A consumer’s guide to satellite remote sensing of multiple phytoplankton groups in the global ocean

Phytoplankton are composed of diverse taxonomical groups, which are manifested as distinct morphology, size and pigment composition. These characteristics, modulated by their physiological state, impact their light absorption and scattering, allowing them to be detected with ocean color satellite radiometry. There is a growing volume of literature describing satellite algorithms to retrieve information on phytoplankton composition in the ocean. This synthesis provides a review of current methods and a simplified comparison of approaches. The aim is to provide an easily comprehensible resource for non-algorithm developers, who desire to use these products, thereby raising the level of awareness and use of these products and reducing the boundary of expert knowledge needed to make a pragmatic selection of output products with confidence. The satellite input and output products, their associated validation metrics, as well as assumptions, strengths and limitations of the various algorithm types are described, providing a framework for algorithm organization to assist users and inspire new aspects of algorithm development capable of exploiting the higher spectral, spatial and temporal resolutions from the next generation of ocean color satellites

Standards and practices for reporting plankton and other particle observations from images

This technical manual guides the user through the process of creating a data table for the submission of taxonomic and morphological information for plankton and other particles from images to a repository. Guidance is provided to produce documentation that should accompany the submission of plankton and other particle data to a repository, describes data collection and processing techniques, and outlines the creation of a data file. Field names include scientificName that represents the lowest level taxonomic classification (e.g., genus if not certain of species, family if not certain of genus) and scientificNameID, the unique identifier from a reference database such as the World Register of Marine Species or AlgaeBase. The data table described here includes the field names associatedMedia, scientificName/ scientificNameID for both automated and manual identification, biovolume, area_cross_section, length_representation and width_representation. Additional steps that instruct the user on how to format their data for a submission to the Ocean Biodiversity Information System (OBIS) are also included. Examples of documentation and data files are provided for the user to follow. The documentation requirements and data table format are approved by both NASA’s SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and the National Science Foundation’s Biological and Chemical Oceanography Data Management Office (BCO-DMO).This report was an outcome of a working group supported by the Ocean Carbon and Biogeochemistry (OCB) project office, which is funded by the US National Science Foundation (OCE1558412) and the National Aeronautics and Space Administration (NNX17AB17G). AN, SB, and CP conceived and drafted the document. IC, IST, JF and HS contributed to the main body of the document as well as the example files. All members of the working group contributed to the content of the document, including the conceptualization of the data table and metadata format. We would also like thank the external reviewers Cecile Rousseaux (NASA GSFC), Susanne Menden-Deuer (URI) Frank Muller-Karger (USF), and Abigail Benson (USGS) for their valuable feedback

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives

Estimation du P.A.R. (Photosynthetically active radiation) dans les eaux du cas II par télédétection spatiale

BOULOGNE-BU Droit Lettres (621602101) / SudocSudocFranceF

Remote Sensing of Phytoplankton Size Class in Northwest Atlantic from 1998 to 2016: Bio-Optical Algorithms Comparison and Application

Phytoplankton community structure and phytoplankton size class (PSC) are linked to ecological and biogeochemical changes in the oceanic environment. Many models developed to obtain the fraction of PSCs from satellite remote sensing have only been evaluated in open oceans, and very limited effort has been carried out to report on the performance of these PSC models in productive continental shelf waters. In this study, we evaluated the performance of nine PSC models in the coastal Northwest Atlantic (NWA) by comparison of in situ phytoplankton pigment measurements with coincidental satellite data from the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate-resolution Imaging Spectroradiometer (MODIS), and the Visible Infrared Imaging Radiometer Suite (VIIRS). Our results show that no PSC model retrieved all three phytoplankton size classes (pico-, nano-, and micro-phytoplankton) with reliable accuracy in the region of interest. In particular, these PSC models showed poor performance for retrieval of the picophytoplankton fraction of total phytoplankton in our study region, which could be related to the under-representation of pico-dominated samples in the productive waters of the NWA. For the accuracy of retrieved microphytoplankton and combined nano–pico phytoplankton fraction, the regional model developed by Devred et al. (2011) yielded the best result, followed by the model of Brewin et al. (2011). The model of Devred et al. (2011) was applied to satellite-derived chlorophyll-a concentration from the Ocean Color Climate Change Initiative (OC-CCI) archive in the NWA from 1998 to 2016. We report solely on the microphytoplankton biomass and fraction given the inverse relationship that exists with the nano–pico class. The multi-decadal trend along with the deseasonalized trend of microphytoplankton fraction was computed and analyzed for six biogeochemical provinces located in the NWA. Over the 19-year time series, there were significant, positive trends for four of the six provinces, with a slope of 0.36%·yr−1 in the Northwest Continental Shelf (NWCS), 0.25%·yr−1 in the Arctic Waters (ARCT), 0.12%·yr−1 in the Slope Waters (SW) and 0.06%·yr−1 in the Gulf Stream (GFST). Strong positive anomalies of microphytoplankton fraction were found in winter months in NWCS between 2009 and 2014, which could be associated with changes in environmental factors

