Freshwater cyanobacterial harmful algal blooms (CHABs) are a well-known global public health threat. Monitoring and early detection of CHAB toxins are currently accomplished using labor-intensive sampling techniques and subsequent shore-based analyses, with results typically reported 24-48 h after sample collection. We have developed and implemented an uncrewed, autonomous mobile sampler-analytical system capable of conducting targeted in situ toxin measurements in < 2 h. A surface plasmon resonance (SPR) instrument was combined with the environmental sample processor (ESP) to fully automate detection and quantification of particle-associated cyanobacterial microcystins (pMC). This sensor-sampler system was integrated with a long-range autonomous underwater vehicle (LRAUV) and deployed in western Lake Erie for field trials in the summer of 2021. The LRAUV was remotely piloted to acquire samples at selected locations within and adjacent to a CHAB. Sixteen pMC measurements ranging from 0.09 to 0.55 mu g/L lake water were obtained over a 14-day period without recovery of the LRAUV. The SPR/ESP/LRAUV system complements existing satellite, aerial, and manual sampling CHAB survey techniques, and could be used to enhance predictive models that underpin bloom and toxicity forecasts. This system is also extensible to detection of other algal toxins in freshwater and marine environments, with its near real-time assessment of bloom toxin levels potentially offering additional socioeconomic benefits and public health protection in a variety of settings.
Characterizing marine phytoplankton community variability is crucial to designing sampling strategies and interpreting time series. Satellite remote sensing, microscopy sampling, and flow through imaging systems have widely different resolutions: from weekly or monthly with microscopy sampling to daily when no cloud cover or glint is present with polar-orbiting satellites, and hourly for autonomous imaging instruments. To improve our understanding of data robustness against sampling resolution at different taxonomic levels, we analyze 2 yr of data from an Imaging FlowCytobot with hourly resolution and resample it to daily, satellite-temporal, and weekly microscopy sampling resolution. We show that weekly and satellite-temporal resolutions are sufficient to resolve general community composition but that the randomness of satellite-temporal resolution can result in overrepresenting or underrepresenting certain categories. While the yearly phytoplankton biomass bloom is detected in late winter by all four resolutions, category-specific yearly blooms are generally consistent in timing but often underestimated or missed by the weekly and satellite-temporal resolutions, introducing a bias in year-to-year comparisons. A minimum of biweekly sampling, particularly during known bloom periods, would lower the bias in such categories. Similarly, sampling time should be considered as daily variations are category-specific. Overall, morning and low tide sampling tended to have higher biomass. We provide tables for categories detected by the IFCB in Narragansett Bay with their major bloom characteristics and recorded daily variability to inform future sampling designs. These results provide tools to interpret past and future time series, including possible detection of specific taxonomic groups with targeted satellite algorithms.
The use of camera and video technologies for conducting underwater surveys has rapidly expanded over the past several decades. However, the utility of these systems can be significantly hampered by numerous logistical factors, including limited underwater visibility, rough bottom topography, and ease of use for the operator. Video studies can be difficult to compare when methods and terminologies differ. Here, we describe the development of a cost-effective diver-propelled underwater ski-based video system for rapidly acquiring videos in challenging shallow, high-energy rocky benthic habitats for quantifying fish, macroalgae, and invertebrates in a coastal temperate system. The ski held the camera at a (relatively) fixed distance from the seafloor, we used parallel lasers to quantify our observations, and we used the standardized language of the Coastal and Marine Ecological Classification Standard to acquire consistent quantitative data to serve as an ecological baseline, also including archived images. Our results indicate that the ski proved to be an effective tool for capturing insightful data that would otherwise be very difficult and time-consuming to collect. Our baseline and repeatable methods can be used by other investigators at this or other locations for monitoring, re-evaluation, or comparisons to other sites.
