This mini-dissertation contains the results of research to establish a[1 economic value for the mangroves of the Mngazana Estuary in the Eastern Cape. The research is presented in two parts. Component A comprises the literature review and also describes the scope and context for the study, its purpose and the proposed methodology. Component B presents the results of the research in the format of an article to be submitted for publication to the African Journal of Marine Science. Estuaries and mangroves are among the most threatened habitats in South Africa, with the third largest mangrove forest in South Africa at the Mngazana Estuary on the Wild Coast of the Eastern Cape gradually reducing in size. A lack of appreciation of their value has resulted in policies and decisions that promoted the conversion of estuary and mangrove ecosystems to alternative uses, and caused a large-scale loss of mangroves throughout the world. Apart from their key ecological role, the Mngazana Estuary mangroves provide important benefits to the 645 households in three villages that utilise the resources and the sustainable use and management of the mangroves is essential. Economic valuation ascribes values to traded and untraded environmental resources and is a tool that supports policy formulation and decision-making on sustainable management of resources like mangroves. The theory of total economic value provides the conceptual framework for estimating the economic value, but constraints limited this study to estimating the socio-economically significant benefits the mangroves bestow on the communities around the Mngazana Estuary. Using information collected in a household survey and focus group discussions, market-price methods were used to estimate the value of mangroves harvested for building materials and the subsistence consumption of fish by the communities. Values were estimated for mangrove-dependent canoe trails and honey production operations, while a recreational use value was estimated on the basis of travel costs and expenses incurred by visitors to the holiday cottages adjacent to the estuary. The results were incorporated in 20-year valuation models with the net annual benefits then discounted to present value terms. Sensitivity analysis was performed to estimate lower-bound, upper-bound and most-likely values for the benefits. The minimum economic value of the mangroves was estimated to be between R1.1 and R13.6 million, with a most-likely value at a real 5% discount rate of R7.4 million. This study has shown that policies for managing environmental resources must be ecologically, socially and economically sound. This requires an integrated approach to address the socio-economic needs of local communities while safe-guarding environmental resources. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2004.

Gastropods are one of the most diverse species groups in mangrove habitats, however, many of their specific roles in relation to ecological patterns and processes are currently largely unknown. The overall aim of this research project was to provide basic ecological information for key gastropod species from subtropical mangroves within a protected area. South African mangroves cover relatively small areas and are restricted to estuaries, these habitats therefore present unique opportunities and challenges to the species that occur in them. Three gastropod species, Terebralia palustris, Cerithidea decollata, and Melanoides tuberculata, all occur at their natural southernmost range limit within South Africa and were selected based on their prominence and occurrence in mangrove habitats of the iSimangaliso Wetland Park, a UNESCO World Heritage Site. Trophic linkages and resource partitioning, resource utilization rates, and ecological resilience were investigated respectively using: 1) a stable isotope (δ15N and δ13C) approach; 2) an experimental approach to quantify feeding dynamics (ingestion rate, consumption/digestion efficiency and grazing impact); and 3) a mixed-effects modelling approach to relate population responses to environmental variables. The diet of T. palustris was seasonally variable and a number of sources were incorporated by different sized snails, but their grazing impact on microphytobenthos was not significant. The results also indicated an ontogenetic shift in the dietary niche for T. palustris through robust partitioning of resources between different size classes. The diets of C. decollata and M. tuberculata were dominated by different primary resources as a function of where they occurred in the mangroves. Melanoides tuberculata consumed a wide variety of primary resources, a typical trait of an opportunistic generalist species. The ingestion rate of M. tuberculata was not dependent on the availability of microphytobenthos, and was highest when conditions were oligotrophic. The resilience of C. decollata was related to the tree-climbing behaviour of this species and its occurrence was best explained by sediment conductivity. These responses were considered in conjunction to what has previously been reported on the resilience of the mangrove trees. The results of this research project have provided new basic ecological information for all three gastropod species in this data-deficient subtropical region. This information can potentially be used in comparative studies for these species in other regions or in broader scale ecological studies. Terebralia palustris has recently experienced a range contraction along the South African coastline. This research project has shown that the diet of this species is highly variable and that food limitation and competition for resources should be considered as potential drivers of the local decline. Cerithidea decollata has in contrast expanded its distributional range in this region. This research project has shown that this species has a generalist diet and exhibits traits in relation to tolerance that are expected to have facilitated its expansion into temperate saltmarsh habitats that occur in dynamic estuaries. Melanoides tuberculata is a globally invasive species, and as South African populations are within its native range, ecological information from this region is valuable as it can be used to investigate the potential ecological effects following introduction into new habitats beyond the native range. Biological drivers have a significant impact on mangrove ecosystem functioning, particularly in relation to recycling and the retention of organic carbon generated through primary productivity. Understanding the ecological linkages that maintain ecological functioning and stability is therefore an important step towards conserving and sustainably managing threatened ecosystems such as mangrove forests.

