GSA Annual Meeting in Denver, Colorado, USA - 2016

Paper No. 191-12
Presentation Time: 11:15 AM

PREDICTION OF EARTH'S MISSING MINERALS AND THE RELATIVE ABUNDANCES FOR THE MINERAL SPECIES ON EARTH; A STATISTICAL MEASURE TO CHARACTERIZE EARTH-LIKE PLANETS


HYSTAD, Grethe1, HAZEN, Robert M.2, DOWNS, Robert T.3 and GOLDEN, Joshua J.3, (1)Department of Mathematics, Computer Science, and Statistics, Purdue University Northwest, Hammond, IN 46323, (2)Geophysical Laboratory, Carnegie Institution of Washington, 5251 Broad Branch Road, NW, Washington, DC 20015, (3)Department of Geosciences, University of Arizona, Tucson, AZ 85721, Grethe.Hystad@purduecal.edu

Some of the great questions posed by mankind over the centuries are related to our place in the cosmos. Are we and Earth unique, and does life exist elsewhere? A population model for the mineral species frequency distribution is introduced. The mineral species coupled with their localities is a Large Num­ber of Rare Events (LNRE) distribution since most of Earth’s mineral species are rare, known from only a few localities. LNRE models formulated in terms of a type distribution allow the estimation of Earth’s undiscovered, mineralogical diversity and the prediction of the percentage of observed mineral species that would differ if Earth’s history were replayed. We will demonstrate that, in spite of deterministic physical, chemical, and biological factors that control most of our planet’s mineral diversity, Earth’s mineralogy is unique in the cosmos. The characteristic of an “Earth-like” planet is a pervasive theme in planetary science and astrobiology. However, a compelling definition of “Earth-like” planets remains elusive. The mineral frequency distribution of Earth’s crust can provide a mineralogy based statistical measure for characterizing an ideal Earth-like planet.

Recently, we calculated the relative abundances numerically for all the mineral species in Earth’s crust, including the undiscovered ones. These population probabilities provide an estimate of the occurrence probabilities of species in a random sample and can be used to characterize Earth in terms of it’s mineralogy.