Code: ID of the territory the wolf unit was located in
- UTC_Date: UTC date
- UTC_Time: UTC
- Season: season (spring, summer, fall, winter)
- Hab_CODE: habitat code according to RECLASS_Code in Table S3 in Supporting information
- Habitat: habitat according to RECLASS_LABEL in Table S3 in Supporting information
- dist_urban: distance to urban area [m]
- dist_road: distance to main road [m]
- dist_forest_road: distance to forest road [m]
- dist_allcover: distance to cover (forest/shrub/heathland) [m]
- yday: Julian day
- Light: dusk, day, night, dawn
- PercentActive30: percent active in the 30 minutes before and after the location fix, measured in 5-minute intervals
File: fulldata_clean.csv
Description: A data set containing habitat data for all wolf and random locations. X-and Y-coordinates are not provided because of sensitivity reasons. The file contains the following variables:
Variables
- use: wolf (1), random (0)
- ID: ID of the location
- Wolf_ID: ID of the wolf unit
- Territory: wolf territory
- Terr_Code: ID of the territory the wolf unit was located in
- UTC_Date: UTC date
- UTC_Time: UTC
- Season: season (spring, summer, fall, winter)
- Hab_CODE: habitat code according to RECLASS_Code in Table S3 in Supporting information
- Habitat: habitat according to RECLASS_LABEL in Table S3 in Supporting information
- dist_urban: distance to urban area [m]
- dist_road: distance to main road [m]
- dist_forest_road: distance to forest road [m]
- dist_allcover: distance to cover (forest/shrub/heathland) [m]
- yday: Julian day
- Light: dusk, day, night, dawn
File: Activity_vs_Light.Habitat_Distances_clean.R
Description: R-scripts for analyses of activity data and Figures 2 and 3.
File: Habitat_model_WolfGermany_clean.R
Description: R-script for analyses of habitat data in relation to light, temperature,t and Figures 4 and 5
Code/software
All data were extracted using R Statistical Software (R Statistical Software (v 4.1.2; R Core Team 2021 - v 4.4.0; R Core Team 2024) and ArcMap v. 10.7 (ESRI, 2019).