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Abstract The Antarctic Peninsula (West Antarctica) marine ecosystem has undergone substantial changes due to climate-induced shifts in atmospheric and oceanic temperatures since the 1950s. Using 25 years of satellite data (1998-2022), this study presents evidence that phytoplankton biomass and bloom phenology in the West Antarctic Peninsula are significantly changing as a response to anthropogenic climate change. Enhanced phytoplankton biomass was observed along the West Antarctic Peninsula, particularly in the early austral autumn, resulting in longer blooms. Long-term sea ice decline was identified as the main driver enabling phytoplankton growth in early spring and autumn, in parallel with a recent intensification of the Southern Annular Mode (2010-ongoing), which was observed to influence regional variability. Our findings contribute to the understanding of the complex interplay between environmental changes and phytoplankton responses in this climatically key region of the Southern Ocean and raise important questions regarding the far-reaching consequences that these ecological changes may have on global carbon sequestration and Antarctic food webs in the future.

Essential Climate Variables (ECVs) like ocean colour provide crucial information on the Optically Active Constituents (OACs) of seawater, such as phytoplankton, non-algal particles, and coloured dissolved organic matter (CDOM). The challenge in estimating these constituents through remote sensing is in accurately distinguishing and quantifying optical and biogeochemical properties, e.g., absorption coefficients and the concentration of chlorophyll a (Chla), especially in complex waters. This study evaluated the temporal and spatial variability of bio-optical properties in the coastal waters of the Western Iberian Coast (WIC), contributing to the assessment of satellite retrievals. In situ data from three oceanographic cruises conducted in 2019–2020 across different seasons were analyzed. Field-measured biogenic light absorption coefficients were compared to satellite estimates from Ocean-Colour Climate Change Initiative (OC-CCI) reflectance data using semi-analytical approaches (QAA, GSM, GIOP). Key findings indicate substantial variability in bio-optical properties across different seasons and regions. New bio-optical coefficients improved satellite data retrieval, reducing uncertainties and providing more reliable phytoplankton absorption estimates. These results highlight the need for region-specific algorithms to accurately capture the unique optical characteristics of coastal waters. Improved comprehension of bio-optical variability and retrieval techniques offers valuable insights for future research and coastal environment monitoring using satellite ocean colour data.

Numerous policies have been proposed by international and supranational institutions, such as the European Union, to surveil Earth from space and furnish indicators of environmental conditions across diverse scenarios. In tandem with these policies, different initiatives, particularly on both sides of the Atlantic, have emerged to provide valuable data for environmental management such as the concept of essential climate variables. However, a key question arises: do the available data align with the monitoring requirements outlined in these policies? In this paper, we concentrate on Earth Observation (EO) optical data applications for environmental monitoring, with a specific emphasis on ocean colour. In a rapidly changing climate, it becomes imperative to consider data requirements for upcoming space missions. We place particular significance on the application of these data when monitoring lakes and marine protected areas (MPAs). These two use cases, albeit very different in nature, underscore the necessity for higher-spatial-resolution imagery to effectively study these vital habitats. Limnological ecosystems, sensitive to ice melting and temperature fluctuations, serve as crucial indicators of a climate in change. Simultaneously, MPAs, although generally small in size, play a crucial role in safeguarding marine biodiversity and supporting sustainable marine resource management. They are increasingly acknowledged as a critical component of global efforts to conserve and manage marine ecosystems, as exemplified by Target 3 of the Kunming–Montreal Global Biodiversity Framework (GBF), which aims to effectively conserve 30% of terrestrial, inland water, coastal, and marine areas by 2030 through protected areas and other conservation measures. In this paper, we analysed different policies concerning EO data and their application to environmental-based monitoring. We also reviewed and analysed the existing relevant literature in order to find gaps that need to be bridged to effectively monitor these habitats in an ecosystem-based approach, making data more accessible, leading to the generation of water quality indicators derived from new high- and very high-resolution satellite monitoring focusing especially on Chlorophyll-a concentrations. Such data are pivotal for comprehending, at small and local scales, how these habitats are responding to climate change and various stressors.

