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USGS2026

Examples of eruption response teams from the Alaska Volcano Observatory

During times of eruption response, volcano observatories need to organize themselves differently than during normal operations. The number of formal operational roles grows to ensure that critical responsibilities are covered, including management of all activities at the observatory as well as increased staffing to ensure proper surveillance of data and issuance of timely notices and warnings. The scope and approach differ for each observatory and, in fact, for different eruptions. The Alaska Volcano Observatory (AVO) maintains an extensive monitoring program and issues forecasts and warnings about volcanic eruptions and unrest in Alaska. Since 2000, AVO has used formal roles to perform these duties and has implemented a variety of team approaches to respond to larger eruptions. For the Augustine (2006) and Redoubt (2009) eruptions, management scaled from 3 up to ~ 8 people in a command team to cover all aspects of the response. During these and other eruptions (e.g., Okmok, 2008), an operations room was staffed continuously to cover real-time responsibilities pertaining to monitoring and issuing alerts while the command team focused on overall management. More recently, such as for Bogoslof in 2016–2017 and Shishaldin in 2019 and 2023, AVO used a virtual real-time response team to handle warning tasks and variations of an Observatory Volcanic Event Response Team (OVERT; Moran et al. 2024) to manage overall observatory response activities. In 2025, AVO employed a formal OVERT for the first time to oversee its response to unrest at Mount Spurr. Frequent implementation, nimble scaling, constant evaluation, flexibility, and good communication make the team approach effective. We present examples of several response teams used over the last 25 years, and lessons learned from them, in the hope that these will be helpful to other observatories facing crisis responses. These examples may also allow stakeholders and the public to better understand how observatories work.

Alaska↗

USGS2026

Plant diversity shifts with drying and wetting cycles following removal of poplar plantations in Dongting Lake, China

Dongting Lake, the second largest lake in China, plays a crucial role in maintaining regional ecological security by providing key habitats for waterbirds. This study examined how hydrology and topography (ditches and mounds) together generate fine-scale wet–dry gradients that shape species establishment and successional trajectories. Over the past decade, vegetation restoration has been implemented through the removal of poplar plantations. We selected sites in West Dongting Lake representing different stages following poplar removal, including active plantations (Poplar), one-year (1Yr) and five-year (5Yr) restored sites, and natural floodplain reference sites. Analyses of seasonal water-level dynamics over several years revealed distinct hydrological regimes among restoration stages, with differences in inundation duration and amplitude corresponding to ditch–mound topography. Species diversity indicators showed that species richness was highest in Poplar (37 species) and lowest in Reference sites (14 species), with exotic species richness following the same trend. The lowest Cody index occurred between 1Yr and Reference sites, while the Jaccard similarity differed significantly among site pairs, with lower similarity observed in comparisons with the Reference site. Non-metric Multidimensional Scaling (NMDS) analysis indicated minimal overlap between Poplar and Reference sites, with 1Yr and 5Yr sites clustering together but remaining distinct from the Reference site. These results suggest that poplar cultivation and its associated mound-ditch topography have altered hydrological and community structure of the wetland, facilitating the persistence of exotic species. Natural recolonization is driven by the interaction between seasonal water-level dynamics and topography, which regulate inundation duration and wet–dry cycles. Effective restoration may require removal of poplar plantations and regrading of artificial ditches and mounds to restore natural hydrological connectivity to support vegetation recovery in these subtropical monsoonal wetlands.

