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Research about United States

Source-linked reports with geographic coverage including United States.

At least 109 records · Page 6Linked to original sources
USGS2026

Perceptions of relational organizing as a tool for human–bear coexistence

Conflict between humans and American black bears ( Ursus americanus ) is a growing concern in North America, especially in wildland–urban interfaces. Beyond ecological drivers, conflict reduction relies on changing human behavior. Neighbor-to-neighbor conversations, also known as relational organizing, may drive social diffusion of coexistence actions. However, little research has explored the behavioral conditions enabling (a) residents to initiate conversations and (b) neighbors to listen and adopt bear-safe practices. Using the capability, opportunity, motivations and behavior (COM-B) framework, we analyzed 34 semi-structured interviews with engaged residents in two western U.S. communities with ongoing coexistence efforts. Results highlight that interviewees have heterogeneous knowledge and skills (capability), are committed to leveraging interpersonal relationships but concerned about protecting these relationships (social opportunity), feel more able to engage in relational organizing with enabling programmatic support and regulatory frameworks (physical opportunity), and are motivated by identity, emotion, and beliefs about consequences.

Colorado, Montana↗
USGS2026

The cost of limited nocturnal roost availability on pre-migratory energy budgets in a central-place foraging shorebird, Numenius hudsonicus (Hudsonian Whimbrel)

Mobile species often travel long distances between the sites they use for different behaviors, such as central-place foragers that make daily commutes between a central roost and foraging sites. For migratory shorebird species that use coastal habitats, the limited availability of suitable nocturnal roost sites can lead individuals to commute long distances to their foraging territories, forcing them to balance the energetic cost of commuting with the need to refuel in between migratory flights. We investigated this potential trade-off in a population of Numenius hudsonicus (Hudsonian Whimbrel) that show wide variation in commute distance between a shared central nocturnal roost and individual foraging territories in coastal South Carolina, USA. We combined high-resolution movement data, behavioral state modeling, and empirical foraging behavior data to assess how increasing commute distances from a central nocturnal roost affect individual daily activity budgets, foraging habitat use, potential net energy gain, and breeding ground departure date. We found that N. hudsonicus that commute farther from their nocturnal roost spend a higher proportion of each day foraging and commuting, and that they delay their departure to the breeding grounds by 3–6 days. Our results indicate that roosting habitat close to foraging areas can reduce the energetic cost of commuting to help shorebirds avoid delays in migratory timing. Thus, protecting, restoring, and creating nocturnal roosting habitat close to foraging areas may enhance successful shorebird migration.

South Carolina↗
USGS2026

Ecological stability of zooplankton communities in changing arctic lakes over three decades

In the Arctic, rapid warming is altering disturbance regimes, creating an urgent need to assess the ecological stability of these relatively pristine ecosystems. The Arctic landscape has thousands of lakes that are experiencing both gradual, persistent disturbances (e.g., warming) and increased frequency and intensity of pulse disturbances (e.g., land-surface failures). To assess the ecological stability of lake communities in a changing environment, we analyzed long-term data (14–39 years) on zooplankton communities and environmental variables from 25 lakes in arctic Alaska. We characterized long-term change and evaluated the resistance and recovery of communities to natural or experimental disturbances. We hypothesized that reference lakes would demonstrate resistance to background environmental change, represented by variable but consistent relative abundances over time, while manipulated or disturbed lakes would show recovery after the disturbance ceased, as represented by directional changes in relative abundance with return to pre-disturbance conditions. Environmental variables including water conductivity, chlorophyll- a , NO 3 − , pH, dissolved oxygen, light extinction, and soluble reactive phosphorus changed directionally through time, suggesting press effects due to climate change. Zooplankton communities were resistant to environmental change in undisturbed lakes, but, despite monitoring lakes for up to 28 years after disturbance, few lakes showed evidence of recovery to pre-disturbance conditions. This lack of recovery may indicate shifting baselines due to environmental change. The variation we did observe was largely due to shifts in species relative abundance rather than in species turnover, and this variability was related to lake depth. Zooplankton communities and environmental variables displayed more interannual variation in shallow (depth ≤ 6 m) lakes than in deep lakes. Overall, our results demonstrate that arctic zooplankton communities have high resistance to the effects of climate change but potentially low recovery or long recovery times to pulse disturbances.

