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Abstract The surge of pelagic 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 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 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 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 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 Sargassum dynamics in affected regions, thus contributing to a deeper understanding of marine ecosystem dynamics and resilience. 

The purpose of this note is to present an enhancement to a Maxey–Riley theory proposed in recent years for the dynamics of inertial particles on the ocean surface [Beron-Vera et al., “Building a Maxey–Riley framework for surface ocean inertial particle dynamics,” Phys. Fluids 31, 096602 (2019)]. This updated model removes constraints on the reserve buoyancy, defined as the fraction of the particle volume above the ocean surface. The refinement results in an equation that correctly describes both the neutrally buoyant and fully buoyant particle scenarios. 

This study addresses the horizontal and vertical dispersion of passive tracers in idealized wind-driven subtropical gyres. Synthetic particles within a closed basin are numerically advected to analyze their dispersion under different theoretical velocity fields. Horizontal dispersion simulations incorporate the classic wind-driven Stommel circulation along with (i) surface Ekman drift associated with the Stommel wind field and (ii) inertial effects due to particle size and buoyancy. Results reveal that the Ekman drift inhibits particle dispersion across the entire domain leading to tracer concentration in a quasi-stable distribution skewed toward the western side of the basin. Similar behavior is observed with inertial particles. The equilibrium state is quantified for different diffusivity values, particle sizes, and buoyancies. For vertical dispersion, simulations incorporate the three-dimensional Ekman velocity, which includes a negative vertical component, while ignoring inertial effects. Initially, surface particles accumulate around the gyre center while slowly sinking, but they disperse across the basin once they surpass the Ekman layer and are free from surface effects. Tracers sink more on the western side of the basin, regardless of horizontal diffusivity. On average, ignoring inertial effects, particles sink less with higher diffusivity and more with lower diffusivity, suggesting a potential for high horizontal distribution of sunken tracers in the ocean. 

A recent Maxey–Riley theory for Sargassum raft motion, which models a raft as a network of elastically interacting finite size, buoyant particles, predicts the carrying flow velocity to be given by the weighted sum of the water and air velocities (1−α)v+αw. The theory provides a closed formula for parameter α, referred to as windage, depending on the water-to-particle-density ratio or buoyancy (δ). From a series of laboratory experiments in an air–water stream flume facility under controlled conditions, we estimate α ranging from 0.02% to 0.96%. On average, our windage estimates can be up to nine times smaller than that considered in conventional Sargassum raft transport modeling, wherein it is customary to add a fraction of w to v chosen in an ad hoc piecemeal manner. Using the formula provided by the Maxey–Riley theory, we estimate δ ranging from 1.00 to 1.49. This is consistent with direct δ measurements, ranging from 0.9 to 1.25, which provide support for our α estimation. 

Ulam’s method is a popular discretization scheme for stochastic operators that involves the construction of a transition probability matrix controlling a Markov chain on a set of cells covering some domain. We consider an application to satellite-tracked undrogued surface-ocean drifting buoy trajectories obtained from the National Oceanic and Atmospheric Administration Global Drifter Program dataset. Motivated by the motion of Sargassum in the tropical Atlantic, we apply Transition Path Theory (TPT) to drifters originating off the west coast of Africa to the Gulf of Mexico. We find that the most common case of a regular covering by equal longitude–latitude side cells can lead to a large instability in the computed transition times as a function of the number of cells used. We propose a different covering based on a clustering of the trajectory data that is stable against the number of cells in the covering. We also propose a generalization of the standard transition time statistic of TPT that can be used to construct a partition of the domain of interest into weakly dynamically connected regions. 

By analyzing a time-homogeneous Markov chain constructed using trajectories of undrogued drifting buoys from the NOAA Global Drifter Program, we find that probability density can distribute in a manner that resembles very closely the recently observed recurrent belt of high Sargassum concentration in the tropical Atlantic between 5 and 10°N, coined the Great Atlantic Sargassum Belt (GASB). A spectral analysis of the associated transition matrix further unveils a forward attracting almost-invariant set in the northwestern Gulf of Mexico with a corresponding basin of attraction weakly connected with the Sargasso Sea but including the nutrient-rich regions around the Amazon and Orinoco rivers mouths and also the upwelling system off the northern coast of West Africa. This represents a data-based inference of potential remote sources of Sargassum recurrently invading the Intra-Americas Seas (IAS). By further applying Transition Path Theory (TPT) to the data-derived Markov chain model, two potential pathways for Sargassum into the IAS from the upwelling system off the coast of Africa are revealed. One TPT-inferred pathway takes place along the GASB. The second pathway is more southern and slower, first going through the Gulf of Guinea, then across the tropical Atlantic toward the mouth of the Amazon River, and finally along the northeastern South American margin. The existence of such a southern TPT-inferred pathway may have consequences for bloom stimulation by nutrients from river runoff.