The value of mangrove habitats as fish nurseries was assessed by comparing communities of early stage and juvenile fishes between estuaries with and without mangroves. Early stage fishes were sampled using boat-based plankton towing while juveniles were sampled by seine netting. Sampling took place at five sites spaced 1 km apart starting near the estuary mouth in four estuaries along the temperate coastline of the Eastern Cape Province of South Africa. Four estuaries were selected based on shared similarities which included catchment area, estuarine area and shared habitats barring the presence of mangroves which occupied the river margins of two systems. Results revealed that early stage and juvenile fish communities (both marine- and estuary-spawned) were similar between systems with and without mangrove habitats. Differences in fish communities among estuaries were rather attributed to axial salinity gradients associated with greater freshwater input, while season and temperature produced significant variances in fish densities with Generalised Additive Models revealing responses of communities to these variables. A common estuarine-dependent fish, Rhabdosargus holubi (Family Sparidae), was further investigated to determine habitat use, residency and dietary patterns in different mangrove habitats. High habitat residency in this species was revealed during a short-term tagging study using Visible Implant Elastomer tags and long-term isotope analysis in juveniles sampled from two contrasting mangrove habitats. A wider feeding niche was observed in an eelgrass-red mangrove connected habitat when compared with more exposed white mangrove areas. Low dependence on mangrove habitats in temperate estuaries is likely due to their tidally dominated inundation and limited refuge potential due to smaller area coverage by mangroves in temperate estuaries. Relatively lower primary productivity in warm temperate mangrove areas, relative to their tropical counterparts, provides no significant feeding advantage or refuge opportunities relative to other available habitats in these estuaries. Warm temperate estuaries, which are both spatially and temporally highly variable, instead host species which are habitat generalists, able to capitalise on these highly dynamic environments.

Crabs are conspicuous inhabitants of temperate salt marshes and tropical mangroves and interact with their environment through several processes. However, detailed information on crab community processes is absent for most South African estuaries and nearshore coastal regions. This study evaluated the primary producers supporting crab species in the salt marsh dominated Swartkops estuary and the mangrove Mngazana estuary. Various methods estimating crab abundances were also assessed in different microhabitats and the larval distribution of crabs in the coastal zone was also investigated. Various methods for estimating crab abundance have been employed in the past, each with its inherent biases. The microhabitat of a mangrove forest in Australia was structurally altered by the manipulation of the litter, pneumatophores and the associated algae. These alterations did not affect the behavioural activity or the numbers of crabs recorded in any of the experimental treatments by either visual counts or pitfall traps. However, the number of crabs caught in the pitfall traps differed between the sites. Species-specific behaviour which was not investigated in this study may bias crab abundance estimates when using pitfall traps and therefore requires further investigation. Benthic consumers inhabiting shallow coastal environments may ultimately have the origin of their nutrition in a number of possible sources. Isotopic and gut content analysis of Thalamita crenata and juvenile Scylla serrata in the Mngazana estuary in South Africa revealed that these two portunids are able to share a habitat by resource partitioning. Differences were noted for species-specific utilization of primary producers not only between seasons within a site, but also between sites. This highlighted the use of locally produced primary producers sustaining food webs in estuaries. Mangrove production in the Mngazana estuary is very important and contributes to most of the carbon in the underlying sediments in the mangrove forest. However, the relatively large number of species and biomass encountered in this estuary may also be attributed to the fact that the different species are able to exploit of a number of different resources. The variation in stable isotope analysis of the different crab species throughout the estuary indicated that these crabs able to occupy the same habitat by feeding on a number of different resources and may preferentially select for a specific primary producer. A stable isotope of crabs in the salt marsh Swartkops estuary indicated that the dominant primary producer sustaining crab communities may even take place on a relatively smallscale. Sesarma catenata found at the inner marsh site recorded more depleted carbon signatures than those encountered in the other sites approximately 100 m away, and reflected signatures similar to the locally-encountered inner marsh plants. The relatively enriched nitrogen signatures of the anthropogenically-impacted Swartkops estuary is an indication of extensive inputs due to urbanization and industrialization, in contrast to the relatively pristine Mngazana estuary which exhibited low nitrogen signatures. Emphasis has been placed on the abiotic component of the exchange of nutrients and energy, although living organisms may also be transported, both actively and passively, between ecosystems. Little variation in either species composition or abundance was found between seasons for the larval distribution of brachyuran crabs on the east coast of South Africa. Due to the lack of published larval descriptions, larvae could not be identified to species level and it was therefore not possible to identify whether the larvae were hatched or spawned in an estuary or in a marine environment, or whether the larvae originated in the northern tropical regions. Frequent wind-reversals which are common in this region may retain larvae close inshore and supply the southern temperate locations with larvae from the northern locations. In conclusion, this study has shown that in highly productive systems with a number of potential primary producers, the crabs that inhabit the estuary show a marked diversity in resource utilization which could potentially allow a number of closely related species to occupy different trophic levels. This study also highlights the importance of locally produced sources in an estuary, which may occur on very small scales and this needs to be factored in with the design of any future stable isotope studies of this nature.

