Photocopy of typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1979. / Bibliography: leaves 238-248. / Microfiche. / xii, 248 leaves ill., maps 29 cm

Bibliography: leaves 86-90 / Microfiche. / viii, 90 leaves, bound ill., maps 29 cm

Thesis (M.S.)--University of West Florida, 2009. / Title from title page of source document. Document formatted into pages; contains 82 pages. Includes bibliographical references.

Thesis (M.Eng.)--Memorial University of Newfoundland, 1999. / Bibliography: leaves 127-134.

Thesis (Ph. D.)--McGill University, 1967. / Includes bibliographical references (leaves 79-85).

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Fung, Ho Lam. / Thesis submitted in: November 2006. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 343-360). / Abstracts in English and Chinese. / Acknowledgements --- p.i / Abstract --- p.iii / Contents --- p.xii / List of Tables --- p.xix / List of Figures --- p.xxxi / Chapter Chapter 1: --- General Introduction / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Objectives --- p.17 / Chapter 1.3 --- Monitoring methods investigated in this research --- p.18 / Chapter 1.4 --- The distribution of corals in Hong Kong --- p.21 / Chapter 1.5 --- Study sites --- p.23 / Chapter 1.6 --- Thesis Outline --- p.25 / Chapter Chapter 2: --- "Coral Mapping in Cheung Sha Wan, A Ye Wan and A Ma Wan, Tung Ping Chau" / Chapter 2.1 --- Introduction --- p.31 / Chapter 2.2 --- Study sites --- p.37 / Chapter 2.3 --- Methods and Materials --- p.38 / Chapter 2.3.1 --- Fieldwork procedure --- p.38 / Chapter 2.3.2 --- Laboratory work procedure --- p.40 / Chapter 2.3.3 --- Data analysis --- p.40 / Chapter 2.4 --- Results and Discussion --- p.42 / Chapter 2.4.1 --- Species count --- p.42 / Chapter 2.4.2 --- Coral coverage --- p.42 / Chapter 2.4.3 --- Species composition --- p.43 / Chapter 2.4.4 --- Diversity index --- p.43 / Chapter Chapter 3 --- "Evaluation of Monitoring Methods in Cheung Sha Wan, Tung Ping Chau, a Coral Community with Low (< 10%) Coral Cover" / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Materials and methods --- p.61 / Chapter 3.2.1 --- Line Intercept Transect (LIT) Method --- p.62 / Chapter 3.2.2 --- Point Intercept Transect (PIT) Method --- p.62 / Chapter 3.2.3 --- Random Point Video Transect (RPVT) Method --- p.63 / Chapter 3.2.4 --- Quadrat (QUAD) Method --- p.64 / Chapter 3.2.6 --- Sampling effort in each monitoring method --- p.65 / Chapter 3.2.7 --- Sample size determination --- p.66 / Chapter 3.2.7.1 --- Optimal sample size --- p.66 / Chapter 3.2.7.2 --- Unit effort sample size --- p.67 / Chapter 3.2.8 --- Statistical analysis --- p.68 / Chapter 3.2.8.1 --- Univariate analysis --- p.68 / Chapter 3.2.8.2 --- Multivariate analysis --- p.69 / Chapter 3.4 --- Results --- p.70 / Chapter 3.4.1 --- Optimal sample size --- p.70 / Chapter 3.4.1.1 --- Percent coral cover --- p.71 / Chapter 3.4.1.2 --- Species count --- p.72 / Chapter 3.4.1.3 --- Diversity indices --- p.72 / Chapter 3.4.1.4 --- Community structure --- p.73 / Chapter 3.4.2 --- Sampling efforts in different monitoring methods --- p.75 / Chapter 3.4.3 --- Sample size under fixed effort --- p.76 / Chapter 3.4.3.1 --- Percent coral cover --- p.77 / Chapter 3.4.3.2 --- Species count --- p.78 / Chapter 3.4.3.3 --- Diversity indices --- p.78 / Chapter 3.4.3.4 --- Community structure --- p.80 / Chapter 3.5 --- Discussion --- p.84 / Chapter 3.5.1 --- Optimal sample size --- p.84 / Chapter 3.5.2 --- Coral cover --- p.86 / Chapter 3.5.3 --- Species count --- p.90 / Chapter 3.5.4 --- Diversity Indices --- p.93 / Chapter 3.5.5 --- Community structure --- p.96 / Chapter Chapter 4 --- "Evaluation of Monitoring Methods in A Ye Wan and A Ma Wan, Tung Ping Chau: Coral Communities with Mid to High Percent Coral Cover (25% to 50%)" / Chapter 4.1 --- Introduction --- p.146 / Chapter 4.2 --- Methods and material --- p.149 / Chapter 4.2.1 --- Field monitoring --- p.149 / Chapter 4.2.2 --- Laboratory work --- p.149 / Chapter 4.2.3 --- Sampling effort in each monitoring method --- p.150 / Chapter 4.2.4 --- Sample size determination --- p.150 / Chapter 4.2.5 --- Statistical analysis --- p.151 / Chapter 4.2.5.1 --- Univariate analysis --- p.151 / Chapter 4.2.5.2 --- Multivariate analysis --- p.152 / Chapter 4.3 --- Results --- p.152 / Chapter 4.3.1 --- A Ye Wan --- p.152 / Chapter 4.3.1.1 --- Optimal sample size --- p.152 / Chapter 4.3.1.1.1 --- Percent coral cover --- p.154 / Chapter 4.3.1.1.2 --- Species count --- p.154 / Chapter 4.3.1.1.3 --- Diversity indices --- p.155 / Chapter 4.3.1.1.4 --- Community structure --- p.155 / Chapter 4.3.1.2 --- Sampling efforts in different monitoring methods --- p.157 / Chapter 4.3.1.3 --- Sample size under fixed effort --- p.158 / Chapter 4.3.1.3.1 --- Percent coral cover --- p.158 / Chapter 4.3.1.3.2 --- Species Count --- p.159 / Chapter 4.3.1.3.3 --- Diversity indices --- p.160 / Chapter 4.3.1.3.4 --- Community structure --- p.162 / Chapter 4.3.2 --- A Ma Wan --- p.165 / Chapter 4.3.2.1 --- Optimal sample size --- p.165 / Chapter 4.3.2.1.1 --- Percent coral cover --- p.167 / Chapter 4.3.2.1.2 --- Species count --- p.167 / Chapter 4.3.2.1.3 --- Diversity indices --- p.168 / Chapter 4.3.2.1.4 --- Community structure --- p.169 / Chapter 4.3.2.2 --- Sampling efforts in different monitoring methods --- p.171 / Chapter 4.3.2.3 --- Sample size under fixed effort --- p.172 / Chapter 4.3.2.3.1 --- Percent coral cover --- p.172 / Chapter 4.3.2.3.2 --- Species Count --- p.173 / Chapter 4.3.2.3.3 --- Diversity indices --- p.174 / Chapter 4.3.2.3.4 --- Community structure --- p.175 / Chapter 4.4 --- Discussion --- p.178 / Chapter 4.4.1 --- Optimal sample size --- p.178 / Chapter 4.4.2 --- Coral Cover --- p.178 / Chapter 4.4.3 --- Species Count --- p.181 / Chapter 4.4.4 --- Diversity Indices --- p.182 / Chapter 4.4.5 --- Community Structure --- p.184 / Chapter Chapter 5 --- Role of Community Characteristic on the Performance of Monitoring Methods / Chapter 5.1 --- Introduction --- p.281 / Chapter 5.2 --- Methods and materials --- p.284 / Chapter 5.2.1 --- Coral Mapping --- p.284 / Chapter 5.2.2 --- Monitoring Methods --- p.285 / Chapter 5.2.3 --- Statistical analysis --- p.286 / Chapter 5.3 --- Results --- p.286 / Chapter 5.3.1 --- Sample size as a function of different reef characteristics --- p.286 / Chapter 5.3.2 --- Performance of reef monitoring methods in sites with different reef characteristics --- p.287 / Chapter 5.3.2.1 --- Coral cover --- p.287 / Chapter 5.3.2.2 --- Species count and Margalef's Index --- p.288 / Chapter 5.3.2.3 --- Other diversity indices --- p.289 / Chapter 5.3.2.4 --- Community structure --- p.290 / Chapter 5.4 --- Discussion --- p.291 / Chapter 5.4.1 --- Effect of reef characteristics on sampling time --- p.291 / Chapter 5.4.2 --- Effect of reef characteristics on the performance of monitoring methods --- p.293 / Chapter 5.4.3 --- Recommendation on the choice of monitoring method --- p.301 / Chapter Chapter 6 --- Summary and Prospectives --- p.337 / References --- p.343