The Atlantic Meridional Transect (AMT) program (www.amt-uk.org) provides the perfect opportunity to observe the phytoplankton community size structure over a long latitudinal transect 50oN to 50oS, thereby covering the most important latitude-related basin-scale environmental gradients of the Atlantic Ocean. This work presents cell abundance data of phytoplankton taxa recently collected during cruises AMT28 and 29 (in 2018 and 2019, respectively) using flow cytometer and microscope observations, as well as the pigment composition of the community, to assess the abundance and spatial distribution of taxonomic groups across the Atlantic. The community size structure showed a clear consistency between cruises at large spatial scale, with a dominance of picoplanktonic Cyanobacteria in oceanic gyres, an increase in all groups in the equatorial upwelling region, and high biomass of microplankton size class at higher latitudes. Phytoplankton carbon biomass for oceanographic provinces, ranged from median values of 10 to 47 mg Carbon m-3, for the oligotrophic gyres, and South Atlantic (45°S-50oS), respectively. Satellite images of total chlorophyll a (as a proxy for phytoplankton biomass) as well as the relative contribution of the three phytoplankton size classes were produced for both cruises, and despite the small number of matchups, statistically agreed well with in situ size classes estimated as carbon biomass, constituting the first attempt in the literature to match satellite size classes with in situ data derived from cell abundance. The comparison of community structure between recent cruises (2019, 2018, 2015) and earlier ones (1995-1998) indicates a decrease in the number of diatom-bloom forming species, and an increase in Dinoflagellates, whereas nitrogen-fixing Trichodesmium abundance in tropical Atlantic remains constant. Within the recent period, a relative increase in the median values of picoplankton fraction was seen in SATL region, counterbalanced by a decrease in both nano- and microplankton fractions. Additionally, this study includes a database of species identified by microscopy, which had been interrupted for 20 years, providing a basis for long-term series of phytoplankton species.

Changes in coccolithophore productivity in response to climate-driven ocean warming are likely to have cascading biogeochemical effects that feed back to the changing climate. This paper investigates the role (and interplay) of large-scale oceanographic and atmospheric processes across the North- and Equatorial Atlantic, including Saharan dust deposition, on the distribution of coccolithophore communities. The study is based on biological and hydrological data collected across the photic zone of the ocean, and aerosol data collected from the lower atmosphere, across 50°N–1°S during the Atlantic Meridional Transect in boreal Autumn of 2018 (AMT28), in synergy with Earth Observations. Results confirm existing understanding of the distribution of coccolithophore communities which are related to major meridional hydrological gradients across the North Atlantic. Dynamic, oxygenated and microphytoplankton-enriched waters at higher-latitudes were characterized by less diverse coccolithophore populations, dominated by placolith-bearing r-selected coccolithophores. In contrast, the heavily stratified and picoplankton-enriched waters of the subtropical gyre revealed more diverse populations, dominated by umbelliform coccolithophores and holococcolithophores at the surface, and by floriform taxa in the lower photic zone. Mean concentrations of 14.4×103 cells/L present in the North Atlantic Tropical Gyre Province (30–12°N), only slightly lower compared to 17.7×103 cells/L produced in the North Atlantic Drift province (50–40°N), provide a snapshot perspective on the importance of coccolithophore production in heavily stratified gyre conditions. Higher concentrations of 19’-Hexanoyloxyfucoxanthin (HexFuco) in regions of enhanced production of r-selected placolith-bearing species suggest that this pigment should not be generalized as a proxy for the entire coccolithophore community. Enhanced abundances of fast-blooming Emiliania huxleyi and Gephyrocapsa oceanica, and of cyanobacteria (including both picoplankton and N2-fixing Trichodesmium spp.) at the surface of the region of more persistent Saharan dust deposition (at ~12-10°N) appeared to result from dust-born nutrient input. Underneath this stratified surface layer, enhanced productivity in the deep chlorophyll maximum (DCM) appeared decoupled from that on the surface, fueled by geostrophic eastward shoaling of the nutricline across the tropical North Atlantic. As this was the region of highest macronutrient concentrations measured along and below the nutricline, our data suggest that the NE tropical Atlantic may act as a permanent dust-born nutrient depocenter as previously hypothesized.

