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Deep subsurface organic-rich shale supports abundant, diverse, and novel fungi

As Earth’s principal reservoir of organic carbon and microbial biomass, the deep subsurface hosts microorganisms capable of mobilizing this once-sequestered carbon. Contrary to standard assumptions of eukaryotic scarcity, this study documents abundant fungal communities, ranging from 4.2 × 10 3 to 6.8 × 10 3 fungal cells mL −1 , across a methane-producing organic-rich shale 247–556 meters below the surface. Although fungal:bacterial cell ratios ranged from 1:7028 to 1:713, application of biomass conversion factors developed for oceanic systems yielded a median fungal:bacterial biomass ratio of 1:4.7. 16S rRNA gene amplicons revealed bacterial and archaeal communities mirroring those found in well-characterized extremophilic, carbon-degrading environments, while sequencing of 18S rRNA gene and ITS rRNA spacer amplicons collectively identified a eukaryotic hotspot with 689 fungal OTUs across six phyla. The dominant fungal classes, Agaricomycetes and Dothideomycetes, are well-established degraders of recalcitrant carbon compounds at the surface, suggesting they may similarly contribute to organic matter degradation and ecosystem maintenance in the subsurface. Cultivation and isolation efforts yielded 205 fungal strains, including 13 candidate novel taxa, underscoring the deep subsurface as an underexplored eukaryotic habitat. Stable carbon isotopes indicate methane is predominantly generated via microbial conversion of the fossil carbon, while water isotopes suggest in situ geochemical conditions have been relatively stable since the Late Pleistocene, with subglacial recharge as a plausible mechanism for microbial introduction. Collectively, these findings suggest that fungi are underrecognized contributors to organic matter transformation and functional diversity in the deep biosphere, revealing a critical gap in our understanding of deep subsurface ecosystem processes.

Indiana, Michigan, Ohio

Groundwater quality near an oil field in a stream-dominated recharge setting, California, USA

Alluvial valley aquifers are important sources of water supply in many areas but effects of co-located oil and gas development on these resources have not been widely reported, especially in settings where recharge is dominated by stream infiltration. Interpreting the presence of geochemical indicators in the context of hydrology, geology, and other factors provides a more complete understanding of the relations between groundwater and sources of oil-field fluids and aids in identifying risks associated with oil and gas development. Groundwater and Salinas River water samples were collected in an alluvial valley near the San Ardo Oil Field in Monterey County, California and analyzed for a wide range of dissolved chemical, gas, and isotopic constituents to determine if oil-field fluids (water and gas from oil-producing and non-producing zones) have mixed with fresh groundwater used for supply. Hydraulic gradients, age-dating tracers, and other geochemical indicators show that recharge from the Salinas River has the potential to dilute oil-field fluids that might migrate or seep into the aquifer. Groundwater and Salinas River water collected downgradient of the San Ardo Oil Field showed little or no evidence of mixing with oil-field fluids. Some samples within the oil field contained trace amounts of hydrocarbons or elevated temperatures, indicating that any potential effects from oil-field activities are minor or have been diluted by recharge from the Salinas River. The two samples with the most geochemical evidence of potential mixing with oil-field fluids (SP-18 and GW-17) were collected west of or along the Los Lobos fault, where naturally occurring hydrocarbons are near the land surface. Those samples are also near active or inactive oil-field wells, and so anthropogenic activities and pathways cannot be ruled out as a cause of trace detections of hydrocarbons and elevated temperatures in the aquifer.

