This study investigated the perceived effects of climate change on crop production and household livelihoods of smallholder farmers in Mopani and Vhembe district, South Africa. Data was collected through a questionnaire administered to 150 smallholder farmers. The questionnaires were complemented by 8 focus group discussions and secondary data. Multinomial logit regression model was used to analyse the factors influencing smallholder farmers’ choice of climate change adaptation strategies. The study findings revealed that subsistence farmers perceived prolonged droughts (56.4%) as the main shock stressing crop production. Droughts often lead to low crop yield and high crop failure (73.3%). In response to the prevailing climatic conditions different gender adopted different strategies, 41% of female farmers adapted by changing planting dates, while male farmers employed crop variety and diversification (35%) and mixed cropping (15%). The smallholder farmers were vulnerable with limited adaptive capacity to withstand climate change due to compromised social, human, physical, natural and financial assets. The results showed that smallholder farmers tend to adapt better when they have access to extension officers (P<0.01). Therefore, it is important for the government to strengthen the relationship between smallholder farmers and extension officers for better climate change adaptation.

Climate change and variability have direct negative impacts on rural smallholder farmers. These impacts involve extreme climatic events such as excessive temperatures, prolonged droughts and floods which affect people’s livelihoods. This study was conducted in Nkomazi Local Municipality, Mpumalanga, South Africa. The main objective of the study was to investigate indigenous weather and climate indicators used by smallholder farmers and the role of indigenous knowledge in their farming systems. The research used qualitative methods, including focus group discussions and key informant interviews. The findings indicated that farmers observed animal behaviour, plants, atmospheric indicators and human ailments to predict weather.

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This study aimed to help smallholder farmers to use their indigenous knowledge in combination with modern climate indicators when making farming decisions in Nkomazi Local Municipality. The Poynton model was used to predict the distribution of the plant and animal indicators if the temperature continues to rise by at 50C. Twelve villages were sampled with 100 participants applying both qualitative and quantitative research methods. ArcMap 10.7.1 was used to map the distribution of indigenous climate indicators in these villages, and SPSS 25.0 was used to analyse the quantitative data. Qualitative data was analysed through thematic analysis. Mostly used indicators smallholder farmers relied on for weather predictions included animals (31%) followed by plants (26%). The Poynton model predicted negative results with a 50C temperature increase, meaning that if the hot temperatures continue rising, the farmers' indigenous indicators will decline or disappear, making it difficult for the rural smallholder farmers to make informed farm-level decisions. These are the negative effects climate change has on rural smallholder farmers. Therefore, the study suggests an integration of Indigenous Knowledge Systems (IKS) and modern science to adapt to climate change, have access to updated agricultural information and ability to make informed farm-level decisions.