Authors: Zhiyong Hu*, University of West Florida
Topics: Spatial Analysis & Modeling, Biogeography, Environmental Science
Keywords: species distribution model, deep learning, carbon dioxide, scleractinian corals, climate effect
Session Type: Virtual Poster
Start / End Time: 9:35 AM / 10:50 AM
Room: Virtual 52
Presentation File: No File Uploaded
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.