Dongting Lake↗

USGS2026

Previous prescribed burns saved thousands of ancient sequoias during historically unprecedented wildfires

Wildfires in California’s Sierra Nevada during 2020–2021 killed giant sequoias ( Sequoiadendron giganteum ) at rates unseen for millennia, underscoring the vulnerability of highly fire-adapted trees to ongoing environmental change. Following a century of fire exclusion and fuel accumulation, the effectiveness of prescribed burns in reducing giant sequoia mortality from wildfire remained poorly quantified. Here we estimate mortality outcomes for 26,403 giant sequoias across 19 groves in Sequoia and Kings Canyon national parks following the Castle (2020) and KNP Complex (2021) wildfires using a Bayesian framework. We map tree mortality using a deep learning classifier integrating 3 m PlanetScope imagery, airborne lidar, and field observations. From an estimated 7,974 sequoia deaths (95% Bayesian credible interval (CI): 7,555–8,430), corresponding to 30.2% mortality (CI: 28.6–31.9%), we find previous prescribed burns (≤10 years prior) reduced mortality odds by 77% (CI: 69–83%), making treated trees nearly four times more likely to survive. Counterfactual simulations suggest that prescribed burns prevented at least 1,888 (CI: 1,487–2,302) deaths, and universal treatment would have saved an additional 3,888 (CI: 3,236–4,580) giant sequoias. These results show that prescribed burns substantially improve survival during extreme wildfires, offering guidance for conserving long-lived, fire-adapted forests under intensifying fire regimes.

California↗

USGS2026

Sediment response to stream restoration in an agricultural watershed

Despite widespread implementation of stream restoration there is limited research of its effectiveness in impaired agricultural settings. To quantify the effects of stream restoration on sediment load, we investigated erosion and deposition along 9 stream reach sites (4 restored, 4 unrestored, and 1 downstream) in Turtle Creek, Pennsylvania, United States - a representative agricultural subbasin of the Chesapeake Bay. These stream restoration projects had the goal of reducing sediment load primarily by installing log structures and regrading streambanks in order to stabilize streambanks and reconnect floodplains. Floodplain and streambank sediment fluxes were quantified over a 3-year period through repeated measurement of clay pads and pins and measurement of sediment bulk density. Uncrewed aerial imagery was collected at 3 of the sites, then processed using structure from motion (SfM) to create high-resolution digital elevation models. Terrain analysis enabled three-dimensional understanding of the generality of the specific field flux measurement locations to the larger stream reach. Restored sites on average had deposition on streambanks compared to streambank erosion along unrestored sites, and approximately two times greater floodplain deposition than unrestored sites. Overall, restored stream had an average seven-fold increase in the net balance (sum of streambank and floodplain) of sediment flux, a 81.2 kg/m/yr increase in retention, compared to unrestored stream. The measured larger streambed particle size distribution (D 50 ) in restored streams also suggests additional improvements to instream habitat quality. Terrain analysis confirmed that the field-based measurements were representative of the larger reach. These results indicate that stream restoration in agricultural watersheds using less-engineered designs can reduce sediment loading and improve stream habitat and health goals.

Pennsylvania↗

USGS2026

Precipitation intensity increased across the South Pacific Convergence Zone in the Industrial Age

The position, strength, and variability of precipitation in the South Pacific Convergence Zone (SPCZ) remain challenging for coupled ocean-atmosphere climate models to represent, leaving future rainfall projections in this dynamically important region uncertain. Here, we present quantitative records of mean annual precipitation (MAP) spanning the past 1,000 years using sediment cores from five freshwater lakes on different islands in the western portion of the SPCZ. Precipitation reconstructions are based on the hydrogen isotope composition of the dinoflagellate biomarker dinosterol, which is inversely correlated with MAP. We show that MAP in the western tropical Pacific increased over the past ∼300 years, with a significant increase beginning in 1,820 ± 75 C.E., coincident with a warming trend in the Western Pacific Warm Pool. These results contrast with the expected drying associated with reduced Pacific Walker Circulation as global temperatures increase in many climate models. Future warming may promote more intense SPCZ precipitation.

