New paper assessing how much tracking data biases affect species distribution models
Dr Ana Sequeira and Dr Malcolm O’Toole have led a newly published paper on tracking marine animals published in the journal Methods in Ecology and Evolution. The study Quantifying effects of tracking data bias on species distribution models used simulation data emulating the movement of marine preda
16-Oct-2020 (written by Charlotte Birkmanis)
Dr Ana Sequeira and Dr Malcolm O’Toole have led a newly published paper on analysing tracking data bias to estimate species distributions. 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 emulating the movement of marine predators to test the effects of different types of tracking data when predicting species distributions.
Telemetry, or tracking, datasets assist in the conservation of threatened species by increasing our knowledge of where these animals go. This study assessed the effects of common biases in telemetry data and provided ideas for how to alleviate some of these effects. The team, also including Nuno Queiroz, Nicolas Humphries and David Sims, found that the results of species distribution models can be affected by tagging location bias, and when using short tracks, which can result from tag failure, battery depletion, or damage to the tag's antenna.
They found that replacing short tracks with longer tracks, or with tracks from other locations, can assist reducing the effects of these biases and improve model performance. This study provides a reference to effectively use tracking datasets obtained with different tag types for different species and habitats when predicting large scale species distributions.
Great work and congratulations to all involved!
