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Mangrove partitioning and storage of macronutrients and trace metals were examined in different arid coastal settings of Western Australia. Total living biomass in three Rhizophora stylosa forests, which ranged from 233 to 289 t DW ha -1 , was significantly greater than biomass in three Avicennia marina forests (range: 79-155 t DW ha -1 ). Although prop roots and stems were the largest single tree components for R. stylosa and A. marina, respectively, most nutrients were stored in leaves and living roots of both species. However, only a small fraction of the total nutrient pool was vested in tree biomass; the vast bulk was in soils. A large belowground pool of dead fine roots was identified at all stands, equivalent to 36-88% DW of total living tree biomass. The amount of Ca, S, Cl, Na, Si, Fe, Mn, Zn, B, Mo and Cu vested in dead roots of both species was greater than in the total living tree biomass. The proportion of Fe and S vested in live and dead roots was exceptionally large, consistent with previous evidence of metal plaques on mangrove roots. Sulphur, iron and zinc in dead roots of both species constituted the bulk of these metals. R. stylosa trees preferentially accumulated more Mg, S, Cl, Na, Si, Fe, Mn, B and Mo than A. marina trees. Proportionally greater storage of P, N, Ca, K, Cu and Zn occurred in two of the three A. marina forests. Foliar concentrations of Mg, S, Mn, B and Mo in mangrove leaves were at the high end of the range reported for other tropical trees, but other elemental concentrations were at the low or mid-range. Nitrogen limitation in these forests is implied by a positive correlation between total tree N and net canopy production and by a lower percentage of ecosystem N in tree biomass as compared with other forests. Unlike terrestrial forests where a large proportion of nutrient capital is vested in floor litter, most elements in these mangrove forests are stored in dead roots. A large reservoir of dead roots below the forest floor may serve as a conservation mechanism, particularly in such arid oligotrophic environments.

The problem to be considered is that of determining lot‐sizes for a group of products which are produced at a single workcentre. It is assumed that the requirements for each product are known, period by period, out to the end of some common time horizon. (A reasonable assumption in a Material Requirements Planning context when we are dealing with components of one or more other items already scheduled.) For each product there is a fixed setup cost incurred each time production takes place. Unit production and holding costs are linear. The time required to set up the machine is assumed to be negligible. All costs and production rates can vary from product to product but not with respect to time. In each period there is a finite amount of machine time available that can vary from period to period. The objective is to determine lot‐sizes so that 1) costs are minimized, 2) no backlogging occurs and 3) capacity is not exceeded.An exact solution to this complex problem is out of the question. Therefore, a simple heuristic has been developed which guarantees a feasible solution, if one exists. Results of a large number of test problems, including three supplied by industrial sources, are presented. The results indicate that the heuristic will usually generate a very good solution with a relatively small amount of computational effort.