Replication Data for: Virtual fencing in remote boreal forests: performance of commercially available GPS collars for free-ranging cattle

This dataset contains all the raw data sets, processing code, and analysis for reproducing and replicating the analysis for the article: Virtual fencing in remote boreal forests: performance of commercially available GPS collars for free-ranging cattle. In total there are 21 files included, from which '01_Analysis.html' and '01_Analysis.pdf' describes the final output of all analysis and includes the figures as published in the article. '01_Analysis.qmd' is a quarto markdown file (Quarto is a multi-language, next generation version of R Markdown from Posit, see https://quarto.org/) which makes it possible to rerun the analysis. This file is dependent on the other files and the original folder structure. The dependent files include spatial information from the GPS collars ('collars.csv' and 'collars_new.csv'), measures from the differential GPS ('dGPS.csv' and 'dGPS_new.csv'), observations from field personnel ('kobo_forms.csv'), environmental information (all '.tiff' files), and other supporting information. Furthermore, data pre processing is conducted in the R-script '02_preparation_data.R' creating two output files ('processed_data_mob.txt' and 'processed_data_stat.txt'). This script can be optionally sourced from '01_Analysis.qmd'.
Article abstract: Background The use of virtual fencing in cattle farming is beneficial due to its flexibility, not fragmenting the landscape or restricting access like physical fences. Using GPS technology, virtual fence units emit an audible signal and a low-energy electric shock when crossing a predefined border. However, animal welfare concerns arise from potential stress and confusion caused by GPS errors. Especially in large remote grazing areas and complex terrains, where the performance of the GPS units can be affected by landscape structure, errors can lead to unnecessary shocks to the animals. This study aimed to explore factors affecting the GPS performance of commercially available virtual fence collars for cattle (NoFence©), both using static tests and mobile tests, i.e. when deployed on free-ranging cattle. Results The static tests revealed generally high fix success rates (% successful positioning attempts), and a lower success rate at four of 30 test locations was most likely due to a lack in GSM coverage. On average the GPS precision and accuracy errors were 3.3 m ±2.5 SD and 4.6 m ±3.2 SD, respectively. We found strong evidence that the GPS precision and accuracy errors were affected by the canopy cover, with increased errors under closed canopies. We also found evidence for an effect of the sky-view on the GPS performance, although at a lesser extent than canopy. The direction of the accuracy error in the cartesian plane was not uniform, but biased, depending on the aspect of the test locations. With an average of 10.8 m ±6.8 SD, the accuracy error of the mobile tests was more than double that of the static tests. Furthermore, we found evidence that more rugged landscapes resulted in higher GPS accuracy errors. However, the error was not affected by canopy cover, sky-view, or behaviors during the mobile tests. Conclusions This study showed that GPS performance can be negatively affected by landscape complexity, such as increased ruggedness and covered habitats, resulting in reduced virtual fence effectiveness and potential welfare concerns for cattle. These issues can be mitigated through proper pasture planning, such as avoiding rugged areas for the virtual fence border.

本数据集汇集了所有原始数据集、处理代码及分析，旨在复现并复制关于《远程北方针叶林中的虚拟围栏：商用GPS项圈对放牧牛只性能的影响》一文的分析。数据集共包含21个文件，其中'01_Analysis.html'和'01_Analysis.pdf'详细描述了所有分析结果的最终输出，并包含了与文章中发表的图表。'01_Analysis.qmd'为Quarto markdown文件（Quarto是Posit公司推出的下一代多语言R Markdown，详见https://quarto.org/），使得重新运行分析成为可能。此文件依赖于其他文件及原始的文件夹结构。依赖文件包括来自GPS项圈的空间信息（'collars.csv'和'collars_new.csv'）、差分GPS的测量数据（'dGPS.csv'和'dGPS_new.csv'）、来自现场工作人员的观察数据（'kobo_forms.csv'）、环境信息（所有'.tiff'文件）以及其他辅助信息。此外，数据预处理通过R脚本'02_preparation_data.R'进行，生成两个输出文件（'processed_data_mob.txt'和'processed_data_stat.txt'）。此脚本可从'01_Analysis.qmd'中可选导入。

文章摘要：背景 cattle 养殖中虚拟围栏的应用因其灵活性而有益，它不会破碎景观或限制访问，与物理围栏不同。利用GPS技术，虚拟围栏单元在跨越预设边界时发出声音信号和低能量电击。然而，GPS错误可能引起的压力和困惑引发了动物福利的担忧。特别是在大型远程放牧区和复杂地形中，GPS单元的性能可能受到景观结构的影响，错误可能导致动物受到不必要的电击。本研究旨在探讨影响商用虚拟围栏项圈（NoFence©）对牛只GPS性能的多种因素，包括静态测试和移动测试，即当部署在放牧牛只上时的情况。结果 静态测试揭示了普遍较高的定位成功率（%成功定位尝试），在30个测试点中的4个测试点的成功率较低，最可能的原因是GSM覆盖不足。平均而言，GPS的精度和误差分别为3.3米±2.5标准差和4.6米±3.2标准差。我们发现GPS精度和误差受到林冠覆盖的影响，林冠覆盖增加时误差增大。我们还发现天空视野对GPS性能有影响，尽管程度不如林冠。笛卡尔平面上的精度误差方向并不均匀，而是有偏差，取决于测试点的方位。移动测试的精度误差平均为10.8米±6.8标准差，是静态测试的两倍以上。此外，我们发现崎岖的地形会导致更高的GPS精度误差。然而，误差不受林冠覆盖、天空视野或移动测试中的行为的影响。结论 本研究表明，GPS性能可能受到景观复杂性的负面影响，如崎岖度和覆盖栖息地的增加，从而导致虚拟围栏的有效性降低，并对牛只的福利产生潜在影响。这些问题可以通过适当的放牧规划来缓解，例如避免在崎岖区域设置虚拟围栏边界。