Mathematical models play a critical role in effective management of marine ecosystems, which face numerous challenges from climate change and human activities. Findings from models can guide policies and increase public knowledge of future threats to the oceans. However, as these tools become more complex to reflect the many factors and processes of marine systems, they can also take on new sources of uncertainty arising from feedback loops, inaccurate or imprecise parameters. This results in lack of predictability that can make the findings difficult to interpret and apply.
Here, I will suggest means to quantify uncertainty in ocean ecosystem models and scenarios, to help make these tools more useful to decision-makers.
Yunne Shin is a marine ecologist, Senior Researcher at IRD (Institut de Recherche pour le Développement), France. Her research focuses on marine biodiversity, the size-based and trophic ecology of fish and the integrated functioning of marine ecosystems under fishing and climate change. She has been developing trait-based ecosystem models, indicator analyses, and scenarios to quantify global change impacts on marine biodiversity. She served as a coordinating lead author of the IPBES Global Assessment of Biodiversity and Ecosystem Services, and the IPBES-IPCC first joint Report. She is a member of the Scientific Council of the French Office on Biodiversity (OFB).