Assimilation of SeaWiFS ocean chlorophyll data into a three-dimensional global ocean model

Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll data were assimilated with an established three-dimensional global ocean model. The assimilation improved estimates of chlorophyll relative to a free-run (no assimilation) model. Compared to SeaWiFS, annual bias of the assimilation model was 5.5%, with an uncertainty of 10.1%. The free-run model had a bias of 21.0% and an uncertainty of 65.3%. In situ data were compared to the assimilation model over a 6-year time period from 1998 through 2003, indicating a bias of 0.1%, and an uncertainty of 33.4% for daily coincident, co-located data. SeaWiFS bias was slightly higher at − 1.3% and nearly identical uncertainty at 32.7%. The free-run bias and uncertainty at − 1.4% and 61.8%, respectively, indicated how much the assimilation improved model results. Annual primary production estimates for the 1998–2003 period produced a nearly 50% improvement by the assimilation model over the free-run model as compared to a widely used algorithm using SeaWiFS chlorophyll data. These results suggest the potential of assimilation of satellite ocean chlorophyll data for improving model results.     

Improving the physics of a coupled physical–biogeochemical model of the North Atlantic through data assimilation: Impact on the ecosystem

Several studies on coupled physical–biogeochemical models have shown that major deficiencies in the biogeochemical fields arise from the deficiencies in the physical flow fields. This paper examines the improvement of the physics through data assimilation, and the subsequent impact on the ecosystem response in a coupled model of the North Atlantic. Sea surface temperature and sea surface height data are assimilated with a sequential method based on the SEEK filter adapted to the coupling needs. The model domain covers the Atlantic from 20°S to 70°N at eddy-permitting resolution. The biogeochemical model is a NPZD-DOM model based on the P3ZD formulation. The results of an annual assimilated simulation are compared with an annual free simulation.With assimilation, the representation of the mixed layer depth is significantly improved in mid latitudes, even though the mixed layer depth is generally overestimated compared to the observations. The representation of the mean and variance of the currents is also significantly improved.The nutrient input in the euphotic zone is used to assess the data assimilation impact on the ecosystem. Data assimilation results in a 50% reduction of the input due to vertical mixing in mid-latitudes, and in a four- to six-fold increase of the advective fluxes in mid-latitudes and subtropics. Averaged zonally, the net impact is a threefold increase for the subtropical gyre, and a moderate (20–30%) decrease at mid and high latitudes.Surface chlorophyll concentration increases along the subtropical gyre borders, but little changes are detected at mid and high latitudes. An increase of the primary production appears along the Gulf Stream path, but it represents only 12% on average for mid and high latitudes. In the subtropical gyre centre, primary production is augmented but stays underestimated (20% of observations). These experiments show the benefits of physical data assimilation in coupled physical–biogeochemical applications.     

Improving assimilation of SeaWiFS data by the application of bias correction with a local SEIK filter

Ocean-biogeochemical models show typically significant errors in the representation of chlorophyll concentrations. The model state can be improved by the assimilation of satellite chlorophyll data with algorithms based on the Kalman filter. However, these algorithms do usually not account for the possibility that the model prediction contains systematic errors in the form of model bias. Accounting explicitly for model biases can improve the assimilation performance. To study the effect of bias estimation on the estimation of surface chlorophyll concentrations, chlorophyll data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are assimilated on a daily basis into the NASA Ocean Biogeochemical Model (NOBM). The assimilation is performed by the ensemble-based SEIK filter combined with an online bias correction scheme. The SEIK filter is simplified here by the use of a static error covariance matrix. The performance of the filter algorithm is assessed by comparison with independent in situ data over the 7-year period 1998–2004. The bias correction results in significant improvements of the surface chlorophyll concentrations compared to the assimilation without bias estimation. With bias estimation, the daily surface chlorophyll estimates from the assimilation show about 3.3% lower error than SeaWiFS data. In contrast, the error in the global surface chlorophyll estimate without bias estimation is 10.9% larger than the error of SeaWiFS data.     

