A new article, ‘Drones and machine-learning for monitoring dugong feeding grounds and gillnet fishing’ by Cossa, D. et al., highlights the potential of using unmanned aerial vehicle-based imaging (drones) and machine-learning to identify and monitor dugong foraging hotspots.

Dugong hotspots in Saco East and Saco West, Inhaca Island, southern Mozambique were surveyed to evaluate the influence of gillnet fishing activities on dugong feeding grounds.

“This study highlights the clear potential of drones and machine-learning to study and monitor animal behaviour in the wild, particularly in hotspots and remote areas. We encourage the establishment of effective management strategies to monitor and control the use of gillnets, thereby avoiding the accidental bycatch of dugongs.”

Lead author, Damboia Cossa is a member of the CMS Dugong MOU Technical Advisory Group.

The full article is available for download here: Cossa. D. et al., 2023: Drones and machine-learning for monitoring dugong feeding grounds and gillnet fishing

Cossa, D. et al., (2023), Drones and machine-learning for monitoring dugong feeding grounds and gillnet fishing. Marine Ecology Progress Series, Vol. 716: 123–136.