Reduced light is one of the primary threats to seagrass meadows in the coming decades, with reduced light reaching the benthos due to eutrophication. We assessed a multispectral photography technique using near‐infrared photography to estimate chlorophyll content in the seagrass Zostera marina . Using near‐infrared and red wavelength cameras in the lab environment, we measured normalized difference vegetation index (NDVI) in photographs of sampled seagrass leaves. In samples taken from three different environments, we found a positive correlation between lab‐based NDVI and chlorophyll content, with variation attributable to leaf age. In samples grown under different light conditions, we found high levels of NDVI associated with lower light possibly due to seagrass photoacclimation. This method may be used in addition to existing seagrass monitoring methods to collect data on seagrass photic status and estimate chlorophyll content, and detect possible light limitation due to turbidity or high epibiota cover. The relatively low cost and time required for this method may make it useful where researchers are already collecting and imaging seagrass as part of routine monitoring.
The ocean–atmosphere exchange of carbon largely depends on the balance between carbon export of particulate organic carbon (POC) as sinking marine particles, and POC remineralization by attached microbial communities. Despite the vast spectrum of types, sources, ages, shapes, and composition of individual sinking particles, they are usually considered as a bulk together with their associated microbial communities. This limits our mechanistic understanding of the biological carbon pump (BCP) and its feedback on the global carbon cycle. We established a method to sample individual particles while preserving their shape, structure, and nucleic acids by placing a jellified RNA‐fixative at the bottom of drifting sediment traps. Coupling imaging of individual particles with associated 16S rRNA analysis reveals that active bacterial communities are highly heterogenous from one particles origin to another. In contrast to lab‐made particles, we found that complex in situ conditions lead to heterogeneity even within the same particle type. Our new method allows to associate patterns of active prokaryotic and functional diversity to particle features, enabling the detection of potential remineralization niches. This new approach will therefore improve our understanding of the BCP and numerical representation in the context of a rapidly changing ocean.
Freshwaters are impacted by many pollutants. Scientists and resource managers need to reliably detect and monitor these pollutants by employing appropriate sampling techniques to quantify and mitigate their impacts. Emerging freshwater contaminants such as microplastics are difficult to monitor as effective sampling techniques have not been fully developed and lack standardization. Here, we propose a novel method, adapted from stream invertebrate kick‐net sampling, which can be employed for long‐term, standardized microplastic monitoring. We hypothesized that invertebrate kick‐net sampling would be effective at collecting microplastics, capturing higher microplastic concentrations than standard microplastic sampling, due to collecting suspended and benthic microplastics simultaneously. We sampled 28 streams for microplastics using standard drift and sediment microplastic collection methods and invertebrate kick‐netting. As predicted, kick‐netting captured microplastics at higher concentrations than conventional sampling, regardless of whether values were expressed per volume of water (as in drift samples), per kg of sediment or per area sampled (as in benthic samples). Consequently, kick‐net sampling has the potential to be a time‐ and cost‐efficient tool for monitoring microplastic pollution. We recommend the employment of invertebrate kick‐netting as a new, standardized means to investigate and routinely monitor microplastic concentrations worldwide. This would generate a more robust dataset of global freshwater microplastic pollution, making it possible to answer unresolved questions pertaining to changes in microplastic pollution profiles. Standardized, long‐term records of microplastic concentrations in freshwaters would also allow a more accurate assessment of the ecological risks of microplastic pollution. Finally, long‐term microplastic data could be used to inform much‐needed regulatory decisions pertaining to microplastic pollution.
ABSTRACTZooplankton analysis represents a bottleneck in marine ecology studies due to the difficulty to obtain zooplankton data. The last decades have seen the intense development of zooplankton imaging systems, to increase the zooplankton data spatio‐temporal resolution as well as enabling the combination of size, taxonomy, and functional traits in aquatic ecology studies. Here, we propose a benchmark between the ZooScan, a commercially available, laboratory‐based scanner, which analyses zooplankton preserved samples, and the ZooCAM, an in‐flow imaging system designed for on‐board live zooplankton imaging. Sixty‐one zooplankton samples collected over the Bay of Biscay in environments ranging from estuarine to offshore blue waters were imaged with both instruments. Zooplankton Normalized Biovolume‐Size Spectra slopes, mean sizes, abundances, and zooplankton community biogeographical patterns were computed for each instrument and compared at the taxonomic group, the sampling stations and the Bay of Biscay scales. Both instruments produced similar zooplankton variables by stations and by taxa and described similar zooplankton community compositions and biogeographical patterns, on the large mesozooplankton size range, i.e., [0.3–3.39] mm ESD. We conclude that the ZooCAM and the ZooScan data can be combined to generate long term or spatially resolved zooplankton time series. Our study shows that benchmarking imaging instruments or techniques (1) offers a robust assessment of interoperability between instruments, mitigating possible instrumental biases, and (2) may be of great interest in the case of instrumental obsolescence or breakdown, to choose the most conservative replacement solution in a long term time series framework.
