This study was conducted in the Nkangala district, in the province of Mpumalanga in South Africa. This province remains the largest forestry production region in South Africa. The majority of people living in Mpumalanga are farmers and they have contributed immensely to promote food security. The objective of the study was to determine the level of climate change awareness among small scale maize producers in Mpumalanga province. Random sampling techniques was used to select two hundred and fifty one (251) farmers to be interviewed. A pre-tested questionnaire was administered to maize farmers, focusing on matters relating to climate change awareness in maize production. Data was captured and analysed using software package for social science (SPSS version 20 of 2012). Descriptive statistics were applied to analyse and describe the data. Logistic regression analysis followed to demonstrate the significance of the independent variables on climate change awareness. The results of the analysis indicated that the information received and the size of the farm had an impact on climate change awareness in the area of study. It was therefore recommended that the majority of farmers in Mpumalanga needed to be made aware of climate change in order to assist them to build the adaptive capacity, increase resilience and reduce vulnerability. Information on climate change awareness should be disseminated well to ensure that it will attract the attention of the farmers / Agriculture and  Animal Health / M. Sc. (Agriculture)

Thesis (M.Sc. (Geography)) --University of Limpopo, 2018 / Soil erosion, which is a critical component of land degradation, is one of the serious global environmental problems often threatening food security, water resources, and biodiversity. A comprehensive assessment and analysis of remote sensing applications in the spatial soil erosion mapping and monitoring over time and space is therefore, important for providing effective management and rehabilitation approaches at local, national and regional scales. The overall aim of the study was to assess the use of multispectral remote sensing sensors in mapping and monitoring the spatio-temporal variations in levels of soil erosion in the former homelands of Sekhukhune district, South Africa. Firstly, the effectiveness of the new and freely available moderate-resolution multispectral remote sensing data (Landsat 8 Operation Land Imager: OLI and Sentinel-2 Multi-Spectral Instrument: MSI) derived spectral bands, vegetation indices, and a combination of spectral bands and vegetation indices in mapping the spatio-temporal variation of soil erosion in the former homelands of Sekhukhune District, South Africa is compared. The study further determines the most optimal individual sensor variables that can accurately map soil erosion. The results showed that the integration of spectral bands and spectral vegetation indices yielded high soil erosion overall classification accuracies for both sensors. Sentinel-2 data produced an OA of 83, 81% whereas Landsat 8 has an OA of 82.86%. The study further established that Sentinel-2 MSI bands located in the NIR (0.785-0.900 μm), red edge (0.698-0.785μm) and SWIR (1.565-2.280 μm) regions were the most optimal for discriminating degraded soils from other land cover types. For Landsat 8 OLI, only the SWIR (1.560-2.300 μm), NIR (0.845-0.885 μm) region were selected as the best regions. Of the eighteen spectral vegetation indices computed, Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) and Global Environmental Monitoring Index (GEMI) were selected as the most suitable for detecting and mapping soil erosion. Secondly, the study assessed soil erosion in the former homelands of Sekhukhune, South Africa by applying a time-series analysis (2002 and 2017), to track changes of areas affected by varying degrees of erosion. Specifically, the study assessed and mapped changes of eroded areas (wet and dry season), using multi-date Landsat products 8 OLI and 7 Enhanced Thematic Mapper (ETM+)). Additionally, the study used extracted eroded areas and overlay analysis was performed together with geology, slope and the Topographic Wetness Index (TWI) of the area under study to assess whether and to what extent the observed erosional trends can be explained. ii Time series analysis indicated that the dry season of 2002, experienced 16.61 % (224733 ha) of erosion whereas in 2017 19.71% was observed. A similar trend was also observed in the wet season. This work also indicates that the dominant geology type Lebowa granite: and Rustenburg layered its lithology strata experienced more erosional disturbances than other geological types. Slopes between 2-5% (Nearly level) experienced more erosion and vice-versa. On the hand, the relationship between TWI and eroded areas showed that much erosion occurred between 3 and 6 TWI values in all the seasons for the two different years, however, the dry season of 2002 had a slightly higher relationship and vice-versa. We, therefore, recommend use and integration of freely and readily available new and free generation broadband sensors, such as Landsat data and environmental variables if soil erosion has to be well documented for purposes of effective soil rehabilitation and conservation. Keywords: Food security Global changes, Land degradation, Land-based ecosystems, Land management practices, Satellite data, Soil conservation, Sustainable Development; Topographic Wetness Index; Time series analysis.

