Cazelles Bernard, Chavez Mario, Berteaux Dominique, Ménard Frédéric, Vik Jon Olav, Jenouvrier Stéphanie, Stenseth Nils C
Ecole Normale Supérieure, CNRS UMR 7625, Paris, France.
Oecologia. 2008 May;156(2):287-304. doi: 10.1007/s00442-008-0993-2.
Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The versatility and attractiveness of the wavelet approach lie in its decomposition properties, principally its time-scale localization. It is especially relevant to the analysis of non-stationary systems, i.e., systems with short-lived transient components, like those observed in ecological systems. Here, we review the basic properties of the wavelet approach for time-series analysis from an ecological perspective. Wavelet decomposition offers several advantages that are discussed in this paper and illustrated by appropriate synthetic and ecological examples. Wavelet analysis is notably free from the assumption of stationarity that makes most methods unsuitable for many ecological time series. Wavelet analysis also permits analysis of the relationships between two signals, and it is especially appropriate for following gradual change in forcing by exogenous variables.
小波分析是一种强大的工具，已在科学和工程领域广泛应用。小波方法的通用性和吸引力在于其分解特性，主要是其时间尺度定位。它特别适用于非平稳系统的分析，即具有短暂瞬态成分的系统，如在生态系统中观察到的那些系统。在这里，我们从生态学角度回顾小波方法用于时间序列分析的基本特性。小波分解具有本文所讨论的几个优点，并通过适当的综合和生态实例加以说明。值得注意的是，小波分析不受平稳性假设的限制，而平稳性假设使得大多数方法不适用于许多生态时间序列。小波分析还允许分析两个信号之间的关系，并且特别适合跟踪外生变量强迫的逐渐变化。
