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At least 883 records · Page 49Linked to original sources
USGS2021

Aquatic-terrestrial linkages control metabolism and carbon dynamics in a mid-sized, urban stream influenced by snowmelt

Freshwater streams can exchange nutrients and carbon with the surrounding terrestrial environment through various mechanisms including physical erosion, flooding, leaf drop, and snowmelt. These aquatic-terrestrial interactions are crucial in carbon mobilization, transformation, ecosystem productivity, and have important implications for the role of freshwater ecosystems in the global carbon budget. We utilized high-frequency oxygen, temperature, and carbon dioxide (CO 2 ) data to infer watershed connectivity in Boulder Creek, a mid-sized (1160 km 2 ) watershed located in Colorado, USA. Daily modeled gross primary production (GPP), ecosystem respiration (ER), net ecosystem production (NEP), and reaeration coefficients ( K 600 ) were paired with high-frequency, in-situ dissolved CO 2 data to characterize changes in metabolic regime and carbon flux on a stream influenced by seasonal snowmelt. GPP and ER were correlated ( ρ = −0.72, p ≪ 0.001) during the non-snowmelt period and NEP was frequently negative. Mean F CO2 during the non-snowmelt period was approximately 302 (±171) mmol C m −2 d −1 and was primarily supported by watershed CO 2 inputs. During snowmelt, GPP and ER were not significantly correlated ( ρ = −0.22, p = 0.05), and mean NEP was significantly more negative than during non-snowmelt. Watershed connectivity was higher during snowmelt, as evidenced by significantly higher F CO2 (843 ± 338 mmol C m −2 d −1 ) and greater allochthonous CO 2 inputs than during non-snowmelt periods, emphasizing the effects of seasonal differences in aquatic-terrestrial linkages in this stream. We suggest that our understanding of watershed carbon budgets is subject to temporal dynamics which control the degree of connectivity between terrestrial and aquatic ecosystems.

Colorado↗
USGS2021

Climatic controls on soil carbon accumulation and loss in a dryland ecosystems

Arid and semiarid ecosystems drive year-to-year variability in the strength of the terrestrial carbon (C) sink, yet there is uncertainty about how soil C gains and losses contribute to this variation. To address this knowledge gap, we embedded C-depleted soil mesocosms, containing litter or biocrust C inputs, within an in situ dryland ecosystem warming experiment. Over the course of one year, changes in microbial biomass and total soil organic C pools were monitored alongside hourly measurements of soil CO 2 flux. We also developed a biogeochemical model to explore the mechanisms that gave rise to observed soil C dynamics. Field data and model simulations demonstrated that water exerted much stronger control on soil biogeochemistry than temperature, with precipitation events triggering large CO 2 pulses and transport of litter- and biocrust-derived C into the soil profile. We expected leaching of organic matter would result in steady accumulation of C within the mineral soil over time. Instead, the size of the total organic C pool fluctuated throughout the year, largely in response to microbial growth: increases in the size of microbial biomass were negatively correlated with the quantity of C residing in the top 2 cm, where most biogeochemical changes were observed. Our data and models suggest that microbial responses to precipitation events trigger rapid metabolism of dissolved organic C inputs, which strongly limit accumulation of autotroph-derived C belowground. Accordingly, changes in the magnitude and/or frequency of precipitation events in this dryland ecosystem could have profound impacts on the strength of the soil C sink.

Utah↗
USGS2022

Hydrologic and landscape controls on dissolved organic matter composition across western North American Arctic lakes

Northern high-latitude lakes are hotspots for cycling dissolved organic carbon (DOC) inputs from allochthonous sources to the atmosphere. However, the spatial distribution of lake dissolved organic matter (DOM) is largely unknown across Arctic-boreal regions with respect to the surrounding landscape. We expand on regional studies of northern high-latitude DOM composition by integrating DOC concentrations, optical properties, and molecular-level characterization from lakes spanning the Canadian Taiga to the Alaskan Tundra. Lakes were sampled during the summer from July to early September to capture the growing season. DOM became more optically processed and molecular-level aromaticity increased northward across the Canadian Shield to the southern Arctic and from interior Alaska to the Tundra, suggesting relatively greater DOM incorporation from allochthonous sources. Using water isotopes (δ 18 O-H 2 O), we report a weak overall trend of increasing DOC and decreasing aromaticity in lakes that were hydrologically isolated from the landscape and enriched in δ 18 O-H 2 O, while within-region trends were stronger and varied depending on the landscape. Finally, DOC correlated weakly with chromophoric dissolved organic matter (CDOM) across the study sites, suggesting that autochthonous and photobleached DOM were a major component of the DOC in these regions; however, some of the northernmost and wetland-dominated lakes followed pan-Arctic riverine DOC-CDOM relationships, indicating strong contributions from allochthonous inputs. As many lakes across the North American Arctic are experiencing changes in temperature and precipitation, we expect the proportions of allochthonous and autochthonous DOM to respond with aquatic optical browning with greater landscape connectivity and more internally produced DOM in hydrologically isolated lakes.

