Mapping farmer perceptions, Conservation Agriculture practices and on-farm measurements: The role of systems thinking in the process of adoption. (June 2021)

• Record Type: Journal Article
• Authors: Lalani, Baqir; Aminpour, Payam; Gray, Steven; Williams, Meredith; Büchi, Lucie; Haggar, Jeremy; Grabowski, Philip; Dambiro, José
• Is Part Of: Agricultural systems. Volume 191(2021)
• Publication Date: 2021-06
• Subjects: Conservation Agriculture -- Decision-making -- Mental models -- Cropping systems; Agricultural systems -- Periodicals; Agriculture -- Environmental aspects -- Periodicals; 338.16
• DOI: 10.1016/j.agsy.2021.103171
• Languages: English
• ISSNs: 0308-521X

Abstract

Abstract: CONTEXT: Conservation Agriculture (CA) usage, particularly in Southern Africa, has remained low with lower yield, higher weed pressure and lower soil quality cited as reasons for 'disadoption'. OBJECTIVE: Using a detailed case study of 50 farmers in two villages in Cabo Delgado (Northern Mozambique), this study seeks to test the hypothesis that farmers' perceptions of CA are associated with distinctly different 'mental models' and if these "ways of thinking" overlap with farmers' identified/self-identified groupings (e.g. CA users, 'disadopters' and conventional tillage users). Secondly, we examine whether these different mental models (perceptions) are associated with actual differences in on-farm measurements. Finally, we explore the hypothesis that 'systems thinking' (i.e., understanding nonlinear causal relationships and internal feedback loops that drive a complex system) and CA usage are positively associated. METHODS: Fuzzy Cognitive Mapping (FCM) was used to elicit representations of farmers' mental models. To explore the association between farmers' mental models of CA/conventional practices and on-farm measurements we evaluated cowpea aboveground biomass, yield, weed cover, and soil quality parameters from the farmer's main plot. We drew on network analysis to measure structural metrics of cognitive maps that provide important information about a person's mental model (perceptions) of causal interdependencies of farming dynamics. RESULTS AND CONCLUSIONS: We find evidence of two data-driven distinct clusters of farmers' mental models that are in relative alignment with farmers' identified/self-identified groupings. Cluster 1 mainly consists of conventional users and cluster 2 mainly consists of CA users/disadopters. While no significant differences in socio-demographic variables were observed, clusters of mental models were associated with key differences in on-farm measurements. Importantly, cluster 1, who tended to be conventional users, had lower yields, lower soil cover, significantly lower carbon stock and higher weed coverage than cluster 2. Soil quality indicators were higher in cluster 2 as were farmers' overall revenue per hectare. Moreover, cluster 2 had significantly higher degrees of 'systems thinking' (measured through complex network analysis of graphical mental models) than cluster 1 which had higher forms of linear thinking. We argue that higher forms of experiential learning and practice of CA relate to higher degrees of systems thinking and stronger positive perceptions of CA, even among the CA 'disadopters'. SIGNIFICANCE: Our findings highlight the importance of systems thinking abilities and inclusion of biophysical, socio-economic and mental modelling variables rather than simple binary measurements which may have led to erroneous conclusions on CA and thus has implications for how CA is understood and promoted in future. Graphical abstract: Unlabelled Image Highlights: Conservation Agriculture usage, particularly in Southern Africa, has remained low. This study tests whether farmers' perceptions are associated with distinctly different 'mental models', thinking and on farm measurements. Farmers mental models align with farmers' identified/self-identified groupings. Higher degree of 'systems thinking' and positive on-farm realities are associated with Conservation Agriculture usage. Systems thinking abilities need to be considered rather than simple binary measurements.