Alaska↗
USGS2026

Assessing low-dose copper treatment for dreissenid mussels: Effects on nontarget organisms

Zebra mussels ( Dreissena polymorpha ), an invasive dreissenid mussel, have been established and caused considerable effects in many North American aquatic ecosystems. In response, copper-based pesticides have been used to manage zebra mussel populations. We evaluated the effects of a low-dose (60 µg Cu/L for 10 d) copper-based molluscicide for zebra mussel suppression on nontarget species in Lake Minnetonka (Minnesota, USA). Specifically, we assessed changes in four fish species, a native mussel species, adult zebra mussels, chlorophyll-a concentrations (as a proxy for phytoplankton productivity), the zooplankton community, and the benthic invertebrate community before and after treatment. Chlorophyll- a concentration increased in both the treated and reference bays 1 and 4 d posttreatment. Non-target zooplankton community composition changed in both bays over the course of this study; zooplankton abundance and diversity initially decreased in the treated bay but gradually recovered and was back to pretreatment and reference bay levels after one year. We observed no significant differences in non-target benthic invertebrate abundance or diversity between the treated and reference bays, although abundance and diversity estimates were dynamic and uncertain. Among caged non-target organisms, copper bioaccumulation was higher in both mussel species than in fish, and among fish, was highest in fathead minnow ( Pimephales promelas ). These findings contribute to our understanding of the potential effects of copper-based pesticides on aquatic ecosystems and provide insights for zebra mussel management.

Minnesota↗
USGS2026

Assessing a low-dose copper treatment for dreissenid mussels: Effects on zebra mussel (Dreissena polymorpha) population

We conducted and evaluated a low-dose copper treatment (applied as EarthTec QZ) to suppress zebra mussel ( Dreissena polymorpha Pallas 1771) veliger abundance and settlement in a 66.3 ha bay in Lake Minnetonka (Hennepin County, MN) over a 3-y period. We maintained a mean (standard deviation [SD]) concentration of 83.0 (10.3) µg/L as copper over the 10-d treatment period, much lower than the maximum allowable 1 mg/L as copper. Veliger density was reduced from 6.0 veligers/L before treatment to 0.3 veligers/L following the treatment period. Posttreatment zebra mussel settlement was 1900 times lower in the treated bay compared to an untreated bay days after the treatment despite similar pretreatment veliger densities. Veliger density and settlement remained suppressed nearly 2 y following the treatment. Sampling for adult zebra mussels within the treated bay returned variable results but survival of caged adult zebra mussels indicated ~30% treatment-related mortality. Copper in surface waters returned to near pretreatment concentrations 90 d after treatment. Our study demonstrates that low-dose applications of a copper molluscicide can effectively reduce zebra mussel veliger densities and settlement.

Minnesota↗
USGS2026

Climate-driven changes in wetland hydroperiods predict losses in habitat suitability for amphibian breeding

Environmental regimes are shifting with accelerating climate change, disrupting interactions between species and ecosystems shaped by the climate of the pre-industrial era. Species assemblages that depend on a dynamic network of ephemeral and permanent habitats may be especially sensitive to changing climate, whereby shifting environmental regimes may limit species persistence in landscapes in ways not captured by species physiology or coarse habitat metrics alone. Here we forecasted the loss of montane and subalpine wetlands as breeding habitat for three amphibian species in the US Pacific Northwest, Ambystoma gracile , Ambystoma macrodactylum , and Rana cascadae . We combined historical and recent surveys to build occupancy models of current breeding habitat use. We combined these results with existing hydrological models to predict the loss of suitable breeding habitats by the 2080s due to increased wetland drying. We found that species-specific occupancy of wetlands used for reproduction was predicted by both abiotic (e.g., elevation, wetland area) and biotic (e.g., emergent vegetation) site-level characteristics. Among wetlands currently used for reproduction, we estimated that between 12% and 23% could become unsuitable for the aquatic phase of each species by the 2080s, with watershed-scale losses ranging from 0% to 80%. This suggests that wetland habitat loss could limit the persistence of these species in the Pacific Northwest, though impacts are expected to vary across landscapes. More broadly, we demonstrate a novel approach to quantifying species climate change vulnerability that can be used to identify areas of both risk and resilience in changing landscapes and help to prioritize the application of practical conservation solutions in areas of greatest need.