Abstract To establish effective water quality monitoring strategies in estuaries, it is imperative to identify and understand the main drivers for the variation of water quality parameters. The tidal effect is an important factor of the daily and fortnightly variability in several estuaries. However, the extent of that influence on the different physicochemical and biological parameters is still overlooked in some estuarine systems, such as the Sado Estuary, a mesotidal estuary located on the west coast of Portugal. The main objective of this study was to determine how the water quality parameters of the Sado Estuary varied with the fortnightly and the semidiurnal tidal variation. To achieve this goal, sampling campaigns were conducted in May/18, Nov/18 and Jun/19, under neap and spring tidal conditions, with data collection over the tidal cycle. Results were observed to be significantly influenced by the tidal variation, in a large area of the estuary. Flood seemed to mitigate possible effects of nutrient enrichment in the water column. Additionally, significant differences were also observed when considering the different sampling stations. Temperature, Suspended Particulate Matter (SPM) and nutrients showed the highest values at low water. Lastly, the implications of the tidal variability in the evaluation of the water quality according to Water Framework Directive were also discussed, highlighting the importance of studying short-time scale variations and the worst-case scenario to ensure water quality is maintained. These findings are relevant for the implementation of regional management plans and to promote sustainable development.

In mesotidal estuaries, the spatial and temporal variation of physicochemical and biological parameters, and thus water quality, is strongly influenced by tidal dynamics. Hence, to improve monitoring and management strategies, it is imperative to understand how tidal conditions affect water quality parameters and the overall water quality assessments. Multiple indexes and water quality indicators have been used to address water quality issues, monitoring and reporting, mainly in the scope of the Water Framework Directive (WFD). In this work, the tidal effect on nutrients, dissolved oxygen, suspended solids (SPM), Secchi depth, chlorophyll a and phytoplankton composition in a temperate mesotidal estuary was assessed. Moreover, the effect of tidal conditions on the water quality indicators and classification systems was also evaluated. This study was conducted at two stations (Barreiro and Alcântara) located in the Tagus Estuary (Lisbon, Portugal), presenting different anthropogenic pressures. Nutrient concentrations were the variables which yielded the highest differences in response to the tidal conditions, especially at Alcântara, where the influence of a nearby outfall was evident. Therefore, Alcântara also presented stronger classification variability in response to the tidal effect, especially in classifications with less salinity classes. Results indicate that low neap tide is the best tidal condition to assess the worst-case scenario due to the low dilution factor. However, it is important to highlight that all tidal conditions should be sampled to understand the overall condition of water bodies. The classification using mean as a metric (TRIX) was more susceptible to the presence of high nutrient concentrations in general, while the 90th percentile responded better to the presence of several high values in an area with lower nutrient concentrations.

Phytoplankton biomass, through its proxy, Chlorophyll a, has been assessed at synoptic temporal and spatial scales with satellite remote sensing (RS) for over two decades. Also, RS algorithms to monitor relative size classes abundance are widely used; however, differentiating functional types from RS, as well as the assessment of phytoplankton structure, in terms of carbon remains a challenge. Hence, the main motivation of this work it to discuss the links between size classes and phytoplankton groups, in order to foster the capability of assessing phytoplankton community structure and phytoplankton size fractionated carbon budgets. To accomplish our goal, we used data (on nutrients, photosynthetic pigments concentration and cell numbers per taxa) collected in surface samples along a transect on the Atlantic Ocean, during the 25th Atlantic Meridional Transect cruise (AMT25) between 50° N and 50° S, from nutrient-rich high latitudes to the oligotrophic gyres. We compared phytoplankton size classes from two methodological approaches: (i) using the concentration of diagnostic photosynthetic pigments, and assessing the abundance of the three size classes, micro-, nano-, and picoplankton, and (ii) identifying and enumerating phytoplankton taxa by microscopy or by flow cytometry, converting into carbon, and dividing the community into five size classes, according to their cell carbon content. The distribution of phytoplankton community in the different oceanographic regions is presented in terms of size classes, taxonomic groups and functional types, and discussed in relation to the environmental oceanographic conditions. The distribution of seven functional types along the transect showed the dominance of picoautotrophs in the Atlantic gyres and high biomass of diatoms and autotrophic dinoflagellates (ADinos) in higher northern and southern latitudes, where larger cells constituted the major component of the biomass. Total carbon ranged from 65 to 4 mg carbon m–3, at latitudes 45° S and 27° N, respectively. The pigment and cell carbon approaches gave good consistency for picoplankton and microplankton size classes, but nanoplankton size class was overestimated by the pigment-based approach. The limitation of enumerating methods to accurately resolve cells between 5 and 10 μm might be cause of this mismatch, and is highlighted as a knowledge gap. Finally, the three-component model of Brewin et al. was fitted to the Chlorophyll a (Chla) data and, for the first time, to the carbon data, to extract the biomass of three size classes of phytoplankton. The general pattern of the model fitted to the carbon data was in accordance with the fits to Chla data. The ratio of the parameter representing the asymptotic maximum biomass gave reasonable values for Carbon:Chla ratios, with an overall median of 112, but with higher values for picoplankton (170) than for combined pico-nanoplankton (36). The approach may be useful for inferring size-fractionated carbon from Earth Observation.

