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美洲虎运动行为:利用轨迹和关联规则挖掘算法揭示行为状态和社会互动。

Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions.

机构信息

Computer Engineering and Digital Systems Department-Escola Politécnica da Universidade de São Paulo (USP), São Paulo, São Paulo, Brazil.

Centro Nacional de Pesquisa e Conservação de Mamíferos Carnívoros (CENAP), ICMBIO, Atibaia, São Paulo, Brazil.

出版信息

PLoS One. 2021 Feb 4;16(2):e0246233. doi: 10.1371/journal.pone.0246233. eCollection 2021.

Abstract

Animal movement data are widely collected with devices such as sensors and collars, increasing the ability of researchers to monitor animal movement and providing information about animal behavioral patterns. Animal behavior is used as a basis for understanding the relationship between animals and the environment and for guiding decision-making by researchers and public agencies about environmental preservation and conservation actions. Animal movement and behavior are widely studied with a focus on identifying behavioral patterns, such as, animal group formation, the distance between animals and their home range. However, we observed a lack of research proposing a unified solution that aggregates resources for analyses of individual animal behavior and of social interactions between animals. The primary scientific contribution of this work is to present a framework that uses trajectory analysis and association rule mining [Jaiswal and Agarwal, 2012] to provide statistical measures of correlation and dependence to determine the relationship level between animals, their social interactions, and their interactions with other environmental factors based on their individual behavior and movement data. We demonstrate the usefulness of the framework by applying it to movement data from jaguars in the Pantanal, Brazil. This allowed us to describe jaguar behavior, social interactions among jaguars and their behavior in different landscapes, thus providing a highly detailed investigation of jaguar movement decisions at the fine scale.

摘要

动物运动数据通常通过传感器和项圈等设备进行收集,这增加了研究人员监测动物运动并提供有关动物行为模式信息的能力。动物行为被用作了解动物与环境之间关系的基础,并为研究人员和公共机构在环境保护和保护行动方面的决策提供指导。动物运动和行为得到了广泛的研究,重点是识别行为模式,例如动物群体形成、动物之间的距离及其家域。然而,我们观察到缺乏提出统一解决方案的研究,该方案可聚合资源,以分析单个动物行为和动物之间的社会互动。这项工作的主要科学贡献是提出了一个框架,该框架使用轨迹分析和关联规则挖掘[Jaiswal 和 Agarwal,2012]来提供相关性和依赖性的统计度量,以根据其个体行为和运动数据确定动物之间、它们的社会互动以及它们与其他环境因素之间的关系水平。我们通过将其应用于巴西潘塔纳尔的美洲虎运动数据来证明该框架的有用性。这使我们能够描述美洲虎的行为、美洲虎之间的社会互动以及它们在不同景观中的行为,从而对美洲虎在精细尺度上的运动决策进行了高度详细的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a97a/7861389/7cdc9d7dca12/pone.0246233.g001.jpg

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