Geophysical Research Letters↗

USGS2026

Body size, dispersal potential, range size and habitat fragmentation are linked to extinction risk of freshwater mussels

Aim: Trait-based approaches are increasingly recognized as a tool for understanding species’ vulnerabilities to intensifying global change. For species with complex life histories that involve a parasitic life stage, a combination of traits associated with either the host or parasite could influence extinction risk. Location: United States of America Taxon: Freshwater mussels are a highly threatened assemblage of bivalves with an obligate ectoparasitic larval stage requiring a host fish. Adult mussels are sedentary, with long-distance dispersal dictated by the dispersal ability of the host fish during the parasitic larval life phase. Methods: We integrate several open-source spatial and trait datasets for freshwater mussels and host fishes to test hypotheses about the relationship between species-level traits such as body size, area of occupancy (AOO), host fish dispersal, habitat fragmentation, and mussel extinction risk. Results: Imperiled mussels were smaller, had smaller areas of occupancy, used small-bodied, dispersal-limited host fishes, and had higher densities of large dams in their AOO compared to non-imperiled mussels. Conclusions: Body size, along with AOO and dispersal potential, appear to have cascading effects on imperilment where decreases in these traits potentiate population fragmentation via large dams. Thus, in contrast to many other groups, freshwater mussel body size is inversely related to extinction risk and small-bodied mussels should be closely monitored to prevent future extinctions.

Journal of Biogeography↗

USGS2026

Mesophotic octocoral larval settlement preferences and behaviors

Introduction Lab-based coral reproduction is advancing restoration efforts to support coral populations injured by the 2010 Deepwater Horizon oil spill. Objectives This study aimed to answer foundational questions concerning coral spawning and larval settlement that need to be resolved for these mesophotic and deep-sea coral species before restoration efforts can be scaled up. Methods From 2021 to 2023, fragments of the mesophotic octocorals Swiftia exserta and Thesea nivea were collected from the continental shelf offshore from Texas to Florida and transported to a federal facility in Florida. Multiyear spawning allowed for in-depth analysis of spawning periodicity, egg development, larval behavior, settlement rate, and substrate preference. In addition, we determined the likelihood of successful development and survival during early stages of development. Results Fertilization rates remained high throughout spawning periods of both species, with S. exserta spawning during a 1-month period and T. nivea continuing to spawn year-round. Larvae from both corals significantly preferred tiles seeded with crustose coralline algae, and there were species-specific preferences in substrate material. Additionally, larval survival or mortality was typically evident within a few days when in the presence of settlement substrates. In the absence of substrates, we observed larvae surviving for up to 2 months without settling. Conclusions This work answers critical questions to inform the long-term logistical planning for eventual out-planting of these species. Further, it highlights avenues that could accelerate future restoration-based reproduction efforts into unexplored mesophotic and deep species.

Alabama, Louisiana, Mississippi, Texas↗

USGS2026

The Cascadia Region Earthquake Science Center (CRESCENT): Advancing understanding of Cascadia's earthquake hazards

The Cascadia Subduction Zone (CSZ) is capable of producing large megathrust earthquakes and tsunamis, posing significant risks to the Pacific Northwest. This paper examines the seismic characteristics of the CSZ, including its offshore coupling, sparse seismicity, and a complex paleoseismic record. While recent advances in geophysical methods and data collection have improved our understanding of subduction zone processes, important uncertainties remain regarding rupture dynamics, ground shaking, and tsunami impacts. The Cascadia Region Earthquake Science Center (CRESCENT) has been established to address these challenges through coordinated research, education, and community engagement. By integrating scientific studies, fostering collaboration, and leveraging new technologies, CRESCENT seeks to improve hazard assessment and resilience in the region. This paper outlines the primary challenges and opportunities in advancing subduction zone science and enhancing societal preparedness for future CSZ events.

