Impacts of high-nitrate freshwater inputs on macrotidal ecosystems. I. Seasonal evolution of nutrient limitation for the diatom-dominated phytoplankton of the Bay of Brest (France)

The chemical factors (inorganic nitrogen, phosphate, silicic acid) that potentially or actually control primary production were determined for the Bay of Brest, France, a macrotidal ecosystem submitted to high-nitrate-loaded freshwater inputs (winter nitrate freshwater concentrations >700 mu M, Si:N molar ratio as low as 0.2, i.e. among the lowest ever published). Intensive data collection and observations were carried out from February 1993 to March 1994 to determine the variations of physical [salinity, temperature, photosynthetically active radiation (PAR), freshwater discharges] and chemical (oxygen and nutrients) parameters and their impacts on the phytoplankton cycle (fluorescence, pigments, primary production). With insufficient PAR the winter stocks of nutrients were almost nonutilized and the nitrate excess was exported to the adjacent ocean, due to rapid tidal exchange. By early April, a diatom-dominated spring bloom developed (chlorophyll a maximum = 7.7 mu g l(-1); primary production maximum = 2.34 g C m(-2) d(-1)) under high initial nutrient concentrations. Silicic acid was rapidly exhausted over the whole water column; it is inferred to be the primary limiting factor responsible for the collapse of the spring bloom by mid-May. Successive phytoplankton developments characterized the period of secondary blooms during summer and fall (successive surface chlorophyll a maxima = 3.5, 1.6, 1.8 and 1.0 mu g l(-1); primary production = 1.24, 1.18 and 0.35 g C m(-2) d(-1)). Those secondary blooms developed under lower nutrient concentrations, mostly originating from nutrient recycling. Until August, Si and P most likely limited primary production, whereas the last stage of the productive period in September seemed to be N limited instead, this being a period of total nitrate depletion in almost the whole water column. Si limitation of spring blooms has become a common feature in coastal ecosystems that receive freshwater inputs with Si:N molar ratios <1. The peculiarity of Si Limitation in the Bay of Brest is its extension through the summer period.

Analyse des tendances des séries temporelles de la concentration en azote minéral dissous dans les trois principaux estuaires de la façade Manche-Atlantique

Estuaries are areas which, from their structure, their fonctioning, and their localisation, are subject to significant contribution of nutrients. One of the objectif of the RNO, the French network for coastal water quality monitoring, is to assess the levels and trends of nutrient concentrations in estuaries. A linear model was used in order to describe and to explain the total dissolved nitrogen concentration evolution in the three most important estuaries on the Chanel-Atlantic front (Seine, Loire and Gironde). As a first step, the selection of a reliable data set was performed. Then total dissolved nitrogen evolution schemes in estuary environment were graphically studied, and allowed a resonable choice of covariables. The salinity played a major role in explaining nitrogen concentration variability in estuary, and dilution lines were proved to be a useful tool to detect outlying observations and to model the nitrogenlsalinity relation. Increasing trends were detected by the model, with a high magnitude in Seine, intermediate in Loire, and lower in Gironde. The non linear trend estimated in Loire and Seine estuaries could be due to important interannual variations as suggest in graphics. In the objective of the QUADRIGE database valorisation, a discussion on the statistical model, and on the RNO hydrological data sampling strategy, allowed to formulate suggestions towards a better exploitation of nutrient data.

Explaining dinophysis cf. acuminata abundance in Antifer (Normandy, France) using dynamic linear regression

Classical regression analysis can be used to model time series. However, the assumption that model parameters are constant over time is not necessarily adapted to the data. In phytoplankton ecology, the relevance of time-varying parameter values has been shown using a dynamic linear regression model (DLRM). DLRMs, belonging to the class of Bayesian dynamic models, assume the existence of a non-observable time series of model parameters, which are estimated on-line, i.e. after each observation. The aim of this paper was to show how DLRM results could be used to explain variation of a time series of phytoplankton abundance. We applied DLRM to daily concentrations of Dinophysis cf. acuminata, determined in Antifer harbour (French coast of the English Channel), along with physical and chemical covariates (e.g. wind velocity, nutrient concentrations). A single model was built using 1989 and 1990 data, and then applied separately to each year. Equivalent static regression models were investigated for the purpose of comparison. Results showed that most of the Dinophysis cf. acuminata concentration variability was explained by the configuration of the sampling site, the wind regime and tide residual flow. Moreover, the relationships of these factors with the concentration of the microalga varied with time, a fact that could not be detected with static regression. Application of dynamic models to phytoplankton time series, especially in a monitoring context, is discussed.