Thesis (Ph.D.)(Geo-Informatics), University of Pretoria, 2006. / Includes summary. Includes bibliographical references. Available on the Internet via the World Wide Web.

The post journals of certain Hudson's Bay Company forts were examined for evidence that air mass frequencies during the first half of the nineteenth century were markedly different from those of a modern (1955-1959) period. The "partial collective" technique of Bryson was used to determine the modern frequencies and to provide the basis of the conditional probability structure employed to estimate the historic air mass frequencies. There is evidence from each station for which analysis was performed of a greatly increased presence of "Arctic" air, probably as a consequence of a weakened zonal atmospheric circulation and a decrease in the eastward penetration of "Pacific" air. / Arts, Faculty of / Geography, Department of / Graduate

MENVSC (Geography) / See the attached abstract below

Climate models are software tools that simulate the climate system and require evaluation to assess their skill, guide their development, and assist in selecting model simulations from among the many different ones available. There are a variety of methods and approaches that can be used to evaluate models. But there is no one best method and many possible and valid approaches exist. Models contain inherent uncertainties which complicate their evaluation, and include limitations in the knowledge of climate process dynamics and structural errors in constructing the models. Similar to the multiplicity of methods for the evaluation of model simulations, there also exist many possible approaches to addressing these sources of uncertainty. The challenge with uncertainty, is the difficulty in disaggregating it from the underlying element of legitimate chaotic behaviour in complex systems. In response, this dissertation is primarily one of methodological development to contribute to new ways of addressing the model evaluation challenge. The work defines and demonstrates a new evaluation method which complements the existing toolset. Specifically, the method defines a model performance metric that focuses on the extent to which a model is able to simulate global modes of climate variability (modes, e.g.: ENSO) evident in the observed climate data. Modes are one aspect of the climate that can be evaluated and are fundamental to model skill. Therefore their credible simulation is a necessary (but not sufficient) condition to ensuring that models are producing the right result (appropriate variability on the range of spatial and temporal scales) for the right reason. By ranking models by this metric of their skill in capturing fundamental global modes, poorly performing model simulations can be identified for potential exclusion (discounted). This metric therefore serves as a potential method to assist in the management of uncertainty when assessing multi-model data. The method develops a novel application of Independent Component Analysis (ICA). ICA is used to find representations of modes in a record of the present day climate (represented by reanalysis data), and then their degree of manifestation in global models is assessed. Recognising the large volume of model data (highly autocorrelated in space and time) the technique includes a data reduction technique to facilitate the evaluation of multiple model simulations. The technique also includes a novel measure of variance to differentiate it from a similar technique (Principal Component Analysis), and offers an approach to improve the consistency of results (signals) when using an unmixing matrix initialized with random values. As reanalysis data is itself a model product (constrained by observations), the performance metric is tested for its strength in discriminating modes by using two different reanalysis datasets and a dataset containing only Gaussian noise. The metric is found to perform predictably, and clearly demonstrates the ability to discriminate signal from noise when using geopotential height (GHT, 700mb and 500mb) and near surface air temperature data (TAS). The dependency of model performance on the variable measured by any metric can be a problem for model evaluation, as it introduces the choice of which variable should be measured to assess model performance. The ICA-based metric is found to be slightly less sensitive to a change in model rank between GHT (700mb) and TAS, compared to a similar novel variance metric (Fourier Distance) and a mean climate metric (bias). The ICA application is also found to produce plausible representations of modes (static maps), while a direct association to known modes is left for future work due to inherit complexities. The plausibility, consistency, and rank sensitivity of the novel application of ICA, suggests it has value in assisting the evaluation of multi-model datasets and the ensemble members for any one model.

The present research aimed first at testing the Theory of Planned Behaviour and the extended model of the Theory of Planned Behaviour in a non-WEIRD nation context (i.e., western, educated, industrialized, rich and democratic); and secondly, at exploring the role of social and economic status not as an outcome of climate change but as a factor that influences the appraisal of climate change and the responses to climate change (i.e., pro-environmental behaviour). Two cross-sectional studies were conducted. Study 1 (N = 452) replicated previous findings in support of the Theory of Planned Behaviour; but also showed the important role of moral obligation and emotions such as guilt. Different to previous research, instrumental rather than experiential attitudes revealed to be associated with intention and pro-environmental behaviour. The latter finding was replicated in Study 2 (N = 681), which also aimed at exploring the role of social and economic status for both appraising climate change as threat and responding to climate change. Both objective and subjective socio-economic status did indeed influence responses to climate change (i.e., pro-environmental behaviour) and whether climate change was appraised as a threat. However, the effects of objective and subjective socio-economic status were opposite than expected. Implications of the present research are outlined in detail with regards to current discourses on appraisals of and responses to climate change. / Psychology