生長於潮間帶的紅樹林是熱帶和亞熱帶地區最具生產力的生態系統之一。香港擁有十個紅樹品種，其覆蓋面積約共三百五十公頃。位於香港西北面的米埔是現時香港最大的紅樹林區。這片紅樹林及其鄰近濕地於一九九五年被列為拉姆薩爾重要的濕地。隨著經濟的迅速發展、污染及一些不可持續的開發，全球紅樹林的面積不斷地萎縮。而香港的紅樹也正面對城市發展及基建的直接威脅。因此，了解及監測紅樹林的生長狀況、覆蓋面積的轉變是紅樹林保育的基礎。遙感是具有成本效益和能提供及時數據的技術，在紅樹林的生態保育及監測上發揮著重要功能。 / 是次研究選擇位於米埔的紅樹林區。通過結合高光譜和雷達數據以及實地磡測，以達到三個目的。第一，利用模式辨認分析找出可提高品種辨識度的光譜帶及雷達數據。第二，把挑選出來的光譜帶及雷達數據組合，利用不同的分類法包括最大概似法、决策樹 C5.0演算法、類神經網路及支持向量機進行紅樹林的品種分類，並籍此測試各分類法的精度。第三，利用植被指數及雷達數據中取得的參數為獨立變量，而在野外點測的葉面積指數 (LAI) 為因變量，通過迴歸分析以估算整片紅樹林的葉面積指數，籍此了解紅樹林現時的生物物理狀況。 / 根據特徵選擇的結果，位於高光譜數據中的綠波段 (570nm, 580nm, 591nm及601nm)、紅波段 (702nm)、紅邊位 (713nm)、近紅外波段 (764nm及774nm)、 短波紅外波段 (1276nm, 1316nm及1629nm) 以及在不同季節取得的過濾後向散射數據是最能辨識品種差異。 / 據品種分類的結果顯示，單用多時後向散射特徵數據存在很大誤差。而在大多的情況下，單用光譜數據比起混合光譜及後向散射數據的分類表現為佳。但對於某些品種來說，後向散射數據能給予比較準確的預測。另外，在同數據組合下，分類法在訓練精度上沒有多大的分別。除了類神經網路分類法以外，其他分類法的測試精度總比其訓練精度低。這說明類神經網路模型比起其他分類法的模型要為穩定，而决策樹模型則被過度訓練。根據生產者及使用者精度分析，因為缺乏足夠的訓練樣本，桐花樹及海桑屬的精度較其他品種為低。 / 據不同植被指數的簡單線性迴歸模型顯示，利用三角植被指數 (TVI)及修正葉綠素吸納比例指數一 (MCARI 1) 對於葉面積指數的估算是最準確。相反地，葉面積指數與從雷達數據中取得的參數關係則比較弱。這表示單用雷達參數不能對葉面積指數進行準確的估算。在結合植被指數及雷達參數的多元逐步迴歸分析下，三角植被指數及在灰度共生矩陣下得出的角二階矩參數能減低葉面積指數估算的誤差。總結以上兩項分析，光譜及雷達數據在紅樹林的品種分類及葉面積指數估算上有互補的作用。 / Mangrove is one of the most productive ecosystems flourished in the intertidal zone of tropical and subtropical regions. Hong Kong has ten true mangrove species covering an approximate area of 350 hectares. Mai Po locating in the northwestern part of Hong Kong nourishes the largest mangrove stand and it was listed as a Wetland of Importance under the Ramsar Convention in 1995. Over the years, areas of mangrove have been shrinking globally due to development, pollution, and other unsustainable exploitation and Hong Kong was no exception. In Hong Kong, mangroves are usually sacrificed for urban development and infrastructure construction. Therefore, it is crucial to monitor their growth conditions, change of extent and possible unsustainable practices threatening their existence. Remote sensing being a cost-effective and timely tool for vegetation conservation is most suitable for such purpose. / Taking Mai Po as study area, this study acquired satellite-borne hyperspectral and radar data supplemented with in situ field survey to achieve three purposes. First, features from the remotely-sensed data that are significant to species discrimination were identified through pattern recognition. Second, selected features grouped into different subsets were used to delineate the boundary of mangrove species through supervised classification. In the meantime, classifiers including maximum likelihood (ML), decision tree C5.0 (DT), artificial neural network (ANN) and support vector machines (SVM) were tested for their accuracy performance. The third purpose is to understand the current biophysical condition of mangrove through leaf area index (LAI) modeling by regressing field-measured LAI against vegetation indices, backscatter and textural measures. / Results from feature selection revealed that hyperspectral narrowbands locating in green at 570nm, 580nm, 591nm, 601nm; red at 702nm; red-edge at 713nm; near infrared at 764nm and 774nm and shortwave infrared at 1276nm, 1316nm and 1629nm as well as the multi-temporal filtered backscatter captured in different seasons have high sensitivity to species difference. / Species-based classification using multi-temporal backscatter features alone do not provide a satisfactory accuracy. Comparatively, results from pure spectral bands have better overall accuracy than that from combining spectral and radar features. However, radar backscatter does improve accuracy of some species. Besides, all classifiers had similar variations of training accuracy under the same feature subset. However, the testing accuracy is much lower with the exception of ANN. Performance of ANN was more stable and robust than other classifiers while serious overtraining occurs for the DT classifier. Moreover, most species were mapped accurately as revealed by the producer’s and user’s accuracy with the exception of A. corniculatum and Sonneratia spp. due to deficiency of training samples. / Simple linear regression model with VIs revealed that triangular vegetation index (TVI) and modified chlorophyll absorption ratio index 1 (MCARI1) had the best relationship with LAI. However, weak relationship was found between field- measured LAI and radar parameters suggesting that radar parameters cannot be used as single predictor for LAI. Results from stepwise multiple regression suggested that TVI combined with GLCM-derived angular second moment (ASM) can reduce the estimation error of LAI. To conclude, the study has demonstrated spectral and radar data are complementarity for accurate species discrimination and LAI mapping. