Light‐level geolocator analyses: A user's guide. Issue 1 (25th June 2019) - Lisovski, Simeon; Bauer, Silke; Briedis, Martins; Davidson, Sarah C.; Dhanjal‐Adams, Kiran L.; Hallworth, Michael T.; Karagicheva, Julia; Meier, Christoph M.; Merkel, Benjamin; Ouwehand, Janne; Pedersen, Lykke; Rakhimberdiev, Eldar; et al.
Abstract: Light‐level geolocator tags use ambient light recordings to estimate the whereabouts of an individual over the time it carried the device. Over the past decade, these tags have emerged as an important tool and have been used extensively for tracking animal migrations, most commonly small birds. Analysing geolocator data can be daunting to new and experienced scientists alike. Over the past decades, several methods with fundamental differences in the analytical approach have been developed to cope with the various caveats and the often complicated data. Here, we explain the concepts behind the analyses of geolocator data and provide a practical guide for the common steps encompassing most analyses – annotation of twilights, calibration, estimating and refining locations, and extraction of movement patterns – describing good practices and common pitfalls for each step. We discuss criteria for deciding whether or not geolocators can answer proposed research questions, provide guidance in choosing an appropriate analysis method and introduce key features of the newest open‐source analysis tools. We provide advice for how to interpret and report results, highlighting parameters that should be reported in publications and included in data archiving. Finally, we introduce a comprehensive supplementary online manual that applies the concepts to several datasets, demonstrates the use of open‐source analysis tools with step‐by‐step instructions and code and details our recommendations for interpreting, reporting and archiving. Abstract : Over the past decade, light‐level geolocator tags have emerged as an important tool for tracking animals. However, due to various caveats, the translation of light recordings into location estimates can be daunting. In this 'How to…' paper, we provide a practical guide for the analysis of geolocator data by describing good practices and discussing common pitfalls.