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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.

Estuaries are among the most productive ecosystems on Earth and provide multiple ecosystem services. They harbor ecologically important habitats for fish, shellfish, and birds and support diverse human activities (e.g., marine transportation, fishing, and tourism). However, climate change, together with the predicted increase of human activities, may increase the hazards in these systems and alter estuarine ecosystems dynamics. Coupled hydrodynamics and biogeochemical numerical models, which jointly simulate the physical, chemical, and biological processes at the relevant spatial and temporal scales, are useful tools to support climate change impact studies on estuarine ecosystems dynamics. A general overview of some well-established coupled hydrodynamic–biogeochemical models is presented and their use to support the study of climate change impacts on estuarine ecosystems is discussed. The use of coupled hydrodynamic–biogeochemical models to support the long-term, climate-adapt management of estuarine ecosystems and the definition of mitigation and adaptation strategies within a climate change context is demonstrated with a case study: the evaluation of climate change impacts in the lower trophic levels dynamics in the Aveiro lagoon using the model ECO-SELFE. Existing coupled hydrodynamic–biogeochemical models already have numerous benefits in climate change impact studies. Future research should improve these models’ capabilities to reduce limitations and uncertainties, in particular those related to the coupled representation of the physical and biological processes and their feedbacks over long time scales.

Chlorophyll a concentration (Chl) product validation off theWestern Iberian coast is here undertaken by directly comparing remote sensing data with in situ surface reference values. Both standard and recently developed alternative algorithms are considered for match-up data analysis. The investigated standard products are those produced by the MERIS (algal 1 and algal 2) and MODIS (OC3M) algorithms. The alternative data products include those generatedwithin the CoastColour Project and Ocean Color Climate Change Initiative (OC-CCI) funded by ESA, as well as a neural net model trained with field measurements collected in the Atlantic off Portugal (MLPATLP). Statistical analyses showed that satellite Chl estimates tend to be larger than in situ reference values. The study also revealed that a non-uniform Chl distribution in the water column can be a concurring factor to the documented overestimation tendency when considering larger optical depth match-up stations. Among standard remote sensing products, MODIS OC3M and MERIS algal 2 yield the best agreement with in situ data. The performance of MLPATLP highlights the capability of regional solutions to further improve Chl retrieval by accounting for environmental specificities. Results also demonstrate the relevance of oceanographic regions such as the Nazaré area to evaluate how complex hydrodynamic conditions can influence the quality of Chl products. This studywas performed in the framework of HabSpot FCT Project, PTDC/MAR/100348/2008 and European Space Agency projects DUE CoastColour (ESRIN/AO/1-6141/09/l-EC) and Climate Change Iniciative — Ocean Color (AO-1/6207/09/I-LG). The work has been also partially supported by the European Space Agency within the framework of the MERIS Validation Activities under contract n. 12595/09/I-OL, and sampling activities benefited from European projects HERMES (GOCE-CT-2005-511234) and Hermione (EC contract 226354) support. We would like to thank NASA OBPG for the MODIS data and ESA Project AOPT-2423 for providing MERIS full resolution images. Ana C. Brito was funded by a Portuguese Post-doc grant from FCT (BPD/63017/2009) and by the Investigador FCT Program (IF/00331/2013). Davide D'Alimonte was funded by Investigador FCT Program (IF/00541/2013). info:eu-repo/semantics/publishedVersion

This study is an integrated overview of pigment and microscopic analysis of phytoplankton communities throughout the Mozambican coast. Collected samples revealed notable patterns of phytoplankton occurrence and distribution, with community structure changing between regions and sample depth. Pigment data showed Delagoa Bight, Sofala Bank and Angoche as the most productive regions throughout the sampled area. In general, micro-sized phytoplankton, particularly diatoms, were important contributors to biomass both at surface and sub-surface maximum (SSM) samples, although were almost absent in the northern stations. In contrast, nano- and pico-sized phytoplankton revealed opposing patterns. Picophytoplankton were most abundant at surface, as opposed to nanophytoplankton, which were more abundant at the SSM. Microphytoplankton were associated with cooler southern water masses, while picophytoplankton were related to warmer northern water masses. Nanophytoplankton were found to increase their contribution to biomass with increasing SSM. Microscopy information on the genera and species level revealed the diatoms Chaetoceros spp., Proboscia alata, Pseudo-nitzschia spp., Cylindrotheca closterium and Hemiaulus haukii as the most abundant taxa of the micro-sized phytoplankton. Discosphaera tubifera and Emiliania huxleyi were the most abundant coccolithophores, nano-sized phytoplankton. This was a special study of the “Ecosystem Survey Mozambique 2007” of the EAF Nansen Programme funded by NORAD, IMR (Bergen, Norway) and FAO. We thank Maurício Lipassula from the Eduardo Mondlane University (Mozambique) and also Drs. D. Gove and P. Santana Afonso from the Fisheries Institute of Mozambique (IIP). We also thank the crew and fellow scientists from IIP onboard the R/V “Dr. Fridtjof Nansen” and Nancy Tenenbaum for an English revision of this manuscript. Carolina Sá was funded through a grant by FCT (SFRH/BD/24245/2005) and ESA Due CoastColour. Miguel Costa Leal was funded through the project TRANSMAP (INCO-CT2004-510862) funded by the European Commission, 6th Framework. We are also thankful to two anonymous referees for helpful comments that improved this manuscript. published

