Teses / dissertações sobre o tema "Spice plants – geographical distribution"

Models that are used for predicting species' potential distributions are important tools that have found applications in a number of areas of applied ecology. The majority of these models can be classified as correlative, as they rely on strong, often indirect, links between species distribution records and environmental predictor variables to make predictions. Correlative models are an alternative to more complex mechanistic models that attempt to simulate the mechanisms considered to underlie the observed correlations with environmental attributes. This study explores the influence of the type and quality of the data used to calibrate correlative models. In terms of data type, the most popular techniques in use are group discrimination techniques, those that use both presence and absence locality data to make predictions. However, for many organisms absence data are either not available or are considered to be unreliable. As the available range of profile techniques (those using presence only data) appeared to be limited, new profile techniques were investigated and evaluated. A new profile modelling technique based on fuzzy classification (the Fuzzy Envelope Model) was developed and implemented. A second profile technique based on Principal Components Analysis was implemented and evaluated. Based on quantitative model evaluation tests, both of these techniques performed well and show considerable promise. In terms of data quality, the effects on model performance of false absence records, the number of locality records (sample size) and the proportion of localities representing species presence (prevalence) in samples were investigated for logistic regression distribution models. Sample size and prevalence both had a significant effect on model performance. False absence records had a significant influence on model performance, which was affected by sample size. A quantitative comparison of the performance of selected profile models and group discrimination modelling techniques suggests that different techniques may be more successful for predicting distributions for particular species or types of organism than others. The results also suggest that several different model design! sample size combinations are capable of making predictions that will on average not differ significantly in performance for a particular species. A further quantitative comparison among modelling techniques suggests that correlative techniques can perform as well as simple mechanistic techniques for predicting potential distributions.

The results of a community survey of the rocky intertidal and subtidal reef ichthyofauna of the Tsitsikamma National Park and adjacent areas are presented. An updated species checklist is given, comprising 116 species of 46 families, including a new genus and species of Tripterygiid. Single species are shown to dominate, in terms of numbers, both the cryptic and subtidal components for all the areas sampled down the vertical profile. Species richness, evenness and diversity are found to increase with depth for both the cryptic and suprabenthic components. A community level feeding study shows an increase in trophic specialisation with depth and food availability is found to be an important factor delimiting littoral fish vertical distribution. The nursery function of the Tsitsikamma rocky littoral area is assessed and it is shown that shallow littoral areas as a whole are more important than intertidal pools alone in functioning as nurseries. The results of the study are found to fit into the existing trend of an increase in species richness and diversity, from west to east, along the South African coast. A significant difference is shown between the observed frequencies of species on exploited reefs outside the Park and unexploited reefs inside the Park. The density of the key reef predator Petrus rupestris is shown to be nine times more abundant on deep reef inside the park compared to deep reef outside the park (0.0045 fish/m² and 0.0005 fish/m² respectively) and a paucity of larger individuals of this species on exploited reefs is noted. Marked differences in the relative abundance of other species between exploited and unexploited reefs are evident and it is hypothesised that community disruption has occurred on exploited reefs, either directly or indirectly because of the removal of P. rupestris. These results are discussed in the context of marine reserves as a conservation strategy and a recommendation is made to extend the 5.6km seaward boundary of the Tsitsikamma National Park westwards to include the large concentration of presently exploited rocky reefs between the Blaaukrans river mouth and Natures Valley.

We are facing an ever-increasing environmental crisis on our planet, with multiple threats from humankind. Industrialisation, deforestation, overpopulation and exploitation of our natural resources is driving species to extinction and changing the environment we live in. We need to plan for the future in order to adapt or mitigate these risks. Recent advances in computing and analytical techniques, plus the rise of readily available spatial data, provide us with a means to understand the complex interactions between species, environmental change and human activity. Coffea arabica (Arabica coffee) is a critically important crop species in several tropical countries. Globally its export value is over $13 billion dollars per year. Wild populations of this species are of immense importance to the global coffee sector, due to the traits associated with the standing genetic diversity, such as disease resilience, new flavour profiles, and agronomically favourable morphological variation (root length; compact habit). In its countries of origin, Ethiopia and South Sudan, the wild species provides the planting stock for a multi-million-dollar export sector. Arabica coffee is well known across the globe, as the increasingly popular beverage coffee. The ubiquitous cultural nature of coffee drinking means that coffee acts as a flagship species for demonstrating science and the benefits of conservation and sustainable use, enabling the findings of this thesis to gain traction with a wider audience, who might otherwise not engage with research and social and environmental issues. Coffea arabica is greatly influenced by climate. The wild and cultivated variants of this species are restricted to a relatively narrow climate niche, within Ethiopia and anywhere where it is cultivated. Coffee production is considerably influenced by changes in rainfall, temperature or seasonality. Ethiopia has already experienced climate change; mean temperatures from the 1960s onwards show an average increase of 0.28 °C per decade, a shortening wet season, and an increase in the number of hot days. The continuation of this rapid change in climate will influence both wild populations and production of Arabica coffee in Ethiopia. Within this thesis I forecast the fate of wild and cultivated Arabica coffee in Ethiopia, under climate change, reviewing risks and opportunities from the recent past until the end of the century. To do this I developed several novel methods, which are initially used to project the future of wild and cultivated coffee cultivation in Ethiopia. For the wild species, I have developed several new spatial techniques, particularly dealing with the issue of the “modifiable areal unit problem” within species extinction risk assessments. I have updated and refined existing techniques into one package, allowing multiple future climate scenarios/projections to be processed and assessed quickly. I present my scientific findings in the form of five submitted manuscripts (see ‘List of original articles’, on p.8). Using the findings, results and recommendations from these papers, I repurpose the outputs and impact of the science, graphically and within various media (including two more manuscripts, media and social media), for multiple audiences. Using these spatial techniques and visualisations, I show the impact climate change will have on Arabica coffee in Ethiopia, both as a crop and as a wild species within the humid forests of the country. I show that the present coffee-growing areas could be reduced by up to 60% if no interventions are made, but conversely, that there is an opportunity to increase the coffee growing area of Ethiopia four-fold if the right actions are taken. For wild Arabica coffee I show that the species is threatened with extinction due to climate change. Specifically, I show that wild Arabica coffee would be assessed as Least Concern (under little or no risk; IUCN Extinction Red List) if climate change is not factored in, as opposed to Endangered (threatened with extinction) if climate change is included in an extinction risk assessment. The work in this thesis demonstrates the power of spatial analysis, modelling, and high data quality, for plant conservation.

