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Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 37.6 billion barrels of oil and 281.6 trillion cubic feet of gas in 31 geologic provinces of South America and the Caribbean.
Mobile device location data offer a low-cost alternative for measuring visitation to outdoor recreation sites and are known to correlate with official visitation counts. Less is known about whether these data can recover recreation demand and consumer surplus comparable to surveybased methods. We compare travel cost models estimated using mobile device and survey data for 17 U.S. National Park Service sites. Results are mixed. We examine the roles of aggregation and sampling bias and use LASSO regression to assess whether sample and site characteristics explain discrepancies.
Per- and polyfluoroalkyl substances (PFAS) are a class of widespread, environmentally persistent compounds that pose a potential threat to wildlife and human health. Despite recent efforts to reduce the use of long-chain PFAS in industrial practices and commercial/consumer products, the persistence and solubility of PFAS have led to their detection in wildlife on a global scale. Osprey ( Pandion haliaetus ) have long been used as a sentinel species with an extensive history of serving as an effective bioindicator of contamination. Here we report on a large-scale evaluation of PFAS and potential health effects in osprey from the Chesapeake and Delaware Bays, USA. In 2011 and 2015, we collected plasma samples from osprey nestlings throughout the Chesapeake and Delaware Bay watersheds. We quantified 40 PFAS congeners in osprey plasma via liquid chromatography-mass spectrometry and analyzed plasma for indicators of immune and thyroid function, and plasma biochemistry. In all birds, perfluorooctanesulfonic acid (PFOS) was the most commonly detected PFAS, followed by perfluoroundecanoic acid, (PFUnA) and perfluorodecanoic acid (PFDA). In nestling plasma from Chesapeake Bay, PFOS tended to be a higher average contributor to PFAS profiles compared to samples from Delaware Bay. In contrast, long-chain perfluoroalkyl carboxylic acids (PFCAs) such as PFUnA and PFDA comprised larger percentages of total PFAS in osprey plasma from Delaware Bay relative to Chesapeake Bay. While some PFAS concentrations were associated with plasma health indicators, the proportion of variation explained was low. Overall, our study provides a more thorough understanding of PFAS presence in the Chesapeake and Delaware Bays and is one of the first to examine whether PFAS exposure is associated with adverse health effects in wildlife.
The monarch butterfly ( Danaus plexippus ) is a species of iconic cultural interest. Thanks to annual overwintering monarch counts at hundreds of locations in coastal California, we are able to track fluctuations with high temporal and spatial resolution. Between 1997 and 2024, monarch populations at overwintering sites in the western United States experienced severe dips, at times (2018–2020, 2023–2024) giving the appearance of a population collapse. From 2018 to present, the Pismo State Beach Overwintering Monarch Grove has conducted multiple counts during overwintering and geolocated counts of individual monarch clusters to specific trees within the site. This study determined how annual monarch population variability is influenced by both climate and prior year population density at the state, region, and overwintering-site scale. Furthermore, through a machine-learning process, we investigated how overwintering site configuration and structure drive monarch winter space-use dynamics within the Pismo Beach site. Our approach found monarchs exhibit a preference for specific overwintering sites in California, and that 64% of annual variability of counts across sites can be explained by climate and density dependence, with density dependence explaining 50% of total variability. Within the site we found very little regional climate effect, but individual trees, tree size, distance to boundary, and the amount of shade were all strong indicators of monarch presence. Additionally, only 11 out of 320 trees at the Pismo Beach site accounted for 83.6% of all counts over 6 years, highlighting how monarchs use specific trees and how tree structure may create preferred microclimates for clustering.
The salinity of inland freshwaters is rising globally, particularly in urban watersheds where winter road deicers are widely applied. Attributing stream salinity dynamics to specific sources and transport pathways remains challenging due to episodic salt inputs, engineered drainage, and strong coupling between hydrology and subsurface storage. We present a modeling framework that couples climate-driven deicer build-up and wash-off with transient transit time distribution theory to simulate salt transport through drainage, interflow, and groundwater pathways. Applied to an urban watershed in Northern Virginia (USA), the model reproduces ten years of high-frequency stream salinity measurements across daily-to-decadal timescales. The calibrated model implies an average deicer application of 206 tonnes Cl −1 yr −1 , or roughly one 20 kg bag of rock salt person −1 yr −1 when normalized by the 20,000 people living in the watershed. In winter months, higher infiltration routes a large fraction of snowmelt and deicers into shallow subsurface pathways, enhancing vadose-zone and interflow contributions to stream salinity. Limited subsurface storage capacity and seasonal hydrologic turnover flush excess chloride from the vadose zone and groundwater during subsequent summer storms. By linking climate-driven deicer inputs, hydrologic connectivity, and stream water age, the framework provides a transferable basis for diagnosing and managing freshwater salinization in urban watersheds.
