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USGS2025

Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health

Produced water is a chemically complex waste stream generated during oil and gas development. Roughly four trillion liters were generated onshore in the United States in 2021 (ALL Consulting, 2022, https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf ). Efforts are underway to expand historic uses of produced water to offset freshwater needs in water-stressed regions, avoid induced seismic activity associated with its disposal, and extract commodities. Understanding the potential exposures from current and proposed produced water uses and management practices can help to inform health-protective practices. This review summarizes what is known about potential human exposure to produced water from onshore oil and gas development in the United States. We synthesize 236 publications to create a conceptual model of potential human exposure that illustrates the current state of scientific inquiry and knowledge. Exposure to produced water can occur following its release to the environment through spills or leaks during its handling and management. Exposure can also arise from authorized releases, including permitted discharges to surface water, crop irrigation, and road treatment. Knowledge gaps include understanding the variable composition and toxicity of produced water released to the environment, the performance of treatment methods, migration pathways through the environment that can result in human exposure, and the significance of the exposures for human and ecosystem health. Reducing these uncertainties may help in realizing the benefits of produced water use while simultaneously protecting human health.

Environmental Health Perspectives↗
USGS2025

Statewide cumulative human health risk assessment of inorganics-contaminated groundwater wells, Montana, USA

Across the United States, rural residents rely on unregulated and generally unmonitored private wells for drinking water, which may pose serious health risks due to unrecognized contaminants. We assessed the nature, degree, and spatial distribution of cumulative health risks from inorganic contaminants in groundwater. Our analysis included nearly 84,000 data points from 6500+ wells, across 51 of Montana's 98 watersheds, using a public groundwater database. We compared a drinking water screening level cumulative risk assessment (CRA) for inorganics based on the U.S. Environmental Protection Agency (EPA) protective health thresholds (Maximum Contaminant Level Goals, Health Advisories [MCLG-HAs]) to a CRA based on EPA public supply enforceable Maximum Contaminant Levels (MCLs). Based on median concentrations of 19 inorganics (antimony, arsenic, barium, beryllium, boron, cadmium, chromium, copper, fluoride, manganese, molybdenum, nickel, nitrate, lead, selenium, strontium, thallium, uranium, zinc), 75% of watersheds had MCLG-HA-based cumulative risk values > 1.0; arsenic and uranium contributed the most risk, followed by strontium, fluoride, manganese and boron. Hence, this screening level (Tier I) CRA indicated widespread potential for unrecognized human health risk to private well users from inorganic contaminants considering both carcinogenic and non-carcinogenic risks. Sensitivity analysis showed that benchmarks applied (MCLG-HAs versus MCLs) exerted the largest control on results. Our findings identify priority regions for Tier 2 risk assessments to elucidate local sources and distributions of geogenic versus anthropomorphic contaminants. Our study is the first statewide assessment of cumulative health risk from groundwater that we are aware of, and results support increased statewide drinking water education and testing to reduce human health risks from contaminated private well water.

Montana↗
USGS2026

Perspectives and insights gained from applying landscape ecological approaches to the Upper Mississippi riverscape

Advances in remote sensing, spatial data collection, hydraulic and geospatial models, and the maturation of landscape ecology during the early 2000s spurred the concept of rivers as landscapes or ‘riverscapes’. Since that time, the Upper Mississippi River Restoration (UMRR) Program - one of the world’s longest running large-river ecosystem restoration and monitoring programs - has applied landscape ecological principles to the Upper Mississippi River System (UMRS). I examine spatial patterns of aquatic nutrient concentrations, submersed aquatic vegetation, and fish and mussel communities, finding that within-river patterns are often patchy in nature, likely resulting from how nutrient processes and community traits interact with spatial variability in hydraulic exchange patterns. Local-scale patchy spatial patterns in the UMRS are embedded in system-scale longitudinal gradients and a hierarchical view of the river has provided a foundation for strategic river restoration planning. Key Words: Aquatic Habitat, hydraulic connectivity, patch, restoration, riverscape

BioScience↗
USGS2024

Perspectives on transportable array Alaska background noise levels

Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.