California

Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022

The 1973 Oklahoma Groundwater Law (Oklahoma Statutes §82-1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. At present (2025), the Oklahoma Water Resources Board has not established a maximum annual yield for the Red River alluvial aquifer east of Lake Texoma. To support the evaluation and determination of a maximum annual yield, a hydrogeologic framework and conceptual groundwater-flow model were developed to assess groundwater availability in the Red River alluvial aquifer east of Lake Texoma. The scope of this hydrologic investigation is the alluvium and terrace containing the Red River alluvial aquifer in Oklahoma between Lake Texoma, the Texas State line, and the Arkansas State line, an extent referred to in this report as “the eastern part of the Red River alluvial aquifer.” Parts of the alluvium and terrace extent in Arkansas and Texas are included in some analyses to address hydrologic influences from outside the aquifer’s boundaries in Oklahoma. The eastern part of the Red River alluvial aquifer in southeastern Oklahoma consists of approximately 401,280 acres of Quaternary alluvium and terrace deposits associated with the Red River and its major tributaries. Mean annual recharge to the aquifer for the 1980–2022 study period was estimated to be 8.62 inches per year, or 17.98 percent of the mean annual precipitation over the same period (47.94 inches). This mean annual recharge rate is equivalent to an inflow of approximately 288,250 acre-feet per year for the eastern part of the Red River alluvial aquifer. Recharge estimated using the Soil-Water-Balance code accounts for 98.7 percent of the conceptual-model inflows to the eastern part of the Red River alluvial aquifer. Saturated-zone evapotranspiration accounts for 11.9 percent and net streambed seepage accounts for 87.4 percent of the outflows in the conceptual model.

Arkansas, Oklahoma, Texas

Utilization of stochastic ground motion simulations for scenario-based performance assessment of geo-structures

Probabilistic seismic performance assessments of engineered structures can be highly sensitive to the seismic input excitation and its variability. In the present study, the scenario-based performance assessment recommended by Federal Emergency Management Agency (FEMA) P-58 guidelines is adopted to estimate seismic fragility of concrete dams for various seismic hazard scenarios. Due to the scarcity of recorded ground motions and thereby their poor representation of uncertainties, stochastic ground motion simulation methods are utilized to obtain the required input excitations. Moreover, to understand the uncertainty in ground motion simulation models, two broadband stochastic simulation models are used to generate input excitations representing six seismic hazard scenarios defined by earthquake magnitude, source-to-site distance, and soil conditions. Optimal intensity measure parameters for each scenario are identified using a systematic procedure that considers criteria such as efficiency, practicality, proficiency, sufficiency, and hazard compatibility. Fragility curves and surfaces are derived using the cloud analysis technique, taking into account various damage measures and limit state functions. The study finds that the derived fragility curves are particularly sensitive to the selection of earthquake scenarios, the choice of records, and the methods used to calculate fragility curves, with less sensitivity observed to different engineering demand parameters. Given this sensitivity, particularly to ground motion selection, the study highlights the necessity of incorporating both model-to-model variability (epistemic uncertainty) and record-to-record variability (aleatory uncertainty), alongside the established material and modeling uncertainties, in the probabilistic seismic assessment.

Reliability Engineering and System Safety (RESS)

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

Alaska

Biodegradation of chlorinated ethenes at a karst site in middle Tennessee

This report presents results of field and laboratory investigations examining the biodegradation of chlorinated ethenes in a karst aquifer contaminated with trichloroethylene (TCE). The study site, located in Middle Tennessee, was selected because of the presence of TCE degradation byproducts in the karst aquifer and available site hydrologic and chlorinated-ethene information. Additional chemical, biological, and hydrologic data were gathered to evaluate whether the occurrence of TCE degradation byproducts in the karst aquifer was the result of biodegradation within the aquifer or simply transport into the aquifer. Geochemical analysis established that sulfate-reducing conditions, essential for reductive dechlorination of chlorinated solvents, existed in parts of the contaminated karst aquifer. Other areas of the aquifer fluctuated between anaerobic and aerobic conditions and contained compounds associated with cometabolism, such as ethane, methane, ammonia, and dissolved oxygen. A large, diverse bacteria population inhabits the contaminated aquifer. Bacteria known to biodegrade TCE and other chlorinated solvents, such as sulfate-reducers, methanotrophs, and ammonia-oxidizers, were identified from karst-aquifer water using the RNA-hybridization technique. Results from microcosms using raw karst-aquifer water found that aerobic cometabolism and anaerobic reductive-dechlorination degradation processes were possible when appropriate conditions were established in the microcosms. These chemical and biological results provide circumstantial evidence that several biodegradation processes are active in the aquifer. Additional site hydrologic information was developed to determine if appropriate conditions persist long enough in the karst aquifer for these biodegradation processes to be significant. Continuous monitoring devices placed in four wells during the spring of 1998 indicated that pH, specific conductance, dissolved oxygen, and oxidation-reduction potentials changed very little in areas isolated from active ground-water flow paths. These stable areas in the karst aquifer had geochemical conditions and bacteria conducive to reductive dechlorination of chlorinated ethenes. Other areas of the karst aquifer were associated with active ground-water flow paths and fluctuated between anaerobic and aerobic conditions in response to rain events. Associated with this dynamic environment were bacteria and geochemical conditions conducive to cometabolism. In summary, multiple lines of evidence developed from chemical, biological, and hydrologic data demonstrate that a variety of biodegradation processes are active in this karst aquifer.

