To study the quality response of beetroot to nitrogen fertilizers, a pot trial was conducted in the glasshouse facility of the Department of Soil, Crop and Climate Sciences, Faculty of Natural and Agricultural Sciences, University of the Free State, during the 2011 season. The effect of five nitrogen sources (limestone ammonium nitrate, ammonium nitrate, urea, ammonium sulphate and urea ammonium nitrate) at five nitrogen levels (0, 50, 100, 150 and 200 kg N ha-1) on beetroot (Detroit Dark Red) on a Bainsvlei soil type was investigated. The data collected was analyzed using Tukeyâs Least Significant Difference test, at 5% level of significance to determine statistically significant differences between means. The results showed that all fertilizers used resulted in a reduction in plant height for the first six weeks of growth. Nitrogen application only increased plant height significantly from week 8 where the height of plants that received nitrogen, irrespective of the fertilizer used, were significantly taller than control plants. At week 8 no significant differences in height were noted between various nitrogen application rates, but by week 10 significant differences in plant height were noted between the 50 kg N ha-1 and 150 kg N ha-1 or 200 kg N ha-1 application rates. The findings showed that beet plants reacted better to N-fertilization using ammonium sulphate nitrate and urea ammonium nitrate than other nitrogen sources, although limestone ammonium nitrate and ammonium nitrate also produced improvements in plant growth, whereas plants that received urea showed no improvements. Nitrogen at 100 kg ha-1 resulted in more leaves per plant than its application at other levels. Urea ammonium nitrate as a nitrogen source significantly improved plant leaf area, leaf fresh mass, total fresh mass and root diameter. Application of nitrogen at 200 kg ha-1 also increased leaf area, leaf fresh mass, total fresh mass, beet diameter and beet volume. Urea ammonium nitrate increased leaf dry mass by an average of 397% while the lowest leaf dry mass by (139.42% of control) was observed with the use of limestone ammonium nitrate as a nitrogen source. The greatest leaf dry mass was obtained at the highest rate of nitrogen application (200 kg ha-1) and the lowest leaf dry mass was observed at the control level. Beet yields were found to increase as the nitrogen application rate increased, from 2.99 t ha- 1 in the control treatments to 14.37 t ha-1 in the treatments that received 200 kg N ha-1. Fertilizing with urea ammonium nitrate gave the highest yields (12.17 t ha-1), while using limestone ammonium nitrate gave the lowest yields (9.00 t ha-1). Application of nitrogen at 50 kg ha-1 resulted in firmer beets than nitrogen application at other levels. Beets from plants that did not receive any nitrogen were significantly softer than those that received nitrogen at higher levels. The darkening of beet colour (decrease of L*) was experienced at the control level while the highest changes of colour (increase of L*) was obtained at the highest nitrogen level. Nitrogen at 100 kg ha-1 influenced the lowest change of coefficient a from red to green while the control level resulted in more intensive change. The results showed that nitrogen at the control level led to more intensive changes of coefficient b colours from yellow to blue and its application at the highest level resulted in less intensive changes of coefficient b colours from yellow to blue. Neither nitrogen source nor nitrogen level had any effect on the pH, sucrose or fructose contents of the roots. Application of nitrogen at 150 kg ha-1 resulted in greater total soluble solids content in the roots, while the starch content of plants that received no nitrogen was significantly greater than that of plants receiving nitrogen. Nitrogen application at 100 kg ha-1 and at the control level influenced the glucose content, which was significantly higher in these plants than in those that received 50, 150 and 200 kg N ha-1, however, the highest glucose content of the roots was observed at the control level. Nitrogen application at 200 kg ha-1 resulted in higher nitrogen content in the leaves as compared to application of other nitrogen sources at different levels. Limestone ammonium nitrate influenced potassium content of the leaves more than other nitrogen sources. Nitrogen application at 200 kg ha-1 resulted in a greater calcium content in the leaves than other nitrogen sources. The highest sodium content of the leaves was observed at 150 kg N ha-1 while the lowest sodium content was observed at 50 kg N ha-1. Urea ammonium nitrate had a greater positive influence on the manganese content of the leaves than other nitrogen sources. Plants that received no nitrogen had significantly greater levels of iron in the leaves than at all nitrogen levels. Ammonium nitrate as a nitrogen source influenced the calcium content of the beets more than other nitrogen sources. Other root minerals such as phosphorus, potassium, sodium, magnesium, manganese, copper, iron and zinc were not significantly influenced by nitrogen source or nitrogen level, or the interaction between these factors.