Agricultural production is the major source of household food security and income for smallholder maize farmers in the rural households in the Kingdom of eSwatini. The sector also contributes approximately 6.5% to the national gross domestic product and 50% of raw material for industries and other sectors. However, the sector is faced with several challenges which hinder its development. The challenges are brought about by climate change. Farmers implement various strategies to adapt to the negative effects of climate change. Farmers awareness and perceptions of impacts of climate change influence the strategies and hence, farmers’ level of adaptation. This study was undertaken to assess smallholder maize farmers’ awareness and perceptions of the impacts of climate change in three maize producing regions of eSwatini. Descriptive statistics and a regression model were used for data analysis. The results from a descriptive analysis indicated that 71.3% of farmers were aware of climate change, while 28.7% were not aware. A regression test revealed that climate-related information was highly significant in determining farmers’ awareness of the impacts of climate change. A Likert scale analysis showed that rural-urban migration, floods incidents and soil erosion were the most important variables that influenced small-scale maize farmers’ perceptions of climate change. The study revealed that there should be more focus on improving extension services to promote access to financial services. / Agriculture and  Animal Health / M.Sc. (Agriculture)

Ocean tides worldwide have exhibited secular changes in the past century, simultaneous with a global secular rise in mean sea level (MSL). The combination of these two factors contributes to higher water levels, and may increase threats to coastal regions and populations over the next century. Equally as important as these long-term changes are the short-term fluctuations in sea levels and tidal properties. These fluctuations may interact to yield locally extreme water level events, especially when combined with storm surge. This study, presented in three parts, examines the relationships between tidal anomalies and MSL anomalies on yearly and monthly timescales, with a goal of diagnosing dynamical factors that may influence the long-term evolution of tides in the Pacific Ocean. Correlations between yearly averaged properties are denoted tidal anomaly trends (TATs), and will be used to explore interannual behavior. Correlations of monthly averaged properties are denoted seasonal tidal anomaly trends (STATs), and are used to examine seasonal behavior. Four tidal constituents are analyzed: the two largest semidiurnal (twice daily) constituents, M2 and S2, and the two largest diurnal (once daily) constituents, K1 and O1. Part I surveys TATs and STATs at 153 Pacific Ocean tide gauges, and discusses regional patterns within the entire Pacific Ocean. TATs with statistically significant relations between MSL and amplitudes (A-TATs) are seen at 89% of all gauges; 92 gauges for M2, 66 for S2, 82 for K1, and 59 for O1. TATs with statistically significant relations between tidal phase (the relative timing of high water of the tide) and MSL (P-TATs) are observed at 55 gauges for M2, 47 for S2, 42 for K1, and 61 for O1. Significant seasonal variations (STATs) are observed at about a third of all gauges, with the largest concentration in Southeast Asia. The effect of combined A-TATs was also considered. At selected stations, observed tidal sensitivity with MSL was extrapolated forward in time to the predicted sea level in 2100. Results suggest that stations with large positive combined A-TATs produce total water levels that are greater than those predicted by an increase in MSL alone, increasing the chances of high-water events. Conversely, negative correlation between sea level and tidal properties may mitigate somewhat against sea level rise; changes in total water levels in 2100 at stations with a negative combined A-TAT are less than that predicted by MSL rise alone. Climate change scenarios that take into account greater increases in MSL due to increased Antarctic ice melt show larger changes in total water levels over the same time period. Part II examines the mechanisms behind the yearly (TAT) variability in the Western Tropical Pacific Ocean. Significant amplitude TATs are found at more than half of 26 gauges for each of the two strongest tidal constituents, K1 (diurnal) and M2 (semidiurnal). For the lesser constituents analyzed (O1 and S2), significant trends are observed at ten gauges. Frictional mechanisms related to the El Nino Southern Oscillation (ENSO) are found to be important in influencing tides in the Western Pacific, as well as resonant triad interactions, a nonlinear coupling that exchanges energy between the M2, K1, and O1 tides. Both of these factors contribute to the observed tidal variability in the Solomon Sea region. Part III analyzes the seasonal behavior of tides (STATs) at twenty tide gauges in the Southeast Asian waters, which exhibit variation by 10-30% of mean tidal amplitudes. A barotropic ocean tide model that considers the seasonal effects of MSL, stratification, and geostrophic and Ekman velocity is used to explain the observed seasonal variability in tides due to variations in monsoon-influenced climate forcing, with successful results at about half of all gauges. The observed changes in tides are best explained by the influence of non-tidal velocities (geostrophic and Ekman), though the effect of changing stratification is also an important secondary causative mechanism. From the results of these surveys and investigations, it is concluded that short-term fluctuations in MSL and tidal properties at multiple time scales may be as important in determining the state of future water levels as the long-term trends. Global explanations for the observed tidal behavior have not been found in this study; however, significant regional explanations are found at the yearly time scale in the Solomon Sea, and at the seasonal time scale in Southeast Asia. It is likely that tidal sensitivity to annual and seasonal variations in MSL at other locations also are driven by locally specific processes, rather than factors with basin-wide coherence.