Tennessee

Geologic map of the northwest flank of Mauna Loa volcano, Island of Hawai‘i, Hawaii

Mauna Loa, the largest active volcano on Earth, has erupted 34 times since written descriptions became available in A.D. 1832. The most recent eruption of Mauna Loa occurred on November 27, 2022, after a 38 year hiatus; it lasted for 12 days. Some eruptions began with only brief seismic unrest, whereas others followed several months to a year of increased seismicity. Once underway, Mauna Loa’s eruptions can produce lava flows that may reach the sea in less than 24 hours, severing roads and utilities. For example, lava flows that erupted from the Southwest Rift Zone in 1950 advanced at an average rate of 9.3 kilometers per hour (5.8 miles per hour); all three lobes reached the ocean within ~24 hours. Near the eruptive vents, the flows likely traveled even faster. In terms of eruption frequency, pre-eruption warning, and rapid flow emplacement, Mauna Loa has great volcanic-hazard potential for the Island of Hawai‘i. Volcanic hazards on Mauna Loa can be anticipated, and risk substantially mitigated, by documenting its past activity to refine our knowledge of the hazards, and by alerting the public and local government officials of our findings and their implications for hazards assessments and risk. The map of the north and west flanks of Mauna Loa shows the distribution and relation of volcanic and surficial sedimentary deposits. It incorporates previously reported work published as generalized small-scale maps and a more detailed map. Within the mapped area, lava has flowed from three different source regions: the Northeast Rift Zone (22 percent), the summit (64 percent), and radial vents (14 percent). All three have different points of origin which, in turn, affect the flow characteristics and periodicity of activity. The map area includes the uppermost part of the NERZ and extends from the highest elevation––13,040 feet at the south end of the Kokoolau quadrangle, just below the summit caldera––to the sea northwest and west of the summit. Lava that erupts from the north and west flanks typically flows to the west, northwest, or north, depending on the vent location. Both morphologic lava flow types—‘a‘ā and pāhoehoe—are present. Pāhoehoe units tend to spread out or widen in low-slope regions, such as in the saddle regions between Mauna Loa and Mauna Kea or between Mauna Loa and Hualālai. In comparison, ʻaʻā flows generally produce narrower flow lobes that have higher relief. This map is the fifth in a series of five maps that will cover Mauna Loa volcano. NOTE: Map sheet 1 contains lines and type with overprint. This feature may be turned on or off in the Adobe Acrobat page display preferences.

