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U.S. Geological Survey global seabed mineral resources

The U.S. Geological Survey (USGS) provides science and data on seabed mineral resources and ecosystems, as well as on the potential hazards associated with extraction. The Nation relies on minerals for infrastructure, technology, manufacturing, and energy production. Critical minerals are essential to the economic and national security of the United States and have a supply chain vulnerable to disruption. For decades, USGS scientific innovation has contributed to the delineation of seabed mineral resources, the mechanisms of seabed mineral formation, and the environmental impacts of resource extraction. Since 1962, the USGS has also led scientific inquiries into the potential for deep sea mining. By providing impartial science on seabed minerals and their environmental setting in the deep oceans, the USGS enables decision-makers to evaluate the best practices for mineral resource development.

Fact Sheet

Regional models for postfire debris-flow likelihood and rainfall thresholds across the western United States

The U.S. Geological Survey (USGS) uses an empirical model developed with logistic regression (the ‘M1’ model) to rapidly assess debris-flow likelihood and to identify quantitative rainfall thresholds for debris flows after wildfire in the western United States. The M1 model was calibrated to a debris-flow inventory from southern California (United States) and has been applied throughout the western United States. Limited spatial coverage in the calibration dataset has motivated evaluation of M1 model accuracy outside the calibration region (e.g., the Sierra Nevada or the eastern Cascade Range, United States). Previous test cases showed that M1 overpredicts debris-flow likelihood and underpredicts rainfall thresholds for some locations (e.g., Arizona, northern California, Colorado, New Mexico, United States). We sought to improve the regional applicability of a debris-flow likelihood model by expanding the debris-flow inventory used for calibration, testing multiple potential models and generating an updated model framework. The updated inventory includes 3788 observations from 67 burned areas paired with short duration rainfall ratios. The updated model framework consists of a modified model structure and sets of coefficients calibrated separately to the entire updated inventory and to subsets of the inventory that intersect three Environmental Protection Agency (EPA) Level 2 ecoregions (Mediterranean California, Upper Gila Mountains and Western Cordillera). Comparisons of predictions from the updated models with observed rainfall and debris-flow activity show that the updated models outperform the M1 model by ~15%–60% and improve the uniformity of predictive performance across the western United States. The updated models also reduce false positive rates relative to M1 and generate rainfall thresholds that are better aligned with relative differences in regional climatology and debris-flow activity.

Arizona, California, Colorado, Idaho, Montana, Nev

Final project peport for “Mapping riparian vegetation response to climate change on the San Carlos Apache Reservation and Upper Gila River watershed to inform restoration priorities: 1935 to present – Phase 2: Focus on tamarisk vegetation”

Riparian ecosystems play a critical role in supporting wildlife habitats, maintaining water quality, and sustaining ecological resilience in arid landscapes. In the Upper Gila River level-4 Hydrologic Unit Code (HUC-4; Identification Number – 1504) watershed of Arizona and New Mexico, and across areas of the San Carlos Apache Tribe of the San Carlos Apache Reservation (hereafter, Tribe/Tribal – entity; or Reservation - place), riparian ecosystems have been substantially altered by the widespread expansion of tamarisk ( Tamarix spp.), an invasive and non-native riparian species. Tamarisk has high water use and increased flammability, making it a growing concern as droughts intensify across the southwestern United States (U.S.). Recent research indicates that tamarisk is increasingly stressed under prolonged drought conditions, which can elevate wildfire risk and further degrade riparian habitat. In response, the U.S. Geological Survey (USGS) Western Geographic Science Center, in collaboration with the Tribe, developed remote sensing–based tools to map riparian vegetation composition and monitor vegetation condition over time. These tools enable accurate identification of tamarisk extent, detection of vegetation stress, and comparison with native species such as cottonwood and willow. This information directly supports restoration and management actions, including targeted tamarisk removal, protection of endangered species habitat, and prioritization of areas for native vegetation recovery. The tools also provide insight into how riparian vegetation responds to changing climate and hydrologic conditions, strengthening long-term planning for riparian forest management. Findings from this work demonstrate that riparian vegetation responses vary across river systems, indicating differences in plant composition and hydro-climatic conditions. Tamarisk on both the Gila and San Carlos Rivers generally exhibit greater declines in greenness in response to higher temperature as well as lower precipitation and river flow, while cottonwood ( Populus fremontii ) and willow (Salix spp.) are particularly sensitive to changes in discharge along the San Carlos River and respond more directly to both high and low flows, with more moderate responses to precipitation and temperature. By providing actionable, science-based information, this research supports climate adaptation planning, wildfire risk reduction, and improved riparian ecosystem health, with benefits that extend beyond the Reservation to regional water and wildlife conservation efforts.

