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Knowledge gaps and missing links in understanding mass extinctions: Can mathematical modeling help?

Ivan Sudakow1, Corinne Myers2, Sergei Petrovskii3

  • 1Department of Physics, University of Dayton, OH, USA; School of Mathematics and Statistics, The Open University, Milton Keynes, UK.

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Mass extinctions (MEs) are dramatic increases in extinction rates. Mathematical models can bridge gaps in the fossil record, improving our understanding of extinction causes and mechanisms.

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Area of Science:

  • Paleobiology
  • Macroevolution
  • Geochemistry

Background:

  • Species and clade extinctions are normal macroevolutionary processes.
  • Mass extinctions (MEs) represent dramatic, global increases in extinction rates linked to environmental change, particularly in the carbon cycle.
  • Current understanding of ME triggers and periodicities is limited by the incomplete and low-resolution fossil record.

Purpose of the Study:

  • To propose integrating mathematical models into mass extinction research.
  • To shift focus from ME triggers to organismal kill mechanisms.
  • To enhance understanding of how biological and paleobiological sciences can inform each other.

Main Methods:

  • Review of existing research on mass extinctions.
  • Conceptual framework for integrating mathematical modeling with geological, geochemical, and ecological methods.
  • Focus on organismal kill mechanisms as a unifying approach.

Main Results:

  • Mathematical models can compensate for data gaps and resolution issues in the fossil record.
  • Models can connect ecosystem-level processes to global-scale extinction events.
  • A shift in focus to kill mechanisms offers a more standardized approach across scales.

Conclusions:

  • Integrating mathematical models with traditional methods offers significant advantages for ME research.
  • Further utilization of mathematical modeling is recommended for a comprehensive understanding of mass extinctions.
  • This approach can improve insights into ME precipitation and interdisciplinary scientific collaboration.