<p>The Table Mountain Group (TMG) Aquifer is the second largest aquifer system in South Africa, after dolomites. This aquifer has the potential to be a signinficant source of water for the people of the Western Cape. The occurrence of hot water springs in the TMG in relation with the main geological fault systems in SOuth Africa shows that deep flow systmes do exist. Little is known about these deep aquifer systems in South Africa (i.e. flow mechanisms). To close the above-mentioned knowledge gap, this study was initiated. The current study gave a review of some of the aspects that needs to be considered when distinguishing deep groundwater from shallow groundwater.</p>

<p>Understanding of Groundwater Dependent Ecosystems (GDEs) and their extent within the Table Mountain Group (TMG) aquifer is poor. To understand the dependence to basic ecological and hydrogeological concepts need explanation. The use of current literature aided in identification and classification. From the literature it has come clear that groundwater dependence centers around two issues, water source and water use determination. The use of Geographical Information System (GIS) showed its potential in proof of water sources. Rainfall data and a Digital Elevation Model (DEM) for the Uniondale area have been used to do watershed delineation, which is in line with locating GDEs on a landscape. Thus the conceptual approach should be a broad one that sets a basis for both investigation (scientific research) and institutional arrangements (management).</p>

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science. Johannesburg, 2013. / Species richness and estimates of species richness were calculated based on assemblages of bats, within the biomes of South Africa, Lesotho and Swaziland following the vegetation classification of Mucina and Rutherford (2006). Similarity indices were used to explore the various relationships between the assemblages between the various biomes. Taxonomic diversity and distinctness examined the various assemblages within each of the biomes to investigate which biomes contained assemblages that were taxonomically diverse and/or taxonomically distinct compared to all species known to occur within South Africa, Lesotho and Swaziland. The Desert biome had the lowest recorded species richness (5 species), and there was insufficient data to calculate estimates of species richness for this biome. While the Albany had 11 species recorded with species estimates (Est.) ranging between 11-12, then in increasing order - Nama-Karoo (12 species, Est. 13-25 species), Succulent-Karoo (13 species, Est. 15-30 species), Fynbos (17 species, Est. 18-25 species), Indian Ocean Coastal Belt (31 species, Est. 32-36 species), Forest (32 species, Est. 37-46 species), Grassland (39 species, Est. 42-54 species), Azonal (45 species, Est. 49-63 species) and Savanna (57 species, Est. 59-67 species). The mean recorded estimates (based on the averages of all models) and rounding up to a full species indicates that the Albany biome contains the lowest expected species richness of 12 species, then Fynbos and Nama-Karoo (21 species), Succulent-Karoo (22 species), Indian Ocean Coastal Belt (34 species), Forest (43 species), Grassland (49 species), Azonal (54 species) and Savanna (64 species). Sample completeness was calculated for each of the biomes which indicates in ascending order that the Albany biome is 93.2% complete followed by the Indian Ocean Coastal Belt biome (91.1%), Savanna biome (89.9%), Azonal biome (84.1%), Fynbos biome (81.5%), Grassland biome (80.7%), Forest biome (75.8%), Succulent-Karoo biome (61.3%), and Nama-Karoo biome (59.9%). This showed that the Albany biome was found to be the only biome that has been sufficiently sampled. The Jaccard and Sørensen pair wise indices resulted in the clustering of the biomes with similar species richness, due to the large range in species richness (5-57 species) between the biomes. The Lennon et al. (2001) index which is not affected by large species richness between the samples indicated that the Desert and Nama-Karoo assemblages were most dissimilar to one another, while the Indian Ocean Coastal Belt assemblage was the most similar to the remaining biome assemblages. The Albany biome assemblage and Azonal biome assemblage were shown to the most dissimilar to one another. The Grassland, Nama-Karoo and Savanna biomes contribute to higher taxonomic diversity, while the Albany, Azonal, Fynbos, Nama-Karoo and Succulent-Karoo biomes contain lower species richness generally but represent a higher taxonomic distinctness from the chiroptera assemblages in the Grassland and Savanna biomes. The Desert, Forest and Indian Ocean Coastal Belt biomes do not iv contain bat assemblages that are neither taxonomically distinct nor diverse when compared to the taxa of South Africa, Lesotho and Swaziland. The bat assemblage within the Nama-Karoo are both taxonomically diverse and distinct from chiroptera assemblages found within the other nine biomes, requiring a greater focus on conservation actions for the bat species assemblage located within this biome.