A dynamic CSTT model for the effects of added nutrients in Loch Creran, a shallow fjord

Despite a tendency for the complexity of physical–biological models to increase, simple coupled models remain useful for some applications and can provide insights into crucial links between physical and biological processes. This argument is illustrated with an account of a simple 3-box model intended to help assess the capacity of fjords to assimilate nutrients from fish farms. The model, a dynamic version of the UK “Comprehensive Studies Task Team” (CSTT) steady-state model for eutrophication, was applied to Loch Creran (Scottish Western Highlands) and was implemented using Stella 8 and tested using historical data from 1975 (before the installation of a salmon farm) and field data collected in 2003, during the period of operation of the farm. The model's biological state variables are chlorophyll, dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP), and it includes a simple run-off model to convert rainfall into river discharge. The physical processes involved in exchange between the loch and the adjacent waters of the Firth of Lorne were parameterised as a constant daily exchange rate.Between 1975 and 2003, local inputs of nutrient increased but, despite this, there was little apparent increase in nutrient concentrations in the loch, and observed chlorophyll concentrations decreased substantially. Model simulations of chlorophyll and DIN agreed well with observations in 1975, as did DIN simulations in 2003. However, simulated chlorophyll was overestimated in 2003.Some of the agreement between observations and simulations come from the use of observed boundary conditions to force the model. However, even when boundary conditions are subtracted from simulations and observations, the simulations in most cases retain a significant correlation with observations, demonstrating that the model's ‘interior’ processes do add to its ability to replicate conditions in the loch.     

Multivariate assimilation in MERCATOR project: New statistical parameters from forecast error estimation

The new operational prototype of Mercator (french Global Ocean Data Assimilation Experiment contribution) is composed of a North Atlantic primitive equation ocean model OPA (Ocean Parallel Algorithm between 20°S and 70°N, [Madec, G., P. Delecluse, M. Imbard and C. Lévy (1998). OPA8.1 ocean general circulation model reference manuel. Notes du pôle de modélisation IPSL. n°11: 91p]) and of a multivariate and multidata assimilation scheme [De Mey, P. and M. Benkiran (2002). “A multivariate reduced-order optimal interpolation method and its application in Mediterranean basin-scale circulation.” Ocean Forecasting : Conceptual basis and application, Pinardi, N., Springer Verlag.] This system has already given some significant improvements from previous Mercator configurations (M. Benkiran, personal communication). However some biases on ocean state still remain in the tropics where the reduced-order optimal interpolation scheme is suspected to be ill-parameted in the model forecast error. Indeed the guess error covariance matrix is decomposed into an error variance value and a spatio-temporal correlation function which are assumed to have some “good” properties (spatial homogeneity of the correlation function, constant ratio between signal and error variance). This study shows how we can use ensemble methods to validate these assumptions. We can see that the correlation function can reach negative values locally, mostly in regions of high variability contradictory with the homogeneous hypothesis. The reduced space used in the operational configuration is based on the signal seasonal Empirical Orthogonal Functions (EOFs). An empirical relationship between signal and error variance has been set and the correlation function is the same on every dimension of the reduced space. By projection of the estimated guess error variance onto the reduced space, we find a repartition of this quantity quite different to what was set in the system. The error statistics is found to be inhomogeneous compared to hypothesis made in the assimilation scheme. These two new parameters tested separately in the assimilation scheme gives significant improvements of the forecast and analysis results. This is particularly obvious in the tropics. But relationship between signal and error statistics (as assumed in the optimal interpolation) is found to be complex.     

