Global Trends in Marine Plankton Diversity across Kingdoms of Life.

The ocean is home to myriad small planktonic organisms that underpin the functioning of marine ecosystems. However, their spatial patterns of diversity and the underlying drivers remain poorly known, precluding projections of their responses to global changes. Here we investigate the latitudinal gradients and global predictors of plankton diversity across archaea, bacteria, eukaryotes, and major virus clades using both molecular and imaging data from Tara Oceans. We show a decline of diversity for most planktonic groups toward the poles, mainly driven by decreasing ocean temperatures. Projections into the future suggest that severe warming of the surface ocean by the end of the 21st century could lead to tropicalization of the diversity of most planktonic groups in temperate and polar regions. These changes may have multiple consequences for marine ecosystem functioning and services and are expected to be particularly significant in key areas for carbon sequestration, fisheries, and marine conservation. VIDEO ABSTRACT.

Global climate-change trends detected in indicators of ocean ecology.

Strong natural variability has been thought to mask possible climate-change-driven trends in phytoplankton populations from Earth-observing satellites. More than 30 years of continuous data were thought to be needed to detect a trend driven by climate change1. Here we show that climate-change trends emerge more rapidly in ocean colour (remote-sensing reflectance, Rrs), because Rrs is multivariate and some wavebands have low interannual variability. We analyse a 20-year Rrs time series from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite, and find significant trends in Rrs for 56% of the global surface ocean, mainly equatorward of 40°. The climate-change signal in Rrs emerges after 20 years in similar regions covering a similar fraction of the ocean in a state-of-the-art ecosystem model2, which suggests that our observed trends indicate shifts in ocean colour-and, by extension, in surface-ocean ecosystems-that are driven by climate change. On the whole, low-latitude oceans have become greener in the past 20 years.

Global satellite-observed daily vertical migrations of ocean animals.

Every night across the world's oceans, numerous marine animals arrive at the surface of the ocean to feed on plankton after an upward migration of hundreds of metres. Just before sunrise, this migration is reversed and the animals return to their daytime residence in the dark mesopelagic zone (at a depth of 200-1,000 m). This daily excursion, referred to as diel vertical migration (DVM), is thought of primarily as an adaptation to avoid visual predators in the sunlit surface layer1,2 and was first recorded using ship-net hauls nearly 200 years ago3. Nowadays, DVMs are routinely recorded by ship-mounted acoustic systems (for example, acoustic Doppler current profilers). These data show that night-time arrival and departure times are highly conserved across ocean regions4 and that daytime descent depths increase with water clarity4,5, indicating that animals have faster swimming speeds in clearer waters4. However, after decades of acoustic measurements, vast ocean areas remain unsampled and places for which data are available typically provide information for only a few months, resulting in an incomplete understanding of DVMs. Addressing this issue is important, because DVMs have a crucial role in global ocean biogeochemistry. Night-time feeding at the surface and daytime metabolism of this food at depth provide an efficient pathway for carbon and nutrient export6-8. Here we use observations from a satellite-mounted light-detection-and-ranging (lidar) instrument to describe global distributions of an optical signal from DVM animals that arrive in the surface ocean at night. Our findings reveal that these animals generally constitute a greater fraction of total plankton abundance in the clear subtropical gyres, consistent with the idea that the avoidance of visual predators is an important life strategy in these regions. Total DVM biomass, on the other hand, is higher in more productive regions in which the availability of food is increased. Furthermore, the 10-year satellite record reveals significant temporal trends in DVM biomass and correlated variations in DVM biomass and surface productivity. These results provide a detailed view of DVM activities globally and a path for refining the quantification of their biogeochemical importance.

Algorithms to retrieve the spectral diffuse attenuation coefficient of light in the ocean from remote sensing.

We recently found a significant bias between spectral diffuse attenuation coefficient (Kd(λ)) retrievals by common ocean color algorithms and measurements from profiling floats [Remote. Sens.14, 4500 (2022)10.3390/rs14184500]. Here we show, using a multi-satellite match-up dataset, that the bias is markedly reduced by simple "tuning" of the algorithm's empirical coefficients. However, while the float dataset encompasses a larger proportion of the ocean's variability than previously used datasets, it does not cover the whole range of variability of observed remote sensing reflectance (Rrs). Thus, using algorithms tuned to this more comprehensive dataset may still result in a temporal and/or geographical bias in global application. To address this generalization issue, we evaluated a variety of analytical algorithms based on radiative transfer theory and settled on a specific one. This algorithm computes Kd(λ) from inherent optical properties (IOPs) obtained from an Rrs inversion and information about the angular distribution of the radiance transmitted through the air/ocean interface. The resulting Kd(λ) estimates at 412 and 490 nm were not appreciably biased against the float measurements. Evaluation using other in-situ datasets and radiative transfer simulations was also satisfactory. Statistical performance was good in both clear and turbid waters. Further work should be conducted to examine whether the tuned algorithms and/or the new analytical algorithm demonstrate adequate hyperspectral performance.

