Limnology and Oceanography: Methods

Anthropogenic changes such as climate change and pollution have strong effects on plankton and its ecosystem services. In freshwater, phytoplankton forms the basis of the food web and plays a key role in water quality. It is therefore important to monitor the plankton community. In Switzerland, lake plankton has been monitored for decades by cantonal authorities. But in the future, there will be a limitation in the availability of trained taxonomists that are able to count plankton samples under the microscope as well as time and budget constraints. New technologies will be needed to fulfil the federal requirements on the monitoring of lakes in the future. Here we focus on two such instruments, both based on plankton automated imaging: the FlowCam and the Aquascope. The first is a commercially available instrument, the second is custom made. They are the only automated imaging instruments that can track freshwater plankton across the desired size range (phytoplankton and zooplankton). Their design makes them the state of the art technologies to make quantitative observations of plankton. While the FlowCam is a laboratory instrument, the Aquascope is originally designed for field deployment. In this report, we focus the empirical work on the laboratory application of the Aquascope approach of automated imaging and classification for long term plankton monitoring. We find that there are major advantages of the Aquascope approach but the application as a laboratory instrument still needs further development. The major advantages of the Aquascope approach compared to traditional, human-supervised, microscopy methods are the automation and the speed of the data processing, the availability of individual level traits and the management of the data generated. One of the major drawbacks is the lack of taxonomic resolution (mostly at the genus level). Nevertheless, we show that with a larger benchmarking project, it might be possible to continue the long term time series on a coarse taxonomic level as usually reported by cantonal authorities to the general public. We discuss advantages and limitations of Aquascope relative to traditional microscopy and FlowCam, and propose ways forward for future development and application of this approach.

The Pi-10 is the latest iteration of the Plankton Imager: a high-speed colour line-scan camera that images particles in a flow-through system. The Pi-10 is a cost-effective, easy to install and low maintenance automated instrument that can be used on any platform with access to water and power supply. We tested the Pi-10 on the research vessel Cefas Endeavour, connected to a continuous water supply pumping water at 34 L min-1. The instrument collected images of particles, within the size range of 180 {micro}m - 3.5 cm, automatically and continuously, alongside other vessel operations, in all weathers over a period of 18 days. The Pi-10 successfully captured and saved up 5000 images per minute, translating into a 46 GB of digital storage per day. When particle density exceeded 147 per litre, the instrument stopped saving all images, while still recording the number of particles that passed through the system. This is akin to subsampling, with more sub-sampling required in areas or times of high particle density (e.g at the time of spring plankton bloom or in turbid waters). The Pi-10 collects high volumes of data in a continuous manner, thus providing unprecedented fine spatial data. The high frequency nature of the instrument opens the door to new areas of research. These include, in particular, the observation of fine scale processes, the move towards real-time sampling, and the increased capability to build a digital twin of the oceans. As technologies continue evolving the Pi-10 performance will increase, being able to collect and save more and more images.

Chronological data from hard structures have been instrumental in reconstructing information about the past across numerous disciplines. Isotopic and trace elemental chronologies from the depositional layers of speleothems, corals, bivalve shells, fish otoliths and other structures are routinely used to reconstruct climate, growth, temperature, geological, archeological and migratory histories. Recent in situ analytical advances have revolutionized the use of these structures. This is particularly true of fish, in which detailed origin, life-history, and migration history can be reconstructed from their otoliths. Specifically, improvements in laser ablation-inductively coupled plasma mass spectrometry (LA-ICPMS) have allowed increases in temporal resolution, precision, and sample throughput. Many studies now combine multiple chemical and isotopic tracers, taking advantage of multivariate statistical methods and multiple trace-elements and isotope systems to glean further information from individual samples. This paper describes a novel laser ablation split-stream (LASS) methodology which allows simultaneous collection of the Sr isotope composition (87Sr/86Sr) and trace-elemental data from chronologically deposited carbonate samples. The study investigates the accuracy and precision of varying laser spot sizes on a marine shell standard and fish otoliths using LASS and presents a comparison to traditional "single stream methods" using pre-existing otolith data on the same samples. Our results indicate that LASS techniques can be used to provide accurate and precise data at the same laser spot sizes as previous otolith studies, thereby doubling analytical throughput, while also providing improved spatially and temporally-matched data reduction using newly developed features for the Iolite data reduction platform.