Hawaii

Impact of gas/liquid phase change of CO2 during injection for sequestration

CO 2 sequestration in deep saline formations is an effective and important process to control the rapid rise in CO 2 emissions. The process of injecting CO 2 requires reliable predictions of the stress in the formation and the fluid pressure distributions – particularly since monitoring of the CO 2 migration is difficult – to mitigate leakage, prevent induced seismicity, and analyze wellbore stability. A key aspect of CO 2 is the gas–liquid phase transition at the temperatures and pressures of relevance to leakage and sequestration, which has been recognized as being critical for accurate predictions but has been challenging to model without ad hoc empiricisms. This paper presents a robust multiphase thermodynamics-based poromechanics model to capture the complex phase transition behavior of CO 2 and predict the stress and pressure distribution under super- and sub- critical conditions during the injection process. A finite element implementation of the model is applied to analyze the behavior of a multiphase porous system with CO 2 as it displaces the fluid brine phase. We find that if CO 2 undergoes a phase transition in the geologic reservoir, the spatial variation of the density is significantly affected, and the migration mobility of CO 2 decreases in the reservoir. A key feature of our approach is that we do not a priori assume the location of the CO 2 gas/liquid interface – or even if it occurs at all – but rather, this is a prediction of the model, along with the spatial variation of the phase of CO 2 and the change of the saturation profile due to the phase change.

Journal of the Mechanics and Physics of Solids

Beyond optimality: Dryland ecosystems infrequently use water efficiently for carbon gain

Optimality theory assumes plants maximize carbon gain per unit water lost and is often implemented to scale leaf-level carbon gain and water use to regional and global scales. Optimality theory is often mathematically represented by assuming plant water-use efficiency (WUE) scales with VPD k , where k = ½ represents expected optimal behavior. It is unclear, however, if this relationship holds in arid and semi-arid ecosystems that are strongly impacted by soil and atmospheric moisture status. We used data from seven flux tower sites along an aridity gradient in New Mexico to answer: how does the relationship between WUE and VPD compare to expectations based on optimality theory? To address this question, we integrated the Dynamic Evapotranspiration Partitioning Approach for Rapid Timescales with a stochastic antecedent model to estimate ecosystem-level WUE (GPP/T) and the net sensitivity of WUE to VPD, or k Dynamic , which we compare to the theoretical optimal sensitivity of k = ½. Our results show that optimality theory is not always appropriate, and k Dynamic often deviates from ½, especially at some of the more arid sites or during periods of low soil moisture. At less arid, higher elevation sites, k Dynamic is most consistent with optimality theory at moderate VPD levels, but not at high VPD. In general, the sensitivity of WUE to VPD is highly variable such that k Dynamic exhibits notable daily and seasonal variability, suggesting highly dynamic stomatal behavior. These results emphasize that representing plant water-use strategies as dynamic in time and space is critical to improving large-scale estimates of plant water use.

New Mexico

Mine waste as a potential source of critical minerals and other commodities: Examples from the Four Corners states, USA

The growing demand for critical minerals and other mineral resources has raised concerns about possible supplies of these essential commodities. Mine waste is a potential source of these essential commodities. We compiled a geospatial database of publicly available data of the largest non-fuel mine waste features (>200,000 m 2 in areal extent) in the Four Corners states of the United States, where most of those features are from porphyry Cu deposits. The combined volume of those large porphyry Cu mine waste features is approximately 17 cubic kilometers, 60% of which is ore-related material such as tailings. Using publicly available data on density, grade, and previous recovery values, we estimate the contained endowments of Ag, As, Au, Bi, Cu, Mo, Re, S, Sb, Se, Te, and W. These estimates indicate endowments within ore-related mine wastes are collectively comparable to endowments of giant to supergiant deposits. If fully recovered, these commodities could meet current global demand from less than 1 year (Sb) to more than 200 years (Re), underscoring the enormous untapped resource potential of mine waste.

