Prediction of suitable habitat of deep-sea framework-forming scleractinian corals in the Gulf of Mexico under the RCP 8.5 scenario of global emission of carbon dioxide

Keywords: species distribution model, deep learning, carbon dioxide, scleractinian corals, climate effect
Session Type: Virtual Poster
Day: Friday
Session Start / End Time: 4/9/2021 09:35 AM (Pacific Time (US & Canada)) - 4/9/2021 10:50 AM (Pacific Time (US & Canada))
Room: Virtual 52

Abstract

Rising carbon dioxide levels raise ocean acidification level and temperature This paper presents spatial prediction of suitable habitat of deep-sea framework-forming scleractinian corals in the Gulf of Mexico for the year 2100 under the RCP 8.5 scenario of global emission of carbon dioxide. Ocean bottom temperature and PH values were predicted using a global climate change model under the most intensive CO2 emission scenario. A deep machine learning species distribution model was calibrated using current observed presence of corals and environmental variables data and the suitable habitat was predicted using the model and environmental data in 2100 with climate and chemical variables updated based on the CO2 emission scenario.