This article describes the main findings of a full year of continuous operation of a 2-meter Autonomous Sail and Solar Surface Drone, the Nav2 (Navocean Inc.), as part of a Harmful Algal Bloom (HAB) monitoring program in Lake Okeechobee. The Nav2 was equipped with a set of water quality and atmospheric sensors, that recorded high frequency measurements ({inverted exclamation} 1 min) and transmitted near real-time information to allow reporting through a web portal for assessment and operation responses. Major findings include detection of HABs early in the year through chlorophyll (chl-a) and phycocyanin (phyco) fluorometric measurements, as well as different spatial scales of variability in the algal patches. The 24/7 high resolution monitoring allowed detection of patch motion and discrimination between growth and motion along a transect. Furthermore, the platform can potentially fingerprint specific HAB species based on the relatively fine-scale spatial expression of the phyco to chl-a ratio, which essentially captures the bloom macrostructure (e.g. surface scums versus more uniform sub-surface waves over 0.1 - 1 km scale). Sensor outputs, when converted to concentrations based on calibrated with pure laboratory standards, did not accurately yield true chl-a or phyco values when compared to validation samples, likely due to the high turbidity of the lake. However, routine solid-state validations of fluorometric measurements proved useful for assessing consistency in optical sensors to check for sensor drift (e.g. to due biofouling), which was not significant. Overall this demonstration shows that the Nav2 can uniquely and reliably provide in situ HAB and environmental monitoring capabilities in a large, turbid, shallow lake. We envision that platform as an innovative technology for water resource managers by providing turn-key long-duration baseline environmental data (hands-off waypoint navigation), early warnings of HABs for protecting human health, and for HAB mitigation monitoring.

Understanding the intricate dynamics of ocean biogeochemistry is crucial for deciphering its role in climate change. Our study addresses this challenge by integrating advanced computational techniques and innovative sensor technology to enhance remote sensing capabilities. Drawing on recent insights into the vast carbon reservoirs within the ocean, particularly within the dissolved organic matter (DOM) pool, we highlight the pressing need for comprehensive spatial and temporal understanding facilitated by a combination of satellite and in situ data. However, existing remote sensing methods face limitations in capturing subsurface processes, hindering our ability to grasp carbon fluxes within the oceanic water column fully. Recent advancements in remote sensing offer promising avenues for addressing these challenges. Studies investigating polarized radiance distribution and Chromophoric Dissolved Organic Matter (CDOM) provide valuable insights into improving remote sensing capabilities. Building upon these advancements, we propose a novel data-driven approach utilizing HyperOCR sensors and non-negative matrix factorization (NMF). Non-negative matrix factorization (NMF) is a powerful tool for extracting meaningful biological signatures from hyperspectral data, offering a granular yet comprehensive view of spectral diversity. Our study showcases the potential of NMF in elucidating spatial and temporal variations in biogeochemical processes within the ocean. Leveraging HyperOCR sensors, our approach offers a cost-effective and efficient means of enhancing remote sensing capabilities, enabling the rapid deployment and identification of seasonal patterns in the water column. Through extensive validation against field data from the Adriatic Sea, we demonstrate the utility of our approach in refining satellite measurements and improving algorithms for analyzing ocean color data. Our findings underscore the importance of integrating multiple observational platforms and advanced computational techniques to enhance the accuracy and reliability of remote sensing in ocean biogeochemistry studies. In conclusion, our study contributes to a deeper understanding of marine ecosystems responses to environmental changes and offers a new perspective on remote sensing capabilities, particularly in challenging coastal waters. By bridging the gap between satellite and in situ measurements, our approach exemplifies a promising pathway for advancing remote sensing of ocean biogeochemistry.

1Diatoms are microscopic marine algae that are critical for global primary production, carbon sequestration, and fisheries productivity. However, select diatoms may form harmful algal blooms, which threaten marine ecosystems and the fisheries they sustain. Rapidly identifying harmful blooms is necessary to effectively manage marine resources, yet current identification methods are limited by expensive and labor-intensive in situ point sampling. Hyperspectral remote sensing enables scalable monitoring, but its ability to resolve taxonomic shifts within phytoplankton groups (e.g. diatoms) is largely unknown. To investigate this uncertainty, we cultured four dominant diatom genera from the California Current upwelling system, including this systems most abundant harmful algae, Pseudo-nitzschia. The hyperspectral absorption and backscatter of these taxa were measured and used to model spectral reflectances that remote sensing platforms (satellites/drones) might detect. Differences between fingerprints of these taxa were quantified using vector-based and statistical analyses. Mean spectral differences of 48% were observed between the most dominant diatom, Thalassiosira, and the most toxic diatom, Pseudo-nitzschia. Differences of approximately 30% were found between Pseudo-nitzschia and the second and third most abundant diatoms, Chaetoceros and Asterionellopsis. Successful identification of Pseudo-nitzschias reflectance fingerprint was driven by the presence of a unique feature around 560 nm. The distinct spectral fingerprint of Pseudo-nitzschia indicates that it can be distinguished from benign diatom blooms using hyperspectral remote sensing platforms.