Correction: O'Brien et al. Correction of Radiometry Data for Temperature Effect on Dark Current, with Application to Radiometers on Profiling Floats. Sensors 2022, 22, 6771.

The authors wish to correct the following errors in the original paper [...].

The Tara Pacific expedition-A pan-ecosystemic approach of the "-omics" complexity of coral reef holobionts across the Pacific Ocean.

Coral reefs are the most diverse habitats in the marine realm. Their productivity, structural complexity, and biodiversity critically depend on ecosystem services provided by corals that are threatened because of climate change effects-in particular, ocean warming and acidification. The coral holobiont is composed of the coral animal host, endosymbiotic dinoflagellates, associated viruses, bacteria, and other microeukaryotes. In particular, the mandatory photosymbiosis with microalgae of the family Symbiodiniaceae and its consequences on the evolution, physiology, and stress resilience of the coral holobiont have yet to be fully elucidated. The functioning of the holobiont as a whole is largely unknown, although bacteria and viruses are presumed to play roles in metabolic interactions, immunity, and stress tolerance. In the context of climate change and anthropogenic threats on coral reef ecosystems, the Tara Pacific project aims to provide a baseline of the "-omics" complexity of the coral holobiont and its ecosystem across the Pacific Ocean and for various oceanographically distinct defined areas. Inspired by the previous Tara Oceans expeditions, the Tara Pacific expedition (2016-2018) has applied a pan-ecosystemic approach on coral reefs throughout the Pacific Ocean, drawing an east-west transect from Panama to Papua New Guinea and a south-north transect from Australia to Japan, sampling corals throughout 32 island systems with local replicates. Tara Pacific has developed and applied state-of-the-art technologies in very-high-throughput genetic sequencing and molecular analysis to reveal the entire microbial and chemical diversity as well as functional traits associated with coral holobionts, together with various measures on environmental forcing. This ambitious project aims at revealing a massive amount of novel biodiversity, shedding light on the complex links between genomes, transcriptomes, metabolomes, organisms, and ecosystem functions in coral reefs and providing a reference of the biological state of modern coral reefs in the Anthropocene.

Plankton networks driving carbon export in the oligotrophic ocean.

The biological carbon pump is the process by which CO2 is transformed to organic carbon via photosynthesis, exported through sinking particles, and finally sequestered in the deep ocean. While the intensity of the pump correlates with plankton community composition, the underlying ecosystem structure driving the process remains largely uncharacterized. Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve our understanding of carbon export in the oligotrophic ocean. We show that specific plankton communities, from the surface and deep chlorophyll maximum, correlate with carbon export at 150 m and highlight unexpected taxa such as Radiolaria and alveolate parasites, as well as Synechococcus and their phages, as lineages most strongly associated with carbon export in the subtropical, nutrient-depleted, oligotrophic ocean. Additionally, we show that the relative abundance of a few bacterial and viral genes can predict a significant fraction of the variability in carbon export in these regions.

Factors driving the seasonal and hourly variability of sea-spray aerosol number in the North Atlantic.

Four North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) field campaigns from winter 2015 through spring 2018 sampled an extensive set of oceanographic and atmospheric parameters during the annual phytoplankton bloom cycle. This unique dataset provides four seasons of open-ocean observations of wind speed, sea surface temperature (SST), seawater particle attenuation at 660 nm (cp,660, a measure of ocean particulate organic carbon), bacterial production rates, and sea-spray aerosol size distributions and number concentrations (NSSA). The NAAMES measurements show moderate to strong correlations (0.56 < R < 0.70) between NSSA and local wind speeds in the marine boundary layer on hourly timescales, but this relationship weakens in the campaign averages that represent each season, in part because of the reduction in range of wind speed by multiday averaging. NSSA correlates weakly with seawater cp,660 (R = 0.36, P << 0.01), but the correlation with cp,660, is improved (R = 0.51, P < 0.05) for periods of low wind speeds. In addition, NAAMES measurements provide observational dependence of SSA mode diameter (dm) on SST, with dm increasing to larger sizes at higher SST (R = 0.60, P << 0.01) on hourly timescales. These results imply that climate models using bimodal SSA parameterizations to wind speed rather than a single SSA mode that varies with SST may overestimate SSA number concentrations (hence cloud condensation nuclei) by a factor of 4 to 7 and may underestimate SSA scattering (hence direct radiative effects) by a factor of 2 to 5, in addition to overpredicting variability in SSA scattering from wind speed by a factor of 5.

