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Collecting hydrological observations over the whole Bay of Biscay continental shelf can require several weeks. As a result, the observations are not truly synoptic and the interpretation of hydrological structures is corrupted by the time-lags between observations at distinct locations. We evaluated the effects of non-synoptic sampling during a spring cruise (17 April to 13 May 2000), using outputs from 3D hydrodynamic models as a substitute for true synoptic sampling. We developed a method for clustering hydrological regions based on the vertical structure of the water column and temporal changes in hydrography. In parallel, outputs from the 3D model were compared with field observations. The results show that in spring 2000 the Bay of Biscay continental shelf could be separated into six principal hydrological regions, one of them being characterised by vertical stability and low temporal variability. This region corresponds to an area where pelagic fish spawning activity is known to be persistently low.

Empirical evidence supports the hypothesis of a general relationship between sea temperature and recruitment of cod stocks across the North Atlantic, as well as between recruitment and the size of the spawning population. In the North Sea, cod year-class strength is inversely related to sea surface temperature during the first half of the year. This stock is currently at a low level, and the future trajectory of the stock biomass will be strongly influenced by recruitment levels. In the present study we investigate the possible use of observed and modelled sea surface temperature (SST) to increase the accuracy and/or time horizon of recruitment forecasts for this stock. We show that the statistical model developed for forecasting spring temperature has good skill (35% skill, with a standard error of 0.36°C) when predictions are made in late January. Within the frame of the current fish stock assessment working group we incorporate SST observations and January forecasts and simulate short-term recruitment projections. The resulting model accounts for a greater fraction of the variance in recruitment (42%) than that obtained without temperature (17%). In operational mode, the model allows forecasting 1.5 years in advance but the accuracy of predicted recruitment remains low. This example indicates that we have not yet reached a point where environmental information can be used with great benefit for the management of North Sea cod. However, a similar strategy may yield greater benefits if developed for other stocks for which environmental effects are better understood and/or account for a larger fraction of the variability in recruitment, for species with a shorter generation time and species for which recruitment forecast is critical to management (e.g. anchovy), and in areas where environmental prediction capabilities may be greater either in accuracy or in lead time.