Global Biogeochemical Cycles↗
USGS2023

Predicting daily river chlorophyll concentrations at a continental scale

Eutrophication is one of the largest threats to aquatic ecosystems and chlorophyll a measurements are relevant indicators of trophic state and algal abundance. Many studies have modeled chlorophyll a in rivers but model development and testing has largely occurred at individual sites which hampers creating generalized models capable of making broad-scale predictions. To address this gap, we compiled a large data set of chlorophyll a concentrations matched to other water quality, meteorological, and reach characteristic data for a diverse set of 82 streams and rivers across the United States. We used this data set and extreme gradient boosting, a tree-based machine learning algorithm, to predict daily chlorophyll a concentrations. Furthermore, we tested several practical considerations of broad-scale models, such as making predictions at sites not included in model training or the utility of in situ water quality data versus universally available remotely estimated model inputs. Predictions were very strongly correlated to observations when compared against a randomly withheld subset of days; however, the model had lower accuracy when applied to completely novel sites withheld from model training. Turbidity and total nitrogen were the two most important variables for predicting chlorophyll a . Although in situ variables improved modeled estimates and were identified as more important during model interpretation, using only remote inputs still resulted in highly correlated predictions with small bias. Testing a model across many sites allowed for identification of common variables relevant to chlorophyll a and highlighted several challenges for applying data-driven models to new sites or at larger spatial scales.

Water Resources Research↗
USGS2023

Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

Delaware River Basin↗
USGS2024

Adaptation and Response in Drylands (ARID): Community insights for scoping a NASA terrestrial ecology field campaign in drylands

Dryland ecosystems cover 40% of our planet's land surface, support billions of people, and are responding rapidly to climate and land use change. These expansive systems also dominate core aspects of Earth's climate, storing and exchanging vast amounts of water, carbon, and energy with the atmosphere. Despite their indispensable ecosystem services and high vulnerability to change, drylands are one of the least understood ecosystem types, partly due to challenges studying their heterogeneous landscapes and misconceptions that drylands are unproductive “wastelands.” Consequently, inadequate understanding of dryland processes has resulted in poor model representation and forecasting capacity, hindering decision making for these at-risk ecosystems. NASA satellite resources are increasingly available at the higher resolutions needed to enhance understanding of drylands' heterogeneous spatiotemporal dynamics. NASA's Terrestrial Ecology Program solicited proposals for scoping a multi-year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. A primary goal of the scoping study is to gather input from the scientific and data end-user communities on dryland research gaps and data user needs. Here, we provide an overview of the ARID team's community engagement and how it has guided development of our framework. This includes an ARID kickoff meeting with over 300 participants held in October 2023 at the University of Arizona to gather input from data end-users and scientists. We also summarize insights gained from hundreds of follow-up activities, including from a tribal-engagement focused workshop in New Mexico, conference town halls, intensive roundtables, and international engagements.

Earth's Future↗
USGS2024

Controls on lake pelagic primary productivity: Formalizing the nutrient-color paradigm

Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We used data from 58 diverse and globally distributed temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. Across these diverse systems, and given relatively limited inputs, model predictions of primary production were highly correlated with observed values derived from high-frequency sensor data. Our analysis provides a model structure, including calibrated parameter estimates, that may be broadly useful for understanding current and future patterns in lake primary production.