Climate change is driving unprecedented declines in dominant, habitat-forming foundation species across marine and terrestrial ecosystems globally. As climatic novelty becomes the norm, ecosystem reassembly will become increasingly common. Predicting and understanding these transitions, and their implications for future ecosystem functioning, is essential for designing effective forward-looking management strategies. We explored 3 scenarios that describe a range of ecosystem reassembly trajectories following declines in previously dominant habitat-forming taxa: compensation, in which functionally similar subdominant or immigrating taxa maintain ecosystem structure and function; decline, in which no compensation occurs leading to loss of ecosystem structure and function; and transformation, in which the ecosystem present historically can no longer persist and shifts into a fundamentally different ecosystem type with distinct structure and function. This range of potential outcomes highlights the urgent need to assess the ecological feasibility and functional implications of potential management actions. Scientists and managers can work together to quantify local-scale climatic novelty and ecosystem resilience to better predict the most likely reassembly trajectories and identify management interventions that will optimize ecosystem function. This approach would allow for more proactive planning to support persistence of ecosystem structure and function, helping to future-proof ecosystem management in a rapidly changing world.
Managing ecosystems in an era of rapid change is inherently challenging not only because of uncertainty in future climate but also due to diverse responses of ecosystems to climate. Projections of ecological transformation alongside information about plausible vegetation trajectories can help land managers explore divergent scenarios and consider how modeled outcomes match their observations. Climate-analog impact models (AIMs) compare environmental information (e.g., vegetation types) between sets of climatically similar locations to infer change and can be used to identify multiple outcomes. We used AIMs to project changes in vegetation across the western United States under a mid-21st century climate scenario, characterize ecological transformation vulnerability based on projection divergence, and demonstrate how AIMs can inform decision-making. We projected high or very high vulnerability to ecological transformation across 29% of the western US, nearly 1 M km 2 . Vulnerability varied among vegetation groups; 75% of alpine vegetation had high or very high vulnerability vs. 6% of desert scrub. We estimate that 9% of the study area faces a high likelihood of transformation based on combined measures of vulnerability and projection agreement. Transformation at the vegetation type ( n = 50) level is projected for 40% (1.4 M km 2 ) of the study area, based on primary projections. As vegetation shifts towards types supported by a more arid climate, forested area is expected to contract by 9% and subalpine forests specifically by 54%. Elsewhere, vulnerability is low or trajectories are uncertain, implying opportunities for managers to intervene. Dry forests, for example, could be stabilized through vegetation management and intentional fire use. Our findings suggest likely ecological transformations with significant downstream consequences for ecosystem services and natural resources. They are best used within decision-making frameworks that draw on multiple lines of evidence including local expertise and complementary knowledge systems.
In the original article (ten Brink and Geist, 2025), we derived on‐fault magnitude–frequency relationships with uncertainties from a combinatorial optimization method that assigns individual earthquakes from a regional catalog to the different faults. Our model used a magnitude versus area relationship from Shaw (2023). His relationship was published with an error, M=f(1/√A), instead of M=f(1/A) (Shaw, 2025). Here, we recalculate the magnitude–frequency relationship with uncertainties using the Shaw (2025) corrected formula. The remaining parameters of the model, the model itself, and the number of repeated optimization runs have not changed. Figures 1 and 2 show the corrected results and replace figures 3 and 4 in the original article.
Starting in the early 2000s, increasing oil and gas development in western North Dakota created a need for additional water resources from surface-water and groundwater sources near the North Unit of Theodore Roosevelt National Park. To summarize the use of water in that area, the U.S. Geological Survey, in cooperation with the National Park Service, developed a map of surface-water and groundwater resources, aquifers, and water-use diversions, and plotted water-use trends from 1980 to 2023. Reported water used from permits in the map area has more than doubled since 2020, increasing from about 750 acre-feet in 2020 to about 2,300 acre-feet in 2022 and 2,000 acre-feet in 2023. Surface water provided the primary source of reported water used for the study period with an average of about 410 acre-feet per year from 1980 through 2017 and about 1,330 acre-feet per year from 2018 through 2023. After 2011, groundwater sourced from the Little Missouri River, Tobacco Garden Creek, Fox Hills, Fort Union, and Dakota aquifers became a larger portion of total annual reported water use from permits in the map area. From 1980 through 2015, water use for irrigation averaged 86 percent of the total annual reported surface-water and groundwater use in the map area. Starting in 2011, however, industrial uses became a proportionally larger total use of water, and in 2015, became the highest reported volume of water use in the map area. From 2011 to 2023, industrial use designated for water depots increased from 50 acre-feet to about 1,370 acre-feet, accounting for about 70 percent of total reported water use in the map area in 2023.
