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Vigie-Chiro
Maps of habitat suitability
Method
Maps of habitat suitability are generated thanks to random forest models, that aim at predicting bat activity counts (the response variable) using different descriptive variables such as habitat, bioclimatic conditions, ground elevation, proximity to roads, wind turbines or artificial light at night.
Species are identified thanks to the Tadarida classifier developed for Vigie-Chiro. According to the species, data is sorted thanks to the probability of identification provided by Tadarida (> 90 % for most species, or > 50 % for rare species).
Step 1: Species activity counts are predicted according to a
forest of regression trees based on descriptive variables:
Species activity counts
and more...
Road network
Bioclimatic conditions
Habitat
(Corine Land Cover)
Wind farms
1/23
Step 2: Thanks to the forest of decision trees built in step 1, predictions are made on a systematic grid of
500m x 500m covering France.
The results depend on the sampling effort and the performance of the identification software Tadarida. We are constantly trying to reduce the identification errors, using the method published by Barré et al. (2019).
How to read the maps
The method used to create the maps can be summarised in this way: for example, knowing that Daubenton's bat was contacted much more in wetlands than in other habitats, the probability to contact this species in wetlands is relatively high, and the model will thus predict a higher density of Daubenton's bat in wetlands than in other habitats. However, Daubenton's bat being rarely contacted in areas with artificial light at night, the model will predict a lower density of the species in wetlands lighted at night.
The colour scale is adjusted for each species and represents the predicted number of bat passes per night. The dark pruple zones are supposed to be unfavourable for the species while yellow zones are supposed to be favourable.
Results are presented after step 2 if the species is not in an ambiguous acoustic group. The maps below are predictions for the summer.
Results
Download the maps (TIF)
Species with Tadarida probability of identification > 90 %
Species with Tadarida probability of identification > 50 %
Download the maps (PNG)
Species with Tadarida probability of identification > 90 %
Species with Tadarida probability of identification > 50 %
Recommanded citation :
Roemer C, Severe T, Bas Y & Kerbiriou C (2026, september) Maps of habitat suitability. Muséum national d'Histoire naturelle. Retrieved from https://croemer3.wixsite.com/teamchiro/maps-predicted-activity
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