Adaptive management in crop pest control in the face of climate variability: an agent-based modeling approach
François Rebaudo, UMR EGCE IRD-247 CNRS-UPSud-9191; Instituto de Ecología, Universidad Mayor de San Andres
Olivier Dangles, Institut de Recherche pour le Développement, Laboratoire Evolution, Génomes, Comportement et Ecologie (UMR IRD, CNRS, Université Paris Sud), Université Paris-Saclay, Campus CNRS, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette Cedex, France; Pontificia Universidad Católica del Ecuador, Facultad de Ciencias Exactas y Naturales, Av. 12 de Octubre y Roca, Quito, Ecuador
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Climate changes are occurring rapidly at both regional and global scales. Farmers are faced with the challenge of developing new agricultural practices to help them to cope with unpredictable changes in environmental, social, and economic conditions. Under these conditions, adaptive management requires a farmer to learn by monitoring provisional strategies and changing conditions, and then incrementally adjust management practices in light of new information. Exploring adaptive management will increase our understanding of the underlying processes that link farmer societies with their environment across space and time, while accounting for the impacts of an unpredictable climate. Here, we assessed the impacts of temperature and crop price, as surrogates for climate and economic changes, on farmers’ adaptive management in crop pest control using an agent-based modeling approach. Our model simulated an artificial society of farmers that relied on field data obtained in the Ecuadorian Andes. Farmers were represented as heterogeneous autonomous agents who interact with and influence each other, and who are capable of adapting to changing environmental conditions. The results of our simulation suggest that variable temperatures led to less effective pest control strategies than those used under stable temperatures. Moreover, farmers used information gained through their own past experience or through interactions with other farmers to initiate an adaptive management approach. At a broader scale, this study generates more than an increased understanding of adaptive management; it highlights how people depend on one another to manage common problems.
adaptive management; agent-based model; agro-ecosystems; farmers; pest
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