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Data from: Direction matching for sparse movement data sets: determining interaction rules in social groups

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DataCite Commons2025-11-20 更新2025-04-09 收录
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https://borealisdata.ca/citation?persistentId=doi:10.5683/SP3/UBPQB8
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<b>Abstract</b><br/>It is generally assumed that high-resolution movement data are needed to extract meaningful decision-making patterns of animals on the move. Here we propose a modified version of force matching (referred to here as direction matching), whereby sparse movement data (i.e., collected over minutes instead of seconds) can be used to test hypothesized forces acting on a focal animal based on their ability to explain observed movement. We first test the direction matching approach using simulated data from an agent-based model, and then go on to apply it to a sparse movement data set collected on a troop of baboons in the DeHoop Nature Reserve, South Africa. We use the baboon data set to test the hypothesis that an individual’s motion is influenced by the group as a whole or, alternatively, whether it is influenced by the location of specific individuals within the group. Our data provide support for both hypotheses, with stronger support for the latter. The focal animal showed consistent patterns of movement toward particular individuals when distance from these individuals increased beyond 5.6 m. Although the focal animal was also sensitive to the group movement on those occasions when the group as a whole was highly clustered, these conditions of isolation occurred infrequently. We suggest that specific social interactions may thus drive overall group cohesion. The results of the direction matching approach suggest that relatively sparse data, with low technical and economic costs, can be used to test between hypotheses on the factors driving movement decisions.

<b>摘要</b><br/>学界普遍认为,要提取移动中动物的有效决策模式,需获取高分辨率的运动数据。本文提出一种改进版的力匹配(force matching)方法,本文中将其称为方向匹配(direction matching);该方法可利用稀疏运动数据(即采集间隔以分钟而非秒为单位),基于对观测运动的解释能力,检验作用于目标动物的假设受力情况。我们首先基于智能体模型(agent-based model)生成的模拟数据,对方向匹配方法进行验证,随后将其应用于南非DeHoop自然保护区内一群狒狒的稀疏运动数据集。我们利用该狒狒数据集检验两个对立假设:一是个体运动受整个群体的影响,二是个体运动受群体内特定其他个体的位置影响。本研究的数据对两个假设均提供了支持,且对后者的支持力度更强。当目标个体与特定同伴的距离超过5.6米时,目标动物会表现出朝向该同伴移动的一致模式。尽管当整个群体高度聚集时,目标动物也会对群体运动做出响应,但此类场景的发生频率较低。本研究据此认为,特定的社会互动或许是推动整体群体凝聚力的关键因素。方向匹配方法的研究结果表明,技术与经济成本较低的相对稀疏的运动数据,可用于检验关于驱动运动决策的各类影响因素的假设。
提供机构:
Borealis
创建时间:
2024-12-03
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