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At least 1,189 records · Page 66Linked to original sources

USGS2026

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota↗

USGS2026

Extreme Potomac floods at Washington D.C. during the past 500 years

Washington D.C. faces one of the highest 100-year flood risks of any major city along the U.S. East Coast. In addition to storm-surge inundation during hurricanes and nor'easters, water-level observations for Washington are strongly skewed by major floods on the Potomac River. Using geologic and historic records we find new evidence for ice-jam flooding at Georgetown during the Little Ice Age, as recently as 1784, that was up to ∼2x the magnitude of the largest events of the past hundred years (1936, 1942). Over the 19th century (a) human modifications to the Potomac estuary as well as (b) increasingly heavy rainfall and (c) land-clearance in the watershed may have contributed to increasingly frequent large floods at Washington. Early surveys of the U.S. Capitol Building and other local landmarks also suggest sea level on the Potomac estuary at Washington has risen by upwards of 0.7 m (2.2 ft) since the 1790s.

Maryland, Virginia↗

USGS2026

Assessing the influence of conservation implementation on water quality during surface runoff events at edge-of-field monitoring sites located in the Laurentian Great Lakes basin

The Laurentian Great Lakes are a vital freshwater resource in the United States, and nonpoint source (NPS) nutrient pollution, specifically phosphorus (P) and nitrogen (N), from agricultural land use continues to negatively impact water quality throughout the Great Lakes basin. One focus of the Great Lakes Restoration Initiative (GLRI), a mechanism to coordinate conservation efforts in the Great Lakes that began in 2010, is reducing NPS nutrient pollution through the implementation of conservation practices in priority watersheds (Genesee River, Fox River, Maumee River, and Saginaw River). As part of GLRI efforts, the objective of the study presented here was to evaluate the effects of conservation implementation, specifically increasing vegetative cover on fields and in primary flowpaths through perennial or cover crop planting and grassed waterways, on surface-runoff water quality at 12 agricultural fields (six paired and six unpaired) located in priority watersheds. We determined the percentage difference in mean event response variables between the periods before and after conservation implementation at individual sites, describing patterns across sites to synthesize lessons learned from these GLRI evaluations. Generally, we found that mean event flow-weighted concentration (FWC) and yield (kilograms per hectare) decreased for suspended sediment (SS) and nitrate (NO 3 – -N) across many sites. Mean event FWC and yield for total P (TP) showed mixed results across sites, while mean event FWC and yield for orthophosphate generally increased across sites. These results indicate that perennial or cover crop planting and grassed waterways effectively reduce SS and NO 3 – -N losses in surface runoff from agricultural fields, but mitigating TP and dissolved P losses remains a challenge.

Laurentian Great Lakes basin↗

USGS2026

Year-round daytime pCO2 undersaturation in an instream series of urban reservoirs with a history of harmful algal blooms

Daytime water quality was determined monthly over two years in an instream series of four urban reservoirs with recurring blooms of Prymnesium parvum —a cool-season toxigenic species. Temperature, pH, and laboratory-measured total alkalinity were used to estimate p CO 2 . System-wide, p CO 2 was negatively associated with dissolved oxygen. Chlorophyll- a , phycocyanin (cyanobacterial pigment), and P. parvum were negatively associated with p CO 2 and positively with dissolved oxygen. Three reservoirs were productive and, during daytime, p CO 2 -undersaturated year-round or near-year-round, while a fourth (third in the series) was unproductive and mostly p CO 2 -oversaturated. Seasonal phycocyanin and chlorophyll- a patterns indicated that cyanobacterial and eukaryotic ( P. parvum included) phytoplankton growth drives daytime CO 2 depletion in the productive reservoirs during the warm and cool seasons, respectively. The system’s moderate alkalinity (HCO 3 − ) may serve as an alternative carbon source for photosynthesis; however, the persistent depletion of CO 2 and the energetic cost of using HCO 3 − are consistent with a scenario where phytoplankton growth is CO 2 -limited. Daytime p CO 2 undersaturation across seasons has been rarely reported, but this study indicated it occurs more often than recognized. The non-monotonic spatial patterns in productivity and carbonate system conditions across the study reservoirs indicate that localized influences from a heterogeneous urban landscape may help shape individual lake metabolism.

