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Begouen Demeaux, Charlotte, and Emmanuel Boss. "Validation of Remote-Sensing Algorithms for Diffuse Attenuation of Downward Irradiance Using BGC-Argo Floats." Remote Sensing 14, no. 18 (2022): 4500. http://dx.doi.org/10.3390/rs14184500.
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Estimates of the diffuse attenuation coefficient (Kd) at two different wavelengths and band-integrated (PAR) were obtained using different published algorithms developed for open ocean waters spanning in type from explicit-empirical, semi-analytical and implicit-empirical and applied to data from spectral radiometers on board six different satellites (MODIS-Aqua, MODIS-Terra, VIIRS–SNPP, VIIRS-JPSS, OLCI-Sentinel 3A and OLCI-Sentinel 3B). The resultant Kds were compared to those inferred from measurements of radiometry from sensors on board autonomous profiling floats (BGC-Argo). Advantages of BGC-Argo measurements compared to ship-based ones include: 1. uniform sampling in time throughout the year, 2. large spatial coverage, and 3. lack of shading by platform. Over 5000 quality-controlled matchups between Kds derived from float and from satellite sensors were found with values ranging from 0.01 to 0.67 m−1. Our results show that although all three algorithm types provided similarly ranging values of Kd to those of the floats, for most sensors, a given algorithm produced statistically different Kd distributions from the two others. Algorithm results diverged the most for low Kd (clearest waters). Algorithm biases were traced to the limitations of the datasets the algorithms were developed and trained with, as well as the neglect of sun angle in some algorithms. This study highlights: 1. the importance of using comprehensive field-based datasets (such as BGC-Argo) for algorithm development, 2. the limitation of using radiative-transfer model simulations only for algorithm development, and 3. the potential for improvement if sun angle is taken into account explicitly to improve empirical Kd algorithms. Recent augmentation of profiling floats with hyper-spectral radiometers should be encouraged as they will provide additional constraints to develop algorithms for upcoming missions such as NASA’s PACE and SBG and ESA’s CHIME, all of which will include a hyper-spectral radiometer.
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Bellacicco, Vellucci, Scardi, Barbieux, Marullo, and D’Ortenzio. "Quantifying the Impact of Linear Regression Model in Deriving Bio-Optical Relationships: The Implications on Ocean Carbon Estimations." Sensors 19, no. 13 (2019): 3032. http://dx.doi.org/10.3390/s19133032.
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Linear regression is widely used in applied sciences and, in particular, in satellite optical oceanography, to relate dependent to independent variables. It is often adopted to establish empirical algorithms based on a finite set of measurements, which are later applied to observations on a larger scale from platforms such as autonomous profiling floats equipped with optical instruments (e.g., Biogeochemical Argo floats; BGC-Argo floats) and satellite ocean colour sensors (e.g., SeaWiFS, VIIRS, OLCI). However, different methods can be applied to a given pair of variables to determine the coefficients of the linear equation fitting the data, which are therefore not unique. In this work, we quantify the impact of the choice of “regression method” (i.e., either type-I or type-II) to derive bio-optical relationships, both from theoretical perspectives and by using specific examples. We have applied usual regression methods to an in situ data set of particulate organic carbon (POC), total chlorophyll-a (TChla), optical particulate backscattering coefficient (bbp), and 19 years of monthly TChla and bbp ocean colour data. Results of the regression analysis have been used to calculate phytoplankton carbon biomass (Cphyto) and POC from: i) BGC-Argo float observations; ii) oceanographic cruises, and iii) satellite data. These applications enable highlighting the differences in Cphyto and POC estimates relative to the choice of the method. An analysis of the statistical properties of the dataset and a detailed description of the hypothesis of the work drive the selection of the linear regression method
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O’Brien, Terence, and Emmanuel Boss. "Correction of Radiometry Data for Temperature Effect on Dark Current, with Application to Radiometers on Profiling Floats." Sensors 22, no. 18 (2022): 6771. http://dx.doi.org/10.3390/s22186771.
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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.
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Claustre, Hervé, Kenneth S. Johnson, and Yuichiro Takeshita. "Observing the Global Ocean with Biogeochemical-Argo." Annual Review of Marine Science 12, no. 1 (2020): 23–48. http://dx.doi.org/10.1146/annurev-marine-010419-010956.