Phytoplankton and detritus particles may be co-captured in Flow-CAM systems, leading to misrepresentation of phytoplankton abundance. In this study, I use logistic regression as a binary classifier to identify detritus particles in FlowCAM data from the Southern North Sea. Standard particle features from the manufacturers software were used as inputs, with surface texture (intensity variance) and compactness (derived from particle perimeter and area) proving most relevant to detritus classification. This classifier achieved 81% accuracy using a training dataset of approximately 7300 observations, reducing the workload compared to other classification methods. The reconstructed particle size spectra closely matched the observed spectra for detritus and phytoplankton. Binary classifiers like this offer a fast, effective alternative for detritus screening, aiding the pre-processing and re-analysis of FlowCAM datasets.

Harmful algal blooms caused by cyanobacteria (cyanoHABs) are detrimental to human and environmental health and can be difficult to monitor without specialized training and equipment. A variety of instruments have been developed to measure cyanoHAB indicators (i.e., chlorophyll a or phycocyanin) that do not require advanced laboratory processes (e.g., pigment extraction). We compared measurements from five in vivo fluorometers (Turner Trilogy in-vivo module, Turner Fluorosense, Turner Cyanofluor, bbe AlgaeTorch, and bbe Phycoprobe) to results from solvent-based extractions for chlorophyll a and phycocyanin at six different waterbodies in Rhode Island. We found a strong relationship between extracted phycocyanin and in vivo fluorometers (R2 ranging from 0.78-0.96). We found less consistency between in vivo measurements of chlorophyll a and the extracted results (R2 between 0.34 and 0.82). Some variability in the chlorophyll a results can be explained by differences in the phytoplankton community across the different sampling sites. Phycocyanin results from in vivo fluorometry were also strongly related with cell counts, which implies that phycocyanin measurements from these instruments can be a good proxy for cell counts. Many federal, state, and local entities use cell counts of cyanobacteria to determine when to issue health or contact advisories for waterbodies. Producing accurate cell counts requires highly specialized training/equipment, processing time, and counts can vary greatly between technicians. The results from this study encourage further adoption of in vivo fluorometry and phycocyanin for cyanoHAB monitoring efforts.

The focus of this study was to assess the potential of otolith microchemistry as a fishery management tool for different European freshwater fish species in an Alpine foreland with a diverse range of different water bodies but low geological variation. 87Sr/86Sr isotope and Sr/Ca ratios in water samples from 26 habitat sites in a pre-alpine catchment region around lake Chiemsee, Germany, an important region for recreational and economic fisheries, were analysed. 87Sr/86Sr isotope ratios and the Sr mass fractions in otoliths of 246 fish out of 16 species were determined using (laser ablation) inductively coupled plasma mass spectrometry ((LA)-ICP-MS). Habitats could be discriminated into three distinct strontium isotope regions (SIGs) and seven clusters with characteristic 87Sr/86Sr isotope and Sr/Ca ratios. The direct comparison of 87Sr/86Sr isotope ratios in water and otolith samples allowed to identify fish that might have been a) migrating b) transferred from other water bodies or c) stocked from fish farms. Sr/Ca ratios in water and the Sr mass fraction in otoliths were highly correlated, although significant differences between species from the same environment could be documented. Sr mass fractions in sagittae of Perca fluviatilis were about 60 % of those in sagittae of Coregonus spp and of lapilli of roach Rutilus rutilus from the same habitats. Different partition factors for water to otolith Sr/Ca mass fractions were determined for different species. Discrimination of fish otoliths by 87Sr/86Sr isotope ratios and Sr mass fractions according to habitat clusters was possible with success rates ranging from 92 % to 100 % for cyprinids, European perch Perca fluviatilis, whitefish Coregonus spp. and European grayling Thymallus thymallus, and was 74 % for salmonids. Otolith microchemistry proved to have great potential to serve as a fishery management tool at smaller spatial scales such as in the studied Alpine foreland when considering the limited variation of 87Sr/86Sr isotope and Sr/Ca ratios, the type and spatial distribution of habitats, and the species and question under investigation. HighlightsO_LIOtolith microchemistry applied in in area with limited geological variability C_LIO_LIFish transferred, stocked or migrated were identified C_LIO_LIRegressions between Sr/Ca ratios in water predict Sr mass fractions in otoliths C_LIO_LISpecies specific Sr discrimination from water into otoliths C_LIO_LIEuropean freshwater fish species assigned to habitat clusters of origin C_LI

