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89 records · Page 3Linked to original sources
USGS2025

Beavers in the Tualatin River Basin, northwestern Oregon

Growing interest in beaver-assisted restoration in the Tualatin River Basin of northwestern Oregon motivated a series of studies by the U.S. Geological Survey to assess the capacity of the stream network to support beaver dams and to evaluate the effects of beaver dams and ponds on urban streams. This multichapter volume describes the data collection from 2016–17 and the findings of these studies, which were done in partnership with Clean Water Services. Chapter A documents the locations of beaver dams in the Tualatin River Basin and how many beaver dams the stream network could support with existing and improved riparian vegetation. Beaver dam capacity was estimated by modifying existing tools to account for the low gradient of many streams in the Tualatin River Basin. Chapter B describes the effects of beaver dams and ponds on hydrologic and hydraulic responses of storm flows. Hydrologic and hydraulic responses for two urban stream reaches were compared with and without beaver dams and ponds and for a range of streamflow conditions using two-dimensional hydraulic models. Chapter C characterizes the effects of beaver dams and ponds on the transport and deposition of suspended sediment. Continuous turbidity, discrete suspended-sediment samples, and streamflow measurements collected during storms and base-flow periods were used to assess: (1) suspended-sediment loads upstream and downstream from two beaver-affected reaches, and (2) seasonal and longitudinal turbidity patterns. Chapter D describes the effects of beaver dams and ponds on longitudinal, spatial, and seasonal water-quality patterns. Continuous and synoptic water-quality data were collected along urban stream reaches, and net ecosystem production was calculated for two beaver-affected reaches. The findings of these studies illustrate that the effects of beaver dams and ponds on hydrology, hydraulics, suspended-sediment transport and deposition, and water quality are dependent on the characteristics of a stream reach (for example, channel gradient, groundwater exchange, and riparian vegetation) and the characteristics of beaver dams and ponds along that reach. This information can be used to consider the implications of beaver-assisted restoration in the Tualatin River Basin and the effects of beaver dams and ponds in urban streams.

Oregon↗
USGS2026

Advancing outreach effectiveness to improve conservation practice adoption

Agricultural conservation practices are central to achieving Chesapeake Bay watershed restoration goals, yet long-term adoption remains challenging even when practices are technically effective and financial assistance is available. Adoption is not a single decision, but a staged and context-dependent process. Awareness and willingness to commitment, implementation, and persistence, are all important. Progress along this pathway is influenced by interacting factors such as knowledge, attitudes, beliefs, social norms, trust, perceived risk, farm characteristics, and practical constraints. Improving adoption requires outreach strategies that respond to the specific factors limiting progress at each stage rather than relying on a one-size-fits-all approach.

Chesapeake Bay watershed↗
USGS2026

Hydrological control on soil redox condition and carbon loss of coastal wetland under sea-kevel rise

Coastal wetlands are critical carbon sinks with their biogeochemical and ecological functioning shaped by dynamic hydrological conditions that are increasingly influenced by climate change. A key unresolved question is how hydrologic flow, vegetation response, and rising sea levels interact to regulate soil redox condition and carbon loss in coastal wetlands. Using a field-tested hydrological–biogeochemical–ecological modeling framework, we reveal how the interplay between terrestrial groundwater discharge and tidal fluctuations generates complex groundwater flow patterns at the terrestrial–aquatic interface, and how these patterns modulate soil redox conditions, in turn influencing soil organic matter decomposition and carbon loss. Notably, rising sea levels suppress soil CO 2 emissions while reducing lateral dissolved carbon losses, thereby enhancing litter carbon sequestration under anoxic conditions. As vegetation responds to sea-level rise and carbon inputs diminish, litter carbon subsequently declines. These findings underscore a critical hydrological control on carbon cycling, advancing our understanding of coastal ecosystem resilience in a warming world.

