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Phytoplankton turn seawater green when their concentration increases. This allows us to monitor them using ocean colour. However, as the spectral properties of phytoplankton and their relationship with other coloured substances in seawater vary, subtle differences (anomalies) in ocean colour occur that can cause large errors in estimates of phytoplankton abundance. Identifying and understanding these anomalies is required to interpret ocean-colour data properly, but not all scientists have access to, or can afford, the in-situ instrumentation needed to do this. We show that practical, low-cost tools developed in the 19th century (a Secchi disk and Forel-Ule colour scale) can be used to quantify a colour anomaly in the Weddell Sea. Our findings imply that ocean-colour anomalies can be identified using affordable methods. Furthermore, records collected over the last century may contain clues on how ocean ecosystems have changed with climate.
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Oceanic submesoscale processes are ubiquitous in the North Pacific Subtropical Gyre (NPSG), where the biological carbon pump is generally ineffective. Due to difficulties in collecting continuous observations, however, it remains uncertain whether episodic submesoscale processes can drive significant changes in particulate organic carbon (POC) export into the mesopelagic ocean. Here we present observations from high-frequency Biogeochemical-Argo floats in the NPSG, which captured the enhanced POC export fluxes during the intensifying stages of a submesoscale front and a cyclonic eddy compared to their other life stages. A higher percentage of POC export flux was found to be transferred to the base of mesopelagic layer at the front compared to that at the intensifying eddy and the mean of previous studies (37% vs. ~10%), suggesting that the POC export efficiency was significantly strengthened by submesoscale dynamics. Such findings highlight the importance of submesoscale fronts for carbon export and sequestration in subtropical gyres.
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Fiducial reference measurements are in-situ data traceable to metrology standards, with associated uncertainties. This paper presents the methodology used to derive the uncertainty budget for underway, above-water measurements from the Seabird Hyperspectral Surface Acquisition System deployed on an Atlantic Meridional Transect in 2018. The average uncertainty of remote sensing reflectance for clear sky days was â¼ 6% at wavelengths < 490 nm and â¼ 12% at wavelengths > 550 nm. The environmental variability such as sun position, wind speed and skylight distribution caused the greatest uncertainty. The different components of the uncertainty budget are critically assessed to indicate how the measurement procedure could be improved through reducing the principal uncertainty sources.
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We describe an approach to partition a vertical profile of chlorophyll-a concentration into contributions from two communities of phytoplankton: one (community 1) that resides principally in the turbulent mixed-layer of the upper ocean and is observable through satellite visible radiometry; the other (community 2) residing below the mixed-layer, in a stably stratified environment, hidden from the eyes of the satellite. The approach is tuned to a time-series of profiles from a Biogeochemical-Argo float in the northern Red Sea, selected as its location transitions from a deep mixed layer in winter (characteristic of vertically well-mixed systems) to a shallow mixed layer in the summer with a deep chlorophyll-a maximum (characteristic of vertically stratified systems). The approach is extended to reproduce profiles of particle backscattering, by deriving the chlorophyll-specific backscattering coefficients of the two communities and a background coefficient assumed to be dominated by non-algal particles in the region. Analysis of the float data reveals contrasting phenology of the two communities, with community 1 blooming in winter and 2 in summer, community 1 negatively correlated with epipelagic stratification, and 2 positively correlated. We observe a dynamic chlorophyll-specific backscattering coefficient for community 1 (stable for community 2), positively correlated with light in the mixed-layer, suggesting seasonal changes in photoacclimation and/or taxonomic composition within community 1. The approach has the potential for monitoring vertical changes in epipelagic biogeography and for combining satellite and ocean robotic data to yield a three-dimensional view of phytoplankton distribution.
