title: Studying dispersal at the landscape scale: efficient combination of population surveys and capture-recapture data.
abstract: Researchers often rely on capture-mark-recapture (CMR) data to study animal dispersal in the wild. Yet their spatial coverage often does not encompass the entire dispersal range of the study individuals, sometimes producing misleading results. Information contained in population surveys and variation in population spatial structure can be used to overcome this issue. We build an integrated model in a multisite context in which CMR data are only collected at a subset of sites, but numbers of breeding pairs are counted at all sites. In a Black-headed Gull Chroicocephalus ridibundus population, the integrated-modeling approach induces an increase in precision for the demographic parameters of interest (variances, on average, were decreased by 20%) and provides a more precise extrapolation of results from the CMR data to the whole population. Patterns of condition-dependent dispersal are therefore made easier to detect, and we obtain evidence for colony-size dependence in recruitment, dispersal, and breeding success. These results suggest that first-time breeders disperse to small colonies in order to recruit earlier. The exchange of experienced breeders between colonies appears as a main determinant of the observed variation in colony sizes.
authors.affiliation: Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, UMR 5175, 1919 Route de Mende, 34293 Montpellier, Cedex 5, 34293 France. peron_guillaume@yahoo.fr
authors.forename: Guillaume
authors.initials: G
authors.lastname: Péron
authors.forename: Pierre-André
authors.initials: PA
authors.lastname: Crochet
authors.forename: Paul F
authors.initials: PF
authors.lastname: Doherty
authors.forename: Jean-Dominique
authors.initials: JD
authors.lastname: Lebreton
mesh_terms: D000818:Animals; D046091:Charadriiformes / Q000502:physiology*; D003710:Demography; D017753:Ecosystem; D008954:Models, Biological; D012726:Sexual Behavior, Animal; D013997:Time Factors