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Joshua Mark Rosera

Publications and source records attributed to Joshua Mark Rosera.

16 recordsLinked to original sources
USGS2026

Global pegmatite-hosted lithium, cesium, and rubidium resources: A dataset for grade and tonnage modeling

Quantitative mineral resource assessments of potential undiscovered deposits can inform future mineral supply scenarios, but their accuracy is conditional on building robust grade and tonnage models of known deposits. This study presents an up-to-date global compilation and analysis of recently discovered and original, in-situ pegmatite-hosted Li, Cs, and Rb resources prior to historic production. Our analysis yields a median tonnage of 21.2 million tons (Mt) and grade of 1.12% Li 2 O, respectively, for global Li pegmatite deposits ( n = 73). The grades and tonnages of Li pegmatite resources vary depending on the age of the bedrock host domain, pegmatite crystallization age, and primary ore mineralogy. Lithium pegmatite resources hosted in Archean to transitional Archean-Paleoproterozoic domains have the largest median tonnage (29.8 Mt; n = 38), and those hosted in Paleoproterozoic to Mesoproterozoic domains have smaller median tonnages (6.5 Mt; n = 16). Cesium deposits where pollucite is the primary ore mineral have a bimodal grade distribution, with modes of 2.40 and 0.035 wt% Cs 2 O for high- and low-grade deposits, respectively, while Rb deposits are more unimodal with a median grade of 0.247 wt% Rb 2 O. Pegmatite-hosted Cs and Rb resources have median tonnages of 7.6 and 6.3 Mt, respectively. Covariation between ore mineralogy and the degree of crustal enrichment in pegmatite-hosted deposits is diagnostic of petrogenetic differences, including melt source characteristics, magma evolution, or variable degrees of volatile solubility. The Li pegmatite compilation is suitable for fitting robust numerical models to support quantitative assessments. More well-defined Rb and Cs pegmatite resources are required for quantitative assessments, but these data provide useful information about original in-place resources for framing supply discussions.

Ore Geology Reviews↗
USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the southern Appalachian orogen

The first quantitative mineral resource assessment for undiscovered lithium pegmatite deposits in the southern Appalachian region of the United States was conducted. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical and mineral occurrence data. Lithium pegmatite prospectivity of the tracts was ranked with simplified mappable criteria, including proximity to Paleozoic felsic intrusions and major lithotectonic structures, stream sediment geochemical anomalies, and pegmatite occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. These estimates were integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was applied to convert the probabilistic estimates of contained lithium into recoverable material. The identified lithium pegmatite resources for the Carolina Lithium and Kings Mountain deposits, North Carolina, contain 1589 thousand tons (kt) of Li 2 O. The median contained undiscovered resource for the southern Appalachian orogen was estimated to be 2240 kt Li 2 O. At 90% confidence, the region contains at least 130 kt Li 2 O, and 10,700 kt at 10% confidence. After applying economic filters, the median recoverable contained resource was 1430 kt Li 2 O, corresponding to approximately 201 years of current lithium imports for consumption in the United States. North and South Carolina are likely to contain most of these resources. Coarse data resolution and intra-state variations in the geological data contribute to uncertainty of undiscovered lithium pegmatite resources. Continued efforts to harmonize disparate geospatial datasets with updated or new information can improve the accuracy and precision of estimated undiscovered lithium pegmatite resources in the study area and at broader scales.

Alabama, Georgia, Maryland, North Carolina, South ↗
USGS2026

Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database

The global demand for critical mineral commodities is rapidly increasing, making domestic production an important factor in supporting the economy and national security. Large scale, publicly available geochemical databases allow for the application of data informatics methods to interrogate critical mineral commodities data for correlations in deposit formation and distribution, particularly for identifying enrichment of multiple critical mineral commodities at the same deposit. In this study, we applied network analysis to the Critical Minerals Mapping Initiative (CMMI) ore geochemistry (Critical Minerals in Ores, CMiO) database to identify the high concentration (defined as 10× bulk crustal abundance) co-occurrence of different critical mineral commodities across a mineral system hierarchy from deposit environments to individual deposits. Identifying patterns or unique outliers in enrichment in network communities will allow for the location of secondary critical mineral commodity resources from under-utilized deposits. We find trends in the enrichment of critical mineral commodities in network-communities between the elements praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) across multiple CMiO database deposit environments and groups down to specific deposit types and sites. A separate trend in network community deposition is observed as well between iridium (Ir) and platinum (Pt) in deposit environments, groups, types, and sites. Network analysis focused on critical minerals in magmatic-hydrothermal deposits identified multiple deposit sites from different deposit types within the CMiO database with concentrations of Dy, Nd, Tb, Pr, Ir, and Pt that are at least ten times greater than the crustal average. This approach can be applied to any target element(s) or deposit(s) of interest, allowing broad investigation of co-enriched critical mineral commodities.

