Predicting Seasonal Movements and Distribution of the Sperm Whale Using Machine Learning Algorithms

Sperm Whale DataResearchers tested machine learning algorithms and compared them to predict the potential distribution of sperm whales during the wet and dry seasons. Fieldwork was conducted in the south-western part of Mauritius Island in 2014, 2016, and 2018. 21 sperm whales were fitted with Wildlife Computers SPOT and SPLASH10 tags. The results of this study helped fill knowledge gaps of the seasonal movements and habitat uses for which a regional IUCN assessment is still missing.

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