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特征的关注度日益提升，这推动了自动化追踪技术的研发进程，此类技术可稳定记录自由活动个体的社交互动事件。其中颇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，收集空间关联的发生频次、持续时长与空间距离相关数据。尽管近距离记录的原理十分直观——即传播中的无线电波会随距离增加而衰减，但针对野外部署场景的系统校准仍颇具挑战，这是因为多数研究物种的活动范围覆盖复杂且异质化的生境。
2. 本研究针对新近研发的数字近距离记录系统（Encounternet）开展校准工作，以期将其部署于野生新喀鸦（Corvus moneduloides）种群中。本研究的核心目标是构建定量模型，可通过记录器采集的信号强度值，实现记录器间（进而对应乌鸦间）距离的可靠事后估算。为精准刻画乌鸦搭载的记录器之间的无线电通信过程，我们整合了理论分析、野外实验、统计建模、行为观测与计算机模拟等手段开展校准工作。
3. 研究结果表明，仅依靠信号强度信息，即可将乌鸦的互动事件可靠归类至预设的距离区间中，从而为社交动态分析提供有力支撑。例如，可在分析阶段对野外部署记录器获取的原始数据集进行筛选，优先保留乌鸦间距仅数米的互动事件——此类场景下，乌鸦可通过直接观察实现社会行为的学习。进一步优化数据分类所面临的核心挑战之一在于：与多数研究物种一样，新喀鸦会在多样的生境与行为情境中发生社交互动，而不同情境下的信号衰减特性存在差异。
4. 本研究证实，经过良好校准的近距离记录系统，可用于绘制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交关联图谱。但与此同时，本研究也凸显出：针对特定研究开展系统校准需投入大量工作，这类校准需充分兼顾野外部署场景中的生物学与技术层面的复杂性。尽管本研究仅针对单一案例展开，但我们所采用的多步校准逻辑，可推广至诸多其他追踪系统与研究物种中。