Journal of Geochemical Exploration↗
USGS2025

Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments

Correlations between grade and tonnage exist in mineral resource data compiled from published reports, but they are not always addressed during quantitative assessment of undiscovered mineral resources. Failure to account for correlated grade and tonnage distributions can result in geologically unrealistic assessment results. Current software tools simulate univariate ore tonnage and multivariate resource grades of undiscovered deposits independently. As a result, analysts are forced to rely on ad-hoc solutions to minimize the correlation issues by: 1) creating subsets of data with restricted criteria; 2) truncating grade and tonnage distributions; and 3) testing model robustness using exploratory data analysis. While these methods represent pragmatic solutions, the statistical solutions presented here provide additional options to address real correlations in grade and tonnage data used for mineral resource assessments. We present a modified version of the MapMark4 package in R that introduces two alternatives for modeling grade and tonnage distributions, consisting of a multivariate solution that accounts for correlations between ore tonnage and metal grades and an empirical solution that utilizes simple random sampling with replacement to reproduce coupled grades and tonnages from the input data. We present simulations for contained ore and metal for three case studies representing tungsten skarn, komatiite-hosted nickel, and sediment-hosted carbonate amagmatic zinc-lead (Mississippi Valley-type) deposits. Employing the methods presented here yields quantitative mineral resource assessment results that more closely reflect the empirical distributions of grades and tonnages observed in nature and expands the applicability of these tools for ongoing critical mineral resource assessments.

Applied Computing and Geosciences↗
USGS2025

Extracting data from maps: Lessons learned from the artificial intelligence for critical mineral assessment competition

The U.S. Geological Survey (USGS), Defense Advanced Projects Research Agency (DARPA), NASA Jet Propulsion Laboratory (JPL), and MITRE ran a 12-week machine learning competition aimed at accelerating development of AI tools for critical mineral assessments. The Artificial Intelligence for Critical Mineral Assessment Competition solicited innovative solutions for two challenges: 1) automated georeferencing of historical maps, and 2) automated feature extraction from historical maps. Competitors used a new dataset of historical map images to train, validate, and evaluate their models. Automated georeferencing pipelines attained a median root-mean square error of 1.1 km. Prompt-based extraction (i.e., with user input) of polygons, polylines, and points from geologic maps yielded median F1-scores of 0.77, 0.56, 0.35, respectively. Geologic maps pose numerous challenges for AI workflows because they vary significantly. However, despite its short duration, the competition yielded promising results that have since spurred further innovation in this area and led to the development of new AI tools to semi-automate key, time-consuming parts of the assessment workflow.

Applied Computing and Geosciences↗
USGS2025

Quantitative mineral resource assessment of lithium pegmatite deposits in the Appalachian Orogen, USA

Lithium is classified as a U.S. critical mineral commodity, and its demand is projected to drastically increase through 2040, driven by electric vehicle production and energy storage applications (IEA 2021).Most global lithium production is not in the United States increasing vulnerability to a supply disruption. The U.S. Geological Survey is actively assessing domestic lithium deposits including lithium-bearing pegmatites in the Appalachian orogen. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical, and mineral occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. Estimates were then integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was used to estimate the amount of potentially recoverable undiscovered resources. Preliminary computations for the northern Appalachians, including application of the economic filter to the median recoverable contained resource, yields 900,000 metric tons of Li 2 O that correspond to enough Li 2 O to replace 127 years of import reliance at the current rate (7,100 t Li 2 O/yr; USGS, 2025). For the southern Appalachians, preliminary computations yielded 1,430,000 metric tons of Li 2 O, which corresponds to 201 years of import reliance.

