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1,090 records · Page 28Linked to original sources
USGS2026

Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin

More than 50 explosive eruptions occurred from Halemaʻumaʻu at Kīlauea volcano over 17 days from May 11 to 27, 1924. Ballistics weighing as much as 14,000 kg were ejected and most landed within 2 km of the vent. Fine ash made up a major component of the tephra and was dispersed tens of kilometers downwind. Draining of the Halemaʻumaʻu lava lake occurred in late February 1924, with the crater floor eventually subsiding by a further ∼70 m (to ∼180 m below the crater rim) by the time the first explosions took place during the night of May 10–11. The largest explosions occurred on May 17–18 and smaller explosions continued until May 27, at which point Halemaʻumaʻu had more than doubled in width and depth. The explosions generated plumes reaching up to ∼10 km high with ballistics ejected up to 2 km from the crater. Almost 100 years later, we investigate and characterize the preserved tephra deposits within ∼3 km of the 1924 crater rim. Grain size and shape analyses were performed on 202 samples collected from 34 tephra profiles using dynamic image analysis, with a subset of layers from nine tephra profiles used for componentry (200 grains per layer in the 0.5–1 mm size fraction). Additionally, we characterize the average diameters (using the five largest clasts) at 216 locations and measure the average diameters of 2291 ballistics (largest per ∼100 m 2 area). Physical descriptions from fieldwork and grain size distributions were used to subdivide the tephra layers into five lithofacies: coarse homogeneous, fine homogenous, red ash, accretionary lapilli-bearing, and finely laminated. Grain size versus shape data show a range of values that demonstrate most grains are dense, smooth, and equant, in alignment with lithic clasts dominating the tephra componentry. The fine grained and accretionary lapilli-bearing nature of some of these lithofacies confirms that water influenced the style of the explosions. However, we also note juvenile clasts within many of the tephra layers, indicating that many of the layers were formed during phreatomagmatic explosions (sensu stricto), despite the eruptive mechanism being dominantly phreatic. Juvenile clasts are more abundant higher in the tephra profiles, suggesting that juvenile magma was more involved later in the explosive sequence. Thermal and hydrologic modeling indicate that groundwater inflow into a short-lived, small-diameter volcanic conduit (10-m to 120-m-diameter used for modeling) during the 78–85 days preceding the first explosion provides a physically plausible mechanism for this eruptive sequence.

Hawaii↗
USGS2026

Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis)

Crayfish are critical functional components of aquatic ecosystems. Previous research has documented adverse effects of mineral extraction on crayfish. Here, we characterize potential risks of mining-derived waterborne nickel (Ni) to crayfish by documenting the effects of dissolved Ni on growth and food consumption of juvenile virile crayfish ( Faxonius virilis) in a 28-day chronic laboratory exposure. Nominal Ni concentrations ranged from 31.25 to 500 micrograms per liter (µg/L; pH = 7.96 ± 0.20, hardness = 150 ± 1 milligrams per liter as calcium carbonate). Crayfish survival, carapace length, and wet weight were measured. After 28 days of exposure, a 24-h feeding trial was performed to determine differences in food consumption. During the growth trial, 99% of crayfish survived. Change in wet weight and final wet weight were the most sensitive endpoints, with 20% effect concentrations of 24.8 and 22.6 µg/L Ni, respectively. Crayfish exposed to an average of 438 µg/L Ni consumed 41% less, and weighed 65.1% less, than control crayfish. These results suggest chronic, sublethal exposure to waterborne Ni may have negative effects on crayfish growth. Reduced growth and consumption rates in crayfish could have wide-ranging consequences throughout aquatic ecosystems since crayfish are consumers, prey, keystone trophic regulators, and ecosystem engineers. Finally, these results could inform bioenergetics and may be coupled with population models to predict potential changes in population sizes of native and invasive crayfishes.