Total alkalinity is a pivotal water quality parameter dictating the response of natural waters to acid-base system perturbations such as ocean acidification and acid mine drainage. Its value as a biogeochemical and ecological variable is enhanced not just by high measurement quality, but also by measurement accessibility. This research demonstrates an instrument that advances the accessibility of high-precision, high-accuracy total alkalinity measurement using open-source, and low-cost instrumentation. Repeated testing of water samples from Lake Superior demonstrated a measurement precision (standard deviation or SD) of 3.0 mu mol kg(-1). Analysis of standards and reference materials demonstrated an uncertainty of 5.3 mu mol kg(-1) as well as robustness to freshwater and saltwater matrices. This instrument adds to the wealth of inorganic carbon measurement technologies in marine and lacustrine settings and stands to enhance the ability of both communities to generate accurate and accessible measurements of total alkalinity.
Analysis of lignin in seawater is essential to understanding the fate of terrestrial dissolved organic matter (DOM) in the ocean and its role in the carbon cycle. Lignin is typically quantified by gas or liquid chromatography, coupled with mass spectrometry (GC-MS or LC-MS). MS instrumentation can be relatively expensive to purchase and maintain. Here we present an improved approach for quantification of lignin phenols using LC and absorbance detection. The approach applies a modified version of parallel factor analysis (PARAFAC2) to 2(nd) derivative absorbance chromatograms. It is capable of isolating individual elution profiles of analytes despite co-elution and overall improves sensitivity and specificity, compared to manual integration methods. For most lignin phenols, detection limits below 5 nmol L-1 were achieved, which is comparable to MS detection. The reproducibility across all laboratory stages for our reference material showed a relative standard deviation between 1.47% and 16.84% for all 11 lignin phenols. Changing the amount of DOM in the reaction vessel for the oxidation (dissolved organic carbon between 22 and 367 mmol L-1), did not significantly affect the final lignin phenol composition. The new method was applied to seawater samples from the Kattegat and Davis Strait. The total concentration of dissolved lignin phenols measured in the two areas was between 4.3-10.1 and 2.1-3.2 nmol L-1, respectively, which is within the range found by other studies. Comparison with a different oxidation approach and detection method (GC-MS) gave similar results and underline the potential of LC and absorbance detection for analysis of dissolved lignin with our proposed method.
Application of high-frequency monitoring of dissolved organic carbon (DOC) is difficult in instances where training datasets are challenging to develop (e.g., remote locations) and the relationship between optical features and DOC concentration changes due to environmental or landscape shifts (e.g., climate or land-use change). We developed and compared three partial least squares (PLS) models using in situ water level measurements, conductivity, and UV-Vis spectral attenuation to predict DOC. Two site-specific models were developed using data from a hillslope-dominated forest or a low-relief wetland-pond-dominated stream catchment. The third model, using data from both sites, exhibited the best performance (DOC range = 4-15.5 mg C L-1, mean = 8.38 mg C L-1, training RMSE = 0.34 mg C L-1, internal validation RMSE = 0.50 mg C L-1, external validation RMSE = 2.43 mg C L-1). We further demonstrate using PLS model statistics to monitor performance and elucidate when and how models should be updated. These statistics, Hotelling's T-2 and squared prediction errors, are useful consistency checks for the predictions made and detect underlying inconsistencies that, if undetected, can reduce the robustness of DOC prediction. For example, via the T-2 statistic, we identified the summer-autumn transition as a period when DOC composition differed from what was represented in the training dataset. We also determined that elevated SUVA(254) values contributed to the overall bias observed in predictions made during the subsequent year as part of the external validation. This enabled the application of a bias correction that reduced the RMSE from 2.43 to 0.89 mg C L-1. The method presented here could be applied to future monitoring programs enabling model updates to monitor DOC fluxes accurately from optical datasets (e.g., attenuance or fluorescence) in the face of developing datasets in remote locations or environmental change. Implementation of this approach may also identify possible regime shifts or landscape and hydrologic change associated with climate and other environmental changes relevant to terrestrial to aquatic fluxes.
