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At least 19 recordsLinked to original sources
USGS2021

Assessment of multiple ecosystem metabolism methods in an estuary

Ecosystem metabolism is a key ecological attribute and easy to describe, but quantifying metabolism in estuaries is challenging. Properly scaling measurements through time and space requires consideration of hydrodynamics and mixing water from heterogeneous sources, making any estimation uncertain. Here, we compared three methods for modeling ecosystem metabolism in a portion of the Sacramento-San Joaquin Delta. Metabolism estimates based on laboratory incubations, continuous in situ buoys, and an oxygen isotope approach all indicated the system was net heterotrophic, and calculated rates were comparable in magnitude when averaged over the 2-month study. Daily metabolic rates based on in situ buoys were the most variable, likely due to horizontal and vertical advection and poor portrayal of the dissolved oxygen budget. After temporally averaging in situ buoy estimates or smoothing the dissolved oxygen time series for tidal effects, rates were more comparable to the other methods, which may be necessary to account for tidal advection and unbalanced contributions from subhabitats within the metabolic footprint. Incubation-based rates represent the finest temporal and spatial scale and only account for pelagic processes, which may explain why incubation-based rates were lower than the other two methods. The oxygen isotope method provided temporally and spatially integrated rates that were bracketed by the other two methods and may be a valuable tool in systems matching the model requirements. Because uncertainty arises in each method from a number of assumptions and scaling calculations, the resolution of metabolic rates in estuaries is likely coarser and more variable than in other aquatic ecosystems.

California↗
USGS2015

Applications of optical sensors for high-frequency water-quality monitoring and research

The recent commercial availability of in-situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents over time scales during which environmental conditions actually change. Traditional approaches for data collection (daily to monthly discrete samples) are often limited by high sample collection, processing, and analytical costs, difficult site access, and logistical challenges, particularly for long-term sampling at a large number of sites. Optical sensors that continuously measure constituents in the environment by absorbance or fluorescence properties (Figure 1) have had a long history of use in oceanography for measuring highly resolved concentrations and fluxes of organic matter, nutrients, and algal material. However, much of the work using commercially-available optical sensors in rivers and streams has taken place in only the last few years. Figure 1. [NOT SHOWN] Optical sensor technology is now sufficiently developed to warrant broader application for research and monitoring in coastal and freshwater systems, and the United States Geological Survey (a U.S. science agency) is now using these sensors in a variety of research and monitoring programs to better understand water quality in-situ and in real-time. Examples are numerous and range from the applications of nitrate sensors for calculating loads to estuaries susceptible to hypoxia (Pellerin et al., 2014) to the use of fluorometers to estimate methymercury fluxes (Bergamaschi et al., 2011) and disinfection byproduct formation (Carpenter et al., 2013). Transmitting these data in real-time provides information that can be used for early trend detection, help identify monitoring gaps critical for water management, and provide science-based decision support across a range of issues related to water quality, freshwater ecosystems, and human health. Despite the value of these sensors, collecting data that meet high-quality standards requires investment in and adherence to tested and established methods and protocols for sensor operation and data management (Pellerin et al., 2013). For example, optical sensor measurements can be strongly influenced by a variety of matrix effects, including water temperature, inner filtering from highly colored water, and scattering of light by suspended particles (Downing et al., 2012). Characterizing and correcting sensors for these effects – as well as the continued development of common methodologies and protocols for sensor use – will be critical to ensuring comparable measurements across sites and over time. In addition, collaborative efforts such as the Nutrient Sensor Challenge (www.nutrients-challenge.org) will continue to accelerate the development, production and use of affordable, reliable and accurate sensors for a range of environments. REFERENCES Bergamaschi .B.A., Fleck J.A., Downing B.D., Boss E., Pellerin B.A., Ganju N.K., Schoellhamer D.H., Byington A.A., Heim W.A., Stephenson M., Fujii R. (2011), Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4): 1355-1371. Carpenter K.D., Kraus T.E.C., Goldman J.H., Saraceno J., Downing B.D., Bergamaschi B.A., McGhee G., Triplett T. (2013), Sources and Characteristics of Organic Matter in the Clackamas River, Oregon, Related to the Formation of Disinfection By-products in Treated Drinking Water: U.S. Geological Survey Scientific Investigations Report 2013–5001, 78 p. Downing .B.D., Pellerin B.A., Bergamaschi B.A., Saraceno J., Kraus T.E.K. (2012), Seeing the light: The effects of particles, temperature and inner filtering on in situ CDOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10: 767-775. Pellerin B.A., Bergamaschi B.A., Downing B.D., Saraceno J., Garrett J.D., Olsen L.D. (2013), Optical Techniques for the Determination of Nitrate in En