The Tagus Estuary is one of the largest estuaries in Europe and merges large urban and industrial areas. Understanding phytoplankton community variability is key for an appropriate assessment of the estuarine ecological status. The objective of the present study was to assess the importance of the tidal influence over the phytoplankton community and to evaluate its main drivers of variation. Weekly sampling was performed at two stations on the Tagus Estuary with different anthropogenic pressures (Alcântara and Barreiro). The sampling covered periods with different tidal amplitude. Alcântara presented both the lowest and highest concentrations of dissolved inorganic nitrogen (DIN) and orthophosphate concentration (DIP), depending on the tidal height. Such high variability in this sampling station is probably due to its proximity to a sewage treatment station outfall and to the estuary mouth. In the present study, both seasonal and tidal variations influenced the chlorophyll a concentration of which the tidal cycle explained up to 50% of the chlorophyll a variations. Chlorophyll a displayed a seasonal trend with two peaks of phytoplankton biomass between spring and mid-summer. The main drivers of chlorophyll a variation were radiation, water temperature, tidal amplitude, salinity, river discharge, and the inorganic nutrients DIN and DSi. The estuarine phytoplankton community was mainly dominated by Bacillariophyceae, especially at Alcântara. Bacillariophyceae were less important at Barreiro, where communities had a higher representation from other phytoplankton groups, such as Cryptophyceae and Prasinophyceae. The drivers of variability in the community composition were similar to those influencing the total biomass. In conclusion, the spring-neap tidal cycle strongly influenced the phytoplankton community, both in terms of biomass and community composition. Of the several tidal conditions, spring tides were the tidal condition that presented both higher biomass and higher Bacillariophyceae representativity in the community.

Early detection of dense harmful algal blooms (HABs) is possible using ocean colour remote sensing. Some algorithms require a training dataset, usually constructed from satellite images with a priori knowledge of the existence of the bloom. This approach can be limited if there is a lack of in situ observations, coincident with satellite images. A laboratory experiment collected biological and bio-optical data from a culture of Karenia mikimotoi, a harmful phytoplankton dinoflagellate. These data showed characteristic signals in chlorophyll-specific absorption and backscattering coefficients. The bio-optical data from the culture and a bio-optical model were used to construct a training dataset for an existing statistical classifier. MERIS imagery over the European continental shelf were processed with the classifier using different training datasets. The differences in positive rates of detection of K. mikimotoi between using an algorithm trained with purely manually selected areas on satellite images and using laboratory data as training was overall