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BACKGROUND: Biogeochemical-Argo floats are collecting an unprecedented number of profiles of optical backscattering measurements in the global ocean. Backscattering (BBP) data are crucial to understanding ocean particle dynamics and the biological carbon pump. Yet, so far, no procedures have been agreed upon to quality control BBP data in real time. METHODS: Here, we present a new suite of real-time quality-control tests and apply them to the current global BBP Argo dataset. The tests were developed by expert BBP users and Argo data managers and have been implemented on a snapshot of the entire Argo dataset. RESULTS: The new tests are able to automatically flag most of the "bad" BBP profiles from the raw dataset. CONCLUSIONS: The proposed tests have been approved by the Biogeochemical-Argo Data Management Team and will be implemented by the Argo Data Assembly Centres to deliver real-time quality-controlled profiles of optical backscattering. Provided they reach a pressure of about 1000 dbar, these tests could also be applied to BBP profiles collected by other platforms.
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Lagrangian analysis is becoming increasingly important to better understand the ocean's biological and biogeochemical cycles. Yet, biologists and chemists often lack the technical skills required to set up such analyses. Here, we present a new product of pre-computed ocean Lagrangian trajectories (OLTraj) targeting non-expert users, and demonstrate how to use it by means of worked examples. OLTraj is based on satellite-derived geostrophic currents, which allows one to directly compare it with other in-situ or satellite products. We anticipate that OLTraj will foster a new interest in Lagrangian applications in ocean biology and biogeochemistry.
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Measurements of particulate organic carbon (POC) in the open ocean provide grounds for estimating oceanic carbon budgets and for modelling carbon cycling. The majority of the published POC measurements have been collected at the sea surface. Thus, POC stocks in the upper layer of the water column are relatively well constrained. However, our understanding of the POC distribution and its dynamics in deeper areas is still modest due to insufficient POC measurements. Moreover, the uncertainty of published POC estimates is not always quantified, and neither is it fully understood. In this study, we determined the POC concentrations of samples collected in the upper 500 m during an Atlantic Meridional Transect and described a method for quantifying its experimental uncertainties using duplicate measurements. The analysis revealed that the medians of the total experimental uncertainties associated with our POC concentrations in the productive and mesopelagic zones were 2(±2) mg/m 3 and 3(±1) mg/m 3, respectively. In relative terms, these uncertainties corresponded to â¼12% and â¼35% of POC concentrations, respectively. We modelled the POC uncertainty in order to identify its main causes. This model however could explain only â¼19% of the experimental POC uncertainty. Potential sources of the unexplained uncertainty are discussed.
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Three catadromous Pacific eels (2 Anguilla marmorata, 1 A. megastoma) from the Archipelago of Vanuatu were tagged with pop-up satellite archival transmitters and their migration tracks towards their presumed spawning area approximately 870 km northeast of the point of release were reconstructed in order to evaluate their movements in relation to oceanographic conditions. We used the timing of diel vertical migrations to derive the eels' positions. Two A. marmorata exhibited steep-angled turns resulting in a zig-zag migration path along the east-west axis, while one A. megastoma took a relatively straight course towards the presumed spawning area. They migrated with a speed over ground of 21-23 km day-1. In this region, the eastward flow of the South Equatorial Counter Current (SECC, â¼ 5-10°S) separates the westward flowing South Equatorial Current (SEC; â¼0-5°S and 10-18°S) into two branches. During shallower nighttime migration depths around 150 m eels crossed a variable flow field through the southern branch of the westward SEC with westward propagating mesoscale eddies and the eastward SECC, but stayed south of the stronger northern branch of SEC possibly increasing retention time of larvae within this area. The eels headed towards a tongue of high-salinity Subtropical Underwater (STUW) that may have provided cues for orientation. The eels did not move beyond a salinity front of 35.9-36.0 at a depth of 100-200 m, which may have provided cues for orientation towards the spawning area. These 3 tracks may represent the movements of mature silver eels all the way to where they spawn.
