agriLOVE: agriculture, land-use and technical change in an evolutionary, agent-based model with M. Coronese, F. Lamperti and A. Roventini
Available here - Revision requested
This paper presents a novel agent-based model of land use and technological change in the agricultural sector under environmental boundaries, finite available resources and changing land productivity. In particular, we model a spatially explicit economy populated by boundedly-rational farmers competing and innovating to fulfill an exogenous demand for food, while coping with a changing environment shaped by their production choices. Given the strong technological and environmental uncertainty, farmers learn and adaptively employ heuristics which guide their decisions on engaging in innovation and imitation activities, hiring workers, acquiring new farms, deforesting virgin areas and abandoning unproductive lands. Such activities in turn impact on land productivity, food production, food prices and land use. We firstly show that the model can replicate key stylized facts of the agricultural sector. We then extensively explore its properties across several scenarios featuring different institutional and behavioral settings. Finally, we showcase the properties of model in different applications considering deforestation and land abandonment; soil degradation; and climate impacts.
Rain does not fall on one roof alone: the share of local knowledge in idir mediates risk perceptions on rainfall frequency and intensity in marginal farming systems with G. Ragaglini, C. Fadda, M.E. Pè, A. Nuvolari and A. Mantino
The perception on precipitation variability is key to food security of smallholder farmers in the current changing climate. In rainfed areas, households able to interpret correctly short-term precipitation deviations and extremes do retain a significant advantage in terms of resilience. Membership into informal associations (such as idir) foster the exchange of traditional and local knowledge. However, despite the communitarian nature of these rural societies, we know little about how the share of local knowledge influences risk perceptions on rainfall. In our study, we combine data from agronomic and socioeconomic surveys together with daily rainfall estimates to explore links between the households’ risk perceptions and the social dimension of local knowledge. We build a panel dataset, interviewing 280 smallholder households in the Ethiopian highlands in the spring of 2013 and 2019, while characterizing the frequency and intensity of rainfalls during the crop growing seasons. By analyzing varietal and soil management choices, we identify a novel indirect measure of farmer’s risk perception on rainfall abundance and scarcity. This measure shows high heterogeneity among neighboring households. Regressing the perception indices on rainfall parameters, we find that changes in volatility and maximum are rarely perceived by farmers. We further interact changes in the rainfall parameters with idir membership, to see whether the share of local knowledge mediates risk perceptions on rainfall frequency and intensity. Findings reveal that idir membership mediates the risk perception on rainfall parameters and that members comprehend better changes in rainfall patterns among crop growing seasons. Our findings suggest that the share of local knowledge in informal institutions like idir should be considered for risk reduction and programs of climate change mitigation.
Group-based and crowdsourced citizen science variety testing approaches for bean growers in Central America with J. Sellare, K. De Sousa, M. Dell'Acqua, K. Paredes, J. Robalino, J. C. Rosas and J. van Etten
Available upon request - Under review
Participatory approaches for crop variety testing incorporate traditional knowledge and consider site-specific sociocultural complexities. They have demonstrably increased on-farm agrobiodiversity and enhanced productivity, livelihoods and food-security for small-scale farmers and their households. However, traditional participatory approaches have drawbacks and are seldom streamlined or scaled. Crowdsourced citizen science addresses some of these challenges. In this study, we compare a crowdsourced citizen science approach — triadic comparisons of technologies (tricot-CCS) — with the benchmark state-of-the-art group-based participatory variety testing approach (GB-PVS). We focus on on-farm testing of bean common bean (Phaseolus vulgaris L.) in the Trifinio area in Central America. We compare the impact of these two approaches on bean growers, especially in terms of i) adoption, ii) yield, iii) on-farm diversification and iv) food security. We use data from 1,978 smallholder farmers from 140 communities, who were randomly assigned to either tricot-CCS, GB-PVS or control (no treatment) to perform variety testing and selection. Regression analyses revealed that farmers involved in GB-PVS and tricot-CCS had comparable levels of variety adoption and a comparably higher degree of on-farm varietal diversification with respect to control farmers. While tricot-CCS reduces the likelihood of participants dropping out of the program, GB-PVS is more effective in decreasing households’ food insecurity, which can be attributed to the improved agronomic management of the crops. These findings suggest that tricot-CCS provides more cost-effective, equitable and externally-valid intervention benefits, which can be combined with the group-based activities and knowledge exchange among technical staff and farmers that characterize GB-PVS to benefit the farmers.
Land-use transitions in an evolutionary agent-based model: alternative soil management regimes under environmental boundaries with M. Coronese, F. Lamperti and A. Roventini
Drivers of soil erosion in Mediterranean marginal areas: a mixed-method approach combining fuzzy cognitive mapping, agronomic modeling and interviews with De Leo S., Mancini Teixeira H. and A. Mantino
Women's empowerment in agriculture and trait preferences in Bangladesh with Tufan H.
Under utilized crops and food security: the case of breadfruit in Madagascar with Cerroni S. and M. Bozzola
Trait prioritization in plant breeding programs: a review on tools and approaches with Garner E., Gomez M., Miller C., Puerto S. and Tufan H.