The Northern Antarctic Peninsula (NAP), located in West Antarctica, is amongst the most impacted regions by recent warming events. Its vulnerability to climate change has already led to an accumulation of severe changes along its ecosystems. This work reviews the current findings on impacts observed in phytoplankton communities occurring in the NAP, with a focus on its causes, consequences, and the potential research priorities toward an integrated comprehension of the physical–biological coupling and climate perspective. Evident changes in phytoplankton biomass, community composition and size structure, as well as potential bottom-up impacts to the ecosystem are discussed. Surface wind, sea ice and meltwater dynamics, as key drivers of the upper layer structure, are identified as the leading factors shaping phytoplankton. Short- and long-term scenarios are suggested for phytoplankton communities in the NAP, both indicating a future increase of the importance of small flagellates at the expense of diatoms, with potential devastating impacts for the ecosystem. Five main research gaps in the current understanding of the phytoplankton response to climate change in the region are identified: (i) anthropogenic signal has yet to be disentangled from natural climate variability; (ii) the influence of small-scale ocean circulation processes on phytoplankton is poorly understood; (iii) the potential consequences to regional food webs must be clarified; (iv) the magnitude and risk of potential changes in phytoplankton composition is relatively unknown; and (v) a better understanding of phytoplankton physiological responses to changes in the environmental conditions is required. Future research directions, along with specific suggestions on how to follow them, are equally suggested. Overall, while the current knowledge has shed light on the response of phytoplankton to climate change, in order to truly comprehend and predict changes in phytoplankton communities, there must be a robust collaboration effort integrating both Antarctic research programs and the whole scientific community under a common research framework.

Aquaculture has become the fastest-growing sector of the food industry worldwide. The increase of intensive aquaculture practices, however, has been raising global concern about economic and social impacts, but mostly due to the associated potential environmental impacts. The aim of this report is to make a preliminary assessment of the impact of an intensive sea bass aquaculture (Dicentrarchus labrax, L. 1758) on surrounding coastal waters. The aquaculture site is located at the SW Iberian coast (Sines, Portugal), having 16 cages, each holding approximately 150,000 specimens at different stages of growth. We present a spatial and temporal description of environmental physical, chemical, and biological parameters taken in the course of four monitoring campaigns conducted between June 2018 and April 2019. All monitored parameters, except phosphate concentration in October only at one sampling station, showed values within the desirable ranges for marine finfish production and the natural range of Portuguese coastal waters. So far, results do not reveal any detrimental impact of the production units on local water quality, although more research is needed. The preliminary findings suggest that the lack of stress on the receiving waters may be attributed to the hydrodynamic regime in the production area, the feeding strategy, and the dimension of the production.

Diatoms usually dominate microphytobenthic biofilms in coastal and estuarine intertidal environments. Yet, functional studies on biofilms often skip species analysis because benthic diatoms are notoriously difficult to extract from sediments and challenging to identify at that taxonomic level. Valid, less time-consuming alternatives would surely be welcomed and increase the inclusion of community structure information in microphytobenthos (MPB) ecophysiological studies. Starting with an original 181-species abundances matrix (OSM), obtained during a 2-year spatial–temporal survey in a Tagus Estuary intertidal flat with contrasting sediment textures, the current study assessed the effectiveness of several approaches to species abundances analysis. The effect of excluding abundance data or rare species, the influence of taxonomic resolution, or the use of size-based metrics on biotic multivariate patterns was examined by an objective comparison that replicated these different approaches on three different levels: (1) inter-matrix correlations, (2) performance in several non-parametric multivariate analyses (ANOSIM, MDS), and (3) correlations with the environmental dataset. When compared with the OSM, all matrices had strong or very strong positive correlations. All discriminated successfully spatial patterns, separating well assemblages from sandy and muddy sediments, and all had significant correlations with the environmental dataset. Apart from the relative biovolume species matrix (BSM), only the species matrices were able to discriminate significantly temporal patterns. The exclusion of the rarest species (48% of total) had a negligible effect, with the common and original species abundances matrices having a ρ > 0.99 correlation. Of the alternative approaches to species abundances, species presence/absence and the genera abundances matrices yielded the best results overall. Genera presence/absence and the size-class matrices had intermediate performances, with the former performing comparatively poorly with regard to seasonal patterns. BSM had the lowest correlation with the environmental variable dataset (ρ = 0.598) and the worst overall performance in the other multivariate routines. This means that either a high-taxonomic resolution qualitative analysis (i.e. species presence/absence) or, in alternatively, a genus-level analysis retaining abundance data may be sufficient to describe basic spatial differences in estuarine intertidal flats. However, if seasonal variations in mudflat diatom assemblage structure are to be detected, species-level abundance data are still necessary.

