Spatially Optimal Habitat Management For Natural Pest Control Services
Creators: name: Zhang, Wei
name: Van Derr Werf, Wopke
name: Swinton, Scott M.
name: Zhang, Wei
name: Van Derr Werf, Wopke
name: Swinton, Scott M.
Publisher: name: Unknown
Year: 2007
Subjects: subject: Environmental Economics and Policy
subject: ecosystem services
subject: biological control
subject: natural enemies
subject: habitat management
subject: soybean aphid
subject: spatial optimization
subject: land use

description: The control of crop pests by their natural enemies represents an important ecosystem service that maintains the stability of agricultural systems and has the potential to mitigate pest control costs. Recently, there has been growing interest in enhancing natural control services via habitat management that provides resources for adult natural enemies, such as food and shelter. Management of natural enemy populations has received little attention in the economic literature on pest control. Most such prior studies have explored optimal chemical-based pest management. One recent paper developed a threshold-based pesticide decision rule to account for the presence of natural enemies. However, no prior studies have investigated economically optimal spatial habitat configuration for natural enemies of crop pests. Non-crop areas (NCA) such as hedgerows and woodlots in agricultural landscapes are important sources of alternative prey for pest predators and hosts for parasitoids, as well as shelter from adverse conditions (including hibernation). Empirical evidence from recent ecological research shows that pest suppression is positively correlated with the proportion of NCA in the landscape. While most prior research has taken the landscape configuration as given, Bianchi and van der Werf (2003) explore the effect of the shape, area, and fragmentation of NCA elements on the control of aphids by C. septempunctata using a spatially explicit simulation model. This study explores spatial manipulation of NCA in a simulated landscape to optimize net returns from natural biological pest control. For migratory natural enemies, farm property rights can influence optimal spatial habitat distribution in a landscape due to the effects of economic externalities and common pool resources on individual incentives to set aside NCA for habitat. It is costly not only for the supply farmer to exclude others from access to the enhanced pest control services, but also to protect the natural enemies from non-target effects of neighbors´ pesticides. The benefits of pest predation services may also be rivalrous in that neighboring farms may compete for them with the provider farm. These forms of market failure imply that the first farmer, acting alone, would lack the incentive to set aside the collectively optimal amount of habitat for both the provider farmer and the neighbor. Exploratory research into collective action has shown that incentives can be designed to induce coordinated habitat conservation by individual land managers across a landscape (Parkhurst et al., 2002). However, no prior studies have explored the economic incentive effects in the context of ecological parameters to develop policy recommendations for practical problem. This study attempts to do that for the natural control of aphid pests by migratory insect natural enemies. This study aims to achieve four objectives. First, we propose a spatially explicit conceptual model for agricultural land use that maximizes the aggregate net benefit of habitat management over the size, shape, and spatial location of NCA. Second, we develop an empirical simulation model for the spatial distribution of control services. Third, we conduct optimization analysis for several management scenarios to account for different scales of management (farm level v.s. landscape scale) and the effect of chemical pesticides as a pest control alternative. Finally, we derive policy implications for appropriate incentive schemes to induce coordinated action. The spatial economic optimization model maximizes aggregate net benefit of habitat management. The model simulates the migration of natural enemies, the predation of crop pests, and the effect on crop yield and associated income. We model natural control services as an exponential function of NCA and spatially distribute the control services according to a selected distribution function. To account for the uncertainty in the probability distribution of insect dispersal, three alternative distribution kernels commonly used in ecological modeling are considered. While the model does not focus on any specific natural enemy species, we parameterize using i) coefficients inspired by the soybean aphid-multicolored Asian lady beetle relationship estimated from Michigan field trial data, and ii) data from secondary sources. Simulated economic results are driven by 1) the value of crop yield protected (a function of pest density and natural enemy predation), 2) the distance of the crop area from natural enemy habitat (a function of the size and shape of NCA), 3) the opportunity cost of foregone crop income from NCA set aside, 4) the effects of NCA fragmentation and configuration on farming costs (e.g., linear vs. island NCA shapes), and 5) the number and configuration of private farms in the simulated landscape. This detailed and closely coupled bioeconomic model will be applied to illustrate optimal provision of managed ecosystem services under alternative land ownership regimes. It aims to provide insights for incentive design to bring private choice in line with socially desirable provision of pest predation services by natural enemies. Reference: Bianchi, F.J.J.A. and W. van der Werf, 2003. The Effect of the Area and Configuration of Hibernation Sites on the Control of Aphids by Coccinella septempunctata (Coleoptera: Coccinellidae) in Agricultural Landscapes: A Simulation Study. Environmental Entomology, 32(6), 1290-1304. Parkhurst, G. M., Shogren, J. F., Bastian, C., Kivi, P., Donner, J. and Smith, R. B. W., 2002. Agglomeration bonus: an incentive mechanism to reunite fragmented habitat for biodiversity conservation. Ecological Economics, 41 (May, 2002):305-328.