Search

The French coast of the Eastern English Channel (ECC) is classified as potential eutrophication zone by the Paris and Oslo Convention (OSPAR), and as moderate to poor according to phytoplankton quality element of the Water Framework Directive (WFD). Indeed, the French part of the EEC is regularly affected by Phaeocystis globosa bloom events, which have detrimental effects on the marine ecosystem, economy as well as public health. Since phytoplankton is an important indicator of water quality, the MAREL Carnot oceanographic multi-sensor station was installed in the Eastern English Channel at the Carnot wall in Boulogne sur Mer in 2004 to monitor water quality and phytoplankton in order to complement results from existing more conventional low resolution monitoring programs, with high frequency data (sampling every 20 minutes). The purpose of this paper is to introduce the MAREL Carnot dataset and show how it can be used for several research objectives. MAREL Carnot collects high frequency, multi-parameter observations from surface water, as well as meteorological measurements, and send data almost immediately to an inshore data center. In this paper, we present several physiochemical and biological parameters measured by this station. In addition, we demonstrated, based on previous research activities, that the MAREL Carnot dataset is useful for evaluating environmental or ecological statuses, marine phytoplankton ecology, physical oceanography, turbulence, as well as public policy. Most importantly, we showed its contribution to Marine Strategy Framework Directive (MSFD) and other regional or universal conventions.

This article describes the historical data series produced by the SRN network managed by Ifremer. Since 1992, the SRN (‘Suivi Régional des Nutriments’ in French; Regional Nutrients Monitoring Programme) network has been analysing phytoplankton species and measuring twelve physicochemical parameters at ten different stations distributed along three different transects located in the Eastern English Channel, and the Southern Bight of the North Sea. The SRN collects a maximum of 184 samples per year and detects up to 281 taxa, including harmful algal bloom species (HABs), with a bi-weekly to monthly sampling frequency (depending on the location and the season). The objectives of this monitoring program are to assess the influence of continental inputs on the marine environment, and their implications on possible eutrophication processes. It also aims to estimate the effectiveness of development and management policies in the marine coastal zone. The regular acquisition of data allows the establishment of a long-term monitoring of the evolution of coastal water quality, as well as the observation of the consequences of large-scale alterations and modifications that are more related to regional anthropogenic activities. This paper provides an overview of the main characteristics of SRN data (descriptive statistics and data series main patterns) as well as an analysis of temporal trends using specific numerical tools available as an R package to help make use of such data. Main results of several research projects are also highlighted providing the readers with examples of what is doable with such a data set.

ATLID (ATmospheric LIDar) is the atmospheric backscatter LIDAR (Light Detection and Ranging) on board of the EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) mission, the sixth Earth Explorer Mission of the ESA (European Space Agency) Living Planet Programme [1-5]. ATLID’s purpose is to provide vertical profiles of optically thin cloud and aerosol layers, as well as the altitude of cloud boundaries [6-10]. In order to achieve this objective ATLID emits short duration laser pulses in the UV, at a repetition rate of 51 Hz, while pointing in a near nadir direction along track of the satellite trajectory. The atmospheric backscatter signal is then collected by its 620 mm aperture telescope, filtered through the optics of the instrument focal plane assembly, in order to separate and measure the atmospheric Mie and Rayleigh scattering signals. With the completion of the full instrument assembly in 2019, ATLID has been subjected to an ambient performance test campaign, followed by a successful environmental qualification test campaign, including performance calibration and characterization in thermal vacuum conditions. In this paper the design and operational principle of ATLID is recalled and the major performance test results are presented, addressing the main key receiver and emitter characteristics. Finally, the estimated instrument, in-orbit, flight predictions are presented; these indicate compliance of the ALTID instrument performance against its specification and that it will meet its mission science objectives for the EarthCARE mission, to be launched in 2023.