Sequential data assimilation in an upwelling influenced estuary

We have evaluated the impact of assimilating chlorophyll, nitrate, phosphate, silicate and ammonium into a coupled 1D hydrodynamic ecosystem model (GOTM-ERSEM) in an upwelling influenced estuary. The assimilation method chosen is the Ensemble Kalman Filter (EnKF), which has been demonstrated to improve field estimates of key variables (chlorophyll, nutrients) for bulk algal bloom prediction. The 1D model has been set up for a central station inside the Ría de Vigo (Spain). Data from bi-weekly surveys are used to constrain the model. Temperature and salinity profiles are used to ensure the correct representation of the water structure through a relaxation scheme. Chlorophyll extracts and nutrients at three depths are assimilated sequentially during 1 year simulation (1991). The assimilation period includes episodes of active upwelling and downwelling. All five assimilated variables are successfully constrained and represent a large improvement on the reference simulation (without assimilation). Small divergences can be related to poorly resolved physical processes in the model. The assimilation was further evaluated by comparing observed biomass partitioning with model results. Diatoms accounted for the largest biomass update and the largest improvement in terms of percentage of variance explained (R²). This is particularly significant as they represent the 46% of the yearly integrated observed biomass of the planktonic autotrophs. Nonetheless the R² value was low for all phytoplankton groups. Bacteria and nanoflagellates showed an improvement with respect to their yearly Root Mean Square (RMS), while the other functional groups worsen or remained unaffected. Chlorophyll assimilation was responsible for most of the impact on the phytoplankton biomass with small contributions from the silicate. It had minor impact on the updates of nutrients which in turn corrected the state variables related to the detrital pool. In this current setting, combined assimilation of chlorophyll and nutrients is not sufficient to produce a skillful simulation of the phytoplankton succession.     

Remotely-sensed chlorophyll a observations of the northern Red Sea indicate seasonal variability and influence of coastal reefs

The biological dynamics of the open northern Red Sea (21.5°–27.5° N, 33.5°–40° E) have not been studied extensively, due in part to both the inaccessibility of this desert region and political considerations. Remotely-sensed chlorophyll a data therefore provide a framework to investigate the primary patterns of biological activity in this oceanic basin. Monthly chlorophyll a data from the 8-year Sea-viewing Wide Field-of-View sensor (SeaWiFS) mission, and data from the Moderate Resolution Imaging Spectroradiometer (MODIS), were analyzed with the Goddard Earth Sciences Data and Information Services Center (GES DISC) online data analysis system “Giovanni”. The data indicate that despite the normal low chlorophyll a concentrations (0.1–0.2 mg m^− 3) in these oligotrophic waters, there is a characteristic seasonal bloom in March–April in the northernmost open Red Sea (24° to 27.5° N) concurrent with minimum sea surface temperature. The location of the highest chlorophyll concentrations is consistent with a linear box model [Eshel, G., and Naik, N.H., 1997. Climatological coastal jet collision, intermediate water formation, and the general circulation of the Red Sea. J. Phys. Oceanogr. 27(7), 1233–1257.] of Red Sea circulation. Two years in the data set exhibited a different seasonal cycle consisting of a relatively weak northern spring bloom and elevated chlorophyll concentrations to the south (21.5° to 24° N).The data also indicate that large coral reef complexes may be sources of either nutrients or chlorophyll-rich detritus and sediment, enhancing chlorophyll a concentration in waters adjacent to the reefs.     

Biological effects of dilution of Dead Sea brine with seawater: implications for the planning of the Red Sea–Dead Sea “Peace Conduit”

The Dead Sea is a severely disturbed ecosystem. Its water level has been decreasing at a rate of nearly 1 m per year during the last decade due to anthropogenic intervention in its water balance. Since the peace treaty between Israel and Jordan was established in 1994, a proposal for the construction of a water carrier, the “Peace Conduit,” between the Gulf of Aqaba (Red Sea) and the Dead Sea is being investigated. This water carrier is intended to mitigate damaging processes that currently occur in the Dead Sea and its surrounding area. The difference in elevation of about 416 m could be exploited for seawater desalination by reverse osmosis. To examine the possible effects of the mixing of Dead Sea brines with seawater and seawater concentrates on the Dead Sea as an ecosystem, we have set up simulation experiments under field conditions in experimental ponds at Sedom, in which Dead Sea water was diluted with Red Sea water. The main components of the Dead Sea biota are the unicellular green alga Dunaliella and several types of red halophilic Archaea. Phosphate is the limiting inorganic nutrient. Massive Dunaliella blooms developed, accompanied by dense communities of red halophilic Archaea, in some of the experimental ponds, imparting a brown-red coloration to the brines. The extent of biological development depended on the extent of dilution and on phosphate availability. The results of the simulation experiments show that biological phenomena and their impact on the Dead Sea ecosystem should be taken into consideration during the planning of the “Peace Conduit.”     