Wetland hydrology controls the function of the wetland ecosystem and hence it is the principal parameter for delineation and management of wetlands. It is defined as the water table depth, duration, and frequency required for an area to develop anaerobic conditions in the upper part of the soil profile leading to the formation of iron and manganese based soil features called redoximorphic features. The redoximorphic features must occur at specific depths in the soil profile with specific thickness and abundance to qualify for a hydric soil indicators. Therefore, hydric soil indicators are used to evaluate the wetland hydrology if such a relationship has been verified. The aims of the study were i) to determine soil variation and hydric soils indicators along a toposequence, ii) to determine the relationships between soil water saturation, redox potential and hydric soil morphological properties and iii) to determine the distribution of soil properties and accumulation of soil organic carbon in hydric and non-hydric soils. The study was conducted at the upper head-water catchment of the Bokong wetlands in the Maloti/Drakensberg Mountains, Lesotho. The soil temperature ranged between -10 and 23°C. The soils had a melanic A overlying an unspecified material with or without signs of wetness, or a G horizon. The organic O occurred in small area. Soil profiles were dug along a toposequence and described to the depth of 1000 mm or shallower if bedrock was encountered. Redoximorphic features were described using standard soil survey abundance categories. Soil samples were collected from each horizon and analysed for selected physical and chemical soil properties. The soils had low bulk density ranging from 0.26 in the topsoil to 1.1 Mg m-3 in the subsoil. Significantly low bulk density was observed in the valleys and highest bulk densities were observed on the summits. The soil organic carbon content ranged between 0.18% in the subsoil and 14.9% in the topsoil. The soil also had a high dithionite extractable Fe (mean 93±53 g kg-1) and low CEC (mean 26±9 cmolc kg-1). Soil pH and CEC were relatively lower in the valleys and higher on the summits. Principal component analysis indicated four principal components accounted for 60% of the total variance. The first principal component that contributed 23% of the variation showed high coefficients for soil properties related to organic matter turnover, the second components were related to inherent fertility, the third and fourth were related to acidity and textural variation. Hydric indicators identified in Bokong were histisols (A1), histic epipedon (A2), thick dark surfaces (A12), redox dark surfaces (F6), depleted dark surfaces (F7), redox depressions (F8), loamy gleyed matrix (F2) and umbric surfaces (F13). The thick dark surfaces with many prominent depletions and gley matrix (A12 and F7) occurred in the valleys, while the midslopes and footslopes were dominated by umbric surfaces (A13). The indicators F6, F7 and F8 were not common. Indicators that were related to the peat formation (A1, A2 and F13) were frequently observed. The relationship between soil water saturation and redoximorphic features was verified by monitoring the groundwater table with piezometers, installed in ten representative wetlands at depths of 50, 250, 500, 750, and 1000 mm for two years from September 2009 to August 2011. Redoximorphic feature abundance categories were converted into indices. Strong correlations were observed between redoximorphic indices and cumulative saturation percentage. The depth to chroma 3 and 4 (d_34) and depth to the gley matrix (d_gley) correlations were R2 = 0.77 and R2 = 74 respectively. All redoximorphic indices were poorly correlated with average seasonal high water table. Strong correlation were also observed between profile darkening index (PDI) and cumulative saturation (R² = 0.88) and weak correlations were observed between PDI and average seasonal high water table (R² = 0.63). A paired t test indicated that soil pH, exchangeable Mg and Na, dithionite extractable Fe and Al were significantly different between hydric and non-hydric soils. Hydric soils had significantly higher Mg, Na and Fe content, and significantly low soil pH and Al content. Generally it appeared that soluble phosphorus, Fe and exchangeable bases accumulated in hydric soils, while the soil pH and Al content decreased. The mean soil organic carbon contents were 3.61% in hydric soils and 3.38% in non-hydric soils. However, non-hydric soil relatively stored more organic carbon (174.4 Mg C ha-1) than hydric soils (155.1 Mg C ha-1). The mean soil organic carbon density of the study area was 166±78.3 Mg C ha-1) and the estimated carbon stored was 21619 Mg C (0.022 Tg C; 1Tg = 1012g) within the 1000 mm soil depth. About 384.9 Mg C was stored in the hydric soils within the study area, which was about 1.9% of the total carbon stored in the area to the bedrok or depth of 1000 mm. Among the wetland types, bogs had significantly higher organic carbon levels (6.17%) and stored significantly higher carbon (179 Mg C ha-1) with at least 44% was store in the A1 horizon. It was concluded that the strong correlation observed between PDI, d_34, d_gley and cumulative saturation representing hydric indicators such as histisols (A1), histic epipedon (A2), umbric surfaces (F13), loamy gleyed matrix (F2) can be used to determine the duration and frequency of the water table in the landscape studied. These hydric indicators can be used to delineate wetlands, however, more indicators can be developed.

