Light-level geolocator analyses: A user's guide
Light-level geolocator analyses: A user's guide
复制标题
DOI：
10.1111/1365-2656.13036
复制
发表时间：
2020-01-01
影响因子：
4.8
通讯作者：
Bridge, Eli S.
中科院分区：
文献类型：
--
作者：
Lisovski, Simeon;Bauer, Silke;Bridge, Eli S.
光级地理定位器标签使用环境光记录来估计个人在其携带设备的时间内的行踪。在过去的十年中，这些标签已经成为一种重要的工具，并被广泛用于跟踪动物的迁徙，最常见的是小型鸟类。分析地理定位器数据对新科学家和有经验的科学家来说都是令人望而生畏的。在过去几十年中，已经开发出了几种分析方法有根本差异的方法，以科普各种警告和往往复杂的数据。在这里，我们解释了地理定位器数据分析背后的概念，并提供了一个实用的指南，涵盖了大多数分析的常见步骤-黄昏，校准，估计和细化位置的注释，以及运动模式的提取-描述了每个步骤的良好实践和常见陷阱。我们讨论的标准，决定是否地理定位器可以回答提出的研究问题，提供指导，选择适当的分析方法，并介绍最新的开源分析工具的关键功能。我们为如何解释和报告结果提供建议，强调应在出版物中报告并纳入数据存档的参数。最后，我们介绍了一个全面的补充在线手册，将这些概念应用于几个数据集，演示了开源分析工具的使用，并提供了分步说明和代码，并详细介绍了我们对解释，报告和存档的建议。
Light-level geolocator tags use ambient light recordings to estimate the whereabouts of an individual over the time it carried the device. Over the past decade, these tags have emerged as an important tool and have been used extensively for tracking animal migrations, most commonly small birds. Analysing geolocator data can be daunting to new and experienced scientists alike. Over the past decades, several methods with fundamental differences in the analytical approach have been developed to cope with the various caveats and the often complicated data. Here, we explain the concepts behind the analyses of geolocator data and provide a practical guide for the common steps encompassing most analyses - annotation of twilights, calibration, estimating and refining locations, and extraction of movement patterns - describing good practices and common pitfalls for each step. We discuss criteria for deciding whether or not geolocators can answer proposed research questions, provide guidance in choosing an appropriate analysis method and introduce key features of the newest open-source analysis tools. We provide advice for how to interpret and report results, highlighting parameters that should be reported in publications and included in data archiving. Finally, we introduce a comprehensive supplementary online manual that applies the concepts to several datasets, demonstrates the use of open-source analysis tools with step-by-step instructions and code and details our recommendations for interpreting, reporting and archiving.