Browsing by Author "Kotzee, Ilse M"

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    Flood hazards in a changing world: Challenges and opportunities in the Garden Route
    (2022-07) Smith-Adao, Lindie B; Blanchard, R; Kotzee, Ilse M; Le Maitre, D; Ntshotsho, Phumza; Audouin, Michelle A; Forsyth, G; Walters, M
    In its 2022 Global Risks Report, the World Economic Forum states that environmental concerns dominate the top five long-term risks (in terms of likelihood) with three of them also being among the top five in terms of impact. Biodiversity loss and ecosystem collapse, as well as climate action and adaptation failure and extreme weather are highlighted as the top three environmental risks over the next ten years. Anthropogenic environmental disasters, natural disasters and water crises are expected to have significant impacts on economic stability and social cohesion over the next decade (World Economic Forum (WEF), 2022).
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    Human dependence on natural resources in rapidly urbanising South African regions
    (IOP Publishing, 2019-01) Balbi, S; Selomane, O; Sitas, Nadia E; Blanchard, Ryan; Kotzee, Ilse M; O’Farrell, Patrick J; Villa, F
    Enhancing the governance of social-ecological systems for more equitable and sustainable development is hindered by inadequate knowledge about how different social groups and communities rely on natural resources. We used openly accessible national survey data to develop a metric of overall dependence on natural resources. These data contain information about households' sources of water, energy, building materials and food. We used these data in combination with Bayesian learning to model observed patterns of dependence using demographic variables that included: gender of household head, household size, income, house ownership, formality status of settlement, population density, and in-migration rate to the area. We show that a small number of factors – in particular population density and informality of settlements – can explain a significant amount of the observed variation with regards to the use of natural resources. Subsequently, we test the validity of these predictions using alternative, open access data in eThekwini and Cape Town metropolitan areas of South Africa. We discuss the advantages of using a selection of predictors which could be supplied through remotely sensed and open access data, in terms of opportunities and challenges to produce meaningful results in data-poor areas. With data availability being a common limiting factor in modelling and monitoring exercises, access to inexpensive, up-to-date and free to use data can significantly improve how we monitor progress towards sustainability targets.