South Africa mainly produces oil seed sunflowers of which 86% is produced in the Free State and North West provinces which are known for their sandy soils. Temperatures can rise to 42°C in these soils when planting commences during November to January. These conditions, in combination with other factors such as planting date and planting depth, soil type, different cultivars, and seedling vigour, can influence the emergence rate of sunflower seedlings. This will cause uneven stand which could affect the yield negatively. In an attempt to evaluate the influence of soil factors and planting techniques on sunflower emergence, three experiments were conducted in the greenhouse at the Department of Soil, Crop and Climate Sciences of the University of the Free State. These experiments evaluated the effect of seed size, planting techniques, and soil factors, and high soil temperatures on the emergence rate of selected sunflower cultivars. Three seed sizes (seed size one to three) of three cultivars (PAN 7049, PAN 7057, and PAN 7063) were planted at two planting depths (25 and 50 mm respectively) during three planting dates (September 2010, November 2010, and February 2011) to determine the influence on the emergence rate of seedlings. It was found that a smaller seed size, such as seed size three, emerged faster than larger seeds, seed size one. The influence of two planting depths (25 and 50 mm) during the previously mentioned planting dates with two soil types (Bainsvlei and Tukulu) on the emergence of sunflower seedlings was also tested. Cultivar emergence was faster at 25 than at 50 mm. It was also observed that the emergence rate was faster during February 2011 than during September and November 2010. Although the emergence was faster during February 2011, above ground growth (plant height and dry weight) was greater during November 2010 than during September 2010 and February 2011. The influence of four soil temperatures (35, 40, 45, and 50°C respectively) on the emergence of sunflower cultivars was tested. An under floor heating wire (23 kW) was attached to a galvanised metal grid and was used to simulate day and night temperatures in the top soil. The grid and seed were placed at a depth of 25 mm (planting depth). Emergence index declined gradually from 35 to 45°C, but a rapid decline in emergence index was observed from 45 to 50°C. Emergence can be measured or calculated as an emergence index. Emergence is determined as the moment that the seedling is visible above the ground and different formulas exist to determine the emergence. Experiments differ from one another and therefore different emergence index models were developed to accommodate the experiment methods or crop that was used. It can therefore be concluded that differences in emergence exist between cultivars. It is also necessary for producers to acknowledge that soil factors and planting techniques play a vital role during planting until the seedling emerge.

This work studies the links between the Lagrangian transport in the Southern Benguela upwelling system and the ocean circulation through modelling experimentation. More specifically, it intends to show that the wind-induced circulation at short-time scales impacts the drift of Lagrangian particles released in the model. Three ocean model (ROMS) simulations are set-up. Simulation A is forced with a6 hourly atmospheric forcing (surface heat and fresh-water fluxes and wind stress). In simulation B and C, the atmospheric forcing is low-pass filtered with 5 days and 30 days cut-off periods. The ocean model outputs are averaged and saved at deferent temporal frequency: frequencies of 6 hours and 3 days. Particles released in the Lagrangian tracking tool are transported by the velocity vectors produced by the ocean model into the nursery area located at Saint Helena Bay. The presence of short-term fluctuations result in higher inner shelf transport and amore elongated plume dispersion pattern with much refine spatial scales. This finding contrasts with previous studies where the inner shelf transport success was always low compared to the outer shelf nursery. When the high frequency signal is filtered out, the inner shelf transport is greatly reduced especially during the upwelling season. The archiving frequency of the ROMS output is shown to impact Lagrangian studies, especially when the atmospheric forcing has variability at short time scales (less than 5 days).Monthly mean forcing results in dynamics variable with periods of not less than a month and 5 daily averaged forcing with sub-weekly dynamics. Therefore, in simulations B and C the less than 3 days archiving of the model outputs is not necessary, because their forcing does not generate dynamics with such periods. The latter must be adapted so that it does not filter out the ocean response to the high frequency atmospheric forcing. To explain the Lagrangian transports, as a first approach, the transport success was linked to the variability of the ocean circulation.

