4.7 Article

A bird's-eye view on turbulence: seabird foraging associations with evolving surface flow features

出版社

ROYAL SOC
DOI: 10.1098/rspb.2021.0592

关键词

foraging cues; seabirds; oceanographic features; turbulence; unmanned aerial vehicles; hidden Markov model

资金

  1. Special EU Programmes [IVA5048]

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The study highlights the importance of understanding physical mechanisms underlying seabird foraging, particularly focusing on how turbulent features in the water can serve as foraging cues. Using a drone-based approach, they were able to track surface-foraging terns and correlate their behavior with dynamic turbulent surface flow features, providing insight into the factors influencing seabird foraging behavior.
Understanding physical mechanisms underlying seabird foraging is fundamental to predict responses to coastal change. For instance, turbulence in the water arising from natural or anthropogenic structures can affect foraging opportunities in tidal seas. Yet, identifying ecologically important localized turbulence features (e.g. upwellings approximately 10-100 m) is limited by observational scale, and this knowledge gap is magnified in volatile predators. Here, using a drone-based approach, we present the tracking of surface-foraging terns (143 trajectories belonging to three tern species) and dynamic turbulent surface flow features in synchrony. We thereby provide the earliest evidence that localized turbulence features can present physical foraging cues. Incorporating evolving vorticity and upwelling features within a hidden Markov model, we show that terns were more likely to actively forage as the strength of the underlying vorticity feature increased, while conspicuous upwellings ahead of the flight path presented a strong physical cue to stay in transit behaviour. This clearly encapsulates the importance of prevalent turbulence features as localized foraging cues. Our quantitative approach therefore offers the opportunity to unlock knowledge gaps in seabird sensory and foraging ecology on hitherto unobtainable scales. Finally, it lays the foundation to predict responses to coastal change to inform sustainable ocean development.

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