Chlorophyll-a (Chl-a) underestimation by global satellite algorithms in the Southern Ocean has long been reported, reducing their accuracy, and limiting the potential for evaluating phytoplankton biomass. As a result, several regional Chl-a algorithms have been proposed. The present work aims at assessing the performance of both global and regional satellite algorithms that are currently available for the Western Antarctic Peninsula (WAP) and investigate which factors are contributing to the underestimation of Chl-a. Our study indicates that a global algorithm, on average, underestimates in-situ Chl-a by ~59%, although underestimation was only observed for waters with Chl-a > 0.5 mg m−3. In high Chl-a waters (>1 mg m−3), Chl-a underestimation rose to nearly 80%. Contrary to previous studies, no clear link was found between Chl-a underestimation and the pigment packaging effect, nor with the phytoplankton community composition and sea ice contamination. Based on multi-sensor satellite data and the most comprehensive in-situ dataset ever collected from the WAP, a new, more accurate satellite Chl-a algorithm is proposed: the OC4-SO. The OC4-SO has great potential to become an important tool not only for the ocean colour community, but also for an effective monitoring of the phytoplankton communities in a climatically sensitive region where in-situ data are scarce.

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided.

Monitoring water quality parameters and their ecological effects in transitional waters is usually performed through in situ sampling programs. These are expensive and time-consuming, and often do not represent the total area of interest. Remote sensing techniques offer enormous advantages by providing cost-effective systematic observations of a large water system. This study evaluates the potential of water quality monitoring using Sentinel-2 observations for the period 2018–2020 for the Sado estuary (Portugal), through an algorithm intercomparison exercise and time-series analysis of different water quality parameters (i.e., colored dissolved organic matter (CDOM), chlorophyll-a (Chl-a), suspended particulate matter (SPM), and turbidity). Results suggest that Sentinel-2 is useful for monitoring these parameters in a highly dynamic system, however, with challenges in retrieving accurate data for some of the variables, such as Chl-a. Spatio-temporal variability results were consistent with historical data, presenting the highest values of CDOM, Chl-a, SPM and turbidity during Spring and Summer. This work is the first study providing annual and seasonal coverage with high spatial resolution (10 m) for the Sado estuary, being a key contribution for the definition of effective monitoring programs. Moreover, the potential of remote sensing methodologies for continuous water quality monitoring in transitional systems under the scope of the European Water Framework Directive is briefly discussed.

Phytoplankton bloom phenology studies are fundamental for the understanding of marine ecosystems. Mismatches between fish spawning and plankton peak biomass will become more frequent with climate change, highlighting the need for thorough phenology studies in coastal areas. This study was the first to assess phytoplankton bloom phenology in the Western Iberian Coast (WIC), a complex coastal region in SW Europe, using a multisensor long-term ocean color remote sensing dataset with daily resolution. Using surface chlorophyll a (chl-a) and biogeophysical datasets, five phenoregions (i.e., areas with coherent phenology patterns) were defined. Oceanic phytoplankton communities were seen to form long, low-biomass spring blooms, mainly influenced by atmospheric phenomena and water column conditions. Blooms in northern waters are more akin to the classical spring bloom, while blooms in southern waters typically initiate in late autumn and terminate in late spring. Coastal phytoplankton are characterized by short, high-biomass, highly heterogeneous blooms, as nutrients, sea surface height, and horizontal water transport are essential in shaping phenology. Wind-driven upwelling and riverine input were major factors influencing bloom phenology in the coastal areas. This work is expected to contribute to the management of the WIC and other upwelling systems, particularly under the threat of climate change.