Correction of Radiometry Data for Temperature Effect on Dark Current, with Application to Radiometers on Profiling Floats.

Measurements of daytime radiometry in the ocean are necessary to constrain processes such as photosynthesis, photo-chemistry and radiative heating. Profiles of downwelling irradiance provide a means to compute the concentration of a variety of in-water constituents. However, radiometers record a non-negligible signal when no light is available, and this signal is temperature dependent (called the dark current). Here, we devise and evaluate two consistent methods for correction of BGC-Argo radiometry measurements for dark current: one based on measurements during the day, the other based on night measurements. A daytime data correction is needed because some floats never measure at night. The corrections are based on modeling the temperature of the radiometer and show an average bias in the measured value of nearly 0.01 W m-2 nm-1, 3 orders of magnitude larger than the reported uncertainty of 2.5×10-5 W m-2 nm-1 for the sensors deployed on BGC-Argo floats (SeaBird scientific OCR504 radiometers). The methods are designed to be simple and robust, requiring pressure, temperature and irradiance data. The correction based on nighttime profiles is recommended as the primary method as it captures dark measurements with the largest dynamic range of temperature. Surprisingly, more than 28% of daytime profiles (130,674 in total) were found to record significant downwelling irradiance at 240-250 dbar. The correction is shown to be small relative to near-surface radiance and thus most useful for studies investigating light fields in the twilight zone and the impacts of radiance on deep organisms. Based on these findings, we recommend that BGC-Argo floats profile occasionally at night and to depths greater than 250 dbar. We provide codes to perform the dark corrections.

Relationships between optical backscattering, particulate organic carbon, and phytoplankton carbon in the oligotrophic South China Sea basin.

The particulate backscattering coefficient (bbp) provides effective proxies for particulate organic carbon (POC) and phytoplankton carbon (Cphy); however, their bio-optical relationships in the oligotrophic ocean are rarely reported. In this work, based on the in-situ synchronous optical and biogeochemical measurements in the oligotrophic South China Sea (SCS) basin, we refined the regional relationships between POC (and Cphy) and bbp and investigated the impacts of phytoplankton community compositions and size classes on the bbp variability. The observations showed that: 1) POC and Cphy exhibited good linear relationships with bbp; 2) the relationship between Cphy and POC could also be fitted in a linear function with a positive POC intercept, and the POC contributed by phytoplankton-covarying non-algal particles was nearly two-fold of Cphy; and 3) the POC-specific bbp (b*bp) was positively correlated with the fraction of the phytoplankton groups haptophytes (Type 8) and diatoms to total Chla, but negatively correlated with the fraction of pico-phytoplankton to Chla (fpico). These findings suggest that in oligotrophic waters, the variability of b*bp was mainly determined by the variability in the relative contribution of large phytoplankton with complex structures.

Deriving the angular response function for backscattering sensors.

We derived the angular response function (WN) for scattering sensors that automatically satisfies the normalization criterion and its corresponding weight (WT). WN's, derived for two commercial sensors, HydroScat-6 (HOBI Labs) and ECO-BB (Sea-Bird Inc.), agrees well with the Monte Carlo simulation and direct measurements. The backscattering measured for microbeads of known sizes agrees better with Mie calculation when the derived WN was applied. We deduced that the reduction of WT with increasing attenuation coefficient is related to path length attenuation and showed that this theoretically derived correction factor performs better than the default methods for the two commercial backscattering sensors. The analysis conducted in this study also leads to an estimate of uncertainty budget for the two sensors. The major uncertainty for ECO-BB is associated with its angular response function because of its wide field of view, whereas the main uncertainty for the HydrScat-6 is due to attenuation correction because of its relatively long path length.

Light color acclimation is a key process in the global ocean distribution of Synechococcus cyanobacteria.