Washington↗
USGS2026

Predicting Minnesota lake ice phenology with deep learning, explainable methods, and a physically based benchmark, 1980-2018

Globally, lakes are losing ice cover, but our understanding of the rates and variability of change are biased toward few lakes with long-term records. Recent works have used remote sensing and predictive modeling to supplement the observational record, but these approaches produce large errors when estimating ice phenology for individual lakes. Accurate, lake-specific estimates of ice formation and breakup through time are important for estimating variability in ice loss across heterogenous lakes and for understanding broader implications. This work explores machine learning (ML) approaches for hindcasting ice phenology using observations from 1980 to 2018 across 625 Minnesota lakes, covering 4359 lake-years of record. We used daily weather and static lake attributes to develop 60 neural networks for hindcasting lake ice time series. We considered LSTMs and attention-based transformers of varying size and initial parameters. We found that the largest LSTM performed most accurately on withheld data, and on a test set of unseen years and lakes, it outperformed a state-of-the-art physically based model in daily accuracy (97% vs. 95%), year-level metrics (RMSE for ice formation = 6.9 vs. 13.2 days; ice breakup = 7.5 vs. 12.2 days; ice duration = 9.6 vs. 13.7 days), and estimating loss of ice cover from 1980 to 2018 (observed = 8.4 days, LSTM = 7.2 days, GLM = 3.4 days). This demonstrates that ML can estimate historical lake ice formation and breakup dates within a week of observed phenology across heterogeneous lakes and recreate broad scale trends in ice cover phenology with limited long-term ice records.

Minnesota↗
USGS2026

Sediment vulnerability ranking for river basins across the contiguous U.S. using integrated biophysical and social-ecological data

Nearly half of streams and rivers in the United States (U.S.) have fair to poor conditions for aquatic ecosystem health as declared by the U.S. Environmental Protection Agency, and sediment was identified as a primary factor impairing these waterbodies. We rank sediment vulnerability using physical, ecological, and socioeconomic datasets in 163 4-digit Hydrologic Unit Codes within 18 regions across the contiguous U.S. based on the National Hydrography Dataset. We refer to sediment vulnerability as the potential for excess sediment to adversely impact social-ecological aspects of streams and rivers. Metrics were organized into six variable groups: (1) geomorphic setting, (2) modeled sediment and phosphorus, (3) hydrologic conditions, (4) anthropogenic factors and land use, (5) socioeconomic considerations, and (6) measures of ecosystem sensitivity. Correlations and principal component analysis were used to reduce and select metrics that explained the highest variability across basins. Results from the regional analysis identify basins with higher sediment vulnerability in each region, whereas national results identify hotspots of highly ranked basins in the Midwest and the central U.S. with a concentration of moderately to highly ranked basins in the south-central and southwestern U.S. Indicators of socioeconomic and ecological vulnerability integrated with physical drivers of sediment production help identify important gaps in sediment monitoring and research.

contiguous United States↗
USGS2026

Climate change vulnerability assessment for guiding ecosystem restoration in fire-prone landscapes of the western U.S.

