Migratory connectivity derived from sparse ring reencounter data with unknown numbers of ringed birds

The large databases on ring reencounters, e.g. Euring database, contain extant information on the spatial distribution and potentially, on migratory connectivity of birds. However, reencounter data are normally sparse due to low reencounter probability. Further, to extract unbiased information about the spatial distribution of birds, spatial variation in reencounter probability has to be corrected for. To do so, knowledge of the total numbers of ringed birds is crucial but often not available. We present a general, combined statistical model to estimate population specific migration patterns based on the European reencounter data for which the number of ringed birds is unknown. Our approach combines a Cormack-Jolly-Seber model with a multinomial model. We present, for the first time, estimates and credible intervals of the spatial distribution of different populations of a migrant bird during the non-breeding period based on imperfect ringing data. Here, we used the Common Nightingale (Luscinia megarhynchos) as a representative long-distance migrant. The model allowed estimation of which proportions of the different breeding populations use a western, central or eastern flyway. Sensitivity analysis based on simulated data showed that most of these estimates were robust against violation of the most important model assumptions, i.e. homogeneity in recapture probability, homogeneity in breeding area return probability, and in reencounter probability within the flyways. We provide a general technique to account for spatial variation in reencounter probability when analysing migratory connectivity based on ring reencounter data with unknown numbers of ringed individuals. It is applicable for almost all migrating species with reencounter data.