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Optical models have been proposed to relate spectral variations in the beam attenuation (cp) and optical backscattering (bbp) coefficients to marine particle size distributions (PSDs). However, due to limited PSD data, particularly in the open ocean, optically derived PSDs suffer from large uncertainties and we have a poor empirical understanding of the drivers of spectral cp and bbp coefficients. Here we evaluated PSD optical proxies and investigated their drivers by analyzing an unprecedented dataset of co-located PSDs, phytoplankton abundances and optical measurements collected across the upper 500 m of the Atlantic Ocean. The spectral slope of cp was correlated (r>0.59) with the slope of the PSD only for particles with diameters >1â µm and also with eukaryotic phytoplankton concentrations. No significant relationships between PSDs and the spectral slope of bbp were observed. In the upper 200 m, the bbp spectral slope was correlated to the light absorption by particles (ap; r<-0.54) and to the ratio of cyanobacteria to eukaryotic phytoplankton. This latter correlation was likely the consequence of the strong relationship we observed between ap and the concentration of eukaryotic phytoplankton (r=0.83).
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Cell abundances of Prochlorococcus, Synechococcus, and autotrophic picoeukaryotes were estimated in surface waters using principal component analysis (PCA) of hyperspectral and multispectral remote-sensing reflectance data. This involved the development of models that employed multilinear correlations between cell abundances across the Atlantic Ocean and a combination of PCA scores and sea surface temperatures. The models retrieve high Prochlorococcus abundances in the Equatorial Convergence Zone and show their numerical dominance in oceanic gyres, with decreases in Prochlorococcus abundances towards temperate waters where Synechococcus flourishes, and an emergence of picoeukaryotes in temperate waters. Fine-scale in-situ sampling across ocean fronts provided a large dynamic range of measurements for the training dataset, which resulted in the successful detection of fine-scale Synechococcus patches. Satellite implementation of the models showed good performance (R2 > 0.50) when validated against in-situ data from six Atlantic Meridional Transect cruises. The improved relative performance of the hyperspectral models highlights the importance of future high spectral resolution satellite instruments, such as the NASA PACE mission's Ocean Color Instrument, to extend our spatiotemporal knowledge about ecologically relevant phytoplankton assemblages.
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Different techniques exist for determining chlorophyll-a concentration as a proxy of phytoplankton abundance. In this study, a novel method based on the spectral particulate beam-attenuation coefficient (cp) was developed to estimate chlorophyll-a concentrations in oceanic waters. A multi-layer perceptron deep neural network was trained to exploit the spectral features present in cp around the chlorophyll-a absorption peak in the red spectral region. Results show that the model was successful at accurately retrieving chlorophyll-a concentrations using cp in three red spectral bands, irrespective of time or location and over a wide range of chlorophyll-a concentrations.
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Clorofila A/análisis , Aprendizaje Profundo , Análisis Espectral , Sesgo , Bases de Datos como Asunto , Redes Neurales de la Computación , Reproducibilidad de los Resultados , Factores de TiempoRESUMEN
A critical driver of the ocean carbon cycle is the downward flux of sinking organic particles, which acts to lower the atmospheric carbon dioxide concentration. This downward flux is reduced by more than 70% in the mesopelagic zone (100 to 1000 meters of depth), but this loss cannot be fully accounted for by current measurements. For decades, it has been hypothesized that the missing loss could be explained by the fragmentation of large aggregates into small particles, although data to test this hypothesis have been lacking. In this work, using robotic observations, we quantified total mesopelagic fragmentation during 34 high-flux events across multiple ocean regions and found that fragmentation accounted for 49 ± 22% of the observed flux loss. Therefore, fragmentation may be the primary process controlling the sequestration of sinking organic carbon.
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Ciclo del Carbono , Dióxido de Carbono/metabolismo , Fitoplancton/metabolismo , Animales , Océanos y Mares , Zooplancton/metabolismoRESUMEN
Marine microscopic particles profoundly impact global biogeochemical cycles, but our understanding of their dynamics is hindered by lack of observations. To fill this gap, optical backscattering measured by satellite sensors and in-situ autonomous platforms can be exploited. Unfortunately, these observations remain critically limited by an incomplete mechanistic understanding of what particles generate the backscattering signal. To achieve this understanding, optical models are employed. The simplest of these models-the homogeneous sphere-severely underestimates the measured backscattering and the missing signal has been attributed to submicron particles. This issue is known as the missing backscattering enigma. Here we show that a slightly more complex optical model-the coated sphere-can predict the measured backscattering and suggests that most of the signal comes from particles >1 µm. These findings were confirmed by independent size-fractionation experiments. Our results demonstrate that the structural complexity of particles is critical to understand open-ocean backscattering and contribute to solving the enigma.