Climate-driven alterations to fire regimes challenges forest management and restoration in the western United States, where increased wildfire severity threatens ecosystem integrity and resilience. In this study, we demonstrate the application of the FireCLIME (Fire-Climate-Landscape Interactions in Montane Ecosystems) Vulnerability Assessment (VA) as a decision-support tool for evaluating management actions, including restoration strategies, under climate uncertainty. Through collaborative workshops with USDA Forest Service managers, we assessed three project areas in two national forests: Lincoln National Forest (LNF, New Mexico) and Bighorn National Forest (BNF, Wyoming). These two locations represent distinct climate zones, forest ecosystems, and fire regimes. We examined how changing climate and fire regimes affect ecosystem vulnerability with the FireCLIME VA, which integrates exposure to climate and fire regime changes, ecosystem response factors, and adaptive capacity via management intervention to compare vulnerability outcomes relative to desired future conditions (DFC). Results revealed that forests that departed more from historical conditions (LNF) exhibited greater vulnerability. Soil burn severity and associated erosion emerged as common vulnerability drivers across all sites. For both forests, treatments were able to reduce departure from DFC. Treatment effectiveness varied by ecosystem type; some interventions demonstrated broad capacity to lower vulnerability and achieve DFC for a wide range of components, while others had more targeted effects for specific components. This assessment framework reveals substantial synergy between climate adaptation planning and restoration ecology principles, suggesting that vulnerability assessments can effectively guide restoration planning under climate uncertainty by balancing risk reduction with ecosystem resilience enhancement.

New Mexico, Wyoming↗
USGS2026

Incorporating wetland drowning thresholds to assess the spatiotemporal variability in potential wetland migration and submergence from sea-level rise

In the coming decades sea-level rise rates could exceed the upper bounds of coastal wetland vertical movement leading to wetland submergence. Consequently, understanding the spatiotemporal variability of wetland migration and submergence at regional and national scales can inform decision making. In this study, we developed an approach that addresses elevation error in digital elevation models for wetlands, incorporates uncertainty in current and future water levels, and utilizes recent literature on coastal wetland drowning thresholds. We used our framework to predict wetland change with sea-level rise for the middle and upper Texas coast—a region that is experiencing some of the highest relative sea-level rise rates in the United States. Our elevation-based approach produced contemporary wetland maps that had a high level of agreement (> 87–91%) with existing national wetland maps. For the intermediate relative sea-level rise scenario, extensive change is predicted within the study area by 2100, including a net decrease in coverage of irregularly oceanic-flooded wetlands (-37%) and regularly oceanic-flooded wetlands (-23%). The wetland migration space of these two wetland zones is largely made up of existing wetlands (> 70%), but also includes other upland areas, such as pasture/hay and grassland. By breaking down our results for the full region and two distinct focal areas, we highlight the spatiotemporal variability of wetland change. Our scalable approach provides natural resource managers with information for developing location-specific strategies for balancing the trade-offs associated with wetland change from sea-level rise.

Texas↗
USGS2026

ETAS-positive: Extracting unbiased epidemic-type aftershock models from incomplete earthquake catalogs

Earthquake catalogs are inherently incomplete, and short-term fluctuations in catalog completeness can strongly bias estimates of seismicity parameters. Here, we extend the positive statistics framework recently introduced for estimating Gutenberg–Richter a and b values to the Epidemic-Type Aftershock Sequence (ETAS) model. The approach focuses on complete magnitude–time intervals defined by pairs of earthquakes in which the second event is larger than the first. Comprehensive synthetic tests demonstrate that the proposed ETAS + method retrieves nearly unbiased parameter estimates even from highly incomplete catalogs, whereas parameters obtained using classical estimation approaches are strongly biased. Application to Southern California reveals a similar trend, with the productivity scaling parameter α approaching the b value, consistent with self-similar earthquake triggering within estimation uncertainties. Owing to its robustness against catalog incompleteness and computational efficiency, the ETAS + method provides a powerful new tool for seismicity analysis and earthquake forecasting.