Ecotoxicology↗
USGS2026

Wind River subbasin restoration: Annual report of U.S. Geological Survey activities January 2024 through December 2024

We sampled juvenile wild Oncorhynchus mykiss (Steelhead Trout) in headwater streams of the Wind River, Washington, to characterize population attributes and investigate life-history metrics, particularly migratory patterns, and early life-stage survival. Additionally, this sampling provides an index of abundance of non-native Brook Trout Salvelinus confluentus . We used passive integrated transponder (PIT) tagging and a series of instream PIT-tag interrogation systems (PTISs) to track juveniles and adults. The Wind River subbasin is considered a wild Steelhead refuge by Washington Department of Fish and Wildlife (WDFW). No hatchery Steelhead Trout have been released in the Wind River subbasin since 1997, and hatchery adults are estimated at less than one percent of spawners in most years. Over 25 years of Steelhead Trout status and trend monitoring and research in the subbasin is contributing to understanding of population response to numerous restoration actions in the subbasin, including removal of Hemlock Dam from Trout Creek in 2009, which had an inadequate adult ladder and contributed to increased water temperatures, to near lethal levels for salmonids. Data from our study, and companion work by WDFW, are contributing to the Columbia Basin Fish and Wildlife Program (2009) Research, Monitoring, and Evaluation (RM&E) Strategy of Fish Population Status Monitoring. Specifically, this work addresses the sub-strategies of 1) Assessing the Status and Trends of Diversity of Natural Origin Fish Populations and Uncertainties Research regarding differing life histories of a wild Steelhead Trout population, 2) Assessing the Status and Trend of Adult Natural Origin Fish Populations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions Relative to Environmental, Physical, or Biological Performance Objectives. During summer and fall 2024, we PIT-tagged 2,075 Steelhead Trout parr (age-0 and age-1), in the Trout Creek and upper Wind River watersheds. Age-0 and age-1 parr were at high abundance due to strong spawner numbers in 2023 and 2024 (Estimate of 932 in 2023; and a moderate number of spawners in 2024 though an estimate is not available at this time; 24-year median = 619; Charlie Cochran, WDFW Fish Biologist, personal commun., 2025). An additional 100 parr (age-0 and age-2 or older) were tagged to provide fish for estimating detection efficiencies at PTISs. Steelhead Trout parr were recaptured and detected through repeat headwater sampling, smolt trapping, instream PTISs and Columbia River mainstem PIT-tag detection. We maintained and upgraded six instream PTISs to detect PIT-tagged Steelhead Trout parr, smolts, and adults, providing data for population assessments, and life-cycle research. Detection data from PIT-tagged adult Steelhead Trout at our four primary PTISs allow assessment of adult escapement to tributary watersheds within the Wind River subbasin. Most adult Steelhead detected were tagged by WDFW at an adult trap in the lower Wind River and some as smolts at screw traps. Adult Steelhead Trout detection efficiency estimates at our primary PTIS in Trout Creek have been greater than 99 percent during eight of the past ten years and have exceeded 97% at our primary PTIS in the Wind River during nine of the past ten years. Adult escapement estimates to tributary watersheds are helping evaluate the efficacy of the 2009 removal of Hemlock Dam from rkm 2.0 of Trout Creek. Detections at the instream PTISs have shown trends of age-0 and age-1 Steelhead Trout parr emigration from natal areas during summer and fall, in addition to the expected movement of parr and smolts in spring. Our data suggest that most fish from a cohort that migrate downstream will do so at age-1 for additional rearing in the subbasin. We have estimated that from 15% to 56% of parr tagged as age-0 fish in headwater areas make downstream migrations at age-1 for additional rearing (median = 29%). We have estimated that from 1% to 27% of Steelhead Trout parr, tagged as age-1 fish, make downstream migrations during fall (median = 3.5%): this is especially pronounced in the upper Wind River portion of the watershed (median 10%). These findings raise questions about parr rearing habitat and whether migrations are density- or habitat-quality driven, and answers to such questions are long-term goals of this study as active and passive habitat restoration occurs. Repeat sampling at sites in the subbasin within and between years has enabled assessment of juvenile Steelhead Trout growth patterns. Growth rates (relative change in weight) of age-0 PIT-tagged parr during summer have been similar across the subbasin, though slightly lower in the Trout Creek watershed (Trout Creek sites, 0.57 - 1.25%/day, Wind River sites = 0.94 – 2.48%/day). Summer growth rates have been lower for age-1 parr in the Trout Creek watershed than the upper Wind River watershed (Trout Creek sites, = 0.03 - 0.14%/day, Wind River sites = 0.05 – 0.19%/day). Yearly relative growth was similar across the subbasin for both age-0 and age-1 tagged parr. During 2024 range of mean daily relative change in weight from the previous year for age-0 tagged fish was: Trout Creek sites = 0.96 – 1.41%/day, Wind River sites = 0.80 – 1.30 %/day; and for age1 tagged fish was: Trout Creek sites = 0.37 - 0.50 %/day, Wind River sites = no age-1 tagged recaptures. Non-native Brook Trout are present in the subbasin, chiefly the Trout Creek watershed. Mean percent-of-catch that is Brook Trout, at four sample sites in Trout Creek, has declined from the period 1998 – 2003 to the period 2011 – 2024 (range of decrease = 19 - 82%). Percent-of-catch (of 64 samples, 52 < 10%; 3 > 20%) and number of Brook Trout at the Trout Creek sites from 2011 through 2024, though variable, have generally declined. Habitat restoration evaluation efforts are critical to ensure efficient use of money and resources but require long-term monitoring of population metrics. Detailed viable salmonid population and life-history data, such as that provided by PIT-tagging and instream PTIS networks inform fisheries policy and management and enable assessment of long-term effects of habitat restoration actions such as the removal of Hemlock Dam on Trout Creek and proposed major instream habitat restoration in the upper Wind River.