Invasive plant species are an increasing global threat to native biodiversity. Effective management depends on accurate predictions of their spread. However, modelling the geographic distribution of invasive species, particularly with methods like correlative species distribution models (SDMs), is challenging. SDMs operate under the assumption that species are in equilibrium with their environment (i.e., they occur in all suitable environments); this assumption is more likely to be violated for a species that is still in the process of colonizing suitable environments. SDMs also assume that environmental constraints are the most important factors determining a species' distribution. However, these assumptions are not commonly assessed, and when violated can have consequences for model reliability. I investigated SDM performance and equilibrium in the invasive Vincetoxicum rossicum vine in northeastern North America. Vincetoxicum rossicum has a long, detailed history of occurrence records in its invaded range, which enabled me to observe trends in equilibrium and model performance over a relatively long time scale. I tested the hypotheses that: 1) invasive species approach equilibrium in environmental and geographic space over time; 2) SDM performance will increase as V. rossicum approaches environmental equilibrium; and 3) range expansion in the early stages of an invasion is primarily a function of dispersal rather than environmental constraints, while the reverse is true in later stages. I found that V. rossicum has reached equilibrium in environmental space, but is still expanding its geographic range. SDM performance was poor in the first 30 years following introduction, but then improved as V. rossicum approached environmental equilibrium. SDMs were outperformed by spatial dispersal models in the earliest time period, however, the reverse was true for all subsequent time periods. Overall, these results suggest that V. rossicum’s distribution is becoming more stable and more predictable over time and that models built using the most recent data for this species, will be the most transferable across time and space. Additionally, my findings highlight the need for researchers modelling invasive species’ distributions to consider the inherent assumptions, biases, and unique features related to SDMs and SDMs of invasive species.

Ecological research aimed at the conservation of useful plants has rarely considered the spatial distribution of resources nor the potential implications for management. In this thesis I examined the spatial patterning of a group of 23 useful plant species on the 3,500 ha territory of a Kuna community in Darien, Panama. A systematic random sampling scheme was used to survey the distribution and abundance of the species, as well as the physical environment. A series of canonical analyses was conducted to evaluate the species-environment relationships and to identify spatial structures in the species distributions left unexplained by the environmental variables. Four distinct distribution patterns were identified among the species; these were most strongly explained by land-use, the degree of canopy closure and topography. Significant spatial structures, independent of the environmental variables, were related to anthropogenic pressures and an edaphic gradient. The habitat associations of the individual species are described and data on one species, Sabal mauritiiformis , is used to illustrate the utility of these data in the management of plant resources on human landscapes.

A new sampling method that decouples spatial and environmental correlations was developed and applied to a temperate forest understory. Data were used to contrast niche theory with neutral theory, and only showed support for niche theory. A spatial and environmental partitioning analysis indicated that the effects of dispersal are primarily important within the spatial extent of environments suitable for a given species. The same sampling data were used to test correlates of non-native species invasion at a species level and as a group. The distributions of non-native plant species are also better explained by the niche model; however, non-native species do not appear to negatively impact native species, nor to be negatively impacted by native species. Together, these results suggest that the forest understory is strongly niche-structured, but likely not saturated. Diversity in this forest appears to be primarily determined by regional processes, and only secondarily by local species interactions.

Thesis (MSc)--University of Stellenbosch, 2005.
ENGLISH ABSTRACT: This project consists of two botanical investigations in an agricultural area of the Western Cape Province. A farm known as De Rust, in the Elgin Valley, was used to sample the geographic location, density, height and life stage of six prominent invasive plant species in various land-use categories. In the first investigation, the density, height and age structures of the six invasive species populations were analyzed. The density distribution of the six species was also displayed cartographically. Species were then ranked according to the potential threat that they pose to the conservation of the remaining natural areas on the farm. Results indicated that Acacia mearnsii and Acacia saligna are the major invaders at De Rust and that Hakea sericea can be considered as an emerging invader. The second investigation explores the statistical relationship between the various land-use categories and density, height and age of the six prominent invaders identified in the first investigation. The loglikelihood ratio analysis of observed frequencies resulted in statistically significant (P<0.01; P-values range between 1.35 x 10-3 and 2.7 x 10-224) relationships between certain land-use types and certain invasive species. A conclusion was reached that it could be useful to include land-use categories in simulation models of invasive plant species distribution and spread.
AFRIKAANSE OPSOMMING: Hierdie projek behels twee botaniese ondersoeke in ‘n landbou gebied van die Weskaap. Die plaas bekend as De Rust, in die Elgin Vallei, was gebruik vir die versameling van data te doen met die geografiese ligging, plant digtheid, lengte en lewens stadium van ses prominente indringer plant spesies in verskeie landgebruik kategorieë. Die digtheid, lengte en ouderdomstruktuur van ses indringerspesies was in die eerste ondersoek geanaliseer. Die verspreiding van digtheid was ook in kaarte uitgelê. Spesies was daarna volgens hulle potentiële dreiging teen die bewaring van oorblywende natuurlike dele van die plaas in ‘n rangorde geplaas. Resiltate dui aan dat Acacia mearnsii en Acacia saligna die belangrikste indringer plante op De Rust is en dat Hakea sericea as ‘n opkomende indringer beskou kan word. Die tweede ondersoek kyk na die verhouding tussen verskeie grondgebruik kategorië en die digtheid, lengte en ouderdom van die ses prominente indringer spesies wat in die eerste ondersoek identifiseër is. ‘n Log tipe ratios ontleding van bewaarde frekwensies het ‘n statisties belangrike uitkoms gehad (P<0.01; P-waardes tussen 1.35 x 10-3 en 2.7 x 10-224) vir die verhoudings tussen sekere grondgebruik tipes en sekere indringer spesies. Die gevolgtrekking was dat dit handig mag wees om grondgebruik kategorieë in simulasies van indringer plant verspreiding te gebruik.