Arizona, New Mexico

Niobium-rich minerals from the Sheep Creek carbonatite-related deposits, Montana, USA

The Sheep Creek area in southwest Montana contains a number of small, tabular, carbonatite-related deposits that are rich in Nb- and REE-minerals. Two of the “vein-dikes” were mined at a small scale for Nb in the late 1950s. The most abundant Nb-bearing minerals are columbite-(Fe), nioboaeschynite-(Ce), baotite, and two varieties of Ti-Nb-Fe-oxide. An early oxide with Ti/Nb (atomic) near unity later broke down to a mixture of columbite + TiO2 with distinctly lower Nb content. Zircon intergrown with the Nb-REE minerals was dated by U-Pb methods to 116±2 Ma. This age is in agreement with previous dating (Th-Pb on monazite, Re-Os on molybdenite), and indicates that the Sheep Creek deposits are early Cretaceous in age.

Montana

Permafrost thaw controls iron flux from wetlands and sulfide-bearing rocks to Arctic rivers and streams

Recent warming has caused widespread iron mobilization into Arctic waterbodies that degrades ecosystems and threatens natural resources. Yet, understanding where and when iron flux occurs remains limited. Here, we investigate iron loading across regional to local scales in Arctic Alaska using climate, water chemistry, and borehole data together with mapped geology and permafrost presence. We show that both anoxic microbial iron reduction and acid rock drainage from iron-sulfide oxidation mobilize iron. Iron influx is strongly associated with lowland wetlands, sulfide-rich upland bedrock, and near-surface permafrost. Acid rock drainage chemistry correlates very strongly with the depth of seasonal thaw above permafrost from the previous year, indicating a one-year lag. These findings clarify the spatial and temporal dynamics of Arctic river rusting, provide a mechanistic understanding of the phenomenon, and may allow anticipation of its occurrence and assessment of its implications for aquatic ecosystem health and subsistence resources under ongoing climate change.

Alaska

The Europa Imaging System (EIS) investigation

The Europa Imaging System (EIS) consists of a Narrow-Angle Camera (NAC) and a Wide-Angle Camera (WAC) that are designed to work together to address high-priority science objectives regarding Europa’s geology, composition, and the nature of its ice shell. EIS accommodates variable geometry and illumination during rapid, low-altitude flybys with both framing and pushbroom imaging capability using rapid-readout, 8-megapixel (4k × 2k) detectors. Color observations are acquired using pushbroom imaging with up to six broadband filters. The data processing units (DPUs) perform digital time delay integration (TDI) to enhance signal-to-noise ratios and use readout strategies to measure and correct spacecraft jitter. The NAC has a 2.3° × 1.2° field of view (FOV) with a 10-μrad instantaneous FOV (IFOV), thus achieving 0.5-m pixel scale over a swath that is 2 km wide and several km long from a range of 50 km. The NAC is mounted on a 2-axis gimbal, ±30° cross- and along-track, that enables independent targeting and near-global (≥90%) mapping of Europa at ≤100-m pixel scale (to date, only ∼15% of Europa has been imaged at ≤900 m/pixel), as well as stereo imaging from as close as 50-km altitude to generate digital terrain models (DTMs) with ≤4-m ground sample distance (GSD) and ≤0.5-m vertical precision. The NAC will also perform observations at long range to search for potential erupting plumes, achieving 10-km pixel scale at a distance of one million kilometers. The WAC has a 48° × 24° FOV with a 218-μrad IFOV, achieving 11-m pixel scale at the center of a 44-km-wide swath from a range of 50 km, and generating DTMs with 32-m GSD and ≤4-m vertical precision. The WAC is designed to acquire three-line pushbroom stereo and color swaths along flyby ground-tracks.

