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USGS2026

Whatever it takes— Shaping the L&O Letters Early Career Publication Honor to deliver true benefit

There are clear advantages for those who openly share their research. Publishing Open Access (OA) articles can increase author visibility (McCabe and Snyder 2014 ), improve productivity metrics (i.e., more diverse and higher citation rates; Huang et al. 2024 ; Piwowar et al. 2018 ), widen collaborative networks (Tai and Robinson 2018 ), and help secure future funding and/or comply with funder mandates (Herrmannova et al. 2019 ; Larivière and Sugimoto 2018 ; McKiernan et al. 2016 and references therein). These benefits can be vital for students and early career researchers (ECRs) trying to advance and thrive in academia. However, publishing papers in Gold OA journals such as L&O Letters comes at a notable financial cost, as these journals require that the corresponding author (or their organization or funder) pay a fee to make their published article immediately freely available to the public. These article processing charges can be prohibitively expensive (Fontúrbel and Vizentin-Bugoni 2021 ; Mekonnen et al. 2022 ; Ross-Hellauer et al. 2022 ). While Read and Publish agreements and waiver programs may be available to help cover these costs, these programs often exclude independent authors as well as those affiliated with ineligible or non-participating institutions (e.g., publisher waivers using the Research4Life eligibility criteria for access currently only allow authors from one of 13 South American countries/territories to publish free of charge). Besides the financial barrier, authors from underrepresented groups can also face a myriad of other publishing roadblocks, such as linguistic challenges (for speakers of English as a foreign language; Amano et al. 2023 ; Franco-Santos 2024 ; Ramírez-Castañeda 2020 ) and geopolitical-scientific bias (e.g., science conducted in the Global South being seen as less impactful and innovative than that conducted in the Global North; Ghosh 2022 ; Smits et al. 2025 ). For context, Global South (GS) and Global North (GN) are not geographic determinations (i.e., South and North hemispheres), but geopolitical classifications regarding a nation's level of development (underdeveloped, developing, or developed). For example: Australia and Brazil are both located in the southern hemisphere, but the former is considered as a Global North (developed) country and the latter as a Global South (underdeveloped or developing) country. When a subset of researchers is unable to openly publish their work, the diversity of voices represented in OA literature can decline (Williams et al. 2023 ). Loss of diversity is a loss to science, as diversity increases productivity, innovation, and scientific impact (refer to opening quote; Freeman and Huang 2014 ; AlShebli et al. 2018 ; Tomillo et al. 2022 ). To partially address the above-mentioned challenges and enable underfunded ECRs to publish their work in OA format, the biennial L&O Letters Early Career Publication Honor (ECPH) was established in 2020 by the ASLO Raelyn Cole Editorial (RCE) Fellows (Hotaling et al. 2022 ). Below we reflect on the benefits, outcomes, and scientific impact of the 2022 call and introduce the articles it helped publish in L&O Letters , which are bundled in this section of the ECPH Virtual Issue. Articles published in L&O Letters during other calls are available in their respective sections. We also refer the reader to six articles published by ECRs in other journals (not included in this Virtual Issue) whose content originally warranted their leading author an ECPH in 2022.

Limnology and Oceanography Letters↗
USGS2015

A method for estimating the diffuse attenuation coefficient (KdPAR)from paired temperature sensors

A new method for estimating the diffuse attenuation coefficient for photosynthetically active radiation ( K d PAR ) from paired temperature sensors was derived. We show that during cases where the attenuation of penetrating shortwave solar radiation is the dominant source of temperature changes, time series measurements of water temperatures at multiple depths ( z 1 and z 2 ) are related to one another by a linear scaling factor ( α ). K d PAR can then be estimated by the simple equation K d PAR = ln( α )/( z 2 − z 1 ). A suggested workflow is presented that outlines procedures for calculating K d PAR according to this paired temperature sensor (PTS) method. This method is best suited for conditions when radiative temperature gains are large relative to physical noise. These conditions occur frequently on water bodies with low wind and/or high K d PAR s but can be used for other types of lakes during time periods of low wind and/or where spatially redundant measurements of temperatures are available. The optimal vertical placement of temperature sensors according to a priori knowledge of K d PAR is also described. This information can be used to inform the design of future sensor deployments using the PTS method or for campaigns where characterizing sub‐daily changes in temperatures is important. The PTS method provides a novel method to characterize light attenuation in aquatic ecosystems without expensive radiometric equipment or the user subjectivity inherent in Secchi depth measurements. This method also can enable the estimation of K d PAR at higher frequencies than many manual monitoring programs allow.

Limnology and Oceanography: Methods↗
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

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↗
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↗
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↗
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↗
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↗
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↗
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↗
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↗
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↗
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↗
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↗