The Agulhas Current System is a vital element of the global ocean-climate system by virtue of its role in the transfer of energy, nutrients and organic material. In the context of working towards better climate change projections, it is necessary to develop a robust understanding of the complex dynamical mechanisms which facilitate this transfer. Mesoscale cyclonic and anticyclonic eddies transport heat, salt, organic matter and nutrients from the Indian Ocean into the South Atlantic Ocean. In so doing, they are key drivers of the Atlantic Meridional Overturning Circulation (AMOC). As such, it is important that they are adequately simulated by numerical models in order to advance the accuracy of climate prediction. In the absence of spatially and temporally coherent observing systems, numerical models provide the capacity to describe the oceanographic conditions of the region. Given the complexity of the regional dynamics, and the challenges it presents to free-running numerical models, data assimilation is a valuable tool in improving simulation quality. An important step in this continuing process is the objective, quantitative evaluation of model configurations, such that they can be continuously refined. In this study, the impact of assimilating along-track sea level anomaly (SLA) data is investigated with regard to the simulation of mesoscale eddies in the Agulhas System. Two configurations of a Hybrid Coordinate Ocean Model (HYCOM) configuration are analysed; one free run (hereafter 'Free') and one with along-track SLA data from satellite altimetry assimilated (hereafter 'Assim.') via an Ensemble Optimal Interpolation (EnOI) data assimilation scheme. The results of these two configurations are compared with each other, and against a set of corresponding observational data from satellite altimetry (hereafter 'Aviso'). To this end, an automatic eddy detection and tracking algorithm is implemented, in order to quantify eddy characteristics in a coherent and consistent manner.

Topography influences climate dynamics by redirecting how the atmosphere transports moisture, and energy. By doing so, topography alters precipitation patterns, circulation of wind, riverine fluxes, and ocean upwelling distributions. This dissertation investigates the linkages between major topographic features and atmospheric dynamics within an Earth System perspective. The studies presented build upon the foundations of theoretical atmospheric thermodynamics and dynamical principles and primarily delves into the interactions between the Indo-Asian Monsoon and the surrounding topographies. First, I explore gaps in the current body of literature, mainly using observational datasets and reanalysis products. I then add in more sophisticated tools, such as general circulation models (GCMs) to investigate how terrain orogen impact the regional climatic regime with an emphasis on the monsoonal environment. To do so I explore drawbacks in using currently available GCMs and demonstrate the necessity of utilizing appropriate model horizontal-grid resolution when studying atmosphere-terrain interactions. I then delve into reexamining previously explored monsoon theories, and develop new concepts and theories for the Indo-Asian Monsoon. Lastly, I apply such model tools to further understand the orogen of the Tibetan Plateau. To do so, I examine the paleoenthalpy methods and determine its viability in measuring the paleoelevation of the Tibetan Plateau. Ultimately, we apply this method to aid the paleoclimate community in deciphering the evolution of Tibet during the Cenozoic era. Constraining the evolution of the regional topography is crucial for understanding the hydrological cycle and the climatic evolution of Eurasia.

<div> <div> <div> <p>The mid-Miocene Climatic Optimum (MMCO), 17-14.50 million years ago, is studied using general circulation models (GCMs). This period of time is characterized by enhanced warming in the deep ocean and in the mid-to-high latitudes. Previous GCMs fail to accurately represent the warmer climate of the MMCO, providing evidence that other warming feedbacks are missing in the models. This study focuses on cloud feedbacks by modifying the Community Earth System Model (CESM 1.0) to explore the MMCO climate. We implement modifications in pre-industrial (284.7 ppm CO2) and modern slab ocean cases (367.0 ppm CO2, 400 ppm CO2, and 800 ppm CO2). One modified case showing the most potential implements an aerosol de- pendent ice nucleation mechanism and a theory based cloud phase separation. This modified case allows the model predicted aerosol concentrations to interact with the cloud microphysics and provide more realistic cloud water contents. The data shows an increase in surface temperature and increase in upper atmospheric cloud fraction when compared to the control case. Preliminary results suggest that this model is able to capture the mid-to-high latitude warming trends and weaker equator to pole temperature gradient. </p> </div> </div> </div>