Alabama, Connecticut, Delaware, Georgia, Maine, Ma↗
USGS2025

Tertiary metallogeny of the Rocky Mountains Province, USA

Tertiary ore deposits in the Rocky Mountains physiographic province primarily formed through magmatic-hydrothermal processes associated with shifting tectonics and lithospheric conditions. Important deposit types in the province are calc-alkaline and Climaxtype porphyry; high-, medium-, and low-sulfidation epithermal; alkalic magmatic; carbonate replacement; tungsten skarn and vein; and sandstone uranium. Province wide, there is diachroneity from north to south among both ore-forming and magmatic events.

Rocky Mountains Province↗
USGS2025

Mappable criteria for Li-mineralized pegmatites in the Appalachian orogen (utilizing the mineral systems approach)

Li-mineralized pegmatites are found throughout the Appalachian orogenic belt. Available evidence layers (e.g. tectonic setting, structures, geochemistry, geochronology) are used to develop mappable criteria for mineral resource assessments of Li-mineralized pegmatites in the northern and southern U.S. Appalachians. These evidence layers are placed into a mineral systems anatomy and classification of tectonic settings approach. We find that triggers of Li-mineralized pegmatite petrogenesis are closely associated with terrane accretion, continental collision, and orogenic collapse, spanning the Acadian to Alleghanian orogenies. These include overthickened crust in the northern Appalachians (Acadian altiplano) and terrane accretion in the southern Appalachians. The energy drivers of the system are anatexis broadly plutonism and/or deformation-related melting processes. Metal sources are associated with magmatic fluids of highly differentiated granitoids (e.g. peraluminous, S-type) and Silurian- Devonian sedimentary rocks. In many instances permeability and pathways of these systems are structurally controlled along major fault systems and within highly deformed metasedimentary rocks in the north. Notably, there are Li-mineralized pegmatite gaps along the Appalachian orogen that include: 1) regions of exposure of unfavorable metamorphic grade rocks, 2) favorable areas deeply buried by sedimentary rocks, and 3) gaps of unknown causes. Exhumation and preservation of midcrustal rocks are favourable as hosts to lithiummineralized pegmatites.

southern Appalachian mineral resourse assessment a↗
USGS2024

Using stochastic point pattern analysis to track regional orientations of magmatism during the transition to cenozoic extension and Rio Grande rifting, Southern Rocky Mountains

The southern Rocky Mountains in Colorado and northern New Mexico hosted intracontinental magmatism that developed during a tectonic transition from shortening (Laramide orogeny, ca. 75 to 40 Ma) through extension and rifting. We present a novel approach that uses stochastic weighted bootstrap simulations of a large set of new and historical geochronology data to better understand how regional anisotropies responsible for focusing magma emplacement evolved through time. This technique can detect subtle trends in directional distributions, including multi-modal orientations, and can be filtered from regional to local scales. Our results indicate that magmatism followed first the northeast trend of the Colorado mineral belt between 75 and 40 Ma and deviated afterward. These deviations vary depending on the scale of the analysis. At the smallest scale we evaluated (<75 km), the orientation of magmatism from 45 to 30 Ma rotated counter-clockwise before aligning with the north-south trend of the modern Rio Grande rift. Larger, regional-scale analyses indicate magma centers between 40 to 35 Ma and 25 to 20 Ma were dominantly oriented southwest-northeast, whereas magmatism between 35 and 25 Ma had north-south orientation. The large areal footprint of magmatism and shifting regional patterns suggest that ancient zones of weakness in the North American lithosphere accommodated magma flow at different moments in time, rather than controlled by a retreating interface of the Farallon and North American plates.

Tectonics↗
USGS2023

Fluorine-rich mafic lower crust in the southern Rocky Mountains: The role of pre-enrichment in generating fluorine-rich silicic magmas and porphyry Mo deposits

