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Title: Local scale models of coral reef ecosystems for scenario testing and decision support
Author: Fung, T. C.
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2009
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The world’s coral reefs have been severely degraded over the past four decades and better management is urgently required to reverse this trend. Mathematical models are important tools for hypothesis and scenario testing, and are thus essential for better management. In this thesis, models of a coral reef ecosystem are constructed that aim to identify the key ecological processes responsible for reef degradation. The models operate at a ‘local’ intra-reef scale and they are dynamic, deterministic and non-spatial. A modelling strategy is used which adds complexity in a step-wise fashion, and this aids in the interpretation of results. The models are analyzed using mathematical equilibrium theory and are then parameterised using empirical data from reefs worldwide. Afterwards, the potential of reefs to undergo phase shifts from coral- to algaldominance under the effects of three anthropogenic stressors – fishing, nutrification and sedimentation – are investigated. This involves the application of a novel type of genetic algorithm, systematic sweeps of the parameter ranges and two types of sensitivity analysis. A key result is that the presence of macroalgae can give rise to multiple equilibria and hence discontinuous phase shifts under each of the three stressors investigated, by strengthening positive feedback to an algal-dominated state. Another key result is that reef benthic covers show a high degree of non-linearity under the three stressors. Overall, the results show that reefs are inherently prone to phase shifts under anthropogenic stress. These results suggest that in order to maximise resilience to reef degradation, there is an urgent need to effectively manage different anthropogenic stressors simultaneously. The models in this thesis can be parameterised for local reef areas at specific locations and then used for scenario testing, and they also serve as a solid foundation on which to add and investigate more complexity.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available