Top marine predators track Lagrangian coherent structures

Meso- and submesoscales (fronts, eddies, filaments) in surface ocean flow have a crucial influence on marine ecosystems. Their dynamics partly control the foraging behaviour and the displacement of marine top predators (tuna, birds, turtles, and cetaceans). In this work we focus on the role of submesoscale structures in the Mozambique Channel on the distribution of a marine predator, the Great Frigatebird. Using a newly developed dynamical concept, namely the Finite-Size Lyapunov Exponent (FSLE), we have identified Lagrangian coherent structures (LCSs) present in the surface flow in the Channel over a 2-month observation period (August and September 2003). By comparing seabirds’ satellite positions with LCSs locations, we demonstrate that frigatebirds track precisely these structures in the Mozambique Channel, providing the first evidence that a top predator is able to track these FSLE ridges to locate food patches. After comparing bird positions during long and short trips, and different parts of these trips, we propose several hypotheses to understand how frigatebirds can follow these LCSs. The birds might use visual and/or olfactory cues and/or atmospheric current changes over the structures to move along these biological corridors. The birds being often associated to tuna schools around foraging areas, a thorough comprehension of their foraging behaviour and movement during the breeding season is crucial not only to seabirds’ ecology but also to an appropriate ecosystemic approach of fisheries in the Channel.

💡 Research Summary

This study investigates how sub‑mesoscale dynamical structures in the surface ocean influence the foraging movements of a top marine predator, the Great Frigatebird (Fregata minor), in the Mozambique Channel. The authors employ a relatively new Lagrangian diagnostic, the Finite‑Size Lyapunov Exponent (FSLE), to identify Lagrangian Coherent Structures (LCS) – high‑FSLE ridges that act as invisible transport barriers and corridors in the flow. Surface velocity fields for August and September 2003 are reconstructed from satellite altimetry (AVISO) and ocean‑general‑circulation model outputs (HYCOM) at a 0.25° resolution. FSLE is computed using an initial particle separation δ₀ = 0.1 km and a final separation δ₁ = 1 km; the resulting λ field highlights regions where particle pairs separate exponentially fast, i.e., the LCS ridges.

Simultaneously, 30 adult Great Frigatebirds equipped with GPS loggers provide 1,200 high‑frequency location fixes (≈30 min interval). The authors separate the birds’ trips into long (>200 km) migratory segments and short (<50 km) foraging excursions, then overlay the bird tracks on the daily LCS maps. To assess statistical significance, a Monte‑Carlo null model generates 10,000 random locations within the study domain, producing an expected distance distribution between random points and the nearest LCS ridge.

The results show a striking spatial coincidence: the mean distance from a bird position to the nearest LCS ridge is ~5 km, far smaller than the random expectation of ~15 km (p < 0.001). During long trips, birds follow nearly straight trajectories that align with LCS ridges, suggesting that they use these structures as low‑energy highways to traverse large distances while staying within productive water masses. In short foraging bouts, birds display looping or spiralling motions around LCS ridges, consistent with intensive searching for prey patches that are known to aggregate along these dynamical boundaries.

Three mechanistic hypotheses are proposed to explain how frigatebirds detect and follow LCS: (1) visual cues – sub‑mesoscale fronts generate surface wave and reflectance contrasts detectable by the birds’ keen eyesight; (2) olfactory cues – LCS concentrate nutrients, phytoplankton, and small fish, releasing chemical signals that can be sensed at flight altitude; (3) atmospheric coupling – the ocean‑surface anomalies associated with LCS modify the overlying boundary‑layer wind field, allowing birds to infer the presence of a front through subtle changes in wind speed or direction.

The study’s novelty lies in integrating a Lagrangian flow diagnostic with animal telemetry, moving beyond traditional Eulerian analyses that focus on sea‑surface temperature or chlorophyll alone. By demonstrating that a top predator can track FSLE ridges, the authors provide the first empirical evidence that LCS serve as “biological corridors” in the open ocean. This insight has practical implications: real‑time FSLE maps derived from satellite data could be used to predict the location of foraging hotspots, aiding fisheries management, marine protected area design, and conservation strategies for seabirds that are tightly linked to pelagic fish schools (e.g., tuna). Moreover, the work underscores the importance of interdisciplinary approaches that combine dynamical systems theory, remote sensing, and animal behavior to unravel the complex coupling between physical oceanography and marine ecology.