Data from: Novel, continuous monitoring of fine-scale movement using fixed-position radio telemetry arrays and random forest location fingerprinting

1. Radio-tag signals from fixed-position antennas are most often used to indicate presence/absence of individuals, or to estimate individual activity levels from signal strength variation within an antenna’s detection zone. The potential of such systems to provide more precise information on tag location and movement has not been explored in great detail in an ecological setting. 2. By reversing the roles that transmitters and receivers play in localization methods common to the telecommunications industry, we present a new telemetric tool for accurately estimating the location of tagged individuals from received signal strength values. The methods used to characterize the study area in terms of received signal strength are described, as is the random forest model used for localization. The resulting method is then validated using test data before being applied to true data collected from tagged individuals in the study site. 3. Application of the localization method to test data withheld from the learning dataset indicated a low average error over the entire study area (< 1m) while application of the localization method to real data produced highly probable results consistent with field observations. 4. This telemetric approach provided detailed movement data for tagged fish along a single axis (a migratory path) and is particularly useful for monitoring passage along migratory routes. The new methods applied in this study can also be expanded to include multiple axes (x, y, z) and multiple environments (aquatic and terrestrial) for remotely monitoring wildlife movement.1. 固定位置天线（fixed-position antennas）接收的无线电标记信号（Radio-tag signals），通常用于指示标记个体的出现或消失，或是通过天线探测区域（detection zone）内的信号强度变化（signal strength variation）估算个体的活动水平。然而，此类系统为标记个体位置与移动轨迹提供更精准信息的潜力，在生态场景（ecological setting）中尚未得到充分细致的探索。 2. 本研究反转电信行业（telecommunications industry）通用定位方法中发射机与接收机的角色，提出一种全新的遥测工具（telemetric tool），可基于接收信号强度值（received signal strength values）精准估算标记个体的位置。本文详述了以接收信号强度为依据表征研究区域的方法，以及用于定位的随机森林模型（Random Forest model）。所提出的定位方法首先通过测试数据完成验证，随后才应用于研究样地中标记个体采集的真实观测数据。 3. 将定位方法应用于从学习数据集（learning dataset）中预留的测试数据后，结果显示整个研究区域内的平均定位误差极低（小于1米）；而将该方法应用于真实观测数据时，所得结果置信度极高，且与野外观测结果（field observations）高度一致。 4. 该遥测方法可为沿单轴（洄游路径）移动的标记鱼类提供精细化的移动数据，尤其适用于洄游通道的通行监测。本研究采用的新型方法还可进一步扩展，支持多轴（x、y、z）监测以及多环境（水生与陆生环境，aquatic and terrestrial environments）下的野生动物移动远程监测。