Conference Paper↗
USGS2025

Identifying conditions associated with outliers produced by three different chlorophyll fluorometers: A comparison of instrumentation and development of correction formulae

Measurements of chlorophyll concentration reported by fluorometers (fChl) are used in environmental research and monitoring, as inputs to models, and in the interpretation of remote sensing data. Researchers and managers benefit from understanding how to interpret and ensure the accuracy of fChl data collected by in situ fluorometers. Although fChl values produced by different manufacturers are often in agreement with discrete laboratory-derived Chlorophyll a (Chl a ) concentration measurements, there are instances in which results significantly differ. Further, when measuring fChl side by side, different fluorometers may report values that differ significantly from each other, despite passing calibration checks prior to deployment. We compared environmental conditions and phytoplankton species composition associated with instances in which fChl measurements from three different fluorometers (EXO2 Total Algae Smart Sensor, YSI Inc./Xylem Inc., Yellow Springs, Ohio; FluoroProbe III, bbe Moldaenke GmbH, Kiel, Germany; WETStar, Sea-Bird Scientific, Bellevue, Washington) were significantly different from laboratory-derived Chl a concentrations. Results indicated that elevated primary productivity, as indicated by high pH, dissolved oxygen, and the ratio of Chl a to phaeophytin, were correlated with underestimated fChl values recorded by each sensor. After removing outliers, we determined unique correction guidance for each of the three sensors and demonstrated that after applying correction formulae, fChl measurements produced by each sensor became directly comparable.

California↗
USGS2018

Passive experimental warming decouples air and sediment temperatures in a salt marsh

Open top chambers (OTCs) are a commonly used passive warming technique in experimental warming studies. OTCs have been shown to be effective in multiple types of terrestrial systems, but their utility in wetland environments remains uncertain. The objective of this work was to evaluate the effectiveness of using OTCs to warm a temperate salt marsh across diurnal and seasonal cycles. We found that OTCs are effective at warming air temperatures on the marsh, with average air temperatures 1.6 ± 0.007 °C and 1.1 ± 0.006 °C warmer within the high and low marsh, respectively over a 16-month period. In contrast, OTCs were ineffective at warming sediments, especially during the day. In fact, sediment temperatures within the OTC were cooler during the day relative to ambient conditions. Such daytime warming of air, but cooling of sediments relative to ambient conditions resulted in a significant decoupling of above and belowground temperatures in the marsh (r = -0.99 and -0.82 on low and high marsh, respectively). Our data indicate that shading by OTCs was responsible for the daytime sediment cooling relative to ambient conditions during most of the year, as incoming solar radiation was reduced by 30% within OTCs. Wet sediments require more energy to heat than the air due to their higher specific heat capacity. Thus, reductions in radiation by OTCs prevented effective warming of sediments, but still allowed for the warming of air. In turn, we conclude that OTCs are not an effective method to experimentally warm tidal marsh sediments.

Limnology and Oceanography: Methods↗
USGS2017

A practical method for the determination of total selenium in environmental samples using isotope dilution-hydride generation-inductively coupled plasma-mass spectrometry

A safe, practical, and accurate method for the determination of selenium (Se) in range of environmental samples was developed. Small sample masses, 5–20 mg, were amended with 82 Se enriched isotope for the isotope dilution (ID), preceding a multi-step wet digestion with nitric acid (HNO 3 ) and hydrogen peroxide (H 2 O 2 ). Samples were incubated in an autoclave for 3 h at 20 psi and 126°C. Digestates were subsequently reduced with concentrated hydrochloric acid to Se(IV) the most favorable valence for hydride generation (HG). The solutions were then analyzed on an ICP-MS equipped with Flow Injection system (FIAS-400). Polyatomic, isobaric, and background interferences were removed through the use of HG and ID with an 82 Se enriched isotope spike. Recoveries for certified reference materials were determined and averaged 96% for biological tissues (NRCC DOLT3, DOLT4, DORM2, TORT2, and TORT3, and NIST 2976) and 108% for estuarine sediment (NRCC PACS2) with an average coefficient of variation for replicate measurements of ∼ 3.5%. Limit of detection was 0.13 ng Se g −1 dry weight or 0.19 ng Se L −1 . This method can be broadly applied to biological tissues, sediments, suspended particulates, and water samples with minimal modifications making this method highly useful for assessing the ecotoxicology of total Se in aquatic ecosystems.