Accurate estimation of Net Primary Productivity (NPP), which is a key component of the terrestrial carbon cycle, is very important in studies of global climate. Ecosystem models have been used for NPP estimates. Determining how much each source of uncertainty contributes to modeled NPP is veiy important before ecosystem models can be used with confidence over larger areas and time periods. This research has systematically evaluated the boreal ecosystem productivity simulator (BEPS) carbon model in mountainous terrain, Kananaskis, Alberta. After parameterization of the model, sensitivity analysis was conducted as a controlled series of experiments involving sensitivity simulations with BEPS by changing a model input value in separate model runs. The results showed that NPP was sensitive to most model inputs measured in the study area, but that the most important input variables for BEPS were LAI and forest species. In addition, the NPP uncertainty resulting from topographic influence was approximately 3.5 %, which is equivalent to 140 kg C ha"1 yr"1. This suggested that topographic correction for the model inputs was also important for accurate NPP estimation. Using the topographically corrected data, the carbon dynamics were simulated, and average annual NPP production by forests in Kananaskis was estimated at 4.01 T ha"1 in 2003. / xix, 117 leaves : col. ill. ; 29 cm.

Soybean rust (SBR), caused by the fungus Phakopsora pachyrhizi Syd., is a real threat to soybean crops in South Africa. Its ability to spread rapidly and its potential to severely reduce yields have earned it the reputation as the most destructive foliar disease of soybeans. SBR has been reported in South Africa every year since its arrival in 2001. While extensive research had been done on the epidemiology and fungicide application requirements in South Africa, no work into the long term climatic vulnerability of soybean production areas to SBR had been done. This meant soybean producers do not know whether SBR is a threat in their areas. Through this research a SBR algorithm was developed using readily available climate data, viz. temperature and rainfall, to create a daily index specifying the climatic vulnerability of SBR infection. The algorithm was applied to a 50 year historical climate database, and a series of maps was created illustrating the long term vulnerability of different areas to SBR infection. These maps allow soybean producers to understand the climatic vulnerability of their area to SBR infection. Time series graphs were created for selected key soybean production areas to allow soybean producers to distinguish periods of high and low climatic risk during the season. This may help with decisions regarding the planting times, the maturation rate of different cultivars as well as the timing and application of fungicides. The framework for a near real time forecasting system was created outlining how the system could amalgamate recently recorded and forecasted weather data, run it through the SBR algorithm and provide a near real time, as well as forecasted vulnerability, based on the climatic conductivity for SBR infection. Anticipated limitations and difficulties on developing the forecasting system are also outlined. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2009.

