In 2006, a baseline survey for the UNEP/GEF-IAS Project was conducted in BFR to assess the status of IAS in the area. Findings indicated that extensive forest parts had severe S. spectabilis encroachment which appeared to interfere with the normal functioning and productivity of the forest. This study was motivated by the magnitude of S. spectabilis invasion in BFR, the level of public and government concern about the invasion, and the magnitude of the IAS problem across East Africa. This study was thus undertaken to address a specific need of the research and capacity building components of the UNEP/GEF-IAS Project. The study1 was carried out to assess the impacts of S. spectabilis invasion on the productivity of BFR and the socio-economic implications on the livelihoods of the dependent stakeholders (local resident population, timber suppliers and the tourism sector). The study used descriptive statistics to assess the levels of awareness of S. spectabilis invasion, perceptions and knowledge of the conservation values of BFR, knowledge on the benefits and costs of living with S. spectabilis and impacts of S. spectabilis on the flow of quantities and revenues from the benefits it generates. The impact on financial profitability and efficiency of timber firms was assessed using Gross margin analysis (GMA) and financial efficiency ratio analysis respectively. The impact on the population structure of chimpanzees was studied using mean differentials and focused group discussions. Results indicate that the level of awareness about S. spectabilis invasion and the knowledge of the conservation values of BFR were high among all the three stakeholder groups. GMA revealed that S. spectabilis invasion increases variable costs in timber production thus reducing profit margins and financial efficiency of timber firms. Alteration of habitat environment occasioned by S. spectabilis invasion was advanced, though with uncertainty, as a possible reason for the difference in chimpanzee numbers between the infested and non infested forest conditions. Like other IAS, S. spectabilis was found to have both benefits and costs though the distribution of the same differs. S. spectabilis can be considered a net benefit to the local dependent communities whereas it may be a net loss to both the timber and tourism sectors. Conflict of interest in S. spectabilis management is discussed and possible solutions suggested. It was recommended that the threat of invasive species should be tackled through a multisectoral approach. / Dissertation (MSc)--University of Pretoria, 2009. / Agricultural Economics, Extension and Rural Development / unrestricted

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Ecological niche modelling is a method designed to describe and predict the geographic distribution of an organism. This procedure aims to quantify the species-environment relationship by describing the association between the organism’s occurrence records and the environmental characteristics at these points. More simply, these models attempt to capture the ecological niche that a particular organism occupies. A popular application of ecological niche models is to predict the potential distribution of invasive alien species in their introduced range. From a biodiversity conservation perspective, a pro-active approach to the management of invasions would be to predict the potential distribution of the species so that areas susceptible to invasion can be identified. The performance of ecological niche models and the accuracy of the potential range predictions depend on the quality of the data that is used to calibrate and evaluate the models. Three different types of input data can be used to calibrate models when producing potential distribution predictions in the introduced range of an invasive alien species. Models can be calibrated with native range occurrence records, introduced range occurrence records or a combination of records from both ranges. However, native range occurrence records might suffer from geographical bias as a result of biased sampling or incomplete sampling. When occurrence records are geographically biased, the underlying environmental gradients in which a species can persist are unlikely to be fully sampled, which could result in an underestimation of the potential distribution of the species in the introduced range. I investigated the impact of geographical bias in native range occurrence records on the performance of ecological niche models for 19 invasive plant species by simulating two geographical bias scenarios (six different treatments) in the native range occurrence records of the species. The geographical bias simulated in this study was sufficient to result in significant environmental bias across treatments, but despite this I did not find a significant effect on model performance. However, this finding was perhaps influenced by the quality of the testing dataset and therefore one should be wary of the possible effects of geographical bias when calibrating models with native range occurrence records or combinations there of. Secondly, models can be calibrated with records obtained from the introduced range of a species. However, when calibrating models with records from the introduced range, uncertainties in terms of the equilibrium status and introduction history could influence data quality and thus model performance. A species that has recently been introduced to a new region is unlikely to be in equilibrium with the environment as insufficient time will have elapsed to allow it to disperse to suitable areas, therefore the occurrence records available would be unlikely to capture its full environmental niche and therefore underestimate the species’ potential distribution. I compared model performance for seven invasive alien plant species with different simulated introduction histories when calibrated with native range records, introduced range records or a combination of records from both ranges. A single introduction, multiple introduction and well established scenario was simulated from the introduced range records available for a species. Model performance was not significantly different when compared between models that were calibrated with datasets representing these three types of input data under a simulated single introduction or multiple introduction scenario, indicating that these datasets probably described enough of the species environmental niche to be able to make accurate predictions. However, model performance was significantly different for models calibrated with introduced range records and a combination of records from both ranges under the well established scenario. Further research is recommended to fully understand the effects of introduction history on the niche of the species. Copyright / Dissertation (MSc)--University of Pretoria, 2009. / Zoology and Entomology / unrestricted