Texas↗

USGS2026

Waterfowl move less in heterogeneous and human-populated landscapes, with implications for spread of avian influenza viruses

Animal movements contribute to the spread of infectious diseases and are driven in part by environmental conditions. We investigated the links among the environment, animal movement, and infectious disease dynamics in waterfowl, which are among the primary wildlife hosts of avian influenza viruses. By combining telemetry data on 4606 individuals from 26 waterfowl species with data on land cover, weather, and vegetation, we found that waterfowl moved less in areas of higher land cover heterogeneity and higher human population density. Moreover, predicted waterfowl movement distances were weakly but positively correlated with distances between detections of H5N1 highly pathogenic avian influenza in wild waterfowl, suggesting that environmental conditions might contribute to the spread of this disease via their effects on bird movements. By considering wildlife movements alongside other drivers of infectious disease dynamics, such as livestock production and human mobility, we move closer to predicting outbreaks and informing interventions.

Ecology Letters↗

USGS2026

Linking community-climate disequilibrium to ecosystem function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community-climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, we develop a simple theoretical model to address both of these problems by linking community-climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near-term even when climate change is expected to enhance functioning in the long-term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre-existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community-climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community-climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

Ecology Letters↗

USGS2026

A conceptual framework and methods for studying the connectivity of fishes

Connectivity is a multifaceted concept that has important implications for the management and conservation of marine and freshwater fishes. We developed a conceptual framework that encompasses multiple, interrelated categories of connectedness, including landscape (e.g., structural, functional) connectivity and ecological (e.g., trophic, genetic, demographic) connectivity, that together shape the flow of organisms, energy and information across ecosystems. We also synthesised six key methods that can be used to study connectivity of fishes: (1) telemetry, including satellite, acoustic, radio and passive integrated transponders (PIT), (2) mark-recapture, (3) environmental tracers, including stable isotopes and otolith-microchemistry, (4) genetics, (5) community structure analysis and (6) emerging technologies and tools (e.g., remote sensing and artificial intelligence). For each method, we describe the categories of connectivity it can assess and provide real-world examples where they have been effectively used. We also identify limitations of each method. This article highlights the diverse and evolving toolbox of methods used to assess fish connectivity, underscoring the need for continued collaboration, innovation and integration of new approaches to refine our understanding and address remaining challenges in this critical area of aquatic ecology and fisheries management.

Fish and Fisheries↗

USGS2026

The development of long-term mean annual total nitrogen and total phosphorus load models for Mississippi, U.S., using RSPARROW

Water-quality degradation from nutrient pollution remains a major challenge for resource managers. Developing effective strategies requires tools to characterize nutrient sources and transport. This study used the RSPARROW framework to develop and assess new, smaller-scale models for Total Nitrogen (TN) and Total Phosphorus (TP) transport across Mississippi (MS). These state-level models were built using 15 years (2005–2020) of observation data and considered variables including multiple nutrient sources, land characteristics, and attenuation processes. The MS models demonstrated comparable accuracy to larger regional SPARROW models, validating the use of smaller-scale models for local management. Results showed agricultural sources are the major contributors to TN, dominated by fertilizer in northern MS and livestock manure in the south. Urban land cover also significantly influenced TN and was the second most significant source of TP, following geologic material (background P). Fertilizer and manure were also important TP sources. This study provides valuable, spatially explicit data on nutrient distribution in MS streams, supporting the state’s nutrient reduction planning. It concludes by highlighting the need for future model improvements via updated source data and mean annual flow estimates.

