ExMove: An open-source toolkit for processing and exploring animal-tracking data in R.

Ongoing technological advances have led to a rapid increase in the number, type and scope of animal-tracking studies. In response, many software tools have been developed to analyse animal movement data. These tools generally focus on movement modelling, but the steps required to clean raw data files from different tracking devices have been largely ignored. Such pre-processing steps are often time-consuming and involve a steep learning curve but are crucial for the creation of high-quality, standardised and shareable data. Moreover, decisions made at this early stage can substantially influence subsequent analyses, and in the current age of reproducibility crisis, the transparency of this process is vital. Here we present an open-access, reproducible toolkit written in the programming language R for processing raw data files into a single cleaned data set for analyses and upload to online tracking databases (found here: https://github.com/ExMove/ExMove). The toolkit comprises well-documented and flexible code to facilitate data processing and user understanding, both of which can increase user confidence and improve the uptake of sharing open and reproducible code. Additionally, we provide an overview website (found here: https://exmove.github.io/) and a Shiny app to help users visualise tracking data and assist with parameter determination during data cleaning. The toolkit is generalisable to different data formats and device types, uses modern 'tidy coding' practices, and relies on a few well-maintained packages. Among these, we perform spatial manipulations using the package sf. Overall, by collating all required steps from data collection to archiving on open access databases into a single, robust pipeline, our toolkit provides a valuable resource for anyone conducting animal movement analyses and represents an important step towards increased standardisation and reproducibility in animal movement ecology.

GPS tracking reveals landfill closures induce higher foraging effort and habitat switching in gulls.

BACKGROUND: Landfills are a major subsidy for some animals, with implications for their life history and demography. Gulls feed extensively on food from landfills and closures are expected to have ecological consequences, but how this influences movement ecology is virtually unknown. METHODS: We used GPS-tracking to quantify foraging behaviour and habitat choice of lesser black-backed gulls (Larus fuscus) breeding at two colonies before and after closure of two nearby landfills. RESULTS: Following closure, gulls from both colonies travelled further and for longer to forage. Gulls also changed habitat selection, although this differed by colony - birds from one colony shifted to agricultural habitats, while at the other, increased their use of urban areas. These behavioural responses had no effect on adult body condition but hint at potential direct effects of higher foraging costs and indirect impacts by shifting to new habitats. CONCLUSIONS: Our results demonstrate how landfill availability influences gull foraging movements and habitat selection. We also emphasize the value of biologging to detect rapid behavioural responses in contrast to more conventional demographic approaches, which is especially important for animals that spend the majority of their lives away from direct observation.