Walking down a city street, we need only look to brightly lit restaurant signs to find our next meal, but animals searching for food in the wild must use cues from complex and changing environments. One of the most dynamic environments is found in coastal areas where seabirds must locate prey in the ever-changing flow of tidal waters. The foraging of various animals has been associated with large-scale features of the open ocean, like the swirling water of 100 km wide eddies, but it was not known what cues birds use to find prey at distances of 10–100 m where feeding actually occurs. In a recent study, Lilian Lieber of Queen's University Belfast, UK, and colleagues in Germany and the UK asked whether surface features such as the spinning and roiling of turbulent water could present visual cues to guide the searching seabirds. Specifically, they predicted that foraging behavior would be affected by turbulent features of the water's surface and the distance of these features from the birds.
The researchers focused on three species of terns foraging in the local flow generated by a decommissioned tidal energy structure in a tidal channel in Northern Ireland. Using an aerial drone, they recorded an overhead view of the water's surface simultaneously with the movements of terns flying over the channel. Lieber and her colleagues then used machine learning to track individual birds and calculate flight movements to determine whether birds were actively feeding by swooping and diving using slower speeds, or were transiting across the environment with faster and more direct flight. By tracking natural particles on the water's surface, they also reconstructed local surface water velocity through time and identified types of turbulent flow, including spinning vortices and upwelling, where deep water rises and spreads outward at the surface. Finally, they used statistical modeling to relate the flight path of individual birds to turbulent features below the bird, as well as those ahead of their flight path to test the prediction that terns modify their behavior based on visual information from the ocean surface.
The scientists found that terns were more likely to swoop, dive and feed at the surface when the water beneath them was swirling in strong vortices, consistent with their predictions. This turbulent feature could be important for finding food, because small fish can become trapped in the spinning water. Terns were also less likely to start actively catching prey when a strong upwelling was ahead of their flight path. As upwelling structures develop over time, new vortices begin to spin at the edges of the spreading water, which start to accumulate tasty prey. By sticking to their flight plan, instead of turning or diving when deep water upwells ahead, the birds could be anticipating rich pickings at the edges of the water structure when they arrive a few moments later.
Using drones is a powerful way to connect bird behavior to surface features of the ocean, which will be particularly important as man-made structures that disrupt the natural flow of water continue to change coastal environments. Although foraging animals likely use many cues to find food, this approach revealed the first evidence that seabirds may extract visual information from physical features of the water to guide foraging behavior at local scales. So, for these birds, it seems the sea itself says ‘bon appétit’.