In the framework of ecological or environmental assessments and management, detection, characterization and forecasting of the dynamics of environmental states are of paramount importance. These states should reflect general patterns of change, recurrent or occasional events, long-lasting or short or extreme events which contribute to explain the structure and the function of the ecosystem. To identify such states, many scientific consortiums promote the implementation of Integrated Observing Systems which generate increasing amount of complex multivariate/multisource/multiscale datasets. Extracting the most relevant ecological information from such complex datasets requires the implementation of Machine Learning-based processing tools. In this context, we proposed a divisive spectral clustering architecture&mdash, the Multi-level Spectral Clustering (M-SC) which is, in this paper, extended with a no-cut criteria. This method is developed to perform detection events for data with a complex shape and high local connexity. While the M-SC method was firstly developed and implemented for a given specific case study, we proposed here to compare our new M-SC method with several existing direct and hierarchical clustering approaches. The clustering performance is assessed from different datasets with hard shapes to segment. Spectral methods are most efficient discovering all spatial patterns. For the segmentation of time series, hierarchical methods better isolated event patterns. The new M-SC algorithm, which combines hierarchical and spectral approaches, give promise results in the segmentation of both spatial UCI databases and marine time series compared to other approaches. The ability of our M-SC method to deal with many kinds of datasets allows a large comparability of results if applies within a broad Integrated Observing Systems. Beyond scientific knowledge improvements, this comparability is crucial for decision-making about environmental management.

The phytoplankton compartment is particularly reactive to changes in nutrient concentration and is used as a quality indicator. Using a simple numerical approach, the response of emblematic harmful taxa from the eastern English Channel and southern North Sea to changes in nutrient inputs was studied. The method is based on a diachronic approach using averaged maxima over sliding periods of six years (1994&ndash, 2018). This gave a final dataset containing pairs of points (number of years) for explained and explanatory variables. The temporal trajectory of the relationship between each pair of variables was then highlighted. Changes were represented as long-term trajectories that allowed a comparison to a reference/average situation. In addition, the relevance of the use of Phaeocystis globosa and the Pseudo-nitzchia complex as eutrophication species indicators was tested. Results showed a significant shift in the 2000s and different trajectories between diatoms and P. globosa abundances in response to changes in Dissolved Inorganic Nitrogen (DIN). The contrasting ecosystems under study reacted differently depending on the initial pressure. While a return to good ecological status does not seem feasible in the short term, it seems that these ecosystems were in an unstable intermediate state requiring continued efforts to reduce nutrient inputs.

[Departement_IRSTEA]Eaux [ADD1_IRSTEA]Systèmes aquatiques soumis à des pressions multiples; International audience; Eutrophication is one of the most common causes of water quality impairment of inland and marine waters. Its best-known manifestations are toxic cyanobacteria blooms in lakes and waterways and proliferations of green macro algae in coastal areas. The term eutrophication is used by both the scientific community and public policy-makers, and therefore has a myriad of definitions. The introduction by the public authorities of regulations to limit eutrophication is a source of tension and debate on the activities identified as contributing or having contributed decisively to these phenomena. Debates on the identification of the driving factors and risk levels of eutrophication, seeking to guide public policies, have led the ministries in charge of the environment and agriculture to ask for a joint scientific appraisal to be conducted on the subject. Four French research institutes were mandated to produce a critical scientific analysis on the latest knowledge of the causes, mechanisms, consequences and predictability of eutrophication phenomena. This paper provides the methodology and the main findings of this two years exercise involving 40 scientific experts.

International audience; Automated pulse shape-recording flow cytometry was applied to address phytoplankton spatial distribution, at high frequency, in stratified and well mixed water masses in the Western and Central English Channel during the summer-fall transition. Cytometric pulse shapes derived from optical features of single cells allowed the characterization of eight phytoplankton groups. Abundance and total red fluorescence (chlorophyll a autofluorescence) per group were used to define six phytoplankton communities. Their distribution revealed high spatial heterogeneity. Abundance presented a longitudinal gradient for six over the eight groups and succession of brutal shifts along the cruise. Maximum values were often located near the Ushant front in the Western English Channel. A latitudinal gradient characterised the Central English Channel waters under the influence of the Seine estuary. Picophytoplankton (Synechococcus-like cells and picoeukaryotes) represented up to 96% of total abundance and half of the total red fluorescence of the communities near the main front and the Bay of Seine, whereas nanoeukaryotes and microphytoplankton, represented only 4% and less than 1% respectively of total abundance. Both nanoeukaryotes and microphytoplankton dominated the total red fluorescence of the communities of the Central English Channel. The study of traits within each group showed a high variability of traits between communities. The comparison between traits showed that they were independent from each other for some groups (size and red fluorescence per cell for PicoHighFLR and Coccolithophore-like cells; orange and red fluorescence for all the groups), whereas they were dependent for other groups (red fluorescence per cell was dependent of size for picophytoplankton, NanoLowFLR, NanoHighFLR, Cryptophyte-like cells and Microphytoplankton). Variance partitioning revealed that the environmental parameters (temperature, salinity and turbidity) accounted less than spatial descriptors (physical and biological processes) in shaping the communities. Hydrological structures (frontal structures, eddies and tidal streams) were responsible for patches of phytoplankton and defined the structure at the sub-mesoscale (1–10 km) in this area.