JGR Biogeosciences↗
USGS2026

Storm surge barriers reduce seaward sediment supply to lagoonal estuaries

Numerical simulations with realistic forcing of fixed infrastructure for a proposed storm surge barrier for a lagoonal estuary, Jamaica Bay (New York, USA), are analyzed during typical forcing conditions to assess alterations to flow and sediment transport with the barrier open. Lagoonal estuaries are shallow and have modest watershed freshwater and sediment inputs, so sediment delivery is primarily from offshore by tidal transport. The storm surge barrier infrastructure across the inlet channel reduces cross-sectional area and increases tidal velocities, increasing frictional and form drag. The overall reduction in tidal amplitude is about 1%, but the quarterdiurnal M 4 component decreases by 11%. The salinity and stratification in the estuary are only slightly modified by mixing by stronger velocities near the barrier. Sediment transport in the inlet scales approximately with tidal velocity cubed and net landward transport is driven by flood-dominant tidal asymmetry. Additionally, tidal asymmetry in the jet flow through barrier openings causes a divergence in sediment transport within several kilometers. The alterations to the tidal currents reduce sediment import to the bay by 20% for fine sand; transport of sediment with slower settling velocities is less affected, with reductions of 3% for medium silt and <1% for fine silt. The study examined tidal exchange with an open barrier, but the overall impact also depends on barrier operations during major storm events. The impacts of barrier infrastructure on lagoonal estuaries are distinct from other estuary types due to their modest freshwater input, predominance of tidal transport, and offshore sediment supply.

New York↗
USGS2026

Mercury cycling across a U.S. semi-arid mountain ecosystem elevation gradient

Mountains comprise ∼30% of the Earth's surface, but mercury (Hg) cycling in these regions remains understudied, particularly in the semi-arid western U.S. where strong climatic and ecological gradients in mountainous landscapes influence Hg deposition, retention, and bioaccumulation. In this study, we quantified growing season inputs, storage, and bioaccumulation of Hg along a ∼2,000 m elevation gradient in the Colorado Rocky Mountains, spanning the plains to the alpine. We measured Hg in atmospheric deposition, vegetation, soil, and 12-day-old chickadees. Accounting for percent canopy cover, open precipitation was the largest component of atmospheric deposition at all elevations, followed by throughfall and litterfall fluxes. Atmospheric Hg fluxes peaked at mid-elevations, likely due to cloud-cap dynamics and denser canopy cover. Total gaseous Hg and precipitation fluxes were highest at low elevations, likely reflecting local emissions and meteorological pooling. Surface soil Hg storage was more strongly predicted by organic matter content ( R 2 = 0.49; p < 0.01) and water retention ( R 2 = 0.45; p < 0.01) than by elevation ( R 2 = 0.21; p < 0.05). Alpine soils (66.3 ± 25.3 ng g −1 ) had significantly higher total Hg concentrations than lower elevations (<41.0 ± 12.7 ng g −1 ; p < 0.01), likely reflecting slower organic matter turnover. Soils on north-facing slopes also retained significantly higher pools of Hg in surface soils compared with south- and east-facing slopes. Vegetation Hg pools were greatest in the alpine region, likely due to long-lived plant species. Methylmercury (MeHg) concentrations in chickadee feathers peaked at mid-elevations (205 ± 155 ng g −1 ), corresponding to higher ecosystem Hg inputs via throughfall. Our results show that deposition, canopy cover, and meteorological conditions—not elevation alone—predict Hg retention and bioaccumulation.

Colorado↗
USGS2008

Response of Ned Wilson Lake watershed, Colorado, to changes in atmospheric deposition of sulfate

The Ned Wilson Lake watershed responds directly and rapidly to changes in precipitation inputs of sulfate, which has important implications for effects of acid deposition on the aquatic system. Chemistry at three precipitation collection sites and three watershed sites (a pond, a lake, and a spring) has been monitored in and near the Flattops Wilderness Area in northwestern Colorado beginning in 1981–1983. Bulk snowpack concentration of sulfate in the watershed and volume-weighted annual mean concentration of sulfate in precipitation at two nearby sites generally decreased from 1981 to 1985, were small through 1987, and increased in 1988–1989. Changes in concentration of sulfate at the watershed sites are controlled by precipitation inputs. Responsiveness of the individual sites was dependent on their position along the hydrologic flow path. The fastest response was in the pond, which has a hydrologic residence time of less than 1 year; over 90% of the variance in concentration of sulfate in the pond was explained by changes in concentration in precipitation. The lake has a hydrologic residence time of 1 to 4 years; a regression model of the concentration of sulfate in the lake, as a function of the concentration in the lake during the previous year and the concentration in precipitation, explained 87% of the variance in concentration of sulfate in the lake. The hydrologic response time of the spring is unknown; it was not responsive to changes in concentration of sulfate in precipitation. The recent increase of sulfate concentration in precipitation and in the pond and lake is evidence for a rapid rather than a delayed response, which could not be determined when only a decreasing trend in sulfate concentration was reported in 1982–1987. Watersheds of this type are sensitive to acidification (acid-neutralizing capacity less than 60 μeq L −1 ), and these results indicate conservative behavior of sulfate. This is important in predicting effects of future changes in atmospheric deposition, which could potentially be caused by anthropogenic emissions or climatic change.

