Geological Society of America

35 D14. Mineralogy/Crystallography (Posters)

Sunday, 4 November 2018
9:00 AM - 5:30 PM
Halls J-K

ESTIMATING EARTH’S UNDISCOVERED, MINERALOGICAL DIVERSITY USING A BAYESIAN APPROACH

Paper number: 35-2
Program: Technical Sessions
Time: 9:00 AM – 5:30 PM

Authors

Grethe Hystad Presenting Author
Purdue University Northwest, Hammond, IN
Ahmed Eleish
Rensselaer Polytechnic Institute, Troy, NY
Robert Hazen
Carnegie Institution for Science, Washington, DC
Shaunna Morrison
Carnegie Institution for Science, Washington, DC
Robert T. Downs
University of Arizona, Tucson, AZ

Abstract

A Bayesian approach is introduced to estimate the total number of mineral species in Earth’s crust. In Bayesian statistics, the parameters are not considered fixed as they are in classical statistics but assumed to have their own probability distribution such that prior information about the parameters can be built into the model. Samples of the model parameters are generated by Markov chain Monte Carlo (MCMC) simulations and used for estimates and inference. Species accumulation curves are constructed and employed to estimate the population size as a function of sampling size. The Poisson lognormal distribution is found to provide the best fit to the mineral species frequency spectrum among the distributions tested. Finally, the population size estimates obtained by Bayesian methods are compared to the empirical Bayes estimates.

Geological Society of America Abstracts with Programs. Vol. 50, No. 6

doi: 10.1130/abs/2018AM-324286

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