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

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journal contribution
posted on 2022-06-30, 15:09 authored by Ivan Sudakow, Corinne Myers, Sergei Petrovskii, Colin D Sumrall, James Witts
Extinction of species, and even clades, is a normal part of the macroevolutionary process. However, several times in Earth history the rate of species and clade extinctions increased dramatically compared to the observed “background” extinction rate. Such episodes are global, short-lived, and associated with substantial environmental changes, especially to the carbon cycle. Consequently, these events are dubbed “mass extinctions” (MEs). Investigations surrounding the circumstances causing and/or contributing to mass extinctions are on-going, but consensus has not yet been reached, particularly as to common ME triggers or periodicities. In part this reflects the incomplete nature of the fossil and geologic record, which – although providing significant information about the taxa and paleoenvironmental context of MEs – is spatiotemporally discontinuous and preserved at relatively low resolution. Mathematical models provide an important opportunity to potentially compensate for missing linkages in data availability and resolution. Mathematical models may provide a means to connect ecosystem scale processes (i.e., the extinction of individual organisms) to global scale processes (i.e., extinction of whole species and clades). Such a view would substantially improve our understanding not only of how MEs precipitate, but also how biological and paleobiological sciences may inform each other. Here we provide suggestions for how to integrate mathematical models into ME research, starting with a change of focus from ME triggers to organismal kill mechanisms since these are much more standard across time and spatial scales. We conclude that the advantage of integrating mathematical models with standard geological, geochemical, and ecological methods is great and researchers should work towards better utilization of these methods in ME investigations.

History

Citation

Physics of Life Reviews Volume 41, July 2022, Pages 22-57

Author affiliation

School of Computing and Mathematical Sciences, University of Leicester

Version

  • AM (Accepted Manuscript)

Published in

Physics of Life Reviews

Volume

41

Pagination

22 - 57

Publisher

Elsevier

issn

1571-0645

eissn

1873-1457

Acceptance date

2022-04-11

Copyright date

2022

Available date

2024-04-15

Spatial coverage

Netherlands

Language

English