We have determined the seasonal (July 2001-July 2002 and vertical variability in the photosynthetic production of dissolved organic carbon (DOCp) and particulate organic carbon (POCp) in a coastal upwelling ecosystem (Ría de Vigo, Northwest Spain), together with the relationship between irradiance and DOCp and the time-course of DOCp over 24-h periods. Euphotic layer-integrated rates of DOCp and POCp ranged between 5 and 190 mg C m Ϫ2 h Ϫ1 and between 40 and 1,130 mg C m Ϫ2 h Ϫ1 , respectively. Irradiance was the most important variable affecting the vertical variability of the percentage of extracellular release [PER, defined as DOCp/(DOCp ϩ POCp)]. Whereas POCp decreased markedly below the surface, DOCp remained constant or even increased, thus causing a sharp increase in PER with depth. Biomass-specific rates of DOC production also increased with depth. These observations were confirmed by the results of photosynthesis-irradiance experiments, which consistently showed highest DOCp and PER values at subsaturating irradiances. Our results argue against the view that the release of DOC is an overflow mechanism occurring preferentially under conditions of high irradiance and low nutrient concentration. PER was uncorrelated with the size structure of phytoplankton biomass and productivity, and Ͼ80% of the variability in integrated DOCp was explained by POCp. These findings indicate that the relative importance of dissolved primary production was independent of the dominant type of planktonic trophic organization. Moreover, production of DOC stopped at night, which strongly indicates that trophic processes were not involved in the release of dissolved photosynthate. Our data support a purely physiological mechanism of passive DOC release by normally growing cells, which is enhanced under suboptimal irradiances but proceeds at a similar biomass-specific rate throughout the year. On an integrated basis, PER averaged 19 Ϯ 1%, thus indicating that even in eutrophic waters, total primary productivity can be significantly underestimated if the dissolved products of photosynthesis are not taken into account.

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SUMMARY: The AIMS (Automatic Identification and characterisation of Microbial populationS) project is developing and integrating flow cytometric technology for the identification of microbial cell populations and the determination of their cellular characteristics. This involves applying neural network approaches and molecular probes to the identification of cell populations, and deriving and verifying algorithms for assessing the chemical, optical and morphometric characteristics of these populations. The products of AIMS will be calibrated data, protocols, algorithms and software designed to turn flow cytometric observations into a data matrix of the abundance and cellular characteristics of identifiable populations. This paper describes the general approach of the AIMS project, with details on the application of artificial neural nets and rRNA oligonucleotide probes.

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