Data from: Calibrating animal-borne proximity loggers

1. Growing interest in the structure and dynamics of animal social networks has stimulated efforts to develop automated tracking technologies that can reliably record encounters in free-ranging subjects. A particularly promising approach is the use of animal-attached ‘proximity loggers’, which collect data on the incidence, duration and proximity of spatial associations through inter-logger radio communication. While proximity logging is based on a straightforward physical principle – the attenuation of propagating radio waves with distance – calibrating systems for field deployment is challenging, since most study species roam across complex, heterogeneous environments. 2. In this study, we calibrated a recently developed digital proximity-logging system (‘Encounternet’) for deployment on a wild population of New Caledonian crows Corvus moneduloides. Our principal objective was to establish a quantitative model that enables robust post hoc estimation of logger-to-logger (and, hence, crow-to-crow) distances from logger-recorded signal-strength values. To achieve an accurate description of the radio communication between crow-borne loggers, we conducted a calibration exercise that combines theoretical analyses, field experiments, statistical modelling, behavioural observations, and computer simulations. 3. We show that, using signal-strength information only, it is possible to assign crow encounters reliably to predefined distance classes, enabling powerful analyses of social dynamics. For example, raw data sets from field-deployed loggers can be filtered at the analysis stage to include predominantly encounters where crows would have come to within a few metres of each other, and could therefore have socially learned new behaviours through direct observation. One of the main challenges for improving data classification further is the fact that crows – like most other study species – associate across a wide variety of habitats and behavioural contexts, with different signal-attenuation properties. 4. Our study demonstrates that well-calibrated proximity-logging systems can be used to chart social associations of free-ranging animals over a range of biologically meaningful distances. At the same time, however, it highlights that considerable efforts are required to conduct study-specific system calibrations that adequately account for the biological and technological complexities of field deployments. Although we report results from a particular case study, the basic rationale of our multi-step calibration exercise applies to many other tracking systems and study species.1. 学界对动物社交网络的结构与动态的兴趣与日俱增，这推动了自动化追踪技术的研发——这类技术可可靠记录自由活动个体的互动遭遇。其中一项极具应用前景的方案是搭载于动物身上的近距离记录器（proximity loggers）：这类设备通过记录器间的无线电通信，采集空间关联的发生频次、持续时长与空间距离等数据。尽管近距离记录的原理十分直观——即传播中的无线电波随距离衰减——但由于多数研究物种会在复杂异质的环境中活动，面向野外部署的系统校准工作仍颇具挑战。2. 本研究针对一款新近研发的数字近距离记录系统（"Encounternet"）开展校准工作，以将其部署于新喀里多尼亚乌鸦（Corvus moneduloides）的野生种群中。本研究的核心目标是构建量化模型，以实现通过记录器采集的信号强度值，稳健地事后估算记录器间（进而对应乌鸦间）的空间距离。为精准刻画乌鸦携带的记录器之间的无线电通信过程，本研究整合理论分析、野外实验、统计建模、行为观测与计算机仿真等手段完成了校准流程。3. 研究结果表明，仅依靠信号强度信息，即可将乌鸦的互动遭遇可靠归类至预设的距离等级中，从而为社交动态分析提供有力支撑。例如，在分析阶段可对野外部署记录器获取的原始数据集进行筛选，仅保留乌鸦间距离在数米以内的互动记录——这类场景下乌鸦可通过直接观察习得新的社会行为。进一步优化数据分类精度所面临的核心挑战之一在于：与多数研究物种类似，新喀里多尼亚乌鸦会在多样的生境与行为情境中形成社会关联，而不同情境下的信号衰减特性存在差异。4. 本研究证实，经过妥善校准的近距离记录系统，可用于刻画自由活动动物在一系列具有生物学意义的距离范围内的社会关联。但与此同时，本研究也凸显出：针对具体研究开展定制化的系统校准需要投入大量工作，以充分考量野外部署过程中的生物学与技术层面的复杂性。尽管本研究仅针对单个案例展开，但本研究采用的多步校准流程的核心逻辑，可推广至诸多其他追踪系统与研究物种中。