Book chapter↗
USGS2025

Insights and strategic opportunities from the USGS 2024 Per- and Polyfluoroalkyl Substances (PFAS) Interagency Workshop

Introduction In 2021, the U.S. Geological Survey (USGS) published Circular 1490 titled, “Integrated Science for the Study of Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) in the Environment: A Strategic Science Vision for the U.S. Geological Survey” (Tokranov and others, 2021). Circular 1490 was created to be a resource for USGS scientists prioritizing and planning research related to per- and polyfluoroalkyl substances (PFAS) and to be a guide for developing partnerships with other scientists, State and Federal agencies, and stakeholders engaged in PFAS research and management and mitigation of the environmental and human-health effects of PFAS. This USGS PFAS Strategic Science Vision document was intended to be the foundation for a “living strategic vision,” periodically providing updates on the state of USGS PFAS research, emerging PFAS data gaps and needs, and progress on interagency and stakeholder PFAS partnerships and priorities. To meet this objective, the USGS planned to host an Interagency and Stakeholder PFAS Workshop every 2–3 years. During September 10–12, 2024, the USGS hosted the first Interagency and Stakeholder PFAS Workshop in Reston, Virginia. The Workshop brought together experts from other Federal agencies (U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, Food and Drug Administration, Department of Defense [Air Force, Army]), State agencies (Washington Fish and Wildlife, Virginia Department of Transportation), and academia (Harvard University, University of Maryland) to address key challenges relating to the measurement and modeling of PFAS and the implications for environmental health. Participants engaged in in-depth discussions centered around six pivotal topics related to PFAS: (1) sampling protocols, methods and interpretation; (2) environmental sources, source apportionment, and occurrence; (3) environmental fate and transport; (4) human and wildlife exposure routes and risk; (5) bioconcentration, bioaccumulation, and biomagnification; and (6) ecotoxicology and effects. Each topic had three breakout sessions. A recurrent theme of workshop discussions was how data on a nationwide scale for PFAS occurrence in various environmental matrices, including air, water, food crops, biota, soil, and streambed sediment could help to advance scientific understanding. Participants noted significant geospatial data gaps, particularly in the midwestern and southern United States and the Pacific Northwest. PFAS data collection tends to be more robust along the eastern seaboard and in California. Participants stressed how enhancing the integration of large and small datasets across various agencies could help to support national scale understanding of PFAS. To address these gaps, attendees suggested leveraging datasets from Federal entities like the USGS and the U.S. Department of Defense, State agencies, and municipal utility services to develop predictive contaminant detection and transport models. Improved coordination between water quality programs and USGS research could help to facilitate access to valuable data, leading to comprehensive databases that inform PFAS point (wastewater treatment plants and landfills) and nonpoint (runoff from land, atmospheric deposition, food packaging) sources, environmental transport mechanisms, environmental detection and concentrations, potential exposure routes, and health effects on different biota, including humans. A specific request was made to develop a map demarking the depth of modern (1953 or later) groundwater, which is susceptible to surface-derived anthropogenic (that is, human-made) contamination, based on tritium-age dating. Emphasis was placed on incorporation of hydrology, groundwater flow paths, groundwater–surface water interactions, and landscape factors in predictive statistical models as a step to improve contaminant source identification and tracking. Molecular fingerprinting approaches garnered attention as techniques to link specific PFAS mixtures detected in a sample to environmental sources and levels in biota (Dávila-Santiago and others, 2022). Integrating data from abiotic (that is, water, soil, and air) and biotic (that is, living organisms) systems identified as a research opportunity. For example, understanding the composition of soils and sediments, which include a mixture of mineral, plant, and animal components, could advance understanding of exposure pathways. The discussions highlighted opportunities to explore and understand the potential redistribution and biotic exposures of PFAS from biosolid and wastewater treatment plant effluent land application practices, in addition to atmospheric releases and discharges from landfill and wastewater treatment plants. Participants identified research gaps surrounding how these sources may contribute to contamination and may affect surrounding ecosystems, including a better definition of anthropogenic background concentrations. Moving forward, the collection of co-occurrence data was noted as a means to improve understanding of complex mixtures and to leverage companion modeling efforts focused on areas with high and low contamination levels to identify areas of concern and unaffected resources. Participants emphasized how centralized USGS databases and the establishment of sample-metadata archives can help to ensure that samples are preserved and accessible for future research. In conclusion, the workshop participants identified opportunities to bridge data gaps and improve measurement techniques, modeling frameworks, databases, and communication, to enhance the understanding of PFAS and their effects on environmental and human health. Upon completion of the workshop, participants indicated an interest in developing strategic data collection, modeling, and analytical approaches to address these challenges.

