Assessing adaptive capacity in smallholder farming systems in Karonga, Malawi.

Climate variability is expected to have a negative impact on agricultural production, particularly in sub-Saharan Africa, including Malawi, where the agricultural sector is a crucial part of the economy. This study focusses on increasing our understanding on the ability of smallholder farmers in Karonga, Malawi, to adapt to climate variability. To achieve this, an integrated framework was used to assess the factors that influence the adaptive capacity of smallholder farming systems in Karonga. The integrated indicator-based framework was used to assess financial, social, human assets, knowledge and information, institutions and entitlements, flexible and forward-looking decision-making, gender and power dynamics, natural assets, physical assets and the frequency of floods. Data were collected through face-to-face interviews, focus group discussions and observations. A total of 38 indicators from literature and observations in the study area were entered and analysed in SPSS and Excel using principal component analysis. The survey results indicate that the aggregate adaptive capacity of respondents is low. Component indicators, such as ownership of livestock, support from the community, livelihood diversification and gender of the decision maker, as well as access to a mobile phone and inorganic fertiliser, and share of more productive land, increased the adaptive capacity of smallholder farmers. On the other hand, component indicators such as less productive land, deforestation, capital exclusion from food for work, age of household head, financial assets and gross annual income reduced the adaptive capacity of smallholder farmers to climate change.

Contribution: The article presents an integrated framework that considers both biophysical and socio-economic factors for assessing adaptive capacity. This framework offers a better understanding of the adaptive capacity of farming systems at the smallholder farmer level. The study's findings provide insights into the dynamic nature of adaptive capacity and identify factors that either enable or constrain adaptive capacity at various levels.