Ability of a “minimum” microbial food web model to reproduce response patterns observed in mesocosms manipulated with N and P, glucose, and Si

We compared an idealised mathematical model of the lower part of the pelagic food web to experimental data from a mesocosm experiment in which the supplies of mineral nutrients (nitrogen and phosphorous), bioavailable dissolved organic carbon (BDOC, as glucose), and silicate were manipulated. The central hypothesis of the experiment was that bacterial consumption of BDOC depends on whether the growth rate of heterotrophic bacteria is limited by organic-C or by mineral nutrients. In previous work, this hypothesis was examined qualitatively using a conceptual food web model. Here we explore the extent to which a “simplest possible” mathematical version of this conceptual model can reproduce the observed dynamics. The model combines algal–bacterial competition for mineral nutrients (phosphorous) and accounts for alternative limitation of bacterial and diatom growth rates by organic carbon and by silicate, respectively. Due to a slower succession in the diatom–copepod, compared to the flagellate–ciliate link, silicate availability increases the magnitude and extends the duration of phytoplankton blooms induced by mineral nutrient addition. As a result, Si interferes negatively with bacterial consumption of BDOC consumption by increasing and prolonging algal–bacterial competition for mineral nutrients. In order to reproduce the difference in primary production between Si and non-Si amended treatments, we had to assume a carbon overflow mechanism in diatom C-fixation. This model satisfactorily reproduced central features observed in the mesocosm experiment, including the dynamics of glucose consumption, algal, bacterial, and mesozooplankton biomass. While the parameter set chosen allows the model to reproduce the pattern seen in bacterial production, we were not able to find a single set of parameters that simultaneously reproduces both the level and the pattern observed for bacterial production. Profound changes in bacterial morphology and stoichiometry were reported in glucose-amended mesocosms. Our “simplest possible” model with one bacterial population with fixed stoichiometry cannot reproduce this, and we suggest that a more elaborate representation of the bacterial community is required for more accurate reproduction of bacterial production.     

Bayesian statistical data assimilation for ecosystem models using Markov Chain Monte Carlo

This study considers advanced statistical approaches for sequential data assimilation. These are explored in the context of nowcasting and forecasting using nonlinear differential equation based marine ecosystem models assimilating sparse and noisy non-Gaussian multivariate observations. The statistical framework uses a state space model with the goal of estimating the time evolving probability distribution of the ecosystem state. Assimilation of observations relies on stochastic dynamic prediction and Bayesian principles. In this study, a new sequential data assimilation approach is introduced based on Markov Chain Monte Carlo (MCMC). The ecosystem state is represented by an ensemble, or sample, from which distributional properties, or summary statistical measures, can be derived. The Metropolis-Hastings based MCMC approach is compared and contrasted with two other sequential data assimilation approaches: sequential importance resampling, and the (approximate) ensemble Kalman filter (including computational comparisons). A simple illustrative application is provided based on a 0-D nonlinear plankton ecosystem model with multivariate non-Gaussian observations of the ecosystem state from a coastal ocean observatory. The MCMC approach is shown to be straightforward to implement and to effectively characterize the non-Gaussian ecosystem state in both nowcast and forecast experiments. Results are reported which illustrate how non-Gaussian information originates, and how it can be used to characterize ecosystem properties.     

Study of the seasonal cycle of the biogeochemical processes in the Ligurian Sea using a 1D interdisciplinary model

A one-dimensional coupled physical–biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version 1D) developed at the GeoHydrodynamics and Environmental Laboratory (GHER) of the University of Liège. The ecosystem model contains 19 state variables describing the carbon and nitrogen cycles of the pelagic food web. Phytoplankton and zooplankton are both divided in three size-based compartments and the model includes an explicit representation of the microbial loop including bacteria, dissolved organic matter, nano-, and microzooplankton. The internal carbon/nitrogen ratio is assumed variable for phytoplankton and detritus, and constant for zooplankton and bacteria. Silicate is considered as a potential limiting nutrient of phytoplankton's growth. The aggregation model described by Kriest and Evans in (Proc. Ind. Acad. Sci., Earth Planet. Sci. 109 (4) (2000) 453) is used to evaluate the sinking rate of particulate detritus. The model is forced at the air–sea interface by meteorological data coming from the “Côte d'Azur” Meteorological Buoy. The dynamics of atmospheric fluxes in the Mediterranean Sea (DYFAMED) time-series data obtained during the year 2000 are used to calibrate and validate the biological model. The comparison of model results within in situ DYFAMED data shows that although some processes are not represented by the model, such as horizontal and vertical advections, model results are overall in agreement with observations and differences observed can be explained with environmental conditions.     

