Assessment of a livestock GPS collar based on an open-source datalogger informs best practices for logging intensity.
Assessment of a livestock GPS collar based on an open-source datalogger informs best practices for logging intensity.
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DOI：
10.1002/ece3.4094
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发表时间：
2018-06
影响因子：
2.6
通讯作者：
Spiess JW
中科院分区：
文献类型：
--
作者：
McGranahan DA;Geaumont B;Spiess JW
30年来，生态学家一直使用全球定位系统（GPS）来跟踪动物。当今的问题包括日志记录频率和估计空间使用和行驶距离的精确度，以及电池寿命和成本。我们开发了一款基于Arduino的低成本（约125美元）开源GPS数据记录器。为了测试该系统，我们在北达科他州的牧场上以20秒的间隔收集了几个1周的牛和羊的位置。我们测试了两个生态学家感兴趣的问题，这些生态学家使用GPS项圈来跟踪动物的运动：（1）有项圈的动物在他们的牛群中聚集的程度如何？(2)不同的记录模式如何评估斑块占用率和每日总行驶距离？测试的记录模式包括常规记录（每5或10分钟记录一个位置）和突发记录（每小时记录5或10分钟，间隔20秒，然后是睡眠期）。领羊在同一个牧场花了75%的白天时间在51米的其他（平均值= 42米）;领牛在111米（平均值= 76米）。在我们比较不同的测井模式与恒定测井模式对空间使用的估计程度时，在1公顷和16公顷斑块中记录的位置比例对于突发测井相差2%-3%，对于常规测井相差1%。虽然所有的记录模式低估了总的每日行驶距离，低估进行了纠正乘估计的回归系数估计的最大似然。突发记录可以将电池寿命延长7倍。我们的结论是，最少两个衣领编程与突发记录稳健估计补丁的使用和放牧牲畜群的空间分布。然而，需要准确估计个体动物旅行的研究问题可能最好通过定期记录间隔来解决，因此在所有GPS数据记录器系统中，电池需求比空间占用问题更大。
Ecologists have used Global Positioning Systems (GPS) to track animals for 30 years. Issues today include logging frequency and precision in estimating space use and travel distances, as well as battery life and cost. We developed a low‐cost (~US$125), open‐source GPS datalogger based on Arduino. To test the system, we collected positions at 20‐s intervals for several 1‐week durations from cattle and sheep on rangeland in North Dakota. We tested two questions of broad interest to ecologists who use GPS collars to track animal movements: (1) How closely do collared animals cluster in their herd? (2) How well do different logging patterns estimate patch occupancy and total daily distance traveled? Tested logging patterns included regular logging (one position every 5 or 10 min), and burst logging (positions recorded at 20‐s intervals for 5 or 10 min per hour followed by a sleep period). Collared sheep within the same pasture spent 75% of daytime periods within 51 m of each other (mean = 42 m); collared cattle were within 111 m (mean = 76 m). In our comparison of how well different logging patterns estimate space use versus constant logging, the proportion of positions recorded in 1‐ and 16‐ha patches differed by 2%–3% for burst logging and 1% for regular logging. Although all logging patterns underestimated total daily distance traveled, underestimations were corrected by multiplying estimations by regression coefficients estimated by maximum likelihood. Burst logging can extend battery life by a factor of 7. We conclude that a minimum of two collars programmed with burst logging robustly estimate patch use and spatial distribution of grazing livestock herds. Research questions that require accurately estimating travel of individual animals, however, are probably best addressed with regular logging intervals and will thus have greater battery demands than spatial occupancy questions across all GPS datalogger systems.
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