Using machine learning models to predict the distribution of a cryptic marine species: the sperm whale

Philippine Chambault, Sabrina Fossette, Mads Peter Heide-Jørgensen & Daniel Jouannet
Implementation of effective conservation planning relies on a robust understanding of the spatio-temporal distribution of the target species. In the marine realm, this is even more challenging for cryptic species with extreme diving behaviour like the sperm whales. Our study aims at investigating the movements and predicting suitable habitat maps for this species in the Mascarene Archipelago in the South-West Indian Ocean. Using 21 satellite tracks of sperm whale and 8 environmental predictors, 14 supervised...
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