Political Ecology and Differential Vulnerabilities to Droughts among Livestock Farmers in South Africa: A Case Study of Mpakeni Community

Most of South Africa’s black rural population reside in the former homelands or Bantustans, commonly referred to as communal areas by the post-apartheid government (Clark and Luwaya 2017). Amongst a variety of livelihood activities that black rural households engage in, livestock production offers multiple-use value, although its contribution to local livelihood is sometimes underestimated (C. M. Shackleton et al. 2005). Some of the objectives that livestock production in black rural areas seeks to achieve include ‘bride price payment, ritual and ceremonial slaughter, meat, milk, occasional cash sales and savings, as well as providing draught power and manure as inputs to crop production’ (Cousins 2018: 373). Indeed, C. M. Shackleton et al. (2005) and Twine (2013) found livestock production to be an essential asset that enables black rural households to spread livelihood risks and build resilience. Given its wide range of benefits, it is unsurprising to note that about 1.11 million black households were involved in livestock production in either subsistence or market-oriented farming between 2009 and 2015 (Cousins 2018). The enormous contributions livestock production makes to rural livelihood in communal areas are perhaps why it is deemed a vehicle that can reduce the high poverty and inequality levels through the injection of effective policies (Hall and Cousins 2013)

LIMITATIONS TO SUSTAINABLE RESOURCE MANAGEMENT IN THE GLOBAL SOUTH: EVIDENCE FROM THE ACCOMMODATION INDUSTRY

Purpose – This paper explores the factors responsible for the low level of sustainability uptake in tourism accommodation establishments in the Global South using the Greater Cape Town Region of South Africa as a case study. Methodology – In-depth semi-structured interviews were conducted with managers of 30 accommodation establishments in the Greater Cape Town Region to obtain information on the barriers and/or challenges they encountered in implementing sustainable resource management (SRM). A content analysis methodology was used to analyse the data. Approach – Given that resource consumption and management are at the core of sustainability in the accommodation industry, SRM was the primary focus of analysis in the study. Findings – This study identified six key challenges undermining SRM implementation in this geographical location: financial and non-financial resource constraints; the service nature of the industry; the limiting policy and infrastructure environment; poor employee commitment/buy-in; and skill and knowledge inadequacies. These provide a holistic foundation for addressing the challenge of low sustainability uptake in the Global South context, and the recommendations are made in line with achieving this objective. Originality of the research – This paper contributes to the limited literature on challenges to sustainability uptake in the tourism accommodation industry in the Global South. Limitations: While a Global South perspective is adopted, the data used in this study were from a small, albeit popular, tourism destination in South Africa. Caution, therefore, has to be exercised when generalising the findings of the study. Keywords Resource Management, Accommodation Industry, Tourism, Challenges to Sustainability, Global South, South Afric

A Seasonal Autoregressive Integrated Moving Average SARIMA forecasting model to predict monthly malaria cases in KwaZuluNatal South Africa

Background. South Africa (SA) in general, and KwaZulu-Natal (KZN) Province in particular, have stepped up efforts to eliminate malaria. To strengthen malaria control in KZN, a relevant malaria forecasting model is important.Objectives. To develop a forecasting model to predict malaria cases in KZN using the Seasonal Autoregressive Integrated Moving Average (SARIMA) time series approach.Methods. The study was carried out retrospectively using a clinically confirmed monthly malaria case dataset that was split into two. The first dataset (January 2005 - December 2013) was used to construct a SARIMA model by adopting the Box-Jenkins approach, while the second dataset (January - December 2014) was used to validate the forecast generated from the best-fit model.Results. Three plausible models were identified, and the SARIMA (0,1,1)(0,1,1)12 model was selected as the best-fit model. This model was used to forecast malaria cases during 2014, and it was observed to fit closely with malaria cases reported in 2014.Conclusions. The SARIMA (0,1,1)(0,1,1)12 model could serve as a useful tool for modelling and forecasting monthly malaria cases in KZN. It could therefore play a key role in shaping malaria control and elimination efforts in the province.Â

A Seasonal Autoregressive Integrated Moving Average (SARIMA) forecasting model to predict monthly malaria cases in KwaZulu-Natal, South Africa

Background. South Africa (SA) in general, and KwaZulu-Natal (KZN) Province in particular, have stepped up efforts to eliminate malaria. To strengthen malaria control in KZN, a relevant malaria forecasting model is important.Objectives. To develop a forecasting model to predict malaria cases in KZN using the Seasonal Autoregressive Integrated Moving Average (SARIMA) time series approach.Methods. The study was carried out retrospectively using a clinically confirmed monthly malaria case dataset that was split into two. The first dataset (January 2005 - December 2013) was used to construct a SARIMA model by adopting the Box-Jenkins approach, while the second dataset (January - December 2014) was used to validate the forecast generated from the best-fit model.Results. Three plausible models were identified, and the SARIMA (0,1,1)(0,1,1)12 model was selected as the best-fit model. This model was used to forecast malaria cases during 2014, and it was observed to fit closely with malaria cases reported in 2014.Conclusions. The SARIMA (0,1,1)(0,1,1)12 model could serve as a useful tool for modelling and forecasting monthly malaria cases in KZN. It could therefore play a key role in shaping malaria control and elimination efforts in the province.

Subsistence farmers’ differential vulnerability to drought in Mpumalanga province, South Africa: Under the political ecology spotlight

This paper examines social differences and drought vulnerability among subsistence livestock farmers in Mpakeni, Mpumalanga province, South Africa. This paper asks, how do social differences between households and power relations shape vulnerability to drought? This is against the backdrop that parallel exposure to climatic risks does not translate to similar vulnerability among households residing in the same community. In-depth interviews were used to obtain primary data from purposively selected participants in Mpakeni. Some key findings reveal that being a non-local elite, a migrant settler and some female-headed households, especially those burdened by the additional tasks of caregiving, amplifies the challenges of securing forage when depleted in communal grazing fields. This is partly due to reduced time allocated to shepherding their livestock to the bank of a local river. Also, non-local elite and those who lacked social ties to the headman found it difficult to get compensated when their livestock were eaten by wild animal upon illegal entry to a game reserve rich in vegetation. This paper argues that vulnerability studies that focus independently on issues like gender, ethnicity and class may miss the dynamics that shape individuals’ vulnerability to drought, which could have severe consequences for implementing effective interventions