Space Science Reviews

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters

Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland

Mineral-rich hardgrounds, such as ferromanganese (FeMn) crusts and phosphorites, occur on seamounts and continental margins, gaining attention for their resource potential due to their enrichment in valuable metals in some regions. This study focuses on the Southern California Borderland (SCB), an area characterized by uneven and heterogeneous topography featuring FeMn crusts, phosphorites, basalt, and sedimentary rocks that occur at varying depths and are exposed to a range of oxygen concentrations. Due to its heterogeneity, this region serves as an optimal setting for investigating the relationship between mineral-rich hardgrounds and benthic fauna. This study characterizes the density, diversity, and community composition of macrofauna (>300 μm) on hardgrounds as a function of substrate type and environment (depth and oxygen ranges). Rocks and their macrofauna were sampled quantitatively using remotely operated vehicles (ROVs) during expeditions in 2020 and 2021 at depths above, within, and below the oxygen minimum zone (OMZ). A total of 3,555 macrofauna individuals were counted and 416 different morphospecies (excluding encrusting bryozoans and hydrozoans) were identified from 82 rocks at depths between 231 and 2,688 m. Average density for SCB macrofauna was 11.08 ± 0.87 ind. 200 cm −2 and mean Shannon-Wiener diversity per rock (H′ [loge] ) was 2.22 ± 0.07. A relationship was found between substrate type and macrofaunal communities. Phosphorite rocks had the highest H′ of the four substrates compared on a per-rock basis. However, when samples were pooled by substrate, FeMn crusts had the highest H′ and rarefaction diversity. Of all the environmental variables examined, water depth explained the largest variance in macrofaunal community composition. Macrofaunal density and diversity values were similar at sites within and outside the OMZ. This study is the first to analyze the macrofaunal communities of mineral-rich hardgrounds in the SCB, which support deep-ocean biodiversity by acting as specialized substrates for macrofaunal communities. Understanding the intricate relationships between macrofaunal assemblages and mineral-rich substrates may inform effects from environmental disruptions associated with deep-seabed mining or climate change. The findings contribute baseline information useful for effective conservation and management of the SCB and will support scientists in monitoring changes in these communities due to environmental disturbance or human impact in the future.

California

Groundwater dominates snowmelt runoff and controls streamflow efficiency in the western United States

Climate change in seasonally snow-covered mountain catchments is reducing water supply and decreasing streamflow predictability. Here, we use tritium age dating to show that contrary to the common assumption that snowmelt quickly contributes to runoff, streamflow during snowmelt in western US catchments is dominated by older groundwater. The average age of streamwater during snowmelt runoff (5.7 ± 4.3 years) was intermediate to the average age of groundwater (10.4 ± 4.5 years) and recent precipitation, indicating that 58% (±34%) of snowmelt runoff was derived from groundwater. Water ages, streamflow, and groundwater storage were mediated by bedrock geology: low-permeability hard rock/shale catchments exhibited younger ages, less storage, and more efficient streamflow generation than high-permeability sandstone/clastic catchments. Our results demonstrate that snowmelt runoff is the result of multiple prior years of climate mediated by groundwater storage. Including these interactions will be crucial for predicting water resources as climate and landscape changes accelerate.

western united States

Regional variations in sea ice and primary productivity in the Bering Sea during Marine Isotope Stage 11