When considering the large amount of work done on dune ecology, and that a number of the classical ecological theories originate from work on dunes, it is apparent that there remains a need for physiological and mechanistic explanations of dune plant phenomena. This thesis demonstrated that in the extreme coastal environment dune plants must survive both high rates of burial (disturbance), and low nutrient availability (stress). The ability of four species to respond to these two factors corresponded with their position in a vegetation gradient on the dunes. A low stem tissue density was shown to enhance the potential stem elongation rate of buried plants, but reduced the maximum height to which a plant could grow. Such a tradeoff implies that tall light-competitive plants are able to survive only in stable areas, while burial responsive mobile-dune plants are limited to areas of low vegetation height. This stem tissue density tradeoff was suggested as the mechanism determining the zonation that species show within the dune vegetation gradient present at various sites in South Africa. Finally, detailed investigations of dune plant ecophysiology found that: 1) The resources used in the response to burial derive from external sources of carbon and nitrogen, as well as simple physiological and physical mechanisms of resource allocation. 2) The leaves of dune plants were found to be operating at one extreme of the photosynthetic continuum; viz efficient use of leaf nitrogen at the expense of water loss. 3) Contrary to other ecosystems, the environmental characteristics of dunes may allow plants to occupy a high disturbance, high stress niche, through the maintenance of lowered competition. 4) At least two mobile-dune species form steep dunes, and are able to optimise growth, on steeper dunes, such that they have to grow less in response to burial than plants that form more shallow dunes. In this thesis, it was shown that the link between the carbon and nitrogen economies of dune plants was pivotal in determining species distributions and survival under extreme environmental conditions. As vast areas of the world’s surface are covered by sand dunes these observations are not just of passing interest.

No presente trabalho foram estudadas 8 espécies lenhosas dos gêneros Cinchona (C. amazonica Standl.), Croton (C. billbergianus Müll.Arg., C. floribundus Spreng., C. lechleri, Müell.Arg., C. matourensis Aubl., C. palanostigma Klotzsch) e Uncaria (U. guianensis (Aubl.) J.F. Gmel. e U. tomentosa (Willd. ex Roem. & Schult.) DC.) de interesse medicinal e ocorrentes no Estado do Acre, Brasil. Dessas plantas foram analisadas as características dendrológicas, a estrutura anatômica do lenho, sua distribuição geográfica e “status” de conservação. A pesquisa consistiu de visitas de campo a diferentes regiões do Estado, coleta de material botânico e do lenho das plantas, levantamento e estudo das exsicatas das espécies em herbários nacionais e internacionais da América do Sul, revisão bibliográfica das espécies na literatura e “sites” especializados, descrição dos parâmetros dendrológicos e da estrutura antômica do lenho das espécies em laboratório, possibilitando a identificação das espécies dos 3 gêneros. As características dendrológicas vegetativas das plantas mostraram variações, resultado das adaptações ao meio ambiente, da idade e de sua ampla distribuição geográfica. A estrutura anatomica do lenho foi mais distinta entre famílias (Euphorbiaceae e Rubiaceae) e gêneros (Cinchona, Croton, Uncaria) e menos nas espécies, constituindose em parâmetro importante e auxiliar na sua identificação. As plantas de Cinchona amazonica apresentaram baixa intensidade populacional, embora com ampla distribuição no Estado do Acre, em outros estados brasileiros e nos países amazônicos. No gênero Croton, as plantas de C.palanostigma mostraram distribuição quase pontual no Acre e extensa na Amazônia e menos ampla na América Latina; C. floribundus com ocorrência pontual no Acre, distribuição concentrada no Estado de São Paulo e em outros estados brasileiros e no Paraguai; C. matourensis encontram-se bem distribuídas no Acre e em outros estados brasileiros e países amazônicos, até o Panamá; C. lechleri ocorrem somente no sudeste do Estado do Acre, na Bolívia, Colômbia, Peru e Equador; C. billbergianus encontram-se bem distribuídas no Estado do Acre, escassa em outros estados amazônicos, ocorrendo em outros países da América Latina até o México. As plantas de Uncaria guianensis e U. tomentosa foram as de maior abundância no Estado do Acre e em toda a Amazônia brasileira, sendo U. tomentosa de menor abundância e distribuição muito ampla ocorrendo, inclusive, até a América Central. Com respeito ao “status” de conservação, as plantas de Croton billergianus, C. matourensis e Uncaria guianensis foram incluídas na categoria LC (comuns e abundantes ou fora de perigo), Cinchona amazonica, Croton lechleri e C. palanostigma em CR (perigo crítico), Uncaria tomentosa em VU (perigo a médio prazo) e Croton floribundus em DD (informação insuficiente). A presença destas espécies não foi constatada nas unidades de conservação do Estado do Acre e, no momento, as florestas onde ocorrem estão sendo exploradas para a extração da madeira, de fármacos e para a ampliação da fronteira agropecuária. Nos herbários das instituições de pesquisa e de ensino do Estado do Acre as coleções de plantas das espécies de Cinchona, Croton e Uncaria são escassas em comparação com as de outros Estados do Brasil e dos países visitados.
This research studied eight wood species of the genus Cinchona (C. amazonica Standl.), Croton (C. billbergianus Müll.Arg. C. floribundus Spreng.; C. lechleri, Müll.Arg.; C. matourensis Aubl. and C. palanostigma Klotzsch) and Uncaria (U. guianensis (Aubl.)J.F. Gmel. and U. tomentosa (Willd. ex Roem. & Schult.)DC.). All of them with medicinal interest, grown in the state of Acre (Brazil). The research consisted mainly in: field work in different regions of the state of Acre and botanical and plants collections, raising the exsiccates of the mentioned species in the most important national and international herbariums of South America, a wide bibliographical review concerning these species, dendrology description and the macro and microscopy description of the wood. The ve getative dendrological characteristics of these species showed variations with age adaptations and geographical distribution. The anatomy structures were different between families (Euphorbiaceae and Rubiaceae) and genus (Cinchona, Croton, Uncaria) and less within species. These results can be used for identification of these genus. In the order hand, this study shows that Cinchona amazonica had low distribution in Acre State, other Brazilian states and Amazonian countries. For Croton genus as C. palanostigma showed an almost punctual distribution in Acre, although had high distribution on the Amazon region and lowest on Latin America; C. floribundus with punctual occurrence on the Acre State and concentrated distribution in Sao Paulo State, other Brazilian States and in Paraguay; C. matourensis had high distribution in Acre, other Brazilian states and Amazonian countries, reaching up to Panama; C. lechleri grew only in the south east of Acre, Bolivia, Colombia, Peru and Ecuador; C. billbergianus was found well distributed in Acre, less abundant in other Amazon states and Latin countries and reaching up to Mexico. Uncaria guianensis and U. tomentosa were the most abundant species in Acre state and in all the Brazilian Amazon, and the U. tomentosa in Brazil can be considered less abundant, although with a wider distribution reaching inclusive the Central America. Concerning the conservation “status”, C billbergianus, C. matourensis and U. guianensis were included in the category LC (common and abundant or out of danger); Cinchona amazonica, Croton lechleri and C. palanostigma on CR (critical danger), Uncaria tomentosa on VU (medium term danger) and Croton floribundus on DD (insufficient information). One of the most important aspects to mention is that there were no evidence of any presence of these species in the conservation unites in the State of Acre, and in the forests where they occur. Also, they are cuttings for raw material for wood, pharmacological exploration and farm and cattle frontiers amplification.. This situation was verified in the State of Acre for the lower collection of plants of Cinchona, Croton and Uncaria in relation to other states in Brazil and in other countries visited.