California, Oregon, Washington↗

USGS2026

Resurvey of cross sections on the Green River in Browns Park, Colorado and Utah

This study resurveyed ten previously established cross sections and established eight new cross sections on the Green River in Browns Park to document changes in channel width, depth, and area since earlier surveys conducted in 1994. The measured area of the channel cross sections on the Green River in Browns Park generally increased between the initial surveys and 2019. This increase in cross-sectional area was observed in nine of the ten resurveyed cross sections and is indicative of net sediment erosion. The increase in cross sectional area occurred through both channel widening (bank retreat) and increases in depth (bed incision). An analysis of the contribution of bank versus bed changes to the overall area change suggests that the erosion is mostly from the bed of the channel. In addition, weak longitudinal trends in the bed-sand grain-size distribution are consistent with progressive depletion of the sand stored on the bed of the Green River in Browns Park. The findings from our cross-section resurvey support the conclusion that the Green River in Browns Park is experiencing progressive sediment loss and is in a state of sediment deficit.

Colorado, Utah↗

USGS2026

Improving building footprint extraction using NAIP and 3DEP lidar derived features with deep learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

Texas↗

USGS2026

Development of liquefaction-targeted design basis in U.S. seismic provisions

Seismic design criteria for new buildings in the United States have historically focused on life safety performance objectives through minimizing the potential for structural collapse. Development of design criteria to meet this performance objective has evolved over time, leading to the current, risk-targeted maximum considered earthquake (MCE R ) design basis. Corresponding MCE R seismic design loads incorporate the full range of probabilistic ground motion hazard information available from U.S. Geological Survey National Seismic Hazard Models, as well as a representation of the uncertainty in structural collapse capacity. Despite these considerable advances in structural design criteria, guidelines for geotechnical hazards such as liquefaction-induced damage, which continue to be based on uniform ground-shaking hazard (i.e., MCE ground motions), are not well-connected with risk-based, collapse prevention performance objectives. This study, undertaken as part of Building Seismic Safety Council efforts to update recommended seismic provisions through the National Earthquake Hazards Reduction Program, presents probabilistic, liquefaction-targeted design objectives and corresponding ground motion parameters, with a focus on improving consistency in first-level screening criteria for liquefaction hazard assessment. This study identifies a potential maximum acceptable annualized probability of liquefaction triggering ( P L,max ) of 2.5% in 50 years, above which liquefaction consequences and potential mitigation measures would be considered. The P L,max -based design basis is calibrated to effective probabilistic liquefaction hazard levels obtained in practice using current MCE peak ground accelerations, and could be implemented via a new liquefaction-targeted maximum considered earthquake (MCE L ) peak ground acceleration ( PGA L ). The proposed PGA L is derived from probabilistic liquefaction hazard curves and includes uncertainties inherent to liquefaction hazard modeling. The potential design effects of the proposed PGA L are demonstrated via comparison with current MCE PGA levels, effects on first-level liquefaction screening analyses, and improvements in the consistency of P L,max levels across the United States, and for a wide range of site conditions.

conterminous United States↗

USGS2026

Life-history stages and behavior influence demographic classification of moose captured on remote cameras

Obtaining accurate information on demographic states, such as the age and sex classes of animals, is an important step for monitoring wildlife populations. Traditionally, demographic data are collected from harvest, aerial surveys and telemetry studies. However, these methods can be expensive, limited to small spatial scales, or biased due to human behavior. Remote cameras have become a mainstay for studying and monitoring wildlife as they are relatively inexpensive, can be deployed over large spatial scales, and effort can be accounted for during surveys. For some species, a variety of demographic information, such as sex and age classes, can be obtained from pictures. Moose Alces alces are a photogenic species found across boreal and semi-boreal forests of the Northern Hemisphere. Previous studies have used demographic data from remote cameras to estimate demographic parameters and population dynamics. A primary assumption is that these age and sex classes are accurately classified. However, numerous factors can influence the ability of observers to identify age and sex classes of moose captured on cameras. We used data from 84 cameras from a 3-year period (2021–2024) in northern Maine, USA, to evaluate how temporal, environmental, site-level, and endogenous factors influence observers' ability to classify age and sex classes of moose. Using Bayesian categorical regression models, we found that temporal variability, position and proximity of moose from cameras, and the behavior of moose influenced our ability to identify age and sex classes. This information can be used to decide which periods to use data for population modeling and how to design studies to reduce the amount of uncertainty associated with different age and sex classes. We anticipate that our approach could also be used for other species whose age and sex classes can be differentiated using remote cameras.