Louisiana↗
USGS2025

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California↗
USGS2026

Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages

Introduction: Hydrologic variability is a key driver of ecological structure in lotic systems, shaping habitat conditions, taxonomic diversity, and the functional traits that mediate species’ persistence and performance (e.g., reproductive success). While many studies examine taxonomic responses to variation in flows, few evaluate how spatiotemporal hydrologic variation influences the functional organization within stream fish communities. Methods: We quantified seasonal habitat structure and functional trait diversity of fish assemblages across six Ozark Plateau headwater streams representing two contrasting flow regimes: Groundwater Flashy and Runoff/Intermittent Flashy. Fish and habitat data were collected seasonally during a dry year (2002) and a wet year (2003). Functional space was constructed using PCoA of morphological, ecological, and life-history traits, and functional diversity was measured using community weighted means (CWMs), functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv). Results: We found that habitat structure differed strongly by flow regime and season, with Runoff/Intermittent streams exhibiting pronounced reductions in depth, area, and velocity, while groundwater streams remained structurally stable. Functional identity of assemblages was similar across flow regimes, dominated by benthic, hydrodynamic taxa with opportunistic and periodic life-history strategies. However, functional structure differed significantly: FEve and FDiv were consistently lower in Runoff/Intermittent Flashy streams in both years, indicating assemblage dominance of species with similar trait combinations and reduced trait partitioning under variable flow. FRic and taxonomic richness remained stable across seasons and flow regimes, suggesting high functional redundancy despite species turnover. Discussion: Together, results show that flow regime mediates both habitat structural stability and functional organization. As climatic warming and extreme drought increase hydrologic instability in headwaters, functional trait approaches provide a sensitive tool for detecting losses of functional roles that may not be evident by using taxonomic metrics alone.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2026

Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data

Ecological models should account for uncertainty to be most effective and useful. Yet, uncertainty from model covariates—unlike that from other sources, such as sampling error or process variability—is seldom explicitly incorporated. This can cause underestimates of uncertainty to cascade through model parameter estimates, predictions, and downstream uses. Burner et al. proposed a method for quantifying uncertainty in covariates and incorporating it into models using informative Bayesian priors. This method was applied to stop-level Breeding Bird Survey (BBS) analyses, where land cover uncertainty at each stop arises from substantial stop location uncertainty. A limited validation of model-estimated land cover, using stops with known locations, indicated the method’s potential effectiveness, but it was not rigorously evaluated. We conduct a robust simulation-based test, generating stop locations, extracting land cover, and simulating bird communities across 210 BBS routes in the upper Midwest. We compare 3 models: a “known” model with true land cover, a “naive” model assuming consistent 800-m stop spacing, and a “full” model using informative priors to estimate land cover. Species parameter estimates and predicted prevalence patterns across gradients in land cover from the full model approached those of the known model and were substantially closer to the true values used in simulations relative to those from the naive model. Naive model parameters were more biased relative to the other models, and credible intervals of predicted species prevalence rarely included the true simulated values. The full model also produced land cover covariate estimates closer to true simulation values relative to the mean informative priors. Our results show that, for the BBS, informative priors enable more accurate stop-level analyses despite location uncertainty. In contrast, naive models that ignore this uncertainty yield poor inferences. More broadly, we demonstrate empirically the utility of informative priors to account for covariate uncertainty in ecological models.

Michigan, Minnesota, Wisconson↗
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↗
USGS2025

Evidence for offset of Cretaceous plutons by the Tintina fault in eastern Alaska: Implications for regional metallogeny

Cretaceous magmatism in eastern interior Alaska is voluminous, but temporally and spatially diverse – suggestive of varying sources and drivers. More than 150 new U-Pb zircon and more than 500 geochemical analyses of Cretaceous plutonic units allow for the grouping of distinct plutonic suites. Magmatism was continuous from 120-66 Ma but can be grouped into temporally distinct pulses from ca. 115-100 Ma, 100-90 Ma, and 75-66 Ma. Geochemical diversity occurs during each pulse, further distinguishing multiple suites. Diverse metallogenic epochs are strongly correlated to pluton chemistry. Mineralization is largely absent prior to 108 Ma. From 108-100 Ma, plutonism is coeval with sparse, but notable Au-quartz veins with variable Bi, As, W, and Mo. From 100-90 Ma, intrusion-related mineralization zones from Au-Cu(-Bi) and U-Th in the northwest to central Au- Bi-As-Te(-W), and Mo-W to the southeast. Porphyry style Cu-Mo(-Au) occurrences occur with the latest Cretaceous plutons emplaced from 75-66 Ma . Restoration of ~450 km of dextral movement on the Tintina fault and comparison of metallogenic and geochemical characteristics of Alaska plutons suggest 100-90 Ma plutons may be the continuation of the metallogenically significant Tombstone, Mayo, and Tungsten suites from the Yukon.

