Search

Phytoplankton play a central role in the planetary cycling of important elements and compounds. Understanding how phytoplankton are responding to climate change is consequently a major question in Earth Sciences. Monitoring phytoplankton is key to answering this question. Satellite remote sensing of ocean colour is our only means of monitoring phytoplankton in the entire surface ocean at high temporal and large spatial scales, and the continuous ocean-colour data record is now approaching a length suitable for addressing questions around climate change, at least in some regions. Yet, developing ocean-colour algorithms for climate change studies requires addressing issues of ambiguity in the ocean-colour signal. For example, for the same chlorophyll-a concentration (Chl-a) of phytoplankton, the colour of the ocean can be different depending on the type of phytoplankton present. One route to tackle the issue of ambiguity is by enriching the ocean-colour data with information on sea surface temperature (SST), a good proxy of changes in three phytoplankton size classes (PSCs) independent of changes in total Chl-a, a measure of phytoplankton biomass. Using a global surface in-situ dataset of HPLC (high performance liquid chromatography) pigments, size-fractionated filtration data, and concurrent satellite SST spanning from 1991 to 2021, we re-tuned, validated and advanced an SST-dependent three-component model that quantifies the relationship between total Chl-a and Chl-a associated with the three PSCs (pico-, nano- and microplankton). Similar to previous studies, striking dependencies between model parameters and SST were captured, which were found to improve model performance significantly. These relationships were applied to 40 years of monthly composites of satellite SST, and significant trends in model parameters were observed globally, in response to climate warming. Changes in these parameters highlight issues in estimating long-term trends in phytoplankton biomass (Chl-a) from ocean colour using standard empirical algorithms, which implicitly assume a fixed relationship between total Chl-a and Chl-a of the three size classes. The proposed ecological model will be at the centre of a new ocean-colour modelling framework, designed for investigating the response of phytoplankton to climate change, described in subsequent parts of this series of papers., This work is supported primarily by a UKRI Future Leader Fellowship (MR/V022792/1). Additional supports from the UK National Centre for Earth Observation (NCEO), the Simons Foundation Project Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems (CBIOMES, 549947, Shubha Sathyendranath), and Royal Society International Exchanges 2021 Cost Share (NSFC) grant (IEC NSFC 211058) are acknowledged. Astrid Bracher and Vanda Brotas are funded by the European Union’s Horizon 2020 Research and Innovation Programme (N810139): Project Portugal Twinning for Innovation and Excellence in Marine Science and Earth Observation (PORTWIMS). Astrid Bracher is also funded by the ESA 656 S5P+Innovation Theme 7 Ocean Colour (S5POC) project (No. 4000127533/19/I-NS). The AWI in-situ data are supported by the Helmholtz Infrastructure Initiative FRAM. Tarron Lamont and Ray Barlow acknowledge funding, logistical, and administrative support from the South African National Department of Forestry, Fisheries and the Environment (DFFE), Bayworld Centre for Research and Education (BCRE), and the South African National Research Foundation (NRF grants: 129229 and 132073). Fang Shen is funded by National Natural Science Foundation of China (No. 42076187 and No. 41771378) for the sampling of in-situ data in eastern China seas. The Atlantic Meridional Transect (AMT) is funded by the UK Natural Environment Research Council (NERC) through its National Capability Long-term Single Centre Science Programme, Climate Linked Atlantic Sector Science (grant number NE/R015953/1) to Plymouth Marine Laboratory. This work contributes to the international IMBeR project and is contribution number 386 of the AMT programme. The authors would like to acknowledge all the contributors who have shared in-situ data to the public domains, including the Western Channel Observatory, TARA Ocean, Rothera Research Station, NASA SeaBASS, ADON, Government of Canada, DATAONE, BCODMO, EDI Data Portal, PANGAEA, and BODC, and all the scientists and crew who were involved in the collection of in-situ data are sincerely appreciated. We thank NOAA for providing daily and monthly OISST (version 2) SST data; ESA for providing monthly SST-CCI (version 2.1) SST data; ESA for providing monthly OC-CCI (version 5.0) Chl-a climatology data; GEBCO for providing bathymetric data (GEBCO2021 Grid). The authors also thank Hongyan Xi for providing comments and suggestions on the early version of the manuscript.

