The Biodiversity Research Centre (BRC) at the University of British Columbia (UBC), in collaboration with the British Ecological Society’s (BES) Movement Ecology Special Interest Group (https://www.britishecologicalsociety.org/membership-community/special-interest-groups/movement-ecology/), will be hosting a workshop for graduate students and postdocs on methods to analyse movement data. The workshop, which will run from June 18 to June 22, will be led by Marie Auger-Méthé (UBC), Luca Börger (Swansea University) and Garrett Street (Mississippi State University).
This week-long workshop will immerse participants in the methodology needed to analyse movement data. We will be presenting methods ranging from simple visualisation techniques to advance statistical models. For example, we will introduce participants to home range estimators, habitat selection techniques, and models to identify behaviours and handle measurement errors. We will also cover accelerometry and how it can be used in dead reckoning and behavioural studies. The workshop will be focused on hands-on tutorial sessions, where the participants will apply the techniques to real data using R and will have the opportunity to try the methods on their own datasets (data will be provided if participants do not have their own data to work with).
Registration fees are: $35 + tax for local participants (not requiring accommodation) and $110 + tax for those requiring accommodation, and members of the BRC and BES will receive an additional $10 discount. Fees will cover the workshop, accommodation for those requesting it, and some extra perks (e.g. coffee breaks).
To register, please send a short ~ 200 word description of why you are interested in participating in this workshop to Marie Auger-Méthé (email@example.com) by April 19. Space is limited to 25 participants and priority will be given to graduate students and postdocs with enough knowledge of R to be able to import movement data in R and do simple movement analyses, so please indicate your career stage and describe your experience with R in one or two sentences.