The second field campaign of the NASA EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) program was conducted in the late spring of 2021 within the vicinity of the Porcupine Abyssal Plain (49.0{degrees}N, 16.5{degrees}W) in the North Atlantic Ocean. Observations from EXPORTS support previous characterizations of this system as highly productive and organic matter rich, with the majority of primary production occurring in large cells ([&ge;] 5 {micro}m) such as diatoms that are primarily utilizing nitrate. Rates of total euphotic zone depth-integrated net primary production ranged from 36.4 to 146.6 mmol C m- 2 d-1, with an observational period average f-ratio of 0.74, indicating predominantly new production. Substantial variability in the contribution of small (<5 {micro}m) and large cells occurred over the observation period, coinciding with the end of the annual spring phytoplankton bloom. Physical changes associated with storms appear to have impacted the integrated production rates substantially, enhancing rates by [~]10%. These disturbances altered the balance between contributions of the different phytoplankton size fractions, thus highlighting the important role of mixed layer variability in nutrient entrainment into the upper water column and production dynamics. In diatoms, inputs of silicic acid related to deepening of the mixed layer increased silicic acid uptake rates yet concomitant increases in NPP in large cells was not observed. This campaign serves as the high productivity endmember within the EXPORTS program and as such, elucidates how nutrient concentrations and size class play key roles in both low and high productivity systems, but in differing ways.

Plankton size spectra are important indicators of the ecosystem state, as they illustrate the quantity of organisms available for higher marine food web and reflect multiple size-dependent processes. Yet, such measurements are typically biased by the available sampling methods, either disrupting fragile organisms or lacking good resolution (in size and/or time and space). In this study, we combined two of the most common approaches to measure zooplankton Normalized Biomass/Biovolume Size Spectra (NBSS) to calculate a complete zooplankton distribution for organisms larger than 1 mm. The reconstructed NBSS slopes appeared steeper and closer to those measured by the UVP5 (+7.6%) and flatter than those of the Multinet (- 20%) particularly in tropics and temperate latitudes. The overall gain in polar biomass was relatively small for reconstructed biomass compared to bulk estimates from Multinet (+0.24 mgC/m3 or +4.25%) and high from the UVP5 (+2.0 mgC/m3 or +53%). In contrast, in the tropical and temperate ecosystems, the gain in biomass was small for UVP5 (+0.67 mgC/m3 or +30.44% and +0.74 mgC/m3 or +19.59% respectively) and high for Multinet (+1.66 mgC/m3 or +136% and +3.4 mgC/m3 or +309% respectively). Given these differences, we suggest here to combine in situ imaging sensors and net data in any comprehensive study exploring key living players in the ocean ecosystem and their contributions to the biological pump.

