Geneviève Lacroix

Atmospheric CO2 flux from mangrove surrounding waters

[1] The partial pressure of CO2 (pCO2) was measured at daily and weekly time scales in the waters surrounding mangrove forests in Papua New Guinea, the Bahamas and India. The pCO2 values range from 380 to 4800 matm. These data, together with previously published data, suggest that overall oversaturation of CO2 with respect to atmospheric equilibriuminsurfacewatersisageneralfeatureofmangrove forests, though the entire ecosystems (sediment, water and vegetation) are probably sinks for atmospheric CO2. The computed CO2 fluxes converge to about +50 mmolC m � 2 day � 1 . If this conservative value is extrapolated for worldwide mangrove ecosystems, the global emission of CO2 to the atmosphere is about 50 10 6 tC year � 1 . Based on this tentative estimate, mangrove waters appear to be regionally a significant source of CO2 to the atmosphere and should be more thoroughly investigated, especially at seasonal time scale. INDEX TERMS: 4806 Oceanography: Biological and Chemical: Carbon cycling; 4805 Oceanography: Biological and Chemical: Biogeochemical cycles (1615); 4820 Oceanography: Biological and Chemical: Gases; 4231 Oceanography: General: Equatorial oceanography; 4235 Oceanography: General: Estuarine processes. Citation: Borges, A. V., S. Djenidi,

Influence of meteorological variability on primary production dynamics in the Ligurian Sea (NW Mediterranean Sea) with a 1D hydrodynamic/biological model

In order to estimate the effects of the meteorological variability on the gross primary production in the Ligurian Sea (NW Mediterranean Sea), a coupling between a hydrodynamic model and a biological one is realized. The one-dimensional version of the GHER hydrodynamic model includes heat and momentum exchanges at the air–sea interface. It is coupled with a simple food-web model from the LEPM. A simulation performed with real meteorological data for the year 1985 reproduces reasonably the seasonal phytoplanktonic dynamics and the distribution between diatoms and flagellates. From this simulation, an annual gross primary production integrated over 200 m of 46.4 g C m−2 year−1 is computed which is representative of an oligotrophic environment. In order to estimate the relative effect on the gross primary production of the meteorological variability on the one hand and of the initial conditions on the other hand, several runs have been performed for the year 1985 with different conditions of light, wind intensity and nitrate initial quantity. The first simulations are performed with daily and monthly mean solar radiation and wind intensity. An averaging of wind intensity yields a decrease in the gross primary production and leads to unrealistic phytoplankton dynamics. It seems then necessary to take into account the 3-hourly variability of the wind intensity in order to simulate the phytoplankton dynamics with relatively good accuracy. On the other hand, an averaging of the solar radiation leads to an increase in the gross primary production. The following simulations are performed with an increase (decrease) in the solar radiation, the wind intensity or the nitrate initial quantity which are representative of the variability observed in a 5-year set of meteorological and hydrobiological data (1984–1988). An increase in the solar radiation is found to reduce the gross primary production, while an increase in the initial nitrate quantity or the wind intensity leads to a higher gross primary production, and the reverse. In the case of variations of the solar radiation (±2%), the simulations give an annual gross primary production integrated over 200 m included between 44.8 and 46.7 g C m−2 year−1, representing a variability of 4%. With the variations of the surface wind intensity (±10%), the runs carry to an annual gross primary production integrated over 200 m from 34.1 to 59.1 g C m−2 year−1, representing a variability of 54%. The variations of the initial nitrate concentration (±50%) lead to an annual gross primary production integrated over 200 m between 20.7 and 69.8 g C m−2 year−1 which represents a variability of 108%. An analysis of the relationship between the total gross primary production and the annual mean depth of the mixed layer has shown that the deeper the mixed layer is, the higher is the total annual gross primary production.

Remotely sensed seasonal dynamics of phytoplankton in the Ligurian Sea in 1997-1999

[1] Remotely sensed data and a one-dimensional hydrophysical model were used to study the seasonal dynamics of surface plant pigments concentration in the Ligurian-Provencal basin. The variations of phytoplankton biomass were estimated from the observations of the Coastal Zone Color Scanner ( 1978 - 1986) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) ( September 1997 to October 1999) radiometers. The factors of physical environment analyzed included remotely sensed sea surface temperature ( from advanced very high resolution radiometers), wind, air temperature, and atmospheric precipitation. The Geohydrodynamics and Environment Research (GHER) model was used to explain the observed correlations between the physical forcing and the response of phytoplankton biomass. The general pattern of phytoplankton seasonal dynamics was typical to subtropical areas: maximum biomass during cold season from October to April and low biomass during summer months. The intensity of winter/spring bloom significantly varied during different years. The correlation was revealed between the summer/autumn air temperature contrast ( expressed as the difference between the air temperatures in August and in November) and the maximum monthly averaged surface chlorophyll concentration during the subsequent winter/spring bloom. The features of seasonal dynamics of phytoplankton are regulated by the physical impacts influencing water stratification. The difference between two seasonal cycles ( from September 1997 to October 1999) illustrates the response of phytoplankton growth to local meteorological conditions. In March - April 1999 the vernal bloom was much more pronounced; it resulted from deeper winter cooling and more intensive winter convection. Heating of surface water layer, wind mixing, and freshwater load with rains and river discharge either stimulate or depress the development of phytoplankton, depending on what limiting environmental factor ( light or nutrient limitation) prevailed.

Study of the oxygen budget of the Black Sea waters using a 3D coupled hydrodynamical-biogeochemical model

Abstract The ventilation of the Black Sea waters by physical and biogeochemical processes is investigated using the Geohydrodynamics and Environment Research (GHER) laboratory 3D coupled hydrodynamical–biogeochemical model. In particular, the penetration at depth of the winter mixing, the generation of unstable motions by frontal instabilities, the exchanges between the north-western shelf and the open sea along the shelf break, the primary production distribution, the generation of detritus and the resulting consumption of oxygen for their recycling are studied. The GHER 3D hydrodynamic model is used to simulate the Black Seas general circulation and the associated synoptic and mesoscale structures. This model is coupled with a simple ecosystem model defined by a nitrogen cycle which is described by seven state variables: nitrate, ammonium, dissolved oxygen, phytoplankton, zooplankton, pelagic and benthic detritus. The model simulates the space–time variations of the biogeochemical state variables. In particular, the spatial variability of the phytoplankton biomass annual cycle, imparted by the horizontal and vertical variations of the physical and chemical properties of the water column, is clearly illustrated. For instance, on the north-western shelf, the seasonal variability of the circulation and in particular, the reversal of the surface current at the end of spring, has a strong influence on the transport of the rich nutrient Danube waters and, thus, on the repartition of the primary production. Furthermore, the results illustrate the seasonal and vertical variations of the dissolved oxygen concentration resulting (a) from its atmospheric and photosynthetic productions in the surface layer, (b) from its loss to the atmosphere in spring and summer and (c) from its consumption associated with the detritus decomposition, the ammonium oxidation during the nitrification process, as well as the oxidation of hydrogen sulfide. The simulated sea surface, phytoplankton fields are compared with satellite estimates of chlorophyll- a fields. Comparisons are made with seasonal mean pictures and snapshot images, illustrating the mesoscale motions of the main coastal current. In the central Black Sea and the Danube delta area, comparisons with available field data are also made. As a general rule, all these comparisons show a quite good qualitative agreement. In particular, at the surface, the simulated phytoplankton space–time distribution is in a good qualitative agreement with satellite observations. However, on a quantitative point of view, the model underestimates the bloom intensity especially in the Danube discharge area.