<p>Understanding of Groundwater Dependent Ecosystems (GDEs) and their extent within the Table Mountain Group (TMG) aquifer is poor. To understand the dependence to basic ecological and hydrogeological concepts need explanation. The use of current literature aided in identification and classification. From the literature it has come clear that groundwater dependence centers around two issues, water source and water use determination. The use of Geographical Information System (GIS) showed its potential in proof of water sources. Rainfall data and a Digital Elevation Model (DEM) for the Uniondale area have been used to do watershed delineation, which is in line with locating GDEs on a landscape. Thus the conceptual approach should be a broad one that sets a basis for both investigation (scientific research) and institutional arrangements (management).</p>

<p>The Table Mountain Group (TMG) Aquifer is the second largest aquifer system in South Africa, after dolomites. This aquifer has the potential to be a signinficant source of water for the people of the Western Cape. The occurrence of hot water springs in the TMG in relation with the main geological fault systems in SOuth Africa shows that deep flow systmes do exist. Little is known about these deep aquifer systems in South Africa (i.e. flow mechanisms). To close the above-mentioned knowledge gap, this study was initiated. The current study gave a review of some of the aspects that needs to be considered when distinguishing deep groundwater from shallow groundwater.</p>

Magister Scientiae - MSc / Understanding of Groundwater Dependent Ecosystems (GDEs) and their extent within the Table Mountain Group (TMG) aquifer is poor. To understand the dependence to basic ecological and hydrogeological concepts need explanation. The use of current literature aided in identification and classification. From the literature it has come clear that groundwater dependence centers around two issues, water source and water use determination. The use of Geographical Information System (GIS) showed its potential in proof of water sources. Rainfall data and a Digital Elevation Model (DEM) for the Uniondale area have been used to do watershed delineation, which is in line with locating GDEs on a landscape. Thus the conceptual approach should be a broad one that sets a basis for both investigation (scientific research) and institutional arrangements (management). / South Africa

Magister Scientiae - MSc / The Table Mountain Group (TMG) Aquifer is the second largest aquifer system in South Africa, after dolomites. This aquifer has the potential to be a signinficant source of water for the people of the Western Cape. The occurrence of hot water springs in the TMG in relation with the main geological fault systems in SOuth Africa shows that deep flow systmes do exist. Little is known about these deep aquifer systems in South Africa (i.e. flow mechanisms). To close the above-mentioned knowledge gap, this study was initiated. The current study gave a review of some of the aspects that needs to be considered when distinguishing deep groundwater from shallow groundwater. / South Africa

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. Johannesburg 1992. / The aim of the study was to develop understanding of the relationships between vegetation types of the grassland biome of South Africa and the environment, with an emphasis on structural and functional characteristics. The grassland biome in South Africa has traditionally been divided into 'pure' grasslands, assumed to be climatically determined, and 'false' grasslands of recent anthropogenic origin. A review of literature from several disciplines including palaeobotany, archaeology, ecology and biogeography indicates that this is not a valid distinction. It is clear that the distribution of the grassland biome as a whole is poorly understood, but the general correlation between the distribution of biomes and climate elsewhere in the world suggests that this warrants more detailed investigation. A water balance approach was used to develop climatic incices that both predict the distribution of grasslands, and are easy to interpret biologically. The indices are the mean. number of days per annum when moisture is available for plant growth, tbe mean temperature on days when moisture is available for plant growth (wet season temperature),. and the mean temperature when moisture is not available for plant growth (dry season temperature). Based on these three.indices the grassland biome in South Africa call be distinguished from neighbouring biomes. The fynbos and succulent karoo biomes have rainfall in winter. The grassland, nama-karoo and savanna biomes have' rainfall in summer. The forest biome experiences rainfall throughout the year. Of the summer rainfall biomes, the quantity of water available in the grassland biome b greater than in the nama-woo, similar to savanna, but less than forest. Grasslands experience cooler dry season temperatures than savannas. The localised distribution of woody plants within the. grassland biome suggests that it is the effect of climate on the fire regime that may be of overriding importance h'l determining the distribution of the biome as a whole. Woody elements are restricted to sites that are either protected from fire, or experience fires of lower intensity than sites that support- grassland, The unifying feature of the grassland biome is its proneness to fire. The presence of a warm, moist season promotes plant production and leads to a high standing crop close to the ground. The prolonged dry season causes vegetation to dry out annually, rendering it flammable. More arid biomes have plants more widely spaced, making it difficult for fire to spread. In more mesic biomes where rainfall is less sea.sonal than in the grasslands or savannas, fuels do not dry out sufficiently to ignite, A number of additional climatic features may promote burning in the grassland biome, It has the highest lightning density of all South Africa's biomes. 'tVarm, dry 'berg' winds desiccate fuels and 1 omote burning in the more mesic grasslands, The 'curing' of the grass sward due to dry season frost and temperature drop is important in establishing early dry season flammability. Savanna trees are fire tolerant, but they appear sensitive to the cold temperatures prevaient in the grassland biome in. the dry season, The relationship between the distribution of functional characters of grassland plants and environmental conditions was investigated. The distincrion between sweetveld, mixed veld and sourveld was recognised as one of the most Important functional features of South Africa's grasslands, The distribution of these vegetation types was examined in detail. Sweetveld occurs In warm, dry areas; sourveld in cool, moist areas. There Is overlap between these tyP.Js that Is dependant on soil nutrient status. Sweetveld that occurs in climatic conditions that would be expected to support mixed veld and sourveld, is on soils derived from basic parent material, including basalt, dolerite, gabbro and norite. Similarly, sourveld that occurs in areas that climatically would be expected to support sweetveld, is on soils derived from acid parent material such as sandstone and quartzite .. Soil nutrients that are most highly correlated to the occurrence of these three veld types are phosphoms availability and an index of nitrogen mineralization potential. 'l'here is an increase in bot; available phosphorus and the index of readily mineralizable nitrogen from sourveld to mixed veld to sweetveld. These features am inc01).10111tedinto a conceptual model that relates the distribution of these grassland types to carbon and nitrogen metabolism, with the role of phosphorus either similar to nitrogen, or else it may act indirectly by affecting the. rate of nitrogen mineralization, Nitrogen mineralization OCcursat lower water availability than carbon assimilation, and its temperature optimum is higher than that of carbon assimilation. Where nitrogen mineralization is favoured ielative to carbon assimilation, sweetveld is likely to (}C(.1\Xr. Where carbon assimilation is. favoured relative to; nitrogen mineralization, sourveld is likely to occur ....Soil texture affects the balance between these two processes in the degree to wm.r;h it protects soil organic matter, and thereforv the size of the nitrogen and ph_QSPllO_rOll.S pools. Changes in the rlj,stribution of South Africa's b~\omesfor a scenario of climate change are predicted using the biome model developed in this study. This illustrates the value of developing predictive models. / MT2017