Fluorine-rich granites and rhyolites occur throughout the southern Rocky Mountains, but the origin of F-enrichment has remained unclear. We test if F-enrichment could be inherited from ancient mafic lower crust by: (1) measuring amphibole compositions, including F and Cl contents, of lower crustal mafic granulite xenoliths from northern Colorado to determine if they are unusually enriched in halogens; (2) analyzing whole-rock elemental and Sr, Nd, and Pb isotopic compositions for upper crustal Cretaceous to Oligocene igneous rocks in Colorado to evaluate their sources; and (3) comparing batch melting models of mafic lower crustal source rocks to melt F and Cl abundances derived from biotite data from the F-rich silicic Never Summer batholith. This approach allows us to better determine if the mafic lower crust was pre-enriched in F, if it is concentrated enough to generate F-rich anatectic melts, and if geochemical data support an ancient lower crustal origin for the F-rich rocks in the southern Rocky Mountains. Electron microprobe analyses of amphibole in lower crustal mafic granulite xenoliths show they contain 0.56–1.38 wt% F and 0.45–0.73 wt% Cl. Titanium in calcium amphibole thermometry indicates that the amphiboles equilibrated at high to ultrahigh temperature conditions (805 to 940 °C), and semiquantitative amphibole thermobarometry indicates the amphiboles equilibrated at 0.5 to 1.0 GPa prior to entrainment in magmas during the Devonian. Mass balance calculations, based on these new measurements, indicate parts of the mafic lower crust in Colorado are at least 3.5 times more enriched in F than average mafic lower crust. Intrusions coeval with the Laramide Orogeny (75 to 38 Ma) pre-date F-rich magmatism in Colorado and have Sr and Nd isotopic compositions consistent with mafic lower crust ± mantle sources, but many of these intrusions contain elevated Sr/Y ratios (>40) that suggest amphibole was a stable phase during magma generation. The F-rich igneous rocks from the Never Summer igneous complex and Colorado Mineral Belt also have Sr and Nd isotopic compositions that overlap with the lower crustal mafic granulite xenoliths, but they have lower Sr/Y, higher Nb and Y abundances, and distinctly less radiogenic 206 Pb/ 204 Pb i compositions than preceding Laramide magmatism. Batch melt modeling indicates low-degree partial melts derived from rocks similar to the mafic lower crustal xenoliths we analyzed can yield silicic melts with >2000 ppm F, similar to estimated F melt concentrations for silicic melts that are interpreted to be parental to evolved leucogranites. We suggest that F-rich silicic melts in the southern Rocky Mountains were sourced from garnet-free mafic lower crust, and that fluid-absent breakdown of amphibole in ultrahigh temperature metamorphic rocks was a key process in their generation. Based on the composition of high-F amphibole measured from lower crustal xenoliths, the temperature of amphibole breakdown and melt generation for these F-enriched source rocks is likely >100 °C higher than similar lower crust with low or average F abundances. As such, these source rocks only melted during periods of unusually high heat flow into the lower crust, such as during an influx of mantle-derived magmas related to rifting or the post-Laramide ignimbrite flare-up in the region. These data have direct implications for the genesis of porphyry Mo mineralization, because they indicate that pre-enrichment of F in the deep crust could be a necessary condition for later anatexis and generation of F-rich magmas.

Colorado, New Mexico↗
USGS2023

Genesis of the Questa Mo porphyry deposit and nearby polymetallic mineralization, New Mexico, USA

The Oligocene Latir magmatic center in northern New Mexico is an exceptionally well-exposed volcanoplutonic complex that hosts a variety of magmatic-hydrothermal deposits, ranging from relatively deep, F-rich porphyry Mo mineralization to shallower epithermal deposits. We present new whole-rock chemical and isotopic data for plutonic rocks from the Latir magmatic center, including extensive sampling of drill core samples of intrusive rocks from the Questa porphyry Mo deposit. These data document temporal chemical trends of porphyry-related mineralization that occurred after caldera-forming magmatism and during postcaldera batholith assembly. Silicic magmas were generated multiple times throughout the history of the Latir magmatic center, but few are associated with the formation of a mineral deposit. Whole-rock trace element ratios and Sr, Nd, and Pb isotope compositions vary throughout the protracted history of silicic magmatism. The caldera-forming ignimbrite and early phase of postcaldera intrusions are unmineralized, more enriched in high field strength elements, and generally contain less radiogenic Sr and Pb and more radiogenic Nd than later intrusions. The Questa porphyry Mo deposit formed immediately after the most isotopically primitive phase of the batholith was assembled, ruling out simple reworking of juvenile mantle-derived crust as the source for mineralizing magmas. Rhyolite dikes associated with polymetallic sulfide deposits intruded ~800 k.y. after Mo mineralization, and Nd isotope data indicate that these dikes are associated with different batches of magma and are unrelated to the Mo-mineralizing intrusions at the Questa mine. Together, these data indicate that the source of magmas changed significantly throughout the 10-m.y. history of the magmatic center. We assess multiple genetic models for porphyry-related magmatism against this data set, favoring models with discrete periods of magma genesis from a deep hybridized zone in the lower crust giving rise to the punctuated periods of mineralization. These observations suggest that the formation of mineral deposits within a central magmatic locus is likely the result of the piecemeal assembly of individual hydrothermal-magmatic systems, and that distal and younger polymetallic mineralization commonly observed near known porphyry deposits represents decoupled processes.

