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Results for “Limnology and Oceanography Methods”

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At least 37 records · Page 2Linked to original sources
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 ∼ 80% to ∼ 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↗
USGS2018

Using in situ UV-Visible spectrophotometer sensors to quantify riverine phosphorus partitioning and concentration at a high frequency

Accurate riverine phosphorus concentration measurements are often critical to meet watershed management goals. Phosphorus monitoring programs often rely on proxy variables such as turbidity and discharge and have limited ability to accurately estimate concentrations of dissolved phosphorus fractions that are most bioavailable. Optical water quality sensors can make subhourly measurements and have been shown to reduce uncertainty in load estimates and reveal high-frequency storm dynamics for nitrate and dissolved organic carbon. We evaluated the utility of in situ UV-Visible spectrophotometers to predict total, dissolved, and soluble reactive phosphorus concentrations in streams draining agricultural, urban, and forested land use/land covers. We present the first statistically validated application of optical water quality sensors to demonstrate how sensors may perform in predicting phosphorus fraction concentrations through training set models. Total phosphorus predictions from UV-Visible spectra were optimal when models were site-specific, and the proportion of variance explained was generally as high as or higher than the results of other studies that rely only on discharge and turbidity. However, root mean square errors for total phosphorus models were relatively high compared to the median concentrations at each site. Models to predict dissolved and soluble reactive phosphorus concentrations explained a greater proportion of the variance than any other known proxy variable technique, and results varied by land use/land cover. Though accuracy limitations remain, this approach has potential to predict concurrent total, dissolved, and soluble reactive phosphorus concentrations at a high frequency for many applications in water quality research and management communities.

Vermont↗
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↗
USGS2020

Reduction of taxonomic bias in diatom species data

Inconsistency in taxonomic identification and analyst bias impede the effective use of diatom data in regional and national stream and lake surveys. In this study, we evaluated the effect of existing protocols and a revised protocol on the precision of diatom species counts. The revised protocol adjusts four elements of sample preparation, taxon identification and enumeration, and quality control (QC). We used six independent datasets to assess the effect of the adjustments on analytical outcomes. The first dataset was produced by three laboratories with a total of five analysts following established protocols (Charles et al. 2002), or their slight variations. The remaining datasets were produced by 1-3 laboratories with a total of 2-3 analysts following a revised protocol. The revised protocol included the following modifications: 1) development of coordinated pre-count voucher floras based on morphological operational taxonomic units (mOTUs), 2) random assignment of samples to analysts, 3) post-count identification and documentation of taxa (as opposed to an approach in which analysts assign names while they enumerate), and 4) increased use of QC samples. The revised protocol reduced taxonomic bias, as measured by reduction in analyst signal, and improved similarity among QC samples. Reduced taxonomic bias improves the performance of biological assessments, facilitates transparency across studies, and refines estimates of diatom species distributions.

Limnology and Oceanography: Methods↗
USGS2023

An assessment of HgII to preserve carbonate system parameters in organic-rich estuarine waters

This work assesses the effectiveness of sample preservation techniques for measurements of pH T (total scale), total dissolved inorganic carbon (C T ), and total alkalinity (A T ) in organic-rich estuarine waters as well as the internal consistency of measurements and calculations (e.g., A T , pH T , and C T ) in these waters. Using mercuric chloride (HgCl 2 )-treated and untreated water samples, measurements of these carbonate system parameters were examined over a period of 3 months. Respiration of dissolved organic matter in untreated samples created large discrepancies in C T concentrations (~37 μ mol kg −1 increase, p < 0.0001), while C T was effectively constant in treated samples (3095.0 ± 1.14 μ mol kg −1 ). A T changes were observed for both treated and untreated samples, with HgCl 2 -treated samples showing the greatest variation (~ 26 μ mol kg −1 decrease, p < 0.001). In response to changing A T /C T ratios, pH T changes occurred in both treated and untreated samples but were relatively small in treated samples. Results in organic-rich estuarine waters that reflect the in situ carbonate system characteristics of the samples at the time of collection can be improved when samples obtained for C T and A T analysis are collected and stored separately. Accurate analyses of C T can be obtained by filtration and preservation with HgCl 2 . Accuracy of A T analyses can be improved by filtration and storage without adding HgCl 2 . The quality of pH T measurements can be improved by prompt analysis in the field and, if this cannot be accomplished, then samples can be preserved with HgCl 2 and measured in the laboratory within 1 week.

