使用wildlifeDI R软件包分析高频跟踪数据中的接触和行为

IF 3.3 3区 地球科学 Q1 GEOGRAPHY Geographical Analysis Pub Date : 2021-09-01 DOI:10.1111/gean.12303
Jed A. Long, Stephen L. Webb, Seth M. Harju, Kenneth L. Gee
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引用次数: 5

摘要

个体间的相互作用是驱动野生动物运动模式的关键因素之一;然而,从野生动物跟踪数据中捕捉和分析个体间相互作用的方法仍然有限。从野生动物追踪数据中提取接触者是一项挑战,因为追踪数据集的时空格局复杂且数量庞大。了解接触的时间和地点对于理解接触的时空模式以及它们与环境、个体行为和社会结构的关系至关重要。在本文中,我们将介绍wildlifeDI R包中的一套新功能,用于自动化接触分析、摘要和输出(例如,可视化),这些功能来自于同时跟踪许多个体的研究,它建立在研究包中已经存在的双体之间交互行为的现有方法之上。该软件包用于研究动物行为、社会网络和疾病传播的接触和相互作用。本研究展示了利用野生生物信息包进行接触分析的两种应用:雌性白尾鹿(Odocoileus virginianus)的接触和猎人与雄性白尾鹿之间的接触。wildlifeDI包代表了一套新的先进的、可重复的分析,用于识别和研究野生动物跟踪研究中的接触和相互作用。我们设计了分析和输出,以整合到现有的R分析工作流程中,以促进在各种野生动物跟踪研究中采用该软件包。
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Analyzing Contacts and Behavior from High Frequency Tracking Data Using the wildlifeDI R Package

Inter-individual interactions are one of the key factors driving patterns of wildlife movement; however, methods for capturing and analyzing inter-individual interactions from wildlife tracking data remain limited. Extracting contacts from wildlife tracking data is a challenge owing to the complex spatial and temporal patterns and the volume of tracking data sets. Knowledge of the time and location of contacts are crucial to understanding the spatiotemporal patterns of contacts and how they relate to the environment, individual behavior, and social structure. In this article we introduce a new suite of functions in the wildlifeDI R package for automating contact analysis, summaries, and outputs (e.g., visualizations) from studies tracking many individuals simultaneously, building upon the existing methods for studying interactive behavior between dyads already present within the package. The package has applications to study contact and interaction for the study of animal behavior, social networks, and disease transmission. We demonstrate two applications of contact analysis using the wildlifeDI package: female white-tailed deer (Odocoileus virginianus) contacts and contacts between hunters and male white-tailed deer. The wildlifeDI package represents a new set of advanced, reproducible analyses to identify and study contacts and interactions in wildlife tracking studies. We designed the analyses and outputs to integrate into existing R analysis workflows to facilitate adoption of the package into a wide variety of wildlife tracking studies.

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来源期刊
CiteScore
8.70
自引率
5.60%
发文量
40
期刊介绍: First in its specialty area and one of the most frequently cited publications in geography, Geographical Analysis has, since 1969, presented significant advances in geographical theory, model building, and quantitative methods to geographers and scholars in a wide spectrum of related fields. Traditionally, mathematical and nonmathematical articulations of geographical theory, and statements and discussions of the analytic paradigm are published in the journal. Spatial data analyses and spatial econometrics and statistics are strongly represented.
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