New Mexico↗
USGS2023

Automated georeferencing and feature extraction of geologic maps and mineral sites

The predictive power of mineral prospectivity analysis depends on high quality, spatially accurate, analysis-ready datasets. Of paramount importance are geologic maps and mineral site data, but the state of readiness for utilizing these datasets remains sub-optimal for advanced computational techniques. As the U.S. Geological Survey (USGS) fulfils its mission to map the distribution of critical mineral commodities, non-georeferenced maps held within historical collections represent rich sources of input data. Through a series of machine learning challenges organized by the Defense Advanced Research Projects Agency (DARPA) in collaboration with the USGS, significant progress has been made in accelerating data ingestion, processing, and preparation tasks that enable mineral prospectivity mapping and mineral resource assessment workflows. Specifically, two tasks that previously required time-intensive human effort, 1) georeferencing map images, and 2) legend-based feature extraction from map images, are discussed.

Conference Paper↗
USGS2023

Critical minerals in Climax-type magmatic-hydrothermal systems

Today’s global economy is challenged to meet the growing demand for commodities used in existing and emerging advanced technologies. Critical minerals are commodities found in a wide variety of ore deposits that are vital to the economic or national security of individual nations that are vulnerable to supply disruption. The U.S. Geological Survey is striving to advance understanding of critical mineral resources by employing a Mineral Systems approach. Climax-type systems are one of 17 mineral systems currently under investigation. The aim of this work is to inventory and assess knowledge gaps on the abundance of 50 critical minerals in Climax-type systems. Here we synthesize geochemical data from ore concentrates, ore, waste, and minerals together with information on production from, and resources in, ore deposits. The goal of this work is to estimate the amount of critical minerals present in processed mine waste and unmined resources, discuss those that could potentially be recovered in the future, and identify important future areas of research.

Conference Paper↗
USGS2021

Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States

Historical mine and mineral deposit datasets are routinely used to inform quantitative mineral assessment models, but they also can contain a wealth of supplementary qualitative information that is generally underutilized. We present a workflow that uses correspondence analysis, an exploratory tool commonly applied to multivariate abundance data, to better utilize qualitative data in these historical datasets. The workflow involves extraction of qualitative information on ore mineralogy from a mineral deposit database, attaches those data to a target geological feature, and analyzes the underlying data structure with correspondence analysis and hierarchical clustering. The output of correspondence analysis is inversely weighted to the relative frequency of ore minerals, and therefore rare mineral species (i.e., those with unusually low frequencies) can disproportionately contribute to the total variance of the dataset. We present a novel technique for aggregating frequencies of rare mineral species that minimizes this effect. We apply this workflow to evaluate how ore mineral assemblages in former and active mines vary in spatial relation to silicic calderas in the southwestern United States. The most common ore mineral associations observed spatially and genetically associated to calderas include those related to polymetallic, base metal-rich systems and epithermal Au–Ag systems. Three other groups of mineralized calderas were identified, including: (1) Hg–Sb mineralized calderas in the northern Great Basin and western Nevada volcanic field; (2) calderas associated with elevated abundances of Mn oxides/hydroxides, fluorite, and Be-minerals, mostly in eastern Utah and New Mexico; and (3) calderas with numerous U ± F deposits, which are located in central Colorado, the eastern Great Basin and in northern Nevada. The latter three groups are associated with economically significant critical mineral resources, including the Li resources of the McDermitt complex and Be associated with the Spor Mountain on the margin of the Thomas caldera complex. We conclude that correspondence analysis is a promising technique that can enhance data exploration of the qualitative information held within mineral deposit datasets. Consequently, it could have numerous applications for mineral potential mapping, resource assessment projects, and characterization of mineral systems.

Natural Resources Research↗
USGS2021

Mapping multivariate ore occurrence data with correspondence analysis

Correspondence analysis is a multivariate method that can be applied to mineral abundance data. Ore mineral assemblages from broadly underutilized prospect and occurrence data can be treated as geochemical anomalies, projected to low-dimensional space, and returned into map view. This approach could have applications for mineral prospectivity mapping and delineation of permissive areas during mineral assessments.

Conference Paper↗