Alaska↗
USGS2026

Modeled groundwater and surface-water interactions surrounding Mobile Bay, Alabama, 2008–15

The U.S. Geological Survey, in cooperation with the Gulf Coast Ecosystem Restoration Council, has used MODFLOW 6 to develop a groundwater-flow model to simulate groundwater and surface-water interactions in the Mobile Bay, Alabama, area. The model results indicated that, on average, groundwater discharge near the coastline is equal to 2.5 percent of the surface water that flows into the bay. The model was also used to determine how changes in recharge, sea level, and groundwater pumping affect groundwater levels and discharge rates. The results indicate that more groundwater discharge occurred in the winter and spring when recharge was higher, sea level was lower, and groundwater pumping was lower than during the summer and fall. Additionally, the amount of emergent groundwater was closely related to sea level; when sea level was higher, there was more area with emergent groundwater. Furthermore, the depth of nonemergent groundwater was related to trends in recharge and pumping. During periods of increased recharge and reduced pumping, a significant portion of the model area exhibited a depth to the water table of less than 1 meter below the land surface. Conversely, during periods of decreased recharge and heightened pumping, much of the model area showed a depth to the water table ranging from 1 to 5 meters.

Alabama, Mississippi↗
USGS2025

Groundwater structures fish growth and production across a riverscape

Landscapes are composed of habitat patches and conditions that vary across space and time. While habitat variability and complexity can support important ecological processes and ecosystem services, the dynamic nature of habitats can also constrain organismal growth and production as optimal conditions are fleeting. In riverine ecosystems, groundwater discharge to streams stabilises water temperature and flow regimes, thus mediating how habitat complexity is expressed. Yet, how stable habitats structure growth and production within the broader landscape matrix is not well understood. In this study, we explored the effects of groundwater on spatiotemporal variation in growth and production for juvenile Yellowstone cutthroat trout ( Oncorhynchus virginalis bouvieri ) across the upper Snake River catchment, Wyoming, USA. We combined machine learning techniques and remotely sensed landscape data to estimate groundwater availability across the river network, which we linked to stream temperature regimes and conspecific density. We then used Bayesian hierarchical models to quantify the effects of temperature, density and groundwater on spatiotemporal variation in fish growth and production in 52 focal reaches. Finally, we predicted body size trajectories and trends in total production continuously over both space and time to understand the effect of groundwater at the riverscape scale. Groundwater discharged to streams where topography changes abruptly in valley-bottom areas underlain by coarse glacial deposits. Groundwater stabilised temperature regimes and was associated with high trout densities. Temperature and density, in turn, interacted to influence growth rates: growth increased strongly with temperature, but this effect was reduced when density was high. Accordingly, variation in groundwater availability among stream reaches diversified growth and production regimes. In reaches with low groundwater availability, growth and production declined over time from summer maxima. In contrast, in reaches with high groundwater availability, temporal trends in growth and production were hump-shaped—peaking in autumn—and mean production was greater. At the riverscape scale, temporal asynchrony in growth rates generated convergent spatial variation in growth capacity, but—when combined with density—led to the formation of distinct hotspots of production. Our results demonstrate how groundwater, an important driver of aquatic ecosystem heterogeneity, structures trout growth and production across space and time. Importantly, rare, but stable habitats may disproportionately affect ecological processes and serve as key sources of population diversity at larger spatial scales.