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Biogeochemical-Argo (BGC-Argo) is a network of profiling floats carrying sensors that enable observation of as many as six essential biogeochemical and bio-optical variables: oxygen, nitrate, pH, chlorophyll a, suspended particles, and downwelling irradiance. This sensor network represents today's most promising strategy for collecting temporally and vertically resolved observations of biogeochemical properties throughout the ocean. All data are freely available within 24 hours of transmission. These data fill large gaps in ocean-observing systems and support three ambitions: gaining a better understanding of biogeochemical processes (e.g., the biological carbon pump and air–sea CO2 exchanges) and evaluating ongoing changes resulting from increasing anthropogenic pressure (e.g., acidification and deoxygenation); managing the ocean (e.g., improving the global carbon budget and developing sustainable fisheries); and carrying out exploration for potential discoveries. The BGC-Argo network has already delivered extensive high-quality global data sets that have resulted in unique scientific outcomes from regional to global scales. With the proposed expansion of BGC-Argo in the near future, this network has the potential to become a pivotal observation system that links satellite and ship-based observations in a transformative manner.
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Matsumoto, George I., Kenneth S. Johnson, Steve Riser, Lynne Talley, Susan Wijffels, and Roberta Hotinski. "The Global Ocean Biogeochemistry (GO-BGC) Array of Profiling Floats to Observe Changing Ocean Chemistry and Biology." Marine Technology Society Journal 56, no. 3 (2022): 122–23. http://dx.doi.org/10.4031/mtsj.56.3.25.
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Abstract The Global Ocean Biogeochemistry (GO-BGC) Array is a project funded by the US National Science Foundation to build a global network of chemical and biological sensors on Argo profiling floats. The network will monitor biogeochemical cycles and ocean health. The floats will collect from a depth of 2,000 meters to the surface, augmenting the existing <ext-link ext-link-type="uri" xlink:href="https://argo.ucsd.edu/">Argo array</ext-link> that monitors ocean temperature and salinity. Data will be made freely available within a day of being collected via the Argo data system. These data will allow scientists to pursue fundamental questions concerning ocean ecosystems, monitor ocean health and productivity, and observe the elemental cycles of carbon, oxygen, and nitrogen through all seasons of the year. Such essential data are needed to improve computer models of ocean fisheries and climate, to monitor and forecast the effects of ocean warming and ocean acidification on sea life, and to address key questions identified in “Sea Change: 2015‐2025 Decadal Survey of Ocean Sciences” such as: What is the ocean's role in regulating the carbon cycle? What are the natural and anthropogenic drivers of open ocean deoxygenation? What are the consequences of ocean acidification? How do physical changes in mixing and circulation affect nutrient availability and ocean productivity?
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Barbieux, Marie, Julia Uitz, Bernard Gentili, et al. "Bio-optical characterization of subsurface chlorophyll maxima in the Mediterranean Sea from a Biogeochemical-Argo float database." Biogeosciences 16, no. 6 (2019): 1321–42. http://dx.doi.org/10.5194/bg-16-1321-2019.
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Abstract. As commonly observed in oligotrophic stratified waters, a subsurface (or deep) chlorophyll maximum (SCM) frequently characterizes the vertical distribution of phytoplankton chlorophyll in the Mediterranean Sea. Occurring far from the surface layer “seen” by ocean colour satellites, SCMs are difficult to observe with adequate spatio-temporal resolution and their biogeochemical impact remains unknown. Biogeochemical-Argo (BGC-Argo) profiling floats represent appropriate tools for studying the dynamics of SCMs. Based on data collected from 36 BGC-Argo floats deployed in the Mediterranean Sea, our study aims to address two main questions. (1) What are the different types of SCMs in the Mediterranean Sea? (2) Which environmental factors control their occurrence and dynamics? First, we analysed the seasonal and regional variations in the chlorophyll concentration (Chl a), particulate backscattering coefficient (bbp), a proxy of the particulate organic carbon (POC) and environmental parameters (photosynthetically active radiation and nitrates) within the SCM layer over the Mediterranean Basin. The vertical profiles of Chl a and bbp were then statistically classified and the seasonal occurrence of each of the different types of SCMs quantified. Finally, a case study was performed on two contrasted regions and the environmental conditions at depth were further investigated to understand the main controls on the SCMs. In the eastern basin, SCMs result, at a first order, from a photoacclimation process. Conversely, SCMs in the western basin reflect a biomass increase at depth benefiting from both light and nitrate resources. Our results also suggest that a variety of intermediate types of SCMs are encountered between these two endmember situations.
