“Examples of Adaptive Peak Tracking as Found in the Fossil Record, Including Obliquity Cycles Tracking”
Authors: Rolf Ergon,Affiliation: University of South-Eastern Norway
Reference: 2025, Vol 46, No 4, pp. 147-162.
Keywords: adaptive landscape, adaptive peak tracking, AIC, fitness landscape, fossil record, moving average smoothing, obliquity cycles, WMSE
Abstract: Species that have persisted over millions of years have done so because they have been able to track peaks in an adaptive landscape well enough to survive and reproduce. Such optima are defined by the mean phenotypic values that maximize mean fitness, and they are predominantly functions of the environment, for example the sea temperature. The mean phenotypic values over time will thus predominantly be determined by the environment over time, and the trait history may be found in the fossil record. Here I use fossil data from four cases found in the literature, and show that adaptive peak tracking models give better results than alternative weighted least squares and directional random walk models. The model performances are compared by use of weighted mean squared errors and Akaike information criterion results.
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BibTeX:
@article{MIC-2025-4-2,
title={{Examples of Adaptive Peak Tracking as Found in the Fossil Record, Including Obliquity Cycles Tracking}},
author={Ergon, Rolf},
journal={Modeling, Identification and Control},
volume={46},
number={4},
pages={147--162},
year={2025},
doi={10.4173/mic.2025.4.2},
publisher={Norwegian Society of Automatic Control}
};