The link between harmful algal blooms, phytoplankton community dynamics and global environmental change is not well understood. To tackle this challenging question, a new method was used to reveal how phytoplankton communities responded to environmental change with the occurrence of an harmful algae, using the coastal waters of the eastern English Channel as a case study. The great interannual variability in the magnitude and intensity of Phaeocystis spp. blooms, along with diatoms, compared to the ongoing gradual decrease in anthropogenic nutrient concentration and rebalancing of nutrient ratios; suggests that other factors, such as competition for resources, may also play an important role. A realized niche approach was used with the Outlying Mean Index analysis and the dynamics of the species’ realized subniches were estimated using the Within Outlying Mean Indexes calculations under low (L) and high (H) contrasting Phaeocystis spp. abundance. The Within Outlying Mean Indexes allows the decomposition of the realized niche into realized subniches, found within the subset of habitat conditions and constrained by a subset of a biotic factor. The two contrasting scenarios were characterized by significantly different subsets of environmental conditions and diatom species (BV-step analysis), and different seasonality in salinity, turbidity, and nutrients. The subset L environmental conditions were potentially favorable for Phaeocystis spp. but it suffered from competitive exclusion by key diatom species such as Skeletonema spp., Thalassiosira gravida, Thalassionema nitzschioides and the Pseudo-nitzchia seriata complex. Accordingly, these diatoms species occupied 81% of Phaeocystis spp.'s existing fundamental subniche. In contrast, the greater number of diatoms, correlated with the community trend, within subset H exerted a weaker biological constraint and favored Phaeocystis spp. realized subniche expansion. In conclusion, the results strongly suggest that both abiotic and biotic interactions should be considered to understand Phaeocystis spp. blooms with greater consideration of the preceeding diatoms. HABs needs must therefore be studied as part of the total phytoplankton community.

The ATmospheric LIDar (Light Detection and Ranging), ATLID, is part of the payload of the Earth Cloud and Aerosol Explorer (EarthCARE) mission, the sixth Earth Explorer Mission of the European Space Agency (ESA) Living Planet Program. After the successful major step of optical and electrical integration, ATLID has started its performance and functional testing in Toulouse Airbus Defence and Space. The emission part of the instrument has been operated with both TxA (Laser transmitter units) delivered from Leonardo team: as major achievement the main performance of both flight lasers have been tested and confirmed with more than 40mJ UV emission @51Hz with operation via instrument control ACDM flight unit (ATLID control and data management). Tests are parallelized with on one side the EFM test (Electrical Flight Model), and on the other side the OFM tests (Optical flight model). The EFM tests aim at validating the functional and electrical architecture via functional testing on each nominal and redundant path with all the flight electronic units and laser sources. The OFM tests aims validating the receiver alignment from telescope input till fiber detectors, the field of view of the three detection channels and their radiometric performance. OFM vibration tests have been performed and have validated design stability against mechanical loads. End of OFM and EFM tests is planned at summer 2018 and will give go ahead for instrument assembly in its final ATLID PFM configuration with laser cooling system integration. After Ambient performance testing, the environmental test campaign immediately start with EMC, mechanical and thermal vacuum testing.

Since the eighties, several French organizations (Ifremer, CNRS, and marines universities) have joined their forces to operate the first high frequency automated network around France. Now days, 14 Instrumented platforms are in operation along the North Sea, the Atlantic and Mediterranean French coasts. Furthermore, this organization is now largely contributing to the French national Research Infrastructure named "I.R. ILICO".

