The effect of farmers’ decisions on pest control with Bt crops : a billion dollar game of strategy

Milne, A; Bell, J; Hutchinson, W; van den bosch, F; Mitchell, P; Crowder, D; Parnell, SR; Whitmore, A

Abstract

A farmer’s decision on whether to control a pest is usually based on the perceived threat of the pest locally and the guidance of commercial advisors. Therefore farmers in a region are often influenced by similar circumstances, and this can create a coordinated response for pest control that is effective at a landscape scale. This coordinated response is not intentional, but is an emergent property of the system. We propose a framework for understanding the intrinsic feedback mechanisms between the actions of humans and the dynamics of pest populations, and demonstrate this framework using the European corn borer, a serious pest in maize crops. We link a model of the European corn borer and a parasite in a landscape with a model that simulates the decisions of individual farmers on what type of maize to grow. Farmers chose whether to grow Bt-maize, which is toxic to the corn borer, or conventional maize for which the seed is cheaper. The problem is akin to the snow-drift problem in game theory; that is to say, if enough farmers choose to grow Bt maize then because the pest is suppressed an individual may benefit from growing conventional maize. We show that the communication network between farmers’ and their perceptions of profit and loss affects landscape scale patterns in pest dynamics. We found that although adoption of Bt maize often brings increased financial returns, these rewards oscillate in response to the prevalence of pests.

Citation

Milne, A., Bell, J., Hutchinson, W., van den bosch, F., Mitchell, P., Crowder, D., …Whitmore, A. (2015). The effect of farmers’ decisions on pest control with Bt crops : a billion dollar game of strategy. PLoS Computational Biology, 11(12), e1004483. https://doi.org/10.1371/journal.pcbi.1004483

• Journal Article Type: Article
• Acceptance Date: Jul 27, 2015
• Publication Date: Dec 31, 2015
• Deposit Date: Nov 25, 2015
• Publicly Available Date: Apr 5, 2016
• Journal: Plos Computational Biology
• Print ISSN: 1553-734X
• Electronic ISSN: 1553-7358
• Publisher: Public Library of Science
• Volume: 11
• Issue: 12
• Pages: e1004483
• DOI: https://doi.org/10.1371/journal.pcbi.1004483
• Publisher URL: http://dx.doi.org/10.1371/journal.pcbi.1004483
• Related Public URLs: http://journals.plos.org/ploscompbiol/
• Additional Information: Funders : Biotechnology and Biosciences Sciences Research Council (BBSRC);USDA; Grant Number: S5198