Two methods for predicting regions susceptible to invasion by alien aquatic animals were developed for southern Africa (excluding Zimbabwe and Mozambique). In the "traditional" (data-poor) approach, distributions of three categories of alien "indicator" species (warm mesothermal, cold stenothermal and eurytopic) were compared to seven existing biogeographical models of distribution patterns of various animals in southern Africa. On the basis of these comparisons a synthesis model was developed which divided southern Africa into seven regions characterised by their susceptibility to invasion by alien aquatic animals with particular habitat requirements. In the "data-rich," geographic information systems (GIS) approach, the distribution of trout (Oncorhynchus mykiss and Salmo trutta) in selected "sampled regions" was related to elevation (as a surrogate of water temperature) and median annual rainfall (MAR) (as a surrogate of water availability). Using concentration analysis, optimum conditions for trout were identified. Regions within a larger "predictive area" which satisfied these conditions, were plotted as a digital map using the IDRISI package. Using this method seven models of potential trout distribution were generated for the following regions: northern Natal (two); southern Natal/Lesotho/Transkei (three), eastern Cape (two) and western Cape (two). Since two of the models were used to refine the methods, only five models were considered for the final assessment. In a modification of the GIS method, another model of potential trout distribution, based on mean monthly July minimum air temperature and MAR parameters, was developed for the region bounded by 29º - 34º S and 26 º - 32°E. This model showed marked similarities to another model, developed for the region bounded by 29 º - 32°S and 26º - 32°E, which was based on elevation and MAR parameters. The validity of the models developed was assessed by independent experts. Of the six models considered, four received favourable judgements, one was equivocal and one was judged to be poor. Based on these assessments it was concluded that the GIS method has credibility and could be used to develop a "data-rich" model of the susceptibility of southern Africa to invasion by alien aquatic animals. This method represents an alternative to the bioclimatic matching approach developed by scientists in Australia. The GIS method has a number of advantages over the "traditional" method: it is more amenable to testing, has greater flexibility, stores more information, produces images of a finer resolution, and can be easily updated. The traditional method has the advantage of being less expensive and requiring a less extensive database.

M.Sc. (Zoology) / The Limpopo Province covers an area of 12.46 million hectares and these accounts for 10.2 per cent of the total land area of the Republic of South Africa. The province is endowed with abundant agricultural resources and it is one of the country’s prime agricultural regions noted for the production of fruits and vegetables, cereals, tea, and sugar. A key feature of the agricultural industry of Limpopo Province is its dualism. There are two distinct types of agricultural production systems. The large scale commercial farming system occupies approximately 70% of the total land area. The smallholder farms are located mostly in the former homeland areas and they cover approximately 30% of the provincial land surface area. The town of Thohoyandou, with its surrounding villages, is the area of greatest human concentration in the Luvuvhu Catchment and subsistence farming is about a third of the total agricultural component. It is important to study the effects of agricultural inputs (e.g. fertilizers and sediment loads) on aquatic ecosystems in order to fully understand the processes involved of these stresses on aquatic ecosystems. Knowledge of these impacts toward the environment and human health is often limited due to lack of capacity building, especially among small scale farmers. Ten bio-monitoring sites were studied on five systems in the Vhembe district. The sites were sampled during the low flow period of November 2011 and the high flow period of April 2012. Sampling sites were selected to present conditions in the Mutale, Mutshindudi and Tshinane Rivers upstream and downstream of the potential influence of small scale agricultural activities...