Modeling mountain pine beetle infestation with an agent-based approach at two spatial scales
Environmental Modelling & Software
Allocating surveillance effort in the management of invasive species: A spatially-explicit model
Environmental Modelling & Software
Introductory Time Series with R
Introductory Time Series with R
Impact of social neighborhood on diffusion of innovation S-curve
Decision Support Systems
Environmental Modelling & Software
Modelling of spatial dynamics and biodiversity conservation on Lure mountain (France)
Environmental Modelling & Software
Position Paper: Modelling with stakeholders
Environmental Modelling & Software
Empirical characterisation of agent behaviours in socio-ecological systems
Environmental Modelling & Software
An agent-based simulation model of human-environment interactions in agricultural systems
Environmental Modelling & Software
Environmental Modelling & Software
Gryphon: a hybrid agent-based modeling and simulation platform for infectious diseases
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
Spatial agent-based models for socio-ecological systems: Challenges and prospects
Environmental Modelling & Software
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The study of how people acquire and diffuse information among heterogeneous populations has a rich history in the social sciences. However, few approaches have been developed to better understand how information diffusion patterns and processes affect resource management in complex socio-ecological systems. This is a timely issue for crop protection diffusion programs, which have a larger place than ever on the international policy agenda due to the growing number of challenges related to controlling agricultural pests. To assess the impact of heterogeneous farmer behaviors (receptivity toward IPM practices) and types of information diffusion (either active or passive) on the success of integrated pest management (IPM) programs, we developed a socio-ecological model coupling a pest model (population growth and dispersion) with a farmer behavioral model (pest control and diffusion of pest management practices). The main objective of the model was to provide insights to explore effective IPM information diffusion strategies at the farmer community level. Our simulations revealed 1) that passive IPM information diffusion among agents seemed to be more effective to control pests over the community of agents than active diffusion and 2) that increasing levels of agent heterogeneity would significantly slow down pest control dynamics at the community level, but to a lower extent in the case of passive IPM information diffusion. Our findings therefore suggest that IPM diffusion programs should focus their efforts in developing methods to create purposefully the conditions for social learning as a deliberate pest control mechanism, while taking into account potential limitations related to the commonly reported farmer heterogeneity. Our study further stresses the need to develop a comprehensive and empirically based framework for linking the social and ecological disciplines across space and time in agricultural system management. While we specifically focus on pest infestation levels and IPM information diffusion strategies in this study, our approach to understand information diffusion within heterogeneous human populations in interaction with environmental features would be applicable to a much wider range of both social and resource management issues.