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Farmers are aware of challenges brought by climate change yet struggle with adaptation measures due to a lack of resources such as early warning systems, ecosystem restoration, climate-resilient infrastructure, and water supply. This study, undertaken to assess smallholder crop farmers' awareness of, and adaptation to, the impacts of climate change, was conducted in the three local municipalities of Mopani district in the Limpopo Province, South Africa: Giyani, Letaba and Maruleng. The proportionate sampling technique was used to obtain the study sample size of 291 farmers. A Statistical Package for Social Sciences (SPSS) version 28 was used to analyze data, along with descriptive statistics and a binary logistic regression model. The results indicated that 100% of smallholder crop farmers were aware of climate change but struggled to implement adaptation measures. The binary logistic regression results revealed that the variables gender, farm size and change of weather had a significant influence on farmers' adaptation measures. Ninety per cent of smallholder crop farmers were aware of, and implemented, climate change adaptation measures. The study recommends a heightened focus on improving the level of farmers' efforts to adapt, to mitigate the effects of climate change in the study area. [ABSTRACT FROM AUTHOR]

In recent decades, southern Africa has experienced a shift towards hotter and drier climate conditions, affecting vital sectors like agriculture, health, water, and energy. Scientific research has shown that the combination of high temperatures and unreliable rainfall can have detrimental effects on agricultural production. Thus, this study focused on assessing climate variability, with implications on rangelands in the Limpopo Province of South Africa over 38 years. Historical climate data from 15 stations, including rainfall and minimum and maximum temperatures from 1980 to 2018, were analysed. To achieve the main objective, various statistics including mean, standard deviation, and coefficient of variation (CV) were computed for all variables across four seasons. The results highlighted significant variability in rainfall, with Musina (71.2%) and Tshiombo (88.3%) stations displaying the highest variability during the September-to-April season. Both minimum and maximum temperatures displayed low variability. The Mann–Kendall test revealed both increasing and decreasing trends in minimum temperatures and rainfall across different stations. Notably, there was a significant increase in maximum temperatures. This study provides valuable climate information for decision makers, aiding in the planning and management of agricultural activities, particularly in understanding how climate variations affect forage availability in rangelands. [ABSTRACT FROM AUTHOR]