Limnology and Oceanography: Methods↗
USGS2020

Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner

Mangrove forests have adapted to sea level rise (SLR) increases by maintaining their forest floor elevation via belowground root growth and surface sediment deposits. Researchers use surface elevation tables (SETs) to monitor surface elevation change (SEC) in mangrove forests, after which this information is used to assess SLR resiliency or to dictate active forest management for vulnerable systems. This method requires significant investments in terms of time and human resources and is limited in the number of points it can measure per plot. We use a low‐cost, portable terrestrial laser scanning (TLS) system to assess SEC for three mangrove forests on Pohnpei Island (Federated States of Micronesia). Cloth simulation filtering was used for ground detection, after which results were refined by filtering points using angular orientation. Digital elevation models then were generated via kriging interpolation for data collected in 2017 and 2019, after which the heights of corresponding points were compared across years. Extreme elevation changes, due to disturbances such as footprints or fallen logs, were removed using interquartile range analysis. The TLS‐obtained average SEC ranged between −6.92 and +6.01 mm, which exhibited an average consistency of 72% when compared to simultaneously collected SET data (root mean square error = 1.36 mm). We contend that this approach represents an improvement over the manual method, where very few points typically are used, that is, ≅ 36 points vs. ≅ 30,000 points in the case of TLS, and could contribute to improved monitoring and management of these rapidly changing forest environments.

Limnology and Oceanography Methods↗
USGS2023

A novel boat-based field application of a high-frequency conductometric ammonium analyzer to characterize spatial variation in aquatic ecosystems

Documenting dissolved inorganic nitrogen (DIN) concentration and form at appropriate temporal and spatial scales is key to understanding aquatic ecosystem health, particularly as DIN fuels primary productivity. In addition to point and non-point source nutrient inputs, factors such as hydrology, geomorphology, temperature, light, and biogeochemical transformations influence nutrient dynamics in surface waters, allowing for the formation of steep spatial gradients and patchiness. Documenting nutrient variability is also necessary to identify sources, quantify transformation rates, and understand drivers. Due to logistical and cost constraints, it is often unfeasible to measure concentrations of nutrients in surface waters using discrete sampling followed by laboratory analysis at a resolution high enough to identify steep spatial gradients and patchiness. Because of these constraints, data generated from discrete sampling are limited in space and time, often missing key variabilities. Recent advancements of in situ nitrate plus nitrite (NO3- and NO2-) sensor technology has enabled highly temporally and spatially resolved NO3- concentration measurements in aquatic ecosystems. However, comparable information about ammonium (NH4+) concentrations remains unavailable. To address this need, U.S. Geological Survey collaborated with Timberline Instruments to modify their commercially available benchtop TL-2800 ammonia analyzer to collect high-frequency continuous (1 unique sample measurement per second) NH4+ concentration measurements at a micromolar (0.5 µM) resolution in flow-through mode while receiving water pumped from a moving boat. Although the utility of this method is described for spatial surveys, we anticipate that it would be adaptable to installation at a fixed station for continuous monitoring of NH4+ concentration.

California↗
USGS2014

A simple headspace equilibration method for measuring dissolved methane

Dissolved methane concentrations in the ocean are close to equilibrium with the atmosphere. Because methane is only sparingly soluble in seawater, measuring it without contamination is challenging for samples collected and processed in the presence of air. Several methods for analyzing dissolved methane are described in the literature, yet none has conducted a thorough assessment of the method yield, contamination issues during collection, transport and storage, and the effect of temperature changes and preservative. Previous extraction methods transfer methane from water to gas by either a "sparge and trap" or a "headspace equilibration" technique. The gas is then analyzed for methane by gas chromatography. Here, we revisit the headspace equilibration technique and describe a simple, inexpensive, and reliable method to measure methane in fresh and seawater, regardless of concentration. Within the range of concentrations typically found in surface seawaters (2-1000 nmol L -1 ), the yield of the method nears 100% of what is expected from solubility calculation following the addition of known amount of methane. In addition to being sensitive (detection limit of 0.1 ppmv, or 0.74 nmol L -1 ), this method requires less than 10 min per sample, and does not use highly toxic chemicals. It can be conducted with minimum materials and does not require the use of a gas chromatograph at the collection site. It can therefore be used in various remote working environments and conditions.