Marine Synechococcus cyanobacteria are major contributors to global oceanic primary production and exhibit a unique diversity of photosynthetic pigments, allowing them to exploit a wide range of light niches. However, the relationship between pigment content and niche partitioning has remained largely undetermined due to the lack of a single-genetic marker resolving all pigment types (PTs). Here, we developed and employed a robust method based on three distinct marker genes (cpcBA, mpeBA, and mpeW) to estimate the relative abundance of all known Synechococcus PTs from metagenomes. Analysis of the Tara Oceans dataset allowed us to reveal the global distribution of Synechococcus PTs and to define their environmental niches. Green-light specialists (PT 3a) dominated in warm, green equatorial waters, whereas blue-light specialists (PT 3c) were particularly abundant in oligotrophic areas. Type IV chromatic acclimaters (CA4-A/B), which are able to dynamically modify their light absorption properties to maximally absorb green or blue light, were unexpectedly the most abundant PT in our dataset and predominated at depth and high latitudes. We also identified populations in which CA4 might be nonfunctional due to the lack of specific CA4 genes, notably in warm high-nutrient low-chlorophyll areas. Major ecotypes within clades I-IV and CRD1 were preferentially associated with a particular PT, while others exhibited a wide range of PTs. Altogether, this study provides important insights into the ecology of Synechococcus and highlights the complex interactions between vertical phylogeny, pigmentation, and environmental parameters that shape Synechococcus community structure and evolution.

Correction of Biogeochemical-Argo Radiometry for Sensor Temperature-Dependence and Drift: Protocols for a Delayed-Mode Quality Control.

Measuring the underwater light field is a key mission of the international Biogeochemical-Argo program. Since 2012, 0-250 dbar profiles of downwelling irradiance at 380, 412 and 490 nm besides photosynthetically available radiation (PAR) have been acquired across the globe every 1 to 10 days. The resulting unprecedented amount of radiometric data has been previously quality-controlled for real-time distribution and ocean optics applications, yet some issues affecting the accuracy of measurements at depth have been identified such as changes in sensor dark responsiveness to ambient temperature, with time and according to the material used to build the instrument components. Here, we propose a quality-control procedure to solve these sensor issues to make Argo radiometry data available for delayed-mode distribution, with associated error estimation. The presented protocol requires the acquisition of ancillary radiometric measurements at the 1000 dbar parking depth and night-time profiles. A test on >10,000 profiles from across the world revealed a quality-control success rate >90% for each band. The procedure shows similar performance in re-qualifying low radiometry values across diverse oceanic regions. We finally recommend, for future deployments, acquiring daily 1000 dbar measurements and one night profile per year, preferably during moonless nights and when the temperature range between the surface and 1000 dbar is the largest.

Detecting Mesopelagic Organisms Using Biogeochemical-Argo Floats.

During the North Atlantic Aerosols and Marine Ecosystems Study in the western North Atlantic, float-based profiles of fluorescent dissolved organic matter and backscattering exhibited distinct spike layers at ∼  300 m. The locations of the spikes were at depths similar or shallower to where a ship-based scientific echo sounder identified layers of acoustic backscatter, an Underwater Vision Profiler detected elevated concentration of zooplankton, and mesopelagic fish were sampled by a mesopelagic net tow. The collocation of spike layers in bio-optical properties with mesopelagic organisms suggests that some can be detected with float-based bio-optical sensors. This opens the door to the investigation of such aggregations/layers in observations collected by the global biogeochemical-Argo array allowing the detection of mesopelagic organisms in remote locations of the open ocean under-sampled by traditional methods.

Evaluation of diagnostic pigments to estimate phytoplankton size classes.

Phytoplankton accessory pigments are commonly used to estimate phytoplankton size classes, particularly during development and validation of biogeochemical models and satellite ocean color-based algorithms. The diagnostic pigment analysis (DPA) is based on bulk measurements of pigment concentrations and relies on assumptions regarding the presence of specific pigments in different phytoplankton taxonomic groups. Three size classes are defined by the DPA: picoplankton, nanoplankton, and microplankton. Until now, the DPA has not been evaluated against an independent approach that provides phytoplankton size calculated on a per-cell basis. Automated quantitative cell imagery of microplankton and some nanoplankton, used in combination with conventional flow cytometry for enumeration of picoplankton and nanoplankton, provide a novel opportunity to perform an independent evaluation of the DPA. Here, we use a data set from the North Atlantic Ocean that encompasses all seasons and a wide range of chlorophyll concentrations (0.18-5.14 mg m-3). Results show that the DPA overestimates microplankton and picoplankton when compared to cytometry data, and subsequently underestimates the contribution of nanoplankton to total biomass. In contrast to the assumption made by the DPA that the microplankton size class is largely made up of diatoms and dinoflagellates, imaging-in-flow cytometry shows significant presence of diatoms and dinoflagellates in the nanoplankton size class. Additionally, chlorophyll b is commonly attributed solely to picoplankton by the DPA, but Chl b-containing phytoplankton are observed with imaging in both nanoplankton and microplankton size classes. We suggest revisions to the DPA equations and application of uncertainties when calculating size classes from diagnostic pigments.

