“Obliquity Feature Extraction for Fossil Data Analysis: The Stickleback Fish Case”
Authors: Rolf Ergon,Affiliation: University of South-Eastern Norway
Reference: 2026, Vol 47, No 1, pp. 1-8.
Keywords: adaptive peak tracking, feature extraction, fossil record, moving average smoothing, phenotypic evolution, power spectrum, stickleback fish
Abstract: A moving average smoothing method for extraction of cycles in time series data is described, with focus on obliquity cycles in fossil data. Since obliquity cycles affect sea temperature, they have left traces in oxygen isotope dO(t) values over time, as found in deep-sea drilling projects. Such values are commonly used as proxy for temperature, which is an important driver for evolutionary change. The proposed method is more generally intended for cases where the environmental driver of phenotypic evolution has been found 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 of extracting obliquity cycles information 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.
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BibTeX:
@article{MIC-2026-1-1,
title={{Obliquity Feature Extraction for Fossil Data Analysis: The Stickleback Fish Case}},
author={Ergon, Rolf},
journal={Modeling, Identification and Control},
volume={47},
number={1},
pages={1--8},
year={2026},
doi={10.4173/mic.2026.1.1},
publisher={Norwegian Society of Automatic Control}
};