SEARCH · Search USGS

Results for “Philosophical Transactions of the Royal Society B: Biological Sciences”

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

SourceResearch connectionFrom yearThrough year

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

1,689 records · Page 4Linked to original sources

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↗

USGS2024

Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee

The Little Sequatchie River and Pryor Cove Branch, in southern Tennessee, drain the eastern escarpment of the Cumberland Plateau to the Sequatchie River near the southern end of the Sequatchie Valley. The Little Sequatchie River is the largest tributary to the Sequatchie River by drainage area, covering over 120 square miles. The hydrology of the two drainage areas has been largely altered by karst processes, which has caused the majority of the streams to sink at the contact between the Mississippian Pennington Formation and the underlying Mississippian Bangor Limestone. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and Tennessee Department of Environment and Conservation, initiated a study in 2021 to map the karst groundwater pathways in both watersheds in order to delineate recharge areas for several springs. One of these springs, Sequatchie Cave, represents a significant habitat for two Species of Greatest Conservation Need, the Glyphopsyche sequatchie (Sequatchie caddisfly) and the federally endangered Marstonia ogmorhaphe (royal marstonia). Springs and springflow-dominated streams in the Little Sequatchie River valley and Pryor Cove also provide water for agricultural practices and serve as a drinking water source for nearby communities. During the study, a total of 25 dye injections were conducted over eight rounds from January 2022 through March 2023. Dye traces from these injections helped to delineate recharge areas for six major springs, ranging from 7.3 to 65.2 square miles in area. The majority of the dye traces remained subsurface (from sinkpoint to recovery site) for long distances, with karst groundwater travelling nearly 8 miles before resurfacing. The dye traces also had rapid traveltimes, often travelling hundreds to thousands of feet per hour. The goal of this project was to provide scientific data related to karst groundwater pathways and spring recharge areas to aid State and Federal agencies in making informed decisions to protect and preserve this unique and vulnerable karst system.

Tennessee↗

USGS2026

Recent scientific contributions by the U.S. Geological Survey in the San Francisco Bay and Sacramento–San Joaquin Delta Estuary

Introduction The San Francisco Bay and Sacramento–San Joaquin Delta Estuary (hereafter, Bay-Delta) is the largest estuary on the West Coast of the United States. The Bay-Delta covers more than 1,600 square miles and drains a watershed of more than 75,000 square miles, which is greater than 40 percent of California. The region surrounding the Bay-Delta is home to about 10 million people, and its habitats (fig. 1) support more than 800 plant and animal species. The waterways of the Bay-Delta are the central hub of California’s extensive freshwater delivery system, supplying water to more than 27 million Californians and 4 million acres of farmland in the Central Valley. The U.S. Geological Survey (USGS) is the primary science agency of the U.S. Department of the Interior, providing a broad range of Earth, water, biological, and mapping data and expertise to inform natural resource management across the country. This fact sheet focuses on research conducted by the USGS in the Bay-Delta region, mostly within the past 5 years. The fact sheet is organized across five major themes: water flow and water quality, fish and wildlife, wetland restoration, invasive species, and hazards. In each of these areas, the USGS works closely with Federal, State, and local agencies; academia; and non-governmental organizations to provide objective, evidence-based science. The data and knowledge gained from USGS research and monitoring are publicly available and are routinely used by agencies, including the U.S. Bureau of Reclamation, U.S. Army Corps of Engineers, U.S. Fish and Wildlife Service, California Department of Water Resources, California Department of Fish and Wildlife, California State Water Resources Control Board, Delta Stewardship Council, and many additional organizations and stakeholders to inform management of the Bay-Delta region and its resources.

California↗

USGS2025

Four-band image mosaic of the Colorado River Corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition

In May 2021, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four spectral bands (red, band 1; green, band 2; blue, band 3; and near infrared, band 4) with a ground resolution of 20 centimeters, are available as 16-bit unsigned-integer GeoTIFF files in Sankey and others (2024) (available online at https://doi.org/10.5066/P9BBGN6G ). The image files are projected in the State Plane Coordinate System, using the central Arizona zone (202) with the North American Datum of 1983 National Adjustment of 2011. The assessed spatial accuracy for these data is based on 47 ground-control points that were independent from the ground-control points used by the contractor for aerotriangulation and is reported at the 95-percent confidence level as 0.514 meter (m) and a root mean square error of 0.297 m. The intended uses of this dataset are primarily in support of scientific research and monitoring applications. Examples of these applications include high-resolution spatial and temporal change detection of the river channel, geomorphic landforms, riparian vegetation, and backwater and nearshore habitat, as well as other ecosystem-wide mapping. These imagery data also serve as reference material for field science mission planning, as base data for field data collection including community science activities, and as a highly detailed guide for technical boat operation during science activities such as reconnaissance for nighttime missions and navigating rapids during low flows.

