USGS Science⌕ Search

SEARCH · USGS Science

Results for “Resources Policy”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

505 records · Page 23Linked to original sources
USGS2025

A probabilistic assessment methodology for the evaluation of geologic energy storage capacity—Natural gas storage in depleted hydrocarbon reservoirs

The need for energy storage, particularly underground, where capacity and duration may far exceed battery storage technologies, is especially relevant given the increasing demands for reliable power alongside the development of intermittent renewable electricity sources. Geologic energy storage facilities already exist, and expanded use would enable storing gases such as methane and hydrogen. In 2018, a National Academies of Sciences, Engineering, and Medicine report, “Future Directions for the U.S. Geological Survey's Energy Resources Program,” recommended that the U.S. Geological Survey (USGS) prioritize assessing underground energy storage in geologic formations in the United States. The U.S. Geological Survey has since developed a methodology for assessing natural gas storage capacities in depleted hydrocarbon reservoirs on a national scale. The methodology introduced in this report prescribes three approaches for calculating gas storage capacity. This methodology relies on the availability of input data, including cumulative hydrocarbon production records, reservoir petrophysical properties, and reservoir pressure data. Assessment inputs can be obtained from public, State-level databases and propriety national-scale databases, although the use of analogs could be warranted for estimating input parameters. Probabilistic assessment results are aggregated to play, petroleum province, regional, and national scales. The steps defined in this report are demonstrated on the Michigan Basin Province, which includes the Mississippian Sandstone Gas Play and the Clinton Structural Play. This methodology could be used to systematically and consistently assess hydrocarbon plays and provinces for natural gas storage capacity across the United States.

Michigan↗
USGS2024

Improving crop-specific groundwater use estimation in the Mississippi Alluvial Plain: Implications for integrated remote sensing and machine learning approaches in data-scarce regions

Study region The Mississippi Alluvial Plain (MAP) in the United States (US). Study focus Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km 3 /year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately. New hydrological insights for the region We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R 2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.

Journal of Hydrology Regional Studies↗
USGS2025

Light absorbing particles deposited to snow cover across the Upper Colorado River Basin, Colorado Rocky Mountains, 2013-16: Interannual variations from multiple natural and anthropogenic sources

Atmospheric particulate matter (PM) as light-absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013–2016) from the mountainous Upper Colorado River basin by comparing among laboratory-measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35–2.50 μm, varied by a factor of 1.9 (range, 0.2300–0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6–22.5 wt. %) including inferred black carbon, natural organic matter, and carbon-based synthetic, black road-tire-wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11–0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source-area contributions implying strong interannual changes in regional source behavior, dust-storm frequency, and (or) transport tracks. Observations of dust-storm activity in the western U.S. and particle-size averages for all samples (median, 25 μm) indicated that regional dust from deserts dominated mineral-dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

Colorado↗
USGS2025

Applying U-Th disequilbrium for dating siliceous sinters

Continental hydrothermal systems are critical avenues for the crustal transport of heat and mass captured for geothermal energy and mineral exploration. Thus, understanding their temporal evolution and longevity is important for resource characterization. Deposits of microlaminated siliceous sinter, common surface expressions of high temperature reservoirs (> 170 °C), have the potential to trace hydrothermal histories. Geothermal reservoirs are often located within uranium-bearing silicic volcanic rock where subsurface fluid-rock interactions extract U into hydrothermal fluids. U incorporated in the surface sinter deposit has the potential to provide a U— Th disequilibrium dating option. We focus on samples from El Tatio geyser field in the Altiplano of northern Chile, the largest geothermal system in the Andes. Our resulting 230 Th/U ages, along with the water and deposit elemental compositions, suggest concentrations of U and Th vary predictably along the sinter apron. While distal facies containing the highest U concentrations (> 50 μg/g) are least affected by detrital Th corrections, they can display suspected open-system behavior. In contrast, more medial facies, where bacterial mats and other porous textures are co mmonly concentrated, have only trace amounts of U (< 0.1 μg/g), which leads to unreliable or geologically improbable dates. Proximal facies tend to date most consistently. By comparing existing 14 C ages with 230 Th/U results, 230 Th/U ages tend to be younger than the 14 C ages, supporting the presence of a 14 C-dead carbon influence. New data confirm that the onset of geothermal activity at El Tatio goes back to the late Pleistocene.