Arizona, Colorado, New Mexico, Utah

Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022

The 1973 Oklahoma Groundwater Law (Oklahoma Statute §82–1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. Every 20 years, the Oklahoma Water Resources Board is required to update the hydrologic investigation on which the maximum annual yield determinations were based. The maximum annual yield allocated per acre of land is used to set the equal-proportionate share pumping rate. The maximum annual yield of 5,913,600 acre-feet per year and equal-proportionate-share of 2.1 acre-feet per acre per year currently (2025) in place for the Antlers aquifer were issued by the Oklahoma Water Resources Board on February 14, 1995. Because more than 20 years have elapsed since the 1995 final order for the Antlers aquifer was issued, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, completed an in-depth hydrologic study that included a hydrogeologic framework and conceptual groundwater-flow model for the 1980–2022 study period. The results of an analysis of land use, long-term climate patterns, streamflow and base-flow patterns, historical groundwater use, as well as groundwater-level fluctuations across the Antlers aquifer are described. In addition, groundwater quality was analyzed for total dissolved solids concentrations and major ions for the Antlers aquifer. An updated hydrogeologic framework was developed that included refining the aquifer boundary in Oklahoma, the creation of new potentiometric surface and saturated thickness of fresh groundwater maps, one multiple-well aquifer test, slug tests, and an analysis of lithologic logs across the aquifer. A conceptual groundwater flow model and water budget were developed by incorporating estimates of recharge from precipitation, saturated-zone evapotranspiration, streambed seepage, lateral groundwater flows, vertical leakage, and withdrawals from groundwater wells.

Oklahoma, Texas

Pesticides in surface waters of the Upper Colorado River Basin, Colorado, 1996-98

Forty-four river, stream, and drain sites in the Upper Colorado River Basin in Colorado were sampled during 1996-98 to determine the occurrence and distribution of pesticides in the basin. In a fixed-station study, 57 surface-water samples were collected from October 1996 through January 1998 at four sites. Each site was sampled approximately monthly for up to a year, with more frequent sampling during the spring and summer growing season. In a synoptic study, surface-water samples were collected at 43 sites in the agricultural areas of the Grand Valley and the Uncompahgre River Valley in May 1998. Each site was sampled once. Pesticide concentrations generally were low and varied seasonally and across land uses. Thirty-five pesticides were detected at least once in the two studies, and 11 pesticides accounted for almost 82 percent of the detections. Herbicides were more commonly detected than insecticides, and only the herbicides alachlor and atrazine were detected in more than 50 percent of the samples. Carbofuran was the most commonly detected insecticide and was detected in 19 percent of the samples. Pesticide detections increased and were measured at higher concentrations in the summer months and at the agriculture sites. All pesticide concentrations were less than drinking-water standards, and most complied with human-health advisories and criteria for the protection of freshwater aquatic life. Pesticides in the Upper Colorado River Basin in Colorado were detected slightly less frequently and generally at lower concentrations than in 20 National Water-Quality Assessment Program study-unit basins that collected water-quality data from 1992 through 1996. Results from surface-water sampling conducted during 1996?98 in the Upper Colorado River Basin in Colorado indicate that beneficial uses of water were not being impaired by the presence of pesticides in surface waters in the basin.

Colorado

Magnitude and frequency of low flows in the Suwannee River Water Management District, Florida

Low-flow frequency statistics for 20 gaging stations having at least 10 years of continuous record and 31 other stations having less than 10 years of continu ous record or a series of at least two low- flow measurements are presented for unregulated streams in the Suwannee River Water Management District in north-central Florida. Statistics for the 20 continuous-record stations included are the annual and monthly minimum consecutive-day average low- flow magnitudes for 1, 3, 7, 14, and 30 consecutive days for recurrence intervals of 2, 5, 10, 20, and, for some long-term stations, 50 years, based on records available through the 1994 climatic year.Only theannual statistics are given for the 31 other stations; these are for the 7- and 30-consecutive day periods only and for recurrence intervals of 2 and 10 years only. Annual low-flow frequency statistics range from zero for many small streams to 5,500 cubic feet per second for the annual 30- consecutive-day average flow with a recurrenceinterval of 2 years for the Suwannee River near Wilcox (station 02323500). Monthly low-flow frequency statistics range from zero for many small streams to 13,800 cubic feet per second for the minimum 30-consecutive-day average flow with a 2-year recurrence interval for the month of March for the same station. Generally, low-flow characteristics of streams in the Suwannee River Water Management District are controlled by climatic, topographic, and geologic fac tors. The carbonate Floridan aquifer system underlies, or is at the surface of, the entire District. The terrane's karstic nature results in many sinkholes and springs. In some places, springs may contribute greatly to low streamflow and the contributing areas of such springs may include areas outside the presumed surface drainage area of the springs. In other places, water may enter sinkholes within a drainage basin, then reappear in springs downstream from a gage. Many of the smaller streams in the District go dry or have no flow for several months in many years. In addition to the low-flow statistics, four synoptic low-flow measurement surveys were conducted on 161 sites during 1990, 1995, and 1996. The measurements were made to provide "snapshots" of flow conditions of streams throughout the Suwannee River Water Management District. Magnitudes of low flows during the 1990 series of measurements were in the range associated with minimum 7-consecutive-day 50-year recurrence interval to the minimum 7-consecutive-day 20-year recurrence interval, except in Taylor and Dixie Counties, where the magnitudes ranged from the minimum 7-consecutive-day 5-year flow level to the7-consecutive-day 2-year flow level. The magnitudes were all greater than the minimum 7- consecutive-day 2-year flow level during 1995 and 1996. Observations of no flow were recorded at many of the sites for all four series of measurements.