Offshore industry still largely relies on traditional approaches for regulatory compliance to environmental impact on the water column. Implementing environmental DNA (eDNA) workflow can offer several advantages, but early stages such as sampling and conservation of the samples require standardization and simplification before they can be routinely applied in offshore monitoring programs. In this study, we assessed the effect of several filter types (Durapore disc, Sterivex capsule and Wattera high-capacity capsule; all with 0.22 {micro}m pore size) allowing for different volume of filtration used for sampling eDNA. We also evaluated the effect of 25 days conservation of unfiltered water samples with different preservative solutions (Benzalkonium chloride -BAC, Longmires solution LONGI and a modified Longmires solution without SDS, LNoSDS) as a viable option when immediate filtration and cold storage are not possible. For downstream eDNA evaluation of filter types and preservation, we used quantitative digital PCR on selected target DNA and metabarcoding for qualitative assessment of marine prokaryotic and eukaryotic communities. Overall, filter choice had relatively less effects on quantitative and qualitative information from eDNA compared with water preservation. Sterivex and Durapore were better filter choices for biodiversity assessment. While the Wattera filter allowed processing of larger water volumes and improved quantification of metazoan DNA, handling and processing were more challenging. For water conservation, LNoSDS was the best option. Chemical agents of LONGI and BAC may provide favourable substrates for some tolerant bacterial strains, altering the microbial community composition, with consequences for the overall qualitative evaluation of conserved eDNA. For targeted metazoan eDNA, however, chemical preservation showed clear benefits. This research highlights key considerations and viable options for eDNA sampling and simple preservation workflows without cold storage for implementation in offshore water column monitoring. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/733101v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@22a175org.highwire.dtl.DTLVardef@1960864org.highwire.dtl.DTLVardef@1010f49org.highwire.dtl.DTLVardef@92a2f6_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LINeed for standardization of eDNA workflow for offshore water column monitoring C_LIO_LIImportance of eDNA sampling (filters) and eDNA conservation (preservatives) C_LIO_LIFilter choice does not affect drastically the dominant eDNA communities C_LIO_LIConservation outside cold storage challenging for eDNA-based biodiversity evaluation C_LIO_LIViable options: Sterivex filter for sampling; Longmires (no SDS) for conservation C_LI

AbstractPhytoplankton community composition in estuaries is tightly linked to freshwater input. While regular freshwater input typically delivers nutrients, fueling phytoplankton growth, the impact of extreme events is less certain. Several observational studies have documented increases in phytoplankton biomass following large precipitation events but cannot to adequately identify the mechanism driving this increase. This paper advances two hypotheses about what drives phytoplankton biomass change following extreme precipitation events. First, the Resident Response Hypothesis (RRH), which suggests local estuarine phytoplankton grow in response to favorable conditions. Alternatively, the Production Introduction Hypothesis (PIH) indicates that large rainfall events introduce new phytoplankton taxa to estuaries during run-off events associated with large storms. These hypotheses were tested at North Inlet Estuary (South Carolina, USA) through a novel experimental design, which utilized multiple treatments to mimic the distinct impacts of large rainfall events on natural phytoplankton communities. Experimental samples were analyzed using photopigments and flow-through imaging microscopy. This allowed a wide assessment of phytoplankton community change both through measuring chlorophyll-a and biomass concentration. Ultimately, there was a strong increase in phytoplankton growth in the storm treatments, primarily identified by diatom pigment increases in response to run-off delivered nutrients, providing support for the RRH. However, biomass concentration analysis of select diatom taxa revealed the introduction of new diatom taxa in run-off water communities. This supports the PIH, suggesting that initial growth from nutrient additions may be due to small cell growth as well as introduction of new taxa.

Marine particle forensics frequently uncover information on composition, age, size, and ecological history. Zooplankton fecal pellets are also studied for process-related data, such as grazing rates and carbon sequestration potential. Here, flow cytometric analyses of fecal pellet contents revealed intact phytoplankton with photophysiological characteristics mirroring those of free-living cells. Mapping the cytometrically derived properties of cells inside fecal pellets onto vertical profiles from free-living cells revealed the potential to estimate depth specific grazing by individual zooplankton. An experiment conducted at sea confirmed that the photophysiological characteristics of free-living phytoplankton from multiple depths, consumed by zooplankton, and excreted within fecal pellets are retained for at least 24 hours after grazing is initiated. These results have implications for high resolution modeling of individual or group specific zooplankton grazing dynamics that are critical for accurately linking zooplankton grazing in the surface ocean with the mesopelagic and deep ocean food webs and carbon export. Scientific Significance StatementFecal pellet forensics have provided significant contributions to the study of zooplankton grazing and the marine carbon cycle. Gaps in knowledge about these processes remain, and continued investigations into fecal pellet contents and their fate are important for assessing connections between the surface and deeper ocean ecosystems. We describe a study conducted in the North Atlantic in the Spring of 2021 using flow cytometry to investigate fecal pellets contents. Observations that intact phytoplankton within the pellets had similar photophysiological properties to the free-living community led to a series of sample collections and experiments which provided a path forward for determining depth specific grazing by zooplankton community members. Phytoplankton survival after passing through zooplankton guts and being packaged into fecal pellets, with their potential for release far below the surface mixed layer, support prior observations of healthy phytoplankton communities at depth and validate this mechanism for the rapid transport of freshly fixed carbon to deep ocean systems. The results should be of interest to plankton ecologists and carbon cycle scientists connecting surface and deep ocean ecosystems as application of this approach at a broader scale will provide opportunities for high resolution modeling of individual and group specific zooplankton behaviors.

