Factors affecting detection probability: Insights from banding data in a long-term continent-wide monitoring program

Abstract

Bird banding studies are essential for providing critical data on species population demographics and movements, as important components for understanding their ecology and conservation and management applications. However, analysing sightings of banded individuals is often complicated by untested assumptions of the species’ behaviour or visibility of the bands, leading to biased populations estimates, especially in large-scale long-term studies. In this study we investigate factors influencing detection rates of colour-banded Eurasian cranes (Grus grus), from a monitoring program spanning 35 years, involving 5049 marked individuals using four different types of bands (ELSA, ‘Finnish’, ‘Spanish’ and alphanumeric) with 172,725 resightings along migratory flyways. Data were compiled from European national banding schemes and the internet-based Crane Observation Ring Archive (iCORA). We used capture-mark-recapture mixture models to study the variation in detection probability from differences in the type of bands used, time since marking, year of observation, natal origin and an additional parameter to account for unexplained resighting heterogeneity. All band types showed high detection probabilities in their first years (as high as 80 %) but declined significantly over time, with detection rates halving within 20 years. Although starting with the lowest detection probability, alphanumeric bands remained relatively stable over time. There was a general increase in detection probability over the 35-year study period, which can be attributed to enhanced observation efforts, addition of pictures to reports and improved coordination of reports. Detection also varied by natal country, each population’s migratory routes, which were related to differences in monitoring efforts and habitat conditions along the flyways. Our findings emphasize the importance of band type, observation effort, migration pattern and environmental factors in determining detection probabilities, but also the importance to account for unexplained heterogeneity with a mixture model. This study is crucial for the study of demographic parameters within the European crane population and future evidence-based population management.