In recent years, the global distribution of phytoplankton functional types (PFT) and phytoplankton size classes (PSC) has been determined by remote sensing. Many of these methods rely on interpretation of phytoplankton size or type from pigment data, but independent validation has been difficult due to lack of appropriate in situ data on cell size. This work uses in situ data (photosynthetic pigments concentration and cell abundances) from the north-east Atlantic, along a trophic gradient, sampled from 2005 to 2010, as well as Atlantic Meridional Transect (AMT) data for the same region, to test a previously developed conceptual model, which calculates the fractional contributions of pico-, nano- and micro-plankton to total phytoplankton chlorophyll biomass ( Brewin et al., 2010 ). The application of the model proved to be successful, as shown by low mean absolute error between data and model fit. However, regional values obtained for the model parameters had some effect on the relative distribution of size classes as a function of chlorophyll-a, compared with the results according to the original model. The regional parameterisation yielded a dominance of micro-plankton contribution for chlorophyll-a concentrations greater than 0.5 mg m − 3 , rather than from 1.3 mg m − 3 in the original model. Intracellular chlorophyll-a (Chla) per cell, for each size class, was computed from the cell enumeration results (microscope counts and flow cytometry) and the chlorophyll-a concentration for that size class given by the model. The median intracellular chlorophyll-a values computed were 0.004, 0.224 and 26.78 pg Chla cell − 1 for pico-, nano-, and micro-plankton respectively. This is generally consistent with the literature, thereby providing an indirect validation of the method based on pigments to assign size classes. Using a satellite-derived composite image of chlorophyll-a for the study area, a map of cell abundance was generated based on the computed intracellular chlorophyll-a for each size-class, thus extending the remote-sensing method for mapping size classes of phytoplankton from chlorophyll-a concentration to mapping cell numbers in each class. The map reveals the ubiquitous presence of pico-plankton, and shows that all size classes are more abundant in more productive areas.

The Water Framework Directive (WFD) requires the assessment of ecological quality of water bodies based on physico-chemical and biological elements. This paper is focused on the use of phytoplankton as a biological indicator of ecological quality in Portuguese transitional waters (TWs). Phytoplankton is considered to be a sensitive indicator to environmental changes, especially nutrient enrichment, and is therefore useful for evaluating eutrophication processes. According to the WFD, three metrics should be generally considered to assess ecological status: phytoplankton biomass (chlorophyll a), phytoplankton composition and abundance, and phytoplankton bloom intensity and frequency. This work presents an integrated methodology that comprises the first and the last metrics indicated above, analyzed during the growing season (February–October). Significant (p

The composition and distribution of phytoplankton assemblages around the tip of the Antarctic Peninsula were studied during two summer cruises (February/March 2008 and 2009). Water samples were collected for HPLC/CHEMTAX pigment and microscopic analysis. A great spatial variability in chlorophyll a (Chl a) was observed in the study area: highest levels in the vicinity of the James Ross Island (exceeding 7 mg m−3 in 2009), intermediate values (0.5 to 2 mg m−3) in the Bransfield Strait, and low concentrations in the Weddell Sea and Drake Passage (below 0.5 mg m−3). Phytoplankton assemblages were generally dominated by diatoms, especially at coastal stations with high Chl a concentration, where diatom contribution was above 90% of total Chl a. Nanoflagellates, such as cryptophytes and/or Phaeocystis antarctica, replaced diatoms in open-ocean areas (e.g., Weddell Sea). Many species of peridinin-lacking autotrophic dinoflagellates (e.g., Gymnodinium spp.) were also important to total Chl a biomass at well-stratified stations of Bransfield Strait. Generally, water column structure was the most important environmental factor determining phytoplankton communities’ biomass and distribution. The HPLC pigment data also allowed the assessment of different physiological responses of phytoplankton to ambient light variation. The present study provides new insights about the dynamics of phytoplankton in an undersampled region of the Southern Ocean highly susceptible to global climate change. published