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

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 Île-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 modelled 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 inter-patch movement model results coupled to landscape graph can assess landscape functional connectivity at large spatial scale

Influences du climat sur la démographie des passereaux communs (mesure à grande échelle spatiale, variabilité interspécifique et prise en compte dans les prédictions biogéographiques sous scénario climatique)

Les conséquences du changement climatique actuel sur les populations d oiseaux ont fait l objet de nombreux travaux au cours des deux dernières décennies. Ces études ont mis en évidence les principaux mécanismes de l influence climatique sur les étapes du cycle de vie aviaire. Au cours de la thèse, nous avons tenté de proposer une vision intégrée de ces mécanismes et d en explorer la variabilité interspécifique. Pour cela, nous avons utilisé les données du Suivi Temporel des Oiseaux Communs (STOC). Nous avons développé des outils d analyse de la phénologie et de la survie à l échelle des populations françaises. Nous avons ensuite exploré les liens qui relient l ajustement phénologique aux conditions climatiques printanières et le taux de croissance à long terme des populations de passereaux communs et étudié la variabilité interspécifique de cet ajustement en examinant les corrélations avec les traits d histoire de vie et les caractéristiques de la niche écologique des espèces. Nous trouvons que les espèces qui ajustent le mieux leur phénologie de reproduction à la température printanière possèdent les taux de croissance à long terme les plus élevés. La capacité d ajustement phénologique est négativement corrélée à la distance de migration et au degré de spécialisation écologique des espèces alors qu elle est positivement corrélée à la taille de leur cerveau. Nous nous sommes enfin intéressés à la sensibilité des populations au climat le long de l aire de distribution afin de mieux comprendre les changements observés et attendus des aires de distributions chez les oiseaux et d améliorer la qualité des prédictions de distributions futures sous scénario climatiquePARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

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

ACLInternational audienceLandscape 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

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

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 Île-de-France region (France). Firstly we measured the butterfl 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 modelled 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