Primo-infections à cytomégalovirus soumises au Centre Pluridisciplinaire et le Diagnostic Pré Natal de Grenoble (bilan des pratiques à travers le devenir post-natal des enfants nés entre 1989 et 2004)

Notre étude rétrospective concerne les dossiers du C.P.D.P.N. de Grenoble et évalue les pratiques grenobloises face à une primoinfection CMV chez une femme enceinte à travers le devenir postnatal des enfants nés entre 1989 et 2004. Le dépistage sérologique est pratiqué de façon inégale dans la région grenobloise et ne devrait plus l'être, il augmente de façon significative (p=0.004) le nombre de PLA proposées et pratiquées sans augmenter de façon significative le nombre de foetopathies diagnostiquées. Les PLA pratiquées sur indications sérologiques ont une mauvaise VPN et devraient être remises en cause quand la surveillance échographique est normale. Le dépistage ciblé des séroconversions est quant à lui significativement plus rentable en terme de fœtopathies dépistées ce qui pose la question d'une virulence plus accrue des souches de virus qui pourraient être impliquées dans des formes plus agressives pour la mère et le fœtus. La meilleure prise en charge qui nous semble ressortir de notre étude est la mise en place première d'une surveillance échographique alerte avec discussion d'une éventuelle PLA au cas par cas si apparition de signes échographiques suspects. L'IRM en plein essor n'a pas prouvé ses qualités dans notre étude et se contente de confirmer des signes échographiques déjà présents ou de découvrir des signes mineurs chez des fœtus sains mais demande à être étudiée dans une série plus importante. Elle doit donc être proposée de façon identique pour tous après 32 SA et répétée si besoin. En aucun cas une PLA négative ne doit faire baisser la vigilance des CPDPN et alléger la surveillance car la VPN n'est que de 66% en cas d'imagerie normale.GRENOBLE1-BU Médecine pharm. (385162101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Chlorophyll-a Concentration Retrieval in the Optically Complex Waters of the St. Lawrence Estuary and Gulf Using Principal Component Analysis

Empirical methods based on band ratios to infer chlorophyll-a concentration by satellite do not perform well over the optically complex waters of the St. Lawrence Estuary and Gulf. Using a dataset of 93 match-ups, we explore an alternative method relying on empirical orthogonal functions (EOF) to develop an algorithm that relates the satellite-derived remote sensing reflectances to in situ chlorophyll-a concentration for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Results show that an accuracy of 41% at retrieving chlorophyll-a concentration can be reached using the EOF method compared to 140% for the widely-used Ocean Chlorophyll 4 (OC4v4) empirical algorithm, 53% for the Garver-Siegel-Maritorena (GSM01) and 54% for the Generalized Inherent Optical Property (GIOP) semi-analytical algorithms. This result is possible because the EOF approach is able to extract region-specific radiometric features from the satellite remote sensing reflectances that are related to absorption properties of optical components (water, coloured dissolved organic matter and chlorophyll-a) using the visible SeaWiFS channels. The method could easily be used with other ocean-colour satellite sensors (e.g., MODIS, MERIS, VIIRS, OLCI) to extend the time series for the St. Lawrence Estuary and Gulf waters

Sea-surface dimethylsulfide (DMS) concentration from satellite data at global and regional scales

The marine biogenic gas dimethylsulfide (DMS) modulates climate by enhancing aerosol light scattering and seeding cloud formation. However, the lack of time-and space-resolved estimates of DMS concentration and emission hampers the assessment of its climatic effects. Here we present DMSSAT, a new remote sensing algorithm that relies on macroecological relationships between DMS, its phytoplanktonic precursor dimethylsulfoniopropionate (DMSPt) and plankton light exposure. In the first step, planktonic DMSPt is estimated from satellite-retrieved chlorophyll a and the light penetration regime as described in a previous study (Gali et al., 2015). In the second step, DMS is estimated as a function of DMSPt and photosynthetically available radiation (PAR) at the sea surface with an equation of the form: log(10)DMS = alpha + beta log(10)DMSPt + gamma PAR. The two-step DMSSAT algorithm is computationally light and can be optimized for global and regional scales. Validation at the global scale indicates that DMSSAT has better skill than previous algorithms and reproduces the main climatological features of DMS seasonality across contrasting biomes. The main shortcomings of the global-scale optimized algorithm are related to (i) regional biases in remotely sensed chlorophyll (which cause underestimation of DMS in the Southern Ocean) and (ii) the inability to reproduce high DMS = DMSPt ratios in late summer and fall in specific regions (which suggests the need to account for additional DMS drivers). Our work also highlights the shortcomings of interpolated DMS climatologies, caused by sparse and biased in situ sampling. Time series derived from MODIS-Aqua in the subpolar North Atlantic between 2003 and 2016 show wide interannual variability in the magnitude and timing of the annual DMS peak(s), demonstrating the need to move beyond the classical climatological view. By providing synoptic time series of DMS emission, DMSSAT can leverage atmospheric chemistry and climate models and advance our understanding of plankton-aerosol-cloud interactions in the context of global change