Florida

Complex carbonate ore mineralogy in the Mountain Pass carbonatite rare earth element deposit, USA

Economic concentrations of rare earth element (REE) minerals are uncommon in the Earth’s crust, with most occurring in carbonatites. Unlike most igneous rocks composed of silicate minerals, carbonatites are dominated by carbonate minerals, some of which can incorporate significant light REEs (LREEs; La, Ce, Pr, Nd). Technological applications of REEs are numerous and they have been identified as some of the most critical mineral commodities to the global economy. The Mountain Pass carbonatite stock in the Mojave Desert of California is the most economically significant REE deposit in the USA and contains a few to tens of percent (by volume) of the carbonate REE ore mineral bastnäsite. Despite the economic significance of the Mountain Pass deposit, studies of its ore mineralogy are limited. Here we present new carbonate ore mineralogy data for a compositionally diverse suite of carbonatitic rocks from the Mountain Pass stock and related dikes. Whole-rock geochemical data are integrated with mineral-scale textural and chemical data obtained by scanning electron microscopy (SEM), electron probe microanalysis (EPMA), and microRaman spectroscopy. Our results document a complex spectrum of REE-bearing carbonate minerals and intermediate mixed-layer structures. Mineral species include bastnäsite [REE(CO 3 )F], hydroxylbastnäsite [REE(CO 3 )OH], parisite [Ca(REE) 2 (CO 3 ) 3 F 2 ], synchysite [Ca(REE)(CO 3 ) 2 F], röntgenite [Ca 2 (Ce,La) 3 (CO 3 ) 5 F 3 ], and sahamalite [(Mg,Fe 2+ )(REE) 2 (CO 3 ) 4 ]. Carbonate ore mineralogy is heterogeneous within and between samples, including at the intracrystal scale. Complexly zoned crystals exhibit as many as five to six different compositional domains and syntaxial intergrowths, commonly with the more Ca-rich varieties (parisite, synchysite) forming crystal rims that surround relict bastnäsite cores. We attribute the phenocryst variability to changes in the chemistry and temperature of primary carbonatite magmas and evolved/exsolved fluids. Cross-cutting vein textures of calcite, celestine and various REE carbonate minerals, interstitial bastnäsite crystallization, breccia blocks lined by fine-grained bastnäsite, and the presence of hydroxylbastnäsite and partially hydroxylated bastnäsite point to the role of secondary hydrothermal processes in REE mineralization. Fluorcarbonate mineral compositions demonstrate that La and Ce are more structurally abundant in bastnäsite, whereas the more Ca-rich species (parisite, synchysite) contain a greater proportion of REE heavier than Pr (Nd, Sm, Eu, Gd) and Y. Atomic ratios of Pr/(Nd + Pr) are likewise variable, with the highest average value for bastnäsite (0.25) compared to parisite (0.22) and sychysite (0.21). This finding has geometallurgical implications, given that current mining operations are focused on recovery of Nd and Pr for high field strength permanent magnets and the Nd/Pr ratios are a critical factor in ore processing and magnet manufacture.

