Increasingly, natural resources have come to be considered in dual dimension as objects that both increase the risk of violence and pose an opportunity to build peace. This linking of natural resources to question of conflict, peace, and security denotes the ‘securitisation’ of natural resources, taken to mean the “discursive construction of an existing threat to a referent object legitimizing extraordinary means.” This begs the question, what might these ‘extraordinary means’ entail? This thesis investigates this question by analysing the United Nations Environmental Cooperation for Peacebuilding’s 2016 report, a body tasked with researching the resource/conflict nexus and producing policy to address it. Utilising a post-structural policy analysis method, I denaturalise the claims made by the policy, applying governmentality, environmentality, and critical security theories to explain the logics and rationales underpinning resource securitisation, and the effects those rationales have. The analysis suggests that the policies security framing serves to represent resource conflict as manageable only through liberal governmental reforms associated with mainstream development practice, the UNEPs monopoly of technical peacebuilding expertise, and surveillance measures placed on unsuitable countries. By emphasising these as the primary solutions, the policy removes natural resource management from public control, downplaying populations agency, and maintaining existing power relations and inequalities.

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This thesis examines the relationship between the forestry industry and indigenous Sámi peoplein northern Sweden, focusing on institutional mechanisms for resolving land-use conflictsregarding forest logging on reindeer herding lands. Sámi reindeer herding communities andforestry companies have overlapping usage rights, making Swedish forests a common poolresource. Clear-cut forestry is damaging the reindeers’ access to lichen and the long-termsurvival of traditional reindeer herding, creating a need for effective Sámi influence in localforest decision-making. This study analyzes the recently reformed institutional framework forparticipatory planning and consultations, as well as participants’ experiences of Sámi influence.Interviews were conducted with three Sámi RHCs, two Sveaskog employees and one ForestAgency official. The theoretical framework draws from literature on co-management, commonpool resources and free, prior and informed consent to analyze Sámi space for influence. Resultsshow that the changes in regulations and practices have enabled RHCs space to withdrawconsent to specific logging plans under specific conditions, but influence is still limited. TheForest Agency has not consulted RHCs despite the new law, indicating continued difficultiesfor Sámi people to influence logging decisions on a local level. The main contribution of thisstudy is showcasing remaining barriers and positive developments based on original empiricalinterview material.

Thesis (M.Sc. (Statistics)) -- University of Limpopo, 2022 / Water is a precious natural resource and one of the most vital substance for sustainability of life . The increase in water evaporation is a major prob lem where factors such as high temperature and minimum rainfall are the contributing factors. The aim of the study was to perform time series mod elling of water evaporation from the selected dams in the Limpopo province South Africa. A daily evaporation time series data was used in the study with variables such as temperature and rainfall. Daily water evaporation rate time series data was differenced to make the data series stationary and Dickey-Fuller test was used to test the stationarity of the data series. The Autoregressive Conditional Heteroskasticity (ARCH) and Generalized Au toregressive Conditional Heteroskasticity (GARCH) model was performed on the water evaporation time series data from the selected dams. Vec tor Autoregression (VAR) was used to determine the relationship between the variables evaporation, rainfall and temperature. Identification of time series models was done using the autoregressive integrated moving average (ARIMA). The best ARIMA models were selected based on the autocor relation function (ACF) and partial autocorrelation function (PACF), and the smallest value of Bayseian Information (BIC). The best models selected for each dam are: Mokolo dam, ARIMA (1, 1, 2) model; Ga-Rantho dam, ARIMA (1, 1, 2) model; Leeukraal DeHoop dam, ARIMA (1, 1, 1) model and Luphephe dam, ARIMA (2, 1, 3) model. The correlation coefficient, coefficient of determinant (R2 ) and root mean square (RMSE) were used to determine the performance of the model. The water evaporation time series data from the selected dams was forecasted using the best selected ARIMA models from the selected dams and then predicted for the next 3 years, where the results showed a positive constant water evaporation rate.

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