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Activity Number: 362 - SPEED: Food, Environment, Biomedical Imaging and Physical System Visualization/Learning, Part 2
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 11:35 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #307786
Title: A Bayesian Approach for Estimating Earth’s "missing" Minerals
Author(s): Grethe Hystad* and Ahmed Eleish and Robert Downs and Shaunna Morrison and Robert Hazen
Companies: Purdue University Northwest and Rensselaer Polytechnic Institute and University of Arizona and Geophysical Laboratory, Carnegie Institution for Science and Geophysical Laboratory, Carnegie Institution for Science
Keywords: Bayesian statistics; Statistical mineral ecology; Species estimation
Abstract:

What is our place in the cosmos? Are we and Earth unique, and does life exist elsewhere? Is the distribution of mineral species in Earth’s near-surface environment a consequence of both deterministic factors (occurring on any Earth-like planet) and chance events (frozen accidents)? Extensive and growing data resources on mineral species and their localities are employed to identify and parameterize frequency distributions of Earth’s mineral kingdom. A Bayesian approach is introduced to estimate the total number of mineral species in Earth’s crust. Markov chain Monte Carlo simulations are used to generate samples of the model parameters such that estimates and inference are directly obtained. What constitutes an Earth-like planet and it’s requisite life-generating processes is a pervasive theme in planetary sciences. Quantitative criteria for characterizing Earth-like planets are suggested by using the mineral frequency distribution of Earth’s crust as a mineralogy-based statistical measure. In spite of deterministic chemical and biological factors that control most of our planet’s mineral diversity, Earth is mineralogically unique in its distribution of rare species.


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