Information content of absorption spectra and implications for ocean color inversion.

The increasing use of hyperspectral optical data in oceanography, both in situ and via remote sensing, holds the potential to significantly advance characterization of marine ecology and biogeochemistry because, in principle, hyperspectral data can provide much more detailed inferences of ecosystem properties via inversion. Effective inferences, however, require careful consideration of the close similarity of different signals of interest, and how these interplay with measurement error and uncertainty to reduce the degrees of freedom (DoF) of hyperspectral measurements. Here we discuss complementary approaches to quantify the DoF in hyperspectral measurements in the case of in situ particulate absorption measurements, though these approaches can also be used on other such data, e.g., ocean color remote sensing. Analyses suggest intermediate (${\sim}5 $∼5) DoF for our dataset of global hyperspectral particulate absorption spectra from the Tara Oceans expedition, meaning that these data can yield coarse community structure information. Empirically, chlorophyll is an effective first-order predictor of absorption spectra, meaning that error characteristics and the mathematics of inversion need to be carefully considered for hyperspectral data to provide information beyond that which chlorophyll provides. We also discuss other useful analytical tools that can be applied to this problem and place our results in the context of hyperspectral remote sensing.

Chlorophyll absorption and phytoplankton size information inferred from hyperspectral particulate beam attenuation.

Electromagnetic theory predicts spectral dependencies in extinction efficiency near a narrow absorption band for a particle with an index of refraction close to that of the medium in which it is immersed. These absorption band effects are anticipated in oceanographic beam-attenuation (beam-c) spectra, primarily due to the narrow red peak in absorption produced by the phytoplankton photopigment, chlorophyll a (Chl a). Here we present a method to obtain Chl a absorption and size information by analyzing an eigendecomposition of hyperspectral beam-c residuals measured in marine surface waters by an automatic underway system. We find that three principal modes capture more than 99% of the variance in beam-c residuals at wavelengths near the Chl a red absorption peak. The spectral shapes of the eigenvectors resemble extinction efficiency residuals attributed to the absorption band effects. Projection of the eigenvectors onto the beam-c residuals produces a time series of amplitude functions with absolute values that are strongly correlated to concurrent Chl a absorption line height (aLH) measurements (r values of 0.59 to 0.83) and hence provide a method to estimate Chl a absorption. Multiple linear regression of aLH on the amplitude functions enables an independent estimate of aLH, with RMSE of 3.19⋅10-3m-1 (3.3%) or log10-RMSE of 18.6%, and a raw-scale R2 value of 0.90 based on the Tara Oceans Expedition data. Relationships between the amplitude functions and the beam-c exponential slopes are in agreement with theory relating beam-c to the particle size distribution. Compared to multispectral analysis of beam-c slope, hyperspectral analysis of absorption band effects is anticipated to be relatively insensitive to the addition of nonpigmented particles and to monodispersion.

Algorithm to derive inherent optical properties from remote sensing reflectance in turbid and eutrophic lakes.