Arizona, Nevada, Utah↗

USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗

USGS2025

A geospatial analysis of water-quality threats from orphan wells in principal and secondary aquifers of the United States

Throughout the history of oil and gas production in the United States, millions of wells have been drilled for exploration and energy production. Hundreds of thousands of unplugged wells are no longer actively producing and are currently under orphan status, with no responsible party obligated for plugging. Orphan wells can pose threats to water resources by providing pathways for contaminants such as hydrocarbons and brines to migrate into water-supply aquifers. In this study, we investigate the potential threats to groundwater resources posed by orphan wells at the national scale. Water-quality data is extremely sparse in relation to orphan wells nationally and may not be suitable for identifying contamination from oil and gas development. We used geospatial and statistical methods to evaluate which principal and secondary aquifer systems may be most susceptible to contamination from orphan wells. Analysis involved three sets of susceptibility factors including: 1) factors related to the number and density of orphan wells; 2) factors that can threaten well integrity and contribute to transport of contaminants; and 3) factors related to groundwater withdrawal rates and the affected populations/communities in the event of water quality disturbances. From a dataset of 117,672 documented orphan wells, 64,203 fall within a principal aquifer system, while the remainder fall within a secondary aquifer system. By assessing the combination of well integrity and hydrogeologic factors within these aquifer systems, five groupings of principal aquifers were identified, where groups ranged from aquifer systems with high numbers of orphan wells, multiple well integrity threats and high withdrawals, to aquifers with a relatively low number of orphan wells, limited well integrity threats and minimal water use. Three regions of the country emerge containing aquifers with higher susceptibility to contamination from orphan oil and gas wells. These regions include 1) The Appalachian Basin (including the Pennsylvanian Aquifer System), 2) The Gulf Coast Aquifers (including the Coastal Lowlands Aquifer system) and 3) The California Aquifers (including the California Coastal Basin Aquifer system). This work is the first multivariate geospatial investigation of orphan wells and groundwater resources on a national scale, and sheds light on which aquifers are most susceptible to groundwater contamination from orphan wells.

Science of the Total Environment↗

USGS2024

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I 15 , the model generally under-forecasted the inundation area. The observed peak I 15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I 15 than observed. Using these I 15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.

California↗

USGS2024

Streamflow depletion caused by groundwater pumping: Fundamental research priorities for management-relevant science

Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.

Water Resource Research↗

USGS2024

Geological context and significance of the clay-sulfate transition region in Mount Sharp, Gale crater, Mars: An integrated assessment based on orbiter and rover data

On Mars, phyllosilicate (“clay”) minerals are often associated with older terrains, and sulfate minerals are associated with younger terrains, and this dichotomy is taken as evidence that Mars’ surface dried up over time. Therefore, in situ investigation of the Mount Sharp strata in Gale crater, which record a shift from dominantly clay-bearing to sulfate-bearing minerals, as seen in visible−near-infrared orbital reflectance spectra, is a key science objective for the Mars Science Laboratory (MSL) Curiosity rover mission. Here, we present regional (orbiter-based) and in situ (rover-based) evidence for a low-angle erosional unconformity that separates the lacustrine and marginal lacustrine deposits of the Carolyn Shoemaker formation from the dominantly eolian deposits of the lower Mirador formation within the orbitally defined clay-sulfate transition region. The up-section record of wetter (Carolyn Shoemaker formation) to drier (lower Mirador formation) depositional conditions is accompanied by distinct changes in diagenesis. Clay minerals occur preferentially within the Carolyn Shoemaker formation and are absent within the lower members of the Mirador formation. At and above the proposed unconformity, strata are characterized by an increase in diagenetic nodules enriched in X-ray amorphous Mg-sulfate. Early clay formation in the Carolyn Shoemaker formation may have created a hydraulic barrier such that later migrating magnesium- and sulfur-rich fluids accumulated preferentially within the lower members of the Mirador formation. The proposed unconformity may have also acted as a fluid conduit to further promote Mg-sulfate nodule formation at the Carolyn Shoemaker−Mirador formation boundary. These results confirm an association of the clay-sulfate transition with the drying of depositional environments, but they also suggest that at least some orbital sulfate signatures within the region are not time-congruent with the environmental signals extracted from primary sedimentology. Our findings highlight that complex interactions among primary depositional environment, erosion, and diagenesis contribute to the transition in clay-sulfate orbital signatures observed in the stratigraphy of Mount Sharp.