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.
Invasive species such as grass carp ( Ctenopharyngodon idella ) pose substantial ecological threats to North American freshwater ecosystems. Understanding their early life stage behavior is critical for management efforts. From spawning to hatching, invasive carp eggs must remain suspended in the water column while drifting downstream for the best chance of survival. This highly vulnerable life stage is a potential target for population control to reduce recruitment. However, studying egg transport and potential dispersal control techniques is challenging, because the availability of live eggs and time period for experimentation are extremely limited. Additionally, accurately replicating the physical characteristics and transport mechanisms of fish eggs using surrogates in laboratory and field studies is not trivial. This study presents a novel method to create fluorescein-dyed, preserved grass carp eggs as surrogates for live eggs in transport and dispersal control experiments. This technique enables year-round studies of grass carp egg transport, offering managers a reliable tool for developing and testing dispersal control and passive sampling methods for invasive carp eggs. In this study, we rehydrate and dye preserved grass carp eggs in varying concentrations of aqueous fluorescein for a range of rehydration times, evaluate dye retention and egg visibility under ultraviolet light (UV-A), and measure diameters and settling velocities for comparison with live eggs. Eggs rehydrated in 0.100 g per liter fluorescein for 30 min maintain adequate brightness for up to 40 min in mixed conditions and exhibit mean settling velocities and densities similar to live eggs, making them ideal for laboratory experiments using quantitative imaging techniques.
Rapids are common in steep rivers, often forming where flow transitions from supercritical (Froude number, Fr > 1) to subcritical ( Fr < 1) through a hydraulic jump. When upstream Fr is supercritical but close to 1, this transition may occur as an undular hydraulic jump, exhibiting a train of stationary waves downstream of the jump toe. Previous studies proposed a method to estimate discharge using only UHJ wave spacing and channel width combined with a wave dispersion equation for large water depths relative to the UHJ wavelength. This method is based on the hypotheses that, by their presence, UHJs indicate near-critical flow conditions ( Fr ≈ 1) and that wave celerity c is equal to and opposite the cross-sectionally averaged flow velocity U . However, these hypotheses have not been thoroughly tested. We used data from published UHJ flume experiments to test the hypotheses that Fr ≈ 1 and c = U , compare the deep-water and general wave dispersion equations, and evaluate the accuracy of discharge estimates. In these experiments, the stationary waves exhibited shallow depths relative to wavelength and flow was subcritical ( Fr < 1) when averaged across multiple wavelengths. Additionally, wave celerity more closely approximated the surface flow velocity than U . By using a Fr representative of actual conditions and applying a coefficient to correct for c ≠ U , the accuracy of the discharge estimates improved. This finding suggests that the critical flow-based method is robust and can produce reliable streamflow estimates if the remotely observed wave trains are correctly interpreted as UHJs, without requiring in situ measurements.
Intensive land use alters hydrology and water quality, threatening freshwater benthic macroinvertebrates. Over 200,000 management practices (MPs) have been implemented across the Chesapeake Bay watershed since the 1980s, yet biological responses remain inconsistent. We synthesized 29 studies from 4 physiographic provinces covering 8 MP categories and evaluated macroinvertebrate responses along MP gradients using structural (richness), functional (biomass), tolerance, and biotic metrics. We hypothesized that MPs enhancing habitat complexity or restoring flow regimes would benefit taxa sensitive to sediment, hydrologic instability and organic pollution, with outcomes shaped by regional context, land use, and chosen metrics. Four themes emerged. (i) Agricultural Riparian Forest Buffers (RFBs) consistently improved sensitive metrics related to abundance, biomass and richness. (ii) Urban streams with Stream Habitat Improvement and Management (SHIM) showed improved richness and diversity, but biomass and tolerance metrics declined or remained neutral, indicating unresolved hydrologic and pollutant stress. (iii) Structural and functional responses diverged: effect sizes for total and feeding-group biomasses (functional metrics) were negative, whereas genus-level Ephemeroptera-Plecoptera-Trichoptera (EPT) richness (structural metric) was positive, indicating that structural shifts may not track underlying production changes. (iv) Physiographic comparisons showed counterintuitive patterns, as RFBs improved EPT richness in Piedmont streams but had negative effects in the Coastal Plain. Evaluating MP effectiveness requires distinguishing a no-MP pathway (stressors → instream conditions → assemblages → responses) from an MP-mediated pathway (practice regime → modified stressors → instream conditions → assemblages → responses), underscoring the need for region-specific, multi-metric monitoring and improved understanding of MP density thresholds and recovery lags.
