A wrap-around movement path randomization method to distinguish social and spatial drivers of animal interactions.

IF 5.4 2区 生物学 Q1 BIOLOGY Philosophical Transactions of the Royal Society B: Biological Sciences Pub Date : 2024-10-21 Epub Date: 2024-09-04 DOI:10.1098/rstb.2022.0531
Kaija Gahm, Ryan Nguyen, Marta Acácio, Nili Anglister, Gideon Vaadia, Orr Spiegel, Noa Pinter-Wollman
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Abstract

Studying the spatial-social interface requires tools that distinguish between social and spatial drivers of interactions. Testing hypotheses about the factors determining animal interactions often involves comparing observed interactions with reference or 'null' models. One approach to accounting for spatial drivers of social interactions in reference models is randomizing animal movement paths to decouple spatial and social phenotypes while maintaining environmental effects on movements. Here, we update a reference model that detects social attraction above the effect of spatial constraints. We explore the use of our 'wrap-around' method and compare its performance to the previous approach using agent-based simulations. The wrap-around method provides reference models that are more similar to the original tracking data, while still distinguishing between social and spatial drivers. Furthermore, the wrap-around approach results in fewer false-positives than its predecessor, especially when animals do not return to one place each night but change movement foci, either locally or directionally. Finally, we show that interactions among GPS-tracked griffon vultures (Gyps fulvus) emerge from social attraction rather than from spatial constraints on their movements. We conclude by highlighting the biological situations in which the updated method might be most suitable for testing hypotheses about the underlying causes of social interactions. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

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一种环绕运动路径随机化方法,用于区分动物互动的社会和空间驱动因素。
研究空间-社会界面需要能够区分相互作用的社会和空间驱动因素的工具。检验决定动物互动因素的假设往往需要将观察到的互动与参考模型或 "空 "模型进行比较。在参考模型中考虑社会互动的空间驱动因素的一种方法是随机化动物的运动路径,在保持环境对运动的影响的同时将空间表型和社会表型脱钩。在这里,我们更新了一个参考模型,该模型可以检测到高于空间限制效应的社会吸引力。我们探索了 "环绕 "方法的使用,并通过基于代理的模拟将其性能与之前的方法进行了比较。环绕法提供的参考模型与原始跟踪数据更为相似,同时仍能区分社交和空间驱动因素。此外,与前一种方法相比,环绕法产生的假阳性结果更少,尤其是当动物每晚不返回一个地方,而是在局部或方向上改变运动中心时。最后,我们表明,GPS 跟踪的狮鹫(Gyps fulvus)之间的互动来自于社会吸引,而不是它们运动的空间限制。最后,我们强调了更新方法可能最适合用于检验有关社会互动根本原因的假设的生物情况。本文是主题 "空间-社会界面:理论与经验的整合 "的一部分。
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来源期刊
CiteScore
11.80
自引率
1.60%
发文量
365
审稿时长
3 months
期刊介绍: The journal publishes topics across the life sciences. As long as the core subject lies within the biological sciences, some issues may also include content crossing into other areas such as the physical sciences, social sciences, biophysics, policy, economics etc. Issues generally sit within four broad areas (although many issues sit across these areas): Organismal, environmental and evolutionary biology Neuroscience and cognition Cellular, molecular and developmental biology Health and disease.
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