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Barbieux, Marie, Julia Uitz, Alexandre Mignot, et al. "Biological production in two contrasted regions of the Mediterranean Sea during the oligotrophic period: an estimate based on the diel cycle of optical properties measured by BioGeoChemical-Argo profiling floats." Biogeosciences 19, no. 4 (2022): 1165–94. http://dx.doi.org/10.5194/bg-19-1165-2022.
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Abstract. This study assesses marine community production based on the diel variability of bio-optical properties monitored by two BioGeoChemical-Argo (BGC-Argo) floats. Experiments were conducted in two distinct Mediterranean systems, the northwestern Ligurian Sea and the central Ionian Sea, during summer months. We derived particulate organic carbon (POC) stock and gross community production integrated within the surface, euphotic and subsurface chlorophyll maximum (SCM) layers, using an existing approach applied to diel cycle measurements of the particulate beam attenuation (cp) and backscattering (bbp) coefficients. The diel cycle of cp provided a robust proxy for quantifying biological production in both systems; that of bbp was comparatively less robust. Derived primary production estimates vary by a factor of 2 depending upon the choice of the bio-optical relationship that converts the measured optical coefficient to POC, which is thus a critical step to constrain. Our results indicate a substantial contribution to the water column production of the SCM layer (16 %–42 %), which varies largely with the considered system. In the Ligurian Sea, the SCM is a seasonal feature that behaves as a subsurface biomass maximum (SBM) with the ability to respond to episodic abiotic forcing by increasing production. In contrast, in the Ionian Sea, the SCM is permanent, primarily induced by phytoplankton photoacclimation, and contributes moderately to water column production. These results clearly demonstrate the strong potential for transmissometers deployed on BGC-Argo profiling floats to quantify non-intrusively in situ biological production of organic carbon in the water column of stratified oligotrophic systems with recurring or permanent SCMs, which are widespread features in the global ocean.
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Chai, Fei, Yuntao Wang, Xiaogang Xing, et al. "A limited effect of sub-tropical typhoons on phytoplankton dynamics." Biogeosciences 18, no. 3 (2021): 849–59. http://dx.doi.org/10.5194/bg-18-849-2021.
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Abstract. Typhoons are assumed to stimulate primary ocean production through the upward mixing of nutrients into the ocean surface. This assumption is based largely on observations of increased surface chlorophyll concentrations following the passage of typhoons. This surface chlorophyll enhancement, occasionally detected by satellites, is often undetected due to intense cloud coverage. Daily data from a BGC-Argo profiling float revealed the upper-ocean response to Typhoon Trami in the northwest Pacific Ocean. Temperature and chlorophyll changed rapidly, with a significant drop in sea surface temperature and a surge in surface chlorophyll associated with strong vertical mixing, which was only partially captured by satellite observations. However, no net increase in vertically integrated chlorophyll was observed during Typhoon Trami or in its wake. In contrast to the prevailing dogma, the result shows that typhoons likely have a limited effect on net primary ocean production. Observed surface chlorophyll enhancements during and immediately following typhoons in tropical and subtropical waters are more likely to be associated with surface entrainment of deep chlorophyll maxima. Moreover, the findings demonstrate that remote sensing data alone can overestimate the impact of storms on primary production in all oceans. Full understanding of the impact of storms on upper-ocean productivity can only be achieved with ocean-observing robots dedicated to high-resolution temporal sampling in the path of storms.
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Stoer, Adam C., Yuichiro Takeshita, Tanya Lee Maurer, et al. "A census of quality-controlled Biogeochemical-Argo float measurements." Frontiers in Marine Science 10 (October 27, 2023). http://dx.doi.org/10.3389/fmars.2023.1233289.