A ocorrência do ácaro vermelho das palmeiras (AVP), Raoiella indica Hirst (Acari: Tenuipalpidae), foi relatada no Novo Mundo em 2004 e desde então este ácaro tem colonizado várias espécies de aceráceas e musáceas, assim como plantas ornamentais de outras famílias nas ilhas do Caribe, Florida (USA), Venezuela, Brasil e Colômbia. Desde aquele primeiro relato, essa espécie tem produzido consideráveis perdas econômicas em coqueiro nos países onde foi encontrada, o que tem conduzido a um interesse cada vez maior em se conhecer o impacto da praga às plantas em que este ácaro tem sido encontrado. Com o objetivo de conhecer aspectos bioecológicos do AVP na Venezuela foram feitas amostragens para determinar a distribuição geográfica nesse país assim como as plantas hospedeiras e inimigos naturais com os quais a praga tem sido encontrada. A biologia da praga foi estudada em plantas ornamentais e em espécies de palmeiras nativas do Neotrópico, para avaliar o seu potencial em causar dano a estas plantas. Além disso, foi estudada sua distribuição intra-planta, sua flutuação populacional em plantios comerciais de coqueiro e também as variações na expressão das enzimas oxidativas (POD e PPO) e o grau de peroxidação de lipídeos em genótipos de coqueiro, como respostas à alimentação deste ácaro. Foram verificados altos níveis populacionais do AVP em plantios comerciais de coqueiro e em outras plantas crescendo naturalmente no litoral na Venezuela. Em apenas oito espécies de Arecaceae, uma de Musaceae e uma de Strelitziaceae foram verificados todos os estágios de desenvolvimento do AVP, sugerindo que este se desenvolve e se reproduz nestas plantas. O ácaro fitoseídeo Amblyseius largoensis (Muma) foi o predador mais frequentemente associado com o AVP em todos os locais estudados. Maiores densidades do AVP foram observadas nas regiões mediana e basal das folhas coletadas nos estratos mediano e basal da copa da planta. Em 2010, os níveis populacionais do AVP foram mais elevados que em 2011, aparentemente em função dos níveis menores de precipitação naquele ano. O AVP conseguiu se desenvolver sobre as espécies de plantas ornamentais, mas não nas espécies de arecáceas nativas do Novo Mundo. Com relação às enzimas oxidativas, as atividades das POD, PPO e a peroxidação de lipídeos foram maiores em plantas infestadas dos cultivares Anão Amarelo da Malásia (AAM) e Gigante do Caribe (GC) quando comparadas com os respectivos controles. Além disso, maiores atividades de POD e PPO foram detectadas no cultivar AAM que no cultivar GC, tanto em plantas infestadas quando não infestadas. Em contraste, maior peroxidação de lipídeos foi verificada em plantas do cultivar GC infestadas. Estes resultados sugerem que provavelmente esses genótipos de coqueiro possuim mecanismos de resistência ao AVP, porem estudos complementares precisam ser realizados.
Occurrence of the red palm mite, Raoiella indica Hirst (Acari: Tenuipalpidae), was related in the New World in 2004 and since then this mite species has colonized several arecaceaous and musaceous plant species, but also ornamental species in the Caribbean Islands, Florida (USA), Venezuela, Brazil and Colombia. Since firstly reported, this mite species has provoked considerable economic losses in coconut in countries where it has been found thus raising more interest to know pest impact on plant species on which mite has been found. In order to know biological aspects of R. indica samplings were made to determine geographical distribution, and also host plants and natural enemies which are found with it. Pest biology was assessed in ornamental plants and also on palms species native to Neotropical region in order to evaluated potential to cause damage on these plant species. Besides intra-plant distribution and population fluctuation was evaluated in coconut commercial plots and also variations in oxidative enzyme expression (POD and PPO) and extent of lipid peroxidation in coconut genotypes as response to R. indica feeding. Higher population levels of RPM were verified in coconut commercial plots but also in naturally growing plants in the coastal line in Venezuela. All developmental stages of the RPM were verified only on eight Arecaceae species, one Musaceae and one Strelitziaceae species thus suggesting that mite is able to develop and reproduce on these plant species. Phytoseiid mite Amblyseius largoensis (Muma) was the most frequent predator species associated to the RPM in all of the sampling areas. Higher mite densities were observed in middle and basal portions from leaf collected from middle and basal canopy. In 2010, RPM population levels were higher than in 2011, probably as function to lower rainfall levels in that year. The RPM completed development on ornamental plant species but did not on arecaeous native to New World. In regard to oxidative enzymes, POD and PPO activities and lipid peroxidation were higher in infested plants from Malaysian Yellow Dwarf (MYD) and Caribbean Tall (CT) as compared to respective controls. Besides higher POD or PPO activities were detected in MYD cultivar than in CT both in infested or no infested plants. In contrast, higher lipid peroxidation was verified in infested CT cultivar. Our results suggest that probably these coconut genotypes exhibit resistance mechanism to the RPM, however more detailed studies are required.