GSA Bulletin↗

USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗

USGS2024

Groundwater-Surface water interactions research: Past trends and future directions

Interactions between groundwater and surface water sustain groundwater-dependent ecosystems and regulate river temperature and biogeochemical cycles, amongst many other processes. These interactions occur in freshwater environments including rivers, springs, lakes, and wetlands, and in coastal environments via tidal pumping, submarine groundwater discharge, and seawater intrusion. Here, we explore groundwater-surface water interactions research using bibliometric analyses of titles, abstracts, and keywords from 20,275 journal papers published between 1970 and 2023 extracted from Scopus. Analyses show that research into groundwater-surface water interactions is highly multi-disciplinary, with growing contributions from the social and biological sciences. The number of groundwater-surface water interactions papers is rapidly increasing with over 1200 papers published per year since 2020. Drawing on our data-driven approach and expert knowledge, we synthesise current research trends and identify critical future research directions. Despite the thousands of papers on groundwater-surface water interactions, important processes are still difficult to quantify or predict at meaningful spatial scales to inform water-resources management. We see benefits in future groundwater-surface water interactions research focusing on: (1) using new technologies including internet-of-things-based sensors, uncrewed vehicles, and remote-sensing approaches for data collection to inform groundwater-surface water interactions at large scales, (2) seeking approaches to upscale site-specific findings to better inform management, and (3) continuing the movement towards multi-disciplinary investigations to better inform the understanding of groundwater-surface water interactions and processes that will enable better management outcomes.

Journal of Hydrology↗

USGS2024

U.S.-Mexico Borderland & vegetation community map

People on both sides of the United States-Mexico border need a high-resolution, binational vegetation community map that spans the entire United States-Mexico borderlands. Traditionally, mapping efforts in this region were impeded by complex logistics related to the international border, differing national needs and plans, and resource allocations and priorities. To address this need, scientists from the U.S. Geological Survey (USGS) Southwest Biological Science Center partnered with the Sonoran Joint Venture, the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program, data engineers from the Department of Biosystems Engineering at the University of Arizona, and collaborators from the Wildlands Network, the Borderlands Program to produce the first prototype land cover map within the overlapping Mojave Desert, Sonoran Desert, and the North American Bird Conservation Initiative’s Bird Conservation Region 33 (BCR33) using Landsat satellite data . BCR33 is an area of high biodiversity, providing habitat for bird species of concern and other wildlife. The land cover map supports FWS recovery plan efforts related to conservation planning activities for many species, including Yellow-billed Cuckoo ( Coccyzus americanus ), Cactus Ferruginous Pygmy-Owl ( Glaucidium brasilianum cactorum ), Southwestern Willow Flycatcher ( Empidonax traillii extimus ), Yuma Ridgway’s Rail ( Rallus obsoletus yumanensis ), Bendire’s thrasher ( Toxostoma bendirei ), LeConte’s thrasher ( Toxostoma lecontei ), Masked Bobwhite ( Colinus virginianus ridgwayi ), jaguar ( Panthera onca ), and endangered plants such as Bartram’s stonecrop ( Graptopetalum bartramii ) and the Pima pineapple cactus ( Coryphantha robustispina ssp. robustispina ). In 2024, a Phase-II map for the full BCR33 region was completed, increasing the understanding of the binational nature of natural communities. The published map and associated paper can be found here .

Borderland↗

USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗

USGS2025

Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center ( https://doi.org/10.18739/A2RN3092P , Talucci et al., 2024).

Arctic↗

USGS2025

Bølling-Allerød productivity in the subarctic Pacific driven by seasonal upwelling

The Bølling-Allerød deglacial event is marked by high diatom productivity and opal deposition throughout the subarctic Pacific. This opal could either constitute a strengthened biological pump and thus carbon sequestration, or a weakened biological pump and release of marine-sequestered CO 2 to the atmosphere. We quantify silicic acid supply at IODP Site U1340 in the Bering Sea using biogenic opal and δ 30 Si of Coscinodiscus , a diatom genus. These records, along with diatom environmental indicators, suggest the Bølling-Allerød had high silicic acid availability related to a shift from stratification to seasonal upwelling dynamics. We thus propose the primary cause of the high productivity event was increased macronutrient supply from vertical exchange that injected old, nutrient-rich, CO 2 -rich waters into the surface. Enhanced CO 2 release from the subarctic Pacific may help explain critical intervals of CO 2 rise that occur at the onsets of the Bølling-Allerød and PreBoreal.

