Date of Award


Document Type



Edith Cowan University

Degree Name

Bachelor of Science Honours


Faculty of Science, Technology and Engineering

First Supervisor

Dr Paul Lavery

Second Supervisor

Dr Gary Kendrick


A recently proposed hypothesis argued that morphologically and functionally similar macroalgae could be grouped to study the structure of macroalgal communities. It was argued that these functional groups can be used to predict changes to community composition that result from disturbance. This study examined whether the functional group model held in detecting changes in macroalgal community structure within one bioregion, by applying it to a habitat exposed to different levels of physical disturbance associated with wave exposure. Results obtained using a functional group approach were compared to those obtained using a species level approach. Three parallel reef lines in Marmion Lagoon, Western Australia, were chosen to represent three levels of exposure (high, intermediate and low) to wave-driven physical disturbance. Wave energy measurements taken simultaneously at each reef line confirmed that a gradient of physical disturbance existed. Community structure on each of the three reef lines was measured by determining the biomass and diversity of both functional groups and species at high, intermediate and low disturbance regimes. Comparisons between the two approaches were made using AN OVA of biomass data and derived diversity indices. Multivariate analysis techniques of ordination, Principal Axis Correlation (PCC) and ANOSIM (analysis of similarities) were used to detect patterns of assemblage change. The macroalgal assemblages within the target habitat were found to be highly variable, particularly within exposure levels, when examined at both the species and functional group levels. Overall, however, the functional group approach was less able to detect differences between levels of exposure. In conclusion, the use of the functional group approach is not recommended for communities displaying high spatial heterogeneity without further rigorous testing of the model. Use of the functional group approach resulted in considerable loss of information and did not account for physiological variations between all species in the one functional group. Furthermore, algal functional groups need to be more clearly defined to overcome problems of assigning species to groups that do not easily fit the model.