Climate change and endocrine disrupting chemicals are currently amongst key drivers for a range of non-communicable diseases and adverse human health conditions. Pesticides constitute an important source of endocrine disrupting chemicals. A growing public health concern is the potential relationship between climate change and adaptive increases in agricultural pesticide use. Effectively, with increases in pesticide use, there may be increased potential for elevated pesticide exposures and, thus, increased endocrine disrupting health risks. The aim of this thesis was to assess whether climate change is a key risk perpetuating factor for endocrine disrupting health risks due to increased agricultural pesticide uses and exposures. The study was conducted in Zimbabwe with farmers in the cotton farming district of Rushinga. Three research methods: 1) interviews with farmers, 2) quantitative structure-activity relationship modelling and, 3) stakeholder interviews with government cotton agronomists working in Rushinga district who acted as key informants. Qualitative in-depth interviews were conducted with 50 active smallholder farmers who had grown cotton for a minimum of 30 years. The interviews gathered farmers' perceptions and observations regarding climate change, changes in pest types, pest populations, pesticide use patterns, pesticide handling practices, and adaptive practices, amongst others. Quantitative structure-activity relationship modelling was, further, applied in identifying key risk pesticides of concern. Amitraz, endosulfan, fenvalerate and lambda-cyhalothrin were determined as having a high likelihood of acting as endocrine disruptors, as validated by literature highlighting the four pesticides' hormone-related cognitive, physiological and reproductive adverse health effects. Findings indicated that a number of farmers' adaptative practices were found to be incremental and, potentially, maladaptive, thereby enhancing pesticide use and exposure. This was indicative of climate change's potential for perpetuating pesticide-related endocrine disrupting health risks. Opportunities exist, however, for farmers to reduce pesticide use, and, thus, potential endocrine disrupting health risks through certain autonomous transformational adaptive practices, such as crop switching and cotton acreage reduction. Assistance to farmers by the government and development agencies, for enhancing opportunities for transformational adaptation is therefore recommended. Furthermore, there is need, at policy level, for phasing out pesticides with endocrine disrupting properties. There is, furthermore, a clear need for enhancing farmers' access to, and comprehension of, pesticide risk information through various innovative means, including research translation to reduce exposure risks.

Climate change is causing loss and damage (L&D) to those who are unable to adapt to its impacts. Coming from a growing recognition that adaptation to climate change has limits, the concept of L&D is a relative new-comer to the international agenda on climate change. To reduce L&D and compensate for it, the United Nations Framework on Climate Change (UNFCCC) first needs to understand what these residual impacts of climate change are. However, the literature on lived-experiences of L&D is limited, especially on non-material L&D which is more difficult to measure. Using Warner et al. (2013) definition of L&D, this study first assesses what material and non-material losses and damages from the Cape Town drought have been on a group of urban-poor women farmers. Then, this research uses a barriers and enablers to adaptation framework to understand how to reduce these losses and damages. This qualitative case-study investigates women farmers’ lived-experiences of L&D during the 2015-2017 drought in Gugulethu, a low-income settlement in Cape Town, to feed into broader debates on ways to reduce L&D in global south cities. Semi-structured interviews were conducted with six women farmers from the Umthunzi Farming Community and five other actors involved in urban agriculture in Gugulethu. The findings suggest that women farmers in this context are already experiencing L&D, with psychological, physical and social implications which appear to be particularly pertinent to their group. All participants had to reduce or stop farming which led to L&D on their urban agriculture benefits as well as L&D on their institutional trust towards the City of Cape Town. Most of these L&D were non-material. Some of the barriers to adapt and reduce L&D were a lack of external support (from the city and NGOs), a lack of financial capacity to adopt coping measures and a lack of knowledge on the possible coping measures and external support options. Enablers to reduce L&D from the drought were access to support from the Western Cape Department of Agriculture (DoA), higher levels of education, a diversity of livelihoods and a strong network with other farmers. In conclusion it emerged that external support from government departments and NGOs to urban-poor women farmers is important for adapting to the possibility of future droughts. The vulnerability of these women farmers in low-income areas need to be addressed at their roots. These emerging conceptual openings emphasise the importance of exploring lived-experiences of L&D to better reduce the risk of L&D in vulnerable communities. Further research is necessary on compensation for unavoidable L&D, which is beyond the limits of this research.