Understanding the natural variability of coastal ecosystems, and in particular distinguishing between the natural fluctuations and the ones that are caused by anthropogenic interventions and long-term climatic variability, is a major concern for establishing adequate management and adaptation strategies. The Aveiro lagoon, a shallow coastal lagoon (Portugal), holds one of the largest saltmarshes and saltpans in Europe and is a very important ecosystem from both economic and ecological viewpoints, making the protection of its water masses a requirement. To better understand the variability of its ecosystem, the factors controlling seasonal, inter-annual and long-term variability of the water quality in the Aveiro lagoon were thus analyzed. The statistical analysis was based on a set of climatic, hydrological and water quality observations undertaken between 1985 and 2010. Seasonal variations were mostly related with the seasonal variation of the main climatic and hydrological drivers, while long-term shifts were typically driven by the anthropogenic interventions in the lagoon. After the adoption of secondary treatment for industrial effluents on 1992, a recovery from hypoxia conditions occurred in the upstream area of the lagoon. After 2000 lower concentrations of silicates occurred downstream, and may also derive from some anthropogenic modifications (e.g., shunting of river water to the sewage system, deepening of the inlet) that may have affected the physical dynamics. In the downstream area of the lagoon, chlorophyll a presented a downward trend between 1985 and 2010 and lower concentrations after 2000, which were probably associated with the lower concentrations of silicates. Results from the data analysis showed that the seasonal, inter-annual and long-term trends observed in the Aveiro lagoon depend on the influence of both anthropogenic and climate drivers, putting in evidence the need to combine these different drivers when evaluating and developing management strategies for estuarine ecosystems.

Monitoring lakes in high-latitude areas can provide a better understanding of freshwater systems sensitivity and accrete knowledge on climate change impacts. Phytoplankton are sensitive to various conditions: warmer temperatures, earlier ice-melt and changing nutrient sources. While satellite imagery can monitor phytoplankton biomass using chlorophyll a (Chl) as a proxy over large areas, detection of Chl in small lakes is hindered by the low spatial resolution of conventional ocean color satellites. The short time-series of the newest generation of space-borne sensors (e.g., Sentinel-2) is a bottleneck for assessing long-term trends. Although previous studies have evaluated the use of high-resolution sensors for assessing lakes’ Chl, it is still unclear how the spatial and temporal variability of Chl concentration affect the performance of satellite estimates. We discuss the suitability of Landsat (LT) 30 m resolution imagery to assess lakes’ Chl concentrations under varying trophic conditions, across extensive high-latitude areas in Finland. We use in situ data obtained from field campaigns in 19 lakes and generate remote sensing estimates of Chl, taking advantage of the long-time span of the LT-5 and LT-7 archives, from 1984 to 2017. Our results show that linear models based on LT data can explain approximately 50% of the Chl interannual variability. However, we demonstrate that the accuracy of the estimates is dependent on the lake’s trophic state, with models performing in average twice as better in lakes with higher Chl concentration (>20 µg/L) in comparison with less eutrophic lakes. Finally, we demonstrate that linear models based on LT data can achieve high accuracy (R2 = 0.9; p-value < 0.05) in determining lakes’ mean Chl concentration, allowing the mapping of the trophic state of lakes across large regions. Given the long time-series and high spatial resolution, LT-based estimates of Chl provide a tool for assessing the impacts of environmental change.

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

The accuracy of three satellite models of primary production (PP) of varying complexity was assessed against 95 in situ 14C uptake measurements from the North East Atlantic Ocean (NEA). The models were run using the European Space Agency (ESA), Ocean Colour Climate Change Initiative (OC-CCI) version 3.0 data. The objectives of the study were to determine which is the most accurate PP model for the region in different provinces and seasons, what is the accuracy of the models using both high (daily) and low (weekly) temporal resolution OC-CCI data, and whether the performance of the models is improved by implementing a photoinhibition function? The Platt-Sathyendranath primary production model (PPPSM) was the most accurate over all NEA provinces and, specifically, in the Atlantic Arctic province (ARCT) and North Atlantic Drift (NADR) provinces. The implementation of a photoinhibition function in the PPPSM reduced its accuracy, especially at lower range PP. The Vertical Generalized Production Model-VGPM (PPVGPM) tended to over-estimate PP, especially in summer and in the NADR. The accuracy of PPVGPM improved with the implementation of a photoinhibition function in summer. The absorption model of primary production (PPAph), with and without photoinhibition, was the least accurate model for the NEA. Mapped images of each model showed that the PPVGPM was 150% higher in the NADR compared to PPPSM. In the North Atlantic Subtropical Gyre (NAST) province, PPAph was 355% higher than PPPSM, whereas PPVGPM was 215% higher. A sensitivity analysis indicated that chlorophyll-a (Chl a), or the absorption of phytoplankton, at 443 nm (aph (443)) caused the largest error in the estimation of PP, followed by the photosynthetic rate terms and then the irradiance functions used for each model.