Altiplano, El Tatio geyser field↗
USGS2025

Lessons in business recovery following the 2023 Kahramanmaraş earthquake sequence, Türkiye informed by women entrepreneurs

On 6 February 2023, Southern Türkiye was hit by devastating earthquakes, directly affecting over 14 million people in 11 cities, causing more than 50,000 deaths and the destruction of more than 800,000 buildings. This article goes beyond the physical damage imposed by the catastrophe to discuss the effects of the earthquakes on the operations of women-owned businesses. The mixed-method study with entrepreneurs belonging to a women’s business association operating in a moderately disrupted part of the region explores their struggles and recovery expectations. Thirty-five questionnaires were analyzed to identify the reasons for business closure, challenges, and needs faced in the post-disaster period and their recovery strategies. In addition, 23 entrepreneurs participated in roundtable discussions to provide a broader context to their responses to survey topics as well as lessons learned. Across both the survey and roundtables, while many respondents reported minor physical damage to their building, they also experienced financial and personal challenges from disruption to equipment, infrastructure, services, supply chains, institutional decisions, employee well-being, and customer base. Many used their business resources and personal savings to assist employees and others in the community. The women entrepreneurs often felt their recovery needs were ignored by government and private relief organizations and encountered barriers to receiving assistance from public and private institutions. Organizing together as women in business, even informally, provided mutual support during the crisis and recovery periods and catalyzed their role in support of their communities. The results illuminate functional community recovery as a balance of recovery of built infrastructure functionality and recovery of the broader social and economic fabric of the community.

southern Turkey↗
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

Hydraulic conductivity and transmissivity estimates from slug tests in wells within the Mississippi Alluvial Plain, Arkansas and Mississippi, 2020

During the spring and summer of 2020, the U.S. Geological Survey conducted single-well slug tests on selected observation wells within the Mississippi Alluvial Plain in Arkansas and Mississippi to estimate hydraulic conductivity and transmissivity values for the Mississippi River Valley alluvial and middle Claiborne aquifers. Well and aquifer data were collected from field measurements, well-construction reports, and published aquifer-thickness information. A total of 324 slug-in and slug-out tests were conducted on 48 wells by using mechanical slugs to displace the water column and submersible pressure transducers to record changes in water levels in the wells. Hydraulic conductivity of the aquifers in which the wells are screened was estimated by curve fitting the water-level-change data using aquifer test analysis software. Estimates of aquifer transmissivity were made by multiplying the estimated hydraulic conductivity value by the aquifer thickness at well locations. Mean hydraulic conductivity estimates for 44 observation wells screened in the Mississippi River Valley alluvial aquifer range from 3 to 401 feet per day, and mean transmissivity estimates range from 285 to 80,559 feet squared per day. Mean hydraulic conductivity estimates for four observation wells screened in units of the middle Claiborne aquifer range from 0.14 to 183 feet per day, and mean transmissivity estimates range from 55 to 67,913 feet squared per day. The results from these tests can be used to improve the understanding of water availability and groundwater migration, to refine groundwater models, and to ultimately provide stakeholders and decisionmakers better information for management of the groundwater resources within the Mississippi Alluvial Plain.

Arkansas, Mississippi↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2025

Relations of groundwater quality to long-term surface disposal of produced water near the Midway-Sunset and Buena Vista Oil Fields, California, USA

Contamination of groundwater by oil-field fluids in proximity to oil and gas development has been an issue of concern to water users and regulators given long histories of development and legacy disposal practices. A robust set of geochemical tracers including petroleum hydrocarbon compounds, thermogenic gases, inorganic ion concentrations, stable isotopes, radioactive isotopes, and noble gases were used to assess if oil-field fluids mixed with groundwater near the Midway-Sunset and Buena Vista Oil Fields in California, USA. Results show evidence of mixing of oil-field fluids with groundwater within the study area from either anthropogenic or natural processes. Produced water plumes associated with modern surface disposal facilities, used since the late 1950s, extend up to 1.5 km and currently remain within the boundaries of the oil fields. Plumes associated with earlier routing of produced water down natural drainages and in large retention structures (Midway Basin and Sunset Basin) near the Buena Vista Lake Bed are present in groundwater east of the oil fields. Based on geochemical tracer evidence, aerial imagery, and aerial electromagnetic surveys, these legacy plumes reach the western portion of the Central Valley aquifer system, an important groundwater resource for agricultural and domestic supply. The legacy plume associated with Sunset Basin may further be detected downgradient in deeper groundwater beneath the southern extent of the Buena Vista Lake Bed based on the presence of thermogenic gases and petroleum hydrocarbon compounds.