Wyoming↗
USGS2025

Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts

Study Region Cape Cod, Massachusetts, U.S.A. Study Focus Anthropogenic nitrogen (N) is a key factor in degrading groundwater and surface-water quality, particularly in coastal New England where onsite wastewater systems are prevalent. This study evaluated whether direct N-load measurements in streams on Cape Cod, Massachusetts, coupled with flow-path information from groundwater-flow models, can effectively identify potential land areas where nitrogen mitigation could substantially reduce loads to receiving waters. Nitrogen fluxes were measured along 63 stream reaches during winter and summer and paired with simulated groundwater recharge areas to identify and rank potential areas for reduction of nonpoint-source N inputs. New Hydrologic Insights for the Region Reach-scale nitrate-N loads ranged from −39.1–1182 kg-N/yr per 100 m of stream, indicating spatially variable groundwater inputs across seasons. “Reachsheds” — areas contributing groundwater recharge to specific stream reaches — were delineated using a regional groundwater-flow model. Strong correlations were found between observed N loads and land-use characteristics, especially the number of septic systems and total N inputs from the sum of considered sources. Observed N loads were moderately correlated with recharge area size and wastewater flow estimates. Correlating reach-specific groundwater N loads with land use and parcel-scale nitrogen-yield data identified reachsheds with the highest potential for N load reduction. This approach enables targeted implementation of restoration efforts to optimize nutrient management and support regional load reduction.

Massachusetts↗
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↗
USGS2026

Widespread landslide activity in an extreme wet season and implications for regional sediment management, eastern San Francisco Bay area, California

Watershed sediment production is expected to increase in a warmer future with more extreme rain, with cascading effects throughout drainage and sediment-transport networks. This study investigated landscape-scale sediment movement in the eastern San Francisco Bay area, California, USA, during the extreme 2016–2017 wet season that brought major rainfall, landslides, and flooding. Mapping 8,928 landslides across a 1,050-km 2 study area revealed new sediment yield of 510–956 t/km 2 , equivalent to denudation of 193–361 mm/ky. These results correspond closely to long-term denudation rates in the northern and central California Coast Ranges, indicating that mass wasting in very wet years dominates long-term sediment mobilization. However, due to long residence times in drainage networks, the 2017 landslides contributed at most ∼1%–2% of the estimated locally derived fluvial sediment transport to San Francisco Bay. Although the amount of sediment mobilized did not threaten municipal water supplies, small rangeland impoundments in this mixed-use landscape lost storage capacity to new sedimentation. Considering regional sediment supply and demand, even the exceptionally large sediment delivery in an extreme wet year cannot meet the need for sediment to accrete tidal wetlands in the bay. To keep pace with rising sea levels, this abnormally high terrestrial sediment input would need to occur in 50 of the next 75 years, an unlikely occurrence due to the prevalence of recent drought years. Shoreline protection and restoration in the bay would need additional sources of sediment, such as through management of dredged sediment through beneficial-reuse programs.

California↗
USGS2025

Observing northern high-latitude river systems to understand changes in a warming Arctic

Purpose of Review Streams and rivers are undergoing rapid change as the Arctic warms and thaws. We review recent observations in Arctic stream systems to identify ubiquitous changes and the most useful tools for observing change and exploring the underlying processes. Recent Findings Recent literature indicates increasingly significant trends in river hydrology and chemistry due to persistent warming in the Arctic and longer observational records for analysis. However, regional differences in the magnitude and direction of these trends persist. We also observe thresholds in ground thaw and surface–groundwater interactions that can impact river hydrology and chemistry. Summary Warming and thaw are occurring rapidly at high latitudes, resulting in increasing, yet variable responses in stream systems across regions and scales. These differences highlight the need for long-term records and an interdisciplinary approach to explain trends and predict future states. Stream systems respond to multiple landscape changes related to hydrology (changing precipitation and subsurface flow), geology (ground thaw dynamics), and ecology (vegetation change).

