five

Data from: Herring gulls respond to human gaze direction

收藏
DataCite Commons2025-05-01 更新2025-04-09 收录
下载链接:
https://datadryad.org/dataset/doi:10.5061/dryad.3jf80g4
下载链接
链接失效反馈
官方服务:
资源简介:
Human-wildlife conflict is one of the greatest threats to species populations worldwide. One species facing national declines in the UK is the herring gull (Larus argentatus), despite an increase in numbers in urban areas. Gulls in urban areas are often considered a nuisance due to behaviours such as food-snatching. Whether urban gull feeding behaviour is influenced by human behavioural cues, such as gaze direction, remains unknown. We therefore measured the approach times of herring gulls to a food source placed in close proximity to an experimenter who either looked directly at the gull or looked away. We found that only 26% of targeted gulls would touch the food, suggesting that food-snatching is likely to be conducted by a minority of individuals. When gulls did touch the food, they took significantly longer to approach when the experimenter’s gaze was directed towards them compared to directed away. However, inter-individual behaviour varied greatly, with some gulls approaching similarly quickly in both treatments while others approached much more slowly when the experimenter was looking at them. These results indicate that reducing human-herring gull conflict may be possible through small changes in human behaviour, but will require consideration of behavioural differences between individual gulls.

人兽冲突(Human-wildlife conflict)是全球物种种群面临的最严重威胁之一。在英国,银鸥(herring gull,学名Larus argentatus)的种群数量在全国范围内呈下降趋势,尽管其在城市区域的数量有所增加。城市中的银鸥常因抢食等行为被视为扰民生物。城市银鸥的取食行为是否受人类行为线索(behavioural cues)的影响,如注视方向,目前仍不明确。为此,我们测量了银鸥接近食物源的时间——食物源被放置在实验者附近,而实验者会对银鸥采取直视或回避注视两种方式。结果显示,仅有26%的目标银鸥会触碰食物,这表明抢食行为可能仅由少数个体实施。在银鸥触碰食物的情况下,实验者直视时,银鸥的接近时间显著长于实验者回避注视时。然而,个体间行为差异显著:部分银鸥在两种处理方式下的接近速度相近,而另一些银鸥在实验者直视时的接近速度则慢得多。这些结果表明,通过调整人类行为的细微变化或许能减少人鸥冲突,但需考虑银鸥个体间的行为差异。
提供机构:
Dryad
创建时间:
2019-07-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作