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We quantified the relationships among the specific growth rate, intracellular iron content, and steady state iron uptake rate for cultures of the marine diazotrophic cyanobacterium Trichodesmium (IMS 101) grown under differing conditions of Fe and N availability. The Fe quotas necessary to support a moderately Fe-limited growth rate (70% [micro]max) of 0.1 [d.sup.-1] under diazotrophy and ammonium were 38 and 8 [micro]mol [mol.sup.-1], indicating a fivefold increased Fe cost for diazotrophy. This increased demand reflects the influences of both the ninefold lower marginal use efficiency and the greater maintenance Fe : C requirement at zero growth rate under diazotrophy (13.5 versus 5.2 [micro]mol [mol.sup.-1]). For diazotrophic growth at [micro] = 0.1 [d.sup.-1], we estimate that 19%-53% of the cellular Fe is bound in nitrogenase. Trichodesmium is capable of luxury uptake of at least 13-fold greater amounts of Fe than needed for moderately Fe-limited growth. At least half of the populations sampled from the continental shelf of northern Australia had Fe : C ratios within the range of iron limitation of laboratory cultures. Bottle incubations showed that, after 3-4 d with added iron, a low Fe: C population (21 [micro]mol [mol.sup.-1]) had higher [N.sub.2] fixation rates than controls, whereas a high Fe : C population (78 [micro]mol [mol.sup.-1]) showed no response. The cellular N : P quotas and [N.sub.2] fixation rates were compared to those previously reported for the Atlantic Ocean. Empirically, these data suggest a critical N : P ratio ~40-50 for the onset of P limitation of growth. Only 10% of the Trichodesmium populations from coastal Australia had N : P ratios within the putative P-limitation range (>40), whereas 40% the Atlantic populations fell within this range. These comparisons, along with those for N fixation versus colony Fe: C ratio, suggest that Fe limitation is more prevalent in the Australia Trichodesmium populations, while P limitation predominates in the Atlantic populations.

The neurotoxins from freshwater blue green algae are measured by means of sensitive receptor binding techniques. Two microtiter plate based bioassays that use radioactively labeled saxitoxin (SX) binding by sodium channels or saxiphilin have emerged for measuring STX and its derivatives, which are often found in Anabaena and Aphanizomemon.

Combining whole-cell hybridization with flow cytometry can be used to analyze marine cyanobacterial picoplankton. The technique uses fluorescently labeled rRNA-targeted peptide nucleic acid probes. The technique was used to detect Prochlorococcus and Synechococcus in samples of ocean water.

Artificial neural networks have been used successfully in a number of areas of civil engineering, including hydrology and water resources engineering. In the vast majority of cases, multilayer perceptrons that are trained with the back-propagation algorithm are used. One of the major shortcomings of this approach is that it is difficult to elicit the knowledge about the input/output mapping that is stored in the trained networks. One way to overcome this problem is to use B-spline associative memory networks (AMNs), because their connection weights may be interpreted as a set of fuzzy membership functions and hence the relationship between the model inputs and outputs may be written as a set of fuzzy rules. In this paper, multilayer perceptrons and AMN models are compared, and their main advantages and disadvantages are discussed. The performance of both model types is compared in terms of prediction accuracy and model transparency for a particular water quality case study, the forecasting (4 weeks in advance) of concentrations of the cyanobacterium Anabaena spp. in the River Murray at Morgan, South Australia. The forecasts obtained using both model types are good. Neither model clearly outperforms the other, although the forecasts obtained when the B-spline AMN model is used may be considered slightly better overall. In addition, the B-spline AMN model provides more explicit information about the relationship between the model inputs and outputs. The fuzzy rules extracted from the B-spline AMN model indicate that incidences of Anabaena spp. are likely to occur after the passing of a flood hydrograph and when water temperatures are high.