Marine waters can be highly heterogeneous both on a spatial and temporal scale, yet monitoring programs currently rely primarily on low-resolution methods. This potentially leads to undersampling. This study explores the potential of two high-resolution methods for monitoring phytoplankton dynamics: fast repetition rate fluorometry for information on phytoplankton photosynthesis and productivity and automated scanning flow cytometry for information on phytoplankton abundance and community composition. These methods were tested in combination with an underway Ferrybox system during four cruises on the Dutch North Sea in April, May, June, and August 2017. The high-resolution methods were able to visualize both the spatial and temporal variability of the phytoplankton community in the Dutch North Sea. Spectral cluster analysis was applied to objectively interpret the multitude of parameters and visualize potential spatial patterns. This resulted in the identification of biogeographic regions with distinct phytoplankton communities, which varied per cruise. Our results clearly show that the sampling based on fixed stations does not give a good representation of the spatial patterns, showing the added value of underway high-resolution measurements. To fully exploit the potential of the tested high-resolution measurement setup, methodological constraints need further research. Among these constraints are accounting for the diurnal cycle in photophysiological parameters concurrent to the spatial variation, better predictions of the electron requirement for carbon fixation to estimate gross primary productivity, and the identification of more flow cytometer clusters with informative value. Nevertheless, the richness of additional information provided by high-resolution methods can improve existing low-resolution monitoring programs towards a more precise and ecosystemic ecological assessment of the phytoplankton community and productivity.

International audience; The diversity, toxicity and seasonality of Pseudo-nitzschia sp. were investigated from February to November 2012 in the southern Bight of the North Sea (SBNS) along the French coast. The identification of Pseudo-nitzschia species in this area was addressed for the first time in this study. Our results revealed a low species richness (3 distinct species) in association with moderate (102 pg mL-1) to high (263 pg mL-1) domoic acid (DA) levels in autumn and spring, respectively. Pseudo-nitzschia succession corresponded to the dominance of P. delicatissima in April-May (86% of total diatoms) as a co-occurring species of the Phaeocystis globosa bloom. Following the Phaeocystis bloom (May-September), P. pungens dominated markedly over P. fraudulenta and P. delicatissima and was the only species present in autumn, although at low abundance (-1). The results of this study support the idea that Pseudo-nitzschia seasonality in the SBNS relies principally on temperature and nutrient availability (DIN and silicates), which, in turn, depend on locally fluctuating environmental conditions (rainfalls and winds). This study highlights the potential for the SBNS to be a potential risk area in regard to the possible impacts of DA on marine resources and the DA transfer through marine food webs. This is of particular concern since DA concentration in seawater was not systematically correlated to potentially toxic Pseudo-nitzschia abundance.

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of recurrent data. This method involves two main steps. Firstly, we find the most similar sub-sequence to the sub-sequence before (resp. after) a gap based on the shape-features extraction and Dynamic Time Warping algorithms. Secondly, we fill in the gap by the next (resp. previous) sub-sequence of the most similar one on the signal containing missing values. Experimental results show that our approach performs better than several related methods in case of multivariate time series having low/non-correlations and effective information on each signal.

ESAs Earth Explorer Aeolus was launched in August 2018. Aboard the first spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) was switched on in early September 2018 and demonstrated the capability to provide atmospheric wind profiles globally from particle and molecular backscatter. In doing so, it will contribute to the improvement in numerical weather prediction (NWP) and the understanding of global dynamics. At the same, it is a major step for powerful and frequency stabilized ultraviolet (UV) lasers for space applications. In parallel, ESA and its partners continue the development of this technology by setting up further ground tests based on Aeolus, and preparing the next milestone with ATLID (ATmospheric LIDar) for the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) mission. ATLID is currently fully integrated and getting prepared for its on-ground testing.

International audience; —Marine water quality monitoring and subsequent management require to know when a specific event like harmful algae bloom may occur and which environmental conditions and pressures lead to this event. So, event detection and its dynamic understanding are crucial to adapt strategy. An algorithm is proposed to identify curves mixture and their dynamics features-initiation, duration, peaks and ends of the event. The approach is fully unsupervised, it requires no tuning parameters and is based on Expectation Maximization process to estimate the most robust mixture according to fixed criteria. A complete framework is proposed to deal with a univariate time series with missing data. The approach is applied on Chlorophyll-a series collected weekly since 1989. Chlorophyll-a is a proxy of the phytoplankton biomass. The results are promising according to the phytoplankton composition knowledge, collected at lower frequency, and allowing to discuss about the annual variability of phytoplankton dynamics.

International audience; Missing data are ubiquitous in any domains of applied sciences. Processing datasets containing missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Therefore, the aim of this paper is to build a framework for filling missing values in univariate time series and to perform a comparison of different similarity metrics used for the imputation task. This allows to suggest the most suitable methods for the imputation of marine univariate time series. In the first step, the missing data are completed on various mono-dimensional time series. To fill a missing sub-sequence (gap) in a time series, we first find the most similar sub-sequence to the sub-sequence before (resp. after) this gap according a Dynamic Time Warping (DTW)-cost. Then we complete the gap by the next (resp. previous) sub-sequence of the most similar one. Through experiments results on 5 different datasets we conclude that i) DTW gives the best results when considering the accuracy of imputation values and ii) Adaptive Feature Based DTW (AFBDTW) metric yields very similar shape of imputation values similar to the one of true values.