Macroalgae are abundant on shallow temperate reef environments, often forming complex communities that comprise several strata. In southern Australia, these assemblages are dominated by large canopy forming taxa from the Orders Laminariales and Fucales. The presence of subtidal fucoid macroalgae differentiates these communities from that elsewhere, and emphasises the need for local studies rather than relying on generalisations made elsewhere. Like most natural systems, temperate reefs are often threatened by human activity with degradation reported from many locations in close proximity to urban settlements. The work presented in this thesis involves an examination of the temporal and spatial variability in the structure of macroalgal communities from reefs along the Adelaide (South Australia) metropolitan coast. The work looked specifically at the effects of a dispersed sediment plume, resulting from the 1997 beach sand-replenishment dredging program, on shallow sub-tidal reef systems. An examination of the structure of canopy forming phaeophycean macroalgae in Gulf St Vincent (South Australia), noted large amounts of both spatial and temporal heterogeneity. Notwithstanding, this variation was not random, but demonstrated considerable structure that could be linked to a number of important underlying processes. In particular, macroalgal assemblages appeared as a mosaic of patches, each of which comprised a high-density state clearly dominated by a single genus (Cystophora, Sargassum, or Ecklonia), or alternatively a lower density mixed assemblage (Variable Low Abundance, VLA). Macroalgal community structure appeared to be driven by biotic interactions at small scales (metres), such that patches comprised of different species of algae in high density states rarely abutted one another. Instead, VLA assemblages frequently formed a buffer being situated between these mono generic patches. In terms of successional processes, the high-density states appeared to be relatively stable whereas the VLA state, at least in some systems, was transitory. This finding was supported by the absence of intermediary high- density states (e.g. a mix of Cystophora and Ecklonia) implying that state changes must occur via the VLA state following some form of disturbance. Larger scale patterns appeared to be driven by environmental variation, with factors such as wave exposure influencing habitat suitability for individual species and thereby affecting community composition. These phenomena were examined in terms of life history strategies that tend to promote stability, and which are common in late successional taxa. The importance of properties enhancing stability and the role of disturbance was investigated experimentally using a dispersed sediment plume, which entirely engulfed two reefs, as a pulse impact. This disturbance was of particular relevance given that degradation of macroalgal communities in close proximity to the City of Adelaide has been, at least in part, attributed to the effects of elevated levels of sediment. Follow up surveys revealed that the sedimentation from the plume had primarily affected newly recruiting individuals, with few juveniles surviving to one year of age. Over the following few years, the effect of this recruitment failure cascaded into the adult stand. In broader terms, unfavourable climatic conditions prior to the start of the study, including a particularly severe El Nino event, had a widespread effect on local assemblages, causing high levels of both adult and juvenile mortality. As such, at the commencement of the study, macroalgal communities across the study area were in the process of recovery. This was observed at control sites over the duration of the study. In contrast, recruitment failure at the sediment-affected sites retarded the recovery process, exacerbating the problems associated with prior unfavourable climatic events and leaving them in a degraded state. This study demonstrated that macroalgal assemblages are equipped (under natural conditions) to handle 'normal' environmental fluctuations (such as inter-annual variability). However, the additional stress associated with certain anthropogenic impacts has the potential to push them over the limit, causing degradation. The loss of canopy macroalgae reduces the structural complexity of the system, leading to a concomitant reduction in their ability to recover. As such, these findings are of particular relevance to those charged with the responsibility for managing near-shore marine environments. The plume was created accidentally during a dredging operation for beach sand replenishment of Adelaide's eroding shoreline. / Thesis (Ph.D.)--School of Earth and Environmental Sciences, 2004.