Colorado↗
USGS2008

Convergent radial dispersion: A note on evaluation of the Laplace transform solution

A numerical inversion algorithm for Laplace transforms that is capable of handling rapid changes in the computed function is applied to the Laplace transform solution to the problem of convergent radial dispersion in a homogeneous aquifer. Prior attempts by the author to invert this solution were unsuccessful for highly advective systems where the Peclet number was relatively large. The algorithm used in this note allows for rapid and accurate inversion of the solution for all Peclet numbers of practical interest, and beyond. Dimensionless breakthrough curves are illustrated for tracer input in the form of a step function, a Dirac impulse, or a rectangular input.

Water Resources Research↗
USGS2010

Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands

Remotely sensed data in the visible, near-infrared, and thermal-infrared wave bands were collected from a low-flying aircraft during the Monsoon '90 field experiment. Monsoon '90 was a multidisciplinary experiment conducted in a semiarid watershed. It had as one of its objectives the quantification of hydrometeorological fluxes during the “monsoon” or wet season. The remote sensing observations along with micrometeprological and atmospheric boundary layer (ABL) data were used to compute the surface energy balance over a range of spatial scales. The procedure involved averaging multiple pixels along transects flown over the meteorological and flux (METFLUX) stations. Average values of the spectral reflectance and thermal-infrared temperatures were computed for pixels of order 10 −1 to 10 1 km in length and were used with atmospheric data for evaluating net radiation ( R n ), soil heat flux ( G ), and sensible ( H ) and latent ( LE ) heat fluxes at these same length scales. The model employs a single-layer resistance approach for estimating H that requires wind speed and air temperature in the ABL and a remotely sensed surface temperature. The values of R n and G are estimated from remote sensing information together with near-surface observations of air temperature, relative humidity, and solar radiation. Finally, LE is solved as the residual term in the surface energy balance equation. Model calculations were compared to measurements from the METFLUX network for three days having different environmental conditions. Average percent differences for the three days between model and the METFLUX estimates of the local fluxes were about 5% for R n , 20% for G and H , and 15% for LE . Larger differences occurred during partly cloudy conditions because of errors in interpreting the remote sensing data and the higher spatial and temporal variation in the energy fluxes. Minor variations in modeled energy fluxes were observed when the pixel size representing the remote sensing inputs changed from 0.2 to 2 km. Regional scale estimates of the surface energy balance using bulk ABL properties for the model parameters and input variables and the 10-km pixel data differed from the METFLUX network averages by about 4% for R n , 10% for G and H , and 15% for LE . Model sensitivity in calculating the turbulent fluxes H and LE to possible variations in key model parameters (i.e., the roughness lengths for heat and momentum) was found to be fairly significant. Therefore the reliability of the methods for estimating key model parameters and potential errors needs further testing over different ecosystems and environmental conditions.

