Generalized Stoichiometry and Biogeochemistry for Astrobiological Applications

Christopher P. Kempes, Michael J. Follows, Hillary Smith, Heather Graham, Christopher H. House, Simon A. Levin

Research output: Contribution to journalArticlepeer-review

Abstract

A central need in the field of astrobiology is generalized perspectives on life that make it possible to differentiate abiotic and biotic chemical systems McKay (2008). A key component of many past and future astrobiological measurements is the elemental ratio of various samples. Classic work on Earth's oceans has shown that life displays a striking regularity in the ratio of elements as originally characterized by Redfield (Redfield 1958; Geider and La Roche 2002; Eighty years of Redfield 2014). The body of work since the original observations has connected this ratio with basic ecological dynamics and cell physiology, while also documenting the range of elemental ratios found in a variety of environments. Several key questions remain in considering how to best apply this knowledge to astrobiological contexts: How can the observed variation of the elemental ratios be more formally systematized using basic biological physiology and ecological or environmental dynamics? How can these elemental ratios be generalized beyond the life that we have observed on our own planet? Here, we expand recently developed generalized physiological models (Kempes et al. 2012, 2016, 2017, 2019) to create a simple framework for predicting the variation of elemental ratios found in various environments. We then discuss further generalizing the physiology for astrobiological applications. Much of our theoretical treatment is designed for in situ measurements applicable to future planetary missions. We imagine scenarios where three measurements can be made-particle/cell sizes, particle/cell stoichiometry, and fluid or environmental stoichiometry-and develop our theory in connection with these often deployed measurements.

Original languageEnglish (US)
Pages (from-to)73
Number of pages1
JournalBulletin of Mathematical Biology
Volume83
Issue number7
DOIs
StatePublished - May 18 2021

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Immunology
  • Mathematics(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Pharmacology
  • Agricultural and Biological Sciences(all)
  • Computational Theory and Mathematics

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