Washington↗
USGS2026

Core microbiomes as a potential fingerprinting method of Western USA dust sources

Introduction: Changing frequency and intensity of dust emissions impacts ecosystems and human health. Dust carries microbes, nutrients, heavy metals, and other materials that may change environmental biogeochemistry at deposition sites. Identifying dust sources provides key information on where and when mitigation strategies should be employed. However, commonly used geochemical or isotopic tracers are often not capable of distinguishing between geographic regions. Methods: We explored whether soil bacterial communities may provide distinct fingerprints of dust sources in the western United States. We identified bacterial core communities of dust from ten locations monitored by the National Wind Erosion Research Network (NWERN) with varied land use (cropland, rangeland, and playa), and compared communities to location, soil, and regional characteristics. Samples were collected monthly from Modified Wilson and Cooke (MWAC) samplers, composited by season (spring, summer, and fall), and analyzed using 16S rRNA sequencing. Results: We found distinct bacterial core communities that reflected dust source characteristics. In order of importance, precipitation levels ( p = 0.0001), location ( p = 0.0001), soil texture ( p = 0.0001), seasonality ( p = 0.0001), and elevation (p = 0.0002) were correlated with bacterial community composition. Discussion: Distinct bacterial core communities were associated with site characteristics such as biocrusts, playas, and military base proximity. Our results suggest that the use of core microbiomes may offer a fingerprinting method to identify dust source regions.

Colorado, Nevada, New Mexico, North Dakota, Oklaho↗
USGS2025

Understanding market sensitivity: Estimation of supply and demand elasticities for non-fuel minerals