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wong, Kwan Kit. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 434-472). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / ACKNOWLEDGEMENTS --- p.II / ABSTRACT --- p.IV / 論文摘要 --- p.VI / TABLE OF CONTENTS --- p.VIII / LIST OF ABBREVIATIONS --- p.XIII / LIST OF TABLES --- p.XV / LIST OF FIGURES --- p.XVIII / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- BACKGROUND TO THE STUDY --- p.1 / Chapter 1.1.1 --- Mangrove Mapping and Monitoring --- p.1 / Chapter 1.1.2 --- Mangrove Mapping and Monitoring --- p.3 / Chapter 1.1.3 --- Role of Remote Sensing in Mangrove Study --- p.4 / Chapter 1.2 --- OBJECTIVES OF THE STUDY --- p.6 / Chapter 1.3 --- SIGNIFICANCE OF THE STUDY --- p.7 / Chapter 1.4 --- ORGANIZATION OF THE THESIS --- p.8 / Chapter CHAPTER 2 --- LITERATURE REVIEW --- p.10 / Chapter 2.1 --- INTRODUCTION --- p.10 / Chapter 2.2 --- FACTORS AFFECTING VEGETATION REFLECTANCE --- p.11 / Chapter 2.2.1 --- Foliar structure and principal constituents --- p.12 / Chapter 2.2.2 --- Foliar optical properties --- p.14 / Chapter 2.2.2.1 --- The visible region (400-700nm) --- p.14 / Chapter 2.2.2.2 --- The red edge (690-740nm) --- p.15 / Chapter 2.2.2.3 --- The near-infrared region (700-1300nm) --- p.16 / Chapter 2.2.2.4 --- The short-wave infrared region (1300-2500nm) --- p.17 / Chapter 2.2.3 --- Canopy architecture --- p.18 / Chapter 2.2.4 --- Background reflectance --- p.19 / Chapter 2.2.5 --- Atmospheric perturbation --- p.20 / Chapter 2.2.6 --- Sun-sensor relationship --- p.22 / Chapter 2.3 --- HYPERSPECTRAL IMAGING AND VEGETATION CLASSIFICATION --- p.23 / Chapter 2.4 --- RADAR IMAGING AND VEGETATION CLASSIFICATION --- p.31 / Chapter 2.5 --- PATTERN RECOGNITION FOR VEGETATION CLASSIFICATION --- p.39 / Chapter 2.5.1 --- The Hughes Phenomenon and Dimensionality Reduction --- p.39 / Chapter 2.5.2 --- Statistical Pattern Recognition and Feature Selection --- p.44 / Chapter 2.5.2.1 --- Search Method --- p.47 / Chapter 2.5.2.1.1 --- Exhaustive search --- p.48 / Chapter 2.5.2.1.2 --- Branch and bound --- p.49 / Chapter 2.5.2.1.3 --- Sequential forward/ backward selection --- p.55 / Chapter 2.5.2.1.4 --- Sequential Floating search --- p.57 / Chapter 2.5.2.1.5 --- Oscillating Search --- p.61 / Chapter 2.5.2.1.6 --- Genetic algorithm --- p.64 / Chapter 2.5.2.2 --- Evaluation criteria --- p.66 / Chapter 2.5.2.2.1 --- Distance measure --- p.67 / Chapter 2.5.2.2.2 --- Information measure --- p.68 / Chapter 2.5.2.2.3 --- Classification error --- p.71 / Chapter 2.5.2.3 --- Feature Selection Stability --- p.72 / Chapter 2.5.3 --- Feature extraction --- p.75 / Chapter 2.6 --- BIOPHYSICAL PARAMETERS MEASUREMENT AND ESTIMATION --- p.77 / Chapter 2.6.1 --- Leaf Area Index (LAI) --- p.78 / Chapter 2.6.2 --- Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) --- p.79 / Chapter 2.6.3 --- In-situ Leaf Area Index Measurement --- p.81 / Chapter 2.6.3.1 --- Direct and Indirect Methods --- p.81 / Chapter 2.6.3.2 --- LAI Estimation through Gap Fraction Inversion --- p.85 / Chapter 2.6.3.3 --- Gap Fraction Ground Measurement --- p.89 / Chapter 2.6.3.3.1 --- LAI-2000 Plant Canopy Analyzer --- p.89 / Chapter 2.6.3.3.2 --- Hemispherical Photography --- p.92 / Chapter 2.6.3.4 --- Correction of Indirect LAI Measurement --- p.99 / Chapter 2.6.3.4.1 --- Clumping --- p.100 / Chapter 2.6.3.4.2 --- Mixture of Green and Non-green Elements --- p.101 / Chapter 2.6.4 --- Empirical Relationship with Spectral Vegetation Indices --- p.102 / Chapter 2.6.4.1 --- Traditional Vegetation Indices --- p.103 / Chapter 2.6.4.2 --- Leaf Area Index Estimation from Hyperspectral and Radar Images --- p.106 / Chapter 2.6.5 --- Physically-based Canopy Reflectance Model Inversion --- p.111 / Chapter 2.6.5.1 --- Canopy Reflectance Model --- p.111 / Chapter 2.6.5.2 --- Model Inversion and Biophysical Parameters Extraction --- p.115 / Chapter 2.7 --- SUMMARY --- p.118 / Chapter CHAPTER 3 --- METHODOLOGY --- p.120 / Chapter 3.1 --- INTRODUCTION --- p.120 / Chapter 3.2 --- STUDY AREA DESCRIPTION --- p.120 / Chapter 3.3 --- METHODOLOGICAL FLOW --- p.124 / Chapter 3.4 --- REMOTE SENSING DATA ACQUISITION AND PROCESSING --- p.127 / Chapter 3.4.1 --- Hyperion - EO-1 --- p.127 / Chapter 3.4.1.1 --- Radiometric correction --- p.127 / Chapter 3.4.1.1.1 --- Vertical strips removal --- p.128 / Chapter 3.4.1.1.2 --- Atmospheric correction --- p.129 / Chapter 3.4.1.1.3 --- Wavelength recalibration --- p.135 / Chapter 3.4.1.1.4 --- SNR enhancement through MNF --- p.137 / Chapter 3.4.1.2 --- Geometric correction --- p.139 / Chapter 3.4.1.3 --- Atmospheric correction algorithms comparison --- p.140 / Chapter 3.4.2 --- ASAR - ENVISAT --- p.141 / Chapter 3.4.2.1 --- Data Acquisition --- p.141 / Chapter 3.4.2.2 --- Data Processing --- p.143 / Chapter 3.4.2.2.1 --- Radiometric and Geometric Correction --- p.145 / Chapter 3.4.2.2.2 --- Speckle Filtering --- p.146 / Chapter 3.5 --- FIELD MEASUREMENTS AND DATA PROCESSING --- p.149 / Chapter 3.5.1 --- Species Distribution --- p.149 / Chapter 3.5.2 --- Leaf Spectra Measurement --- p.151 / Chapter 3.5.2.1 --- Leaf Collection and Handling --- p.152 / Chapter 3.5.2.2 --- ASD FieldSpec 3 Setup --- p.154 / Chapter 3.5.2.3 --- Laboratory setup --- p.156 / Chapter 3.5.2.4 --- Spectra Measurement --- p.158 / Chapter 3.5.2.5 --- Spectral similarity and variability --- p.159 / Chapter 3.5.3 --- In situ Leaf Area Index Measurement --- p.161 / Chapter 3.5.3.1 --- The optical instrument --- p.161 / Chapter 3.5.3.2 --- The LAI survey campaign p163 / Chapter 3.5.3.3 --- Data processing and canopy analysis --- p.166 / Chapter 3.5.3.4 --- Canopy parameter computation gap fraction, LAI, clumping index, mean inclination angle --- p.170 / Chapter 3.5.3.5 --- Field LAI and Their Correlation with Reflectance and Backscattering Coefficient Data Exploration --- p.175 / Chapter 3.6 --- FEATURE SELECTION --- p.175 / Chapter 3.6.1 --- Data Preprocessing and Preparation --- p.178 / Chapter 3.6.2 --- Data Format and Split --- p.183 / Chapter 3.6.3 --- Wrapper-based Approach --- p.185 / Chapter 3.6.4 --- Search Algorithm --- p.187 / Chapter 3.6.5 --- Stability Evaluation --- p.187 / Chapter 3.6.6 --- Feature Frequency analysis --- p.188 / Chapter 3.7 --- MANGROVE SPECIES CLASSIFICATION --- p.189 / Chapter 3.7.1 --- Species Separability --- p.193 / Chapter 3.7.2 --- Gaussian Maximum Likelihood Classifier --- p.193 / Chapter 3.7.3 --- Decision Tree Classifier --- p.194 / Chapter 3.7.4 --- Artificial Neural Network Classifier --- p.197 / Chapter 3.7.5 --- Support Vector Machines Classifier --- p.199 / Chapter 3.7.6 --- Accuracy Assessment --- p.204 / Chapter 3.8 --- LEAF AREA INDEX MODELING --- p.206 / Chapter 3.8.1 --- Preliminary Exploration of Relationship between Hyperspectral bands and LAI --- p.206 / Chapter 3.8.2 --- Vegetation Index Derived from Hyperspectral Data. --- p.206 / Chapter 3.8.3 --- Radar Backscatter and Derived Textural Parameters --- p.208 / Chapter 3.8.4 --- Regression Analysis --- p.211 / Chapter 3.8.5 --- Error Estimation --- p.217 / Chapter 3.9 --- SUMMARY --- p.218 / Chapter CHAPTER 4 --- RESULTS AND DISCUSSION (I) FEATURE SELECTION AND MANGROVE SPECIES CLASSIFICATION --- p.221 / Chapter 4.1 --- INTRODUCTION --- p.221 / Chapter 4.2 --- DATA PROCESSING AND EXPLORATION --- p.221 / Chapter 4.2.1 --- Atmospheric correction algorithms comparison --- p.222 / Chapter 4.2.2 --- Radar Data Speckle Reduction --- p.227 / Chapter 4.2.3 --- Statistical Discrimination of Mangrove Spectral Class --- p.230 / Chapter 4.3 --- FEATURE SELECTION --- p.249 / Chapter 4.3.1 --- Sequential Forward Selection (SFS) --- p.250 / Chapter 4.3.2 --- Sequential Floating Forward Selection (SFFS). --- p.256 / Chapter 4.3.3 --- Oscillating Search (OS) --- p.262 / Chapter 4.3.4 --- Search Algorithms comparison --- p.268 / Chapter 4.3.5 --- Final Subset Selection --- p.270 / Chapter 4.3.6 --- Correlation Analysis --- p.280 / Chapter 4.4 --- IMAGE CLASSIFICATION --- p.283 / Chapter 4.4.1 --- Mangrove Spectral Class Separability --- p.284 / Chapter 4.4.2 --- Gaussian Maximum Likelihood (ML) --- p.288 / Chapter 4.4.3 --- Decision Tree (DT) --- p.297 / Chapter 4.4.4 --- Artificial Neural Network (ANN) --- p.304 / Chapter 4.4.5 --- Support Vector Machines (SVM) --- p.312 / Chapter 4.4.6 --- Algorithm Comparison --- p.321 / Chapter 4.5 --- DISCUSSION AND IMPLICATION --- p.325 / Chapter 4.5.1 --- Feature Selection --- p.325 / Chapter 4.5.2 --- Mangrove Classification --- p.342 / Chapter 4.6 --- SUMMARY --- p.351 / Chapter CHAPTER 5 --- RESULTS AND DISCUSSION (II) - LEAF AREA INDEX MODELING --- p.353 / Chapter 5.1 --- INTRODUCTION --- p.353 / Chapter 5.2 --- DATA EXPLORATION --- p.353 / Chapter 5.2.1 --- Dependent Variable: Field measured LAI --- p.353 / Chapter 5.2.2 --- Independent Variables: Vegetation Index and texture measure --- p.355 / Chapter 5.2.3 --- Hyperspectral bands and LAI --- p.356 / Chapter 5.2.4 --- Normality testing --- p.359 / Chapter 5.2.5 --- Linearity testing --- p.363 / Chapter 5.2.6 --- Outliner detection --- p.365 / Chapter 5.3 --- SIMPLE LINEAR REGRESSION ANALYSIS --- p.366 / Chapter 5.3.1 --- LAI2000 Generalized method --- p.369 / Chapter 5.4 --- STEPWISE MULTIPLE REGRESSION ANALYSIS --- p.381 / Chapter 5.4.1 --- LAI2000 Generalized method --- p.384 / Chapter 5.5 --- DISCUSSION AND IMPLICATION --- p.391 / Chapter 5.5.1 --- LAI model comparison --- p.391 / Chapter 5.5.2 --- Species composition and LAI --- p.393 / Chapter 5.5.3 --- Hyperspectral Bands, Vegetation Indices and LAI --- p.397 / Chapter 5.5.4 --- Backscatter, texture measures and LAI --- p.407 / Chapter 5.5.5 --- Complementarity of Vegetation Index and Radar Parameters --- p.414 / Chapter 5.6 --- SUMMARY --- p.421 / Chapter CHAPTER 6 --- CONCLUSION --- p.423 / Chapter 6.1 --- SUMMARY OF THE STUDY --- p.423 / Chapter 6.2 --- LIMITATION OF THE STUDY --- p.427 / Chapter 6.3 --- RECOMMENDATION --- p.431 / Chapter REFERENCE --- p.434 / Chapter APPENDIX A --- GEOMETRIC CORRECTION OF HYPERSPECTRAL DATA --- p.473 / Chapter APPENDIX B --- SCRIPTS DERIVED FROM FEATURE SELECTION TOOLBOX (FST) FOR FEATURE SELECTION --- p.475 / Chapter APPENDIX C --- PREDICTED LAI(BON) AND LAI(2000) FROM SIMPLE LINEAR REGRESSION MODELS --- p.513 / Chapter APPENDIX D --- PREDICTED LAI(BON) AND LAI(2000) FROM MULTIPLE STEPWISE REGRESSION MODELS --- p.524

The vegetation of the Mgeni Estuary, Mhlanga Estuary and Mdloti Estuary was analysed according to the Braun-Blanquet phytosociological method using quadrats of 4m2 and 25m2 in area placed subjectively and the Point-Centred Quarter method with points chosen whilst traversing. A classification of plant communities is given. These are described floristically and related to habitat variables. Indicator species of the climatic climax of coast forest occur within the study area. The absence of coast forest is ascribed to low altitude, tidal inundation and the consequent effect of salinity, basal inundation resulting in a high water-table and the influence of man. The floodplain of the Mgeni Estuary is dominated by mangrove vegetation comprising mainly Bruguiera gymnorrhiza and Avicennia marina whereas vegetation established on Athlone Island is dominated by mesophytic thicket comprising mainly Schinus terebinthifolius, Lantana camara, Chromolaena odorata and Cardiospermum grandiflorum. The floodplain of the Mhlanga Estuary is dominated by Phragmites australis. The shores of the Mdloti Estuary are dominated by Barringtonia racemosa, Phragmites australis and Echinochloa pyramidalis. Major differences in vegetation patterns of the three systems are related primarily to the differences in the open nature of the river mouths. This is controlled mainly by river flow and longshore drift. Differences in vegetation patterns within an estuary are dependent on differences in tolerances to salinity, basal inundation and shade, together with variations in altitude and edaphic factors and competition between species. Generally soils of Mgeni Estuary had higher contents of small sized fractions, bulk densities, reserve acidities, organic matter, salts and exchangeable bases and lower pH than soils at Mhlanga Estuary and Mdloti Estuary. Differences exist between mangrove and non-mangrove soils at Mgeni Estuary and differences between the non- mangrove soils at the three study sites. Major differences in soil characteristics are as a result of differences in tidal inundation, geogenetic parameters and biotic factors. Information on topography, hydrology, geology, climatic factors, biotic factors and historical background of the area is given. A check-list of vascular plants is included. The work is illustrated by 44 figures. / Thesis (M.Sc.)-University of Durban-Westville, 1986.

