Obliquity Feature Extraction for Fossil Data Analysis: The Stickleback Fish Case

Abstract

A moving average smoothing method for extraction of cycles in time series data is described, with focus on obliquity cycles and fossil data. The proposed method is intended for cases where the environmental driver of phenotypic evolution can be shown to include obliquity cycles, either by power spectrum analysis or simply by inspection of raw or smoothed time series. The method gives improved mean trait predictions and better understanding when applied on stickleback fish fossil data from around 10 million years ago. The possibility to extract obliquity cycles will depend on the dynamics of the time series, and the method is thus not universally applicable. It may, however, be possible to adapt the size of the moving window to problems under study, or possibly to obtain improved predictions by inclusion of a sinusoidal component in the mean trait prediction modeling.