Limnology and Oceanography: Methods↗
USGS2024

A video monitoring and computational system for estimating migratory juvenile fish abundance in river systems

Diadromous fishes migrate between marine and fresh waters for reproduction. For anadromous species, which spawn in freshwater, improved access to freshwater spawning and nursery habitats and ability of juveniles to emigrate to the ocean may support population recovery. Despite the potentially enormous influence of early life stage survival on adult population size, managers and scientists have limited capacity to assess numbers of juvenile anadromous fishes leaving freshwater ecosystems. Such data are critical for evaluating reproductive success and habitat suitability and have been identified as a top priority in anadromous fish research and management. We developed a state-of-the-art underwater video and computational system to collect videos to estimate abundances and migration timing for juvenile river herring ( Alosa pseudoharengus ; Alosa aestivalis ). We collected continuous video in the Monument River (Bourne, Massachusetts, USA) from June to November 2017. We trained three types of neural network models to detect and count fish in video frames and evaluated model performance by comparing human counts to model outputs. Our top model assessed presence and absence ( F 1 = 87%) and counted fish (counting error 9.4%) with an accuracy comparable to human counters ( F 1 = 88%). Our system's capability to collect accurate counts of emigrating juveniles will provide critical information that could be related to the numbers of spawning adults, system-specific productivity, and spawning and nursery habitat suitability. Both the video collection system and computational model may be transferrable to other sites and for other species where tracking juvenile emigration may inform management efforts.

Massachusetts↗
USGS2026

Demonstration, validation, and application of hyperspectral microscopy for the collection of cyanobacterial spectral signatures

Cyanobacterial and other algal blooms are an environmental concern in waterbodies worldwide. While these blooms are a nuisance for recreational activities, they can also be harmful to human and wildlife health when the algae produce and release toxins. Algal community composition can be monitored and analyzed by acquiring hyperspectral images that provide information on various photosynthetic and accessory pigments. Validated, traceable measurements are needed to compare data collected by different hyperspectral instruments. In this proof-of-concept study, we detail the development and validation of a custom hyperspectral microscopy imaging system and assess whether this technology can differentiate between cyanobacteria genera based on differences in their reflectance characteristics. As not all cyanobacteria produce toxins, the ability to distinguish among taxa could be used to identify potential toxin-producers and guide field sampling and further research. Spectral characterization of these taxa contributes to remote sensing efforts to characterize and identify cyanobacterial genera at larger spatial scales.

Oregon↗
USGS2026

A simplified two-station approach for modeling metabolism in dam tailwaters subject to diel flow variation

Tailwaters are ubiquitous and highly managed ecosystems whose food webs often rely disproportionately on autochthonous energy. In situ continuous dissolved oxygen data are increasingly being used to estimate gross primary productivity and ecosystem respiration in rivers, but this approach is complicated in tailwaters, where upriver discontinuities (i.e., dams) violate commonly employed one-station approaches. In such cases, two-station metabolism models can be applied, although substantial diel variation in flow (a common outcome of hydropower production) requires more complex treatment of water parcel travel times. Here, we present a new two-station metabolism model that allows estimation of reach-scale gross primary productivity and ecosystem respiration in streams and rivers that experience within-day variation in flow. Our approach simplifies two-station variable flow model implementation compared to previous efforts. We apply our model to a 6-yr dissolved oxygen time series and use Bayesian inference to estimate daily gross primary productivity, ecosystem respiration, and gas exchange velocity ( k 600 ) for a ~12-km reach of the Colorado River downriver of Glen Canyon Dam. We compare our model's performance to a more mechanistically detailed and computationally intensive Eulerian dynamic flow model and also to a widely-used one-station model that uses assumptions of reach uniformity that are often strongly violated in tailwaters. These comparisons show that our metabolism estimates conform with output from the more detailed dynamic flow model and that the one-station approach deviates substantially from both two-station approaches. Our new stream metabolism model can help resolve a fundamental analytical impediment in tailwater ecology.