In today’s rapidly changing economic landscape, understanding market responsiveness to price changes and the factors influencing commodity prices has become increasingly relevant. Price elasticities serve as indicators of how variations in market conditions affect supply and demand, providing insights into the sensitivity of commodity markets to price fluctuations. This paper presents a comprehensive analysis of price elasticities of supply and demand for 74 non-fuel mineral commodities including precious metals, base metals, minor metals, and industrial minerals that are utilized across various industries. We employ various econometric techniques, including fixed effects models for panel data and two-stage dynamic ordinary least squares (2S-DOLS) alongside autoregressive distributed lag (ARDL) models for time series analysis, to derive robust estimates of price elasticities. Our findings reveal variability in elasticities among different commodities and indicate that all studied mineral commodities exhibit price inelastic supply and demand in the short run, which we define as one year for the purposes of our analysis, given that the data is all annual. This research provides original estimates of price responsiveness for a wide range of commodities that have not been previously addressed in the literature, thereby enhancing the understanding of market dynamics in the mineral sector. Given that price elasticities can be influenced by factors such as market structure, technological advancements, mining costs, and industry-specific demand drivers, we use variables that serve as proxies for these factors.

Mineral Economics↗
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↗
USGS2025

A regional model comparison between MODPATH and MT3D of groundwater travel time distributions

Groundwater quality changes in wells and streams lag behind changes to land use due to groundwater travel times. Two contaminant transport methods were compared to assess differences in their simulated travel time distributions (TTDs) to streams and wells in the Wisconsin Central Sands. MODPATH simulates advective groundwater flow with particle tracking, while MT3D simulates age-mass using a finite difference solution without dispersion to allow for direct comparison of the two methods. MODPATH appropriately simulates groundwater TTDs from the water table to surface discharge but is subject to inaccuracies at weak-sink well cells due to the flow-model grid discretization and imprecise location of well discharge within well cells. MT3D better represents weak-sink well cells since it removes mass in proportion to the prescribed pumping rate, although travel time within well cells is neglected. Conversely, MT3D's treatment of surface water boundary cells is not as accurate as MODPATH because mass should be removed from the water table rather than the full cell volume. MT3D simulations of TTDs can also be confounded by the instantaneous vertical distribution of mass introduced throughout recharge cells instead of at the water table, which initiates mass along deeper flow paths. We evaluated 9 MODPATH and 13 MT3D implementations, generating differences in median travel times of up to 18 years. Both methods have strengths and weaknesses, with MT3D better representing weak-sink well cell behavior and MODPATH better representing surficial recharge and discharge. The effect of these characteristics on simulated TTDs, along with ideas for ameliorating method weaknesses, is discussed.

Wisconsin↗
USGS2024

The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates

LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.

Fire↗
USGS2026

Potential impacts of groundwater pumping on stream temperature are greatest in streams with substantial cold groundwater inflows

Groundwater pumping-induced reductions in streamflow (known as ‘streamflow depletion’) have been documented worldwide, but potential impacts of streamflow depletion on stream temperature are not well understood. Here, we use two types of models to identify potential impacts of pumping on stream temperature across the conterminous United States (CONUS) to determine which aspects of a stream's annual thermograph (thermal signatures) can be used to monitor and manage streamflow depletion impacts on stream temperature. We used long-term streamflow and stream temperature data from 30 streamgages across CONUS and surrogate models of streamflow depletion to analyse potential stream temperature impacts at each site. We compared two different stream temperature modelling approaches: (i) a process-based energy balance model and (ii) statistical regression models based on air temperature and stream discharge. We calculated a suite of thermal signatures under depleted and non-depleted conditions for each stream and found that maximum annual 7-day temperature and annual temperature range are potentially the most sensitive to streamflow depletion, with potential changes of at least 2°C at > 70% of the sites when using the process-based model. We also found that the regression-based models predicted much less sensitivity of stream temperature to streamflow depletion than the process-based model. This work provides an initial evaluation and sensitivity analysis of the potential impacts of streamflow depletion on stream temperature. We demonstrate that stream temperature may be most sensitive to pumping in streams with a high proportion of flow sourced from relatively cold groundwater inputs, and that regression-based stream temperature models may underpredict stream temperature changes caused by streamflow depletion.

conterminous United States↗
USGS2026

The Sedimentary Geochemistry and Paleoenvironments Project Phase 2 data release: An open data resource for the study of Earth's environmental history

Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.

