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Vegetation cover and composition in environments surrounding uranium mines in the Grand Canyon ecosystem, Northern Arizona

Mining uranium from breccia-pipe deposits in the greater Grand Canyon region has occurred since the mid-1900s. However, possible ecosystem contamination with harmful levels of radionuclides may have occurred due to mining activities in the 21st century. In response, a 20-year Federal moratorium on new mining claims in the Grand Canyon watershed was initiated in 2012, to allow time to evaluate the potential effects of uranium exploration and mining on human health, wildlife, and water resources. This moratorium, nor the 2023 designation of the “Baaj Nwaavjo I’tah Kukveni–Ancestral Footprints of the Grand Canyon National Monument,” precludes operation or development of mining claims predating 2012. Vegetation is a core ecosystem component that may be affected by uranium mining (for instance, through uptake and storage of radionuclides from the air or soil) or may act as a vector of exposure to wildlife, livestock, and humans (for instance, via their consumption of contaminated plant tissues). To provide baseline information about the plant communities associated with uranium mines in the Grand Canyon region, the U.S. Geological Survey surveyed an approximately 200-meter-wide buffer surrounding four breccia-pipe deposits, each in a unique stage of mine development, and at one reference area (a livestock water tank) that underwent ground disturbance but contains no mineral deposits. We sectioned the buffer zones into 0.65–4.52 hectare plots, within which we (1) inventoried all plant species, (2) measured percent cover of plant species, plant functional groups, and ground surface types (dark cyanobacteria, lichen, moss, bedrock, rock, embedded litter, duff, plant bases, and bare soil) using line-point intercept, and (3) measured length and frequency of gaps between perennial plant canopies using canopy gap intercept. We found that plant composition at the mines and the reference area differed from one another but were all characteristic of expected regional vegetation patterns. We provide this data summary as potential baseline information for future research and management efforts.

Arizona

Coastal Science Navigator companion guide—Discover the U.S. Geological Survey coastal science products you need

The Coastal Science Navigator is an online gateway to a wide variety of U.S. Geological Survey (USGS) coastal change hazards-related information, data, and tools relevant to stakeholders’ scientific and decision-making needs. The products within the Coastal Science Navigator provide data related to past, present, and future threats to our coastlines. The filter search allows users to see all available products and identify relevant options by time scale, geographic scope, coastal hazard theme, and other filters. The guided search suggests products based on users’ answers to a short series of questions. A comprehensive summary is available for each product. The idea for the Coastal Science Navigator arose in 2020 in response to stakeholder feedback identifying the need for a central source for USGS coastal science information. It was published in July 2023 and initially included 55 products. Regular updates are planned to integrate other existing and new products. This guide introduces some of the many coastal change hazards-related products available through the USGS. In it, we showcase the products included in the Coastal Science Navigator’s initial publication in July 2023. While it is not representative of all the information, tools, and data available, we hope it serves as a compelling snapshot of what the USGS has to offer and encourages you to explore the Coastal Science Navigator to discover more of the products you need. To navigate this guide, the products have been organized by the time scale they are best suited for—past, present, or future—although many products cover multiple time scales. An additional section features software, one of the many product types available as filters within the Coastal Science Navigator. Other products include downloadable data, websites, and geonarratives (web pages that combine text, images, and interactive maps into narratives you can scroll through). Featured geographic scopes are also highlighted within this guide, detailing some of the many regions in which the USGS conducts research and illustrating another way to filter products within the Coastal Science Navigator.

Circular

Landsliding follows signatures of wildfire history and vegetative regrowth in a steep coastal shrubland

Five years after the deadly and destructive 9 January 2018 Montecito debris flows (Santa Barbara County, California, USA), an atmospheric river storm on 9 January 2023 triggered widespread landsliding that affected many of the same drainages in the Santa Ynez Mountains. Using high-resolution aerial imagery, we identified >10,000 landslides over an ∼160 km 2 area. Most of the landslides were shallow (<1 m in depth) translational debris slides that initiated on steep (∼40°), south-facing hillslopes, with the highest incidence of landsliding in a sandstone-dominated bedrock unit. The landslides mobilized into debris flows and delivered substantial quantities of sediment downstream, which contributed to costly infrastructure impairments. We detected order-of-magnitude differences in landslide density across the study area that could not be attributed to variations in geomorphology (topographic aspect and slope), geology (bedrock type), or hydrology (seasonal antecedent rainfall, peak hourly storm rainfall intensity, total storm rainfall), which are usually considered relevant factors for shallow landsliding. Rather, we found that vegetation regrowth following wildfire was likely a relevant factor associated with the highly variable landslide densities. Hillslopes with less and different types of vegetation regrowth after fire appear to have been more susceptible to shallow landslides. We identify a possible vegetation control on postfire landsliding, which highlights an opportunity for hypothesis testing using more advanced techniques to track the evolution of vegetation cover and vegetation type in steep shrubland environments following wildfire.