Current Climate Change Reports↗
USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗
USGS2025

Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm

Stream temperature controls a variety of physical and biological processes that affect ecosystems, human health, and economic activities. We used 42 years (1979–2021) of data to predict daily summary statistics of stream temperature across >50,000 stream reaches in the contiguous United States using a recurrent graph convolution network. We comprehensively documented the performance – both across all reaches and by stream type (e.g., reservoir or groundwater influence) – as a baseline for future improvement. The model showed reach-level RMSE of <2 °C with 90 % prediction intervals that contain 90.7 % of observations. We also assessed how the model captured variability in ecologically relevant metrics (e.g., R 2 for annual 7-day maximum = 0.76; R 2 for days exceeding 25 °C = 0.75). This model does not outperform state-of-the-art machine learning efforts (e.g., RMSE ≤1.5 °C) due to a limited input set but does provide the most spatially complete modeling to date to support water availability assessments.

contiguous United States↗
USGS2025

Simulated effects of future water availability and protected species habitat in a perennial wetland, Santa Barbara County, California

This study evaluates the potential water availability in Barka Slough and the effects of changing hydrological conditions on the aquatic habitat of five protected species. Barka Slough is a historically perennial wetland at the downstream western end of the San Antonio Creek Valley watershed (SACVW). A previously published hydrologic model of the SACVW for 1948–2018 was extended to include 2019–2021 and then modified to simulate the future years of 2022–2051. Two models simulating the future years of 2022–2051 were constructed, each with different climate inputs: (1) a repeated historical climate and (2) a 2070-centered Drier Extreme Warming climate (2070 DEW). The model with the 2070 DEW climate had warmer temperatures and an increase in average annual precipitation driven by larger, albeit more infrequent, precipitation events than the model with the historical climate. Simulated groundwater pumpage resulted in cumulative groundwater storage depletion and groundwater-level decline in Barka Slough in both future models. The simulations indicate that Barka Slough may transition from a perennial to an ephemeral wetland. Streamflow, stream disconnection, and depth to groundwater are key habitat metrics for federally listed species in Barka Slough. Future seasonal conditions for each metric are more likely to affect federally listed species’ habitats under 2070 DEW climatic conditions. Future seasonal streamflow volume may negatively impact unarmored threespine stickleback ( Gasterosteus aculeatus williamsoni ) and tidewater goby ( Eucyclogobis newberryi) habitats. Future seasonal stream disconnection may negatively impact the unarmored threespine stickleback habitat. Future groundwater-level decline may negatively impact Gambel’s watercress ( Nasturtium gambelii ) and La Graciosa thistle ( Cirsium scariosum var. loncholepis ) habitats and could influence the ability to use Barka Slough as a restoration or reintroduction site for these species. Results from this study can be used to inform water management decisions to sustain future groundwater availability in the SACVW.

California↗
USGS2025

Characterization of stream water quality and groundwater levels in the Central Pine Barrens region, Suffolk County, New York, 2017–23

The area locally known as the “Central Pine Barrens” region, located in Suffolk County, New York, contains most of Long Island’s preserved and undeveloped land. This region overlays an aquifer system that provides potable groundwater for residents of Suffolk County. Between 2017 and 2023, the U.S. Geological Survey, in cooperation with the Central Pine Barrens Joint Planning & Policy Commission and the Town of Brookhaven, monitored groundwater levels and stream water quality in this region. Groundwater levels were measured monthly at five wells and continuously (15-minute intervals) at a sixth well. Water quality was monitored at five locations in the Carmans River and at two locations in the Peconic River, and samples were analyzed for major ions, trace elements, nutrients, pharmaceuticals, and pesticides. The major ion compositions at the sites were mainly sodium-chloride type waters, and compositions varied the most at the furthest upstream sites in both streams. Concentrations above aquatic-life criteria thresholds also occurred most frequently at the furthest upstream sites. The seasonal patterns of nutrient loads and concentrations varied between the Carmans and Peconic Rivers. Several organic compounds including pharmaceuticals, domestic use products, and pesticides were detected at low concentrations in both streams. Metformin was the most frequently detected pharmaceutical compound, and herbicides were the most frequently detected pesticide class. Water-quality conditions influenced by anthropogenic contributions are a result of current and historical land use, and these contributions include onsite wastewater disposal systems, commercial or domestic fertilizers and pesticides, and urban or industrial contaminants in road runoff. This study characterizes and improves understanding of the current hydrologic conditions in the Central Pine Barrens region and the study findings can help inform the development of plans to manage, protect, and restore water resources.

New York↗