Chemical Geology↗
USGS2025

Spatio-temporal evolution of distributed volcanic fields, case studies—Sierra Chichinautzin and Michoacán-Guanajuato, México

An analysis of 1,375 volcanoes in the Michoacán-Guanajuato (1,148 volcanoes in a 26,200 square-kilometer area) and Sierra Chichinautzin (227 volcanoes in a 3,500 square-kilometer area) volcanic fields in central Mexico identified patterns in the spatial and temporal distribution of past eruptions. A cluster agglomerative hierarchical method and kernel analysis confirmed that the Michoacán-Guanajuato volcanic field comprises four volcanic fields (Valle de Santiago, Uruapan, Apatzingán, and Pátzcuaro volcanic fields) controlled by different fault systems, indicating that it is not a single volcanic field but rather a group of volcanic fields (a “superfield”), each of which has distinct characteristics. In the Sierra Chichinautzin volcanic field, well-constrained isotopic ages were used to build a model of how the spatial distribution of the eruptions has changed over time. Two new 40Ar/39Ar ages from a locally recognized volcanic feature near the town of El Cantil, herein called El Cantil volcano (1,537±17 kilo-annum [ka]) and the volcanic feature at Cerro el Elefante (herein called El Elefante dome) (1,485±92 ka) belong to the oldest volcanic group identified in the Sierra Chichinautzin volcanic field, confirming the timing of the beginning of monogenetic volcanism in the region. Based on the volcanic groups identified in the Sierra Chichinautzin volcanic field, the youngest volcanism (less than 35 ka) is found only in the central-western sector of the field. Principal component analysis determined the directional trends of feeder dikes only for vents <10 ka in the Sierra Chichinautzin volcanic field. Possible magma migration paths through the crust were identified using seismic data from both volcanic fields using an earthquake catalog from 1973 to 2023, which includes 9,016 earthquakes in the Michoacán-Guanajuato volcanic field and 841 in the Sierra Chichinautzin volcanic field. The spatial distribution of the hypocenters does not highlight any trend that could be associated with superficial movement of magma in the Sierra Chichinautzin volcanic field. In the Michoacán-Guanajuato volcanic field, however, eight seismic swarms since 1997 have been detected. These swarms are interpreted to result from ascending magma. Strengthening monitoring systems and reinforcing mitigation measures to address volcanic hazards and risk are important means of preparing for future eruptions in both regions. Analysis such as those herein provide insights as to where an eruption might occur and may help mitigate volcanic hazards.

Michoacán-Guanajuato, Sierra Chichinautzin↗
USGS2025

Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy

The Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked by section 7002 (“Mineral Security”) of title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Congress) with reviewing and revising the methodology used to evaluate mineral commodity supply risk and the U.S. List of Critical Minerals (LCM) no less than every 3 years. Following two previous LCM assessments, this analysis represents the latest technical input for evaluating each mineral commodity’s supply risk and determining their recommended status on the LCM. We evaluated mineral commodity supply risk using two criteria: (1) an economic effects assessment that quantified the potential effects of various trade disruption scenarios on the U.S. economy, and (2) an examination of whether the mineral commodity’s U.S. supply chain relied on a sole domestic producer that represented a single point of failure. For the first criterion, postdisruption equilibrium quantities and prices for each mineral commodity were calculated based on their price elasticities of supply and demand and the availability of excess production capacity for each yearlong foreign trade disruption scenario. Subsequently, a nonlinear optimization routine was used with detailed economic input-output tables to estimate the potential economic effects on the U.S. economy of over 1,200 scenarios for 84 mineral commodities. After accounting for the probability of each scenario’s occurrence, the overall results are presented in terms of changes in U.S. gross domestic product (GDP) by individual industry and the economy overall. The results, which ranged from a net decrease in U.S. GDP of nearly $4.5 billion to a net increase of $33 million, largely reflect U.S. import dependency and world production concentration. Using the Jenks natural breaks optimization method, a statistical classification technique, we categorized the mineral commodities into several classes based on this overall risk quantification. Mineral commodities with annualized probability-weighted net decreases in U.S. GDP greater than $2 million were recommended for inclusion on the LCM. If a mineral commodity did not meet the threshold for inclusion on the LCM under the first criterion, its domestic supply chain was examined under the second criterion, which recommended a mineral commodity for inclusion on the LCM if there was only a single domestic producer. Ultimately, the two criteria resulted in the recommendation of the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the LCM. By using an economic effects assessment, the results of this analysis provide a prioritization that can also be compared directly against other risk analyses and the cost of various risk mitigation strategies.