Open-File Report↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2025

Tapwater exposures, residential risk, and mitigation in a PFAS-impacted-groundwater community

Tapwater (TW) safety and sustainability are priorities in the United States. Per/polyfluoroalkyl substance(s) (PFAS) contamination is a growing public-health concern due to prolific use, widespread TW exposures, and mounting human-health concerns. Historically-rural, actively-urbanizing communities that rely on surficial-aquifer private wells incur elevated risks of unrecognized TW exposures, including PFAS, due to limited private-well monitoring and contaminant-source proliferation in urbanizing landscapes. Here, a broad-analytical-scope TW-assessment was conducted in a hydrologically-vulnerable, Mississippi River alluvial-island community, where PFAS contamination of the shallow-alluvial drinking-water aquifer has been documented, but more comprehensive contaminant characterization to inform decision-making is currently lacking. In 2021, we analyzed 510 organics, 34 inorganics, and 3 microbial groups in 11 residential and community locations to assess (1) TW risks beyond recognized PFAS issues, (2) day-to-day and year-to-year risk variability, and (3) suitability of the underlying sandstone aquifer as an alternative source to mitigate TW-PFAS exposures. Seventy-six organics and 25 inorganics were detected. Potential human-health risks of detected TW exposures were explored based on cumulative benchmark-based toxicity quotients ( ∑ TQ ). Elevated risks ( ∑ TQ ≥ 1) from organic and inorganic contaminants were observed in all alluvial-aquifer-sourced synoptic samples but not in sandstone-aquifer-sourced samples. Repeated sampling at 3 sites over 52–55 h indicated limited variability in risk over the short-term. Comparable PFAS-specific ∑ TQ for spatial-synoptic, short-term (3 days) temporal, and long-term (3 years quarterly) temporal samples indicated that synoptic results provided useful insight into the risks of TW-PFAS exposures at French Island over the long-term. No PFAS detections in sandstone-aquifer-sourced samples over a 3 year period indicated no PFAS-associated risk and supported the sandstone aquifer as an alternative drinking-water source to mitigate community TW-PFAS exposures. This study illustrated the importance of expanded contaminant monitoring of private-well TW, beyond known concerns (in this case, PFAS), to reduce the risks of a range of unrecognized contaminant exposures.

Wisconsin↗
USGS2025

Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems

Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.

