GSA Connects 2021 in Portland, Oregon

Paper No. 8-14
Presentation Time: 11:35 AM


MORRISON, Shaunna1, HAZEN, Robert M.1, PRABHU, Anirudh2, WILLIAMS, Jason1, ELEISH, Ahmed3 and FOX, Peter3, (1)Earth and Planets Laboratory, Carnegie Institution for Science, 5251 Broad Branch Road NW, Washington, DC 20015, (2)Earth and Planets Laboratory, Carnegie Institution for Science, 5251 Broad Branch Road NW, Washington, DC 20015; Rensselaer Polytechnic Institute, 5 State St, Troy, NY 12180, (3)Rensselaer Polytechnic Institute, 5 State St, Troy, NY 12180

Within complex, evolving systems exists high-level multiple correlations across their various parameters and characteristics. Minerals and solid condensed phases are no exception to this complexity and, as a result, many trends related to geology, geochemistry, and/or biology may be obscured within the myriad mineralogic parameters and their relationships to one another and their environments. Therefore, we have the opportunity to explore these data with advanced, multidimensional techniques, such as mineral network analysis [1], to illuminate patterns related to geologic formation, geochemical processes, and biosignatures.

Recent years have seen a dramatic increase in the volume of mineralogical and geochemical data available for study. These large and expanding data resources have created an opportunity to characterize changes in near-surface mineralogy through deep time and to relate these findings to the geologic and biologic evolution of our planet over the past 4.5 billion years [2-5]. Using databases such as the RRUFF Project (, the IMA list of mineral species (, the Mineral Evolution Database (MED;, the Evolutionary System of Mineralogy Database (ESMD;, the Mineral Properties Database (, Mindat (, EarthChem (, and the Astromaterials Data System (, we explore the spatial and temporal distribution of minerals on Earth and planetary surfaces while considering the multidimensional relationships between composition, oxidation state, structural complexity, and paragenetic mode.

In this study, we employ mineral network analysis to explore this wealth of information and to identify and characterize trends in geochemistry, crystallography, paragenetic mode, age, frequency of occurrence, and much more related to the complex geologic and biologic evolution of mineralization on Earth.

[1] Morrison et al. (2017) Am Min, 102, 1588-1596

[2] Hazen et al. (2008) Am Min, 93, 1693-1720

[3] Liu et al. (2017) Nat Comm, 8:1950

[4] Morrison et al. (2020) Frontiers, 8, 208

[5] Hazen & Morrison (2020) Am Min, 105, 627-651