The impact of climate change on species is complex, making the selection and prioritization of management strategies challenging. Host-symbiont dynamics are fundamental to understanding the resilience of a wide range of species in varying ecosystems. The goal of Theme III is to create a generalizable framework that combines short-term acclimatization (Theme I) and long-term adaptability data and models (Theme II) to predict the effect of climate change across the closed-open-complex symbiosis spectrum for all species. Using experimental data and model simulations from Themes I and II, we will use mathematical modeling and machine learning to predict short-term resilience and long-term adaptability of symbiotic systems. This will provide insights into key predictive factors and highlight which types of data are most influential towards prediction. We will develop a multiscale mathematical model which will generate vulnerability and adaptability indices and maps, and allow us to determine the biological mechanisms influencing resilience and adaptability and provide managers with modern and innovative decision-making tools.

Our outcomes will provide managers with the tools they need to monitor the impact of climate changes on ecosystems and predict areas or species of greater resilience to these changes.