Typewritten copy / Includes bibliographical references / 1 v. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Waite Agricultural Research Institute, 1955

Chrysoblephus puniceus is an over-exploited linefish species, endemic to the coastlines off southern Mozambique and eastern South Africa. Over-exploitation and habitat loss are two of the biggest threats to the sustainability of fisheries globally. Assessing the genetic stock structure (a prerequisite for effective management) and predicting climate related range changes will provide a better understanding of these threats to C. puniceus which can be used to improve the sustainability of the fishery. Two hundred and eighty four genetic samples were collected from eight sampling sites between Ponta da Barra in Mozambique and Coffee Bay in South Africa. The mitochondrial control region and ten microsatellite loci were amplified to analyse the stock structure of C. puniceus. The majority of microsatellite and mtDNA pairwise population comparisons were not significant (P > 0.05) although Xai Xai and Inhaca populations had some significant population comparisons for mtDNA (P < 0.05). AMOVA did not explain any significant variation at the between groups hierarchical level for any pre-defined groupings except for a mtDNA grouping which separated out Xai Xai and Inhaca from other sampling sites. SAMOVA, isolation by distance tests, structure analysis, principle component analysis and spatial autocorrelation analysis all indicated a single population of C. puniceus as being most likely. The migrate-n analysis provided evidence of current driven larval transport, with net migration rates influenced by current dynamics.Two hundred and thirty six unique presence points of C. puniceus were correlated with seasonal maximum and minimum temperature data and bathymetry to model the current distribution and predict future distribution changes of the species up until 2030. Eight individual species distribution models were developed and combined into a mean ensemble model using the Biomod2 package. Winter minimum temperature was the most important variable in determining models outputs. Overall the ensemble model was accurate with a true skills statistic score of 0.962. Binary transformed mean ensemble models predicted a northern and southern range contraction of C. puniceus' distribution of 15 percent; by 2030. The mean ensemble probability of occurrence models indicated that C. puniceus' abundance is likely to decrease off the southern Mozambique coastline but remain high off KwaZulu-Natal. The results of the genetic analysis support the theory of external recruitment sustaining the KwaZulu Natal fishery for C. puniceus. While the high genetic diversity and connectivity may make C. puniceus more resilient to disturbances, the loss of 15 percent; distribution and 11 percent; genetic diversity by 2030 will increase the species vulnerability. The decrease in abundance of C. puniceus off southern Mozambique together with current widespread exploitation levels could result in the collapse of the fishery. A single transboundary stock of C. puniceus highlights the need for co-management of the species. A combined stock assessment between South Africa and Mozambique and the development of further Marine Protected Areas off southern Mozambique are suggested as management options to minimise the vulnerability of this species.

A general lack of biological information is hampering the effective management of Angola’s fisheries. While this lack of information is largely a result of the country’s extended civil war that ended in 2002, the subsequent rapid expansion of fisheries is most likely impacting fish abundance and influencing the biology of this regions fishes. Besides the influence of fisheries, the southern Angolan coastal region is considered to be a climate change “hotspot” due to rapidly (>0.8°C/decade) increasing water temperatures. These changes are thought to drive further changes to the biology of fishes. It is therefore critical to provide baseline biological information and to identify the impacts of exploitation and warming on the biology of southern Angolan fishes. Pomatomus saltatrix is a warm-temperate marine fish species that forms an important component of fisheries throughout its broad distribution. P. saltatrix is a migratory predator that displays variable growth and maturity schedules. Typically it is heavily targeted in a range of coastal fisheries of Angola and is therefore an ideal candidate to study the biological impacts of exploitation and climate change. The aim of this study was to provide the first description of P. saltatrix biology in Angola and examine recent changes of the species biological parameters in an attempt to uncouple fishery driven from climate driven changes. Samples of P. saltatrix were collected monthly using standardised biological methods from June 2005 to December 2006 (period 1) and from June 2012 to February 2013 (period 2). The average (508mm – 1st period, 462mm – 2nd period) and maximum (760mm – 1st period, 746mm – 2nd period) size of P. saltatrix was smaller during the second period to suggest selective overharvesting of large individuals by developing fisheries. Angolan P. saltatrix grew very rapidly in their first year and thereafter, relatively slowly when compared to other populations globally. However, fish grew faster (ω = 103 – 1st period, ω = 124 – 2nd period), matured at a larger size (303mm - 1st period, 336mm - 2nd period) and younger age (0.83 years - 1st period, 0.67 years – 2nd period) during the second period. Peaks in reproductive activity remained similar (November) during both periods but a temperature anomaly appears to have influenced spawning during period 2. Sardinella aurita was the dominant prey during both periods but a greater dependence upon mugilids was observed during the second period. Although the changes in life history were not statistically significant, the faster growth observed during period two could be attributed to both increasing temperature and/or exploitation. Fishes generally grow faster, mature smaller and attain a smaller maximum size in warmer temperatures. Fisheries targeting small and large specimens of a species (as observed in this study) largely have the same impacts as ocean warming. With rapidly increasing water temperatures and exploitation rates, faster growth and earlier maturation of P. saltatrix populations will mitigate the impacts of exploitation in the short-term. However, the sustainability of Angola’s P. saltatrix stock is questionable as phenotypic adaptation will have a limited thermal scope and overexploitation will, like in all fisheries, negatively influence recruitment. Ultimately, strict monitoring, regulation and control will be necessary to ensure the sustainability of the P. saltatrix resource in Angola as it continues to face increasing anthropogenic and environmental pressures. Management guidelines and future research suggestions are therefore outlined with reference to the results of analyses conducted during this study.