Namibia is almost entirely semi-arid or arid. With evaporation rates being higher than precipitation rates, farming conditions are extremely adverse. This is exacerbated by the impacts of climate change, namely increased temperature, decreased rainfall and higher rainfall variability, all of which are projected to worsen in the future. More than half of the population is reliant on rain-fed subsistence agriculture for their source of food but these challenging conditions mean that there is widespread food insecurity across the subsistence farming community in Namibia. This leads to a state of vulnerability and dependence on government support in the form of social grants, food aid and remittances from family members in urban areas. The locus for this study is three villages: Omaenene, Okathitukeengombe and Oshihau, in the north-central Omusati region of Namibia. This research investigated local perceptions of climate change vulnerability, farming practices used in other regions that could reduce this vulnerability and finally barriers and enablers to the uptake of new farming practices. These objectives were answered through the use of a systematic literature review and interviews with the local community. Findings revealed that the local population is already experiencing a hotter and drier climate, which has decreased their yield output. Many farmers are concerned about future climatic changes while some are comforted by support from the government or God. In both of these cases, the farmers are vulnerable because they are not currently adapting or planning to adapt to climate change. Although a majority of the farmers claimed that they are willing to try new farming practices, they are inhibited by: limited access to new information, mistrust of new farming practices as well as insufficient labour and resources. Three adaptive farming practices – planting pits, bunds and composting – aimed predominantly at water harvesting, soil conservation and increasing soil quality were selected by the researcher, from a systematic literature review, as appropriate for the village sites. Some of the social and institutional enablers that could be enhanced to promote the uptake of these practices are: i) support from local authorities and possibly enlisting the help of religious and traditional leaders (including building trust within these networks), ii) enhancing information access predominantly through the radio, iii) explaining the severity of climate change and the value of adaptation practices, iv) establishing self-help labour groups and v) the creation of demonstrations sites. In the face of irreversible climate change, this research aims to contribute to empowering local people to adapt their farming practices to the harmful experienced and predicted impacts of climate change and climate variability.

Bibliography: leaves 111-117. / Swartboschkloof forms part of the Jonkershoek catchment complex at the headwaters of the Eerste River, Cape Province, South Africa. It has been selected for multi-disciplinary studies of Mountain Fynbos vegetation. The study area has a mainly equatorial aspect (north-facing) and receives an average of 1600 mm rain per annum, mainly in winter. Temperatures do not reach extremes. Winds blow mainly from the south-east, increasing in strength in summer. North-west winds blow intermittently in winter, bringing rain. The altitude of Swartboschkloof ranges between 285 m and 1200 m and the soils are derived from quartzitic Table Mountain Sandstone and porphyritic Cape Granite. Using the Braun-Blanquet phytosociological method, vegetation and environmental data were collected at 201 relevés throughout the study area; 101 of these relev~s are correlated with a survey of soils of part of the same area. Sixteen fynbos communities, grouped into three groups and five forest communities, grouped into two groups, have been identified. The data of a previous study by Werger, Kruger and Taylor (1972) have been interpreted in the context of this study. A map of the plant communities has been drawn and an attempt has been made to explain the distribution of the communities in terms of environmental factors. There is a strong link between the vegetation and soil geology but application of a method such as principal components analysis would be necessary to explain the relationship clearly.

Central America has been identified as one of the regions in the world where potential climate change impacts on the environment can be pronounced and is considered a climate change ‘hot-spot’. The Intergovernmental Panel on Climate Change Fourth Assessment Report indicates that the region around the western Caribbean and Central America is one where a majority of the climate model simulations indicate rather large changes in temperature and precipitation. This region, however, is one with considerable topographic relief, which implies the existence of large gradients in many critical climate variables. The interactions between the complex topography of Central America and the neighboring oceans give rise to numerous climate zones, horizontally and vertically. Consequently, the region has high biodiversity, it harbors high-value ecosystems and it is important to provide more realistic scenarios to assist in adaptation and mitigation work in the region. In this study, I aim to understand climate change in Central America at spatial scales relevant for impacts assessment. A regional climate model PRECIS was employed to carry out two experiments: the baseline (present-day) run and the scenario run, both performed at 25-km horizontal resolution. The thorough examination of the model performance showed model’s success in capturing the spatial and temporal variability of the key climate variables and its strength in simulating topographically-induced regional climate features. The projected increase in temperature, a large decrease in precipitation in most of Central America, and corresponding hydrological changes under the A2 scenario may have serious negative consequences on water resources, agricultural activities and the ecosystem dynamics in the region.