Phytoplankton versus macrophyte contribution to primary production and biogeochemical cycles of a coastal mesotidal system. A modelling approach

This study presents an assessment of the contributions of various primary producers to the global annual production and N/P cycles of a coastal system, namely the Arcachon Bay, by means of a numerical model. This 3D model fully couples hydrodynamic with ecological processes and simulates nitrogen, silicon and phosphorus cycles as well as phytoplankton, macroalgae and seagrasses. Total annual production rates for the different components were calculated for different years (2005, 2007 and 2009) during a time period of drastic reduction in seagrass beds since 2005. The total demand of nitrogen and phosphorus was also calculated and discussed with regards to the riverine inputs. Moreover, this study presents the first estimation of particulate organic carbon export to the adjacent open ocean. The calculated annual net production for the Arcachon Bay (except microphytobenthos, not included in the model) ranges between 22,850 and 35,300 tons of carbon. The main producers are seagrasses in all the years considered with a contribution ranging from 56% to 81% of global production. According to our model, the -30% reduction in seagrass bed surface between 2005 and 2007, led to an approximate 55% reduction in seagrass production, while during the same period of time, macroalgae and phytoplankton enhanced their productions by about +83% and +46% respectively. Nonetheless, the phytoplankton production remains about eightfold higher than the macroalgae production. Our results also highlight the importance of remineralisation inside the Bay, since riverine inputs only fulfill at maximum 73% nitrogen and 13% phosphorus demands during the years 2005, 2007 and 2009. Calculated advection allowed a rough estimate of the organic matter export: about 10% of the total production in the bay was exported, originating mainly from the seagrass compartment, since most of the labile organic matter was remineralised inside the bay.

FluxEngine: A flexible processing system for calculating atmosphere-ocean carbon dioxide gas fluxes and climatologies

The air-sea flux of greenhouse gases (e.g. carbon dioxide, CO2) is a critical part of the climate system and a major factor in the biogeochemical development of the oceans. More accurate and higher resolution calculations of these gas fluxes are required if we are to fully understand and predict our future climate. Satellite Earth observation is able to provide large spatial scale datasets that can be used to study gas fluxes. However, the large storage requirements needed to host such data can restrict its use by the scientific community. Fortunately, the development of cloud-computing can provide a solution. Here we describe an open source air-sea CO2 flux processing toolbox called the ‘FluxEngine’, designed for use on a cloud-computing infrastructure. The toolbox allows users to easily generate global and regional air-sea CO2 flux data from model, in situ and Earth observation data, and its air-sea gas flux calculation is user configurable. Its current installation on the Nephalae cloud allows users to easily exploit more than 8 terabytes of climate-quality Earth observation data for the derivation of gas fluxes. The resultant NetCDF data output files contain >20 data layers containing the various stages of the flux calculation along with process indicator layers to aid interpretation of the data. This paper describes the toolbox design, the verification of the air-sea CO2 flux calculations, demonstrates the use of the tools for studying global and shelf-sea air-sea fluxes and describes future developments.

How essential are Argo observations to constrain a global ocean data assimilation system?

Observing system experiments (OSEs) are carried out over a 1-year period to quantify the impact of Argo observations on the Mercator Ocean 0.25° global ocean analysis and forecasting system. The reference simulation assimilates sea surface temperature (SST), SSALTO/DUACS (Segment Sol multi-missions dALTimetrie, d'orbitographie et de localisation précise/Data unification and Altimeter combination system) altimeter data and Argo and other in situ observations from the Coriolis data center. Two other simulations are carried out where all Argo and half of the Argo data are withheld. Assimilating Argo observations has a significant impact on analyzed and forecast temperature and salinity fields at different depths. Without Argo data assimilation, large errors occur in analyzed fields as estimated from the differences when compared with in situ observations. For example, in the 0–300 m layer RMS (root mean square) differences between analyzed fields and observations reach 0.25 psu and 1.25 °C in the western boundary currents and 0.1 psu and 0.75 °C in the open ocean. The impact of the Argo data in reducing observation–model forecast differences is also significant from the surface down to a depth of 2000 m. Differences between in situ observations and forecast fields are thus reduced by 20 % in the upper layers and by up to 40 % at a depth of 2000 m when Argo data are assimilated. At depth, the most impacted regions in the global ocean are the Mediterranean outflow, the Gulf Stream region and the Labrador Sea. A significant degradation can be observed when only half of the data are assimilated. Therefore, Argo observations matter to constrain the model solution, even for an eddy-permitting model configuration. The impact of the Argo floats' data assimilation on other model variables is briefly assessed: the improvement of the fit to Argo profiles do not lead globally to unphysical corrections on the sea surface temperature and sea surface height. The main conclusion is that the performance of the Mercator Ocean 0.25° global data assimilation system is heavily dependent on the availability of Argo data.

Bacterial community characterization of water and intestine of the shrimp Litopenaeus stylirostris in a biofloc system

Background Biofloc technology (BFT), a rearing method with little or no water exchange, is gaining popularity in aquaculture. In the water column, such systems develop conglomerates of microbes, algae and protozoa, together with detritus and dead organic particles. The intensive microbial community presents in these systems can be used as a pond water quality treatment system, and the microbial protein can serve as a feed additive. The current problem with BFT is the difficulty of controlling its bacterial community composition for both optimal water quality and optimal shrimp health. The main objective of the present study was to investigate microbial diversity of samples obtained from different culture environments (Biofloc technology and clear seawater) as well as from the intestines of shrimp reared in both environments through high-throughput sequencing technology. Results Analyses of the bacterial community identified in water from BFT and “clear seawater” (CW) systems (control) containing the shrimp Litopenaeus stylirostris revealed large differences in the frequency distribution of operational taxonomic units (OTUs). Four out of the five most dominant bacterial communities were different in both culture methods. Bacteria found in great abundance in BFT have two principal characteristics: the need for an organic substrate or nitrogen sources to grow and the capacity to attach to surfaces and co-aggregate. A correlation was found between bacteria groups and physicochemical and biological parameters measured in rearing tanks. Moreover, rearing-water bacterial communities influenced the microbiota of shrimp. Indeed, the biofloc environment modified the shrimp intestine microbiota, as the low level (27 %) of similarity between intestinal bacterial communities from the two treatments. Conclusion This study provides the first information describing the complex biofloc microbial community, which can help to understand the environment-microbiota-host relationship in this rearing system.