Arizona↗
USGS2005

Integrating seepage heterogeneity with the use of ganged seepage meters

The usefulness of standard half-barrel seepage meters for measurement of fluxes between groundwater, and surface water is limited by the small bed area that each measurement represents and the relatively large associated labor costs. Standard half-barrel cylinders were ganged together to allow one measurement of the summed seepage through all of the meters, reducing labor cost and increasing the representative area of measurement. Comparisons of ganged versus individual-meter measurements at two lakes, under both inseepage and outseepage conditions, indicate little loss of efficiency resulting from routing seepage water through the ganging system. Differences between summed and ganged seepage rates were not significant for all but the fastest rates of seepage. At flow rates greater than about 250 mL min −1 , ganged values were as low as 80% of summed values. Gangedmeter head losses also were calculated to determine their significance relative to hydraulic-head gradients measured at the field sites. The calculated reduction in hydraulic gradient beneath the seepage meters was significant only for the largest measured seepage rates. A calibration tank was used to determine single-meter and gangedmeter efficiencies compared to known seepage rates. Single-cylinder seepage meters required an average correction factor of 1.05 to convert measured to actual values, whereas the ganged measurements made in the tank required a larger correction factor of 1.14. Although manual measurements were used in these tests, the concept of ganging seepage cylinders also would be useful when used in conjunction with automated flowmeters.

Limnology and Oceanography: Methods↗
USGS2007

Toward a transport-based analysis of nutrient spiraling and uptake in streams

Nutrient addition experiments are designed to study the cycling of nutrients in stream ecosystems where hydrologic and nonhydrologic processes determine nutrient fate. Because of the importance of hydrologic processes in stream ecosystems, a conceptual model known as nutrient spiraling is frequently employed. A central part of the nutrient spiraling approach is the determination of uptake length ( S w ), the average distance traveled by dissolved nutrients in the water column before uptake. Although the nutrient spiraling concept has been an invaluable tool in stream ecology, the current practice of estimating uptake length from steady‐state nutrient data using linear regression (called here the “ S w approach”) presents a number of limitations. These limitations are identified by comparing the exponential S w equation with analytical solutions of a stream solute transport model. This comparison indicates that (1) S w is an aggregate measure of uptake that does not distinguish between main channel and storage zone processes, (2) S w is an integrated measure of numerous hydrologic and nonhydrologic processes—this process integration may lead to difficulties in interpretation when comparing estimates of S w , and (3) estimates of uptake velocity and areal uptake rate ( v f and U ) based on S w are not independent of system hydrology. Given these findings, a transport‐based approach to nutrient spiraling is presented for steady‐state and time‐series data sets. The transport‐based approach for time‐series data sets is suggested for future research on nutrient uptake as it provides a number of benefits, including the ability to (1) separately quantify main channel and storage zone uptake, (2) quantify specific hydrologic and nonhydrologic processes using various model parameters (process separation), (3) estimate uptake velocities and areal uptake rates that are independent of hydrologic effects, and (4) use shortterm, non‐plateau nutrient additions such that the effects of regeneration and mineralization are minimized. In summary, the transport‐based, time‐series approach provides a means of estimating traditional measures of nutrient uptake ( S w , v f , U ) while providing additional information on the location and magnitude of uptake (main channel versus storage zone). Application of the transport‐based approach to time‐series data from Green Creek, Antarctica, indicates that the bulk of nitrate uptake (~74% to 100%) occurred within the main channel where benthic uptake by algal mats is a likely process. Substantial uptake (~26%) also occurred in the storage zone of one reach, where uptake is attributed to the microbial community.

Limnology and Oceanography: Methods↗
USGS2009

A simple technique for continuous measurement of time-variable gas transfer in surface waters

Mass balance models of dissolved gases in streams, lakes, and rivers serve as the basis for estimating wholeecosystem rates for various biogeochemical processes. Rates of gas exchange between water and the atmosphere are important and error-prone components of these models. Here we present a simple and efficient modification of the SF6 gas tracer approach that can be used concurrently while collecting other dissolved gas samples for dissolved gas mass balance studies in streams. It consists of continuously metering SF6-saturated water directly into the stream at a low rate of flow. This approach has advantages over pulse injection of aqueous solutions or bubbling large amounts of SF6 into the stream. By adding the SF6 as a saturated solution, we minimize the possibility that other dissolved gas measurements are affected by sparging and/or bubble injecta. Because the SF6 is added continuously we have a record of changing gas transfer velocity (GTV) that is contemporaneous with the sampling of other nonconservative ambient dissolved gases. Over a single diel period, a 30% variation in GTV was observed in a second-order stream (Sugar Creek, Indiana, USA). The changing GTV could be attributed in part to changes in temperature and windspeed that occurred on hourly to diel timescales.