On the key role of nutrient data to constrain a coupled physical–biogeochemical assimilative model of the North Atlantic Ocean

A sequential assimilative system has been implemented into a coupled physical–biogeochemical model (CPBM) of the North Atlantic basin at eddy-permitting resolution (1/4°), with the long-term goal of estimating the basin scale patterns of the oceanic primary production and their seasonal variability. The assimilation system, which is based on the SEEK filter [Brasseur, P., Verron, J., 2006. The SEEK filter method for data assimilation in oceanography: a synthesis. Ocean Dynamics. doi: 10.1007/s10236-006-0080-3], has been adapted to this CPBM in order to control the physical and biogeochemical components of the coupled model separately or in combination. The assimilated data are the satellite Topex/Poseidon and ERS altimetric data, the AVHRR Sea Surface Temperature observations, and the Levitus climatology for salinity, temperature and nitrate.In the present study, different assimilation experiments are conducted to assess the relative usefulness of the assimilated data to improve the representation of the primary production by the CPBM. Consistently with the results obtained by Berline et al. [Berline, L., Brankart, J-M., Brasseur, P., Ourmières, Y., Verron, J., 2007. Improving the physics of a coupled physical–biogeochemical model of the North Atlantic through data assimilation: impact on the ecosystem. J. Mar. Syst. 64 (1–4), 153–172] with a comparable assimilative model, it is shown that the assimilation of physical data alone can improve the representation of the mixed layer depth, but the impact on the ecosystem is rather weak. In some situations, the physical data assimilation can even worsen the ecosystem response for areas where the prior nutrient distribution is significantly incorrect. However, these experiments also show that the combined assimilation of physical and nutrient data has a positive impact on the phytoplankton patterns by comparison with SeaWiFS ocean colour data, demonstrating the good complementarity between SST, altimetry and in situ nutrient data. These results suggest that more intensive in situ measurements of biogeochemical nutrients are urgently needed at basin scale to initiate a permanent monitoring of oceanic ecosystems.     

A box model approach for a long-term assessment of estuarine eutrophication, Szczecin Lagoon, southern Baltic

We develop a layered “box model” to evaluate the major effects of estuarine eutrophication of the Szczecin lagoon which can be compared with integrating measures (chlorophyll a (Chl a), sediment burial, sediment oxygen consumption (SOC), input and output of total nutrient loads) and use it to hindcast the period 1950–1996 (the years when major increase in nutrient discharges by the Oder River took place). The following state variables are used to describe the cycling of the limiting nutrients (nitrogen and phosphorus): phytoplankton (Phy), labile and refractory detritus (D_N, D_Nref, D_P, D_Pref), dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and oxygen (O₂). The three layers of the model include two water layers and one sediment layer. Decrease of the carrying capacity with respect to the increased supply of organic matter of the system with advancing eutrophication over the period studied is parameterized by an exponential decrease of the sediment nitrogen fluxes with increasing burial, simulating changing properties from moderate to high accumulating sediments. The seasonal variation as well as the order of magnitude of nutrient concentrations and phytoplankton stocks in the water column remains in agreement with recent observations. Calculated annual mean values of nutrient burial of 193 mmol N m⁻² a⁻¹ and 23 mmol P m⁻² a⁻¹ are supported by observed values from geological sediment records. Estimated DIN remineralization in the sediments between 100 and 550 mmol N m⁻² a⁻¹ corresponds to SOC measurements. Simulated DIP release up to 60 mmol P m⁻² a⁻¹ corresponds to recent measurements. The conceptual framework presented here can be used for a sequential box model approach connecting small estuaries like the Szczecin lagoon and the open sea, and might also be connected with river box models.     

