The use of crop modeling as a decision tool by farmers and other decision-makers in the agricultural sector to improve production efficiency has been on the increase. In this study, artificial neural network (ANN) models were used for predicting maize in the major maize producing provinces of South Africa. The maize production prediction and projection analysis were carried out using the following climate variables: precipitation (PRE), maximum temperature (TMX), minimum temperature (TMN), potential evapotranspiration (PET), soil moisture (SM) and land cultivated (Land) for maize. The analyzed datasets spanned from 1990 to 2017 and were divided into two segments with 80% used for model training and the remaining 20% for testing. The results indicated that PET, PRE, TMN, TMX, Land, and SM with two hidden neurons of vector (5,8) were the best combination to predict maize production in the Free State province, whereas the TMN, TMX, PET, PRE, SM and Land with vector (7,8) were the best combination for predicting maize in KwaZulu-Natal province. In addition, the TMN, SM and Land and TMN, TMX, SM and Land with vector (3,4) were the best combination for maize predicting in the North West and Mpumalanga provinces, respectively. The comparison between the actual and predicted maize production using the testing data indicated performance accuracy adjusted R2 of 0.75 for Free State, 0.67 for North West, 0.86 for Mpumalanga and 0.82 for KwaZulu-Natal. Furthermore, a decline in the projected maize production was observed across all the selected provinces (except the Free State province) from 2018 to 2019. Thus, the developed model can help to enhance the decision making process of the farmers and policymakers.

Sub-Saharan Africa hosts the highest number of urban slum households in the world with an estimated 60 to 70% of urban residents living in slums. Kenya belongs to this region and has large informal settlements with dire socio-economic conditions. This study on the quality of life, in a typical East African slum, is based on fieldwork carried out in Mathare, Nairobi. The research revealed that Mathare residents prioritise sanitation, waste management and access to water, electricity, education and healthcare as the most essential services for adding quality to their lives. However, one of the main conclusions of this research is that although improved service delivery is necessary, it may not be sufficient in satisfying the quality of life requiremen ts of Mathare residents. Other aspects of economics, such as regular employment as well as socio-cultural issues, like freedom from fear a nd access to communal security, are equally important and policy objectives should pay holistic attention to both the objective living conditions and the subjective life satisfaction indicators of slum dwellers.

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This study analysed the variability of the agro-climatic parameters that impact maize production across different seasons in South Africa. To achieve this, four agro-climatic variables (precipitation, potential evapotranspiration, minimum and maximum temperatures) were considered for the period spanning 1986 -2015, covering the North West, Free State, Mpumalanga and KwaZulu-Natal (KZN) provinces. Results illustrate that there is a negative trend in precipitation for North West and Free State provinces and positive trend in maximum temperature for all the provinces over the study period. Further more, the result showed that among other agro-climatic parameters, minimum temperature had the most influence on maize production in North West, potential evapotranspiration (combination of the agro-climatic parameters), minimum and maximum temperature influenced maize production in KwaZulu-Natal while maximum temperature influenced maize production in Mpumalanga and Free State. In general, the agro-climatic parameters were found to contribute 7.79 %, 21.85 %, 32.52 % and 44.39 % to variation in maize production during the study period in North West, Free State, Mpumalanga and KwaZulu-Natal respectively. The variation in maize production amongst the provinces under investigation could most likely attributed to the variation in the size of the cultivated land among other factors including soil type and land tenure system. There were also difference in yield per hectare between the provinces; KwaZulu-Natal and Mpumalanga being located in the humid subtropical areas of South Africa had the highest yield per hectare 5.61 tons and 4.99 tons respectively while Free State and North West which are in the semi-arid region had the lowest yield per hectare 3.86 tons and 3.03 tons respectively.Understanding the nature and interaction of the dominant agro-climatic parameters discussed in the present study as well as their impact on maize production will help farmers and agricultural policy makers to understand how climate change exerts its influence on maize production within the study area so as to better adapt to the major climate element that either increases or decreases maize production in their respective provinces.

The study focuses on artisanal fishing in Beira, located within the most important fishery area of Mozambique -the Sofala Bank in central Mozambique. The main aim is to establish the degree of compliance with artisanal fishing regulations by artisanal fishermen in light of an increasing concern for the impact of fishing on ecosystems and livelihoods. Qualitative research data was gathered through semi-structured interviews with fishermen, officials from the Department of Fisheries and major stakeholders from the Institute for the Development of Small Scale Fisheries (IDSSF), the National Institute for Fishery Research (NIFR) and the Community Fishing Centres (CFCs). Though a review of the regulations and policies for the management of artisanal fishing in Mozambique indicate that they are well formulated and relevant, there is little to no compliance by the practitioners of artisanal fishing. The data revealed that artisanal fishermen in Beira use types of fishing gear which catches immature and juvenile fish and poses a threat to the health of the marine ecosystems. The most dangerous of these fishing gears are the mosquito net traps (known as "chicocota") and the beach seine. It is clear that the application and enforcement of the relevant regulations under the right circumstances would lead to better management of the fisheries environment and ensure the sustainability of artisanal fishing.