Limnology and Oceanography: Methods↗
USGS2004

A precise method for the analysis of δ18O of dissolved inorganic phosphate in seawater

A method for preparation and analysis of the oxygen isotope composition (δ 18 O) of dissolved inorganic phosphate (DIP) has been developed and preliminary results for water samples from various locations are reported. Phosphate is extracted from seawater samples by coprecipitation with magnesium hydroxide. Phosphate is further purified through a series of precipitations and resin separation and is ultimately converted to silver phosphate. Silver phosphate samples are pyrolitically decomposed to carbon monoxide and analyzed for δ 18 O. Silver phosphate samples weighing 0.7 mg (3.5 µmol oxygen) can be analyzed routinely with an average standard deviation of about 0.3‰. There is no isotope fractionation during extraction and blanks are negligible within analytical error. Reproducibility was determined for both laboratory standards and natural samples by multiple analyses. A comparison between filtered and unfiltered natural seawater samples was also conducted and no appreciable difference was observed for the samples tested. The δ 18 O values of DIP in seawater determined using this method range from 18.6‰ to 22.3‰, suggesting small but detectable natural variability in seawater. For the San Francisco Bay estuary DIP δ 18 O is more variable, ranging from 11.4‰ near the San Joaquin River to 20.1‰ near the Golden Gate Bridge, and was well correlated with salinity, phosphate concentration, and δ 18 O of water.

California↗
USGS2012

Automated measurement of diatom size

Size analysis of diatom populations has not been widely considered, but it is a potentially powerful tool for understanding diatom life histories, population dynamics, and phylogenetic relationships. However, measuring cell dimensions on a light microscope is a time-consuming process. An alternative technique has been developed using digital flow cytometry on a FlowCAM® (Fluid Imaging Technologies) to capture hundreds, or even thousands, of images of a chosen taxon from a single sample in a matter of minutes. Up to 30 morphological measures may be quantified through post-processing of the high resolution images. We evaluated FlowCAM size measurements, comparing them against measurements from a light microscope. We found good agreement between measurement of apical cell length in species with elongated, straight valves, including small Achnanthidium minutissimum (11-21 µm) and large Didymosphenia geminata (87–137 µm) forms. However, a taxon with curved cells, Hannaea baicalensis (37–96 µm), showed differences of ~ 4 µm between the two methods. Discrepancies appear to be influenced by the choice of feret or geodesic measurement for asymmetric cells. We describe the operating conditions necessary for analysis of size distributions and present suggestions for optimal instrument conditions for size analysis of diatom samples using the FlowCAM. The increased speed of data acquisition through use of imaging flow cytometers like the FlowCAM is an essential step for advancing studies of diatom populations.

Limnology and Oceanography: Methods↗
USGS2021

Estimating pelagic primary production in lakes: Comparison of 14C incubation and free-water O2 approaches

Historically, estimates of pelagic primary production in lake ecosystems were made by measuring the uptake of carbon-14 ( 14 C)-labeled inorganic carbon in samples incubated under laboratory or in situ conditions. However, incubation approaches are increasingly being replaced by methods that analyze diel changes in high-frequency in situ data such as free-water dissolved oxygen (O 2 ). While there is a rich literature on the comparison of approaches for estimating primary production using incubations (e.g., 14 C and O 2 bottle experiments), as well for approaches using high-frequency data (e.g., diel O 2 and CO 2 metabolism models), there are few direct comparisons of 14 C incubations and free-water O 2 approaches for estimating primary production. We used 20 lake-years of concurrent measurements of primary production quantified from high-frequency free-water O 2 data and 14 C incubations in four different lakes (4–7 years per lake) to compare these different approaches. Across all lakes, 61% of the 14 C production estimates were within the 95% credible intervals of the free-water O 2 production estimates. Error-in-variable regressions support the assumption that 14 C methods estimate a production value between gross primary production and net primary production and the bottle effect is constant across the entire range of production values considered here. There was little evidence that daily pelagic, epilimnetic estimates of primary production differed substantially based on the selection of free-water O 2 or 14 C approaches in these lakes during summer stratified conditions.