Alaska↗
USGS2026

Assessing environmental drivers of denitrification in restored riverine floodplains

Restoration of impaired floodplains is an increasingly prevalent strategy for alleviating water quality concerns and reducing downstream flooding at watershed scales. Floodplains temporarily store water and slow flow velocity to promote sedimentation during overbank flooding and remove inorganic nitrogen from floodwater and groundwater via denitrification. Evaluating the impacts of different restoration strategies on denitrification can inform more strategic investments into floodplain modifications that improve water quality outcomes. Our research investigates how denitrification rates in floodplains respond to environmental factors that are actionable from an engineering perspective through design and water resources management. We seasonally measured soil denitrification enzyme activity and various environmental characteristics in 4 floodplains with different restoration design and management approaches at the confluence of the Wabash and Tippecanoe Rivers in Indiana, United States. Our results showed that denitrification rates in an agricultural floodplain were significantly lower than in restored floodplains with native vegetation. Certain soil conditions characteristic of floodplain wetlands were associated with higher denitrification, particularly elevated total nitrogen, moisture, silt, and organic matter contents. Vegetation species composition was correlated with denitrification rates. This link may reflect the direct effects of vegetation on soil conditions, such as supplying labile organic carbon, or indirect effects, such as vegetation acting as an indicator of hydrologic regime and land use. Denitrification seasonally varied, peaking in winter when nitrate supply from rivers draining agricultural watersheds in the region is also high. Substrate limitation of soil denitrification enzyme activity was most significant during the summer when overbank flooding, which replenishes soil nitrogen stocks, rarely occurs. Our findings indicate that denitrification capacity will likely be maximized in riverine floodplains that are restored as wetlands with diverse native vegetation and enhanced hydrologic connectivity. Such restoration activities promote higher denitrification rates via elevated moisture, fine sediment deposition, and soil organic matter.

Tippecanoe River, Wabash River↗
USGS2026

Neutron scattering reveals fractionation of natural gas mixtures in unconventional petroleum reservoir pores: Perspectives on energy resource recovery and storage

In unconventional petroleum reservoirs hydrocarbon fluids are hosted by both mineral and organic matter pores. These pores can have diameters that range from microns to less than a single nanometer and, for unconventional reservoirs, there is evidence that small pores ( <20 nm diameter) may constitute a large proportion of the available space. Understanding subsurface volumes and how fluids behave in them can be helpful for predicting hydrocarbon production and storage in the subsurface. One area with knowledge gaps regarding hydrocarbon behavior in small pores is the possibility for mixtures to fractionate (i.e., unmix) based on pore size or pore type. Mixture fractionation as a function of pore size could impact recovery of hydrocarbons, drive compositional shifts during production, and limit fluid storage within candidate reservoirs. To investigate natural gas fractionation in small geologic pores, we applied total neutron scattering to probe methane-ethane mixtures at reservoir pressures (up to ≈30 MPa) and temperature (60°C) within a sample from the Upper Cretaceous Niobrara Formation. Neutron scattering data reveal only minor fractionation occurs between methane and ethane in 20-nm diameter sample mesopores. Increased fractionation is observed for sample micropores, with up to 72% (±1% at 1-sigma) methane found in 2 nm diameter pores following injection of a 50%-50% methane-ethane mixture. These data provide rarely available direct experimental observations of hydrocarbon mixture behavior under nanoconfinement in a sample from an important unconventional petroleum reservoir. Our results are discussed in the context of evaluating hydrocarbon resources in unconventional reservoir meso- and micropores, reconciling observed gas composition changes during production, and more broadly, understanding subsurface pore volumes within an energy storage framework.

Fuel↗
USGS2025

A scientific vision and roadmap for earthquake rupture forecast developments, a USGS perspective

We articulate a scientific vision and roadmap for the development of improved Earthquake Rupture Forecast models, which are one of the two main modeling components used in modern seismic hazard and risk analysis. One primary future objective is to provide fully time-dependent models that include both elastic rebound and spatiotemporal clustering nationwide, which is particularly important for shorter-term hazard and risk considerations (e.g., earthquake insurance products). We also discuss the importance and perennial challenges associated with quantifying epistemic uncertainties, including those associated with deformation-model slip rates, un-quantified sampling errors with respect to off-fault seismicity, and any spatial covariances. The need for more physics-based approaches is also emphasized, as is the benefit of adding model valuation (quantifying usefulness) to our verification and validation protocols. Given the multidisciplinary and system-level nature of this activity, modular design is critical. Future updates will also draw from best-available science by both the United States Geological Survey and the external community. The primary goal of this paper is to highlight plans that guide research and facilitate community engagement with model development, especially with respect to lowering the entry barrier for early career scientists and engineers. The paper is written so readers can focus on the sections that interest them most (see table of contents), with the Introduction and Discussion providing a stand-alone overview and summary.