L’Afrique centrale atlantique (ACA) englobe l’ensemble du domaine bas-guinéen, les îles du Golfe de Guinée et une partie de l’archipel afromontagnard. Plusieurs centres d’endémisme ont été identifiés en son sein et sont généralement considérés comme liés à la présence de refuges forestiers durant les périodes glaciaires. Cependant, l’origine de cet endémisme, sa localisation et les méthodes permettant d’identifier ces centres restent controversées. La localisation de ces zones d’endémisme et des plantes rares qu’elles abritent, est pourtant un prérequis indispensable pour la mise en place de politiques cohérentes de conservation et demeure une priorité pour les organisations privées, institutionnelles ou gouvernementales actives dans la gestion et le maintien durable de la biodiversité.

Cette étude phytogéographique porte sur la famille des Orchidaceae et est basée sur l’analyse de la distribution des taxons endémiques de l’ACA. Elle s’appuie sur un jeu de données original résultant d’un effort d’échantillonnage important au Cameroun et d’un travail d’identification et de localisation de spécimens dans les principaux herbaria européens abritant des collections d’ACA. Durant cette étude, (i) nous avons tout d’abord identifié ces taxons endémiques et documenté leur distribution au travers de plusieurs contributions taxonomiques et floristiques, (ii) nous nous sommes ensuite intéressé aux nouvelles méthodes permettant d’analyser ces données d’herbier de plantes rares et donc pauvrement documentées, testant aussi l’intérêt des Orchidaceae comme marqueurs chorologiques, et finalement, appliquant ces méthodes à notre jeu de données, (iii) nous avons délimité des centres d’endémisme et identifié les territoires phytogéographiques des Orchidaceae en ACA.

(i) Une révision taxonomique des genres Chamaeangis Schltr. et Stolzia Schltr. a été réalisée respectivement. Sept nouveaux taxons ont été décrits: Angraecum atlanticum Stévart & Droissart, Chamaeangis spiralis Stévart & Droissart, Chamaeangis lecomtei (Finet) Schltr. var. tenuicalcar Stévart & Droissart, Polystachya engogensis Stévart & Droissart, Polystachya reticulata Stévart & Droissart, Stolzia repens (Rolfe) Summerh var. cleistogama Stévart, Droissart & Simo et Stolzia grandiflora P.J.Cribb subsp. lejolyana Stévart, Droissart & Simo. Plusieurs notes taxonomiques, phytogéographiques et écologiques supplémentaires ont également été redigées. Au total, nous avons identifié 203 taxons d’Orchidaceae endémiques d’ACA parmi lesquels 193 sont pris en compte pour l’étude des patrons d’endémisme.

(ii) Au Cameroun, les patrons de distribution des Orchidaceae et des Rubiaceae endémiques d’ACA ont été étudiés conjointement. Des méthodes de rééchantillonnage des données (raréfaction) ont été appliquées pour calculer des indices de diversité et de similarité. Elles ont permis de corriger les biais liés à la variation de l’effort d’échantillonnage. Un gradient de continentalité a été observé, les parties côtières étant les plus riches en taxons endémiques d’ACA. Contrairement à la région du Mont Cameroun et aux massifs de Kupe/Bakossi qui ont connu une attention particulière des politiques et des scientifiques, la partie côtière du sud Cameroun, presque aussi riche, reste mal inventoriée pour plusieurs familles végétales.

Cette analyse à l’échelle du Cameroun a également permis de comparer les patrons d’endémisme des Orchidaceae et des Rubiaceae. Les différences observées seraient principalement dues à la présence d’Orchidaceae terrestres dans les végétations basses et les prairies montagnardes de la dorsale camerounaise alors que les Rubiaceae sont généralement peu représentées dans ces habitats. Au sein des habitats forestiers, la concordance entre les patrons d’endémisme des Orchidaceae et des Rubiaceae remet en question l’utilisation des capacités de dispersion des espèces comme critère pour choisir les familles permettant l’identification des refuges forestiers et semble ainsi confirmer la pertinence de l’utilisation des Orchidaceae comme marqueur chorologique.

La distribution potentielle a été utilisée pour étudier en détail l’écologie, la distribution et le statut de conservation de Diceratostele gabonensis Summerh. une Orchidaceae endémique de la région guinéo-congolaise uniquement connue d’un faible nombre d’échantillons. Cette méthodologie semble appropriée pour compléter nos connaissances sur la distribution des espèces rares et guider les futurs inventaires en Afrique tropicale.