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Measurements of the absorption coefficient of chromophoric dissolved organic matter (ay) are needed to validate existing ocean-color algorithms. In the surface open ocean, these measurements are challenging because of low ay values. Yet, existing global datasets demonstrate that ay could contribute between 30% to 50% of the total absorption budget in the 400-450 nm spectral range, thus making accurate measurement of ay essential to constrain these uncertainties. In this study, we present a simple way of determining ay using a commercially-available in-situ spectrophotometer operated in underway mode. The obtained ay values were validated using independent collocated measurements. The method is simple to implement, can provide measurements with very high spatio-temporal resolution, and has an accuracy of about 0.0004 m-1 and a precision of about 0.0025 m-1 when compared to independent data (at 440 nm). The only limitation for using this method at sea is that it relies on the availability of relatively large volumes of ultrapure water. Despite this limitation, the method can deliver the ay data needed for validating and assessing uncertainties in ocean-colour algorithms.
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The "mesopelagic" is the region of the ocean between about 100 and 1000 m that harbours one of the largest ecosystems and fish stocks on the planet1,2. This vastly unexplored ecosystem is believed to be mostly sustained by chemical energy, in the form of fast-sinking particulate organic carbon, supplied by the biological carbon pump3. Yet, this supply appears insufficient to match mesopelagic metabolic demands4-6. The mixed-layer pump is a physically-driven biogeochemical process7-11 that could further contribute to meet these energetic requirements. However, little is known about the magnitude and spatial distribution of this process at the global scale. Here we show that the mixed-layer pump supplies an important seasonal flux of organic carbon to the mesopelagic. By combining mixed-layer depths from Argo floats with satellite retrievals of particulate organic carbon, we estimate that this pump exports a global flux of about 0.3 Pg C yr-1 (range 0.1 - 0.5 Pg C yr-1). In high-latitude regions where mixed-layers are deep, this flux is on average 23%, but can be greater than 100% of the carbon supplied by fast sinking particles. Our results imply that a relatively large flux of organic carbon is missing from current energy budgets of the mesopelagic.
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Catadromous anguillid eels (Genus Anguilla) migrate from their freshwater or estuarine habitats to marine spawning areas. Evidence from satellite tagging studies indicates that tropical and temperate eel species exhibit pronounced diel vertical migrations between 150 to 300 m nighttime depths to 600 to 800 m during the day. Collections of eggs and larvae of Japanese eels (A. japonica) show they may spawn at these upper nighttime migration depths. How anguillid eels navigate through the ocean and find their spawning areas remains unknown, so this study describes the salinity, temperature and geostrophic currents between 0 and 800 m depths within two confirmed and three hypothetical anguillid spawning areas during likely spawning seasons. Within all four ocean gyres many eels would encounter subducted 'Subtropical Underwater' during their nighttime ascents that could provide odor plumes as signposts. Four spawning areas are located near the western margins of where subducted water masses form cores of elevated salinities (~35.0 to 36.8) around 150 m depths, while one is found near the center of subduction. Low salinity surface waters and fronts are present in some of the areas above the high-salinity cores. Spawning may occur at temperatures between 16 to 24°C where the thermocline locally deepens. At spawning depths, weak westward currents (~0 to 0.1 m s-1) prevail, and eastward surface countercurrents are present. Anguillid eels possess acute sensory capabilities to detect these hydrographic features as potential signposts guiding them to where they spawn.
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Using an extensive database of in situ observations we present a model that estimates the particle backscattering coefficient as a function of the total chlorophyll concentration in the open-ocean (Case-1 waters). The parameters of the model include a constant background component and the chlorophyll-specific backscattering coefficients associated with small (<20 µm) and large (>20 µm) phytoplankton. The new model performed with similar accuracy when compared with a traditional power-law function, with the additional benefit of providing information on the role of phytoplankton size. The observed spectral-dependency (γ) of model parameters was consistent with past observations, such that γ associated with the small phytoplankton population was higher than that of large phytoplankton. Furthermore, γ associated with the constant background component suggests this component is likely attributed to submicron particles. We envisage that the model would be useful for improving Case-1 ocean-colour models, assimilating light into multi-phytoplankton ecosystem models and improving estimates of phytoplankton size structure from remote sensing.
