The study, entitled Quantifying effects of tracking data bias on species distribution models and published in the journal Methods in Ecology and Evolution, used simulated data to mimic the movements of marine predators to test the effects of different types of tracking data when predicting species distributions.

Led by Dr Ana Sequeira, the team showed that replacing short tracks with longer tracks, or with tracks from other locations, can help reduce biasing effects and improve model performance. This will be useful when using tracking datasets comprising different tag types attached to different species for predicting large scale species distributions.

Read more by Charlotte Birkmanis here: https://sequeiralab.com/2020/10/16/new-paper-on-analysing-tag-data/