Marine Isotope Stage (MIS) 11 (424-374 ka) has long been an analog for Holocene climate, because it is the most recent interglacial period with similar orbital conditions. However, there is significant global and regional variability in the climate response to MIS 11 warmth. Here, we review sediment core records from across the Bering Sea to investigate changes in paleoceanographic conditions during Marine Isotope Stages 12-10. Sea ice was present over much of the Bering Sea during MIS 11, but today, none of the sites investigated are ever ice-covered. This suggests that sea ice regimes in the Bering Sea during MIS 11 were different to those of the Holocene. There are also regional differences in the response of sea ice to MIS 11 warming. At the Umnak Plateau, Southeastern Bering Sea, sea ice concentrations decline during deglaciation, but they remain high at the slope sites until Peak MIS 11. Sea ice re-advances over the Umnak Plateau during peak interglacial warmth, at the same time that it declines over the slope sites. Late MIS 11 is characterized by high concentrations of seasonal sea ice at the Umnak Plateau, whilst sea ice at the slope sites fluctuates between consolidated and unconsolidated ice cover. This east-west dichotomy may be explained by changes in the behavior of the Aleutian Low. Productivity increases dramatically during deglaciation due to increased upwelling and sea level rise bringing fresh nutrients into the oceans. This is characterized by increased diatom productivity, increased terrestrial carbon deposition, and laminations at all sites.

Alaska

Monitoring changes in Landsat thermal features in urban and non-urban interfaces from 1986 to 2023 in two international urban centers: Implications for climate and global issues

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies.

Remote Sensing

Cancer risk and estimated lithium exposure in drinking groundwater in the US

Importance Lithium is a naturally occurring element in drinking water and is commonly used as a mood-stabilizing medication. Although clinical studies have reported associations between receiving lithium treatment and reduced cancer risk among patients with bipolar disorder, to our knowledge, the association between environmental lithium exposure and cancer risk has never been studied in the general population. Objectives To evaluate the association between exposure to lithium in drinking groundwater and cancer risk in the general population. Design, Setting, and Participants This cohort study included participants with electronic health record and residential address information but without cancer history at baseline from the All of Us Research Program between May 31, 2017, and June 30, 2022. Participants were followed up until February 15, 2023. Statistical analysis was performed from September 2023 through October 2024. Exposure Lithium concentration in groundwater, based on kriging interpolation of publicly available US Geological Survey data on lithium concentration for 4700 wells across the contiguous US between May 12, 1999, and November 6, 2018. Main Outcome and Measures The main outcome was cancer diagnosis or condition, obtained from electronic health records. Stratified Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% CIs for risk of cancer overall and individual cancer types for increasing quintiles of the estimated lithium exposure in drinking groundwater, adjusting for socioeconomic, behavioral, and neighborhood-level variables. The analysis was further conducted in the western and eastern halves of the US and restricted to long-term residents living at their current address for at least 3 years. Results A total of 252 178 participants were included (median age, 52 years [IQR, 36-64 years]; 60.1% female). The median follow-up time was 3.6 years (IQR, 3.0-4.3 years), and 7573 incident cancer cases were identified. Higher estimated lithium exposure was consistently associated with reduced cancer risk. Compared with the first (lowest) quintile of lithium exposure, the HR for all cancers was 0.49 (95% CI, 0.31-0.78) for the fourth quintile and 0.29 (95% CI, 0.15-0.55) for the fifth quintile. These associations were found for all cancer types investigated in both females and males, among long-term residents, and in both western and eastern states. For example, for the fifth vs first quintile of lithium exposure for all cancers, the HR was 0.17 (95% CI, 0.07-0.42) in females and 0.13 (95% CI, 0.04-0.38) in males; for long-term residents, the HR was 0.32 (95% CI, 0.15-0.66) in females and 0.24 (95% CI, 0.11-0.52) in males; and the HR was 0.01 (95% CI, 0.00-0.09) in western states and 0.34 (95% CI, 0.21-0.57) in eastern states. Conclusions and Relevance In this cohort study of 252 178 participants, estimated lithium exposure in drinking groundwater was associated with reduced cancer risk. Given the sparse evidence and unknown mechanisms of this association, follow-up investigation is warranted.

contiguous United States

USGS Geochron Database

Introduction Geochronology helps us understand Earth’s history by determining when important events, like volcanic eruptions, the rise of mountains, the formation of mineral resources, and changes in the landscape, happened. Geochronological data directly support geologic mapping and can inform decisions about geologic hazard mitigation, natural resource management, and infrastructure resilience. The U.S. Geological Survey (USGS) Geochron database provides access to more than 300,000 published, publicly available age measurements from more than 40,000 geological samples. This database is the result of a collaborative effort with State geological surveys and geoscientists from across the globe. The USGS Geochron database is the most comprehensive collection of geochronological data available for the United States. Users can view data through an interactive map explorer, download datasets, and integrate data into geospatial software or other analysis tools.