California

Evaluating harvest liberalization strategies on population dynamics of southern latitude temperate-breeding Canada geese

The recovery of the Canada goose ( Branta canadensis ) is one of North America's greatest conservation success stories. Today, continental abundance of temperate-breeding Canada geese (those breeding in southern Canada and lower 48 states in the United States) greatly exceeds historical levels. As a result of increased abundance, human–goose conflicts have also increased, ranging from private and agricultural property damage to human health concerns. Managers have primarily attempted to lower Canada goose populations using hunter harvest via liberalized hunting regulations (increased bag limits and total hunting days). To evaluate the effectiveness of harvest strategies for temperate-breeding Canada geese, managers need a better understanding of how liberalized hunting regulations affect population dynamics. We estimated survival and harvest probabilities, abundance, and recovery distribution of temperate-breeding Canada geese banded in Arkansas, USA, during 2005–2020. We found that adult harvest probabilities declined overall during the study and adult survival probabilities increased. Annual abundances of juvenile geese (≤1 year old) declined during the study, whereas there was no detectable trend in abundance of the adult population over time. Most Canada geese breeding in Arkansas were shot in Arkansas, indicating potential for population dynamics to be influenced largely by state-specific harvest regulations. However, our results suggest that harvest liberalization as a management tool may have limited capacity to further influence population dynamics of Canada geese. Declines in productivity and recruitment likely had a greater influence on the similar observed declines in juvenile and adult abundances, respectively, during our study. More research is needed to better understand the ecological mechanism affecting the population dynamics of Canada geese in both urban and rural environments.

Arkansas

Collaborative drought science planning in the Colorado River Basin

The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.

Arizona, California, Colorado, Nevada, New Mexico,

Bayesian mapping of regionally grouped, sparse, univariate earth science data

Some earth science data are naturally grouped by region, and it is often desirable to map these data by region. However, if there are only a few samples within each region, then the map should be smoothed in an appropriate way to mitigate the problems that arise from having only a few samples. A smoothing algorithm based on a Bayesian hierarchical model is developed and presented in this report. This algorithm has several features that make it especially suitable for mapping earth science data: it can account for measurements that are censored, it can process multiple datasets with different measurement errors and different censoring thresholds, and it can calculate the uncertainty in any statistic that is mapped. The algorithm is demonstrated by mapping gold concentrations that are measured in streambed sediments in the Taylor Mountains quadrangle in southwestern Alaska.

Alaska

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Colorado

Engineering and risk research—A strategic vision for extending USGS earthquake science to risk assessment and mitigation

As a part of the U.S. Geological Survey (USGS) Natural Hazards Mission Area, the Engineering and Risk Project (ERP) of the Geologic Hazards Science Center conducts civil engineering research to extend natural hazards science to risk assessments. The ERP includes predominantly, but not exclusively, staff funded by the USGS Earthquake Hazards Program. A major focus of the ERP is to deliver actionable information to decisionmakers that helps promote the safety, security, and economic well-being of the Nation. The report discusses briefly the ERP’s evolution and scope, its organization structure, describes key products and deliverables, their efforts to engage with external partners, and its strategy and vision in conducting range of engineering and risk research. The research topics outlined in this report, as developed by the ERP, may be used to facilitate project planning activities during the next 10 years and serve as a longer-term planning resource for the USGS Earthquake Hazards Program and Geologic Hazards Science Center.

Circular

U.S. Geological Survey—Department of the Interior, Region 11, Alaska—2023–24 biennial science report

Introduction U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.