California↗
USGS2026

Cyanobacteria Assessment Network: Pilot study with Sentinel-2 derived chlorophyll data

Harmful algal blooms (HABs) affect global water quality, limiting uses like recreation and consumption because of excessive algal biomass and toxin production. These blooms cause surface scums, taste and odor issues, hypoxia, and negative health and socioeconomic impacts. The US Army Corps of Engineers (USACE) manages over 400 lakes and reservoirs and seeks to improve monitoring of HABs through Sentinel-2 (S2) satellite imagery. The purpose of this project is to develop workflows for a national chlorophyll-a product with 20 m spatial resolution, enabling HAB monitoring for over 270,000 lakes and reservoirs. The 1-year pilot study established a federal partnership to conduct preliminary S2 processing steps, using datasets from Florida, Ohio, and Oregon. Key steps included in situ data aggregation, data assimilation, S2 algorithm evaluation, spatial and temporal compositing, satellite sensor cross-validation, and web hosting of an example prototype product. The study covers 29 USACE reservoirs, with cross-validation using Sentinel-3 (S3) data from 212 lakes. The multiagency initiative aligns with federal agency missions to protect health and the environment, supports acts like the 2017 Harmful Algal Bloom and Hypoxia Research and Control Act, and has annual potential avoided costs of $42 million.

contiguous United States↗
USGS2026

High-resolution landscape-scale maps of nutrients, phytoplankton, and related water-quality constituents in Suisun Bay and the Sacramento–San Joaquin Delta, California, during 2018—Results from high-resolution underway surveys

We examined the abundance and distribution of nutrients and phytoplankton in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) and Suisun, Grizzly, and Honker Bays in California by completing three spatial surveys that used continuous underway high frequency (1 hertz) measurements and sampling onboard a high-speed boat. Surveys were conducted in May, July, and October 2018. Water was sampled continuously during surveys to simultaneously collect information about the concentration and spatial distribution of all major nutrient forms together with information about the major classes of phytoplankton and associated standard field measurements of water quality, such as dissolved oxygen, dissolved organic matter, pH, salinity, specific conductance, turbidity, and water temperature. The results show a greater than 50-fold variation in nutrient and phytoplankton concentrations across space and time, providing evidence of the dynamic environmental processes that shape the ways nutrients interact with and affect Delta aquatic habitats.

California↗
USGS2026

At the edge of change: Native Phragmites persistence and nonnative arrival along the dam-regulated Colorado River

Premise The southwestern United States is at the forefront of nonnative Phragmites australis subsp. australis expansion. Native Phragmites australis subsp. americanus , likely in decline in North America, is ecologically and culturally important and of conservation interest. In the greater Grand Canyon region, the Glen Canyon Dam led to loss of habitat upstream and increases in Phragmites downstream. Recent increases correspond with changes to dam operations and the arrival of nonnative Phragmites . Determining the native status of Phragmites stands along the Colorado River and around Lake Powell can inform complex management choices and restoration planning. Methods Phragmites subspecies at 83 locations from southern Utah through northern Arizona, United States were genetically tested using real-time PCR. Genetic diversity and structure were assessed using microsatellite loci for 13 native Phragmites stands. Morphological traits of southwestern native Phragmites were compared to those of nonnative Phragmites . Results Nonnative Phragmites was identified at four of the 83 locations. Native Phragmites in the study area is genetically diverse with little regional genetic structure, but substantial genetic differentiation among sites. Southwestern native Phragmites is morphologically variable, but characteristics can be used together to distinguish it from nonnative Phragmites . Conclusions The greater Grand Canyon and Glen Canyon regions support a large, genetically diverse native Phragmites population, which is potentially threatened by nonnative Phragmites and changes to river management. Determining conditions that would lead to nonnative Phragmites invasion of desert wetlands will facilitate discussions about the risks and benefits of Phragmites management in these unique ecosystems.

Arizona, Nevada, Utah↗
USGS2026

Deep learning models for mapping surficial geology in selected physiographic regions of New York

Surficial geologic mapping is required for decisions including infrastructure and water-resource development and management. Deep learning, a type of machine learning that uses training data to self-learn and perform tasks, is explored as a tool to help increase efficiency of the labour- and time-intensive mapping process. Deep learning models were trained, and their potential to aid in mapping surficial geology was explored for two physiographic regions in New York: the high-relief Allegheny Plateau and the low-relief Erie-Ontario Lowlands. Key to the development of deep learning models is the availability of highly detailed surficial geologic maps in each of these regions from which the models can learn. Through exploring different groupings of surficial deposits and their corresponding spatial data, deep learning models were iteratively developed to reproduce published mapping for greater than 79% of the training areas, and with similar accuracy in test areas within the same physiographic region. These models were trained using only two inputs: high-resolution lidar data and previously published surficial geologic maps. This straightforward approach is intended to make the methods and models created easily reproducible using widely accessible datasets. This research describes the strengths and limitations of lidar-derived surficial geologic models and how broadly grouping surficial types, characteristics of different physiographic regions, and testing models in physiographic regions outside of their training areas affect model creation and performance. In addition, the models created could be used as a tool for mapping surficial geology in similar physiographic regions, in addition to establishing a framework for creating similar models elsewhere.