California↗
USGS2025

Rainfall thresholds for postfire debris-flow initiation vary with short-duration rainfall climatology

The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris-flow initiation are commonly expressed as rainfall intensity-duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass-movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff-generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris-flow initiation thresholds vary systematically with short-duration rainfall-intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much-needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field-based hazard assessment. Furthermore, if the observed variation in thresholds reflects long-term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris-flow likelihood.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2025

Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets

Coastal marsh wetlands experience variations in vertical gains and losses through time, which have allowed them to infill relict topography and record variations in drivers. The stratigraphic unit associated with the development of the marsh also reflects the long-term importance of key ecosystem services supplied by the marsh environment, including carbon storage and storm mitigation. Mapping these coastal wetland sediments and the marsh unit thickness is challenging as traditional coastal geophysical tools are not easily deployable (acoustic methods) or are unreliable in saline-soil environments (e.g., ground-penetrating radar), leaving core-based methods the most viable mapping method. In the present study, we utilized prior information on the geologic architecture of the region to select spatial and physical metrics that likely persisted throughout evolution of the marsh during the late Holocene. We then assessed the individual and collective power of these metrics to predict marsh thickness observed from cores. Employing regressive predictive models powered by these data, we improve the quantification of marsh thickness for a coastal fringing marsh within the Grand Bay estuary in Mississippi and Alabama (USA). The information gained from this approach yields improved estimates of the carbon stocks in this environment. Additionally, the stored sediment masses reflect the past, and potential future, persistence of the Grand Bay marsh under historical and present marsh-estuarine sediment exchange fluxes. Such improvements to both the sediment budget of recent marsh stratigraphic units and the spatial extent provide new resources for comparison with large-scale landscape models, the latter of which may be used, when validated, to predict future change and ecosystem transformations.

Alabama. Mississippi↗
USGS2024

Using a time-of-travel sampling approach to quantify per- and polyfluoroalkyl substances (PFAS) stream loading and source inputs in a mixed-source, urban catchment

Understanding per- and polyfluoroalkyl substances (PFAS) mass distribution in surface and groundwater systems can support source prioritization, load reduction, and water management. Thirteen sites within an urban catchment were sampled utilizing a time-of-travel sampling approach to minimize the influence of subdaily fluctuations in mass from PFAS point sources and to quantify PFAS and ancillary chemical loads from various PFAS sources. A larger increase in perfluoroalkyl sulfonate (PFSA) loads (8 to 11 μg/s, up to 618%) than in perfluoroalkyl carboxylate (PFCA) loads (no change to 3.4 μg/s, up to 122%) was observed at sites below tributaries influenced by military bases with known groundwater discharge. Point discharges from two sewage treatment plants (STPs) resulted in increases in PFCA and PFSA loads that were similar (6 and 10 μg/s respectively) below the first STP and greater for PFCA compared to PFSA loads (23 and 13 μg/s respectively) below the second STP. Overall, percent increases in total PFAS load ranged from 20 to 277% for military base inputs and 44 to 77% for STP inputs. A focus catchment that represents only 14% (76.9 km 2 ) of the drainage area at the most downstream site (544 km 2 ) accounted for about 70% of PFSA and 40% of PFCA loads observed at the most downstream site. Results show that by using a time-of-travel sampling approach in mixed, urban settings with several PFAS sources, it is possible to quantify stream loads from individual PFAS sources, thereby improving source attribution and providing actionable data for water-resource managers.

ACS ES&T Water↗
USGS2025

A framework for understanding the effects of subsurface agricultural drainage on downstream flows

Understanding controls on streamflow volume and magnitude is important to water resource management applications, such as critical water and transportation structure design and floodplain mapping. Changes in land use and agricultural practices, such as subsurface agricultural drainage, may be contributing to changes in streamflow characteristics. Subsurface agricultural drainage, also known as tile drainage, is the practice of installing drains in the subsurface of agricultural fields to improve productivity. Because of the complex interactions between subsurface drainage systems, precipitation, local soil conditions, and land management practices, it is difficult to determine how subsurface agricultural drainage affects downstream flow. Previously developed subsurface agricultural drainage conceptual models under dry, saturated, and winter conditions are summarized, and current literature on the effects of subsurface agricultural drainage on downstream flows, focusing on peak flow, non-event flow, and total flow to develop frameworks for discussing these systems is compiled. The effects that subsurface drainage has on hydrologic systems are expected to vary by site and are seasonally based on system design, soil type, moisture conditions, precipitation characteristics, and land conditions. Subsurface drainage can affect the magnitude of peak flow by converting surface runoff from a storm event to subsurface runoff. By increasing hydrologic connectivity of a catchment, subsurface drainage can increase non-event flow or the flow between two storm events, typically dependent on lateral flow through the subsurface and groundwater. Theoretically, by diverting water from groundwater recharge or by reducing water available for evapotranspiration, subsurface drainage may increase the total volume of flow. Precipitation changes may increase infiltration, excess overland flow, and flood risk regardless of the presence or absence of subsurface drainage.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗
USGS2026