There are large gaps in the coverage of critical ecological processes related to the movement of individuals or genes (i.e. dispersal), which is critical for determining the spread and persistence of populations across space. In this dissertation we investigate understudied but important aspects of the dispersal process in mangroves, with as the main objective the reduction of parameter and model uncertainty. Models rarely incorporate realism and complexity at the level of emigration, transfer and immigration phases, hampering reliable predictions of dispersal patterns and long-term population dynamics under different climate change scenarios. <p><p>Mangrove ecosystems function at the edge of land and sea, often covering large intertidal areas along (sub)tropical coastal regions worldwide. Mangroves can live in these highly dynamic and demanding environmental conditions via a series of remarkable adaptations. They produce buoyant seeds and fruits (propagules) that disperse at the ocean surface (i.e. hydrochory - see cover image). <p><p>Despite their ecological and economical value, about 40 % of original mangroves have been lost worldwide during the last 50 years due to excessive exploitation and development. Deforestation, degradation and conversion to other land uses like intensive shrimp farming and agriculture have reduced and fragmented these ecosystems at an alarming rate. Climate change, probably most pronouncedly via changes in sea level, poses another important threat. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Macrozoobenthic community structure and composition was investigated along a subtidal-intertidal gradient in the Mngazana Estuary. Six transects were sampled between the spring high water mark (HWST) and the bottom of the river channel in the lower estuary. Fifteen replicate samples were collected along each transect using a Van Veen type grab (211 cm2 bite) during each of three sampling sessions. Samples were sieved through a 500 μm mesh bag and the invertebrates stored in bottles for further analysis in the laboratory. Additional grab samples were collected for sediment particle size analysis and organic matter. Physical variables measured at each transect included: salinity, temperature, dissolved oxygen, depth, pH, percentage mud, organic content and turbidity. Sediment compactness was measured at all intertidal transects and additional sediment samples were collected at mid shore and high shore transects for percentage water content analysis. A total of 104 species were recorded along the intertidal-subtidal gradient in the sampling area. Species richness was higher in the subtidal zone compared to the intertidal zone and polychaetes numerically dominated the macrozoobenthic community at most transects, during all three sessions. At high shore transects the community was characterised by having fewer species, consisting mostly of brachyurans, polychaetes and gastropods. Shannon diversity index (H’) was generally higher for subtidal transects (x¯ = 2.3; range: 2.8 to 1) than for intertidal transects (x¯ = 1.4; range: 2.2 to 0.6) indicating that the distribution of individuals among species in the intertidal zone experienced greater variability. Results for Hill’s numbers followed the same trend as Shannon diversity with subtidal communities mostly consisting of abundant species followed by very abundant species. Intertidal communities generally exhibited lower numbers of abundant and very abundant species. Sedimentary characteristics played a major role in structuring benthic communities in comparison to other physico-chemical variables. Organic content and mud content of the substrate were identified as important factors influencing community patterns observed along the subtidal-intertidal gradient. In addition, sediment compactness and water content of the substrate was found to influence intertidal community structure. Subtidal community structure possibly had a greater dependence on seasonal variations in abiotic and/or biotic factors. Cluster dendrograms used in conjunction with MDS ordination mapping revealed that macrozoobenthic communities were generally distinct between high shore intertidal transects iii and subtidal transects. Most species exhibited a broad spatial distribution along the subtidal-intertidal gradient with mid and high shore transects being the exception. Most species also exhibited marked shifts in abundance and this was especially noticeable at the transition between the subtidal and intertidal zone. Two polychaete species, Prionospio sexoculata and Capitella capitata, were very abundant species and featured amongst the most numerically dominant species collected during each sampling session.

In South Africa mangrove forests are located in estuaries from Kosi Bay in KwaZulu-Natal (KZN) to Nahoon Estuary in the Eastern Cape. The aims of this study were to determine the present state of mangroves in KwaZulu-Natal, by assessing the current population structure, the changes in cover over time and associated anthropogenic pressures. A second objective of this study was to determine the effect of harvesting on the population structure and sediment characteristics in the Mngazana mangrove forest. To determine if harvesting was sustainable at Mngazana Estuary; the growth and mortality rates and associated growth conditions were measured. Finally by using population modelling sustainable harvesting limits were determined by predicting the change in population structure over time. The study focussed on the KwaZulu-Natal province as a fairly recent study addressed mangrove distribution and status in the Eastern Cape Province. A historical assessment of all mangroves forests in KwaZulu-Natal (KZN) revealed that the potential threats to mangroves in South Africa include; wood harvesting, altered water flow patterns coupled with salinity changes, prolonged closed-mouth conditions and subsequent changes to the intertidal habitat. As a result mangroves were completely lost from eleven estuaries in KZN between 1982 and 1999 and a further two estuaries by 2006. Mangroves only occurred in those estuaries where the mouth was open for more than 56 percent of the time with the exception of St Lucia, where the mouth has been closed for longer but the mangrove communities have persisted because the roots of the trees were not submerged. All mangrove forests in KZN were regenerating in terms of population structure as they had reverse J-shaped population curves as well as high adult: seedling ratios. Kosi Bay and Mhlathuze Estuary were two of the larger forests that showed signs of harvesting (presence of tree or branch stumps), but the greatest threat to smaller estuaries seems to be altered water flow patterns due to freshwater abstraction in the catchments and the change of land use from natural vegetation to sugar-cane plantations. These threats affect the hydrology of estuaries and the sediment characteristics (particle size, redox, pH, salinity, temperature) of the mangrove forests. The environmental conditions under which the mangrove forests currently exist were determined for five species. Lumnitzera racemosa and Ceriops tagal exhibited a narrow range of conditions as these