The Eastern Cape contains the majority of the remaining forested areas in South Africa (95.8 percent Coastal forests and 47.6 percent Afromontane forests), however these occur in fragments. Due to the rapid rise in the human population and its needs, conversion of forests to agricultural land and the extraction of timber increases, natural vegetation are lost and this therefore leads to forests becoming fragmented into small forest patches. One of the main consequences of forest fragmentation is loss of contiguous habitat, which is the dominant threat to species globally as it negatively affects both species richness and genetic diversity. This research investigates the effects that forest fragmentation has on small mammal diversity and abundance. The study sampled small mammals in Southern Mistbelt Afromontane forest patches in the Eastern Cape. The first aim of this study was to identify which environmental variable, or combinations of variables, affect the diversity and abundance of small mammals in fragmented forest patches in the Eastern Cape during the austral summer. The second aim was to compare seasonal changes in small mammal diversity and abundance at a forest edge compared to the forest core at Beggars Bush, an Afromontane forest in the Eastern Cape, South Africa. To identify the environmental impacts that different forests have on small mammals, nine different forests were chosen in the Eastern Cape and sampled during the summer in 2013. These nine forests were: Fort Fordyce Forest, Thaba Ndoda Forest, Hogsback Forest, Dassie Kraans Forest, Langeni Forest, Burchell’s Reserve Forest, Maiden Dam Forest and Kagaberg Forest. At each site, three transects of 30 Sherman Traps each were used. Trapping periods within each forest patch lasted between three to five consecutive nights and traps were inspected once a day in the morning. Nine environmental variables were initially identified and after being tested for normality and colinearity, five variables were chosen. These variables were Altitude, Mean Annual Temperature, Gradient, Patch Size and Mean annual potential evaporation. The number of individuals captures and species richness were then incorporated as dependent variables for best subset multiple regression model selection using the Akaike Information Criterion (AIC). For the second aim, the same trapping methods were used when comparing seasonal changes to diversity and abundance within the forest core. However at the forest edge, due to the small size of the forest, only 20 Sherman traps were used in each transect with five traps (25 percent) placed in the grassland and 15 (75 percent) placed in the forest along each transect. This study was one of few to survey small mammal diversity and abundance in fragmented forests in the Eastern Cape. Gradient, patch size and mean annual potential evaporation were the variables that best predicted the individual number of small mammal captures while only gradient best explained species richness. It does however, need to be noted that capture rates and species richness were very low and this would therefore effect the analysis of environmental variables. Future studies should have a larger sample size of forest patches and include more microhabitat environmental variables to determine their effects on small mammal diversity and abundance. However, it should be noted that through climatic extinction filtering, forest mammals are resilient generalists that can tolerate fragmentation effects. Furthermore, it was found that forest edges appear to play a significant role in small mammal diversity and abundance in the Beggars Bush Afromontane forest. Some species were habitat specialists such as Rhabdomys pumilio preferring the grassland habitat and Graphiurus murinus and Aethomys namaquensis the forest habitat, while Myosorex varius was the only species that was not habitat dependant. It was found that there was a greater diversity and abundance at the forest edge compared to within the forest core throughout most of the seasons. One possible flaw was that the sampling methods were different at the edge and within the forest and therefore future studies should ensure that the method stays uniform throughout the study.