Analysis of Long-Term Data Set


INTERPRETATION OF CHLOROPHYLL DATA

Figure 6 shows the complete data set for chlorophyll a concentrations in the Harvey Estuary. The most obvious feature is the Nodulariablooms. There are large year-to-year differences in their magnitude - indeed there are some years when no bloom has occurred - and this leads to two important points.

Firstly, if data were not available for a number of years, it would be difficult to draw conclusions about long-term trends. For example, there was no bloom in the most recent year, and this might be interpreted as an improvement in the estuary, but from what we know of previous data this would be a very dangerous conclusion.

Secondly, because there are marked year-to-year differences in the magnitude of the blooms we can conclude that the magnitude of the bloom in particular years must be controlled by environmental factors which differ from year to year. It is possible to carry out sophisticated statistical analyses of time-course data, including modelling exercises, and this has been done with parts of this data set (Hornberger and Spear, 1980; Humphries et al.,1981; Lukatelich and McComb, 1986) but here we note the usefulness of using simple approaches to testing hypotheses. For example, if we propose that the magnitude of a Nodulariabloom in summer is determined by the amount of nutrient entering the estuary in the previous winter, there should be a relationship between the magnitude of the bloom and the volume of water entering the estuary in the previous winter.

The minimum salinity reached in the estuary in winter serves as a proxy for the volume of river flow. Figure 7 shows the relation between minimum salinity in winter and maximum chlorophyll reached in the following summer. Our hypothesis, that Nodulariabloom magnitude is related to the amount of phosphorus reaching the estuary each year, remains tenable. This has important management implications; for example, if we were able to stop phosphorus entering the system, this would have an almost immediate effect in reducing Nodulariablooms.
 

MACROALGAE

Figure 8 shows the time course for the macroalgae in Peel Inlet, and the data appear erratic; so erratic that for a time it was felt they did not justify collection, and this is the reason for gaps in the data. The biomass is made up of only a few genera of green algae, Cladophora,Chaetomorpha, Enteromorphaand Ulva, and species dominance has changed with time. The growth characteristics of Cladophorahave been investigated in the laboratory, and modelling exercises have been carried out using field data, so that the behaviour of this species at least is fairly well understood

Cladophora montagneanaoccurs as spheres of radiating filaments some 2 cm in diameter, which make up loosely compacted 'beds' on the estuary floor (Gordon et al.,1985).  It grows rapidly under summer conditions of high light and temperature. Much of the nutrients required for growth are recycled from decomposing algae below a layer of viable algae nearer to the surface of the bed. Light is of critical importance, and once a layer of algae has accumulated, self-shading determines the depth of the alfal layer which is capable of undertaking significant photosynthesis and growth. The accumulation of algal biomass has been possible because of the increased nutrient status of the estuary, but at any one time light is more critical in controlling the rate of biomass increase.

This conclusion is consistent with the small amount of macroalgae in the Harvey Estuary, which is attributed to poor light penetration in this water body, aligned as it is in a direction which ensures that it is often wind-stirred, and is subject to intense phytoplankton blooms (Gabrielson and Lukatelich, 1985; Lukatelich and McComb, 1986b; Gordon and McComb, 1988).

This is another hypothesis which may be examined using the time-course data, because there are marked differences between years in light penetration in the water column, largely because of the magnitude of Nodulariablooms spilling into Peel Inlet from the Harvey. The mean annual biomass of macroalgae was plotted against the mean light attenuation during the growth period, December to March (Figure 9). Considering the inherent variability of the data, the relationship is reasonably close. The hypothesis holds, and again has important management implications. We can predict an increase in the magnitude of macro-algal biomass as management proceeds and water clarity improves.