Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

Modelling biological responses to environmental variables in wetlands

Pitcher, Jannette (1999) Modelling biological responses to environmental variables in wetlands. PhD thesis, Murdoch University.

PDF - Whole Thesis
Available Upon Request


Eutrophication and hydrologic changes resulting from increased agricultural and industrial activities have contributed to the degradation and loss of wetlands worldwide. The need to understand the response of wetland components to changing environmental conditions and to assess and predict ecological consequences of these changes has therefore intensified. Ecological models are proving to be valuable tools in managing these threatened ecosystems.

A dynamic, spatially-explicit simulation model was developed to study the effects of different environmental conditions on the dynamics of wetland vegetation. Factors important to vegetation dynamics included in the model are: water regime, sediment type, light and nutrient availability, and competition for resources. The model uses an individual-based modelling approach, in which vegetation communities are simulated as collections of individual plants on a transect through a wetland.

Plants included in the model are common in wetlands on the Swan Coastal Plain near Perth, Western Australia. They include two emergent macrophytes, Baumea articulata and Typha orientalis and a .fringing tree species, Melaleuca preissiana. Emergent macrophytes are characterised by life history characteristics, responses to environmental conditions and morphological attributes. Plants grow according to the resources (light, nutrients and water) they acquire, and photosynthates are allocated according to plant species, developmental stage and environmental conditions.

The model is generic and can be used at different wetlands. A range of abiotic and biotic data is required. Input data include simulation run time, transect dimensions, elevation, nutrient, water, temperature and light levels, soil type and distribution, and vegetation composition and distribution. The model provides spatial and temporal information on the responses of wetland vegetation on a transect basis (e.g. plant distribution, biomass, number and type of plants) and on an individual plant basis (e.g. height, leaf area and biomass).

The model was validated by comparing model results with field and remote sensing data, and information from the literature. Several scenarios were simulated, including: 1) potential effects of different environmental conditions (e.g. water, light and nutrient regimes); 2) historical events; 3) impacts of different management strategies; and 4) development of artificial wetlands under differing planting densities and environmental conditions. Detailed results are presented for the scenarios simulated. In general, model results from the scenarios simulated were in good agreement with field and remote sensing data and information from the literature.

The model has been successfully applied to studying the response of individual plants and plant communities under different environmental conditions. It provided accurate and realistic representations of the compositional and distribution vegetation changes associated with different management strategies and environmental conditions.

The usefulness of the model was demonstrated for studying responses of vegetation to environmental change, and for improving understanding of wetland vegetation dynamics. The model therefore has important implications for the conservation and management of wetland vegetation.

The model was developed to simulate the dynamics of wetland vegetation and is proving to be an effective tool for studying the spatial and temporal responses of wetland vegetation to natural and human-induced environmental changes.

Item Type: Thesis (PhD)
Murdoch Affiliation(s): Division of Science and Engineering
Supervisor(s): McComb, Arthur, Townley, Lloyd and Chambers, Jane
Item Control Page Item Control Page