Extensive use of transfer matrices (TMs) is made in determining the acoustic properties of a duct and in in-duct acoustic propagation models in the automotive industry and for musical acoustics purposes. The experimental apparatuses of classical TM measurement methods feature two measurement heads. Two microphones are flush with the walls of each head. The pressure signals are processed following the transfer function method constructed on an analytical model of acoustic propagation in measurement heads. The present paper aims at presenting a measurement method based on a three-microphone experimental apparatus and on its acoustic calibration through two reference measurements: the three-measurement two-calibration method for measuring the TM (3M2C-TM). Two microphones are flush with the measurement head walls and one is in the cap closing one side of the measured duct. 3M2C-TM proved essential for an accurate measurement of the four TM elements of two different ducts: a cylindrical duct and an expansion chamber.

The application of the new Water Framework Directive (WFD) of the European Union will require a dense and frequent monitoring of chlorophyll-a near the coast. Not counting the transitional water bodies located in the vicinity of estuaries, not less than seventy four coastal water bodies have to be monitored along the coast of the French Atlantic continental shelf and the English Channel. All the available data have to be gathered to implement a comprehensive monitoring scheme. To this purpose, we evaluate the capacity of ocean colour imagery to complete the conventional in situ data set collected in coastal networks. Satellite-derived chlorophyll-a concentration is obtained by the application of a coastal Look-Up-Table to water-leaving radiance of the Sea-viewing Wide Field Instrument Sensor (SeaWiFS) for the 1998-2004 period. Seven years of satellite-derived and in situ chlorophyll-a concentrations are compared at seven representative stations of different water bodies. These comparisons show that the satellite products are reliable in most of the situations studied and throughout the seasons. Then the satellite imagery is used to classify the coastal waters following the eutrophication risk criterion of the WFD. This classification is made according to the percentile-90 of chlorophyll-a calculated during the productive season, from March to October. Despite a lack of sensor coverage over a small fraction of the near shore waters, this work shows that the satellite monitoring can considerably ease the application of the WFD. (C) 2008 Elsevier Inc. All Fights reserved.

Les performances nordiques – notamment danoises – en matière d’emploi mais aussi de taux de pauvreté ou d’inégalités suscitent depuis plusieurs années l’intérêt des chercheurs et des responsables politiques français. Elles sont souvent rapportées à la « flexicurité », au moins pour ce qui concerne le Danemark, et mises en relation avec l’un des composants de celle-ci, la flexibilité du marché du travail, parfois réduite à la seule faiblesse de la protection de l’emploi. Cet article cherche notamment à prendre la mesure de la flexibilité du marché du travail danoise et à la qualifier, ainsi qu’à la situer parmi d’autres formes de flexibilité et parmi les autres éléments constitutifs du « triangle d’or » danois (l’indemnisation généreuse du chômage et les politiques actives d’emploi). Il cherche aussi à voir si c’est cette même configuration qui permet de comprendre les bons résultats des autres pays nordiques. Après avoir explicité le rôle de la flexibilité du marché du travail dans les trois pays nordiques, les auteurs montrent les traits communs que présentent les politiques nordiques de sécurisation des trajectoires et formulent l’hypothèse que l’investissement social systématique des pays nordiques dans le capital humain entretient un rapport étroit avec leur réussite en matière d’emploi. The Nordic performances – and specially the Danish success – as regards employment, but also in the field of fighting poverty and inequalities, have developed for several years the interest of the French researchers and political leaders. These results are often considered as a product of “flexicurity”, at least concerning Denmark, and attributed only to one of its component, the flexibility of the labour market, sometimes limited to a low level of employment protection. This article tries to appreciate the flexibility of the Danish labour market, to define it and to position it among other forms of flexibility and other components of the “Danish golden triangle” (the generous compensation for unemployment and active employment policies). The authors also try to assess if this specific configuration makes it possible to understand the good results of other Nordic countries. After having clarified the role of the flexibility of the labour market in three Nordic countries, they identify the common features of the Nordic active employment policies to support the individual along his/her working life. They formulate the assumption that the systematic social investment of the Nordic countries in human capital is closely related to their success as regards employment.

