Astrobiology routinely confronts questions of planetary environment and the ‘habitability’ of a planet—guiding exoplanet astronomical sensing and data interpretation as we look for life elsewhere. But terrestrial-like planet climate states are complex and require increasingly sophisticated computer modeling to understand and to predict.
From studying the Earth, we also know that life itself has played a key role in determining climate and habitability for most of the past 4 billion years—creating a chicken-and-egg problem for understanding exoplanets. However, existing attempts to incorporate ecosystem behavior into climate models are rudimentary—typically deploying highly parameterized and simplified models of biochemical feedback. For example: modeling basic photosynthetic production or simple chemotrophic processes (organisms making their own food by oxidizing inorganic compounds).
This may be inadequate for accurately evaluating either the long-term state of planetary environments or for assessing a biosphere’s response to perturbations (e.g. asteroid impacts, orbital change). Critically, what no existing models explicitly incorporate is the property of awareness-based decision-making by organism populations on global scales. Examples could extend from microbial life to multicellular organisms, including: quorum sensing in bacterial populations, chemical signaling and response in plants, nesting and migratory behavior in insects and animals, and resource hunting in animals (including humans).
This project’s initial goals are to develop a theoretical framework, and to construct a number of computational test cases—making use of existing physical climate models for the Earth.
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