Open-File Report↗
USGS2025

False positives in the identification of dynamic earthquake triggering

Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with global M ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial-temporal windows in Southern California tested in DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 , thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023, https://doi.org/10.1029/2023jb026487 ), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor-Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance.

JGR Solid Earth↗
USGS2025

Cascading land surface hazards as a nexus in the Earth system

Earth’s surface is sculpted by numerous processes that move sediment, ranging from gradual and benign to abrupt and catastrophic. Although infrequent, high-magnitude sediment mobilization events can be hazardous to people and infrastructure, leaving topographic imprints on the landscape and remarkable narratives in the historical record. Hazardous events such as fires, storms, and earthquakes accelerate erosion and sediment transport, increasing landscape sensitivity to subsequent perturbations, thus forming a cascading hazard. Although the redistribution of sediment across Earth’s landscape can result in higher risks to vulnerable populations, cascading processes are commonly unaccounted for in hazard assessments. Cascading hazards can occur almost immediately after triggering events, such as coseismic landslides, or over months, years, or even decades after an initial perturbation, such as debris flows after wildfires or flooding in channels alluviated by volcanic debris. Sediment cascades span Earth’s surface, from mountaintops to river valleys, where erosion, deposition, and aggradation can lead to a myriad of hazardous processes, including decreased river conveyance capacity, which increases the likelihood of downstream flooding. An improved understanding of the magnitude, frequency, and persistence of cascading hazards is critical given the rapid changes in the frequency and severity of storms, fires, sea-level change, and cryospheric melting, as well as the expansion of high-population-density urban footprints in regions susceptible to solid Earth hazards. Understanding the full consequences and underlying physics of Earth’s cascading land surface hazards can help minimize future human and economic losses.

California↗
USGS2026

Regreening, restoring, and reconnecting a southwestern wetland ecosystem – the Zeedyk wetland

Alluvial wetland ecosystems are vital as biodiversity hotspots but are increasingly threatened by anthropogenic stressors and drought. These pressures are especially acute in arid and semi-arid regions, where eco-hydrologic connectivity is fragile and recovery is slow. This study quantifies the efficacy of nature-based solutions, particularly the ‘Zeedyk approach,’ which employs low-tech Natural Infrastructure in Dryland Streams (NIDS)—including rock detention structures—to slow surface water, raise groundwater tables, and restore wetland function at a spring-fed wetland in Cebolla Canyon, New Mexico, U.S.A. Our results depict a Restoration Feedback Loop that captures stages of change from a healthy wetland in 1935, altered by 20th-century agriculture and grazing, to the re-establishment of the historical flow regime by 2024 documented through an 89-year archive of aerial imagery (1935–2024). By the end of our study period, the Spring-Fed Wetland had expanded by roughly 229% of the original 1935 area, to 4.13 ha. Using 40 years of satellite data, we assess changes in vegetation and hydrology with remote sensing indices. Spatial and temporal analyses reveal significant increases in vegetation greenness and wetness, particularly in an Expanded Wetland subregion, which exhibited ∼3.5x higher wetness and ∼1.5x higher greenness trends compared to adjacent areas. Monthly metrics highlight seasonal variability, with increases in greenness linked to monsoonal rainfall and lateral water redistribution, indicating that restoration impacts extend beyond the primary wetland. This study demonstrates the utility of cloud-based platforms like Google Earth Engine and USGS EarthExplorer for long-term monitoring of wetland restoration, while quantifying the efficacy of the ‘Zeedyk approach’ and demonstrating its potential as a scalable method to restore and conserve wetland meadows in other arid and semi-arid landscapes.