Bulletin of the Seismological Society of America↗
USGS2025

Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective

Aeromagnetic and magnetotelluric (MT) data are used to better understand the geology and mineral resources near the Stibnite-Yellow Pine mining district in central Idaho. The reduced-to-pole (RTP) transformation of regional-scale aeromagnetic data shows that allochthonous island-arc rocks west of the Salmon River suture are significantly more magnetic than the Laurentian continental rocks east of the suture and that the granitoids of the Idaho batholith have moderate to low magnetization in both early, metaluminous, and late, peraluminous phases. Application of tilt derivative to aeromagnetic data highlights major crustal-scale structures. The 5-km upward continued magnetic data indicate island-arc rocks have deep magnetic sources. The 110-km-long MT profile images resistivity structure to depths around 30 km. At shallow depths, resistivity corresponds to mapped geologic units, with moderate resistivities underlying volcanic and roof-pendant metasedimentary rocks and moderate to high resistivities occurring beneath the Idaho batholith. Crustal-scale moderate resistivities beneath the suture image the results of tectonomagmatic processes that accompanied suturing and translating allochthonous terranes. Low resistivity values beneath and fringing the batholith are derived from metasedimentary rocks that may have served as a melt source and reductant during melt generation and provided metals during later ore formation. In the Stibnite-Yellow Pine mining district, a high-resolution aeromagnetic compilation is shown to correlate with mapped lithologies and mineral deposit-related structures. The RTP transform distinguishes magnetic and nonmagnetic granitoid phases of the Idaho batholith. The tilt derivative highlights metasedimentary rocks, some of which are favorable ore hosts. The Meadow Creek fault hosts the Stibnite and Hangar Flats deposits and is imaged as a magnetic low due to hydrothermal alteration. Reconstructions of magnetic anomaly offsets and orebodies indicate around 3 km of post-95 Ma dextral separation, with some or all of the offset inferred to postdate the main Au mineralization episode (61–66 Ma).

Idaho↗
USGS2026

Mineral chemistry perspective on remobilization of stored magma at Kamakai'a Hills, Southwest Rift Zone of Kilauea, Island of Hawai'i, USA