Objective Test whether dietary differences among hatchery strains of Lake Trout Salvelinus namaycush were associated with variation in egg thiamine concentrations and assess the potential for using strain-specific traits to mitigate thiamine deficiency complex (TDC) in Lake Ontario restoration efforts. Methods Stomach content analysis and stable isotope mixing models were used to compare diets among four hatchery strains of Lake Trout, representing lean and humper morphotypes. Egg thiamine concentrations were measured to test whether dietary differences correlated with susceptibility to TDC. Results Significant differences in diet and egg thiamine concentrations were observed among Lake Trout strains. A humper-like morphotype strain exhibited elevated thiamine levels, which were associated with reduced consumption of prey known to degrade thiamine levels when consumed, Alewife Alosa pseudoharengus and Rainbow Smelt Osmerus mordax , and increased reliance on Round Goby Neogobius melanostomus or sculpin species (Slimy Sculpin Cottus cognatus and Deepwater Sculpin Myoxocephalus thompsonii ). These findings support the link between the consumption of Alewife and Rainbow Smelt and thiamine deficiency. Conclusions Our findings support a link between strain-specific dietary preferences and susceptibility to TDC in Lake Trout. Preferential stocking of strains less prone to TDC, such as the strain derived from a humper morph from Lake Superior, could enhance restoration success in Lake Ontario. This strategy may be especially effective given the continued dominance of Alewife in the lake's prey base and the current management priorities supporting fisheries for Pacific salmon Oncorhynchus spp.
Objective We aimed to compare two machine learning approaches—boosted beta regression (BBR) and beta mixed model forest (BMF)—to a Bayesian mixed-effects beta regression (BME) for the prediction of rotary screw trap (RST) efficiency for out-migrating juvenile salmonids from environmental covariates. Methods We identified two machine learning approaches that shared the ability to model overdispersed probabilities. We compared the BBR and BMF machine learning models to a BME model to evaluate precision in detection probability prediction and model performance on bias in parameter estimation. We tested our three candidate models using a simulation study to understand the specific advantages and disadvantages of each when the data set was increasingly sparse and the capture probabilities were realistically small. We then applied the models to a case study of RST data from the Klamath River in California, United States. Results The BME and BMF outperformed BBR in all simulated scenarios, although the BMF displayed poor explanatory power. In the case study, the BME and BMF identified environmental covariates that predicted RST efficiency. Conclusions Using the BME as a benchmark for comparing machine learning approaches to trap efficiency modeling, our simulations and case study demonstrated that the BMF performed well and is a viable modeling approach with strong predictive power. The BME model would be the preferred modeling approach when its strong explanatory power is desired.
The Working Group on American Eel (WGAMEEL) met virtually three times in 2022-2024 to address the five Terms of Reference (ToRs) of its three-year term. The first two ToRs tasked WGAMEEL with listing and evaluating data on American eel landings, abundance indices, and spatial and habitat data and also to describe assessment methods used in Canada and the US. Canada-wide American eel trajectory was estimated using 12 fishery-independent datasets. Generally, longer datasets had more negative trends than shorter ones. Limiting data to the post-2000 years produced fewer negative trends that did not differ from zero, suggesting the observed declines occurred pre-2000. Spatial modelling for American eel requires knowledge and mapping that covers the breadth of habitat types occupied by the species, including freshwater, estuarine, and marine environments. In recent years there has been an expansion of online databases with data from the aquatic environment, particularly in freshwater, with estuarine and marine data less consistently documented. This report broadly compiles abiotic data series of relevance to American eel. A larger challenge for spatial modelling will be acquiring enough high quality, georeferenced biological data sets with suitable observations to assess occurrence, abundance, and trends over time in a spatial framework. The third ToR considered Indigenous Knowledge Systems for American eel. A survey reaching First Nations representatives from four Canadian provinces confirmed the cultural importance of eels in Indigenous communities, and that Indigenous knowledge possessed by the participant groups are place-based and contextual, especially regarding threats impacting eels. The final two ToRs focused on identifying stock assessment modelling approaches applicable to American and European eel, and assessing whether any of these approaches might be appropriate for American eel management moving forward. WGAMEEL evaluated the various approaches for assessing American eel or providing management advice. Two approaches that could be completed in the next few years because of their minimal data needs are index-based methods and catch-only method. A suite of approaches considered by WGAMEEL that would take more time and data were spatial or habitat models, management strategy evaluation, and spawner-per-recruit (SPR) models potentially paired with meta-population models.
