Nadine Andrieu

Relevancy and role of whole-farm models in supporting smallholder farmers in planning their agricultural season

The way a model is designed to assist farmers in their decision-making may influence how it is understood and perceived by farmers and shape interactions between farmers and model users (researcher, advisor). This study compared the strengths and weaknesses of three types of whole farm models used by researchers to assist 18 crop-livestock farmers in Burkina Faso in planning the next agricultural season. Due to its simplicity, the static simulation tool of annual farm stocks and flows led to superior changes in the farmers knowledge and practices. The rule-based dynamic simulation tool helped the researchers grasp farmers decision-making processes but was difficult for farmers to understand due to the discrepancy between its multi-annual time step and the farmers short-term planning horizon. The optimisation tool stimulated more strategic discussions regarding paths to improve farm income despite a design that was distant from the farmers reality. Three types of models used in a farmers decision support process are assessed.The static stock-flow simulation tool facilitates farmer learning on farm operations.The rule-based dynamic tool helps researchers grasp farmer decision-making processes.The optimisation tool stimulates discussion on paths leading to improved farm income.

Climate-Smart Farms? Case Studies in Burkina Faso and Colombia

The climate-smart agriculture concept aims to encourage reflection on the transition to sustainable agricultural systems adapted to climate change. This chapter is based on participatory research studies carried out in Colombia and Burkina Faso to investigate, with farmers, the relevance of new (agroclimatic information) or long promoted (compost) solutions that could be considered climate-smart. These studies were based on an analysis of farmers’ strategies to cope with climate change and variability, while also relying on modelling in the case of Burkina Faso. We highlight that these solutions should be dovetailed with existing strategies. The range of adaptation mechanisms used by farmers in Colombia influenced their agroclimatic information needs. In Burkina Faso, these adaptation mechanisms led to specific effects of compost on climate-smart agriculture assessment criteria. We discuss methodological lessons learned for the co-design of farms adapted to climate change.

Coconception d’innovations agropastorales assistée par un modèle à l’échelle de l’exploitation. Cas de l’embouche bovine

In agropastoral areas of West Africa, some farmers aim to intensify their farming systems. Action research in partnership (ARP) methods may support these changes through the use of modeling tools. The objective of this article was to analyze the relevance of the use of a simulation model at farm scale within an ARP framework to codesign agropastoral innovations. The study was conducted in Koumbia and Kourouma villages located in the west of Burkina Faso. The article analyzes results obtained by seven farmers who aimed at developing cattle fattening. Simulations of the project were carried out and compared to a baseline scenario corresponding to the practices implemented by farmers the year before the ARP. At the same time, the technical staff of the project provided the farmers with financial support to help them improve fattening cattle feed at full scale by introducing fodder crops and improving storage fodder capacity. Interviews and follow-ups were carried out to investigate farmers’ perception of the relevance of the model and to analyze their adoption of the proposed techniques. The farmers the most interested in the use of the model were those who lacked experience in cattle fattening. The model helped them assess the expected effects of this type of activity on the farm income, crop balance, and mineral crop balance. Follow-ups performed after the experimental phase showed that farmers carried on the activities simulated by the model and tested in the field. The study highlights the benefits from associating modeling with on-field experiments in order to facilitate the adoption of technical innovations by stakeholders.