New Mexico↗
USGS2026

Water-withdrawal and groundwater-level fluctuations, physical and infiltration characteristics of Ohio River sediment, and isotope-based estimates of water sources relative to a riverbank filtration system in an alluvial aquifer, Louisville, Kentucky, 2000–20

The U.S. Geological Survey and the Louisville Water Company, from 2000 to 2020, cooperatively investigated physical and hydrologic conditions in the Ohio River alluvial aquifer and adjacent riverbed sediments in the northeast part of Louisville, Kentucky, to increase knowledge of processes affecting water sources to collector wells during operation of a riverbank filtration system (RBF). The RBF, in 2020, included an initial collector well (CW1) completed in 1999 and a tunnel and collector well system (TCWS) composed of four collector wells (CW2–CW5) completed in late 2010 that were connected by a tunnel that routed water to a pumping station and a treatment plant. Daily mean water-withdrawal rates typically ranged from about 10.4 to 20.7 million gallons per day (Mgal/d) from 2005 to 2007, then were cyclic from 2008 to 2010 and ranged from as low as about 9 to 13 Mgal/d in winter-spring months up to about 19 to 20 Mgal/d in summer-autumn months. From 2011 through 2017, peak daily mean water-withdrawal rates from CW2–CW5 fluctuated between winter-spring lows of about 20–30 Mgal/d to summer-autumn peak rates of about 41.6 Mgal/d in 2013 to about 48.2 Mgal/d in 2012. From 2017 to 2020, TCWS peak daily mean water-withdrawal rates decreased from about 45.7 Mgal/d in 2017 to about 37.5 Mgal/d in 2020 and peak daily mean rates from CW1 ranged from about 20.7 Mgal/d in 2020 to about 21.6 Mgal/d in 2018. Periods in 2019–20 with tunnel pumping station daily mean water-withdrawal rates smaller than about 30 Mgal/d had generally stable water levels in CW2 and indicated the sustainable yield of the TCWS collector wells under the prevailing hydrologic conditions. Drawdown during July–August of 2008 and 2009 was associated with CW1, the sole operating collector well. Groundwater-flow directions outside the CW1 cone of depression during July–August of 2008 and 2009 were from areas near the alluvial valley margin toward the Ohio River and in 2009 toward Harrods Creek. Collector wells CW2 through CW5 derived water during 2011–19 surveys from surface-water infiltration, as indicated by drawdown that extended beneath the Ohio River and Harrods Creek. Increases in drawdown toward the alluvial valley margins in July–August of 2013 and 2015, compared with July 2011, indicated less available recharge from those flow directions and decreased yield of groundwater from the aquifer after progressively longer TCWS water withdrawals. Drawdown at CW2–CW5 and at observation wells between them lessened in October 2019 and indicated that onshore groundwater levels can recover when collector well withdrawals decrease. Overlapping cones of depression in 2011–15 potentiometric surfaces centered around CW2, CW3, CW4, and CW5, and drawdown along divides between those wells indicated well interference between collector wells. Well-interference effects increased during 2013 and 2015 survey periods, despite decreased water-withdrawal rates compared with July 2011, and expanded to include CW1 when its use resumed. Groundwater-level fluctuations in observation wells near the Ohio River were consistent with gradual depletion of groundwater yield during tunnel pumping station operation at river elevations of about 420 feet above the National Geodetic Vertical Datum of 1929 (NGVD 29) and enhanced recharge of the aquifer when river elevations were above flood stage of about 430 feet above NGVD 29. Groundwater-level declines in observation wells near the Ohio River were most apparent in summer and some autumn months between 2012 and 2017 during periods when tunnel pumping station mean daily water-withdrawal rates were about 35 Mgal/d or more. Periods of relatively stable groundwater levels during 2019–20 in observation wells between CW2–CW5, when tunnel pumping station water-withdrawal rates were about 30–33 Mgal/d or less, also indicated that the prevailing sustainable yield was about 30 Mgal/d or less. Wells associated with CW3 and CW4 had the largest increases in slopes of best-fit lines relating water-level difference to water-withdrawal rate between 2012 and 2020, an indication of decreased efficiencies of those wells to supply water or of changes in groundwater yield around the well. Increased slopes of best-fit lines relating water-level difference to water-withdrawal rate from 2019 to 2020, when groundwater levels were otherwise relatively stable, also indicated that the specific capacity of one or more TCWS collector wells may have declined during that period. Riverbed surface elevation, roughness, and hardness changes between hydroacoustic surveys indicated active accretion and erosion of bed sediment offshore from the riverbank filtration system in 2002–4. Riverbed hydraulic conductivity computed from 2013 to 2015 in tests at 11 sites ranged from 0.2 to 230 feet per day. Ten temporary piezometer sites with adjacent operating collector wells had drawdowns that ranged from about 4 to 11.7 feet and hammer blows greater than or equal to 49 counts, which indicated a relatively great density of alluvial sediments and the potential for diminished riverbed infiltration rates. Contributions of Ohio River infiltration to collector wells estimated from deuterium and oxygen-18 isotopic ratios in representative Ohio River and groundwater samples were considerably larger in warmer months than cooler months and ranged from 80–90 percent in CW1–CW5 in May 2020 to 100 percent in May 2019 at CW2, CW4, and CW5. Groundwater contributions to water withdrawals by collector wells increased in cooler autumn months and ranged from 40 percent at CW3 and CW5 in November 2020 to 70 percent at CW2, CW4, and CW5 in November–December 2019. November 2019 and November 2020 isotopic compositions of water from the collector wells had enriched deuterium and oxygen-18 isotopic ratios consistent with mixtures of evaporation-modified water from the Ohio River and meteoric-origin groundwater.