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Biogeochemical- (BGC-) Argo aims to deploy and maintain a global array of autonomous profiling floats to monitor ocean biogeochemistry. With over 250,000 profiles collected so far, the BGC-Argo network is rapidly expanding toward the target of a sustained fleet of 1,000 floats. These floats prioritize the measurement of six key properties: oxygen, nitrate, pH, chlorophyll-a, suspended particles, and downwelling light. To assess the current biogeochemical state of the ocean, its variability, and trends with confidence, it is crucial to quality control these measurements. Accordingly, BGC-Argo maintains a quality control system using manual inspection and parameter-specific algorithms for flagging and adjusting data. In this study, we provide a census of the quantity and quality of measurements from BGC-Argo based on their quality flagging system. The purpose of this census is to assess the current status of the array in terms of data quality, how data quality has changed over time, and to provide a better understanding of the quality-controlled data to current and future users. Alongside increasing profile numbers and spatial coverage, we report that for most parameters between 80 and 95% of the profiles collected so far contain high-quality BGC data, with an exception for pH. The quality of pH profiles has seen a large improvement in the last five years and is on track to match the data quality of other BGC parameters. We highlight how BGC-Argo is improving and discuss strategies to increase the quality and quantity of BGC profiles available to users. This census shows that tracking percentages of high-quality data through time is useful for monitoring float sensor technology and helpful for ensuring the long-term success of BGC-Argo.
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Johnson, Gregory, and Andrea Fassbender. "After Two Decades, Argo at PMEL, Looks to the Future." Oceanography, 2023. http://dx.doi.org/10.5670/oceanog.2023.223.
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The NOAA Pacific Environmental Laboratory (PMEL) has contributed to the revolutionary Argo ocean observing system since its inception, developing CTD calibration algorithms and software that have been adopted by the international Argo community. PMEL has provided over 1,440 Argo floats—~13% of the global array—with ~500 currently active. PMEL scientific contributions using Argo data have ranged from regional to global analyses of ocean circulation and water-mass variability, to ocean warming and its contributions to sea level rise and Earth’s energy imbalance, to estimates of global ocean deoxygenation. In recent years, PMEL has initiated both Deep Argo (with a regional pilot array of full-ocean-depth profiling floats in the rapidly changing and dynamic western South Atlantic) and Biogeochemical (BGC) Argo (with a pilot array in the biogeochemically diverse and economically important California Current Large Marine Ecosystem). PMEL is also developing innovative near-global maps of ocean physical and biogeochemical parameters using machine learning algorithms that enable investigations of societally important oceanographic phenomena, and an Adopt-A-Float program. Future challenges include growing the financial, infrastructure, and human resources necessary to take the Deep and BGC Argo missions global and to fulfill the One Argo mission of a global, full-depth, multidisciplinary ocean observing array.
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Maurer, Tanya L., Joshua N. Plant, and Kenneth S. Johnson. "Delayed-Mode Quality Control of Oxygen, Nitrate, and pH Data on SOCCOM Biogeochemical Profiling Floats." Frontiers in Marine Science 8 (August 11, 2021). http://dx.doi.org/10.3389/fmars.2021.683207.
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The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project has deployed 194 profiling floats equipped with biogeochemical (BGC) sensors, making it one of the largest contributors to global BGC-Argo. Post-deployment quality control (QC) of float-based oxygen, nitrate, and pH data is a crucial step in the processing and dissemination of such data, as in situ chemical sensors remain in early stages of development. In situ calibration of chemical sensors on profiling floats using atmospheric reanalysis and empirical algorithms can bring accuracy to within 3 μmol O2 kg–1, 0.5 μmol NO3– kg–1, and 0.007 pH units. Routine QC efforts utilizing these methods can be conducted manually through visual inspection of data to assess sensor drifts and offsets, but more automated processes are preferred to support the growing number of BGC floats and reduce subjectivity among delayed-mode operators. Here we present a methodology and accompanying software designed to easily visualize float data against select reference datasets and assess QC adjustments within a quantitative framework. The software is intended for global use and has been used successfully in the post-deployment calibration and QC of over 250 BGC floats, including all floats within the SOCCOM array. Results from validation of the proposed methodology are also presented which help to verify the quality of the data adjustments through time.