The ATmospheric LIDAR ATLID[1] is part of the payload of the Earth Cloud and Aerosol Explorer[2] (EarthCARE) satellite mission, the sixth Earth Explorer Mission of the European Space Agency (ESA) Living Planet Programme. EarthCARE is a joint collaborative satellite mission conducted between ESA and the National Space Development Agency of Japan (JAXA) that delivers the Cloud Profiling Radar (CPR) instrument. The payload consists of four instruments on the same platform with the common goal to provide a picture of the 3D-dimensional spatial and the temporal structure of the radiative flux field at the top of atmosphere, within the atmosphere and at the Earth’s surface. This paper is presenting an updated status of the development of the ATLID instrument and its subsystem design. The instrument has recently completed its detailed design, and most of its subsystems are already under manufacturing of their Flight Model (FM) parts and running specific qualification activities. Clouds and aerosols are currently one of the biggest uncertainties in our understanding of the atmospheric conditions that drive the climate system. A better modelling of the relationship between clouds, aerosols and radiation is therefore amongst the highest priorities in climate research and weather prediction.

The European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) are co-operating to develop the EarthCARE satellite mission with the fundamental objective of improving the understanding of the processes involving clouds, aerosols and radiation in the Earth's atmosphere. The EarthCARE Multispectral Imager (MSI) is relatively compact for a space borne imager. As a consequence, the immediate point-spread function (PSF) of the instrument will be mainly determined by the diffraction caused by the relatively small optical aperture. In order to still achieve a high contrast image, de-convolution processing is applied to remove the impact of diffraction on the PSF. A Lucy-Richardson algorithm has been chosen for this purpose. This paper will describe the system setup and the necessary data pre-processing and post-processing steps applied in order to compare the end-to-end image quality with the L1b performance required by the science community.

International audience; Phytoplankton observation in the ocean can be a challenge in oceanography. Accurate estimations of its biomass and dynamics will help to understand ocean ecosystems and refine global climate models. Relevant data sets of phytoplankton defined at a functional level and on a sub-meso-and daily scale are thus required. In order to achieve this, an automated, high-frequency, dedicated scanning flow cytometer (SFC, Cytobuoy b.v., the Netherlands) has been developed to cover the entire size range of phytoplankton cells whilst simultaneously taking pictures of the largest of them. This cytometer was directly connected to the water inlet of a PocketFerryBox during a cruise in the North Sea, 08–12 May 2011 (DYMAPHY project, INTERREG IV A " 2 Seas "), in order to identify the phytoplankton community structure of near surface waters (6 m) with a high spatial resolution basis (2.2 ± 1.8 km). Ten groups of cells, distinguished on the basis of their optical pulse shapes, were described (abundance, size estimate, red fluorescence per unit volume). Abundances varied depending on the hydrological status of the traversed waters, reflecting different stages of the North Sea blooming period. Comparisons between several techniques analysing chlorophyll a and the scanning flow cytometer, using the integrated red fluorescence emitted by each counted cell, showed significant correlations. For the first time, the community structure observed from the automated flow cytometry data set was compared with PHYSAT reflectance anomalies over a daily scale. The number of matchups observed between the SFC automated high-frequency in situ sampling and remote sensing was found to be more than 2 times better than when using traditional water sampling strategies. Significant differences in the phyto-plankton community structure within the 2 days for which matchups were available suggest that it is possible to label PHYSAT anomalies using automated flow cytometry to resolve not only dominant groups but also community structure .

International audience; Phytoplankton is an important indicator of water quality assessment. To understand phytoplankton dynamics, many fixed buoys and ferry boxes were implemented, resulting in the generation of substantial data signals. Collected data are used as inputs of an effective monitoring system. The system, based on unsupervised Hidden Markov Model (HMM), is designed not only to detect phytoplancton blooms but also to understand their dynamics. HMM parameters are usually estimated by an iterative Expectation-Maximisation approach. We propose to estimate HMM parameters by using spectral clustering algorithm. The monitoring system is assessed on database signals from MAREL-Carnot station (Boulogne-sur-Mer, France). Experiment results show that the proposed system is efficient to detect environmental states such as phytoplankton productive and non productive periods without a priori knowledge. Furthermore, discovered states are consistent with biological interpretation.

