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Rural livelihoods in most developing countries are threatened by climate-related risks such as drought, flood, heat waves, storms, and so on. Although farmers have adopted several adaptation strategies, they have proven less effective than hoped. Hence, index-based livestock insurance, an innovation that significantly assists farmers to acclimatise to climate-related risks, has been proposed; and its adaptability has attracted a notable increase in other African countries. However, the success of its adoption is dependent on the inclination of the farmers to pay for the service. Accordingly, this study investigates their willingness to pay for index-based livestock insurance and its determinants, and the factors influencing the total livestock units to be insured in the North West province of South Africa. Cross-sectional data were obtained from 277 cattle farmers, drawn randomly from the study area. The contingent valuation method was applied to determine the farmers’ willingness to pay; and only 10.8% were willing to pay. Simultaneously, the Heckit sample selection model was used to analyse the data to identify the factors responsible for farmers’ willingness to pay and total livestock units to insure. The findings revealed that farmer’s experience, age, education, marital status, awareness of insurance and household dependents were statistically significant, and influenced the maximum price R600 ($42, max willingness to pay, WTP) of those who accepted index-based livestock insurance. However, by implication, the study concluded that to adopt index-based livestock insurance in the study area among the livestock farmers, there should be policies to cater for the aforementioned factors.

Purpose It is globally accepted that climate change is presently the greatest threat to the sustainability of human livelihood and biodiversity. Most farmers in the study area are highly aware of climate change and its consequences on the farming system; however, mitigation strategies are clearly lacking. Among the mitigation, mechanism to reduce the threat is achieved by increasing the amount of carbon sinks and reducing greenhouse gas emission through the adoption of agroforestry practices. The purpose of this study is to determine if awareness on climate change leads to the adoption of agroforestry practices, and to examine the determinants. Design/methodology/approach A total number of 117 questionnaires were administered to the farmers in the district using stratified random sampling technique. Data were captured and analysed using STATA and XLSTAT software. Descriptive statistics and Heckprobit sample selection model were used to determine the objectives of the study. Findings The result established that climate change awareness does not lead to the adoption of agroforestry in the study area in which information source and member’s association were statistically significant at (p < 0.1) and (p < 0.05), respectively, and determine the adoption of agroforestry practices, while farming experience (p < 0.1), age (p < 0.05), extension visit (p < 0.05) and education (p < 0.1), were the determining factors that influence the awareness of climate change in the study area. Practical implications Regular number of extensions visit, information and training on agroforestry should be provided to the farmers in the study area. Social implications Farmers’ association should be strengthened among the rural farmers. Originality/value The causal effect or relationship of climate change awareness on mitigation through the practice of agroforestry in South Africa, especially in the study area, has not been measured. This research set a pace in the area of climate change awareness leading to mitigation strategies through the use of agroforestry practices as an option to be used in the rural farming area of South Africa.

Agricultural information plays a vital role in adopting agricultural technology. The study explored if information acquisition is related to the adoption of sustainable land management practices (SLMP) and jointly decided in Mpumalanga Province of South Africa. Primary data were collected through face-to-face interviews, using a proportionate random sampling technique to get 250 smallholder farmers to participate in the survey. A seemingly unrelated bivariate probit (SUBP) model and a recursive bivariate probit (RBP) model were adopted to examine the objective. The statistical estimation of the SUBP showed that there is a relationship, an empirical association between information acquisition and SLMP; while RBP estimation showed that information acquisition was exogenous in the adoption model; thus, the decision to acquire information and adopt SLMP was not jointly decided. Therefore, the study presents the determinants of information acquisition alongside with the adoption of SLPM. The result from the SUBP model, indicated that the years spent in school; agricultural extension service; the number of extension visits and the years of farming, influenced both information acquisition and the adoption of SLMP. The cost attached positively influenced the adoption of SLMP; while gender, marital status and age only influenced the information acquisition.