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Clorofila/metabolismo , Océanos y Mares , Fitoplancton/citología , Dispersión de Radiación , Bases de Datos como Asunto , Geografía , Modelos Biológicos , Reproducibilidad de los ResultadosRESUMEN
We present an extensive data set of particle attenuation (c(p)), backscattering (b(bp)), and chlorophyll concentration (Chl) from a diverse set of open ocean environments. A consistent observation in the data set is the strong coherence between c(p) and b(bp) and the resulting constancy of the backscattering ratio (0.010 +/- 0.002). The strong covariability between c(p) and b(bp) must be rooted in one or both of two explanations, 1) the size distribution of particles in the ocean is remarkably conserved and particle types responsible for c(p) and b(bp) covary, 2) the same particle types exert influence on both quantities. Therefore, existing relationships between c(p) or Chl:c(p) and phytoplankton biomass and physiological indices can be conceptually extended to the use of b(bp). This finding lends support to use of satellite-derived Chl and b(bp) for investigation of phytoplankton biomass and physiology and broadens the applications of existing ocean color retrievals.
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Ambiente , Material Particulado/análisis , Dispersión de Radiación , Océano Atlántico , Clorofila/metabolismo , Modelos Lineales , Océano Pacífico , Fitoplancton/metabolismoRESUMEN
Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (aPhi*) or the chlorophyll-a fluorescence quantum yield (eta) are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements. These algorithms are specifically designed for turbid productive waters and are based on red and near-infrared reflectances. By means of simulated data, it is shown that the spectral regions where the algorithms are maximally sensitive to Chla overlap those of maximal sensitivity to variations in the above bio-optical parameters. Thus, to increase the accuracy of Chla retrieval, we suggest using spectral regions where the algorithms are less sensitive to Chla, but also less sensitive to these interferences. aPhi* appeared to be one of the most important sources of error for retrieving Chla. However, when the phytoplankton backscattering coefficient (bb,Phi) dominates the total backscattering, as is likely during algal blooms, variations in the specific bb,Phi may introduce large systematic uncertainties in Chla estimation. Also, uncertainties in reflectance measurements, which are due to incomplete atmospheric correction or reflected skylight removal, seem to affect considerably the accuracy of Chla estimation. Instead, variations in other bio-optical parameters, such as eta or the specific backscattering coefficient of total suspended particles, appear to have minor importance. Suggestions regarding the optimal band locations to be used in the above algorithms are finally provided.
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Algoritmos , Clorofila/análisis , Monitoreo del Ambiente/métodos , Interpretación de Imagen Asistida por Computador/métodos , Modelos Biológicos , Nefelometría y Turbidimetría/métodos , Agua/análisis , Clorofila A , Simulación por Computador , Aumento de la Imagen/métodos , Luz , Modelos Químicos , Fitoplancton/aislamiento & purificación , Fitoplancton/metabolismo , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Microbiología del AguaRESUMEN
The analytical development and underlying hypothesis of a three-band algorithm for estimating chlorophyll-a concentration ([Chla]) in turbid productive waters are presented. The sensitivity of the algorithm to the spectral location of the bands used is analyzed. A large set of experimental observations ([Chla] varied between 4 and 217 mg m(-3) and turbidity between 2 and 78 nephelometric turbidity units) was used to calibrate and validate the algorithm. It was found that the variability of the chlorophyll-a fluorescence quantum yield and of the chlorophyll-a specific absorption coefficient can reduce considerably the accuracy of remote predictions of [Chla]. Instead of parameterizing these interferences, their effects were minimized by tuning the spectral regions used in the algorithm. This allowed us to predict [Chla] with a relative root-mean-square error of less than 30%.