MEGAFAUNA Detecting, Predicting and Protecting Pelagic Megafauna Hotspots in the Coral Sea

Summary

The EU faces the challenge to protect pelagic biodiversity over immense Overseas Countries and Territories. However, cost-efficient, safe and reproducible methods are still missing for assessing the diversity and abundance of pelagic megafauna (marine mammals, sea turtles and sharks). We will adapt image-based surveys and deep learning—a new method based on artificial intelligence—to pelagic megafauna. A Coral Sea Nature Park (CSNP) was recently created in New Caledonia Overseas Territory but this area still lacks reserves in pelagic ecosystems. We will propose a reserve network that optimises the trade-off between critical habitat protection of pelagic megafauna and fisheries economic profitability in this area. This network will directly advise decision makers of the CSNP and help fulfil IUCN target of 30% of oceans protected by reserves by 2030. Our objectives are: RO1—Detect pelagic megafauna, RO2—Predict pelagic megafauna hotspots, and RO3—Protect hotspots in the Coral Sea. To reach RO1, image-based surveys will be conducted and megafauna will be automatically detected on images using deep learning. To reach RO2, habitat models will be used to predict megafauna diversity and abundance as a function of environmental variables. To reach RO3, fisheries economic data will be incorporated to propose a reserve network optimising both conservation and economic needs. This project will be jointly hosted by the Marine Biodiversity Exploitation and Conservation Laboratory (MARBEC) and the Montpellier Laboratory of Informatics, Robotics, and Microelectronics (LIRMM), both part of the University of Montpellier. Supervised by D. Mouillot (MARBEC) and M. Chaumont (LIRMM), I will receive the best appropriate interdisciplinary training. After an enriching research experience in the U.S, I aim to integrate a long-term research position in Europe. This fellowship would be a superb opportunity to develop an independent and innovative research project in marine numerical ecology.

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Web resources:	https://cordis.europa.eu/project/id/845178
Start date:	01-02-2020
End date:	31-01-2022
Total budget - Public funding:	196 707,84 Euro - 196 707,00 Euro