(iii) En ACA, les Orchidaceae permettent d’identifier plusieurs centres d’endémisme qui coïncident généralement avec ceux identifiés précédemment pour d’autres familles végétales. Ces constats supportent aussi l’utilisation des Orchidaceae comme marqueur chorologique. La délimitation des aires d’endémisme des Orchidaceae a ainsi permis de proposer une nouvelle carte phytogéographique de l’ACA. Les éléments phytogéographiques propres à chacune des dix phytochories décrites ont été identifiés et leurs affinités floristiques discutées. Les résultats phytogéographiques obtenus (a) soutiennent l’existence d’une barrière phytogéographique matérialisée par la rivière Sanaga entre les deux principaux centres et aires d’endémisme de l’ACA, (b) étendent l’archipel afromontagnard situé principalement au Cameroun au plateau de Jos (Nigeria) et (c) montrent l’importance de la chaîne montagneuse morcelée Ngovayang-Mayombe pour la distribution de l’endémisme en ACA. Cette chaîne de montagne, qui s’étend le long des côtes de l’océan du sud Cameroun au Congo-Brazzaville et qui correspond à plusieurs refuges forestiers identifiés par de nombreux auteurs, est ici considérée comme une seule aire d’endémisme morcelée./

Atlantic central Africa (ACA) covers the Lower Guinean Domain, the four islands of the Gulf of Guinea and a part of the afromontane archipelago. Different centres of endemism have been identified into this area and are usually considered as related to glacial forest refuges. However, the origin of this endemism, the localization of the centres and the methods employed to identify these centres are subject to debate. Yet, the localization of these centres of endemism and the identification of the rare plants they harbor is an essential prerequisite to setting up rational conservation policies, and remains a priority for private, institutional and governmental organizations which are dealing with the sustainable management of biodiversity.

This phytogeographical study focuses on Orchidaceae and analyses the distribution of the taxa endemic to ACA. We use an original dataset resulting from an important sampling efforts and the identification of specimens coming from all the principal herbaria where collections from ACA are housed. During this study, (i) we first identified the taxa endemic to ACA and documented their distribution through several taxonomic and floristic contributions, (ii) we used and developed new methods allowing to correct for sampling bias associated with the use of rare and poorly documented taxa, testing at the same time the use of Orchidaceae as chorological markers, and finally, applying these methods to our dataset, (iii) we delimited the centres of endemism and identified the phytogeographical territories of Orchidaceae in ACA.

(i) A taxonomic revision of Chamaeangis Schltr. and Stolzia Schltr. respectively was carried out. Seven new taxa were described: Angraecum atlanticum Stévart & Droissart, Chamaeangis spiralis Stévart & Droissart, Chamaeangis lecomtei (Finet) Schltr. var. tenuicalcar Stévart & Droissart, Polystachya engogensis Stévart & Droissart, Polystachya reticulata Stévart & Droissart, Stolzia repens (Rolfe) Summerh var. cleistogama Stévart, Droissart & Simo and Stolzia grandiflora P.J.Cribb subsp. lejolyana Stévart, Droissart & Simo. Several additional taxonomic, phytogeographical and ecological notes were also published. We finally identified 203 Orchidaceae taxa endemic to ACA, among which 193 were used to study the patterns of endemism.

(ii) In Cameroon, the distribution patterns of both Orchidaceae and Rubiaceae endemic to ACA were studied. Subsampling methods (rarefaction) were applied to calculate diversity and similarity indices and to correct potential bias associated with heterogeneous sampling intensity. A gradient of continentality was confirmed in Cameroon, the coastal part being the richest in taxa endemic to ACA. The Cameroon Mountain and the Kupe/Bakossi mountain massifs have received a great consideration of politics and scientists. On the contrary, the Southern coastal part of Cameroon, though almost as rich as the Northern part, remains poorly known for several plant families.

This analysis also allowed us to compare patterns of endemism of Orchidaceae and Rubiaceae. The differences observed could be mainly due to the terrestrial habit of some Orchidaceae, which are only found in the grasslands of the highest part of the Cameroonian volcanic line where endemic Rubiaceae are rare. Within forest habitats, the concordance between the patterns of endemism of Orchidaceae and Rubiaceae question the widespread use of dispersal ability as a selection criterion for the families used to identify forest refuges. This also confirms the relevance of Orchidaceae as chorological marker.

Species distribution modelling was used of an in depth study of the ecology, the distribution and the conservation status of Diceratostele gabonensis Summerh. an Orchidaceae endemic to the Guineo-Congolian regional centre of endemism which is only known from very few collections. This method is proved to be appropriate to complete our knowledge on the distribution of rare plant species and to guide the future inventories in tropical Africa.

(iii) In ACA, an analysis of the distribution of endemic Orchidaceae confirmed the presence and location of several centres of endemism previously identified on the basis of other plant families. This result again supports the use of Orchidaceae as a chorological marker. The chorological study of the endemic Orchidaceae allowed us to propose a new phytogeographical map for ACA. Phytogeographical elements for each of the ten phytochoria described were identified and their floristic affinities were also discussed. Our results (a) support the existence of a phytogeographical barrier, materialized by the Sanaga River, between the two main centres and area of endemism of the ACA, (b) extend the limits of the afromontane archipelago to the Jos Plateau in Nigeria and (c) show the importance of the Ngovayang-Mayombe line to explain the distribution of endemism in ACA. This mountainous line, stretching along the ocean coast from Southern Cameroon to Congo-Brazzaville, corresponds to several forest refuges identified by many authors, and is here considered as an unique but discontinuous area of endemism.