Inherent optical properties play an important role in understanding the biogeochemical processes of lakes by providing proxies for a variety of biogeochemical quantities, including phytoplankton pigments. However, to date, it has been difficult to accurately derive the absorption coefficient of phytoplankton $[{a_{ph}}(\lambda )]$[aph(λ)] in turbid and eutrophic waters from remote sensing. A large dataset of remote sensing of reflectance $[{R_{rs}}(\lambda )]$[Rrs(λ)] and absorption coefficients was measured for samples collected from lakes in the middle and lower reaches of the Yangtze River and Huai River basin (MLYHR), China. In the process of scattering correction of spectrophotometric measurements, the particulate absorption coefficients $[{a_p}(\lambda )]$[ap(λ)] were first assumed to have no absorption in the near-infrared (NIR) wavelength. This assumption was corrected by estimating the particulate absorption coefficients at 750 nm $[{a_p}({750})]$[ap(750)] from the concentrations of chlorophyll-a (Chla) and suspended particulate matter, which was added to the ${a_p}(\lambda )$ap(λ) as a baseline. The resulting mean spectral mass-specific absorption coefficient of the nonalgal particles (NAPs) was consistent with previous work. A novel iterative IOP inversion model was then designed to retrieve the total nonwater absorption coefficients $[{a_{nw}}(\lambda )]$[anw(λ)] and backscattering coefficients of particulates $[{b_{bp}}(\lambda )]$[bbp(λ)], ${a_{ph}}(\lambda )$aph(λ), and ${a_{dg}}(\lambda )$adg(λ) [absorption coefficients of NAP and colored dissolved organic matter (CDOM)] from ${R_{rs}}(\lambda )$Rrs(λ) in turbid inland lakes. The proposed algorithm performed better than previously published models in deriving ${a_{nw}}(\lambda )$anw(λ) and ${b_{bp}}(\lambda )$bbp(λ) in this region. The proposed algorithm performed well in estimating the ${a_{ph}}(\lambda )$aph(λ) for wavelengths $ > {500}\;{\rm nm}$>500nm for the calibration dataset [${\rm N} = {285}$N=285, unbiased absolute percentage difference $({\rm UAPD}) = {55.22}\% $(UAPD)=55.22%, root mean square error $({\rm RMSE}) = {0.44}\;{{\rm m}^{ - 1}}$(RMSE)=0.44m-1] and for the validation dataset (${\rm N} = {57}$N=57, ${\rm UAPD} = {56.17}\% $UAPD=56.17%, ${\rm RMSE} = {0.71}\;{{\rm m}^{ - 1}}$RMSE=0.71m-1). This algorithm was then applied to Sentinel-3A Ocean and Land Color Instrument (OLCI) satellite data, and was validated with field data. This study provides an example of how to use local data to devise an algorithm to obtain IOPs, and in particular, ${a_{ph}}(\lambda )$aph(λ), using satellite ${R_{rs}}(\lambda )$Rrs(λ) data in turbid inland waters.

Improved correction for non-photochemical quenching of in situ chlorophyll fluorescence based on a synchronous irradiance profile.

In situ chlorophyll fluorometers have been used to quantify the distribution of chlorophyll concentration in natural waters for decades. However, chlorophyll fluorescence is depressed during daylight hours due to non-photochemical quenching (NPQ). Corrections attempted to date have provided improvement but still remain unsatisfactory, often over-estimating the expected value. In this study, we examine the relationship between NPQ and instantaneous Photosynthetically Active Radiation (iPAR) using field data from BGC-Argo floats equipped with Chlorophyll-a fluorometers and radiometers. This analysis leads to an improved NPQ correction that incorporates both iPAR and mixed layer depth (MLD) and is validated against data collected at sunrise or sunset. The optimal NPQ light threshold is found to be iPAR = 15 µmol quanta m-2 s-1, and the proposed methods based on such a light threshold correct the NPQ effect more accurately than others, except in "shallow-mixing" waters (NPQ light threshold depth deeper than MLD). For these waters, an empirical-relationship-based method is proposed for improvement of NPQ correction using an iPAR profile. It is therefore recommended that, for optimal NPQ corrections, profiling floats measuring chlorophyll fluorescence in daytime be equipped with iPAR radiometers.

Validation of the particle size distribution obtained with the laser in-situ scattering and transmission (LISST) meter in flow-through mode.

High spatial and temporal resolution estimates of the particle size distribution (PSD) in the surface ocean can enable improved understanding of biogeochemistry and ecosystem dynamics. Oceanic PSD measurements remain rare due to the time-consuming, manual sampling methods of common particle sizing instruments. Here, we evaluate the utility of measuring particle size data at high spatial resolution with a commercially-available submersible laser diffraction particle sizer (LISST-100X, Sequoia Scientific), operating in an automated mode with continuously flowing seawater. The LISST PSD agreed reasonably well with discrete PSD measurements obtained with a Coulter Counter and data from the flow-through sampling Imaging Flow-Cytobot, validating our methodology. Total particulate area and Volume derived from the LISST PSD agreed well with beam-attenuation and particulate organic carbon respectively, further validating the LISST PSD. Furthermore, When compared to the measured spectral characteristics of particulate beam attenuation, we find a significant correlation. However, no significant relationship between the PSD and spectral particulate backscattering was found.