Quantifying variation in migratory strategies using ring-recoveries

Bird populations have traditionally been labelled as “migrant” or “resident” on the basis of field observations and qualitative interpretations of patterns of ring–recoveries. However, even such a non–systematic approach has identified many intermediate species where only part of the population migrates (partial migrants) or where different components of the population migrate to different extents (differential migrants). A method that would allow a quantitative definition of migratory tendency to be derived for many species would facilitate investigations into the ecological causes and life–history consequences of migratory behaviour. Species or populations could then be placed objectively into the continuum between true residency and an obligate, long–distance migratory habit. We present a novel method for the analysis of ring–recovery data sets that produces just such a quantitative index of migratory tendency for British birds, developed as part of the BTO’s Migration Atlas project (Wernham et al., 2002). The method uses distributions of ringing–to–recovery distances to classify individual species’ patterns of movement relative to those of other species. The areas between species’ cumulative distance distributions are treated as inter–species dissimilarities and a one–dimensional map is then constructed using multi–dimensional scaling. We have used the method in example analyses to show how it can be used to investigate the factors that affect the migratory strategies that species adopt, such as body size, territoriality and distribution, and in studies of their consequences for demographic parameters such as annual survival and the timing of breeding. We have also conducted initial analyses to show how temporal changes in the indices could reveal otherwise unmeasured population consequences of environmental change and thus have an important application in conservation science. Finally, we discuss how our approach to producing indices of migratory tendency could be enhanced to reduce the bias that follows from spatial or temporal variation in reporting rates and how they could be made more broadly valuable by incorporating other data sets and recovery data from other countries.