论文标题
使用功率谱分析对动物运动数据中异常扩散的分类
Classification of anomalous diffusion in animal movement data using power spectral analysis
论文作者
论文摘要
近年来，运动生态学领域的高分辨率数据迅速增加，导致发展了许多统计和数值方法来分析迁移轨迹。数据通常是在个人的水平和长期内收集的，可能包括一系列行为。在这里，我们使用功率谱密度（PSD）来表征黑翅风筝（Elanus caeruleus）和白色鹳（Ciconia ciconia）的随机运动模式。首先将轨道分割并聚集在不同的行为（运动模式）中，对于每种模式，我们测量了过程的PSD和衰老属性。对于觅食风筝，我们发现$ 1/f $噪声，以前在生态系统中报告的主要是在人群动态的背景下，但不是针对运动数据。我们进一步提出了每种行为模式的合理模型，通过比较所测量的PSD指数和单个标记PSD的分布与已知的理论结果和模拟。
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.