Laminated sediments can record seasonal changes in sedimentation of material from anoxic waters, including minerals of the redox-sensitive elements Fe, Mn, and S that form under varying oxygen levels, mineral saturation conditions, and from microbial metabolism. However, preserving both the oxygen-sensitive minerals for identification is challenging when preservation of the spatial arrangement of laminae is also required. In this study, we compare methods for embedding sedimentary materials from anoxic waters and sediments from Brownie Lake, Minnesota, USA for analysis of the redox speciation for Fe, Mn, and S using synchrotron-based X-ray absorption near edge spectroscopy (XANES). We found that acetone dehydration and resin replacement in a 100% N2 glovebox successfully preserved the speciation of Fe and Mn minerals within laminated sediments. However, acetone removed some sulfur species from sediments, and epoxies contained sulfur species, which challenged identification of native sulfur species. Results from this study will aid researchers who are interested in spatial analysis of oxygen sensitive sediments, soils, or microbial mats in choosing a preservation method.
Microbes in the dark ocean are exposed to hydrostatic pressure increasing with depth. Activity rate measurements and biomass production of dark ocean microbes are, however, almost exclusively performed under atmospheric pressure conditions due to technical constraints of sampling equipment maintaining in situ pressure conditions. To evaluate the microbial activity under in situ hydrostatic pressure, we designed and thoroughly tested an in situ microbial incubator (ISMI). The ISMI allows autonomously collecting and incubating seawater at depth, injection of substrate and fixation of the samples after a preprogramed incubation time. The performance of the ISMI was tested in a high‐pressure tank and in several field campaigns under ambient hydrostatic pressure by measuring prokaryotic bulk 3 H‐leucine incorporation rates. Overall, prokaryotic leucine incorporation rates were lower at in situ pressure conditions than under to depressurized conditions reaching only about 50% of the heterotrophic microbial activity measured under depressurized conditions in bathypelagic waters in the North Atlantic Ocean off the northwestern Iberian Peninsula. Our results show that the ISMI is a valuable tool to reliably determine the metabolic activity of deep‐sea microbes at in situ hydrostatic pressure conditions. Hence, we advocate that deep‐sea biogeochemical and microbial rate measurements should be performed under in situ pressure conditions to obtain a more realistic view on deep‐sea biotic processes.
Because the diffusivity of particles undergoing the Brownian motion is inversely proportional to their sizes, the size distribution of submicron particles can be estimated by tracking their movement. This particle tracking analysis (PTA) has been applied in various fields, but mainly focused on resolving monodispersed particle populations and is rarely used for measuring oceanic particles that are naturally polydispersed. We demonstrated using Monte Carlo simulation that, in principle, PTA can be used to size natural, oceanic particles. We conducted a series of lab experiments using microbeads of NIST-traceable sizes to evaluate the performance of ViewSizer 3000, a PTA-based commercial instrument, and found two major uncertainties: (1) the sample volume varies with the size of particles and (2) the signal-to-noise ratio for particles of sizes < 200-250 nm was reduced and hence their concentration was underestimated with the presence of larger particles. After applying the volume correction, we found the instrument can resolve oceanic submicron particles of sizes greater than 250 nm with a mean absolute error of 3.9% in size and 38% in concentration.