Error quantification of a high-resolution coupled hydrodynamic-ecosystem coastal-ocean model: Part 2. Chlorophyll-a, nutrients and SPM

Marine systems models are becoming increasingly complex and sophisticated, but far too little attention has been paid to model errors and the extent to which model outputs actually relate to ecosystem processes. Here we describe the application of summary error statistics to a complex 3D model (POLCOMS-ERSEM) run for the period 1988–1989 in the southern North Sea utilising information from the North Sea Project, which collected a wealth of observational data. We demonstrate that to understand model data misfit and the mechanisms creating errors, we need to use a hierarchy of techniques, including simple correlations, model bias, model efficiency, binary discriminator analysis and the distribution of model errors to assess model errors spatially and temporally. We also demonstrate that a linear cost function is an inappropriate measure of misfit. This analysis indicates that the model has some skill for all variables analysed. A summary plot of model performance indicates that model performance deteriorates as we move through the ecosystem from the physics, to the nutrients and plankton.     

Future aspects in marine ecosystem modelling

Existing ecosystem models are briefly presented and summarised. The problem of coupling physical and biological models as well as aspects of prediction and predictability are discussed. The general perception that marine ecosystems are inherently unpredictable due to non-linearity becomes questionable if the response of climate variability in marine ecosystems is analysed. Many authors have shown correlations between climate variability and the variability of abundance or biomass of marine organisms such as phytoplankton, zooplankton, benthos or fish recruitment in different parts of the world ocean. In the northern hemisphere, certain species show a linear response to climate variability mainly during winter and spring. However, the underlying mechanisms are not well understood. Often, a phase lag can be observed between climate variability and the reaction of organisms. The identification of a plausible mediator between climate and biology is difficult, since all possible physicochemical mechanisms having a direct or indirect influence on the variability of abundance or biomass of marine organisms have to be considered as mediator.The understanding of the reason of the phase lag, which possibly implies a “biological memory”, and the identification of all possible mediators are necessary to predict the response of marine organisms to climate variability. The identification of mediators will result in an improvement of coupled models, a deeper understanding of physical–biological interaction and the improvement of predictive capability of marine ecosystem models.     

Environmental changes in the western Black Sea related to anthropogenic and natural conditions

The Black Sea northwestern shelf (NWS) ecosystem has been subjected to the strongest anthropogenic pressure of the entire Black Sea as about 80% of the freshwater runoff is discharged there.This paper presents a review of the global environmental changes related mainly to increased eutrophication in the western Black Sea basin.A case study (CoMSBlack 92a cruise) attempts to highlight the interaction of some natural and anthropogenic factors responsible for specific chemical and biological features in the western Black Sea environment. The significance of processes located near the Danube river mouth, which, due to their relatively small space scale, have not been recognized before, is clarified. Hydrological processess of specific importance to the distribution and transformation of antropogenic inputs are river plume dynamics, coastal upwelling and mixing and downwelling over the shelf break and slope in this part of the basin. A layer of low hydrological variability (“conservative layer”) appears to be a natural feature of the area, hypothesized to precondition specific biological and chemical processes there.The results suggest that the interplay between the Danube anthropogenic nutrient load with the natural hydrological fronts and gradients provides opportunities for enhanced biological activity thus contributing to the global environmental changes in the Black Sea NWS.     

Topological constraints on the dynamics of wasp-waist ecosystems

Small pelagic fish species like anchovy or sardines are of high ecological and economical importance. As marine food webs are fished down, these small pelagics tend to be more exploited and overfished. It is not yet very well known what the possible effects of their collapse can be, therefore there is an urgent need to outline a theoretical framework for understanding their dynamics. These fish occupy very special position in food webs, ensuring energy transfer between species lower and higher levels, while forming narrow “wasp-waists” poor in number of species (but very abundant). Our purpose was to quantify the interaction structure of model food webs of equal complexity but different levels of “wasp-waistedness”. We analysed the topological properties of the webs by characterising every direct and indirect interactions between individual species, as well as by assessing the relative positional importance of each species in each web. We found that (1) the shorter the interaction pathways considered, the weaker the predictive power of node degree for positional importance, (2) the importance of species varies more in wasp-waist food webs, (3) if longer indirect chain effects are considered, indirect effects can well be stronger than direct ones, (4) interactions between coexisting wasp-waist species are stronger than the average, and (5) the “self-regulatory” looping effects are also stronger for wasp-waist species. Based on the topological properties of the networks, our results describe constraints acting on the dynamical behaviour of wasp-waist ecosystems. We give explanations, from this viewpoint, for regime shifts in which one WW species replaces another, and for the unpredictable dynamics of these fish stocks. From a marine conservation viewpoint, we illustrate that as the abundance of wasp-waist species decreases, the architecture of energy flows becomes highly vulnerable and unreliable. We provide an approach for quantifying these structural changes.     