Phytoplankton observation in the ocean can be a challenge in oceanography. Accurate estimations of their biomass and dynamics will help to understand ocean ecosystems and refine global climate models. This requires relevant datasets of phytoplankton at a functional level and on a daily and sub meso scale. In order to achieve this, an automated, high frequency, dedicated scanning flow cytometer (SFC, Cytobuoy, NL), has been developed to cover the entire size range of phytoplankton cells whilst simultaneously taking pictures of the largest of them. This cytometer was directly connected to the water inlet of a~pocket Ferry Box during a cruise in the North Sea, 8–12 May 2011 (DYMAPHY project, INTERREG IV A "2 Seas"), in order to identify the phytoplankton community structure of near surface waters (6 m) with a high resolution spacial basis (2.2 ± 1.8 km). Ten groups of cells, distinguished on the basis of their optical pulse shapes, were described (abundance, size estimate, red fluorescence per unit volume). Abundances varied depending on the hydrological status of the traversed waters, reflecting different stages of the North Sea blooming period. Comparisons between several techniques analyzing chlorophyll a and the scanning flow cytometer, using the integrated red fluorescence emitted by each counted cell, showed significant correlations. The community structure observed from the automated flow cytometry was compared with the PHYSAT reflectance anomalies over a daily scale. The number of matchups observed between the SFC automated high frequency in situ sampling and the remote sensing was found to be two to three times better than when using traditional water sampling strategies. Significant differences in the phytoplankton community structure within the two days for which matchups were available, suggest that it is possible to label PHYSAT anomalies not only with dominant groups, but at the level of the community structure.

Long-term trends in the phytoplankton community along the French coast of the English Channel and southern Bight of the North Sea were studied and related to physico-chemical factors and large-climatic indices. Phytoplankton and hydrological data were acquired through three transects. Sampling took place between 1992 and 2011 as part of the French Phytoplankton Monitoring Network (REPHY) and the Regional Nutrients Monitoring Network (SRN). Trends in time-series were identified with dynamic linear models tailored to environmental monitoring data characteristics (e.g. irregular sampling frequency, missing data). Temporal and spatial patterns in the phytoplankton community were explained with a partial triadic analysis. Relationships between the phytoplankton community composition, environmental factors, and climatic indices were assessed using a redundancy analysis (RDA). The analyses revealed long-term changes in the community composition, characterized by a temporal structure that remained common to all transects. The abundance of some groups of taxa such as the one composed by Gymnodinium and Gyrodinium, as well as the group of Pseudo-nitzschia increased during the study period, whereas the abundance of other taxa as for example Guinardia and the group of Coscinodiscus and Stellarima globally decreased. More generally, the proportion of dinoflagellates relative to diatoms increased. Trends in environmental variables were also observed in most sites and related to decreases in nutrient concentrations and an increasing trend in salinity. The RDA indicated that the Atlantic Multidecadal Oscillation index and salinity were the main factors defining the temporal structure of the phytoplankton community. This suggests that variations observed in the phytoplankton community are linked to hydro-climatic changes in the coastal environment.

The aim of the present work is to show an approximation, through an experimental an theoretical study, to quantify the mechanical losses in a turbocharging system. These are linked to the dynamics in the turbo shaft bearings, both axial and radial. Theoretical and experimental methodologies are presented in order to develop a mechanical losses model. The experimental work consists on a measurement campaign in quasi-adiabatic operating conditions, while in the theoretical part, a mathematical model is developed taking into account the radial and axial bearings. The model uses some assumptions in order to solve the Navier-Stokes equations, leading to a simplified model which includes viscosity and the Reynolds number of the oil film formed on the bearings. The proposed model has shown a good agreement with the experimental data, The authors of this paper wish to thank M.A. Ortiz and V. Ucedo for their invaluable work during the experimental setup and campaign, F.J. Arnau, Ph.D, for its excellent job maintaining and expanding Open WAMs code base and M.A. Reyes-Belmonte for all his hard and rigorous work extrapolating turbine maps and preparing and launching the simulations. This work has been partially supported by the Spanish Ministerio de Ciencia e Innovacion through grant number DPI2010-20891-C02-02.

[EN] Nowadays turbocharging the internal combustion engine has become a key point in the reduction on pollutant emissions and the improvement on engine performance. The matching between the turbocharger and the engine is vital due to the highly unsteady flow the turbocharger works with. In the present paper the importance of the heat transfer phenomena inside small automotive turbochargers will be analyzed. This phenomenon will be studied from the point of view of both the turbine and the compressor in one-dimensional modelling. The goodness of the model will be demonstrated predicting turbine and compressor outlet temperatures. An accurate prediction of these parameters will be key designing the intercooler and the after treatment devices. A series of tests in a gas stand with steady and pulsating hot flow in the turbine side will be modeled to show the good agreement in turbocharger enthalpies prediction., This paper is partially supported by the Universitat Politècnica de València PAID-06-11 2034.