species are only found at Kosi Bay, while Avicennia marina, Bruguiera gymnorrhiza and Rhizophora mucronata were found to exist under a wider range of conditions. The growth rate and response to environmental conditions of the three dominant species were important to determine as these species are impacted by harvesting. Mangrove growth rates were measured at Mngazana Estuary in the Eastern Cape, the third largest mangrove forest in South Africa. Areas of this estuary where mangroves harvesting has occurred, show significant differences in sediment characteristics as well as changes in population structure in harvested compared to non harvested sites. The growth rate (in terms of height) of Avicennia marina individuals increased from seedlings (0.31 cm month-1) to adults (1.2 cm month-1), while the growth of Bruguiera gymnorrhiza stabilised from a height of 150 cm at 0.65 cm month-1. The growth of Rhizophora mucronata peaked at 0.72 cm month-1 (height 151-250 cm) and then decreased to 0.4 cm month-1 for taller individuals. Increases in diameter at breast height (DBH) ranged between 0.7 and 2.3 mm month-1 for all species. Some environmental variables were found to be important drivers of growth and mortality of individuals less then 150 cm. A decrease in sediment pH significantly increased the mortality of Avicennia marina seedlings (0-50 cm) (r = - 0.71, p<0.05) and significantly decreased the growth of Rhizophora mucronata and Bruguiera gymnorrhiza seedlings (r = -0.8, r = 0.52 – p < 0.05 respectively). At Mngazana Estuary, mortality of this species showed a positive correlation with sediment moisture content indicating that this species prefers drier conditions. The density of Rhizophora mucronata was significantly correlated to porewater temperature in Northern KZN as was the growth of adult (>300 cm) Rhizophora trees at Mngazana Estuary. Mortality of Avicennia marina individuals (51-150 cm) was related to tree density indicating intraspecific competition and self thinning. Selective harvesting of particular size classes of Rhizophora mucronata was recorded when comparing length of harvested poles (~301 cm) and the size class distribution of individuals. Taking into account the differences in growth rate for each size class for this species it will take approximately 13 years to attain a height of 390 cm which is the height at which trees are selected for harvesting at this estuary. This is 2.6 times slower than those individuals growing in Kenya. The feasibility of harvesting is dependent on the growth rate of younger size classes to replace harvested trees as well as the rate of natural recruitment feeding into the population. Different harvesting intensity scenarios tested within a matrix model framework showed that limits should be set at 5 percent trees ha-1 year-1 to maintain seedling density at > 5 000 ha-1 for R. mucronata. However harvesting of Bruguiera gymnorrhiza should be stopped due to the low density of this species at Mngazana Estuary. Harvesting of the tallest trees of Avicennia marina can be maintained at levels less than 10 percent ha-1 year-1. Effective management of mangrove forests in South African is important to maintain the current state, function and diversity of these ecosystems. Management recommendations should begin with determining the freshwater requirements of the estuaries to maintain the mouth dynamics and biotic communities and deter the harvesting of (whole) adult trees particularly those species that do not coppice. Further management is needed to ensure that forests are cleared of pollutants (plastic and industrial), and any further developments near the mangroves should be minimized.

Orientador: Silvia Rodrigues Machado / Coorientador: Camilla Rozindo Dias Milanez / Resumo: A poluição por metais tem sido um dos principais problemas ambientais, tendo em vista a sua toxicidade, persistência no ambiente e bioacumulação. Os manguezais frequentemente são expostos a esses contaminantes, sendo o ferro um dos metais presentes em maior concentração no sedimento e com papel biogeoquímico importante quanto à precipitação e ciclagem de metais. Investigamos o acúmulo, a distribuição e a eliminação de ferro em Avicennia schaueriana Stapf & Leechm. ex Modenke, Laguncularia racemosa (L.) C.F. Gaertn. e Rhizophora mangle L. submetidas a diferentes concentrações de ferro. Para esse estudo, propágulos das três espécies estudadas foram coletados em campo e cultivados em meio nutritivo de Hoagland. Após o cultivo, as plantas foram submetidas a quatro tratamentos pela adição de 0 (controle), 10, 20 e 100 mg L-1 de Fe(II)SO4 no meio nutritivo. As plantas foram então coletadas, sendo realizadas análises químicas, anatômicas, histoquímicas e ultracitoquímicas. Parte dessas análises também foi feita em campo para comparação dos dados. Os resultados mostraram que a placa de ferro é local de grande acúmulo de ferro nessas plantas. L. racemosa foi a espécie que mais acumulou ferro em placa e raízes, enquanto A. schaueriana apresentou os níveis mais altos em caules e folhas. A bioacumulação de ferro em placa e raízes de L. racemosa aumentou progressivamente à medida que a concentração de ferro no substrato aumentou. A secreção de ferro por glândulas de sal ocorreu e foi fort... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Metal pollution has long been one of the major environmental problems due to its toxicity, environmental persistence and bioaccumulation. Mangroves are often exposed to these contaminants, and iron is one of the metals present in higher concentrations in sediments and has an important biogeochemical role as regards the precipitation and cycling of metals. We investigate the iron accumulation, distribution and elimination in Avicennia schaueriana Stapf & Leechm. ex Modenke, Laguncularia racemosa (L.) CF Gaertn. and Rhizophora mangle L. exposed to different concentrations of iron. For this study, propagules of all species were collected in field and were cultivated in Hoagland's nutritive medium. After growing, plants were exposed to four treatments by adding 0 (control), 10, 20 and 100 mg L-1 of Fe(II)SO4 to the nutritive medium. Then, plants were collected and chemical, anatomical, histochemical and ultracitochemical analysis were carried out. Part of these analyses was also made in the field for data comparison. The results showed that the Fe-plaque is a place of high iron accumulation in these plants. L. racemosa accumulated the highest amounts of iron in the plaque and roots, while A. schaueriana presented the highest levels in stems and leaves. The bioaccumulation of iron in plaque and roots of L. racemosa increased progressively as the added-iron concentration rose. The iron secretion through salt glands occurred and it was strongly inhibited in L. racemosa at iron concentrations above controls, while A. schaueriana did not show a noticeable drop from controls to the highest added-iron concentration used. In general, L. racemosa presented the lowest translocation factors among the three studied species. With the increase of iron in the substrate, there was a drop in translocation factors between aerial parts and root... (Complete abstract click electronic access below) / Doutor