Executive Summary The use of field-deployable fluorescence sensors to better understand dissolved organic matter concentrations and composition has grown immensely in recent years. Applications of these sensors to critical monitoring efforts have also grown, encompassing post-fire monitoring, wastewater tracking, and use as a proxy for various contaminants. Despite the growth, it is well known that these sensors require corrections for temperature (Watras and others, 2011) and are subject to many light-field interferences caused by both scattering and absorbance due to dissolved and particulate substances (Downing and others, 2012; Lee and others, 2015; Booth and others, 2023). The most common fluorescence sensors used by the U.S. Geological Survey (USGS) include those targeting fluorescent dissolved organic matter (fDOM) and chlorophylls. Because fDOM sensors primarily measure fluorescence in the dissolved to colloidal phases, corrections to the interferences caused by particulates can be made relatively easily. By the end of 2024, the USGS had 69 fDOM sensors deployed within official water quality monitoring networks included on the USGS National Water Dashboard ( https://dashboard.waterdata.usgs.gov/app/nwd/en/ ) and numerous others used in surveys and research applications across the Nation. Although temperature corrections are widely applicable across sensor models, interference corrections can be model specific due to differences in design specifications across manufacturers and models (Booth and others, 2023). The corrections are also potentially subject to changes in manufacturing within a specific sensor model. Recently, USGS staff obtained information regarding possible changes in the manufacturing of its most widely-used fDOM sensor model, raising concerns about data consistency and quality in the USGS fDOM sensor networks. Furthermore, changes in turbidity sensors since the corrections guidance was performed may also affect the performance of the corrections. The turbidity sensor used in the original experiments (Downing and others, 2012) was determined to have a signal output approximately 1.3 times higher than the output of the turbidity sensor currently used in an extensive field comparison study (Messner and others, 2023). With these changes, it is imperative that the corrections be reevaluated to maintain data consistency and continuity across the USGS. In this study, we evaluated turbidity corrections for fDOM sensors over a range of serial numbers covering manufacturing dates 2015 through 2022 and turbidity serial numbers covering the range 2013 through 2022. The goal was to determine whether reported changes in the manufacturing process of the fDOM and turbidity sensors affected the correction approach developed by Downing and others (2012) such that additional guidance would be required to address this manufacturing change. To evaluate, we repeated a laboratory-based test similar to that performed by Downing and others (2012) in which a series of tank experiments with multiple sensors were deployed in a suspension of Elliot Silt Loam (ESL). High turbidities of the ESL suspension were maintained throughout the tank by turbulent recirculation using submersible pumps. Particulates were removed using a recirculated line equipped with a capsule filter (0.45 micron). Measurements were collected throughout the filtration until turbidities reached approximately 5 formazin nephelometric units (FNU; data available in Baxter and others, 2023). Each experimental run included a mixture of unique sensor combinations to account for variability imposed by the turbidity and temperature sensors. The fDOM correction factor was calculated for each combination of fDOM and turbidity sensors included in the test. We observed no systematic change in fDOM correction coefficients across serial numbers representing manufacturing years 2015 through 2022. However, the results highlighted questions raised about the corrections for high-turbidity samples, as noted in USGS Techniques and Methods (Booth and others, 2023). Applying the inverse of the commonly-used fDOM ratio with a quadratic fit performed better than the exponential fits when correcting fDOM data for turbidity in the ESL laboratory filtration test and generated a simple scale factor correction equation. This approach also served as a better indicator of data quality than the exponential fit approach. Similar to fDOM, more rigorous quality assurance measures may be necessary to evaluate turbidity sensor calibrations and performance. Sensors exceeding a certain age may need to be replaced despite passing quality assurance checks during calibration. Further testing of the turbidity corrections for different sediment and water types is warranted to better understand the variations in the fits and correctable ranges of turbidity in different systems.
No abstract available.