Fore-C: Ecological forecasts of coral disease to create opportunities for timely, effective management

Megan Donahue1, Jamie Caldwell1, Scott F Heron2, Austin Greene1, Erick Francis Geiger3,4, Gang Liu3,4, Jacqueline L De La Cour3,4, Tracy D. Ainsworth5, William Leggat6, Tess Moriarty6, Laurie J Raymundo7 and C. Mark Eakin3, (1)University of Hawai‘i at Manoa, Hawai‘i Institute of Marine Biology, Kane‘ohe, HI, United States, (2)James Cook University, Townsville, QLD, Australia, (3)NOAA/NESDIS/STAR Coral Reef Watch, College Park, MD, United States, (4)Global Science and Technology Inc Greenbelt, Greenbelt, MD, United States, (5)University of New South Wales, School of Environmental and Life Sciences, Sydney, NSW, Australia, (6)University of Newcastle, School of Environmental and Life Sciences, Callaghan, NSW, Australia, (7)University of Guam, University of Guam Marine Laboratory, Mangilao, Guam
Abstract:
Disease is a prominent threat to the long-term health and sustainability of corals and reef communities. Increasing ocean temperatures worldwide and more localized threats from terrestrial runoff increase the susceptibility of corals and other marine organisms to disease and pathogen loading. However, coral disease outbreaks are highly variable in space and time, making it difficult to investigate, monitor, and manage disease, particularly in remote regions. We have developed a set of predictive models for coral disease outbreak risk based on more than a decade of disease surveys across the tropical Pacific as well as satellite-derived observations of sea surface temperature (SST) and ocean color. Combining these models with near real-time observations of SST and ocean color, and seasonal forecasts of ocean temperature, we developed ecological forecasts of disease risk for Pacific coral reef regions. More accurate predictions of coral disease risk provide scientists, resource managers, and decision makers greater opportunity to plan for timely, effective responses to outbreak events. Herein we present a forecasting framework in a web-based toolbox, allowing users to visualize the risk profile of their reefs and prepare an effective response when disease risk is high.