New York↗
USGS2026

The rising threat of lead: Trends in fatalities of California condors

Endangered species face threats that change over time, and understanding variation in the importance of threats is valuable for guiding species recovery. The reintroduced population of critically endangered California condors has faced a number of threats over the three decades since the species was first released back to the wild. We modeled interannual and interseasonal trends in the leading causes of death for wild condors. Our analysis showed strong evidence ( P = 0.971) that the estimated annual probability of death from lead toxicosis has increased since reintroduction started. This increase was most pronounced in the central California subpopulation. Adults were disproportionately affected by lead toxicosis, a trend that may be explained by increased exposure associated with age-related changes in foraging behavior that lead to decreased reliance on clean proffered food sources. Population-level mortality from trauma showed a temporary increase in 2012, and fire-related mortality was higher during the summer months. Pattens also varied across subpopulations, with the southern California subpopulation of condors showing distinct temporal peaks in deaths from trauma (in 2012) and predation (in 2010). Our analysis suggests that threats to condors have not been static over space and time. Managers can therefore use this information to adaptively manage and target mitigation efforts when and where they are the most effective.

California↗
USGS2026

Depositional environment and diagenetic history of gas hydrate-bearing sediments of the Alaska North Slope (HYDRATE 02 Geo Data Well)

We characterized the lithological, solid-phase geochemical, and rock magnetic properties of sediment cores from subpermafrost strata on the Alaska North Slope collected as part of the U.S. Department of Energy (DOE), the Japan Organization for Metals and Energy Security (JOGMEC), and the U.S. Geological Survey (USGS) Collaborative Gas Hydrate Research and Development (R&D) Project in Alaska. Pressure cores were recovered from the HYDRATE 02 Geo Data Well (GDW) at the Kuparuk State 7-11-12 site through two hydrate-bearing sand reservoirs, the B1 and D1 sands, and their finer-grained bounding sediments. Both the B1 and D1 sands are quartz-rich, chert-bearing, very fine litharenite sands. These submature to immature sands are poorly to moderately sorted and angular with local fine-scale cross-stratification. The B1 sand has larger grains and a lower clay content as compared to the D1 sand. These sands are the upper portions of upward coarsening progradational sequences. The clay- and silt-rich bounding muds exhibit fine-scale wavy and lenticular laminations, suggesting episodic high energy deposition events. Overall, these sediments were deposited in a shoreface to nearshore marine environment during the Paleogene, modulated by changing depositional energy associated with sea level variation. Organic matter δ 13 C and C/N composition of these sediments indicate a source mixture of land plants and freshwater plankton, with possible minor presence of oil within the B1 sand. These sediments contain high and variable total sulfur (TS) content, suggesting porewater conditions influenced by variable salinity over time. Rock magnetic analyses indicate precipitation of greigite in the mud beneath the D1 sand, in the basal C shale overlying the B1 sand, and the mud beneath the B1 sand, likely due to intervals of sulfate limitation during periods of lower Arctic Ocean salinity. Based on pyrite abundance, TS, and δ 34 S-TS composition, the D1 sand and bounding sediments experienced more substantial sulfide precipitation. The unit E basal shale overlying the D1 sand contains a 0.25 m thick pyrite-dominant sand, indicating local bottom water anoxic conditions. X-ray fluorescence scanning and discrete measurements provide additional supporting interpretation of the depositional and diagenetic processes that have occurred at this site and track the relative amount of drilling fluid contamination with barium abundance in the core samples.

Alaska↗