title: The Effect of Farmers' Decisions on Pest Control with Bt Crops: A Billion Dollar Game of Strategy.
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.
authors.affiliation: Computational and Systems Biology, Rothamsted Research, Harpenden, United Kingdom.
authors.forename: Alice E
authors.initials: AE
authors.lastname: Milne
authors.affiliation: Rothamsted Insect Survey, Rothamsted Research, Harpenden, United Kingdom.
authors.forename: James R
authors.initials: JR
authors.lastname: Bell
authors.affiliation: Department of Entomology, University of Minnesota, St. Paul, Minnesota, United States of America.
authors.forename: William D
authors.initials: WD
authors.lastname: Hutchison
authors.affiliation: Computational and Systems Biology, Rothamsted Research, Harpenden, United Kingdom.
authors.forename: Frank
authors.initials: F
authors.lastname: van den Bosch
authors.affiliation: Department of Agricultural and Applied Economics, University of Wisconsin, Madison, Wisconsin, United States of America.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Mitchell
authors.affiliation: Department of Entomology, Washington State University, Pullman, Washington, United States of America.
authors.forename: David
authors.initials: D
authors.lastname: Crowder
authors.affiliation: Computational and Systems Biology, Rothamsted Research, Harpenden, United Kingdom.|School of Environment & Life Sciences, University of Salford, Manchester, United Kingdom.
authors.forename: Stephen
authors.initials: S
authors.lastname: Parnell
authors.affiliation: Sustainable Soils and Grassland Systems, Rothamsted Research, Harpenden, United Kingdom.
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Whitmore
mesh_terms: D000818:Animals; D019295:Computational Biology; D018556:Crops, Agricultural / Q000191:economics / Q000382:microbiology / Q000469:parasitology; D003657:Decision Making; D000067565:Farmers / Q000706:statistics & numerical data*; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D007915:Lepidoptera / Q000382:microbiology / Q000472:pathogenicity; D008954:Models, Biological; D016818:Nosema; D010572:Pest Control, Biological / Q000191:economics / Q000706:statistics & numerical data; D030821:Plants, Genetically Modified / Q000382:microbiology / Q000469:parasitology; D014481:United States; D003313:Zea mays / Q000382:microbiology / Q000469:parasitology