Limnology and Oceanography: Methods↗
USGS2023

Reconstructing missing data by comparing interpolation techniques: Applications for long-term water quality data

Missing data are typical yet must be addressed for proper inferences or expanding datasets to guide our limnological understanding and management of aquatic systems. Interpolation methods (i.e., estimating missing values using known values within the dataset) can alleviate data gaps and common problems. We compared seven popular interpolation methods for predicting substantial missingness in a long-term water quality dataset from the Upper Mississippi River, U.S.A. The dataset included 80,000 sampling sites collected over 30 yr that had substantial missingness for total nitrogen (TN), total phosphorus (TP), and water velocity. For all three interpolated water quality variables, random forests had very high prediction accuracy and outperformed the methods of ordinary kriging, polynomial regressions, regression trees, and inverse distance weighting. TP had a mean absolute error (MAE) of 0.03 mg (L-TP) −1 , TN had a MAE of 0.39 mg (L-TN) −1 , and water velocity had a MAE of 0.10 m s −1 . The random forests' error rates were mapped and showed low spatiotemporal variability across the riverscape, indicating high model performance across many habitat types and large spatial scales. In the current era of “big data,” interpolation becomes an imperative step prior to ecological analyses yet remains unfamiliar and underutilized. Our research briefly describes the importance of addressing missingness and provides a roadmap to conduct model intercomparisons of other big datasets. We also share adaptable data analysis scripts, which allows others to readily conduct interpolation comparisons for many limnology applications and contexts.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2025

Spatial mapping of dissolved methane using an in situ sensor in Puget Sound

Release of methane, as gas bubbles or in the dissolved phase, from the seafloor has been observed in coastal waters (< 200 m) and deep ocean basins (> 1000 m). Methane dissolution within the water column affects the geochemistry of the surrounding water, leading to localized oxygen loss and potential escape to the atmosphere, particularly from shallower sites. Traditional methods for detecting and quantifying dissolved methane rely on collecting discrete water samples for ship- or land-based ex situ analysis and post processing. Here, we report on the use of a reduced response time, in situ methane sensor, the Sensor for Aqueous Gases in the Environment (SAGE), for detecting and quantifying dissolved methane concentrations in a wide range of seafloor environments. During a Fall 2022 research cruise on the R/V Thomas G. Thompson in Puget Sound, SAGE was integrated onto a towed conductivity/temperature/depth rosette and deep-sea camera system with live-stream 1 Hz telemetry and used to spatially map the concentration of methane approximately 1 m above the seafloor. The site had been previously identified as an active methane plume field characterized by gas bubbles, fluid venting, and a faulted seabed. The widespread background dissolved concentration of methane measured by SAGE was 83 nM, and a range of 78–670 nM was observed throughout the survey. The results highlight the capacity of SAGE to map the spatial and temporal variability of dissolved methane concentrations in situ and to identify and localize sites of variable methane emissions from the seafloor.

Washington↗
USGS2014

Autonomous bed-sediment imaging-systems for revealing temporal variability of grain size

We describe a remotely operated video microscope system, designed to provide high-resolution images of seabed sediments. Two versions were developed, which differ in how they raise the camera from the seabed. The first used hydraulics and the second used the energy associated with wave orbital motion. Images were analyzed using automated frequency-domain methods, which following a rigorous partially supervised quality control procedure, yielded estimates to within 20% of the true size as determined by on-screen manual measurements of grains. Long-term grain-size variability at a sandy inner shelf site offshore of Santa Cruz, California, USA, was investigated using the hydraulic system. Eighteen months of high frequency (min to h), high-resolution (μm) images were collected, and grain size distributions compiled. The data constitutes the longest known high-frequency record of seabed-grain size at this sample frequency, at any location. Short-term grain-size variability of sand in an energetic surf zone at Praa Sands, Cornwall, UK was investigated using the ‘wave-powered’ system. The data are the first high-frequency record of grain size at a single location of a highly mobile and evolving bed in a natural surf zone. Using this technology, it is now possible to measure bed-sediment-grain size at a time-scale comparable with flow conditions. Results suggest models of sediment transport at sandy, wave-dominated, nearshore locations should allow for substantial changes in grain-size distribution over time-scales as short as a few hours.