Climate change has emerged as one of the most critical issues of the 21st century. It stands to impact communities across the globe, forcing individuals and governments alike to adapt to a new environment. While it is critical for governments and organizations to make strides to change business as usual, individuals also have the ability to make an impact. The goal of this thesis is to study the beliefs that shape climate-related attitudes and the factors that drive the adoption of sustainable practices and technologies using a foundation in statistical learning. Previous research has studied the factors that influence both climate-related attitude and adoption, but comparatively little has been done to leverage recent advances in statistical learning and computing ability to advance our understanding of these topics. As increasingly large amounts of relevant data become available, it will be pivotal not only to use these emerging sources to derive novel insights on climate change, but to develop and improve statistical frameworks designed with climate change in mind. This thesis presents two novel applications of statistical learning to climate change, one of which includes a more general framework that can easily be extended beyond the field of climate change. Specifically, the work consists of two studies: (1) a robust integration of social media activity with climate survey data to relate climate-talk to climate-thought and (2) the development and validation of a statistical learning model to predict renewable energy installations using social, environmental, and economic predictors. The analysis presented in this thesis supports decision makers by providing new insights on the factors that drive climate attitude and adoption.

Geoengineering is the intentional alteration of the Earth’s climate system. The international Geoengineering Model Intercomparison Project (GeoMIP) seeks to identify the potential benefits and side effects of geoengineering on the Earth's climate. This thesis examines the first two experiments from the contribution of the Canadian Centre for Climate Modelling and Analysis to GeoMIP. In the first experiment (G1), atmospheric carbon dioxide concentrations are quadrupled and the solar constant is reduced to offset the increased greenhouse gas forcing. In the second experiment (G2), atmospheric carbon dioxide concentrations are increased at the rate of 1% per year and the solar constant is incrementally reduced to offset the greenhouse gas forcing. In concert with these experiments, results from two other experiments were analyzed, one in which the atmospheric greenhouse gas concentrations are quadrupled one in which they are increased at the rate of 1% per. The results obtained are in broad agreement with earlier work, showing that solar radiation management geoengineering schemes can prevent an increase in mean global surface temperature as atmospheric carbon dioxide concentrations increase. Though the mean global temperature remains constant while geoengineering is employed, there are regional and zonal differences from the control climate, with high latitude warming and cooling in the tropical and subtropical regions. In particular, the meridional temperature gradient is reduced compared to that of the control climate. The G2 experiment was very similar to the G1 experiment in terms of the spatial surface temperature changes, though the changes seen in the G2 experiment were less pronounced and the regions of statistical significance were smaller. During the geoengineering period, seasonal changes and a statistically significant decrease in global precipitation, particularly over the ocean were apparent in the G1 run. As with temperature, the spatial pattern of precipitation changes during the geoengineering period for G2 are similar to the same period in G1, but reduced in magnitude. However, most of the spatial changes to precipitation in the G2 experiment during geoengineering deployment fail to be statistically significant. Following geoengineering termination, the G1 experiment responds rapidly, with surface and ocean temperatures, NH and SH summer sea ice volume, AMOC transport volume and global precipitation following the same time evolution and reaching those same values found in the 4 × CO2 experiment’s first 10 years. Following geoengineering failure, the G2 run also experiences rapid climate change in all of the variables studied, but does not approach the first 10 years of the 1%CO2yr-1 experiment, because the forcings are quite different in the two runs. Taken together, these results suggest that, while geoengineering to reduce incoming solar radiation could offset the global temperature increase due to increased atmospheric greenhouse gas concentrations, there would be regional warming and cooling, as well as both global and regional impacts on the hydrological cycle. These results also suggest that, should geoengineering suddenly stop, the Earth’s climate would react immediately, with rapid changes in nearly all of the climate variables examined. / Graduate

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