A global in-situ data set for validation of ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in-situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient and total suspended matter. Data were obtained from multi-project archives acquired via open internet services, or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 151,673 rows, with each row representing a unique station in space and time (cf 136,250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68,641 (cf 59,781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. The compiled data are available at https://doi.pangaea.de/10.1594/PANGAEA.941318 (Valente et al., 2022)., SI

A chemotaxonomic investigation of surface phytoplankton was undertaken on a research cruise to the Atlantic sector of the Southern Ocean during late austral summer 2009. Based on pigment signatures, several distinct regions emerged that were delineated by physical features. CHEMTAX analysis of high performance liquid chromatography (HPLC) pigment data indicated that diatoms generally dominated communities south of the Antarctic Polar Front (APF), particularly in regions of elevated biomass where chlorophyll-a (chl-a) was >1.5 µg l −1 and diatoms comprised >80% of biomass. Pigment signatures representative of haptophytes-8, indicative of Phaeocystis antarctica, were dominant near the ice shelf. Chl-a concentrations were 0.2–0.6 µg l −1 between the APF and the Subtropical Front (STF) and outputs suggested that chlorophytes, haptophytes-8 and haptophyte-6, in the form of coccolithophores, were the major constituents. Very low chl-a levels ( −1 ) were observed north of the STF and the prokaryotes Synechococcus spp. and Prochlorococcus spp. were the dominant groups in these oligotrophic waters.

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015).

International audience; A multidisciplinary programme, MESOBIO (Influence of mesoscale dynamics on biological productivity at multiple trophic levels in the Mozambique Channel) was undertaken in the Mozambique Channel within the framework of a scientific partnership between France and South Africa. MESOBIO focused on the signature of the highly energetic eddy dynamics in the Mozambique Channel. The Channel, which is known to be one of the most turbulent areas in the world ocean, has a great diversity of marine organisms and is the site of active pelagic fisheries. MESOBIO was mostly based on observations at sea during 12 multidisciplinary cruises between 2002 and 2010. Hydrographic measurements, sampling of biological organisms ranging from phytoplankton to top predators, and experiments on primary production and energy transfer through the food web, were conducted onboard various research vessels. The data were analysed in relation to eddy field characteristics for the periods of the cruises, including seasonal or inter-annual variability in mesoscale activity. A modelling approach was also developed within MESOBIO for both the circulation in the Channel and the biogeochemical response to eddy forcing. This paper introduces the suite of articles on the MESOBIO investigations by summarizing background knowledge for the different disciplines and the key issues that were addressed within the programme.

Phytoplankton production and physiology were investigated at six selected locations during a research cruise in early October 2007 in Tanzanian coastal waters. The dataset included photosynthesis–irradiance and active fluorescence parameters, phytoplankton absorption coefficients, and pigment concentrations. Primary production was estimated to vary over the range 0.79–1.89 g C m–2 d–1. Diagnostic pigments indicated that micro–nanophytoplankton comprised the communities at three stations and nano–picoplankton at the other three stations. At all stations, the populations maximised their photosynthesis in the upper water column under elevated irradiance and low nutrient conditions. Significant photosynthetic activity was also observed at depth under very low light where the communities increased their quantum yield of photochemistry and the proportion of accessory chlorophylls b and c and photosynthetic carotenoids.Keywords: physiological adaptation, primary production, Tanzania coastal watersAfrican Journal of Marine Science 2011, 33(2): 283–295

2004 ENVISAT Symposium, Salzburg, AUSTRIA, SEP, 2004; We measured water leaving reflectance, phytoplankton pigments, optical properties and photosynthetic parameters in the southern Benguela ecosystem in October 2002. These data were used to validate MERIS standard products: reflectance (MERIS wavelengths) and Case 1 Chlorophyll- a. In this heterogeneous area, accurate validation required sampling within a few minutes of the satellite overpass. Inter-pigment relationships e. g. Total Chlorophyll (TChla) to Total Pigment (TP) were robust (R-2 similar to 0.99) yet pigment ratios (TChla/TP) were not constant (range 0.44 to 0.62) increasing log-linearly with biomass (R-2 similar to 0.7). Photosynthetic parameters (e. g. Photosynthetic Quantum Efficiency, PQE) and optical ratios (a(676)/a(440)) also increased log-linearly with biomass (R-2 similar to 0.8). PQE, pigment and optical ratios were linearly inter-correlated (R-2 similar to 0.7 to 0.8). From these data we derived the bio-optical traits for several phytoplankton functional types (PFTs): micro-plankton (diatoms and dinoflagellates) had high biomass, pigment ratios and PQE; nano-flagellates had low to intermediate biomass, pigment ratios and PQE; prokaryotes had very low biomass, pigment ratios and PQE. We present MERIS data analysed for PFTs and new products (PQE).

