Human activities have profoundly altered the spatio-temporal availability of food resources. Yet, there is a clear lack of knowledge on how opportunistic species adapt to these new circumstances by scheduling their daily rhythms and adjust their foraging decisions to predicable patterns of anthropic food subsidies. Here, we used nearly continuous GPS tracking data to investigate the adaptability of daily foraging activity in an opportunistic predator, the yellow-legged gull (Larus michahellis), in response to human schedules. By using waveform analysis, we compared timing and magnitude of peaks in daily activity of different GPS-tracked individuals in eleven different habitat types, in relation to type of day (i.e., weekday vs. weekend). Daily activity rhythms varied greatly depending on whether it was a weekday or weekend, thus suggesting that gulls’ activity peaks matched the routines of human activity in each habitat type. We observed for the first time two types of activity as modelled by waveforms analysis: marine habitats showed unimodal patterns with prolonged activity and terrestrial habitats showed bimodal patterns with two shorter and variable activity peaks. Our results suggest that gulls are able to fine-tune their daily activity rhythms to habitat-specific human schedules, since these likely provide feeding opportunities. Behavioral plasticity may thus be an important driver of expansive population dynamics. Information on predictable relationships between daily activity patterns of gulls and human activities is therefore relevant to their population management.

中文翻译：

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生活在人类景观中的机会主义捕食者的行为节奏。


人类活动深刻改变了食物资源的时空可用性。然而，对于机会主义物种如何通过安排日常节奏并根据可预测的人类食物补贴模式调整觅食决策来适应这些新环境，人们显然缺乏了解。在这里，我们使用近乎连续的 GPS 跟踪数据来研究机会主义捕食者黄腿鸥 (Larus michahellis) 的日常觅食活动对人类日程安排的适应性。通过使用波形分析，我们比较了 11 种不同栖息地类型中不同 GPS 跟踪个体的日常活动峰值的时间和幅度，以及与一天类型（即工作日与周末）的关系。日常活动节奏根据工作日或周末的不同而有很大差异，因此表明海鸥的活动高峰与每种栖息地类型的人类活动惯例相匹配。我们首次观察到通过波形分析建模的两种类型的活动：海洋栖息地显示出具有长时间活动的单峰模式，而陆地栖息地则显示出具有两个较短且可变的活动峰值的双峰模式。我们的结果表明，海鸥能够根据栖息地特定的人类时间表微调其日常活动节奏，因为这可能提供进食机会。因此，行为可塑性可能是人口动态扩张的重要驱动因素。因此，有关海鸥日常活动模式与人类活动之间可预测关系的信息与其种群管理相关。