Doctorat en Sciences
info:eu-repo/semantics/nonPublished

Dissertation (PhD)--University of Stellenbosch, 2006.
ENGLISH ABSTRACT: The spatial distribution of animals and plants at different scales is a central theme in ecology. Knowledge of biodiversity distribution is essential, especially with the current threat of climate change and invasion by alien species. Since the impact of climate change and alien species will be, and has already been pronounced in polar regions, information on the current spatial distributions of biota in these regions is critical to predict the consequences of climate change and alien species on the future survival, distribution and abundance of indigenous biota. This study was conducted on the sub- Antarctic Prince Edward Islands (consisting of Marion Island and Prince Edward Island), which have experienced rapid climate changes over the past 50 years. Additionally, a number of alien plant, vertebrate and invertebrate (also microarthropod) species have been introduced to these islands. Since microarthropods (mites and springtails) play an essential role in decomposition and mineralization of plant material on the islands, the loss of microarthropods from decomposer communities might have disastrous results for ecosystem processes. Therefore it is essential to know the current distributions of microarthropods in order to predict future distributions patterns in reaction to climate change and invasive species. In this study, the spatial distribution of mites and springtails inhabiting the cushion plant Azorella selago Hook, were examined at different scales of observation. Firstly, the microarthropod community was examined at a fine scale. The relationship between microarthropod species richness and abundance and plant size, isolation, within-plant variability, grass cover and microclimate variables were investigated. Thereafter, the spatial variability of microarthropod abundances was examined within stands of plants, with statistical methods using varying degrees of locational information to determine if microarthropod abundance is random, regular or aggregated at this scale. Further, the spatial variability of microarthropod communities in A. selago at different altitudes and on different sides of Marion Island, i.e. island-wide scale, was examined. The last scale of observation was the island-wide scale, in which microarthropod assemblages were compared between Marion Island and Prince Edward Island, as well as in different plant species. Microarthropods showed spatial heterogeneity within A. selago plants (higher abundances in eastern and southern sides of plants), island-wide (lower springtail abundance on the eastern side of the island and at high altitudes) and between islands (more alien species on Marion Island). In contrast, microarthropod abundance was not spatially heterogeneous within a stand of plants, i.e. mostly randomly distributed. The possible mechanisms responsible for these patterns differ between scales, and range from temperature and nutrient availability at the within plant and island wide scale to alien species between islands. Climate change is likely to alter these distribution patterns of microarthropods, either directly (unfavourable climate for indigenous species growth, development and dispersal) or indirectly (favouring alien microarthropod species; increase in grass cover on A. selago plants may alter community structure). The information presented here, is essential for predicting the possible impacts of climate change on microarthropods in fellfield ecosystems on sub-Antarctic islands.
AFRIKAANSE OPSOMMING: Die ruimtelike verspreiding van diere en plante op verskillende skale is ‘n sentrale tema in ekologie. Kennis van die verspreiding van biodiversiteit is belangrik, veral met die huidige bedreiging van klimaatsverandering en indringerspesies. Omdat die impak van klimaatsverandering en indringerspesies in die poolstreke alreeds duidelik is en nog meer so sal word, is inligting oor die huidige ruimtelike verspreiding van biota in hierdie streke noodsaaklik. Hierdie studie is op die sub-Antarktiese Prins Edward-eilande (bestaande uit Marion Eiland en Prins Edward Eiland) uitgevoer, waar die klimaat vinnig verander het oor die afeglope 50 jaar. Bykomend is ‘n aantal indringer plant, vertebraat en invertebraat (ook mikroartropood) spesies op die eilande ingebring. Omdat mikroartropoda (myte en springsterte) ‘n baie belangrike rol in ontbinding en mineralisering van plantmateriaal op hierdie eilande speel, sal die verlies van mikroartropoda uit die ontbindingsgemeenskap rampspoedige gevolge vir die prosesse in die ekosisteem hê. Kennis van die huidige verpreiding van mikroartropoda is dus noodsaaklik om die toekomstige verspreidingspatrone, asook oorlewing en volopheid van inheemse spesies in reaksie op klimaatsveranding en indringerspesies, te voorspel. In hierdie studie is die ruimtelike verspreiding van myte en springsterte wat in die kussingplant Azorella selago Hook voorkom, op verskillende ruimtelike skale ondersoek. Eerstens is die mikroartropood gemeenskap op ‘n klein skaal ondersoek. Die verwantskap tussen mikroartropood spesies rykheid en volopheid en plantgrootte, isolasie, binne-plant variasie, gras bedekking en mikroklimaat faktore is ondersoek. Daarna is die ruimtelike variasie van mikroartropood volopheid binne in ‘n plantstand ondersoek deur gebruik te maak van metodes wat verskillende grade van ligging data gebruik. Dit is gedoen om uit te vind of mikroartropood volopheid lukraak, reëlmatig of versameld verspreid is. Verder is die ruimtelike verspreiding van mikroartropood gemeenskappe in A. selago op verskillende hoogtes bo seespieël en op verskillende kante van Marion Eiland ondersoek. Laastens is die mikroartropood gemeenskap op Marion Eiland en Prins Edward Eiland, asook die gemeenskap in verskillende plant spesies vergelyk. Mikroartropoda is ruimtelik heterogeen verspreid binne-in A. selago (meer individue in die oostelike en suidelike kante van plante), asook regoor Marion Eiland (minder springstert individue aan die ooste kant van die eiland asook minder op hoë hoogtes bo seespieël) en tussen eilande (meer indringerspesies op Marion Eiland). In teenstelling hiermee is mikroartropood volopheid ruimtelik homogeen oor ‘n plantstand, dus meestal lukraak verspreid. Die meganismes wat moontlik vir hierdie patrone verantwoordelik is wissel van temperatuur en voedselbeskikbaarheid op die binne-plant en oor die eiland skaal tot indringerspesies op die tussen-eiland skaal. Klimaatsverandering mag waarskynlik mikroartropood verspreidingspatrone direk (ongunstige klimaat vir inheemse spesies se groei, ontwikkeling en verspreiding), of indirek verander (indringer spesies word begunstig; toename in grasbedekking bo-op A. selago mag die gemeenskapstruktuur van mikroartropoda verander). Hierdie inligting is belangrik vir die voorspelling van die moontlike impak van klimaatsverandering op mikroartropoda in klipveld ekosisteme op sub-Antarktiese eilande.