Effect of mixing on microbial communities in the Rhone River plume

The biological processes involved during mixing of a river plume with the marine underlying water were studied off the Rhone River outlet. Samples of suspended and dissolved matter were collected while tracking a drifting buoy. Three trajectories were performed, at 2-day intervals, under different hydrological and meteorological situations. A biological uptake was evidenced from ammonium (NH₄) and phosphate (PO₄) shortage, indicating an early “NH₄-dependent” functioning occurring before the well-known “NO₃-based” cycle. The different ratios between NH₄, NO₃ and PO₄, as a function of salinity, were discussed to detail the preferential use in PO₄ and NH₄. Salinity zones with enhanced bacterial production, high chlorophyll a concentration, as well as DOC, NH₄ and PO₄ consumption were evidenced from 20 to 35 in salinity. It was shown that the successive abundance of bacteria and phytoplankton during transfer reflected the competition for PO₄ of both communities. On the Rhone River plume, the role played by temperature, light conditions and suspended matter upon biological activity seems relatively minor compared to salinity distribution and its related parameter: nutrient availability. It can be concluded that biological uptake in the Rhone River plume was closely related to the dilution mechanism, controlled itself by the dynamics of the plume. In windless conditions and close to the river mouth, the density gradient between marine and river water induced limited exchanges between the nutrient-rich freshwater and the potential consumers in the underlying marine water. Consequently, little biological activity is observed close to the river mouth. Offshore, mixing is enhanced and a balance is reached between salinity tolerance and nutrient availability to form a favourable zone for marine phytoplankton development. This can be quite far from the river mouth in case of a widely spread plume, corresponding to high river discharge. Under windy and wavy conditions, the plume freshwater is early and rapidly mixed, so that the extension of the “enhanced production zone” is drastically reduced and even bacteria could not benefit from the fast mixing regime induced.     

Seasonality of picophytoplankton chlorophyll a and biomass in the central Cantabrian Sea, southern Bay of Biscay

Seasonal changes in the abundance and biomass of cyanobacteria (Synechococcus and Prochlorococcus) and picoeukaryotes were studied by flow cytometry in the upper layers of the central Cantabrian Sea continental shelf, from April 2002 to April 2006. The study area displayed the typical hydrographic conditions of temperate coastal zones. A marked seasonality of the relative contribution of prokaryotes and eukaryotes was found. While cyanobacteria were generally more abundant for most of the year (up to 2.4 10⁵ cells mL^− 1), picoeukaryotes dominated the community (up to 10⁴ cells mL^− 1) from February to May. The disappearance of Prochlorococcus from spring through summer is likely related to shifts in the prevailing current regime. The maximum total abundance of picophytoplankton was consistently found in late summer–early autumn. Mean photic-layer picoplanktonic chlorophyll a ranged from 0.06 to 0.53 µg L^− 1 with a relatively high mean contribution to total values (33 ± 2% SE), showing maxima around autumn and minima in spring. Biomass (range 0.58–40.16 mg C m^− 3) was generally dominated by picoeukaryotes (mean ± SE, 4.28 ± 0.27 mg C m^− 3) with an average contribution of cyanobacteria of 30 ± 2%. Different seasonality of pigment and biomass values resulted in a clear temporal pattern of picophytoplanktonic carbon to chlorophyll a ratio, which ranged from 10 (winter) to 140 (summer). This study highlights the important contribution of picoplanktonic chlorophyll a and carbon biomass in this coastal ecosystem.