Spatially Explicit Dynamically Optimal Provision of Ecosystem Services: An Application to Biological Control of Soybean Aphid
Grass conservation plantings (CP) are regularly installed as filter strips to supply water quality benefits and provide wildlife habitat, but these CPs also provide other agroecosystem services, including pest control which may reduce the need for insecticide spraying. This research extends previous work (Zhang and Swinton, 2009), by developing a multi-year space-time optimization problem as a dynamic bioeconomic model. The suggested model is applied to the problem of controlling Soybean Aphids in Newton County, Indiana. The previous literature is expanded in four major ways: the objective function is formulated as the social planner’s problem to reflect externalities, stochastic arrival of Soybean Aphids and appearance of natural enemies over space, spatially-explicit composition of the natural habitat network, and spatial heterogeneity of land cover properties. The empirical results show that natural enemies can provide suppression of Soybean Aphid and this reduces spraying frequencies. Installation of CPs increases the flow of ecosystems services across the landscape by providing habitat for beneficial natural enemies that prey upon the soybean aphid and other crop pests.
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- Pimentel, David & Zuniga, Rodolfo & Morrison, Doug, 2005. "Update on the environmental and economic costs associated with alien-invasive species in the United States," Ecological Economics, Elsevier, vol. 52(3), pages 273-288, February.
- Song, Feng & Swinton, Scott M. & DiFonzo, Christina & O'Neal, Matthew & Ragsdale, David W., 2006. "Profitability Analysis Of Soybean Aphid Control Treatments In Three North-Central States," Staff Papers 11489, Michigan State University, Department of Agricultural, Food, and Resource Economics.
- Zhang, Wei & van der Werf, Wopke & Swinton, Scott M., 2010. "Spatially optimal habitat management for enhancing natural control of an invasive agricultural pest: Soybean aphid," Resource and Energy Economics, Elsevier, vol. 32(4), pages 551-565, November.
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