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湍流的鸟瞰视角:海鸟觅食与不断演变的表层水流特征的关联

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

作者信息

Lieber Lilian, Langrock Roland, Nimmo-Smith W Alex M

机构信息

School of Chemistry and Chemical Engineering, Queen's University Belfast, Marine Laboratory, 12-13 The Strand, Portaferry BT22 1PF, Northern Ireland, UK.

Department of Business Administration and Economics, Bielefeld University, Postfach 10 01 31, 33501 Bielefeld, Germany.

出版信息

Proc Biol Sci. 2021 Apr 28;288(1949):20210592. doi: 10.1098/rspb.2021.0592.

Abstract

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.

摘要

了解海鸟觅食背后的物理机制是预测其对海岸变化反应的基础。例如,自然或人为结构引起的水中湍流会影响潮汐海域的觅食机会。然而,识别具有生态重要性的局部湍流特征(例如约10 - 100米的上升流)受到观测尺度的限制,而这种知识差距在易变的捕食者中被放大。在这里,我们采用基于无人机的方法,同步呈现了海面觅食燕鸥(属于三种燕鸥物种的143条轨迹)和动态湍流表面流特征的追踪情况。我们由此提供了最早的证据,表明局部湍流特征可以呈现物理觅食线索。将不断演变的涡度和上升流特征纳入隐马尔可夫模型,我们发现随着潜在涡度特征强度的增加,燕鸥更有可能积极觅食,而飞行路径前方明显的上升流则为保持飞行行为提供了强烈的物理线索。这清楚地体现了普遍存在的湍流特征作为局部觅食线索的重要性。因此,我们的定量方法提供了一个机会,以填补海鸟感官和觅食生态学中迄今无法获得的尺度上的知识空白。最后,它为预测对海岸变化的反应奠定了基础,以指导可持续海洋发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9daa/8079999/b50909c5d643/rspb20210592f01.jpg

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