Extracting reproductive parameters from GPS tracking data for a nesting raptor in Europe

Abstract

Understanding population dynamics requires estimation of demographic parameters like mortality and productivity. Because obtaining the necessary data for such parameters can be labour‐intensive in the field, alternative approaches that estimate demographic parameters from existing data can be useful. High‐resolution biologging data are frequently available for large‐bodied bird species and can be used to estimate survival and productivity. We extend existing approaches and present a freely available tool (‘NestTool') that uses GPS tracking data at hourly resolution to estimate important productivity parameters such as home range establishment, breeding initiation, and breeding success. NestTool first extracts 42 movement metrics such as time spent within a user‐specified radius, number of revisits, home range size, and distances between most frequently used day and night locations from the raw tracking data for each individual breeding season. These variables are then used in three independent random forest models to predict whether individuals exhibited home range behaviour, initiated a nesting attempt, and successfully raised fledglings. We demonstrate the use of NestTool by training models with data from 258 individual red kites Milvus milvus from Switzerland tracked for up to 7 years, and then applied those models to tracking data from different red kite populations in Germany where detailed observations of nests and their outcomes existed for validation. The models achieved > 90% accurate classification of home range and nesting behaviour in validation data, but slightly lower (80–90%) accuracy in classifying the outcome of nesting attempts, because some individuals frequently returned to nests despite having failed. NestTool provides a graphical user interface that allows users to manually annotate individual seasons for which model predictions exceed a user‐defined threshold of uncertainty. NestTool will facilitate the estimation of demographic parameters from tracking data to inform population assessments, and we encourage ornithologists to test NestTool for different species.