Graham W. Lederer, Ph.D.
Graham Lederer is a Physical Scientist for the USGS Geology, Energy & Minerals (GEM) Science Center in Reston, VA.
In my role at the U.S. Geological Survey, I study the supply of materials important to society through materials flow analysis and mineral resource assessment. Materials flow analysis provides a quantitative framework for understanding how mineral resources are transformed into mineral commodities and enter industrial supply chains through processes like primary production, trade, manufacturing, end use, and recycling. Mineral resource assessment involves characterizing mineral deposits and integrating geological, geochemical, and geophysical datasets to better understand how and where minerals resources are concentrated in the Earth.
As a geologist, I am primarily interested in the physical and chemical evolution of the Earth’s crust. My research on ancient and modern orogens focuses on the many processes that create and modify continental crust including deformation, metamorphism, partial melting, and magmatism. Interpreting the spatial and temporal patterns of these petrogenetic processes requires a combination of field- and laboratory-based techniques including detailed structural mapping, microstructural analysis, trace element geochemistry, and accessory phase geochronology. To date, my projects have ranged from characterizing strain in the Grenville basement complex of the Virginia Blue Ridge, constraining the timescales of partial melting in the Himalayan mid-crust through U-Th-Pb dating of syn-tectonic leucogranites, evaluating rare earth phosphate mineralization mechanisms in Proterozoic gneisses of eastern California, and assessing the timing and tempo of large igneous provinces associated with catastrophic changes in Earth history.
Professional Experience
Physical Scientist, United States Geological Survey (2015-present)
Postdoctoral Associate, Massachusetts Institute of Technology (2014-2015)
Teaching Associate, University of California Santa Barbara (2014)
Geologist, United States Geological Survey (2011)
Education and Certifications
Ph.D. Geological Sciences, University of California Santa Barbara (2014) - Timescales of crustal anatexis: monazite petrochronology of Himalayan granites (Advisor: Dr. J. M. Cottle)
B.S. Geology and Environmental Science, College of William and Mary (2009) - Geology and structural history of the Blue Ridge basement complex, Albemarle County, Virginia (Advisor: Dr. C. M. Bail
Science and Products
Ultramafic lands: Sustainability Challenges and Resource Opportunities
Extracting data from maps: applying lessons learned from the AI for Critical Mineral Assessment Competition
21st Century Prospecting: AI-assisted Surveying of Critical Mineral Potential
MinFrame - Methodological infrastructure needed for resource assessment, modeling, and evaluation
Mineral Resource Assessment Training
Locations of mines and prospects in Amelia County, Virginia
Grade and tonnage data for tungsten vein and greisen deposits
Grade and tonnage data for disseminated flake graphite deposits
Training and validation data from the AI for Critical Mineral Assessment Competition
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and
Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California - Geodatabase
Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California - Simulation results
Annual review 2023: Critical minerals
Automated georeferencing and feature extraction of geologic maps and mineral sites
Applications of natural language processing to geoscience text data and prospectivity modelling
Rock-to-metal ratios of the rare earth elements
Rock-to-metal ratio: A foundational metric for understanding mine wastes
USGS 2020 critical minerals review
Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California
Grade and tonnage model for tungsten skarn deposits—2020 update
Evaluating the mineral commodity supply risk of the U.S. manufacturing sector
Meeting the mineral needs of the United States
Draft critical mineral list—Summary of methodology and background information—U.S. Geological Survey technical input document in response to Secretarial Order No. 3359
Beryllium—A critical mineral commodity—Resources, production, and supply chain
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
MapMark4 Shiny: A self-contained implementation of the MapMark4 R package
Science and Products
Ultramafic lands: Sustainability Challenges and Resource Opportunities
Extracting data from maps: applying lessons learned from the AI for Critical Mineral Assessment Competition
21st Century Prospecting: AI-assisted Surveying of Critical Mineral Potential
MinFrame - Methodological infrastructure needed for resource assessment, modeling, and evaluation
Mineral Resource Assessment Training
Locations of mines and prospects in Amelia County, Virginia
Grade and tonnage data for tungsten vein and greisen deposits
Grade and tonnage data for disseminated flake graphite deposits
Training and validation data from the AI for Critical Mineral Assessment Competition
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and
Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California - Geodatabase
Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California - Simulation results
Annual review 2023: Critical minerals
Automated georeferencing and feature extraction of geologic maps and mineral sites
Applications of natural language processing to geoscience text data and prospectivity modelling
Rock-to-metal ratios of the rare earth elements
Rock-to-metal ratio: A foundational metric for understanding mine wastes
USGS 2020 critical minerals review
Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California
Grade and tonnage model for tungsten skarn deposits—2020 update
Evaluating the mineral commodity supply risk of the U.S. manufacturing sector
Meeting the mineral needs of the United States
Draft critical mineral list—Summary of methodology and background information—U.S. Geological Survey technical input document in response to Secretarial Order No. 3359
Beryllium—A critical mineral commodity—Resources, production, and supply chain
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.