Fact Sheet

Comparing subduction ground-motion models to observations for Cascadia

We evaluate Cascadia subduction ground-motion models (GMMs), considered for the 2023 US National Seismic Hazard Model (NSHM) update, by comparing observations to model predictions. The observations comprise regional recordings from intraslab earthquakes, including contributions from 2021 and 2022 events in southern Cascadia and global records from interface earthquakes. Since the 2018 NSHM update, new GMMs for Cascadia have been published by the Next Generation Attenuation (NGA)-Subduction Project that require independent evaluation. In the regional intraslab comparisons, we highlight a characteristic frequency dependence for Cascadia data, with short periods having lower ground motions and longer periods being comparable to other subduction zones. We evaluate differences in northern and southern Cascadia and find that the NGA-Subduction GMMs developed using southern Cascadia data perform better in this region than the model that did not consider these data. We compare ground-motion variability in Cascadia with the NGA-Subduction model predictions and find differences at short periods ( T = 0.1 s) due to the use of global versus regional data in the development of these models. Moreover, the within-event component of aleatory variability from the GMMs overpredicts the standard deviation of Cascadia recordings at very short periods ( T < 0.05 s). Using global interface earthquakes as a proxy to evaluate the Cascadia GMMs, we find long-period overprediction from a simulation-based GMM and some of the empirical GMMs. When comparing recent observations, we find a similar misfit to GMMs and the 2010 and 2022 Ferndale earthquakes. Finally, we observe different basin amplification factors arising in different subsets of the data, which indicate that differences in basin factors between empirical GMMs could arise from the data selection choices by the developers. As part of evaluating the regional basin terms, we apply basin amplification factors from the magnitude 9 Cascadia earthquake simulations to the empirical GMMs for interface earthquakes. The comparisons presented in this study indicate that the NGA-Subduction GMMs for Cascadia perform well relative to observations and older subduction GMMs.

British Columbia, California, Oregon, Washington

Completion summary for monitor wells NRF-17 and NRF-18 at the Naval Reactors Facility, Idaho National Laboratory, Idaho

The U.S. Geological Survey (USGS)—in cooperation with the U.S. Department of Energy (DOE) for the Naval Reactors Laboratory Field Office that supports operations for the Naval Reactors Facility (NRF) located at the Idaho National Laboratory (INL)—drilled and constructed well NRF-17 (formerly borehole USGS 151) and well NRF-18 (formerly borehole USGS 152) for stratigraphic framework analyses and water-quality monitoring at the Idaho National Laboratory (INL) near the NRF, in southeastern Idaho. Borehole USGS 151 was continuously cored from about 48 to 1,070 feet (ft) below land surface (BLS); rotary drilled from approximately 1,070 to 1,720 ft BLS; and re-drilled to complete construction as a monitor well NRF-17, completed to 461 ft BLS. Borehole USGS 152 was continuously cored from approximately 19 to 1,259 ft BLS; rotary drilled from approximately 1,259 to 1,630 ft BLS; and re-drilled to complete construction as a monitor well NRF-18, completed to 450 ft BLS. Geophysical data were examined with photographed core material to record lithologic descriptions and to suggest zones where groundwater flow was anticipated. Basalt flows varied from highly fractured to dense, with high-to-low vesiculation. Well NRF-17 generally was constructed in mostly dense basalt (greater than 75 percent), and well NRF-18 was constructed in primarily fractured and (or) vesicular basalt. In well NRF-17, the well capacity is directly affected by the limited amount of fractured basalt, which serves as the primary pathway for groundwater. This effect was observed during the pumping test conducted after the well's final construction. Single-well aquifer tests were done at wells NRF-17 and NRF-18 to provide estimates of transmissivity and hydraulic conductivity after final well construction and initial well development. Estimated values of transmissivity and hydraulic conductivity for well NRF-17 were 8.81 feet squared per day (ft 2 /d) and 1.04×10 -2 feet per day (ft/d), respectively. Estimated values of transmissivity and hydraulic conductivity for well NRF-18 were 4.77×10 3 ft 2 /d and 5.61 ft/d, respectively. The NRF-17 pump test resulted in 19.41 ft of measured drawdown at a sustained average pumping rate of 3.3 gallons per minute (gal/min). The NRF-18 pump test resulted in 0.55 ft of measured drawdown at a sustained average pumping rate of 31.0 gal/min. Water-quality samples collected from the two wells were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples for select inorganic constituents showed concentrations consistent with signatures from tributary valley groundwater with influences from ephemeral surface-water recharge from the Big Lost River. Water-quality samples analyzed for stable isotopes of oxygen and hydrogen are consistent with signatures from tributary valley groundwater and surface-water recharge inputs to the aquifer. No measured water-quality results were greater than their respective maximum contaminant levels for public drinking-water supplies. Inorganic and nutrient water-quality results for well NRF-17 and well NRF-18 suggest the groundwater in this area is potentially affected by industrial wastewater disposal.