Differentiated magmas stored in the rift zones of Kīlauea have received more attention in recent years following eruption of andesite during the early phase of 2018 lower East Rift Zone activity. Despite this growing interest, some of the most voluminous eruptions of differentiated rift zone magmas remain poorly studied. One such eruption, and the most voluminous exposed differentiated flow field at Kīlauea, is the Kamakaiʻa Hills. This eruption took place in the Southwest Rift Zone of Kīlauea, a region that is hypothesized to contain a long-lived rift zone reservoir. The Kamakaiʻa Hills flow field encompasses >250 × 10 6 m 3 of basaltic andesite and basalt compositions with a mineral assemblage of orthopyroxene + clinopyroxene + plagioclase during its early ʻaʻā phase and clinopyroxene + plagioclase + olivine during its late pāhoehoe phase. To better understand storage conditions and magma accumulation, this study focuses on major, minor, and trace elements from the mineral assemblage present within the early ʻaʻā and late pāhoehoe phases. The diversity of clinopyroxene and plagioclase compositions within the early ʻaʻā and late pāhoehoe phases, as well as diverse compositions of plagioclase and orthopyroxene within the early ʻaʻā phase, suggest multiple magma bodies and limited pre-eruption magma mixing within the broader Kamakaiʻa Hills reservoir. Oscillatory zoning patterns (particularly in clinopyroxene) imply processes such as recharge events, magma mixing or mingling, or convection within a differentially cooling, chemically stratified reservoir over protracted time intervals, whereas only limited resorbed mineral textures indicate incomplete mixing of heat and chemically distinct magmas during the dike intrusion that triggered the eruption. Mineral-mineral and mineral-melt thermobarometry indicate predominantly shallow (≤2.5 km depth) crustal storage conditions of the cooled, differentiated magma (∼1100 °C and cooler for the basaltic andesites) to hotter temperatures for the basalts (all >1100 °C). Despite the known large standard errors estimated for mineral-melt and mineral-mineral barometry (10s to >100 MPa), the calculated pressures and depths broadly correspond with earthquake swarm depths beneath the Kamakaiʻa Hills, and drill core and fluid inclusion barometry storage depths of differentiated magmas within the lower East Rift Zone. The Kamakaiʻa Hills differentiated magmas have H 2 O contents (∼0.5 wt%, using plagioclase-melt hygrometry) equivalent to typical Kīlauea basalts. Our data and interpretations demonstrate a complex, long-lived rift zone storage system that consisted of multiple magma bodies and was mobilized into eruption through intrusion of a hotter and more primitive summit-derived (uprift) magma.

Hawaii↗
USGS2025

Zircon as a pathfinder to REE mineralization

Carbonatites and alkaline silicate rocks are major primary sources of the rare earth elements (REE) and other critical metals, such as Nb. Despite the economic significance of these rocks, their formation and the processes of REE enrichment are poorly understood. Here, statistical analysis of a global dataset demonstrates that zircon geochemistry is a powerful recorder of REE metallogenesis and a potential pathfinder for REE deposits. Zircons from REE and Nb fertile intrusions lack Eu anomalies and have elevated Gd/Yb and Th/Yb, indicating they crystallised from magmas that originated from deep, oxidised and enriched mantle sources. Complexes with Nb enrichment have low U/Nb, reflecting an enriched mantle source, whereas high U/Nb in REE-only fertile intrusions suggest a subduction-metasomatised mantle source. Machine learning models demonstrate high accuracy in classifying zircon from barren and fertile deposits. Classification of detrital zircons shows that REE-enriched deposits correlate with supercontinent assembly, whereas Nb fertile complexes are associated with supercontinent breakup. This approach offers a new, mineral to global scale, petrologic and exploration tool that enhances understanding of REE metallogenesis.

Geochemical Perspectives Letters↗
USGS2025

Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm

Stream temperature controls a variety of physical and biological processes that affect ecosystems, human health, and economic activities. We used 42 years (1979–2021) of data to predict daily summary statistics of stream temperature across >50,000 stream reaches in the contiguous United States using a recurrent graph convolution network. We comprehensively documented the performance – both across all reaches and by stream type (e.g., reservoir or groundwater influence) – as a baseline for future improvement. The model showed reach-level RMSE of <2 °C with 90 % prediction intervals that contain 90.7 % of observations. We also assessed how the model captured variability in ecologically relevant metrics (e.g., R 2 for annual 7-day maximum = 0.76; R 2 for days exceeding 25 °C = 0.75). This model does not outperform state-of-the-art machine learning efforts (e.g., RMSE ≤1.5 °C) due to a limited input set but does provide the most spatially complete modeling to date to support water availability assessments.

contiguous United States↗
USGS2026

Restoring dryland water cycles for precipitation feedback and climate stability; a review