For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

This paper presents both a theoretical and an experimental investigation of the influence of the mean flow on the input impedance of a duct. The input impedance of an axisymetrical flow duct is calculated, taking into account the convective effect of a uniform flow, the dissipative effect of a turbulent flow and the radiation in an open jet. Each of these effects is separately studied. An experimental apparatus has been specifically designed to lower flow noise on the transducers, taking advantage of the Two-Microphone-Three-Calibration (TMTC) method [V. Gibiat and F. Laloe, J. Acoust. Soc. Am. 88, 2533-2545 (1990)], whose full calibration process allows any geometry for the measurement head. Theory and experiments are compared for a 1 m long cylindrical duct carrying a flow whose Mach number equals up to 0.15. The resonant frequencies are in close agreement, within 3%. The relative evolution of the magnitude maxima with increasing flow are in good agreement, within 10%. Despite similar tendencies when modifying the mean flow velocity, the amplitude of variation of the magnitude is 2 to 5 times smaller in the experiments.

Lefebvre, A., Guiselin, N., Barbet, F., and Artigas, F. L. 2011. Long-term hydrological and phytoplankton monitoring (1992–2007) of three potentially eutrophic systems in the eastern English Channel and the Southern Bight of the North Sea. – ICES Journal of Marine Science, 68: 2029–2043. The spatial and main temporal variations in nutrient concentrations and phytoplankton abundance were investigated between 1992 and 2007 in the eastern English Channel and the Southern Bight of the North Sea, zones of consistent presence of Phaeocystis globosa and diatom blooms. Silicate and phosphate were the main nutrients potentially limiting phytoplankton growth, but the dynamics of the limitation seemingly differ between sites. Phosphate concentration showed a clear monotonic decreasing trend, whereas dissolved inorganic nitrogen and silicate trends were more complex. Nitrate was rarely or never a limiting factor. Results highlight three main periods with a Phaeocystis- or diatom-dominated system in the 1990s, and a more complex pattern in the 2000s. The composition of the phytoplanktonic community is described and an attempt made to establish a link between the community and its environment in terms of variability, shifts, and trends. The effects of larger- vs. regional-scale controlling factors are also discussed.

This paper is an analysis of the socio-economic situation of two Punjabi villages. It makes an attempt to explain why the villagers of these rural places have to seek work abroad. The first part of the paper deals with the agricultural condi· tions, the non-agricultural activities available to the villagers, and the budgets of different social categories found in the villages. The second part examines the effects of the process of migration on the young people. It particularly discusses the profile of the migrant, the problems faced by him before his departure, the remittances and their utilization, and the impact of emigration upon women's economic role in the villages and upon the traditional social conflicts. The important conclusion of the paper is that these villagers cannot ensure their social, economic, and cultural reproduction.

Wet atmospheric deposition of dissolved N, P and Si species is studied in well-mixed coastal ecosystem to evaluate its potential to stimulate photosynthetic activities in nutrient-depleted conditions. Our results show that, during spring, seawater is greatly depleted in major nutrients: Dissolved Inorganic Nitrogen (DIN), Dissolved Inorganic Phosphorus (DIP) and Silicic acid (Si), in parallel with an increase of phytoplanktonic biomass. In spring (March-May) and summer (June-September), wet atmospheric deposition is the predominant source (> 60%, relative to riverine contribution) for nitrates and ammonium inputs to this N-limited coastal ecosystem. During winter (October-February), riverine inputs of DIN predominate (> 80%) and are annually the most important source of DIP (> 90%). This situation allows us to calculate the possibility for a significant contribution to primary production in May 2003, from atmospheric deposition (total input for DIN approximate to 300 kg km(-2) month(-1)). Based on usual Redfield ratios and assuming that all of the atmospheric-derived N (AD-N) in rainwater is bioavailable for phytoplankton growth, we can estimate new production due to AD-N of 950 mg C m(-2) month(-1), during this period of depletion in the water column. During the same episode (May 2003), photosynthetic activity rate. considered as gross primary production, was estimated to approximately 30300 mg C m(-2) month(-1). Calculation indicates that new photosynthetic activity due to wet atmospheric inputs of nitrogen could be up to 3%. (c) 2006 Elsevier Ltd. All rights reserved.