Thesis (MTech. Nature Conservaion) -- Tshwane University of Technology 2013.
The aim of this study was to determine the current population status of Aloe peglerae in the Magaliesberg Mountain Range.

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

Plantago ovata Forssk. (Plantaginaceae) is a winter annual species which, in North America, inhabits desert and Mediterranean habitats of the southwest United States, northwest Mexico and the Channel Islands of California and Mexico. In the eastern hemisphere P. ovata inhabits desert regions ranging from the Canary Islands, across northern Africa to western India. The wide disjunction between P. ovata in the western and eastern hemispheres poses an interesting question as to the origin and biogeography of the species. Previous authors have hypothesized that P. ovata was introduced to North America over the Bering land bridge, from Asia, during the Miocene, or introduced anthropogenically from Europe during the 18th century by Spanish settlers. In this study we examined sequence data from the chloroplast trnL-trnF, trnS-trnG and psbA-trnH regions, the nuclear ribosomal internal transcribed spacer (ITS) and a region 5' of the TCP region of a CYCLOIDEA gene. Using a molecular clock based on an ITS calibration within the Plantago genus, and a clock for plant chloroplast, we date a non-anthropogenic introduction event, from the Old World to North America, approximately 200,000-650,000 years ago. This is consistent with a Pleistocene origin, and does not support a Miocene origin of the disjunction. Based on a morphological survey of 552 specimens, from throughout the world range of P. ovata, we suggest the recognition of four subspecific taxa. Molecular phylogenetic analysis of chloroplast DNA and nuclear ribosomal DNA ITS sequences support this taxonomic treatment. Furthermore, phylogenetic sequences of the CYCLOIDEA gene support the morphological data. Both suggest the origin of North American P. ovata as a result of hybridization between Old World P. ovata varieties. This event provides further evidence that hybridization may serve as a predictor of invasiveness in plants.
Graduation date: 2005

A major challenge in savanna rangeland studies is estimating woody vegetation cover and densities over large areas where field based census alone is impractical. It is therefore crucial that the management and conservation oriented research in savannas identify data sources that provides quick, timely and economical means to obtain information on vegetation cover. Satellite remote sensing can provide such information. Remote sensing investigations, however, require establishing statistical relationships between field and remotely sensed data. Usually regression is the empirical method applied to field and remotely sensed data for the spatial estimation of woody vegetation variables. Geostatistical techniques, which take spatial autocorrelation of variables into consideration, have rarely been used for this purpose. We investigated the possibility of improving woody biomass predictions in tropical savannas using cokriging. Cokriging was used to evaluate the cross-correlated information between SPOT (Satellites Pour l’Observation de la Terre or Earth-observing Satellites)-derived vegetation variables and field sampled woody vegetation percentage canopy cover and density. The main focus was to estimate woody density and map the distribution of woody cover in an African savanna environment. In order to select the best SPOT-derived vegetation variable that best correlate with field sampled woody variables, several spectral vegetation and texture indices were evaluated. Next, variogram models were developed: one for woody canopy cover and density, one for the best SPOT-derived vegetation variable, and a crossvariogram between woody variables and best SPOT-derived data. These variograms were then used in cokriging to estimate woody density and map its spatial distribution. Results obtained indicate that through cokriging, the estimation accuracy can be improved compared to ordinary kriging and stepwise linear regression. Cokriging therefore provided a method to combine field and remotely sensed data to accurately estimate woody cover variables.
Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.

M.Sc. (Botany)
In South Africa, controlling and eradicating Azolla filiculoides and Eichhornia crassipes cost annually approximately US$ 60 million to the national budget. However, the success of these operations is mixed because invasive aquatic plants often spread very rapidly either before they are spotted or before decisions are taken to implement control actions. This limitation is further exacerbated by difficulties in determining the invasion potential of newly introduced or unknown aquatic plants, as well as difficulties inherent to species identification. Resolving these drawbacks requires pre-emptive actions such as identifying areas that are most vulnerable to invasion by alien plants. In this study, I first explore whether molecular technique such as DNA barcoding can be useful to: i) overcome potential limitation of morphology-based identification of invasive aquatic plants; and ii) establish successful control of these invasives. For this purpose, I tested the utility of official DNA barcodes (rbcLa + matK or core barcodes), trnH-psbA, and the core barcode + trnH-psbA to identify invasive aquatic plants of South Africa’s freshwaters. Second, I use the technique of ecological niche modeling to identify most vulnerable freshwater systems to species invasion under current and climatic conditions. My analysis indicates that the core barcodes and matK regions perform poorer compared to trnH-psbA, which provides 100% successful identification alone or in combination with the core barcodes. This study therefore validates trnH-psbA as single best DNA barcode for invasive alien aquatic plants of freshwater systems in South Africa. Using this DNA region in BLAST analysis to screen plants species sold in aquarium market in Johannesburg, I found surprisingly that some prohibited species are already in circulation in the market. These include Hydrilla verticillata, egeria densa, Myriophyllum spicatum, and Echinodorus cordifolius. Furthermore, based on climatic parameters, I explored the distribution of the "bad five" aquatic species in South Africa, i.e. the most damaging invaders of freshwater systems. I found distinct distribution potentials for these species under current climatic conditions. Overall, 38% of all South Africa’s dams occur in areas climatically vulnerable to the invasion by the bad five with the Western Cape Province being the most vulnerable. However, under predicted climate change scenario, I found evidence for contrasting shifts in species range: species such as Azolla filiculoides, Eichhornia crassipes, Salvinia molesta might increase their range by at most 2% whilst the ranges of Myriophyllum aquaticum and Pistia stratiotes might contract by at most 5%. This range contraction and expansion will result in some dams currently vulnerable to invasion becoming resilient whilst others that are currently resilient might become vulnerable owing to climate change. This result demonstrates not only the utility of DNA barcoding in implementing control measures, but also provides ways of prioritising control/management efforts.