Charting the course of \emph{Sargassum}: Incorporating nonlinear elastic interactions and life cycles in the Maxey--Riley model

TL;DR

This paper develops a novel, physics-based model incorporating nonlinear elastic interactions and biological life cycles to better predict rgassumnd transport and aggregation in oceanic environments, validated with satellite data.

Contribution

It introduces an enhanced Maxey--Riley model with nonlinear elastic forces and biological factors, improving prediction of rgassumnd dynamics over existing leeway-based models.

Findings

Model outperforms leeway approach in validation

Incorporates biological life cycle effects

Simulates aggregation within oceanic eddies

Abstract

The surge of pelagic \emph{Sargassum} in the Intra-America Seas, particularly the Caribbean Sea, since the early 2010s has raised significant ecological concerns. This study emphasizes the need for a mechanistic understanding of \emph{Sargassum} dynamics to elucidate the ecological impacts and uncertainties associated with blooms. By introducing a novel transport model, physical components such as ocean currents and winds are integrated with biological aspects affecting the \emph{Sargassum} life cycle, including reproduction, grounded in an enhanced Maxey--Riley theory for floating particles. Nonlinear elastic forces among the particles are included to simulate interactions within and among \emph{Sargassum} rafts. This promotes aggregation, consistent with observations, within oceanic eddies, which facilitate their transport. This cannot be achieved by the so-called leeway approach to transport, which forms the basis of current \emph{Sargassum} modeling. Using satellite-derived data, the model is validated, outperforming the leeway model. Publicly accessible codes are provided to support further research and ecosystem management efforts. This comprehensive approach is expected to improve predictive capabilities and management strategies regarding \emph{Sargassum} dynamics in affected regions, thus contributing to a deeper understanding of marine ecosystem dynamics and resilience.