To ensure an optimal continuation of a long time series of zooplankton monitoring surveys, two types of equipment for depth-stratified mesozooplankton sampling were compared. The Institute of Marine Research (Norway) has applied the MOCNESS with good results since 1985, but recent events have made it necessary to change to the Multinet Mammoth. During a cruise in March 2019, both sampling devices were calibrated before 17 paired deployments of the 2 gears were undertaken. During each deployment, three nets and depth-strata covering similar to 425-200, 200-100, and 100-0 m were sampled. All samples were size-fractionated or taxonomically fractionated into 10 different biomass categories. The results revealed no significant differences between the two gears when comparing total depth-integrated biomass (2.46 +/- 0.36 vs. 2.61 +/- 0.59 gDW m(-2)) or depth-integrated biomass of any specific biomass category. Running paired t-tests separately for all combinations of biomass categories and nets, the differences were only significant for zooplankton biomasses in the 180-1000 mu m size fraction and only for Net 2. Possible reasons for this result are discussed in the paper. Gears produced similar catches whether sampling during day or night. We conclude that the MOCNESS and Multinet Mammoth in this study provided comparable results regarding abundances of various zooplankton categories.
Plastics represent the largest component of marine debris globally. In this context, it is essential to quantify the current extent of plastic pollution, including microplastics (MP; plastics < 5 mm), within marine abiotic and biotic compartments. Despite significant effort, MP studies still face methodological impediments to establish accurate and standardized protocols to separate, process and analyze MPs in environmental samples. Furthermore, underestimation and overestimation of MP contamination, either through loss of MPs or introduction of extraneous MPs during handling and processing, is concerning, particularly when assessing risk profiles for marine ecosystems. Presented here is a custom-made stainless steel vacuum filtration apparatus designed to perform size-tiered separation and facilitate retrieval of MPs from a variety of environmental sample matrices. Incorporating this apparatus into a standard MP workflow achieved efficient graduated separation of commonly found MP fragments and fibers, validated by spike-recovery tests. As a case study, the gastrointestinal tracts of three juvenile Australian sharpnose sharks, Rhizoprionodon taylori, were processed using the filtration apparatus, and 46 anthropogenic items ranging from 0.021 to 8.87 mm were retrieved. This study demonstrates the effective use of the size-tiered stainless steel vacuum filtration apparatus and an improved efficiency in downstream microphotography and spectroscopic analyses of MPs from a complex sample matrix. Finally, it contributes to the MP research field by delivering more reliable estimates of MP contamination in marine ecosystems.
An ice buoy system was developed to measure oceanographic properties of freshwater plumes that occur in Arctic coastal oceans under landfast sea ice during the spring freshet. By implanting such systems into sea ice weeks or months in advance of the freshet event, sensors can be located immediately underneath the sea ice layer in situ at depths that riverine freshwater will occupy later when the freshet arrives. This observing approach is modular, can accommodate a wide range of sensors, is designed intentionally for use in remote regions, and can be readily deployed in any nearshore region that can be accessed by snowmachine. The buoy system incorporates an integral floatation collar that allows it to continue sampling as the coastal ocean becomes progressively ice free in the months after the freshet event. Automated sampling and telemetry via a satellite data network provide near-real-time observations of the timing and character of under-ice freshet plumes. An assessment study was done with an array of these ice buoy systems, outfitted with basic hydrographic and optical sensors and deployed in advance of the 2018 and 2019 freshets in landfast sea ice near the mouths of three coastal rivers in Stefansson Sound, Alaska.
Simons Collaborative Marine Atlas Project (Simons CMAP) is an open-source data portal that interconnects large, complex, and diverse public data sets currently dispersed in different formats across different Oceanography discipline-specific databases. Simons CMAP is designed to streamline the retrieval of custom subsets of data, the generation of data visualizations, and the analyses of diverse data, thus expanding the power of these potentially underutilized data sets for cross-disciplinary studies of ocean processes. We describe a unified architecture that allows numerical model outputs, satellite products, and field observations to be readily shared, mined, and integrated regardless of data set size or resolution. A current focus of Simons CMAP is integration of physical, chemical, and biological data sets essential for characterizing the biogeography of key marine microbes across ocean basins and seasonal cycles. Using a practical example, we demonstrate how our unifying data harmonization plans significantly simplifies and allows for systematic data integration across all Simons CMAP data sets.