Water Resources Research↗
USGS2010

Climate, soil water storage, and the average annual water balance

This paper describes the development and testing of the hypothesis that the long-term water balance is determined only by the local interaction of fluctuating water supply (precipitation) and demand (potential evapotranspiration), mediated by water storage in the soil. Adoption of this hypothesis, together with idealized representations of relevant input variabilities in time and space, yields a simple model of the water balance of a finite area having a uniform climate. The partitioning of average annual precipitation into evapotranspiration and runoff depends on seven dimensionless numbers: the ratio of average annual potential evapotranspiration to average annual precipitation (index of dryness); the ratio of the spatial average plant-available water-holding capacity of the soil to the annual average precipitation amount; the mean number of precipitation events per year; the shape parameter of the gamma distribution describing spatial variability of storage capacity; and simple measures of the seasonality of mean precipitation intensity, storm arrival rate, and potential evapotranspiration. The hypothesis is tested in an application of the model to the United States east of the Rocky Mountains, with no calibration. Study area averages of runoff and evapotranspiration, based on observations, are 263 mm and 728 mm, respectively; the model yields corresponding estimates of 250 mm and 741 mm, respectively, and explains 88% of the geographical variance of observed runoff within the study region. The differences between modeled and observed runoff can be explained by uncertainties in the model inputs and in the observed runoff. In the humid (index of dryness <1) parts of the study area, the dominant factor producing runoff is the excess of annual precipitation over annual potential evapotranspiration, but runoff caused by variability of supply and demand over time is also significant; in the arid (index of dryness >1) parts, all of the runoff is caused by variability of forcing over time. Contributions to model runoff attributable to small-scale spatial variability of storage capacity are insignificant throughout the study area. The consistency of the model with observational data is supportive of the supply-demand-storage hypothesis, which neglects infiltration excess runoff and other finite-permeability effects on the soil water balance.

Water Resources Research↗
USGS1997

Moss and soil contributions to the annual net carbon flux of a maturing boreal forest

We used input and decomposition data from 14 C studies of soils to determine rates of vertical accumulation of moss combined with carbon storage inventories on a sequence of burns to model how carbon accumulates in soils and moss after a stand-killing fire. We used soil drainage—moss associations and soil drainage maps of the old black spruce (OBS) site at the BOREAS northern study area (NSA) to areally weight the contributions of each moderately well drained, feathermoss areas; poorly drained sphagnum—feathermoss areas; and very poorly drained brown moss areas to the carbon storage and flux at the OBS NSA site. On this very old (117 years) complex of black spruce, sphagnum bog veneer, and fen systems we conclude that these systems are likely sequestering 0.01–0.03 kg C m −2 yr −1 at OBS-NSA today. Soil drainage in boreal forests near Thompson, Manitoba, controls carbon storage and flux by controlling moss input and decomposition rates and by controlling through fire the amount and quality of carbon left after burning. On poorly drained soils rich in sphagnum moss, net accumulation and long-term storage of carbon is higher than on better drained soils colonized by feathermosses. The carbon flux of these contrasting ecosystems is best characterized by soil drainage class and stand age, where stands recently burned are net sources of CO 2 , and maturing stands become increasingly stronger sinks of atmospheric CO 2 . This approach to measuring carbon storage and flux presents a method of scaling to larger areas using soil drainage, moss cover, and stand age information.

Journal of Geophysical Research D: Atmospheres↗
USGS1997

Hydrological and chemical estimates of the water balance of a closed-basin lake in north central Minnesota

Chemical mass balances for sodium, magnesium, chloride, dissolved organic carbon, and oxygen 18 were used to estimate groundwater seepage to and from Williams Lake, Minnesota, over a 15-month period, from April 1991 through June 1992. Groundwater seepage to the lake and seepage from the lake to groundwater were determined independently using a flow net approach using data from water table wells installed as part of the study. Hydrogeological analysis indicated groundwater seepage to the lake accounted for 74% of annual water input to the lake; the remainder came from atmospheric precipitation, as determined from a gage in the watershed and from nearby National Weather Service gages. Seepage from the lake accounted for 69% of annual water losses from the lake; the remainder was removed by evaporation, as determined by the energy budget method. Calculated annual water loss exceeded calculated annual water gain, and this imbalance was double the value of the independently measured decrease in lake volume. Seepage to the lake determined from oxygen 18 was larger (79% of annual water input) than that determined from the flow net approach and made the difference between calculated annual water gain and loss consistent with the independently measured decrease in lake volume. Although the net difference between volume of seepage to the lake and volume of seepage from the lake was 1% of average lake volume, movement of water into and out of the lake by seepage represented an annual exchange of groundwater with the lake equal to 26–27% of lake volume. Estimates of seepage to the lake from sodium, magnesium, chloride, and dissolved organic carbon did not agree with the values determined from flow net approach or oxygen 18. These results indicated the importance of using a combination of hydrogeological and chemical approaches to define volume of seepage to and from Williams Lake and identify uncertainties in chemical fluxes.