Legacy of the fumigant 1,2-dibromo-3-chloropropane (DBCP) in California groundwater

The fumigant pesticide 1,2-dibromo-3-chloropropane (DBCP) was widely used in California agriculture during the 1960s and 1970s before being banned in 1979. Despite this ban, DBCP continues to contaminate groundwater due to its persistence and mobility. This study evaluates the distribution, historical trends, and projected persistence of DBCP in California using data from over 13,000 public supply wells and additional domestic, irrigation, and observation wells (1980-2022). Since 2010, DBCP has been detected in 9% of public supply wells statewide, with higher frequencies in the San Joaquin Valley (21%) and upper Santa Ana River watershed (13%), where DBCP use was most prevalent. Approximately 70% of wells had decreasing concentration trends, whereas increases were more common in deeper wells, indicating downward vertical migration of the DBCP front. Groundwater age estimates show that recharge timing aligns with the 1960s–1970s loading period, enabling reconstruction of peak inputs and providing a basis for age based modeling. To estimate future persistence, we applied a one dimensional advection–dispersion model that simulates long term declines in peak concentrations based on groundwater age, historical loading, and a 38 year degradation half life. Model projections suggest that concentrations above the maximum contaminant level may persist in a declining number of wells until approximately 2080 (range: 2048–2109), with longer persistence in the San Joaquin Valley. The simplified modeling framework, based on age distributions typical of wells capturing peak concentrations, can provide practical regional scale assessment of non-point source contaminants where long-term monitoring exists. This study highlights how the legacy of DBCP contamination will likely affect California's groundwater resources throughout the 21st century.

California↗
USGS2022

U-Pb scheelite ages of tungsten and antimony mineralization in the Stibnite-Yellow Pine district, central Idaho

The Stibnite-Yellow Pine district contains the largest antimony resource in the United States, as well as significant gold, and is a historic producer of tungsten. Application of in situ laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) direct dating of scheelite from two Au-Sb-W ore deposits, Yellow Pine and Hangar Flats, yielded an older group of U-Pb ages in the range of 60.0 ± 2.8 to 57.0 ± 1.1 Ma and a younger U-Pb age for scheelite intergrown with stibnite of 47.4 ± 1.1 Ma. These in situ analyses were calibrated by isotope dilution-thermal ionization mass spectrometry (ID-TIMS) U-Pb lower intercept ages of two coarsely crystalline scheelite samples that yielded ages of 57.52 ± 0.22 and 56.62 ± 0.16 Ma. Scheelite of the latter age is of sufficient quality to serve as a primary reference material for LA-ICP-MS scheelite U-Pb geochronology. The group of older U-Pb scheelite ages agrees with 40 Ar/ 39 Ar ages of 56.9 ± 1.2 to 56.38 ± 0.54 Ma on adularia from Yellow Pine and Hangar Flats, whereas the younger U-Pb scheelite age is similar to an 40 Ar/ 39 Ar age of 46.00 ± 0.40 Ma on adularia from an epithermal gold-silver deposit in the adjacent Thunder Mountain caldera. Our results indicate that the main stage of tungsten mineralization occurred at ca. 57 Ma, whereas the main stage of antimony mineralization occurred at ca. 47 Ma—thereby providing first-time age constraints for antimony and tungsten mineralization in the Stibnite-Yellow Pine district.

