利用功率谱分析对动物运动数据中的异常扩散进行分类
Classification of anomalous diffusion in animal movement data using power spectral analysis
摘要：
近年来，迁移生态学领域的高分辨率数据迅速增加，导致开发了许多统计和数值方法来分析迁移轨迹。数据往往是在个人一级收集的，而且是长期收集的，可能涵盖一系列行为。在这里，我们使用功率谱密度（PSD）来描述一个黑翅风筝（Elanus caeruleus）和一个白鹳（Ciconia ciconia）的随机运动模式。首先将轨迹分段并聚类为不同的行为（运动模式），对于每种模式，我们测量PSD和过程的老化特性。对于觅食的风筝，我们发现$1/f$噪音，以前报道的生态系统中主要是在人口动态的背景下，但不是运动数据。我们进一步建议合理的模型，通过比较测量的PSD指数和分布的单轨迹PSD已知的理论结果和模拟的行为模式。
英文摘要：
The field of movement ecology has seen a rapid increase in high-resolution data in recent years, leading to the development of numerous statistical and numerical methods to analyse relocation trajectories. Data are often collected at the level of the individual and for long periods that may encompass a range of behaviours. Here, we use the power spectral density (PSD) to characterise the random movement patterns of a black-winged kite (Elanus caeruleus) and a white stork (Ciconia ciconia). The tracks are first segmented and clustered into different behaviours (movement modes), and for each mode we measure the PSD and the ageing properties of the process. For the foraging kite we find $1/f$ noise, previously reported in ecological systems mainly in the context of population dynamics, but not for movement data. We further suggest plausible models for each of the behavioural modes by comparing both the measured PSD exponents and the distribution of the single-trajectory PSD to known theoretical results and simulations.
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