Indiana, Kentucky↗
USGS2024

The 2023 Alaska National Seismic Hazard Model

US Geological Survey (USGS) National Seismic Hazard Models (NSHMs) are used extensively for seismic design regulations in the United States and earthquake scenario development, as well as risk assessment and mitigation for both buildings and infrastructure. This 2023 update of the long-term, time-independent Alaska NSHM includes substantial changes to both the earthquake rupture forecast (ERF) and ground motion models (GMMs). The ERF includes numerous additions to the finite-fault model, considers two deformation models, and introduces updated declustering and smoothing algorithms in the gridded background seismicity model. For the Alaska–Aleutian subduction zone, megathrust earthquakes occur on an updated structural and segmentation model, and the moment magnitude (M) 8+ rupture and rate model include a logic tree branch that considers slip rates derived from geodetic models of interface coupling. The megathrust model considers multiple models of down-dip width, and magnitudes are computed using newly developed scaling relations. For subduction intraslab events and subduction interface events with M < 7, the 2023 update uses a smoothed seismicity model with rupture depths derived from Slab2. The 2023 model updates GMMs in all tectonic settings using the recently published Next Generation Attenuation Subduction (NGA-Sub) GMMs for subduction interface and intraslab events, and the NGA-West2 GMMs for active crustal settings. Collectively, additions and updates to the Alaska NSHM result in hazard increases across most of south-central Alaska relative to the previous model, published in 2007. These changes are primarily due to the adoption of updated rate models for the large-magnitude interface events and the NGA-Sub GMMs that have much higher aleatory variability (sigma), consistent with global observations, and that include models of epistemic uncertainty.

Alaska↗
USGS2025

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↗