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Koestner, Daniel, Dariusz Stramski, and Rick A. Reynolds. "A Multivariable Empirical Algorithm for Estimating Particulate Organic Carbon Concentration in Marine Environments From Optical Backscattering and Chlorophyll-a Measurements." Frontiers in Marine Science 9 (August 12, 2022). http://dx.doi.org/10.3389/fmars.2022.941950.
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Accurate estimates of the oceanic particulate organic carbon concentration (POC) from optical measurements have remained challenging because interactions between light and natural assemblages of marine particles are complex, depending on particle concentration, composition, and size distribution. In particular, the applicability of a single relationship between POC and the spectral particulate backscattering coefficient bbp(λ) across diverse oceanic environments is subject to high uncertainties because of the variable nature of particulate assemblages. These relationships have nevertheless been widely used to estimate oceanic POC using, for example, in situ measurements of bbp from Biogeochemical (BGC)-Argo floats. Despite these challenges, such an in situbased approach to estimate POC remains scientifically attractive in view of the expanding global-scale observations with the BGC-Argo array of profiling floats equipped with optical sensors. In the current study, we describe an improved empirical approach to estimate POC which takes advantage of simultaneous measurements of bbp and chlorophyll-a fluorescence to better account for the effects of variable particle composition on the relationship between POC and bbp. We formulated multivariable regression models using a dataset of field measurements of POC, bbp, and chlorophyll-a concentration (Chla), including surface and subsurface water samples from the Atlantic, Pacific, Arctic, and Southern Oceans. The analysis of this dataset of diverse seawater samples demonstrates that the use of bbp and an additional independent variable related to particle composition involving both bbp and Chla leads to notable improvements in POC estimations compared with a typical univariate regression model based on bbp alone. These multivariable algorithms are expected to be particularly useful for estimating POC with measurements from autonomous BGC-Argo floats operating in diverse oceanic environments. We demonstrate example results from the multivariable algorithm applied to depth-resolved vertical measurements from BGC-Argo floats surveying the Labrador Sea.
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Uitz, J., C. Roesler, E. Organelli, et al. "Characterization of Bio‐Optical Anomalies in the Kerguelen Region, Southern Indian Ocean: A Study Based on Shipborne Sampling and BioGeoChemical‐Argo Profiling Floats." Journal of Geophysical Research: Oceans 128, no. 12 (2023). http://dx.doi.org/10.1029/2023jc019671.
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AbstractThe Southern Ocean (SO) is known for its atypical bio‐optical regime. This complicates the interpretation of proxies measured from satellite and in situ platforms equipped with optical sensors, which occupy an important niche for monitoring the vast and remote SO. A ship‐based field study in concert with time series observations from BioGeoChemical‐Argo (BGC‐Argo) profiling floats were used to investigate spatial and temporal variations in bio‐optical relationships in the open ocean waters surrounding the Kerguelen Plateau in the Indian sector of the SO. Compared to other regions with similar chlorophyll concentrations, chlorophyll‐specific phytoplankton absorption in the blue waveband presented a consistent negative anomaly. The anomaly was uniform over deep mixed layers and correlated with phytoplankton size, photoacclimation and atypically high concentrations of fucoxanthin. The BGC‐Argo observation‐based proxies revealed that the blue absorption anomaly increased with chlorophyll concentration both spatially and temporally and, while particularly pronounced in the naturally iron‐fertilized waters, was also found in the High Nutrient Low Chlorophyll region. While phytoplankton size was an important driver of the anomaly, photoacclimation associated with self‐shading of phytoplankton cells was also involved during intense booms. The backscattering coefficient exhibited negative and positive anomalies in the low and high biomass regimes, respectively. The large positive anomaly in high biomass regimes was attributed to the variable non‐algal particles characteristics associated with a relatively high production of bloom by‐products. With clear understanding of the bio‐optical anomalies, BGC‐Argo floats stand as unique tools for monitoring the bio‐optical spatio‐temporal complexity of the SO.
