Data from: Mapping and explaining wolf recolonization in France using dynamic occupancy models and opportunistic data ...
While large carnivores are recovering in Europe, assessing their distributions can help to predict and mitigate conflicts with human activities. Because they are highly mobile, elusive and live at very low density, modeling their distributions presents several challenges due to i) their imperfect de...
| Main Authors: | , , , , , , , |
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| Format: | Dataset |
| Language: | English |
| Published: |
Dryad
2017
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.g9s1d https://datadryad.org/stash/dataset/doi:10.5061/dryad.g9s1d |
| Summary: | While large carnivores are recovering in Europe, assessing their distributions can help to predict and mitigate conflicts with human activities. Because they are highly mobile, elusive and live at very low density, modeling their distributions presents several challenges due to i) their imperfect detectability, ii) their dynamic ranges over time and iii) their monitoring at large scales consisting mainly of opportunistic data without a formal measure of the sampling effort. Here, we focused on wolves (Canis lupus) that have been recolonizing France since the early 90’s. We evaluated the sampling effort a posteriori as the number of observers present per year in a cell based on their location and professional activities. We then assessed wolf range dynamics from 1994 to 2016, while accounting for species imperfect detection and time- and space-varying sampling effort using dynamic site-occupancy models. Ignoring the effect of sampling effort on species detectability led to underestimating the number of ... : Historic of detections of wolves per site per yearThe rows of this matrix are the 3547 sites and the 23 columns are the 23 years from 1994 to 2016. For each line a 0 means that no detection occured and a 1 means that a detection occured.zst.RData ... |
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