Alaska

lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data. Here we introduce , a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. can be found at https://doi.org/10.5066/P1DZUR3Z

Applied Computing and Geosciences

Structural evolution of iron coordination in proteins across Earth’s oxygenation history

Protein metal-binding sites support essential biological functions shaped by protein fold, subunit interactions, and cofactor chemistry. Because these sites encode both biochemical function and environmental constraint, they offer a route to connect protein evolution with changes in Earth’s surface environment through time. Of particular interest is iron (Fe), the most widely used metal in biology and a cofactor central to both anaerobic and aerobic metabolism. Here, we systematically compare the immediate chemical environments of functionally essential Fe-binding sites in three-dimensional protein structures to test whether Fe coordination spheres differ across oxygen contexts. Using a curated dataset of experimentally determined structures, we identify a clear shift in the local chemistry of Fe-binding environments from anaerobic to aerobic proteins. Aerobic Fe sites are significantly more hydrophilic than anaerobic ones, and amino-acid composition analyses show reduced cysteine use in aerobic Fe-binding neighborhoods. These patterns suggest that as Earth’s surface environments became more oxygenated, proteins retained Fe as a core redox metal while reconfiguring local coordination chemistry in ways less vulnerable to oxidative damage. More broadly, this study introduces and applies the Coordination Sphere Analysis and Comparison (CSAC) workflow, an open and archived Python workflow for extracting local metal-binding environments from structure datasets, providing a framework for linking metalloprotein structure to evolutionary and geobiological transitions across Earth history.

Discover Life

State of science, gap analysis, and prioritization for southeastern United States water-quality impacts from coastal storms—Fiscal year 2023 program report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes

Tropical cyclones (coastal storm events that include tropical depressions, tropical storms, and hurricanes) cause landscape-scale disturbances that can lead to impaired water quality and thus reduce water availability for use. Stakeholders and scientists at local and national scales have illustrated a need for understanding these risks to water quality. A regional and comprehensive understanding of the impacts of tropical storms and hurricanes on surface-water and groundwater quality—and thus water availability—is lacking for potentially impacted coastal and inland areas. As the U.S. Geological Survey considers development of tools to predict the extent to which water-quality impacts of hurricanes affect water availability, an assessment of the state of the science of hurricane impacts is needed, including a gap analysis and prioritization of data and science needs. This assessment focuses on the southeastern coastal States.

southeastern United States

Future water constraints on United States lithium mining under climate change

Lithium is necessary for low-carbon technologies that combat climate change, but lithium extraction is water-intensive. Changes in temperature and precipitation arising from climate change are altering water distribution, which could further strain supplies for new mines and industry, farms, and households. Here we explored how climate change, water use, and mining siting could impact lithium mining in the United States. We analyzed whether there would be sufficient water available to support the single existing and 22 proposed U.S. lithium mines at mid-century under four socioeconomic-climate scenarios and five climate models. Though dependent on socioeconomic-climate scenario, climate model, and lithium deposit type, available water supply in most subbasins would likely be unable to support new mines’ water demands, or even non-mining water demands from other sectors. Water scarcity could hinder the ability of the United States to produce enough lithium to meet domestic demand thereby necessitating higher imports.

conterminous United States

Memory and jamming in fault zone sediments

Many subsurface processes involve transitions in granular material states, from arrested to creeping to flowing. Experiments and frameworks for idealized systems reveal that granular fabrics develop during shearing, co-evolve with applied stress, and govern such transitions. We use microtomography to test whether fabrics at two San Andreas fault sites reflect slip history and whether idealized frameworks extend to nature. Near-surface sediments within the fault zone transition between deformation patterns over the seismic cycle, including bulk/localized grain re-arrangements, individual grain fracturing, and localized zones of fracturing. Aseismic and co-seismic shearing produce distinct preferred grain orientations. Co-seismic fabrics can be preserved after centuries of aseismic strain, aseismic fabrics may be overprinted, and grain size and coordination number influence the fabrics. Idealized frameworks, namely anisotropic critical state theory, frictional jamming, and material memory, can explain our observations, and fault zone sediments likely undergo cycles of memory creation and erasure that influence rigidity spatiotemporally.

California

Low-frequency earthquakes track the motion of a captured slab fragment

Accurate tectonic models are essential for assessing seismic hazard and fault interactions. However, the plate configuration at the complex Mendocino triple junction, where the San Andreas Fault and the Cascadia subduction zone meet, remains uncertain. We analyzed fault slip associated with a recently identified zone of tectonic tremor and low-frequency earthquakes (LFEs) near the southern edge of the subducting Gorda slab. Based on tidal sensitivity and P-wave first motions, we show that the LFEs are generated by dipping, strike-slip motion. This suggests that a former Farallon slab fragment, now captured by the Pacific plate, is translating northward beneath westernmost North America. This geometry effectively extends the slab interface fault, challenging prevailing interpretations of slab window formation and creating a potential unaccounted earthquake hazard in this region.

