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On the use of models in understanding the rise of complex life
Author(s) -
Timothy M. Lenton
Publication year - 2020
Publication title -
interface focus
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 49
eISSN - 2042-8901
pISSN - 2042-8898
DOI - 10.1098/rsfs.2020.0018
Subject(s) - computer science , data science
Recently, several seemingly irreconcilably different models have been proposed for relationships between Earth system processes and the rise of complex life. These models provide very different scenarios of Proterozoic atmospheric oxygen and ocean nutrient levels, whether they constrained complex life, and of how the rise of complex life affected biogeochemical conditions. For non-modellers, it can be hard to evaluate which—if any—of the models and their results have more credence—hence this article. I briefly review relevant hypotheses, how models are being used to incarnate and sometimes test those hypotheses, and key principles of biogeochemical cycling models should embody. Then I critically review the use of biogeochemical models in: inferring key variables from proxies; reconstructing ancient biogeochemical cycling; and examining how complex life affected biogeochemical cycling. Problems are found in published model results purporting to demonstrate long-term stable states of very low Proterozoic atmosphericp O2 and ocean P levels. I explain what they stem from and highlight key empirical uncertainties that need to be resolved. Then I suggest how models and data can be better combined to advance our scientific understanding of the relationship between Earth system processes and the rise of complex life.

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