California

Nitrogen deposition weakens soil carbon control of nitrogen dynamics across the contiguous United States

Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified ( ƒ nitrified ), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta-glucosidase (BG) and N -acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒ nitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒ nitrified . The ƒ nitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒ nitrified , including for high soil C sites predicted to have low ƒ nitrified , which decreased the role of soil C as a predictor of ƒ nitrified . Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID-19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒ nitrified . Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.

contiguous United States

Stream habitat characteristics at selected sites in the Georgia-Florida coastal plain

Habitat characterization is part of a multidisciplinary approach to water-quality assessment implemented by the National Water-Quality Assessment Program. Habitat data were collected in the Georgia-Florida Coastal Plain study unit at 24 sites during 1993-95. Data were collected for habitat characteristics at three spatial scales: basin, segment, and reach. Basin data include physiography, land resource provinces, and land use, providing a description of the environmental setting at each site. Segment data include length, gradient, and sinuosity. A Kendall correlation analysis performed on segment characteristics and the log-of-basin area showed a correlation between segment gradient and the log-of-basin area and a correlation between sinuosity and segment length. Reach data consist of field-collected measurements of both instream and riparian habitats. Sand and detritus were the most common channel-bed substrates among the sampled sites. Measurements of channel width, water depth, and bank width and height were used to create cross-sectional profiles of each sampled area. Elevations of selected durations plotted on cross sections illustrated the percentage of time that the banks were inundated at each site. Sites were divided into two groups based on duration of bank inundation (less than or equal to 1 percent and greater than 1 percent). Bank woody vegetation was also sampled and a clustering algorithm known as Two-Way INdicator SPecies ANalysis (TWINSPAN) was used to analyze these data. TWINSPAN divided the sites into two groups based on their vegetation composition. A statistical comparison of the two types of site groups (duration of bank inundation and vegetation) was performed. The significant association between these groups was consistent with the hypothesis that inundation frequency affected riparian vegetation.

Florida, Georgia

Characterization of change in tree cover state and condition over the conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Forests

Methods to evaluate and improve the modeling of rupture directivity in assessment of seismic hazard

In recent years, there have been several advancements related to the modelling of near-source effects of earthquake rupture on strong ground shaking, leading to an improved characterization of ground motions and resulting seismic hazard. Some of these modifications have stemmed from physics-based numerical modelling of the earthquake rupture process, using physics-based dynamic rupture simulations. These contributions have led to a better understanding of how fault rupture characteristics, geometry, and the style of faulting can interact with the hypocenter-dependence on the path from source to site that may ultimately guide the development of seismic directivity models. Moving forward, the application of modern techniques can be used to incorporate these source characteristics and near-fault ground motion behavior that contribute to the azimuthally varying effects that result in rupture directivity. One example is the application of machine learning methods to support more automated integration of new predictor variables in model development and open more evaluation opportunities to access residuals. Here, we utilize several techniques to take advantage of the plethora of synthetic data and its ability to supplement preexisting trends observed in data. We showcase two examples of how models can be either developed, expanded upon, or constrained using artificial neural network model (ANNs). We evaluate the performance of the ANN with existing methods, comparing misfit, potential limitations, and ability to continue to improve upon these methods in the future. One approach uses a set of simulations with corresponding synthetic ground motions from the Southern California Earthquake Center (SCEC) CyberShake study to develop a ground motion model adapted to incorporate seismic directivity information using an ANN. This large database (TBs) enables us to train the model to capture magnitude, period, and distance variations and how these parameters relate to amplification from hypocenters located along finite-faults. In some cases, there is reduced misfit from better representing source features that aren’t included in base ground motion models that neglect hypocenter location (e.g. azimuthal variation, source-to-site terms). Another ANN method uses a shallow-layered neural network model to better fit a hypocenter-independent model. This method adjusts the median and aleatory variability to account for the averaged impact of various hypocenter distributions to fit the underlying directivity adjustment model. This method serves as a template to apply to other directivity models, improving computational efficiency and more readily enabling integration in hazard codes.

California