Trevail, A. | bioRxiv Science

bioRxiv2023

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

O_LIOngoing 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. C_LIO_LIHere 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. C_LIO_LIThe toolkit is generalisable to different data formats and device types, uses modern tidy coding practices, and relies on few well-maintained packages. Amongst these, we perform spatial manipulations using the package sf, providing a timely resource for movement ecologists following the recent deprecation of the widely-used sp package. C_LIO_LIOverall, 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. C_LI

ecology↗

bioRxiv2023

Strong breeding colony fidelity in northern gannets following High Pathogenicity Avian Influenza Virus (HPAIV) outbreak

High pathogenicity avian influenza virus (HPAIV) caused the worst seabird mass-mortalities on record in Europe across 2021-2022. The northern gannet (Morus bassanus) was one of the most affected species, with tens of thousands of casualties in the northeast Atlantic between April-September 2022. Disease outbreaks can drastically modify the movement ecology of animals and diminish spatial consistency, thereby increasing the potential for disease transmission. To detect potential changes in movement behaviour, we GPS-tracked breeding adults following the initial HPAIV outbreak, at three of the largest gannet breeding colonies where major mortality of adults and chicks occurred (Bass Rock, Scotland, UK; Grassholm, Wales, UK; Rouzic island, Brittany, France). Crucially, GPS-tracked birds remained faithful to their breeding sites and did not prospect other breeding colonies. They performed regular foraging trips at sea, similar to their behaviour before the outbreak. Gannet foraging effort was nonetheless lower than in 2019, thus surviving birds may have benefited from reduced intra- and interspecific food competition. Breeding colony fidelity of adult northern gannets following HPAIV mass-mortalities suggests limited long-term capacity to virus spread, which may contrast with the behaviour of adults during the disease outbreak, or with that of younger individuals.

ecology↗