Maine↗

USGS2026

Modeling legacy nitrogen transport under instantaneous, steady-state, and transient groundwater flow conditions

In hydrologic settings where groundwater discharge contributes substantially to surface waters, legacy nitrogen in groundwater can confound surface water nitrogen loads estimated exclusively from current terrestrial sources. Additionally, legacy nitrogen in groundwater can contribute to lagged responses to nitrogen management efforts. Some methods of estimating groundwater contributions to surface water nitrogen loads account for legacy nitrogen, while others do not. The resulting differences are rarely quantified. We used a numerical modeling framework to compare three methods of estimating time-varying annual groundwater nitrogen loads to surface water receptors on eastern Long Island, New York. The instantaneous load method used steady-state contributing areas and includes no temporal groundwater lag. The second method used numerical simulations of nitrogen loads under steady-state flow, which captures groundwater transport lags but omits the annual variability in transient hydrologic stresses. The third method numerically simulated both transient groundwater flow and nitrogen transport to explicitly capture the effects of legacy nitrogen in groundwater. Depending on antecedent nitrogen and hydrologic conditions, historical nitrogen loads estimated from the numerical simulations were sometimes similar (<10% difference) and other times substantially different (±100%) from the instantaneous load estimates. Additionally, simulated future surface water nitrogen loads responded asymptotically over several decades following reductions in terrestrial nitrogen sources, further highlighting the effect of groundwater transport lag times. The comparison of the three methods, quantification of historical interannual variability, and prediction of lagged responses to nitrogen source reductions provide important context for decision makers using estimated groundwater nitrogen loads to help evaluate nitrogen management efficacy.

New York↗

USGS2026

Structure-aware unsupervised transmission corridor structure extraction from 3DEP lidar using graph attention embeddings and reinforcement-learned DBSCAN

Transmission corridors are critical components of power delivery infrastructure, and their large-area monitoring increasingly relies on national-scale airborne lidar programs. This study presents an unsupervised, scalable framework for extracting transmission corridor structures (including conductors and supporting towers) from U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) lidar point clouds. The workflow begins with height-above-ground filtering and statistical outlier removal to isolate elevated infrastructure candidates. Local Principal Component Analysis (PCA) is then used to compute fine-scale geometric descriptors. To incorporate spatial context and improve structural separability in feature space, we learn point embeddings using a Graph Attention Network (GAT) trained with a structure-consistency triplet objective, yielding representations tailored for downstream density-based grouping rather than semantic classification. To address the spatial non-stationarity of point density and noise across large scenes, we formulate Density-Based Spatial Clustering of Applications with Noise (DBSCAN) parameter selection as a reinforcement learning problem and employ Proximal Policy Optimization (PPO) to adapt 𝜀 and minPts at the block level based on embedding statistics. The final extraction is produced via block-wise DBSCAN and spatial merging to support efficient processing of multi-million-point clouds. Experiments on USGS 3DEP data over Houston, Texas, show that the proposed method produces spatially coherent candidate corridor structures from unstructured lidar. Quantitative assessment is conducted using OpenStreetMap (OSM)-referenced spatial-agreement metrics under a consistent vector-reference protocol, alongside comparative baselines and ablation studies, to examine the relative contributions of graph embedding learning and RL-based adaptive clustering.