The relationships between phytoplankton pigments, optical properties and photosynthetic parameters for different phytoplankton functional types (derived by diagnostic pigment indices, DPI) were determined from data acquired in the Benguela ecosystem and the offshore region in October 2002. We observed robust inter-pigment relationships: total chlorophyll-a (TChla) was highly correlated with total pigment (TP) and accessory pigment (AP). However, the regression equations for stations dominated by flagellates differed from the equations for stations dominated by diatoms and dinoflagellates. The pigment ratio TChla/TP and the optical ratio a676/a440 were not constant but increased non-linearly with increasing TChla or TP; complimentarily the AP/TP and a490/a676 ratios decreased. There were significant non linear relationships between the photosynthetic parameters Fv/Fm or σPSII measured by Fast Repetition Rate Fluorometry and TChla or TP. Pigment ratios, optical ratios, Fv/Fm and σPSII were all inter-correlated with high significance. We determined the distinctive bio-optical properties associated with dominant phytoplankton functional types (derived by DPI) that conformed to the classical partitioning: flagellates (nano-plankton, comprising several taxa) had low biomass,low TChla/TP fraction and low Fv/Fm and high σPSII; diatoms and dinoflagellates (micro-plankton) had high biomass, pigment ratios, Fv/Fm and low σPSII.

International audience; Whether for biogeochemical studies or ocean color validation activities, high-performance liquid chromatography (HPLC) is an established reference technique for the analysis of chlorophyll a and associated phytoplankton pigments. The results of an intercomparison exercise of HPLC pigment determination, performed for the first time on natural samples and involving four laboratories (each using a different HPLC procedure), are used to address three main objectives: (a) estimate (and explain) the level of agreement or discrepancy in the methods used, (b) establish whether or not the accuracy requirements for ocean color validation activities can be met, and (c) establish how higher order associations in individual pigments (i.e., sums and ratios) influence the uncertainty budget while also determining how this information can be used to minimize the variance within larger pigment databases. The round-robin test samples (11 different samples received in duplicate by each laboratory) covered a range of total chlorophyll a concentration, [TChl a], representative of open ocean conditions from 0.045 mg m(-3), typical of the highly oligotrophic surface waters of the Ionian Sea, to 2.2 mg m(-3), characteristic of the upwelling regime off Morocco. Despite the diversity in trophic conditions and HPLC methods, the agreement between laboratories, defined here as the absolute percent difference (APD), was approximately 7.0% for [TChl a], which is well within the 25% accuracy objective for remote sensing validation purposes. For other pigments (mainly chemotaxinomic carotenoids), the agreement between methods was 21.5% on average (ranging from 11.5% for fucoxanthin to 32.5% for peridinin), and inversely depended on pigment concentration (with large disagreements for pigments close to the detection limits). It is shown that better agreement between methods can be achieved if some simple procedures are employed: (a) disregarding results less than the effective limit of quantitation (LOQ, an alternative to the method detection limit, MDL), (b) standardizing the manner in which the concentration of pigment standards are determined, and (c) accurately accounting for divinyl chlorophyll a when computing [TChl a] for those methods which do not chromatographically separate it from monovinyl chlorophyll a. The use of these quality-assurance procedures improved the agreement between methods, with average APD values dropping from 7.0% to 5.5% for [TChl a] and from 21.5% to 13.9% for the principal carotenoids. Additionally, it is shown that subsequent grouping of individual pigment concentrations into sums and ratios significantly reduced the variance and, thus, improved the agreement between laboratories. This grouping, therefore, provides a simple mechanism for decreasing the variance within databases composed of merged data from different origins. Among the recommendations for improving database consistency in the future, it is suggested that submissions to a database should include the relevant information related to the limit of detection for the HPLC method. (C) 2003 Elsevier B.V. All rights reserved.