Idaho↗
USGS2025

Anatectic origin of Mississippian spodumene-bearing pegmatites in western Maine during orogenic plateau collapse

Spodumene pegmatites are an important lithium source, but the processes and tectonic settings in which they form are poorly understood. The Rumford pegmatite district surrounding Plumbago Mountain, western Maine, is host to numerous spodumene pegmatites, including the Plumbago North pegmatite (a world-class spodumene resource). Competing petrogenetic models for these spodumene pegmatites include (1) highly fractionated melts of the Mooselookmeguntic igneous complex and (2) anatexis. We tested these hypotheses by constraining the geologic, magmatic, metamorphic, and tectonic history of the Plumbago Mountain area with detailed geologic mapping and U-(Th)-Pb geochronology. The Silurian Rangeley Formation records initial isoclinal folding prior to, and contact-related metamorphism synchronous with, the intrusion of the 417 ± 4 Ma Plumbago Mountain pluton. Peak amphibolite facies metamorphism and crustal melting occurred during the ca. 410 to 400 Ma Acadian orogeny. Pulsed emplacement of the Mooselookmeguntic igneous complex occurred between ca. 389 and 356 Ma. Cassiterite U-Pb dates of spodumene pegmatites (333–327 Ma) are ≥23 m.y. younger than nearby granitic plutons, strongly arguing against the fractional crystallization model. Metamorphic monazite and xenotime (346–328 Ma) and 330 to 308 Ma 40 Ar/ 39 Ar hornblende dates indicate metamorphism coeval with spodumene pegmatite emplacement, supporting anatectic models. Reheating, anatexis, and spodumene pegmatite emplacement occurred during collapse of the 380 to 330 Ma Acadian orogenic plateau. Lithium enrichment may be linked to one or more stages of partial melting of metasedimentary and plutonic rocks during the formation, tenure, and collapse of the Acadian altiplano and emphasizes the role of anatexis in producing spodumene pegmatites of economic significance.

Maine↗
USGS2025

Waning greenhouse gas emissions from U.S. Federal lease coal production by the mid-21st century

This study presents estimates of future years (2024–2051) United States Federal lease coal production and the resulting greenhouse gas (GHG) emissions from the combustion, transport, and mining of that fuel. Results from the coal production estimate indicate a decline in production from Federal leases; with known production of 240 million short tons (mtn) in 2023 and a projected decline to 34.0 mtn by 2051, which represents a reduction to 14.2% of the 2023 value. In parallel with this projection, total GHG emissions are estimated to decrease from 402.2 million metric tons of carbon dioxide equivalent (MMT CO 2 eq.) in 2024 to 55.0 MMT CO 2 eq. in 2051, a decline to 13.7% of 2024 emissions estimates. The reductions in coal production and emissions are mainly the result of planned coal combustion power plant closures, with major projected closures in 2037 and 2048. However, GHG emissions estimates for future years can be uncertain as they rely heavily on coal production estimates from operators' public business plans and other publicly available resources. Forward looking plans of this type are subject to significant changes if economic and political factors deviate from current information. Results suggest that average GHG emissions over the time series breakout to 95% end point combustion, 3.7% transportation combustion emissions, and 1.3% fugitive emissions, although there is uncertainty associated with these figures. Uncertainty stemming from production projections, sector distributions, and emissions factors on the future emissions estimates increases with time, ranging from −28% to +48% within the 2024–2051 timeframe.

Alabama, Colorado, Montana, North Dakota, Utah, Wy↗
USGS2026

Re-examining the growing degree day minimum for grass carp spawning initiation in Lake Erie: Have we missed the mark?

Understanding the timing of life history processes of invasive fish species, such as adult aggregations during spawning, allows natural resource managers to optimize targeted population control efforts. Temperature-based estimates of the timing of spawning initiation for grass carp ( Ctenopharyngodon idella ) exist from its native range, but have not previously been developed for grass carp reproduction in its invaded range in the Laurentian Great Lakes of North America. We accounted for differences among methods across studies and calculated cumulative growing degree days (GDD) for the dates of grass carp egg capture in Lake Erie tributaries (Sandusky, Maumee, and Huron rivers) during 2015–2024 and compared these values to the existing GDD base 15°C requirement estimate from the native range (633 GDD–15°C). The earliest egg detection in Lake Erie (Sandusky River) was 19 GDD–15°C or 361 GDD–5°C (latest egg detection was 2285 GDD–5°C from the Sandusky River), indicating that spawning was initiated up to 25 days earlier than would be predicted by the native range GDD. Moreover, spawning in Lake Erie tributaries occurred earlier than predicted for 58% of spawning events examined based on the native range GDD. The GDD values for spawning initiation in Lake Erie tributaries can be used to refine the timing of control efforts targeting pre-spawn and spawning adult fish, inform the timing of egg sampling, and provide linkages to existing early life stage models to infer the length of the growing season available for age-0 fish to reassess tributary suitability.

Lake Erie, Maumee, River, Sandusky river↗