Texas↗

USGS2026

2026–2031 U.S. Geological Survey strategy for a hazard ready Nation—Actionable science for risk reduction

Executive Summary The USGS Strategy for a Hazard Ready Nation provides an approach that U.S. Geological Survey (USGS) researchers and staff can use to deliver actionable, user-focused science that supports risk-informed decision making aimed at reducing risk and losses across the Nation. The Strategy builds upon successful efforts within the USGS and seeks to promote and prioritize similar work in the future under an organized framework. Rooted in four priorities—(1) center end-user needs, (2) enhance research relevance, (3) support product and service development and implementation, and (4) improve communication—the USGS Strategy for a Hazard Ready Nation is designed to focus and guide, not prescribe, activities. Strategic actions are proposed to achieve these four priorities in a timely fashion. The USGS plans to continually build upon the Strategy for a Hazard Ready Nation to deliver actionable information for risk-informed decision making.

Circular↗

USGS2026

U.S. Geological Survey Monitoring Milestones—Oe-151 at Woodgate, NY (433112075091501)

On July 9, 1926, monitoring well Oe-151 at Woodgate, New York (USGS ID 433112075091501) recorded its first groundwater data. Since then, the well has provided water data nearly continuously and has now reached a 100-year milestone for data collection. The well is part of the U.S. Geological Survey (USGS) Climate Response Network (CRN), which is a national network of wells selected to monitor natural groundwater conditions. Well Oe-151 is the first well in the network to reach a 100-year Centennial milestone.

New York↗

USGS2026

Timescales of cumulate mobilization and mixing for the 1868 A.D. eruption of Mauna Loa, Island of Hawai‘i

The deadly 1868 A.D. eruption of Mauna Loa’s lower Southwest Rift Zone (Island of Hawai‘i) included a M7.9 earthquake and associated tsunami and landslides, demonstrating the severe hazards posed by Earth’s largest active subaerial volcano. To better understand the relationship between intense seismic activity, dike emplacement, magma storage, transport histories, and mobilization of olivine cumulates at Mauna Loa, we examine compositional zoning of olivine in the 1868 lava flows. Samples range from basalt (< 10% olivine) to picrite (30–40% olivine). The olivine cargo is heterogeneous (Fo 78.2–89.2 ; forsterite = [Mg/(Mg + Fe) × 100]) but dominated by ~ Fo 89 cores that lie above the Fe-Mg equilibrium field of host glasses. Crystal rims < Fo 80 are due to post-eruptive modification in slow cooling lava flows. Minor element compositions fall within the range of other Mauna Loa olivine erupted in the past 200 years. Olivine crystals exhibit both normal and complex Fo zoning patterns that yield timescales of diffusive re-equilibration that range from 3 to 258 days, with 72% of crystals recording 71 days or less. These timescales correspond to magmatic priming of the summit reservoir system ~ 2 months prior to the eruption and the M7.9 earthquake likely facilitated the transport of the crystal-rich summit-derived magmas downrift shortly prior to eruption. If the recently proposed faster Fe-Mg diffusion coefficient is used, timescales instead range from < 1 day to 25 days, with most recording 1 week or less. In this scenario, most of the olivine zoning would have to have been generated after the M7.9 earthquake perturbed the system.

Hawaii↗

USGS2026

Seeing is believing: Livestream video monitoring of Hawaiian eruptions

Livestream video has become a crucial tool for volcano monitoring in recent years, building upon the use of webcam snapshots that have been common for the past two decades. In Hawaii, livestream video was first tested in 2018, and today, livestream video is a vital tool for the Hawaiian Volcano Observatory and partner agencies (National Park Service and Hawaiʻi County Civil Defense) as well as the public. Its role in volcano monitoring has been highlighted by the 2024–present summit eruption of Kīlauea—where three livestream video feeds provide a continuous and easily accessible view of the activity for the public. Here, we describe the methodology and equipment used for the livestream cameras in Hawaii and discuss the benefits and challenges of livestream video monitoring. We show how the nature of livestream video has fundamentally changed volcano monitoring, providing an “up-close” view to the world that was previously limited to observatory field staff. The livestream video feeds, coupled with the historical summit lava fountains, have provided an unprecedented level of engagement with the public, both local and worldwide.

Hawaii↗