A multi-species approach for assessing the impact of land-cover changes on landscape connectivity
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Land-cover changes (LCCs) could impact wildlife populations through gains or losses of natural habitats and changes in the landscape mosaic. To assess such impacts, we need to focus on landscape connectivity from a diachronic perspective.
We propose a method for assessing the impact of LCCs on landscape connectivity through a multi-species approach based on graph theory. To do this, we combine two approaches devised to spatialize the variation of multi-species connectivity and to quantify the importance of types of LCCs for single-species connectivity by highlighting the possible contradictory effects.
We begin with a list of landscape species and create virtual species with similar ecological requirements. We model the ecological network of these virtual species at two dates and compute the variation of a local and global connectivity metric to assess the impacts of the LCCs on their dispersal capacities.
The spatial variation of multi-species connectivity showed that local impacts range from −6.4% to +3.2%. The assessment of the impacts of types of LCCs showed a variation in global connectivity ranging from −45.1% for open-area reptiles to +170.2% for natural open-area birds with low-dispersion capacities.
This generic approach can be reproduced in a large variety of spatial contexts by adapting the selection of the initial species. The proposed method could inform and guide conservation actions and landscape management strategies so as to enhance or maintain connectivity for species at a landscape scale.
KeywordsConnectivity Dispersion Multi-species Landscape graphs Land-cover changes Impact assessment
The authors thank the reviewers for their relevant suggestions that have improved the manuscript. They are very grateful to Anne Mimet for constructive discussions about allometric relationships and Gilles Vuidel for the technical improvement of Graphab software by implementing the transition decomposition process and the spatial generalization of local connectivity metrics. Land-cover data were provided by the Institut d’Aménagement et d’Urbanisme de la Région Île-de-France (IAU-IDF). The graph analysis was performed using the Graphab software, developed by Gilles Vuidel (UMR 6049 ThéMA), in the framework of the ODIT project of the USR 3124 MSHE Ledoux, funded by European FEDER funds. Computations were performed on the supercomputer facilities of the Mésocentre de calcul de Franche-Comté.
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