Abstract
Identifying the breeding status of cryptic bird species has proved problematic without intense or inherently expensive monitoring. Most, if not all, intensive bird monitoring comes with disturbance risks and many projects now rely on tagging of individuals to provide remote information on movements. Given the importance of breeding status when targeting conservation interventions novel methods are needed. This study aimed to identify breeding status in Eurasian Curlew (Numenius arquata) from GPS tag movement patterns using the "recurse" package in R. This package identifies foci of activity (using K-means clustering) based on revisitations. Using a training data set from an individual of known breeding status, we visually assessed the frequency of revisits to particular locations to identify prebreeding, incubation, chick guarding, and post-breeding stages to an accuracy of a within at most half a day and thus breeding outcomes. Limited validation was provided by additional field observations. Based on our results, we estimate a low daily nest survival rate of 0.935 during incubation, that only a small proportion of individuals successfully raised young, and that there was a high proportion (26%) of non-breeders in the population. The Eurasian Curlew is a species of high conservation concern across Europe, and our results concur with recent studies highlighting that population declines are likely to be driven by low levels of productivity. The acquisition of improved knowledge on the behaviors of individuals at each stage of breeding enables more targeted conservation efforts and reduces the need for additional monitoring visits that may cause increased disturbance and risk of nest failure. We hope that the approach outlined may be developed to provide practitioners who have detailed knowledge of the behavior of their study species with a practical means of assessing the breeding status and outcomes of their study populations.