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Using Spatially Explicit Simulated Data to Analyze Animal Interactions: A Case Study with Brown Hyenas in Northern Botswana

机译:使用空间显式模拟数据分析动物相互作用:以博茨瓦纳北部的棕色鬣狗为例

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摘要

New developments in global positioning systems (GPS) and related satellite tracking technologies have facilitated the collection of highly accurate data on moving objects, far surpassing the ability to analyze them. Within geographic information science, 'movement pattern analysis' (MPA) has developed as a subfield that addresses concepts and theories used to explore the spatio-temporal structure in data, although the methodological and analytical framework associated with MPA is new and still evolving. Interactions between individuals can be considered a second order property of movement and have been far less studied. The nature of interactions between individuals in a population is a fundamental aspect of a species' behavioral ecology and information on the frequency and duration of these interactions is vital to understanding mating and territorial behavior, resource use, and infectious disease epidemiology. The focus of this work was to explore how spatially explicit simulated data can be used to analyse dynamic interactions between individuals. Five different techniques that have been used to quantify dynamic interactions based on GPS data of pairs of individuals were utilised, and all were compared in the context of spatially explicit simulated data intended to represent biologically realistic null models for individual movement, and subsequently paired interactions.
机译:全球定位系统(GPS)和相关卫星跟踪技术的新发展促进了有关移动物体的高精度数据的收集,远远超出了对其进行分析的能力。在地理信息科学中,“运动模式分析”(MPA)已发展为一个子领域,致力于解决用于探索数据时空结构的概念和理论,尽管与MPA相关的方法和分析框架仍在不断发展。人与人之间的相互作用可以被认为是运动的二阶性质,而对其的研究则很少。种群中个体之间相互作用的性质是物种行为生态学的基本方面,并且有关这些相互作用的频率和持续时间的信息对于理解交配和领土行为,资源利用和传染病流行病学至关重要。这项工作的重点是探索如何使用空间明确的模拟数据来分析个人之间的动态交互。利用了五种不同的技术,这些技术已被用于基于一对个人的GPS数据来量化动态相互作用,并且在空间明确的模拟数据的背景下对所有这些技术进行了比较,这些数据旨在代表个体运动的生物学真实的空模型,以及随后的配对相互作用。

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