- Impacts of LTI on terrestrial mammal movements and identification of black spots, effective crossing structures and species needs to maintain functional forest connectivity
Impacts of LTI on terrestrial mammal movements and identification of black spots, effective crossing structures and species needs to maintain functional forest connectivity
The aim of the EFACILT program, ecologically, is to assess the impact of two linear transportation infrastructures (LTI), the A34 highway and the Ardennes navigation channel, on wildlife movement and population genetics. The geographic focus of the program is a regional axis considered as a major concern for forest connectivity. Methods will include comparative genetic analyses, GPS tracking, camera traps, localization of animal-vehicle collision and drowning zones. All the data collected will be used to predict LTI crossing and will be integrated in connectivity models, including land cover data in LTI configuration. A socio-economic approach will be developed in this program, in order to identify methods allowing to resolve the contradictory injunctions between ILT construction and wildlife preservation. These actions will be integrated in the Argonne LTSER platform (ZARG), to develop long-term multidisciplinary work, including human-animal interaction, within the framework of a socio-ecological system approach.
The results will be published in international journals and presented communications at national and international conferences. The study will also lead to recommendations for landscape planning (redirecting movements with landscape features towards crossing structures) and/or for LTI construction. Overall, the data collected will provide crucial knowledge on the spatial behaviour of mammals confronted with LTI. This knowledge is essential to limit their ecological impact and to transpose solutions to other cases.
Study area: the northern Argonne massifs of the Champagne wet arc
ILT targets: Highway A34, Canal des Ardennes
Target Species: Red Deer, Wild boar, Roe Deer, Fox, Marten