Impact of Anthropogenic Disturbance on a Mangrove Forest Assessed by a 1D Cellular Automaton Model Using Lotka–Volterra-Type Competition

Impact of Anthropogenic Disturbance on a Mangrove Forest Assessed by a 1D Cellular Automaton Model Using Lotka–Volterra-Type Competition

P.T. Obade N. Koedam K. Soetaert G. Neukermans J. Bogaert E. Nyssen F. Van Nedervelde U. Berger F. Dahdouh-Guebas 

Biocomplexity Research Focus, Laboratory of General Botany and Nature Management, Mangrove Management Group,

Faculteit Wetenschappen en Bio-ingenieurswetenschappen, Vrije Universiteit Brussel (VUB), Belgium

Kenya Marine and Fisheries Research Institute, Kenya

Nederlands Instituut voor Oecologisch Onderzoek, Centrum voor Estuariene en Mariene Ecologie (NIOO-CEMO), The


Laboratoire d’Ecologie du Paysage et Systèmes de Production Végétale, Faculté des Sciences, Université Libre de

Bruxelles (ULB), Belgium

Image Processing and Machine Vision Group, Department of Electronics and Informatics, VUB, Belgium

Complexité et Dynamique des Systèmes Tropicaux, Département de Biologie des Organismes, Faculté des Sciences, ULB,


Department of Forest Biometry and Systems Analysis, Institute of Forest Growth and Forest Computer Sciences,

Technische Universität Dresden, Germany

31 December 2008
| Citation



Mangrove forests are ecologically and economically important and frequently dominating protected coastal areas in the tropics and subtropics at suitable intertidal zones and are often subjected to disturbances that disrupt the structure of an ecosystem, that change resource availability and that create patterns in vegetation by producing a mosaic of seral stages that ecologists have long recognised as important to landscape-level patch mosaics. Several good reasons justify the need for pursuing a predictive understanding of the ecology of mangrove species competition including the role of disturbance events and the aftermath. A predictive understanding can challenge our assumptions concerning the factors that control plant distribution and abundance and provide techniques for predicting rates of species change ranges in response to disturbances. The aim of this study was to evaluate and predict the impact of canopy disturbances on Gazi Bay mangrove forests and the subsequent vegetation patterns both spatially and temporally. The use of a simple 1D cellular automaton provided a detailed and nearly comprehensive parameterisation of the model by forest structure parameters belonging to the standard measurements of mangrove field surveys. In the study presented, the field data were obtained for disturbance impacts at various spatial scales considering not only the spatial extent of the disturbance but also its particular location. For this, multiple sampling transects were selected a priori, based on the vegetation patterns observed on Quickbird satellite image (2002) of Gazi, to reflect major ecological zones and vegetation transitions in space. Earlier field studies already revealed different population trajectories in some cases for the same pairwise species interactions, which are consistent with the hypothesis that different scales of disturbances may affect succession trends. Simulation experiments supported these findings by demonstrating that varying disturbance impacts determine coexistence or mutual exclusion of the interacting species and occasionally leading to equilibrium shifts to alternative states. We suggest the consideration of simulation experiments as a good proxy for predicting mangrove species dynamics not neglecting the need of further evaluation based on the transient ecodynamics.


forecasting, Gazi, Kenya, mangrove, succession trajectory, vegetation dynamics


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