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Abstract
The main objective of this study was to develop a methodology to ascertain spatio-temporal
changes of mangrove vegetation; describe, quantify and predict the spatial patterns through
time using remote sensing, GIS and computer simulation models as tools. Other models,
based on individual-based or cellular automata approaches, have also demonstrated the
importance of local interactions in space on population dynamics. This study is motivated by
the need to understand the pattern dynamics of mangrove species including steady state
analysis and the role of disturbance in mangrove ecosystems. Mangrove canopy turnover
takes hundreds of years under natural conditions, hence the application of appropriate
simulation models may enhance knowledge and predictions on likely evolutionary patterns.
The vegetation characteristics of Gazi Bay were determined and this was a crucial step in
obtaining the parameterization data for the model. Based on the sensitivity analysis, the
species competition coefficients, coupled with the carrying capacity values, were probably the
most important parameters influencing the predictions especially regarding equilibria of the
forest. However, the effects due to synergistic influences of all the tested parameters in the
sensitivity analysis may become clearer when studies are conducted while putting into
perspective important gradients such as environmental and topographical attributes. This
study generated predictive insights on the equilibria of pairwise species interactions based on
the carrying capacities and species interaction coefficients of the mangroves in Gazi Bay and
suggests that phase-plane analysis may be considered an effective proxy to ascertain
equilibria among pairwise competing mangrove species. The results of this study reiterate that
dispersal distances are directly proportional to the population density although this is subject
to moderations due to factors such as carrying capacity (K) and competition coefficients
( 12 ;  21 ) and possibly other inherent ecological factors.
Cellular automaton models based on the Lotka-Volterra model of competition is a good
metaphor for describing and predicting spatial temporal variations of competing mangrove
species that are subjected to various magnitudes of disturbance events. The suitability of the
model, considering the useful insights and cost implications is noteworthy. The competition
was evaluated based on neighbourhood rules at individual level and at population density
levels. Normally, site productivity and resource availability control the rate of return to predisturbance conditions on a patch. However, the uncertainties regarding residuals or biotic
legacies after the event of a disturbance provide a constraint for the model since these may
only be accounted for, in the simulations, using empirical observations over a long period.
The phase-plane analysis results suggest that for the simulations, interacting species
composition may be considered important in determining the temporal stability in Gazi. The
need to evaluate some inherent factors through transient dynamics analysis could enhance the
predictions. Due to the important ecological consequences due to disturbance which results in
creation of canopy openings, it is prudent that future experimental designs to study Gazi
mangroves be specifically focused on tree recruitment and its scale, intensity and spatial
patterns of tree mortalities in response to specific types of disturbance events or regimes. This
would enhance the present knowledge of forest dynamics which may be considered full of
uncertainties without a comprehensive understanding of the disturbance regime.