An alkaline approach to treating cooling towers for control of Legionella pneumophila.

Earlier field and laboratory studies have shown that Legionella species survive and multiply in the pH range 5.5 to 9.2. Additionally, the technical feasibility of operating cooling towers at elevated alkalinities and pH has previously been documented by published guidelines. The guidelines indicate that these conditions facilitate corrosion control and favor chlorine persistence which enhances the effectiveness of continuous chlorination in biofouling control. This information suggests that control of Legionella species in cooling towers can be accomplished by operating the towers under alkaline conditions. To test this possibility, we collected water samples over a period of months from a hospital cooling tower. The samples were analyzed for a variety of chemical parameters. Subsamples were pasteurized and inoculated with non-agar-passaged Legionella pneumophila which had been maintained in tap water. Correlation of subsequent Legionella growth with corresponding pH and alkalinity values revealed statistically significant inverse associations. These data support the hypothesis that operating cooling towers outside of the optimal conditions for Legionella growth (e.g., at elevated alkalinities and a pH greater than 9) may be a useful approach to controlling growth in this habitat.     

655. SCHIMA SINENSIS

Schima sinensis (Hemsl. & E.H. Wilson) Airy Shaw is described and illustrated. The genus Schima is discussed. Five recent collections of Schima species are reviewed.     

Dyar's Rule and the Investment Principle: optimal moulting strategies if feeding rate is size-dependent and growth is discontinuous

We consider animals whose feeding rate depends on the size of structures that grow only by moulting (e.g. spiders'' legs). Our Investment Principle predicts optimum size increases at each moult; under simplifying assumptions these are a function of the scaling of feeding rate with size, the efficiency of moulting and the optimum size increase at the preceding moult. We show how to test this quantitatively, and make the qualitative prediction that size increases and instar durations change monotonically through development. Thus, this version of the model does not predict that proportional size increases necessarily remain constant, which is the pattern described by Dyar''s Rule. A literature survey shows that in nature size increases tend to decline and instar durations to increase, but exceptions to monotonicity occur frequently: we consider how relaxing certain assumptions of the model could explain this. Having specified various functions relating fitness to adult size and time of emergence, we calculate (using dynamic programming) the effect of manipulating food availability, time of hatching and size of the initial (or some intermediate) instar. The associated norms of reaction depend on the fitness function and differ from those when growth follows Dyar''s Rule or is continuous. We go on to consider optimization of the number of instars. The Investment Principle then predicts upper and lower limits to observed size increases and explains why increases usually change little or decline through development. This is thus a new adaptive explanation for Dyar''s Rule and for the most common deviation from the Rule.