Coupled Information Diffusion–Pest Dynamics Models Predict Delayed Benefits of Farmer Cooperation in Pest Management Programs

Abstract

Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' “diffusion of innovation theory”. In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.

Factors determining pesticide use practices by farmers in the Sultanate of Oman

“…The recognition that pest management is most effective when implemented collectively at the regional level precedes IPM itself, and gave rise to the development of area-wide pest management (36) and metapopulation theory (37). Indeed, some pest management decisions are subject to a collective action dilemma (38), whereby the payoffs from adopting a technology depend on whether others adopt it too (39,40). For example, smallholder farmers in Peru are encouraged to plow their previous-season potato fields to kill overwintering weevils before they colonize newly planted fields, but this practice is ineffective if their neighbors do not also plow their fields (41).…”

Impacts of climate change on plant diseases—opinions and trends

“…the identification of novel Phytophthora species: Jung et al 2011;Vettraino et al 2011) to network epidemiology (Jeger et al 2007;Keller et al 2011) and digital pest diagnostics and severity estimation (Bock et al 2010;Norton and Taylor 2010). The involvement of the many stakeholders in plant health (Furstenau et al 2007;Macleod et al 2010) deserves repetition in more than one section of this review, as it can be beneficial not just to adapt the regulatory framework, but also to improve dissemination of plant health knowledge (Jacobi et al 2011;Rebaudo and Dangles 2011) and to devise effective response strategies to new invasive pathogens (Crall et al 2010).…”

Adaptive management in crop pest control in the face of climate variability: an agent-based modeling approach

“…As previously shown by Rebaudo and Dangles (2011), the specific management practices used by Ecuadorian farmers influences how well T. solanivora is controlled. For example, high potato ridging more effectively controls potato moth larvae than does low ridging.…”

“…Equation 2 describes how effectively farmers control T. solanivora (see Rebaudo and Dangles 2011). Pest control is specific to individual farms.…”