Science

U.S. Geological Survey science strategy to address white-nose syndrome and bat health in 2025–2029

Since its discovery in 2006, the fungal disease known as white-nose syndrome (WNS) has killed millions of bats. Of the 47 bat species native to the conterminous United States, Alaska, Hawaii, and Canada, 12 have been affected by WNS, including 3 endangered species and 1 proposed endangered species. WNS has also been detected in 40 States and 9 Canadian Provinces. U.S. Geological Survey (USGS) scientists have been critical in identifying the causal fungus for WNS ( Pseudogymnoascus destructans [Pd]), characterizing the effects of WNS, and tracking the spread of Pd in many bat populations in North America. The mission of the USGS WNS and Bat Health Science Team is to deliver integrated science in order to build resiliency into free-ranging bat populations through more effective WNS management, build capacity for bat health science, and enhance bat health information sharing across USGS science centers and cooperative research units as well as with stakeholders. The USGS can play an important role in supporting regional and national capacity building by providing resources and guidance to local, State, and Tribal management entities and by providing tools to enhance disease management. The USGS Ecosystems Mission Area’s Biological Threats and Invasive Species Research Program is the lead Federal program for free-ranging wildlife disease research and surveillance. As of 2024, guided by the science priorities set by the WNS Steering Committee, USGS scientists are engaged in a nationwide response to WNS. This work is done in close coordination with our partners at the U.S. Fish and Wildlife Service, National Park Service, Bureau of Land Management, U.S. Forest Service of the U.S. Department of Agriculture, U.S. Department of Defense, as well as State and Tribal agencies. In addition to conducting WNS research, the USGS is mapping the spread of WNS and coordinating the North American Bat Monitoring Program (NABat) to understand how WNS and other stressors affect the status and trends of native bats across their range. The USGS is supporting the national WNS response through four science goals: (1) provide situational awareness on the health of bat populations; (2) conduct ecological studies of bats along the gradient of disease vulnerability; (3) contribute actionable science to enhance the resiliency of bat populations; and (4) implement an adaptive, holistic approach to bat health.

Circular

Cascadia Subduction Zone science: Call for the next generation community seismic velocity model

The Cascadia subduction zone (CSZ) hosts major seismic and tsunami hazards, yet key questions persist about the relationship between margin structure, fluid distribution, episodic tremor and slip, shallow megathrust behavior, shaking and tsunamigenesis, and the resulting hazard estimates. Addressing these problems requires an empirically grounded, three‐dimensional seismic velocity model to illuminate subsurface structure and properties and to provide a basis for geophysical studies such as earthquake simulations and ground‐motion estimation. In May 2024, the National Science Foundation‐funded Cascadia Region Earthquake Science Center (CRESCENT) community velocity model (CVM) working group, with U.S. Geological Survey and regional partners, convened a workshop to identify priorities for such a model. Participants emphasized the features necessary for addressing key science questions, including implementing findability, accessibility, interoperability, and reusability (FAIR) access, capturing along‐strike and along‐dip structural heterogeneity, resolving shallow offshore–onshore structure, constraining elastic properties and quantifying their uncertainties for numerical wave propagation simulations, their validation benchmarks, and supporting associated accurate earthquake ground‐motion simulations and hazard assessments. This article describes the priorities defined in the workshop, and a description of how, guided by these needs, CRESCENT plans to develop multiple generations of a CVM to advance CSZ science and improve seismic and tsunami hazard modeling across the Pacific Northwest. The CVM will span the CSZ from the surface to ∼100 km depth, offshore and east of the Cascades into Idaho (∼132°–110° W) and the southern and northern tectonic regime transitions (∼36°–52° N) to capture the entire tectonic system as well as its surroundings.

Cascadia Subduction Zone

Fiber-imaged supershear dynamics in the 2024 Mw 7 Mendocino Fault earthquake

Fault structure and rupture physics are deeply intertwined, and observations of this coupling are critical for understanding earthquake behavior. Rupture propagation is observable at fine scales using dense seismic networks. Fiber-optic sensing allows for long-term deployments of ultradense arrays that enable high-resolution measurements of infrequent, large earthquakes. We recorded the 2024 moment magnitude ( M w ) 7 Mendocino Fault earthquake with a nearby fiber-optic array and imaged its behavior with seismic beamforming. The rupture propagated to the east at subshear velocity; stagnated near the Mendocino Triple Junction, a zone of structural complexity; and subsequently transitioned to supershear velocity. The correlation between source physics and structure shows how lithospheric heterogeneity affects first-order characteristics of earthquake ruptures. Our results also demonstrate the potential for fiber-optic sensing to improve real-time estimation of key parameters for early warning.

California