A quantitative measure of migratory connectivity

The study of the extent of the connection between areas where populations of birds breed and areas where they winter has flourished in recent years mainly thanks to the development of new techniques, but also due to traditional ringing and recovery schemes, which allow tracking of individuals or populations linking wintering and breeding distributions. Currently, studies on migratory connectivity focus on retention of breeding population spatial structure on the non-breeding grounds and vice versa. Here we propose a method to quantify migratory connectivity based on Mantel correlation coefficients and to statistically test for deviations of the observed connectivity from a random mix of individuals. In addition, we propose a procedure, based on clustering algorithms, to identify whether observed connectivity depends on aggregation of individuals or on rigid transference of distribution patterns between areas. We applied this method to a large dataset of ringing recoveries of barn swallows (Hirundo rustica L) migrating from their Western Palearctic breeding areas to sub-Saharan winter quarters. We show that migration of barn swallow populations connects specific breeding and wintering areas, and that the sub-populations quantitatively identified by our method are consistent with qualitative patterns of migratory connectivity identified by studies of individual geographical populations based on other methods. Finally, we tested the performance of the method by running simulations under different scenarios. Such simulations showed that the method is robust and able to correctly detect migratory connectivity even with smaller datasets and when a strong geographical pattern is not present in the population. Our method provides a quantitative measure of migratory connectivity and allows for the identification of populations showing high connectivity between the breeding and wintering areas. This method is suitable for a generalized application to diverse animal taxa as well as to large scale analyses of connectivity for conservation purposes. (C) 2008 Elsevier Ltd. All rights reserved.