Lakes in the Alpine region are recognised as critical CH4 emitters, but a robust characterisation of the magnitude and variability of CH4 fluxes is still needed. We developed a mobile platform for CH4 eddy covariance (EC) flux measurements to tackle this gap. Our approach was shown to be well suited to catch all CH4 emission pathways and overcome the limitations of other methods (e.g., gradient-based). This is by surpassing their local nature and thus being suited for characterising the variability of the within-lake emissions, primarily because of CH4 emissions by ebullition stochasticity. The mobile system was deployed at nine lakes across a latitudinal transect in the Alps and validated by comparing the measured fluxes with a fixed EC station and to chambers and boundary layer estimates. Methane fluxes were explained by water turbidity, dissolved organic carbon, dissolved nitrogen, elevation, particulate organic carbon, and total phosphorus. The highest fluxes and most substantial seasonal variability were found in a shallow low-altitude lake in the Southern Alps. Additionally, the mobile EC permitted to resolve the spatial structure of fluxes at the selected lakes. Finally, we demonstrated the usability of our novel mobile system to characterise intra- and inter-lake variability of fluxes. We suggest that characterising the intra-lake emission heterogeneity and a deeper understanding of inter-lake emission magnitude differences is fundamental for a solid estimate of freshwater CH4 budgets. Key PointsO_LICH4 emissions from alpine lakes are recognised to be an important component to the global methane budget but they are poorly characterized C_LIO_LIWe developed and validated a mobile eddy covariance platform for capturing CH4 fluxes across lakes in the alpine region for two years C_LIO_LIA robust statistical model based on a few in-situ physicochemical and biological parameters can be generally used to predict CH4 fluxes C_LI

Climate change includes increasing surface temperatures as well as extreme events--heatwaves, storms, floods, and droughts. In 2020, these factors produced a record 10,000 wildfires that burned 18,000 km2 in California USA. Air pollution, including airborne ash, from these fires was a widespread human health hazard. While the ecological effects of wildfires have been extensively documented in terrestrial and freshwater systems, impacts on ocean and coastal ecosystems are largely unexplored. Here, we describe the physical and chemical properties of ash from the CZU Lightning Complex fire and experimentally test its effects on the photosynthesis and growth of four unicellular marine phytoplankton. Sieved air-fall ash was primarily composed of particles 250-500 m and contained [~]1 {per thousand} of Fe, Mn, and Ba. Diagnostic indices of polycyclic aromatic hydrocarbons indicated the air-fall ash originated from combusted wood, and the total concentration of the EPA 16 high-priority PAHs exceeded 2.7 ppm. Pulse Amplitude Modulation fluorometry documented various declines in the photosynthetic efficiency of Isochrysis and Dunaliella cultures dosed with ash, and the bulk cellular growth of these cultures was inhibited. While our study demonstrated the impacts of wildfire ash on marine producers, the precise mechanisms are unclear. We provide recommendations for how future studies may further resolve the impacts of ash on phytoplankton productivity, community diversity, and trophic transfer of toxins and describe the long-term impacts of wildfires on coastal marine ecosystems.

In phytoplankton, the intricate balance between respiration and photosynthesis is co-regulated to ensure efficient energy management and adaptation to varying environmental conditions. In cyanobacteria, both processes occur on the same membrane, sharing electron transport carriers within the same cellular compartment. By studying the interaction between photosynthesis and respiration, we can better understand how cyanobacteria balance their energetic budget for survival. In this study, we present an integrated approach that combines tracking gas exchange between cyanobacteria and their environment with analysing the redox kinetics of the underlying photosynthetic electron transport chain. This combined system allows for real-time, simultaneous acquisition of respiration and photosynthesis data. For example, it enabled us to show that the electron transport rate generated by photosystem II, translated to in-vivo oxygen concentration, equals the actual concentration of oxygen produced by water splitting plus the amount of oxygen respired. We further demonstrate that our system can accurately assess light respiration in wild-type strains of cyanobacteria, which amounts to 1/10 of their photosynthetic activity under optimal growth conditions. This level of accuracy was previously achievable only with specific cyanobacteria mutants. We envision applying this system in monitoring programs to elaborate on the role of photosynthetic light reactions within the broader context of primary productivity and to understand its dynamics in response to fluctuations in external environmental conditions.