Minnesota↗
USGS1998

Cenozoic global sea level, sequences, and the New Jersey transect: Results from coastal plain and continental slope drilling

The New Jersey Sea Level Transect was designed to evaluate the relationships among global sea level (eustatic) change, unconformity-bounded sequences, and variations in subsidence, sediment supply, and climate on a passive continental margin. By sampling and dating Cenozoic strata from coastal plain and continental slope locations, we show that sequence boundaries correlate (within ±0.5 myr) regionally (onshore-offshore) and interregionally (New Jersey-Alabama-Bahamas), implicating a global cause. Sequence boundaries correlate with δ 18 O increases for at least the past 42 myr, consistent with an ice volume (glacioeustatic) control, although a causal relationship is not required because of uncertainties in ages and correlations. Evidence for a causal connection is provided by preliminary Miocene data from slope Site 904 that directly link δ 18 O increases with sequence boundaries. We conclude that variation in the size of ice sheets has been a primary control on the formation of sequence boundaries since ∼42 Ma. We speculate that prior to this, the growth and decay of small ice sheets caused small-amplitude sea level changes (<20 m) in this supposedly ice-free world because Eocene sequence boundaries also appear to correlate with minor δ 18 O increases. Subsidence estimates (backstripping) indicate amplitudes of short-term (million-year scale) lowerings that are consistent with estimates derived from δ 18 O studies (25–50 m in the Oligocene-middle Miocene and 10–20 m in the Eocene) and a long-term lowering of 150–200 m over the past 65 myr, consistent with estimates derived from volume changes on mid-ocean ridges. Although our results are consistent with the general number and timing of Paleocene to middle Miocene sequences published by workers at Exxon Production Research Company, our estimates of sea level amplitudes are substantially lower than theirs. Lithofacies patterns within sequences follow repetitive, predictable patterns: (1) coastal plain sequences consist of basal transgressive sands overlain by regressive highstand silts and quartz sands; and (2) although slope lithofacies variations are subdued, reworked sediments constitute lowstand deposits, causing the strongest, most extensive seismic reflections. Despite a primary eustatic control on sequence boundaries, New Jersey sequences were also influenced by changes in tectonics, sediment supply, and climate. During the early to middle Eocene, low siliciclastic and high pelagic input associated with warm climates resulted in widespread carbonate deposition and thin sequences. Late middle Eocene and earliest Oligocene cooling events curtailed carbonate deposition in the coastal plain and slope, respectively, resulting in a switch to siliciclastic sedimentation. In onshore areas, Oligocene sequences are thin owing to low siliciclastic and pelagic input, and their distribution is patchy, reflecting migration or progradation of depocenters; in contrast, Miocene onshore sequences are thicker, reflecting increased sediment supply, and they are more complete downdip owing to simple tectonics. We conclude that the New Jersey margin provides a natural laboratory for unraveling complex interactions of eustasy, tectonics, changes in sediment supply, and climate change.

New Jersey↗
USGS2010

Manganese biogeochemistry in a small Adirondack forested lake watershed

I n September and October 1981, manganese (Mn) concentrations and p H were intensively monitored in a small forested lake watershed in the west-central Adirondack Mountains, New York, during two large acidic storms (each ∼5 cm rainfall, p H 4.61 and 4.15). The data were evaluated to identify biogeochemical pathways of Mn and to assess how these pathways are altered by acidic atmospheric inputs. Concentrations of Mn averaged 1.1 μg/L in precipitation and increased to 107 μg/L in canopy throughfall, the enrichment reflecting active biological cycling of Mn. Rain p H and throughfall Mn were negatively correlated, suggesting that foliar leaching of Mn was enhanced by rainfall acidity. The pulselike input of Mn to the forest floor in the high initial concentrations in throughfall (∼1000 μg/L) did not affect Mn concentrations in soil water (< 20 μg/L) or groundwater (usually < 40 μg/L), which varied little with time. In the inlet stream, Mn concentrations remained constant at 48 μg/L as discharge varied from 1.1 to 96 L/s. Manganese was retained in the vegetative cycle and regulated in the stream by adsorption in the soil organic horizon. The higher Mn levels in the stream may be linked to its high acidity (pH 4.2–4.3). Mixing of Mn-rich stream water with neutral lake water ( p H 7.0) caused precipitation of Mn and deposition in lake sediment.

New York↗
USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