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Coupling inter-patch movement models and landscape graph to assess functional connectivity

Abstract : Landscape connectivity is a key process for the functioning and persistence of spatially-structured populations in fragmented landscapes. Butterflies are particularly sensitive to landscape change and are excellent model organisms to study landscape connectivity. Here, we infer functional connectivity from the assessment of the selection of different landscape elements in a highly fragmented landscape in the Ile-de-France region (France). Firstly we measured the butterfly preferences of the Large White butterfly (Pieris brassicae) in different landscape elements using individual release experiments. Secondly, we used an inter-patch movement model based on butterfly choices to build the selection map of the landscape elements to moving butterflies. From this map, functional connectivity network of P. brassicae was modeled using landscape graph-based approach. In our study area, we identified nine components/groups of connected habitat patches, eight of them located in urbanized areas, whereas the last one covered the more rural areas. Eventually, we provided elements to validate the predictions of our model with independent experiments of mass release-recapture of butterflies. Our study shows (1) the efficiency of our inter-patch movement model based on species preferences in predicting complex ecological processes such as dispersal and (2) how interpatch movement model results coupled to landscape graph can assess landscape functional connectivity at large spatial scales.
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Contributor : Céline Clauzel <>
Submitted on : Tuesday, January 8, 2013 - 10:31:14 AM
Last modification on : Friday, April 2, 2021 - 3:35:42 AM

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Benjamin Bergerot, Pierline Tournant, Jean-Pierre Moussus, Virginie Marie Stevens, Romain Julliard, et al.. Coupling inter-patch movement models and landscape graph to assess functional connectivity. Population Ecology, Springer Verlag, 2013, 55 (1), pp.193-203. ⟨10.1007/s10144-012-0349-y⟩. ⟨halshs-00771180⟩



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