Smallholder farms’ populations are characterized by their heterogeneity giving the diversity of farms’ livelihood settings. Integrated farming system modelling therefore requires a preliminary clear identification of the farm types in a location and for a given population. This study aims to formulate empirically agricultural livelihood system (ALS) typology for the purpose of integrated modeling of smallholder systems in West African drylands, taking Pontieba village in South-western Burkina Faso as a demonstration case. We used a multivariate analysis combining PCA to K-CA, and expert knowledge to identify agricultural livelihood system types in Pontieba. Based on the Sustainable Livelihood Framework, a cross-sectional dataset of 108 households was collected through household interviews. The results revealed the main variables discriminating agricultural livelihoods in Pontieba, which includes variables of human asset (labour, labour age, education and dependency), natural asset (land holdings and livestock), financial asset and livestock), financial (annual gross income, and non-farm income) assets, and production orientation (cotton and marketable food crops production). Three agricultural livelihood system types were identified: (i) Poor-income, landless and subsistence-based farms; (ii) Medium-income, high-dependency, cotton-and livestock-oriented farms, and (iii) better-off income, land-and labour-rich, cotton-and livestock-oriented farms. The study recommends the use of this typology for policy intervention and further systems analysis and modelling. Key words: Agricultural livelihood typology, smallholder farms, sustainable livelihoods, semi-arid areas, integrated systems modelling, Burkina Faso.
Read full abstract