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Catastrophe risk can accelerate unlikely evolutionary transitions.
Snyder-Beattie, Andrew E; Bonsall, Michael B.
  • Snyder-Beattie AE; Mathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford OX1 3PS, UK.
  • Bonsall MB; Mathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford OX1 3PS, UK.
Proc Biol Sci ; 289(1971): 20212711, 2022 03 30.
Article en En | MEDLINE | ID: mdl-35350860
Intelligent life has emerged late in Earth's habitable lifetime, and required a preceding series of key evolutionary transitions. A simple model (the Carter model) explains the late arrival of intelligent life by positing these evolutionary transitions were exceptionally unlikely 'critical steps'. An alternative model (the neocatastrophism hypothesis) proposes that intelligent life was delayed by frequent catastrophes that served to set back evolutionary innovation. Here, we generalize the Carter model and explore this hypothesis by including catastrophes that can 'undo' an evolutionary transition. Introducing catastrophes or evolutionary dead ends can create situations in which critical steps occur rapidly or in clusters, suggesting that past estimates of the number of critical steps could be underestimated. If catastrophes affect complex life more than simple life, the critical steps will also exhibit a pattern of acceleration towards the present, suggesting that the increase in biological complexity over the past 500 Myr could reflect previously overlooked evolutionary transitions. Furthermore, our results have implications for understanding the different explanations (critical steps versus neo-catastrophes) for the evolution of intelligent life and the so-called Fermi paradox-the observation that intelligent life appears rare in the observable Universe.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Evolución Biológica / Inteligencia Tipo de estudio: Etiology_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Evolución Biológica / Inteligencia Tipo de estudio: Etiology_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article