Idaho

Analyzing multi-year nitrate concentration evolution in Alabama aquatic systems using a machine learning model

Rising nitrate contamination in water systems poses significant risks to public health and ecosystem stability, necessitating advanced modeling to understand nitrate dynamics more accurately. This study applies the long short-term memory (LSTM) modeling to investigate the hydrologic and environmental factors influencing nitrate concentration dynamics in rivers and aquifers across the state of Alabama in the southeast of the United States. By integrating dynamic data such as streamflow and groundwater levels with static catchment attributes, the machine learning model identifies primary drivers of nitrate fluctuations, offering detailed insights into the complex interactions affecting multi-year nitrate concentrations in natural aquatic systems. In addition, a novel LSTM-based approach utilizes synthetic surface water nitrate data to predict groundwater nitrate levels, helping to address monitoring gaps in aquifers connected to these rivers. This method reveals potential correlations between surface water and groundwater nitrate dynamics, which is particularly meaningful given the lack of water quality observations in many aquifers. Field applications further show that, while the LSTM model effectively captures seasonal trends, limitations in representing extreme nitrate events suggest areas for further refinement. These findings contribute to data-driven water quality management, enhancing understanding of nitrate behavior in interconnected water systems.

Alabama

Paleoproterozoic vein graphite mineralization caused by decarbonation in the Ruby Range, Montana, USA

Hydrothermal graphite veins are a possible source for modern battery materials and require better understanding of their carbon source(s) and absolute timing to develop mapable criteria for exploration models. We present new observations of graphite vein and alteration paragenesis and U-Pb LA-ICP-MS titanite age data from the Ruby prospect, Montana, USA, that constrain mineralization timing and source. The graphite veins cut high-temperature metamorphic rocks of the lower Christensen Range suite and are associated with intense diopside (Di0.69Hd0.27Jo0.04) alteration of marble. The oldest titanite ages in fresh marble and partially altered calc-silicate gneiss are ca. 2,500 – 2,450 Ma, show elevated REE values, and Eu/Eu* <1.5, consistent with growth during early regional metamorphism. Titanite in diopside-graphite alteration, interpreted as part of the hydrothermal vein-forming episode, cluster around 1,750 Ma, are characterized by lower REE values, and show Eu/Eu* >2; suggesting a low fO 2 fluid generated from metamorphism during the Big Sky orogeny. Our paragenetic observations and titanite ages indicate graphite vein formation via skarnoid decarbonation reactions in marble late in regional orogenesis. Granulite-facies, carbonate-bearing, supracrustal rock terranes are thus favorable for hydrothermal graphite vein deposits.

Montana