Limnology and Oceanography: Methods↗
USGS2011

An inexpensive instrument for measuring wave exposure and water velocity

Ocean waves drive a wide variety of nearshore physical processes, structuring entire ecosystems through their direct and indirect effects on the settlement, behavior, and survivorship of marine organisms. However, wave exposure remains difficult and expensive to measure. Here, we report on an inexpensive and easily constructed instrument for measuring wave-induced water velocities. The underwater relative swell kinetics instrument (URSKI) is a subsurface float tethered by a short (<1 m) line to the seafloor. Contained within the float is an accelerometer that records the tilt of the float in response to passing waves. During two field trials totaling 358 h, we confirmed the accuracy and precision of URSKI measurements through comparison to velocities measured by an in situ acoustic Doppler velocimeter and those predicted by a standard swell model, and we evaluated how the dimensions of the devices, its buoyancy, and sampling frequency can be modified for use in a variety of environments.

Limnology and Oceanography: Methods↗
USGS2012

Seeing the light: the effects of particles, dissolved materials, and temperature on in situ measurements of DOM fluorescence in rivers and streams

Field-deployable sensors designed to continuously measure the fluorescence of colored dissolved organic matter (FDOM) in situ are of growing interest. However, the ability to make FDOM measurements that are comparable across sites and over time requires a clear understanding of how instrument characteristics and environmental conditions affect the measurements. In particular, the effects of water temperature and light attenuation by both colored dissolved material and suspended particles may be significant in settings such as rivers and streams. Using natural standard reference materials, we characterized the performance of four commercially-available FDOM sensors under controlled laboratory conditions over ranges of temperature, dissolved organic matter (DOM) concentrations, and turbidity that spanned typical environmental ranges. We also examined field data from several major rivers to assess how often attenuation artifacts or temperature effects might be important. We found that raw (uncorrected) FDOM values were strongly affected by the light attenuation that results from dissolved substances and suspended particles as well as by water temperature. Observed effects of light attenuation and temperature agreed well with theory. Our results show that correction of measured FDOM values to account for these effects is necessary and feasible over much of the range of temperature, DOM concentration, and turbidity commonly encountered in surface waters. In most cases, collecting high-quality FDOM measurements that are comparable through time and between sites will require concurrent measurements of temperature and turbidity, and periodic discrete sample collection for laboratory measurement of DOM.

Limnology and Oceanography: Methods↗
USGS2014

Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

Limnology and Oceanography: Methods↗
USGS2008

A modeling tool to evaluate regional coral reef responses to changes in climate and ocean chemistry

We developed a spreadsheet-based model for the use of managers, conservationists, and biologists for projecting the effects of climate change on coral reefs at local-to-regional scales. The COMBO (Coral Mortality and Bleaching Output) model calculates the impacts to coral reefs from changes in average SST and CO2 concentrations, and from high temperature mortality (bleaching) events. The model uses a probabilistic assessment of the frequency of high temperature events under a future climate to address scientific uncertainties about potential adverse effects. COMBO offers data libraries and default factors for three selected regions (Hawai'i, Great Barrier Reef, and Caribbean), but it is structured with user-selectable parameter values and data input options, making possible modifications to reflect local conditions or to incorporate local expertise. Preliminary results from sensitivity analyses and simulation examples for Hawai'i demonstrate the relative importance of high temperature events, increased average temperature, and increased CO2 concentration on the future status of coral reefs; Illustrate significant interactions among variables; and allow comparisons of past environmental history with future predictions. ?? 2008, by the American Society of Limnology and Oceanugraphy, Inc.

Limnology and Oceanography: Methods↗