GSA Connects 2024 Meeting in Anaheim, California

Paper No. 46-7
Presentation Time: 8:00 AM-5:30 PM

HOW DOES EXPOSURE AGE INFLUENCE MICROFRACTURING RATES OF COMMON CRUSTAL ROCKS?


WEBB, Patrick, Geology, University of North Carolina at Charlotte, 12818 Darby Chase Dr, Charlotte, NC 28223, EPPES, Missy, Geography & Earth Sciences, UNC Charlotte, 9201 University City Blvd, Charlotte, NC 28223, RASMUSSEN, Monica, Department of Geography & Earth Sciences, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223 and DAHLQUIST, Maxwell, Department of Earth & Environmental Systems, Sewanee: The University of the South, Sewanee, TN 37383

Mechanical weathering (fracturing) plays a key role in bedrock geomorphology (e.g. Eppes and McFadden, 2008; Shobe et al., 2017), but the factors that drive and limit fracturing in the ‘Critical Zone’ remain poorly constrained. There have been recent observations that the rates of macro-fracturing in granitoid clasts from three sites in the Southern Sierra Nevada mountains, California decreases over geologic time. Additional rock property data from the same study suggest that internal feedbacks between microcracking (the propagation of cracks generally only visible with microscopy) and concomitant changes in rock stiffness set the pace for overall cracking rates. Here I hypothesize that the influence of mineralogy on microcracking has a direct relationship to these observations, and that granitoid clasts with progressively older exposure ages experience lower rates of microcracking. The influence of deteriorated and altered mineral grain boundaries and alteration products may contribute to microcrack propagation deceleration, as well as pecific mineral behavior such as biotite and quartz thermal expansion.

Traditional mineralogical and petrological observations made on thin sections from granitoid rocks with known exposure ages will provide qualitative analysis of rock properties. Newly refined methods utilizing UV epoxy-impregnated thin sections will provide data to quantify the orientation and density of microfractures. Processing fracture data through machine learning software will expedite and normalize observations across rocks. Fracture data paired observations will allow us to understand fracture relationships between different minerals and crack propagation. This data will then be compared to those derived from macrofracture observations in the same rocks (e.g. Rasmussen et al., 2024). Observations of the propagation of microcracks in modern and progressively older surfaces could offer a quantification of mechanical breakdown of clasts through time, a connection between microscale and macroscale mechanical weathering, and the direct effect of geologic time on rock mechanics in general.