Abstract:
Climate change is altering coral reef ecosystems worldwide, necessitating new approaches to understand their adaptive potential and inform conservation efforts. In this talk, I will present a collection of studies that implement eco-evolutionary theory and machine learning techniques to advance coral reef science and management.聽First, I will present a systematic analysis of factors influencing coral population persistence under climate change, using an eco-evolutionary framework applied to Hawaiian reefs.聽We find that population growth rate and additive genetic variance鈥攏ot thermal tolerance鈥攁re the strongest predictors of long-term coral persistence.聽Next, I will present ongoing research developing a holobiont framework in which both the coral host and its photosynthetic symbionts undergo independent population dynamics and thermal adaptation. This coupled model reveals that coral persistence under warming requires both partners to evolve in parallel: if either the host or symbiont lacks sufficient genetic variance to track rising temperatures, the holobiont population collapses. Lastly, I will discuss ongoing work using machine learning techniques to detect potential regime shifts on coral reefs. This approach aims to identify critical transitions in reef ecosystems, potentially providing early warning signals for conservation planning. Collectively, this research seeks to contribute to our understanding of coral reef futures and inform strategies for preserving these ecosystems in a rapidly changing environment.