Alabama, Georgia, Louisiana, Mississippi, North Ca↗

USGS2026

Mountain goat declines in a protected, interior, native population

A shifting climate poses threats to alpine-adapted species including mountain goats. We used long-term (12 years) citizen science monitoring data and Bayesian N-mixture modeling to estimate population trends and drivers of population metrics among mountain goats in Glacier National Park (GNP). Median goats per site ( n = 37 sites) declined by 45% (95% credible interval [CRI] = 32%, 57%) from 77.8 (95% CRI = 64.4, 95.1) in 2008 to 42.3 (95% CRI = 34.3, 52.2) in 2019, with consistent declines from 2008 until 2015, when the number of estimated goats stabilized. The decline exceeds IUCN criteria for classifying a population as vulnerable, >30% declines over only two generations. Across years, relatively few goats occupied northwestern GNP. Goat numbers declined the most at northeastern sites, trended toward decline in most southern sites, and increased at only two west-central sites. The proportion of permanent snow and glaciers, the presence of natural mineral licks, and habituation strongly increased the initial abundance of goats in the area. Weather variables had the greatest influence on population growth rates, particularly precipitation between May 15 and June 15 of the previous summer, the neonatal period. Lower growth occurred with less snow water equivalent and lower mean winter temperature, early summer temperature, and early summer precipitation. Projected reductions of permanent snow, increasing spring and summer temperatures, and insufficient and variable spring precipitation raise concerns for the future of native goats in this region. Our analyses reveal ways to improve detection rates of goats during surveys, which is important for optimizing the precision of estimates and the power to detect future trends. Detection increased with goat habituation, retention of observers with experience, use of binoculars, and conducting surveys at lower temperatures and earlier dates. Improving detection will be particularly important given the lower number of goats currently observed in the park. Research to estimate park-wide population size, evaluate genetic structure and diversity, assess changing habitat, human recreation levels and forage, and forward-project climate effects on persistence will be crucial to understanding the context of these results and conserving this iconic, metapopulation at the southern edge of the distribution of native mountain goats.

Montana↗

USGS2026

Best practice guidelines for targeted environmental DNA-based proficiency testing in non-regulatory contexts

The effective use of environmental DNA (eDNA) tools is contingent on strict adherence to established and validated methods. Differences in eDNA methods and quality assurance protocols may contribute to variability in results. However, quality assurance measures such as proficiency testing can provide independent evaluation of laboratory performance against pre-established test criteria. With this commentary, we discuss how broad implementation of recurring proficiency testing in eDNA laboratories can build decision-maker confidence in eDNA results. It can also create a culture of continuous evaluation and improvement that minimizes error and meets performance requirements to inform the sustainable use or monitoring of natural resources. We provide an overview of proficiency testing across molecular disciplines, review the state of proficiency testing in eDNA applications, and draft a roadmap for the expanded application of proficiency testing informed by best practices for targeted eDNA detection. We suggest that best practice proficiency testing can be conducted by an independent, third-party sample provider. By demonstrating that laboratories are competent and capable of producing reliable results, implementation of proficiency testing best practices should foster confidence in eDNA measurements and its use in decision-making processes. Increased confidence in eDNA methods and a clear expectation of what is considered satisfactory performance are also likely to create more favorable conditions for investments in eDNA-based monitoring.

Environmental DNA↗

USGS2026

Microtextural characteristics of adularia in banded quartz veins from the Midas low-sulfidation epithermal deposit, Nevada

High-grade ores at the Miocene Midas low-sulfidation epithermal deposit in northern Nevada are confined to crustiform quartz veins containing abundant adularia. Micro-X-ray fluorescence elemental mapping reveals that adularia is a common gangue mineral occurring in colloform bands, bands showing bladed textures, and bands with dendritic terminations. The adularia aggregates have delicate shapes and are comprised of stacked, submillimeter crystals hosted by fine-grained quartz. The textural evidence suggests that the adularia aggregates originally formed within a gel-like, noncrystalline silica matrix, which subsequently transformed into quartz. This indicates that the adularia did not precipitate in open space along the vein walls. Correlative microscopy, involving scanning electron microscopy-based automated mineralogy and optical petrography, demonstrates that bands containing abundant adularia are not the primary host to ore minerals. The ore minerals occur in different bands within the crustiform veins, implying that adularia and ore mineral precipitation did not always occur simultaneously. It is hypothesized here that fluid flow at Midas involved intermittent short-lived events of fluid flashing, causing rapid solute supersaturation in the liquid. During each flashing event, different amounts of vapor were produced along a given vein. Compositional differences between adjacent bands in the crustiform quartz veins may, therefore, be linked to variations in the amount of vapor formed during each flash event.