Autonomous and cabled platforms are revolutionizing our understanding of ocean systems by providing 4D monitoring of the water column, thus going beyond the reach of ship‐based surveys and increasing the depth of remotely sensed observations. However, very few commercially available sensors for such platforms are capable of monitoring large particulate matter (100–2000 μ m) and plankton despite their important roles in the biological carbon pump and as trophic links from phytoplankton to fish. Here, we provide details of a new, commercially available scientific camera‐based particle counter, specifically designed to be deployed on autonomous and cabled platforms: the Underwater Vision Profiler 6 (UVP6). Indeed, the UVP6 camera‐and‐lighting and processing system, while small in size and requiring low power, provides data of quality comparable to that of previous much larger UVPs deployed from ships. We detail the UVP6 camera settings, its performance when acquiring data on aquatic particles and plankton, their quality control, analysis of its recordings, and streaming from in situ acquisition to users. In addition, we explain how the UVP6 has already been integrated into platforms such as BGC‐Argo floats, gliders and long‐term mooring systems (autonomous platforms). Finally, we use results from actual deployments to illustrate how UVP6 data can contribute to addressing longstanding questions in marine science, and also suggest new avenues that can be explored using UVP6‐equipped autonomous platforms.
Limnology and Oceanography: MethodsVolume 19, Issue 3 p. 159-159 CorrigendumFree Access Corrigendum: Listening to air-water gas exchange in running waters This article corrects the following: Listening to air–water gas exchange in running waters Marcus Klaus, Erik Geibrink, Erin R. Hotchkiss, Jan Karlsson, Volume 17Issue 7Limnology and Oceanography: Methods pages: 395-414 First Published online: June 12, 2019 First published: 05 January 2021 https://doi.org/10.1002/lom3.10407 [Correction added 26 February 2021 after first online publication: the corrigendum was rewritten for clarity.] AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat In 1 the following errors were made: In equations 1-4, as well as the captions for Table 4 and Table S3, the term “k600” should read “ln(k600)”. In other words, the logaritmus naturalis (ln) should be applied to k600 in order to yield correct predictions. In Table S1, the correct unit of water depth is m, not cm, as indicated in the original table. We apologize for these errors. Reference 1Klaus, M., E. Geibrink, E. R. Hotchkiss, and J. Karlsson. 2019. Listening to air-water gas exchange in running waters. Limnol. Oceanogr.: Methods 17: 395– 414. doi:10.1002/lom3.10321Wiley Online LibraryWeb of Science®Google Scholar Volume19, Issue3March 2021Pages 159-159 ReferencesRelatedInformation
Since 1997, dense blooms of the alga Phaeocystis globosa have occurred in the South China Sea (SCS), and previous studies have revealed the co-existence in this sea of two types of P. globosa cell characterized by different marker pigment profiles. However, owing to a lack of quantitative methods for the detection of different types of P. globosa cells, the dynamics of P. globosa blooms in the SCS are still poorly understood. In this study, on the basis of phylogenetic analysis of the mitochondrial atp8 (Mit atp8) gene and pigment profiles, the P. globosa strains from Pacific and Atlantic coastal waters were divided into four genotypes, of which Type I and Type IV strains co-exist in the SCS. Furthermore, two genotype-specific quantitative polymerase chain reaction (qPCR) methods were developed targeting the Mit atp8 gene for quantitative determinations of the densities of Type I and Type IV P. globosa cells. Both qPCR methods were reproducible, highly sensitive, and specific with a wide range of detection (from 30 to 1 x 10(8) cells L-1) for target P. globosa genotypes in the field, thereby facilitating the detection of low cell densities prior to bloom development, as well as high cell densities during bloom periods. Finally, the developed qPCR assays were successfully applied to determine the distribution patterns of Type I and Type IV P. globosa in the Beibu Gulf, a region of the SCS characterized by a high frequency of P. globosa blooms.