California↗
USGS2017

A coupled metabolic-hydraulic model and calibration scheme for estimating of whole-river metabolism during dynamic flow conditions

Conventional methods for estimating whole-stream metabolic rates from measured dissolved oxygen dynamics do not account for the variation in solute transport times created by dynamic flow conditions. Changes in flow at hourly time scales are common downstream of hydroelectric dams (i.e. hydropeaking), and hydrologic limitations of conventional metabolic models have resulted in a poor understanding of the controls on biological production in these highly managed river ecosystems. To overcome these limitations, we coupled a two-station metabolic model of dissolved oxygen dynamics with a hydrologic river routing model. We designed calibration and parameter estimation tools to infer values for hydrologic and metabolic parameters based on time series of water quality data, achieving the ultimate goal of estimating whole-river gross primary production and ecosystem respiration during dynamic flow conditions. Our case study data for model design and calibration were collected in the tailwater of Glen Canyon Dam (Arizona, USA), a large hydropower facility where the mean discharge was 325 m3 s 1 and the average daily coefficient of variation of flow was 0.17 (i.e. the hydropeaking index averaged from 2006 to 2016). We demonstrate the coupled model’s conceptual consistency with conventional models during steady flow conditions, and illustrate the potential bias in metabolism estimates with conventional models during unsteady flow conditions. This effort contributes an approach to solute transport modeling and parameter estimation that allows study of whole-ecosystem metabolic regimes across a more diverse range of hydrologic conditions commonly encountered in streams and rivers.

Arizona↗
USGS2015

Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates

Golden alga ( Prymnesium parvum ) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from &sim; 80% to &sim; 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.

New Mexico, Texas↗
USGS2017

Clearing the waters: Evaluating the need for site-specific field fluorescence corrections based on turbidity measurements

In situ fluorescent dissolved organic matter (fDOM) measurements have gained increasing popularity as a proxy for dissolved organic carbon (DOC) concentrations in streams. One challenge to accurate fDOM measurements in many streams is light attenuation due to suspended particles. Downing et al. (2012) evaluated the need for corrections to compensate for particle interference on fDOM measurements using a single sediment standard in a laboratory study. The application of those results to a large river improved unfiltered field fDOM accuracy. We tested the same correction equation in a headwater tropical stream and found that it overcompensated fDOM when turbidity exceeded ∼300 formazin nephelometric units (FNU). Therefore, we developed a site-specific, field-based fDOM correction equation through paired in situ fDOM measurements of filtered and unfiltered streamwater. The site-specific correction increased fDOM accuracy up to a turbidity as high as 700 FNU, the maximum observed in this study. The difference in performance between the laboratory-based correction equation of Downing et al. (2012) and our site-specific, field-based correction equation likely arises from differences in particle size distribution between the sediment standard used in the lab (silt) and that observed in our study (fine to medium sand), particularly during high flows. Therefore, a particle interference correction equation based on a single sediment type may not be ideal when field sediment size is significantly different. Given that field fDOM corrections for particle interference under turbid conditions are a critical component in generating accurate DOC estimates, we describe a way to develop site-specific corrections.

Limnology and Oceanography: Methods↗
USGS2019

Improving estimates and forecasts of lake carbon dynamics using data assimilation

Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite successful use of this technique in other fields. Data assimilation adds value to both observations and models by constraining models with observations of the system and by leveraging knowledge of the system formalized by the model to objectively fill observation gaps. In this article, we highlight the utility of data assimilation in lake carbon cycling research by using the ensemble Kalman filter to combine simple lake carbon models with observations of lake carbon pools and fluxes. We demonstrate that data assimilation helps reduce uncertainty in estimates of lake carbon pools and fluxes and more accurately estimate the true carbon pool size compared to estimates derived from observations alone. Data assimilation techniques should be embraced as valuable tools for lake biogeochemists interested in learning about ecosystem dynamics and forecasting ecosystem states and processes.

Limnology and Oceanography: Methods↗