Nevada↗

USGS2026

Strength of depensation not influenced by fish population productivity

A long-held assumption in the management of exploited fisheries is that fish populations will compensate with increased recruit survival to replenish the population when adult stock size is reduced through harvest. Observations of depensatory recruitment (reduced recruit survival at low adult stock size) and critical depensatory thresholds have challenged the compensation assumption. Post et al. (2002) postulated that critical depensatory thresholds were related to fish population productivity. Walleye Sander vitreus are a culturally, economically, and recreationally important sportfish whose persistence is being challenged by natural recruitment declines throughout much of its native range. Depensation, among other abiotic and biotic stressors, has been implicated in walleye natural recruitment declines. If walleye population productivity is related to critical depensatory thresholds, then population productivity benchmarks could be established to reduce the probability of crossing them. We used empirically-derived and model predicted depensation values ( q ) and empirical estimates of walleye population productivity to test for relationships between these variables in northern Wisconsin lakes. We found little evidence for a relationship between q and walleye population productivity across all lakes examined. Our finding failed to support the theoretical postulation of a relationship between these variables by Post et al. (2002) for walleye. Little evidence for a relationship between q and population productivity suggests that depensatory thresholds may differ among individual walleye populations and that walleye populations may transition abruptly between compensatory and depensatory states. Given our findings, conservation efforts for walleye that solely focus on low productivity populations may miss other trends because population productivity may not be considered a broad predictor of crossing a critical depensatory threshold.

Fisheries Research↗

USGS2026

Miocene evolution of the Humboldt Current

Diatom records from the East Pisco Basin (EPB) of southern Peru and offshore Ocean Drilling Program (ODP) Hole 682 A reveal stepwise increases in the primary productivity of the Humboldt Current during the middle and late Miocene. Although diatoms are present back through the late middle Eocene, successively enhanced diatom production occurs during the Miocene in four steps. The first step between 14.2 and 13.8 Ma marks the onset of diatom deposition in the Pisco-0 sequence. A second step at ∼12.9 Ma coincides with a major drop in global sea level during which diatom deposition ceased in the EPB but continued in ODP 682 A as well as in Chile, Ecuador, and Colombia. Beginning at 10.4 to 10.0 Ma, a major increase in diatom sedimentation rates in both the EPB and in ODP 682 A signals an abrupt intensification of the Humboldt Current productivity, which may be related to the closure of the Central American Seaway to deeper water circulation. A fourth step coincides with the transgressive deposition of the diatom-rich Pisco-2 sequence at 8.4 Ma and is enhanced by the onset of the global Late Miocene Biogenic Bloom (8.0–4.5 Ma). Between 7 and 6 Ma, common subtropical diatoms in ODP 682 A contrast with high diatom deposition rates in the EPB, suggesting variable El Niño-La Niña conditions. During this time, fossil vegetation evidence from southern Peru supports the presence of seasonal periods of enhanced rainfall typical of El Niño conditions. The Miocene trend of increasing sea mammal diversity in the EPB parallels these steps, further supporting stepwise enhancement of primary productivity in the Humboldt Current during the Miocene.

Humboldt Current↗

USGS2026

Reconstructing Great Lakes air temperature and ice dynamics data back to 1897

Ice cover on the Great Lakes plays an important role in regional climate, supports tourism and recreation, and provides ecological habitat. As the climate warms, ice cover in the Great Lakes is expected to decline, which in turn will create more lake effect precipitation, reduce ice cover for recreation, and alter habitat for aquatic species. While it is important to understand the historical ice patterns to better understand past distributions of aquatic species and improve the accuracy of forecasts for future ice cover on the lakes, Great Lakes ice cover data prior to 1973 is scarce, due to the limited routine satellite observations. We used weather station data around the Great Lakes to compile daily air temperature, calculate cumulative freezing degree-days and net melting degree-days from 1897–2023, and develop raster layers estimating ice duration and variability spatially during the historical period from 1897–1960.

