Environmental variables and machine learning models to predict cetacean abundance in the Central-eastern Mediterranean Sea.

ABSTRACT: Although the Mediterranean Sea is a crucial hotspot in marine biodiversity, it has been threatened by numerous anthropogenic pressures. As flagship species, Cetaceans are exposed to those anthropogenic impacts and global changes. Assessing their conservation status becomes strategic to set effective management plans. The aim of this paper is to understand the habitat requirements of cetaceans, exploiting the advantages of a machine-learning framework. To this end, 28 physical and biogeochemical variables were identified as environmental predictors related to the abundance of three odontocete species in the Northern Ionian Sea (Central-eastern Mediterranean Sea). In fact, habitat models were built using sighting data collected for striped dolphins Stenella coeruleoalba, common bottlenose do

SUBMITTER: Maglietta R 

PROVIDER: S-EPMC9929343 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature