Regionalization and Dynamic Parameterization of Quantum Yield of Photosynthesis to Improve the Ocean Primary Production Estimates From Remote Sensing

Quantum yield of photosynthesis (ϕ) expresses the efficiency of phytoplankton carbon fixation given certain amount of absorbed light. This photophysiological parameter is key to obtaining reliable estimates of primary production (PPsat) in the ocean based on remote sensing information. Several works have shown that ϕ changes temporally, vertically, and horizontally in the ocean. One of the primary factors ruling its variability is light intensity and thereby, it can be modeled as a function of Photosynthetically Available Radiation (PAR). We estimated ϕ utilizing long time-series collected in the North Subtropical Oligotrophic Gyres, at HOT and BATS stations (Pacific and Atlantic oceans, respectively). Subsequently the maximum quantum yield (ϕm) and Kϕ (PAR value at half ϕm) were calculated. Median ϕm values were ~0.040 and 0.063 mol C mol photons−1 at HOT and BATS, respectively, with higher values in winter. Kϕ values were ~8.0 and 10.8 mol photons m−2 d−1 for HOT and BATS, respectively. Seasonal variability in Kϕ showed its peak in summer. Dynamical parameterizations for both regions are indicated by their temporal behaviors, where ϕm is related to temperature at BATS while Kϕ to PAR, in both stations. At HOT, ϕm was weakly related to temperature and its median annual value was used for the whole data series. Differences in the study areas, even though both belong to Subtropical Gyres, reinforced the demand for regional parameterizations in PPsat models. Such parameterizations were finally included in a PPsat model based on phytoplankton absorption (PPsat−aphy−based), where results showed that the PPsat−aphy−based model coupled with dynamical parameterization improved PPsat estimates. Compared with PPsat estimates from the widely used VGPM, a model based on chlorophyll concentration (PPsat−chl−based), PPsat−aphy−based reduced model-measurement differences from ~62.8 to ~8.3% at HOT, along with well-matched seasonal cycle of PP (R2 = 0.76). There is not significant reduction in model-measurement differences between PPsat−chl−based and PPsat−aphy−based PP at BATS though (37.8 vs. 36.4%), but much better agreement in seasonal cycles with PPsat−aphy−based (R2 increased from 0.34 to 0.71). Our results point to improved estimation of PPsat by parameterized quantum yield along with phytoplankton absorption coefficient at the core

Sentinel-2 remote sensing of Zostera noltei-dominated intertidal seagrass meadows

Accurate habitat mapping methods are urgently required for the monitoring, conservation, and management of blue carbon ecosystems and their associated services. This study focuses on exposed intertidal seagrass meadows, which play a major role in the functioning of nearshore ecosystems. Using Sentinel-2 (S2) data, we demonstrate that satellite remote sensing can be used to map seagrass percent cover (SPC) and leaf biomass (SB), and to characterize its seasonal dynamics. In situ radiometric and biological data were acquired from three intertidal meadows of Zostera noltei along the European Atlantic coast in the summers of 2018 and 2019. This information allowed algorithms to estimate SPC and SB from a vegetation index to be developed and assessed. Importantly, a single SPC algorithm could consistently be used to study Z. noltei-dominated meadows at several sites along the European Atlantic coast. To analyze the seagrass seasonal cycle and to select images corresponding to its maximal development, a two-year S2 dataset was acquired for a French study site in Bourgneuf Bay. The po-tential of S2 to characterize the Z. noltei seasonal cycle was demonstrated for exposed intertidal meadows. The SPC map that best represented seagrass growth annual maximum was validated using in situ measurements, resulting in a root mean square difference of 14%. The SPC and SB maps displayed a patchy distribution, influenced by emersion time, mudflat topology, and seagrass growth pattern. The ability of S2 to measure the surface area of different classes of seagrass cover was investigated, and surface metrics based on seagrass areas with SPC >= 50% and SPC >= 80% were computed to estimate the interannual variation in the areal extent of the meadow. Due to the high spatial resolution (pixel size of 10 m), frequent revisit time (<= 5 days), and long-term objective of the S2 mission, S2-derived seagrass time-series are expected to contribute to current coastal ecosystem management, such as the European Water Framework Directive, but to also guide future adaptation plans to face global change in coastal areas. Finally, recommendations for future intertidal seagrass studies are proposed

Satellite-assisted monitoring of water quality to support the implementation of the Water Framework Directive

The EU Water Framework Directive1 (WFD) is an ambitious legislation framework to achieve good ecological and chemical status for all surface waters and good quantitative and chemical status for groundwater by 2027. A total of 111,062 surface waterbodies are presently reported on under the Directive, 46% of which are actively monitored for ecological status. Of these waterbodies 80% are rivers, 16% are lakes, and 4% are coastal and transitional waters. In the last assessment, 4% (4,442) of waterbodies still had unknown ecological status, while in 23% monitoring did not include in situ water sampling to support ecological status assessment2. For individual (mainly biological) assessment criteria the proportion of waterbodies without observation data is much larger; the full scope of monitoring under the WFD is therefore still far from being realised. At the same time, 60% of surface waters did not achieve ‘good’ status in the second river basin management plan and waterbodies in Europe are considered to be at high risk of having poor water quality based on combined microbial, physical and physicochemical indicators3

Estudo da variabilidade temporal da abundancia fitoplanctônica na região de ressurgência do Cabo Frio, RJ, através de diferentes abordagens e escalas de análises

No ambiente marinho, o fitoplâncton é o principal produtor primário, de forma que dele dependem todos os organismos superiores da teia trófica e, portanto, a sustentabilidade deste ambiente. A abundância fitoplanctônica é controlada por múltiples processos, tanto biológicos, como físicos, químicos e climáticos. As relações entre estes processos são estruturadas no espaço e tempo, e desta forma, cada uma das propriedades pode variar dentro do padrão espaço-temporal, e portanto diferentes padrões surgem a partir de diferentes escalas de pesquisa. Neste trabalho, tanto distintas escalas espaciais quanto temporais, além de diferentes metodologias de abordagem, foram empregadas na análise da biomassa fitoplanctônica, na região de ressurgência do Cabo Frio. Assim, no primeiro capítulo foram analisadas séries temporais de 13 anos de variáveis físicas, químicas e biológicas, coletadas in situ na área de estudo. Estes dados permitiram analisar a variabilidade do fitoplâncton em escalas temporais anuais e inter-anuais, num local espacialmente reduzido. No segundo capítulo, foram desenvolvidos modelos ecológicos visando investigar os fatores envolvidos no comportamento da abundância fitoplanctônica ao longo do ano, em Cabo Frio. No terceiro capítulo, a escala espacial foi ampliada para uma porção maior do litoral do Estado do Rio de Janeiro. Este aumento em escala possibilitou o estudo da influência da ressurgência numa escala geograficamente maior e contextualizar a região do Cabo Frio dentro desta porção da costa brasileira.97 p

Temporal characterization of the diffuse attenuation coefficient in Abrolhos Coral Reef Bank, Brazil

Coral reefs are ecosystems sensitive to high sedimentation rates. Remote sensing provides different products for the monitoring of these environments, as for example, the diffuse attenuation coefficient (Kd490) which can be used as a proxy for water turbidity. Our aim in this work was to characterize the temporal variability of water transparency, here indexed as MODIS-Aqua Kd490 in the Abrolhos Coral Reef Bank (ACRB), which is the largest and richest coral reef area in the South Atlantic Ocean. Daily MODIS-Aqua Level-2 images were obtained between July/2002 and October/2012. Kd490 data was derived from the satellite time-series, and reprojected for the study area. Monthly averages and monthly climatology were calculated in a pixel-by-pixel basis and for two sampling boxes, one in the coast and the other one in the archipelago. Kd490 showed a seasonal variation, with maximum values in austral autumn-winter and minimum in austral spring-summer, as can be seen in monthly Kd490 images and in monthly climatology. Coastal waters showed a smoother climatologic curve, while waters from the archipelago showed a more evident peak in the winter. The 10 year time-series showed a noisier pattern in the coastal area, with some increases and decreases out of phase with the seasonal pattern. Waters of archipelago, on the contrary, showed a clear seasonal pattern along time. Different behavior of both series agrees with the influence of cold fronts which causes resuspension of sediments in the ACRB region and with additional contribution of terrestrial discharges in coastal waters.Pages: 7856-786

Caracterização da pluma de sedimentos do rio Doce (ES) utilizando dados TM – Landsat 5

Sediments inputs, organic matter and dissolved substances carried by rivers are major ocean fertilizers producing a significant impact on coastal adjacent region. The aim of this work was to perform a qualitative characterization of Doce river plume (Espírito Santo), brazilian southeast cost, using orbital data TM Landsat 5 sensor. Doce river regime present high level between November/April and low level between May/October (mean river flow 1296 m3/seg and 525 m3/seg, respectively), following basin rainfall. A set of 9 historic images between 1994-2009 were grouped in high and low river flow. Processing of each image consisted of georeferencing, conversion of digital number for surface reflectance and land and cloud masking. Supervised classification of each image was made considering 4 water types classes: River Plume, Mixed Zone, Other Coastal Waters and Clear Ocean. Areas of each water type were estimated and mean reflectance spectrums were plotted in order to recognize optically active substances (OAS). River Plume and Mixed Zone showed bigger mean areas in dry regime and River Plume was smaller compared to Mixed Zone. However, variability between size areas of such classes was higher when comparing images during low rate cal river regime. In both regimes, reflectance spectrums showed the presence of chlorophyll (phytoplankton) and colored, dissolved, organic substances in River Plume, however at a higher concentration in River Plume than in Mixed Zone. Nonetheless, this analysis did not allow OAS quantification in the River Plume.Pages: 5025-503

Monitoring the marine invasive alien species Rugulopteryx okamurae using unmanned aerial vehicles and satellites

Rugulopteryx okamurae is a species of brown macroalgae belonging to the Dictyotaceae family and native to the north-western Pacific. As an Invasive Alien Species (IAS), it was first detected in the Strait of Gibraltar in 2015. Since then, R. okamurae has been spreading rapidly through the submerged euphotic zone, colonizing from 0 to 50 m depth and generating substantial economic and environmental impacts on the Andalusian coasts (southern Spain). More than 40% of marine IAS in the European Union (EU) are macroalgae, representing one of the main threats to biodiversity and ecosystem functioning in coastal habitats. This study presents a monitoring pilot of beached R. okamurae and fresh R. okamurae down to 5 m depth in Tarifa (Cadiz, Spain), combining multispectral remote sensing data collected by sensors on-board Unmanned Aerial Vehicles (UAVs) and satellites, and how this information can be used to support decision-making and policy. We used an UAV flight carried out at Bolonia beach (Tarifa, Spain) on 1st July 2021 and Sentinel-2 (S2) and Landsat-8 (L8) image acquisitions close to the drone flight date. In situ data were also measured on the same date of the flight, and they were used to train the supervised classification Super Vector Machine (SVM) method based on the spectral information obtained for each substrate cover. The results obtained show how multispectral images allow the detection of beached R. okamurae, and the classification accuracy for water, land vegetation, sand and R. okamurae depending on the image resolution (8.3 cm/pixel for UAV flight, 10 m/pixel for S2 and 30 m/pixel for L8). While the UAV imagery precisely delimited the area occupied by this macroalgae, satellite data were capable of detecting its presence, and able to generate early warnings. This study demonstrates the usefulness of multispectral remote sensing techniques to be incorporated in continuous monitoring programmes of the marine IAS R. okamurae in coastal areas. This information is also key to supporting regional, national and European policies in order to adapt strategic management of invasive marine macrophytes.This study has been funded by the Andalusian Regional Government (project PY20-00244), OAPN-2715/2021 and projects RTI2018-098784-J-I00, IJC2019-039382-I, EQC2018-004275 and EQC2019-00572 funded by MCIN/AEI/10.13039/501100011033 and by ”ERDF A way of making Europe“, and grants FPU20/01294 and FPU19/04557 funded by the Ministry of Universities of the Spanish Government. This research was also supported by the project ”Biodiversity of the Coastal Ocean: Monitoring with Earth Observation“ (BiCOME) funded by the European Space Agency (contract No. 4000135756/21/I-EF) in the frame of the FutureEO-1 BIODIVERSITY+ PRECURSORS call. This work represents a contribution to CSIC Interdisciplinary Thematic Platform (PTI) Teledetección (PTI-TELEDETECT).Peer reviewe

The many shades of red tides: Sentinel-2 optical types of highly-concentrated harmful algal blooms

Harmful algal blooms (HABs) have severe environmental and economic impacts worldwide. Improving HAB detection is crucial because massive blooms are likely to increase in both frequency and amplitude in the next decades due to global warming and escalating coastal eutrophication. While satellite remote sensing has proved useful to detect red tides and support HAB monitoring, the discrimination of the dominant bloom-forming species is still a challenge, all the more as the observation of highly concentrated phytoplankton patches can be hampered by a too coarse spatial resolution. Moreover, the majority of HAB studies generally had a regional focus, and a limited number of species were separately documented so far. Here, we provide a broader perspective for red tides remote sensing to better resolve HAB optical and taxonomical diversity. The main objective of the present study was to identify how many optical bloom types could be recognized with the high spatial resolution Sentinel-2 (S2) satellite mission. For that purpose, an extensive database of massive, nearly monospecific blooms, both documented in situ and using synchronous S2 observation was compiled. More than 100 S2 images of various red tides were selected worldwide. Altogether, the S2 database covered the typical reflectance spectra of 27 red tide forming species. The remote-sensing reflectance of each red tide was analysed to evaluate S2 ability to distinguish the dominant species of the bloom. A hierarchical clustering analysis suggested that six optical bloom types could be identified: (1) surface accumulation of cyanobacteria or of green Noctiluca scintillans, (2) surface accumulation of red N. scintillans (a purely heterotrophic plankton devoid of chlorophyll a), (3) red tides of Mesodinium rubrum (a phycoerythrin-bearing ciliate), (4) green seawater discolorations of Lepidodinium chlorophorum (a dinoflagellate with unusual carotenoids), (5) blooms dominated by a dinoflagellate such as Prorocentrum, Gymnodinium, Lingulodinium polyedra, Gonyaulax or Alexandrium, and (6) brown tides dominated by a dinoflagellate (such as Karenia, Karlodinium veneficum, Protoceratium reticulatum, Margalefidinium polykrikoides, or Tripos fusus), a prymnesiophyte (Phaeocystis), or a pelagophyte (Aureococcus anophagefferens). While the results presented here are inherently limited by the concomitant availability of in situ and S2 observations, as well as by S2 spectral resolution, it is a step forward to an improved understanding of HAB bio-optical diversity

Spatio-temporal dynamics and biogeochemical properties of green seawater discolorations caused by the marine dinoflagellate Lepidodinium chlorophorum along southern Brittany coast

Blooms of the marine dinoflagellate Lepidodinium chlorophorum cause green seawater discolorations affecting the recreational use and the tourism economy along southern Brittany (NE-Atlantic, France). Hypoxic conditions associated with phytoplankton biomass recycling are suspected to cause fauna mortalities. An in situ monitoring was performed in 2019 to characterise the seasonal variability of L. chlorophorum. This species was observed from May to November, with a maximum abundance in June–July. Specific bloom sampling demonstrated a dominance of L. chlorophorum within microphytoplankton, and documented its vertical distribution. Satellite observation was used to compute the surface extent of the bloom and to highlight the importance of small-scale temporal variability, with tidal currents being a primary driver of surface distribution of the bloom. Stratification contributed to promoting the bloom of L. chlorophorum. High concentrations of phosphate and ammonium, together with transparent exopolymer particles (TEP), were recorded within the bloom. Bacterial stimulation, leading to nutrient remineralisation or mucus facilitating mixotrophy, is suggested to sustain bloom development. Hence, TEP production might provide an ecological advantage for the dinoflagellate, conversely causing negative effects on the environment and biological resources through hypoxia. These first insights constitute a baseline for further studies in other ecosystems impacted by this species