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With regard to instrumentation, most studies relied on basic equipment for sampling and analysis. In most cases water sampling was effected through the use of a simple bucket or beaker and as such sampling other than surface
water was impossible. Similarly, sediment sampling was done with the use of hand operated plastic corers. An ordinary thermometer was used widely to read water temperatures and this measurement was therefore limited to
surface water temperatures. Many studies measured turbidity and this was effectively done with the help of a secchi disc. Hand held refractometers were used widely to take salinity measurements.
The most widely used analytical instrument was the spectrophotometer. This was mainly used for nutrient analysis. There was very little automation. Consequently only few studies used the auto-analysis technique for
nutrient analysis for example. The absence of the auto-analyser in many labs was a serious limitation in that in cases where samples to be analysed were very small, for example from pore water, some nutrients especially
nitrates in sediments could not be analysed. Sophisticated instruments were used only rarely and in many cases samples had to be sent abroad for analysis. For example, in his studies on organic carbon distribution,
mineralisation, and fluxes in Maruhubi mangroves, Machiwa 1998, 1999 relied on a TOC analyser that was available in Stockholm. Similarly, Mohammed 1998 used a CHN analyser for the analysis of total nitrogen and
total carbon also in Stockholm.
Generally, the different methods employed in the above studies discussed gave more or less accurate data. Having said that however, there is a need of conducting regular inter-calibration exercises among different laboratories in
the country to ensure further improvement in the quality of data generated by different researchers.
2.2.3 Sampling frequency, time of collection and duration of study
Generally, in most studies sampling was of short duration ranging from a few days to weeks. For example, Anderson 1994 in his monitoring of sewage pollution exercise took measurements for a period of two weeks.
Similarly, the studies by Kastner 1996, Gillian 1998, Munisi 1998, van Bruggen 1990 were all of short duration. Third year projects by University of Dar es Salaam students were slightly longer. For example,
Mwandya 1996 conducted a three months study taking measurements during the later part of 1995 to early 1996. Some studies were seasonal in nature and compared results between wet and dry seasons or between monsoons.
For example, Mohammed and Johnstone 1995, 1999 measured wet and dry variations of water column nutrient variations and sediment-water exchanges in the Chwaka Bay mangrove forest while Mamboya 1996 compared
wet against dry season variations of nutrients and dissolved oxygen in Mbezi Creek in Dar es Salaam. Only few studies were of longer duration of one year and longer. Kangwe 1999, Mmochi 1999 carried a two-year study
to looked at the effect of land based pollution on reef building calcareous algae in the refs near Zanzibar Town. Mmochi 1999 carried out a one year monitoring study of water quality in Zanzibar.
2.2.4 Data analysis methods and procedure
Data analysis techniques varied from study to study depending on the type of information gathered, the number of factors involved and the nature of data, among others. In general however, there were few studies that had good
statistical analysis of their data while majority of the studies did not apply any statistical treatment of their data atall. A few that had statistics include studies by Machiwa 1999. In his study in the Maruhubi mangrove forest,
Machiwa used parametric one way analysis of variance ANOVA to test the difference in his measurements in the different zones of the forest. He also used Tukey test to compare sample means. ANOVA was also used in the
studies by Mohammed and Johnstone 1995,1999 and Mohammed et al 1999. Nzali 1994 used the F-test to compare variations in nutrient concentrations between the dry and wet seasons. He also used the non-parametric
Mann Whitney U-test to compare nutrient concentrations at various tide levels.
2.3 Quality, usefulness and reliability of datainformation
2.3.1 Capability of scientistsresearchersreporter
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Many of the studies synthesised in this report were carried out by students either under the supervision of their tutors or, in the case of visiting students, at some institutions by resident researchers. Others are those by senior
researchers and consultants. Students’ reports falls under three categories. These are academic reports produced by students from the University that report results of their field exercises; reports by visiting students; and Masters
and PhD theses. Many of the studies, especially those by senior researchers, are of a good quality. The quality of studies that were closely supervised by capable scientists is also commendable. Masters and PhD theses from the
University are normally examined both locally and externally. This also ensures quality products.
2.3.2 Comparability of methods
In almost all the studies nutrient analyses were carried out by the methods presented in the Manual of Chemical and Biological Methods for Seawater Analysis
by Parsons et al 1984. These are standard methods. In this respect the methods used in these studies are comparable. This is also true for other analytical techniques such as
those used for the analysis of heavy metals and coliforms. In the case of applied studies where information gathering was through interviews and questionnaire, the basic approach was similar in all the studies, even though
variations in the interview techniques were apparent. All in all, the methods used in the various studies were comparable and hence may cause little problems in the interpretation of results in the future. It is noteworthy, as
mentioned above, that the principal methods used in various studies, though standard, are quite old and lack any sophistication. This is a common problem that can be attributed to inaccessibility of new and better techniques.
Improvement of analytical techniques will help produce better and more accurate results.
2.3.3 Publicationsgrey literature
