| Summary: | Finding a common language in describing and interpreting multivariate data
associated with rehabilitation and disturbance ecology, has became a major
challenge.
The main objective of this study is to find and evaluate mathematical models
to describe ecosystem change based on selected indicators of change.
Existing data from a previous rehabilitation project on Hendrina Power Station
(Mpumalanga, South Africa) was used as a database for this study and this
study aims to report on the development of models concentrating on radar
graphs and a model based on matrix mathematics.
The main groups of organisms selected for the construction of models, were
vegetation, soil mesofauna and ant species. The datasets were limited to
some indicative species and their mean abundances were determined. The
grids that were used were randomly chosen and the models were
constructed.
Radar graphs were constructed to model the suite of species identified,
through a sensitivity analysis, to indicate possible rehabilitation success over
time and was applied to the different rehabilitation ages. The surface areas
under the radar graphs were determined and compared for the different
rehabilitation ages in the same year of survey. Correlation graphs were drawn
between the surface area and the rehabilitation ages. These graphs did not
indicate much relevance in indicating rehabilitation success, but the radar
graphs proved to be good indicators of change in abundance of the selected
species over time.
iv
The vegetation species, Eragrostis curvula, was the only species that showed
a strong significant positive relationship with rehabilitation age and could be
considered a good rehabilitation species and indicator of rehabilitation
success. After the evaluation of this model, Eragrostis curvula, and two
additional ant species, Tetramorium setigerum and Lepisiota laevis, were
added. These species that were added, showed an increase in abundance
over time, as found in a previous study. These radar graphs also did not
indicate much relevance and it can be concluded that the radar graphs can
only be used for a visual representation of the changes in abundance of the
relevant species over time.
This study also refers to a matrix model. This model focused on the
interactions between the different variables selected. The percentage carbon
in the soil were also added to the list of species. Model fitting graphs were
constructed and correlations were drawn between the species that had
significant values in the interaction table. This model could be useful for future
studies, but more data and replication is necessary, over a longer period of
time. This will serve to eliminate possible shortcomings of the model. === Thesis (M. Environmental Science (Biodiversity and Conservation Biology))--North-West University, Potchefstroom Campus, 2007.
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