Recently developed techniques for estimating bacterial biomass and productivity indicate that bacterial biomass in the sea is related to phytoplankton concentration and that bacteria utilise 10 to 50 % of carbon fixed by photosynthesis. Evidence is presented to suggest that numbers of free bacteria are controlled by nanoplankton~c heterotrophic flagellates which are ubiquitous in the marine water column. The flagellates in turn are preyed upon by microzooplankton. Heterotrophic flagellates and microzooplankton cover the same size range as the phytoplankton, thus providing the means for returning some energy from the 'microbial loop' to the conventional planktonic food chain.

A strategy is presented for analysing marine biological survey data and relating the biotic patterns to environmental data. To avoid circular argument, biotic and environmental data are kept separate. The strategy is illustrated by a worked example using data on the distribution of 182 nematode species in 107 samples in the River Exe estuary. Nineteen stations are grouped Into 4 main clusters using complementary classification and multi-dimensional scaling (MDS) ordination techniques. These are both based on root-root transformed abundance data with the Bray-Curtis measure of similarity. Indicator species characterising each group are extracted using information statistics. Inverse analyses give clusters of CO-occurnng species which are strongly related to the station groups. Relationships of station groups to environmental variables are revealed by superimposing data for one variable a t a time on the MDS plot, showing that some station groups differ in sediment granulometry and others in salinity, for example. Some of the other factors plotted show no difference between station groups. Similarly, physiognomic charactcrlstics of the species are superimposed on the MDS plots of the inverse analysis of species groups, revealing differences in setal length and trophic status between the species groups. Finally, the 4 major station groups and species groups are related to one another in terms of morphological adaptation to the habitat.

The usefulness and relevance of size-based indicators (SBIs) to an ecosystem approach to fisheries (EAF) are assessed through a review of empirical and modelling studies. SBIs are tabulated along with their definitions, data requirements, potential biases, availability of time-series, and expected directions of change in response to fishing pressure. They include mean length in a population, mean length in a community, mean maximum length in a community, and the slope and intercept of size spectra. Most SBIs can be derived from fairly standard survey data on length frequencies, without the need for elaborate models. Possible fishing- and environment-induced effects are analysed to distinguish between the two causes, and hypothetical cases of reference directions of change are tabulated. We conclude that no single SBI can serve as an effective overall indicator of heavy fishing pressure. Rather, suites of SBI should be selected, and reference directions may be more useful than reference points. Further modelling and worldwide comparative studies are needed to provide better understanding of SBIs and the factors affecting them. The slow response to fishing pressure reflects the complexity of community interactions and ecosystem responses, and prohibits their application in the context of short-term (annual) tactical fisheries management. However, movement towards longer-term (5-10 years) strategic management in EAF should facilitate their use

A general, size-based simulation model is developed to investigate the dynamics of carbon and nitrogen flows in plankton communities. In the model, community structure and transfer processes are all size-dependent, and all model parameters are determined by body size, using empirically determined relationships calculated from published data Major flows include carbon fixation, release of photosynthetically produced dissolved organic carbon (PDOC), nitrogen uptake, respiration, excretion, predation, senescence and sinking. Because the model is based on general ecological principles and not on a specific ecosystem or data set, it can be used to simulate interactions within plankton communities of any ecosystem. The structure of the model can easily be altered to incorporate fewer or more size classes, or different size ranges of organisms. The program adjusts interactions between different components to allow for changes in the number of size classes, and new parameters are estimated, based on mean organism size A standard simulation is described, which serves as the basis for comparing output from a sensitivity analysis. The model is robust with respect to most parameters. Important factors which affect model output include estimates of various rate parameters (which may be altered by environmental effects), shapes of initial biomass distributions (seeding effects), and wet mass to carbon conversion functions. The model is a useful tool to assist in analysing and interpreting carbon and nitrogen flows in planktonic ecosystems.

General allometric equations are derived for rates of nutrient uptake, ingestion, and respiration by planktonic organisms. Previous studies commonly calculated parameters a and b in the allometric equation R = aMb by linear regressions on log‐transformed data. This practice results in variability between data sets in estimates of both a and b, making meaningful comparisons difficult. This problem is overcome by assuming the mass‐specific form of b to be −0.25, based on accumulated empirical evidence. Values of a arc then recalculated from published data, with log transformations and an assumed regression slope of −0.25. Resulting regressions predict values of a (in pg C0.25 d−1) at 20°C as follows: 3.6 for nutrient uptake by phytoplankton and bacteria; 63 and 13 for ingestion and respiration by particle‐feeding heterotrophs. It is hypothesized that organisms that take up dissolved nutrients from solution (autotrophs and osmotrophs, e.g. phytoplankton and bacteria) have lower specific respiration rates (i.e. smaller a) when compared with organisms (either unicellular or multicellular) that ingest particulate material.