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Boyd, Philip W., David Antoine, Kimberley Baldry, et al. "Controls on Polar Southern Ocean Deep Chlorophyll Maxima: Viewpoints From Multiple Observational Platforms." Global Biogeochemical Cycles 38, no. 3 (2024). http://dx.doi.org/10.1029/2023gb008033.
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AbstractDeep Chlorophyll Maxima (DCMs) are ubiquitous in low‐latitude oceans, and of recognized biogeochemical and ecological importance. DCMs have been observed in the Southern Ocean, initially from ships and recently from profiling robotic floats, but with less understanding of their onset, duration, underlying drivers, or whether they are associated with enhanced biomass features. We report the characteristics of a DCM and a Deep Biomass Maximum (DBM) in the Inter‐Polar‐Frontal‐Zone (IPFZ) south of Australia derived from CTD profiles, shipboard‐incubated samples, a towbody, and a BGC‐ARGO float. The DCM and DBM were ∼20 m thick and co‐located with the nutricline, in the vicinity of a subsurface ammonium maximum characteristic of the IPFZ, but ∼100 m shallower than the ferricline. Towbody transects demonstrated that the co‐located DCM/DBM was broadly present across the IPFZ. Large healthy diatoms, with low iron requirements, resided within the DCM/DBM, and fixed up to 20 mmol C m−2 d−1. The BGC‐ARGO float revealed that DCM/DBM persisted for >3 months. We propose a dual environmental mechanism to drive DCM/DBM formation and persistence within the IPFZ: sustained supply of both recycled iron within the subsurface ammonium maxima, and upward silicate transport from depth. DCM/DBM cell‐specific growth rates were considerably slower than those in the overlying mixed layer, implying that phytoplankton losses such as herbivory are also reduced, possibly because of heavily silicified diatom frustules. The light‐limited seasonal termination of the observed DCM/DBM did not result in a “diatom dump”, rather ongoing diatom downward export occurred throughout its multi‐month persistence.
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Petit, Flavien, Julia Uitz, Catherine Schmechtig, et al. "Influence of the phytoplankton community composition on the in situ fluorescence signal: Implication for an improved estimation of the chlorophyll-a concentration from BioGeoChemical-Argo profiling floats." Frontiers in Marine Science 9 (September 21, 2022). http://dx.doi.org/10.3389/fmars.2022.959131.
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In-situ fluorescence is a widely used method to estimate the chlorophyll-a (Chla) concentration, a proxy of the phytoplankton biomass. With the emergence of autonomous platforms such as BioGeoChemical-Argo (BGC-Argo) profiling floats, its use has expanded to global scale observations. However, the relationship between in-situ fluorescence and Chla may vary significantly, leading to major discrepancies between oceanic regions. This study aims to investigate the main sources of the natural variability in the in-situ fluorescence signal in the global open ocean, specifically the influence of the phytoplankton community composition. In this view, we analyzed a combination of three datasets comprising concomitant measurements of in-situ fluorescence, pigment concentrations and phytoplankton absorption spectra. Two datasets cover several contrasted bioregions of the global ocean whereas the third one consists of a regional time series in the northwestern Mediterranean Sea, which allows to examine the effect of phytoplankton community composition on the fluorescence signal on the global, seasonal and vertical scales. We studied the variability of the two major drivers of the natural variability of the fluorescence process, i.e. the light absorption and the fluorescence quantum yield of phytoplankton, in regards of the variability of the pigment composition of the communities. The community composition correlates substantially with the Chla-to-fluorescence ratio, with high fluorescence values associated with phytoplankton communities dominated by large cells. This trend may be explained by the combined effects of the community composition on the phytoplankton absorption coefficient and the fluorescence quantum yield, and is consistently observed globally, seasonally and vertically. Non-photosynthetic pigments also appear to play a critical role in oligotrophic surface waters, leading to a reduction of the quantum yield of fluorescence. The results indicate that the phytoplankton community composition plays a key role in the relationship between the in-situ fluorescence signal and Chla concentration. Therefore, we suggest that taking into account the composition of phytoplankton communities in the retrieval of the Chla concentration from current in-situ fluorometers, those mounted on BGC-Argo floats in particular, would lead to a better estimation of the phytoplankton biomass on a wide range of spatial and temporal scales.