Great Lakes↗

USGS2026

Estimating the power of a standardized monitoring program for sportfish in Georgia, USA

Objective Biological monitoring is a major component of management decisions and operating budgets of many natural resource management agencies. Given the scientific and financial commitments to monitoring, it is critical to estimate the ability to detect trends through time (i.e., power). Methods The Georgia Department of Natural Resources has monitored reservoir sport fish populations since the 1980s. We estimated the power to detect simulated long-term (≥10 years) changes in relative abundance (CPUE) for Largemouth Bass (some of which are a potential genetic admixture of the recently described species Micropterus nigricans [now known as Largemouth Bass] and M. salmoides [now known as Florida Bass)] and Black Crappie Pomoxis nigromaculatus sampled with electrofishing and gill nets, respectively, across multiple reservoirs ( n = 21). Reservoir-specific simulations were parameterized using 13 years (∼2010–2022) of monitoring data. Power was calculated as the proportion of simulations ( n = 1,000) resulting in significant ( P ≤ 0.1) temporal trends across a 10-year period. We considered power ≥0.8 (i.e., 80% of simulations with significant trends) as the threshold for sufficient power across reservoirs. For both species, we estimated power under three scenarios: (1) declining CPUE, (2) increasing CPUE, and (3) reduction to biennial sampling effort with a 50% decline in CPUE. Results Most reservoirs had sufficient power to detect either a 50% decline or a 100% increase in CPUE of Largemouth Bass across a 10-year period. Switching from annual to biennial sampling for Largemouth Bass reduced the number of reservoirs with sufficient power by half. Power was generally lower for Black Crappie until larger declines (75%) or increases (400%) were imposed. Conclusions We found that Largemouth Bass monitoring was generally near or beyond our reference threshold, but post hoc correlation analyses suggested that the power of Black Crappie data could be increased with more within-reservoir station replication. Overall, using data simulation to estimate power proved a valuable tool in assessing the potential ability of common monitoring approaches to detect change.

Georgia↗

USGS2026

The biosphere in the Anthropocene

Earth’s biosphere is in a period of rapid change, resulting from anthropogenic pressures such as climate change, habitat loss and species translocation and extinction. The extraordinary pace of change has led to the suggestion that we live in a new geological epoch of time called the Anthropocene. In this theme issue, we explore the major changes to the terrestrial and marine biospheres, from the deep oceans to the agricultural landscapes of the Anthropocene. We take a deliberately pluralistic approach that represents different viewpoints from the sciences and social sciences, examining our negative and sometimes calamitous impacts on species and ecosystems and our potential for positive interactions with the biosphere, and exploring change over millennia.

Transactions of the Royal Society of London↗

USGS2026

Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning

Remote sensing enables large-scale, image-based assessments of river dynamics, offering new opportunities for hydrological monitoring. We present a publicly available dataset consisting of 281,024 satellite and aerial images of U.S. rivers, constructed using an Application Programming Interface (API) and the U.S. Geological Survey’s National Hydrography Dataset. The dataset includes images, primary keys, and ancillary geospatial information. We use a manually labeled subset of the images to train models for detecting rapids, defined as areas where high velocity and turbulence lead to a wavy, rough, or even broken water surface visible in the imagery. To demonstrate the utility of this dataset, we develop an image segmentation model to identify rivers within images. This model achieved a mean test intersection-over-union ( 𝐼 𝑜 𝑈 ) of 0.57, with performance rising to an actual 𝐼 𝑜 𝑈 of 0.89 on the subset of predictions with high confidence (predicted 𝐼 𝑜 𝑈 > 0.9). Following this initial segmentation of river channels within the images, we trained several convolutional neural network (CNN) architectures to classify the presence or absence of rapids. Our selected model reached an accuracy and F1 score of 0.93, indicating strong performance for the classification of rapids that could support consistent, efficient inventory and monitoring of rapids. These data provide new resources for recreation planning, habitat assessment, and discharge estimation. Overall, the dataset and tools offer a foundation for scalable, automated identification of geomorphic features to support riverine science and resource management.

Remote Sensing↗

USGS2026

Remote compositional analyses of space-weathered lunar maria

Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.

Planetary Science Journal↗