Multifrequency echosounders are versatile devices commonly used in commercial fisheries, fisheries science and biological oceanography for the detection, quantification and even identification of organisms suspended in the underlying water column. They produce data that is rich in information, but can be tedious to process, often relying on expensive commercial software. The aim of our overarching research project was to analyze the vertical distribution of Antarctic krill swarms (Euphausia superba) in different seasons and regions in order to learn more about their behavioral ecology and ecophysiological adaptation. Therefore, we only required visual information on the distribution of krill swarms as well as metrics that characterize their vertical position. Instead of using storageintensive raw acoustic data, we developed a simple method to extract the relevant information from screenshots taken automatically on board a commercial krill fishing vessel during its operations. Using screenshots instead of raw data reduced the amount of data by a factor of >1000 (3 TB of raw data vs. 2.8 GB of screenshots for 8 months of observations) while preserving the information needed to carry out our seasonal behavioral analyses. In this study, we present the workflow and demonstrate that our method produces qualitatively and quantitatively similar results to using raw data, while being much less demanding in terms of computation and data storage. The code for the data processing is written in the open source programming language R, publicly accessible and therefore, provides a useful resource for other scientists interested in the dynamics of vertical biomass distributions from echosounder data.

Mesoscale eddies significantly alter open ocean environments such as those found in the subtropical gyres that cover a large fraction of the global ocean. Previous studies have explored eddy effects on biogeochemistry and microbial community composition but not on the molecular composition of particulate organic matter. This study reports the absolute concentration of 67 metabolites and relative abundances for 640 molecular features to understand how mesoscale eddies impact the metabolome of the North Pacific Subtropical Gyre during two cruises in 2017 and 2018. We find that many metabolites track biomass trends, but metabolites like isethionic acid, homarine, and trigonelline linked to eukaryotic phytoplankton were enriched at the deep chlorophyll maximum of the cyclonic features, while degradation products such as arsenobetaine were enriched in anticyclones. In every analysis, metabolites with the strongest responses were detected via untargeted mass spectrometry, indicating that the molecules most sensitive to environmental perturbation were not among the characterized metabolome. By analyzing depth variability (accounting for 20-40% of metabolomic variability across [~]150 meters) and the vertical displacement of isopycnal surfaces (explaining 10-20% of variability across a sea level anomaly range of 40 centimeters and a spatial distance of 300 kilometers), this analysis constrains the importance of mesoscale eddies in shaping the chemical composition of particulate matter in the largest biomes on the planet. ImportanceMesoscale eddies are common ocean surface currents that circulate seawater vertically and horizontally. This stirring effect alters biogeochemistry and planktonic community composition. Here, we use metabolomics to determine how these eddy-induced changes influence the nature of organic carbon across an eddy dipole. We found that many small, polar molecules track with the overall particulate carbon in the system and that there were significant differences in metabolite composition between eddy states. A few metabolites reflected the increased importance of eukaryotic phytoplankton that were enriched by the higher nutrient supply from depth in the cyclonic eddies. Anticyclones contained more compounds that reflected a higher degree of degradation. This work answers outstanding questions about the importance of these common ocean features in shaping microbial community function.

Cyanobacterial blooms are causing increasing issues across the globe. Bloom forecasting can facilitate adaptation to blooms. Most bloom forecasting models depend on weekly or fortnightly sampling, but these sparse measurements can miss important dynamics. Here we develop forecasting models from five years of high frequency summer monitoring in a shallow lake (which serves as an important regional water supply). A suite of models were calibrated to predict cyanobacterial fluorescence (a biomass proxy) using measurements of: cyanobacterial fluorescence, water temperature, light, and wind speed. High temporal autocorrelation contributed to relatively strong predictive power over 1, 4 and 7 day intervals. Higher order derivatives of water temperature helped improve forecasting accuracy. While traditional monitoring and modelling have supported forecasting on longer timescales, we show high frequency monitoring combined with telemetry allows forecasting over timescales of 1 day to 1 week, supporting early warning, enhanced monitoring, and adaptation of water treatment processes.