Drylands across the globe are experiencing intensifying water scarcity, land degradation, and hydroclimatic extremes. This review integrates evidence from multidecadal field studies, hydrologic monitoring, geomorphic and ecological assessments, remote sensing, and land–atmosphere science to evaluate how restoration influences key components of the terrestrial water cycle. Low-tech natural infrastructure in dryland streams (NIDS)—including check dams, leaky weirs, one-rock dams, and gabions—has emerged as a promising but under-synthesized nature-based solution for restoring hydrologic function in these environments. We describe the mechanisms through which these interventions modify runoff detention, infiltration, sediment and alluvial storage, shallow-groundwater recharge, vegetation recovery, and surface-energy partitioning, and we summarize outcomes across diverse dryland settings. Findings consistently show increased water residence time, enhanced soil-moisture storage, expanded riparian vegetation, extended flow duration, and shifts toward greater latent-heat flux—producing localized cooling and strengthened ecohydrological feedbacks. Building on these localized effects, we articulate a hypothesis that links the spatial extent of restoration, the density of NIDS per unit drainage area, and the magnitude of the latent-to-sensible-heat contrast generated by wetter post-rainfall conditions. Specifically, we hypothesize that when NIDS are implemented at densities permitted by topography and across areas large enough to maintain elevated soil moisture after storm events, the resulting increases in latent heat flux, surface cooling, and boundary-layer moistening may enhance moisture convergence and boundary-layer development, potentially increasing the likelihood or stability of convective precipitation, analogous to how reductions in these processes have contributed to regional drought intensification. These land–atmosphere feedbacks remain untested at scale but represent an important research Frontier. By integrating hydrologic, geomorphic, ecological, and atmospheric perspectives, this review provides a comprehensive framework for considering how low-tech, landscape-scale interventions can strengthen watershed resilience and contribute to climate-relevant nature-based solutions.

Arizona↗
USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗
USGS2026

Effects of a low-lipid diet on the gut microbiome and head kidney transcriptome of juvenile Chinook Salmon

Objective Pacific salmon Oncorhynchus spp. reared in production hatcheries are typically fed high-lipid, energy-dense diets to achieve large size and high body condition prior to release. In contrast, juveniles in natural environments tend to consume low-lipid, high-protein diets, and fish reared for research or conservation purposes are sometimes fed diets that are formulated to mimic natural diets and promote wild-like phenotypes. Understanding how these alternative diets affect fish health beyond growth and body condition could ultimately contribute to improving hatchery fish fitness. Methods In this work, we evaluated changes in the fecal microbiome and gene expression of juvenile Chinook Salmon O. tshawytscha on a standard high-lipid hatchery diet versus a low-lipid diet formulated to mimic the nutrition profile of natural-origin fish. To evaluate the time scale at which diet alters the fecal microbiome, we collected longitudinal samples over a 12-week period and switched the diets of a subset of fish twice during the experiment. We used 16S ribosomal RNA gene amplicon sequencing to characterize fecal microbiome differences between fish on the two diets as well as hatchery-reared fish at a production hatchery, hatchery fish that had been captured after release into a stream, and natural-origin, stream-reared fish of similar ages. Additionally, we conducted RNA sequencing on head kidney samples from laboratory-reared fish to evaluate changes in gene expression in this important immune organ. Results We found that the low-lipid diet and the hatchery diet resulted in microbiomes that differed from the microbiome of natural-origin fish and from each other and that diet-driven changes to the microbiome could occur in under 14 d. The low-lipid diet did not result in a microbiome that resembled the microbiome of naturally produced fish. Instead, the low-lipid diet resulted in a microbiome community that was distinct from those of fish reared on the hatchery diet and fish sampled from the wild. The RNA sequencing results indicated differential enrichment of pathways related to immunity, metabolism, and hormone synthesis between fish that were fed the two experimental diets. Conclusions The results suggest that additional environmental factors influence the microbiome more strongly than diet formulation or that the low-lipid diet has a smaller effect on the microbiome than a natural, ­invertebrate-based diet. Given that the gut microbiome and systemic immune function contribute significantly to disease resistance, our findings highlight the importance of understanding how diets fed to fish in captivity may affect fish health beyond growth and body condition metrics.

Journal of Aquatic Animal Health↗