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  • Quantifying the effect of buffer zones, crop areas and spatial aggregation on the externalities of genetically modified crops at landscape level.

    Author(s) : Ceddia, M. G.Bartlett, M.Perrings, C.

    Author Affiliation : Department of Agricultural and Food Economics, University of Reading, Whiteknights, RG6 6AR, Reading, UK.

    Author Email : m.ceddia@reading.ac.uk

    Journal article : Agriculture, Ecosystems & Environment 2009 Vol.129 No.1/3 pp.65-72 ref.32

    Abstract : The development of genetically modified (GM) crops has led the European Union (EU) to put forward the concept of 'coexistence' to give farmers the freedom to plant both conventional and GM varieties. Should a premium for non-GM varieties emerge in the market, 'contamination' by GM pollen would generate a negative externality to conventional growers. It is therefore important to assess the effect of different 'policy variables' on the magnitude of the externality to identify suitable policies to manage coexistence. In this paper, taking GM herbicide tolerant oilseed rape as a model crop, we start from the model developed in Ceddia et al. [Ceddia, M.G., Bartlett, M., Perrings, C., 2007. LandscapelandscapeSubject Category: Miscellaneous
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    gene flowgene flowSubject Category: Natural Processes
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    , coexistence and threshold effect: the case of genetically modified herbicide tolerant oilseed rape (Brassica napus). Ecol. Modell. 205, pp. 169-180] use a Monte Carlo experiment to generate data and then estimate the effect of the number of GM and conventional fields, width of buffer areas and the degree of spatial aggregation (i.e. the 'policy variables') on the magnitude of the externality at the landscape level. To represent realistic conditions in agricultural production, we assume that detection of GM material in conventional produce might occur at the field level (no grain mixing occurs) or at the silos level (where grain mixing from different fields in the landscape occurs). In the former case, the magnitude of the externality will depend on the number of conventional fields with average transgenic presence above a certain threshold. In the latter case, the magnitude of the externality will depend on whether the average transgenic presence across all conventional fields exceeds the threshold. In order to quantify the effect of the relevant 'policy variables', we compute the marginal effects and the elasticities. Our results show that when relying on marginal effects to assess the impact of the different 'policy variables', spatial aggregation is far more important when transgenic material is detected at field level, corroborating previous research. However, when elasticity is used, the effectiveness of spatial aggregation in reducing the externality is almost identical whether detection occurs at field level or at silos level. Our results show also that the area planted with GM is the most important 'policy variable' in affecting the externality to conventional growers and that buffer areas on conventional fields are more effective than those on GM fields. The implications of the results for the coexistence policies in the EU are discussed.

    ISSN : 0167-8809

    DOI : 10.1016/j.agee.2008.07.004

    Record Number : 20093028707

    Publisher : Elsevier

    Location of publication : Amsterdam

    Country of publication : Netherlands

    Language of text : English

    Indexing terms for this abstract:

    Organism descriptor(s) : Brassica napus var. oleiferabrassica napus var. oleiferaSubject Category: Organism Names
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    , BrassicalesbrassicalesSubject Category: Organism Names
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    , plantsplantsSubject Category: Organism Names
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    Descriptor(s) : agricultural landagricultural landSubject Category: Habitats
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    , agricultural policyagricultural policySubject Category: Miscellaneous
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    , externalitiesexternalitiesSubject Category: Miscellaneous
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    , gene flowgene flowSubject Category: Natural Processes
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    , genetically engineered organismsgenetically engineered organismsSubject Category: Organism Groups
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    , herbicide resistanceherbicide resistanceSubject Category: Properties
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    , landscapelandscapeSubject Category: Miscellaneous
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    , Monte Carlo methodmonte carlo methodSubject Category: Techniques, Methodologies and Equipment
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    , raperapeSubject Category: Commodities and Products
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    , swede rapeswede rapeSubject Category: Commodities and Products
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    , tolerancetoleranceSubject Category: Properties
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    , transgenic plantstransgenic plantsSubject Category: Organism Groups
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    Identifier(s) : canola, Capparales, farmland, genetically engineered plants, genetically modified organisms, genetically modified plants, GEOs, GMOs, oilseed rape, transgenic organisms

    Broader term(s) : Brassica napusbrassica napusSubject Category: Organism Names
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    , BrassicabrassicaSubject Category: Organism Names
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    , BrassicaceaebrassicaceaeSubject Category: Organism Names
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    , BrassicalesbrassicalesSubject Category: Organism Names
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    , eudicotseudicotsSubject Category: Organism Names
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    , angiospermsangiospermsSubject Category: Organism Names
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    , SpermatophytaspermatophytaSubject Category: Organism Names
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    , plantsplantsSubject Category: Organism Names
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    , eukaryoteseukaryotesSubject Category: Organism Names
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