Approaches, challenges and prospects for modeling macroalgal dynamics in the green tide: The case of Ulva prolifera

Abstract

Ulva prolifera blooms, also known as green tides, significantly disrupt coastal ecosystems by altering species balance, energy flow, and nutrient cycling. These blooms, driven by nutrient enrichment, climate change, and human activities, have become a pressing environmental challenge in coastal regions. This review synthesizes current advances in modeling the growth, dispersal, and decline of U. prolifera blooms, emphasizing the roles of environmental drivers such as nutrient availability, temperature, light, and hydrodynamic conditions. We discuss empirical and mechanistic modeling approaches, highlighting their applications, limitations, and potential for predicting bloom dynamics. Special attention is given to model calibration, validation, and the integration of remote sensing and environmental data, which are crucial for ensuring model accuracy and reliability. Despite significant progress, challenges remain in addressing data gaps, incorporating climate variability, and simulating complex ecological interactions. Future research directions include the development of multi-scale, coupled models and the integration of socio-economic impacts to enhance bloom management strategies and inform policy development. The insights presented are intended to advance the understanding of U. prolifera bloom dynamics and contribute to the mitigation of their ecological and socio-economic impacts.