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Developed after a meeting at the Santa Fe Institute on extinction modeling, this book comments critically on the various modeling approaches. In the last decade or so, scientists have started to examine a new approach to the patterns of evolution and extinction in the fossil record. This approach may be called "statistical paleontology," since it looks at large-scale patterns in the record and attempts to understand and model their average statistical features, rather than their detailed structure. Examples of the patterns these studies examine are the distribution of the sizes of mass extinction events over time, the distribution of species lifetimes, or the apparent increase in the number of species alive over the last half a billion years. In attempting to model these patterns, researchers have drawn on ideas not only from paleontology, but from evolutionary biology, ecology, physics, and applied mathematics, including fitness landscapes, competitive exclusion, interaction matrices, and self-organized criticality. A self-contained review of work in this field.
This book investigates the efficacy of statistical modeling in explaining large-scale patterns of evolution and extinction observed in the fossil record. The authors, M.E.J. Newman and R.G. Palmer, synthesize interdisciplinary research from the Santa Fe Institute to evaluate how mathematical frameworks can account for phenomena like mass extinction distributions and species longevity. By shifting the focus from individual fossil analysis to aggregate statistical features, the text provides a rigorous methodology for interpreting long-term biological trends.
What You Will Find
Experts recognize this work as a foundational synthesis for researchers bridging the gap between paleontology and applied mathematics. Readers frequently note the technical density of the prose, which assumes a strong background in quantitative analysis and evolutionary theory.
Page Count:
120
Publication Date:
2003-01-01
Publisher:
Oxford University Press
ISBN-10:
0195159454
ISBN-13:
9780195159455
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