Data from: Evaluation of Argos telemetry accuracy in the High-Arctic and implications for the estimation of home-range size

Animal tracking through Argos satellite telemetry has enormous potential to test hypotheses in animal behavior, evolutionary ecology, or conservation biology. Yet the applicability of this technique cannot be fully assessed because no clear picture exists as to the conditions influencing the accuracy of Argos locations. Latitude, type of environment, and transmitter movement are among the main candidate factors affecting accuracy. A posteriori data filtering can remove “bad” locations, but again testing is still needed to refine filters. First, we evaluate experimentally the accuracy of Argos locations in a polar terrestrial environment (Nunavut, Canada), with both static and mobile transmitters transported by humans and coupled to GPS transmitters. We report static errors among the lowest published. However, the 68th error percentiles of mobile transmitters were 1.7 to 3.8 times greater than those of static transmitters. Second, we test how different filtering methods influence the quality of Argos location datasets. Accuracy of location datasets was best improved when filtering in locations of the best classes (LC3 and 2), while the Douglas Argos filter and a homemade speed filter yielded similar performance while retaining more locations. All filters effectively reduced the 68th error percentiles. Finally, we assess how location error impacted, at six spatial scales, two common estimators of home-range size (a proxy of animal space use behavior synthetizing movements), the minimum convex polygon and the fixed kernel estimator. Location error led to a sometimes dramatic overestimation of home-range size, especially at very local scales. We conclude that Argos telemetry is appropriate to study medium-size terrestrial animals in polar environments, but recommend that location errors are always measured and evaluated against research hypotheses, and that data are always filtered before analysis. How movement speed of transmitters affects location error needs additional research.

基于Argos卫星遥测技术（Argos satellite telemetry）的动物追踪研究，在检验动物行为、进化生态学或保护生物学领域的研究假说方面具备巨大应用潜力。然而，该技术的应用价值尚未得到全面评估，因为目前尚未明确哪些条件会影响Argos定位的精度。纬度、环境类型以及发射器的运动状态，是影响定位精度的主要候选因素之一。后验数据滤波（a posteriori data filtering）可剔除"劣质"定位点，但仍需通过实验进一步优化滤波方案。首先，我们通过实验评估了加拿大努纳武特（Nunavut）地区极地陆地环境中的Argos定位精度：实验采用由人类携带的静态与移动发射器，并将其与GPS发射器（GPS transmitter）配对使用。本研究测得的静态定位误差为已发表文献中的最低值之一。不过，移动发射器的68%误差分位数是静态发射器的1.7至3.8倍。其次，我们测试了不同滤波方法对Argos定位数据集质量的影响。当仅对最优定位等级（LC3与LC2）的定位点进行滤波时，定位数据集的精度提升效果最佳；道格拉斯Argos滤波器（Douglas Argos filter）与自制速度滤波器（homemade speed filter）的性能表现相近，且可保留更多有效定位点。所有滤波方法均有效降低了68%误差分位数。最后，我们在六种空间尺度下，评估了定位误差对两种常用家域面积估算方法的影响：最小凸多边形法（minimum convex polygon）与固定核密度估计法（fixed kernel estimator），二者均为用于表征动物空间利用行为的运动综合替代指标。定位误差常会导致家域面积被显著高估，尤其是在极小空间尺度下。综上，Argos卫星遥测技术适用于极地环境中的中型陆地动物研究，但建议始终结合研究假说对定位误差进行测量与评估，并在分析前对数据进行滤波处理。发射器的运动速度如何影响定位误差，仍有待进一步开展研究。