Geophysical Research Letters↗

USGS2023

The 2023 US 50-State National Seismic Hazard Model: Overview and implications

The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard (both increases and decreases compared to previous NSHMs) are substantial because the new model considers more data and updated earthquake rupture forecasts and ground-motion components. In developing the 2023 model, we tried to apply best available or applicable science based on advice of co-authors, more than 50 reviewers, and hundreds of hazard scientists and end-users, who attended public workshops and provided technical inputs. The hazard assessment incorporates new catalogs, declustering algorithms, gridded seismicity models, magnitude-scaling equations, fault-based structural and deformation models, multi-fault earthquake rupture forecast models, semi-empirical and simulation-based ground-motion models, and site amplification models conditioned on shear-wave velocities of the upper 30 m of soil and deeper sedimentary basin structures. Seismic hazard calculations yield hazard curves at hundreds of thousands of sites, ground-motion maps, uniform-hazard response spectra, and disaggregations developed for pseudo-spectral accelerations at 21 oscillator periods and two peak parameters, Modified Mercalli Intensity, and 8 site classes required by building codes and other public policy applications. Tests show the new model is consistent with past ShakeMap intensity observations. Sensitivity and uncertainty assessments ensure resulting ground motions are compatible with known hazard information and highlight the range and causes of variability in ground motions. We produce several impact products including building seismic design criteria, intensity maps, planning scenarios, and engineering risk assessments showing the potential physical and social impacts. These applications provide a basis for assessing, planning, and mitigating the effects of future earthquakes.

Earthquake Spectra↗

USGS2026

Navigating uncertainty and competing objectives: Spring chinook salmon recovery in the upper Willamette river

Globally, anadromous fish populations are threatened with extinction due to multiple factors, including river impoundments that block migration, widespread alteration of physical habitat, temperature, and flow regimes, commercial and recreational harvest, changes in biological communities, and long-term climate trends. In this synthesis, we describe how physical and biological factors, policy and law, and public resource allocation affect management of spring-run Chinook Salmon ( Oncorhynchus tshawytscha ) in the Upper Willamette River (UWR), Oregon, USA. Efforts to restore salmon populations often involve trade-offs, for example, water management decisions must account for flood control, agricultural and municipal water use, and management of other species. UWR Chinook Salmon recovery efforts are also governed by multiple laws, policies, and action agencies that in some cases have incongruent objectives. Competing and conflicting objectives, combined with uncertainty regarding the outcomes of proposed management actions, create significant challenges for decision makers. Resource limitations, regulatory constraints, and incongruent objectives have created challenges for managers in the UWR, but opportunities exist for improved adaptive management and collaboration, which could build trust and engagement among stakeholders and ultimately support the successful implementation of decision tools. A suite of decision support tools that have been used in the Willamette River basin and elsewhere across the range of Pacific salmon have the potential to enhance decision processes. These tools can be effective when decision makers and stakeholders commit to long-term, collaborative utilization of the tools for decision making, and when available resources and regulatory environments are conducive to implementation and adaptive refinement of both the decision-support tools and management plans. The general biological and institutional principles discussed for UWR Chinook Salmon in this work apply more generally to populations of anadromous fishes across their range, especially to populations in highly regulated river systems.

Oregon↗

USGS2024

Conceptual hydrogeologic framework and groundwater budget near the southeastern part of Puget Sound, Washington

More than 1 million people live within the active model area (AMA) in the southeastern part of the lowlands surrounding Puget Sound, or Puget Lowland, Washington, and groundwater is the source for approximately one-half of their public, domestic, and irrigation water demands. The 887-square-mile AMA, located in King and Pierce Counties, represents the area of analysis for the conceptual hydrogeologic framework and numerical groundwater-flow models within the study area and includes the Puyallup River and Chambers-Clover Creek watersheds. To assess the potential hydrologic and anthropogenic impacts to groundwater and the connected surface-water resources, conceptual and numerical groundwater-flow models of groundwater flow were developed by the U.S. Geological Survey Washington Water Science Center in close cooperation with 18 water-resource agencies and stakeholders. This report presents information used to characterize the groundwater-flow system and the development of a numerical model in the AMA. Included are descriptions of the geology and conceptual hydrogeologic framework, groundwater levels and flow directions, groundwater recharge and discharge, numerical groundwater-flow model construction and results, and model limitations. The study area encompasses the western part of Pierce County and the southwestern part of King County, Washington. The study area extends south to the Nisqually River, southwest to Tanwax Creek, northeast to the Green River, and north through the valley near Auburn and adjacent uplands. It is bounded on the east by foothills of the Cascade Range, and on the northwest by Puget Sound.

Washington↗