Quantifying the effect of buffer zones, crop areas and spatial aggregation on the externalities of genetically modified crops at landscape level
Quantifying the effect of buffer zones, crop areas and spatial aggregation on the externalities of genetically modified crops at landscape level
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DOI：
10.1016/j.agee.2008.07.004
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发表时间：
2009-01-01
影响因子：
6.6
通讯作者：
Perrings, Charles
中科院分区：
文献类型：
--
作者：
Ceddia, M. Graziano;Bartlett, Mark;Perrings, Charles
转基因（GM）作物的发展促使欧盟（EU）提出“共存”的概念，让种植者可以自由种植传统品种和转基因品种。如果市场上出现非转基因品种的溢价，转基因花粉的“污染”将对传统种植者产生负外部性。因此，重要的是评估不同“政策变量”对外部性大小的影响，以确定管理共存的合适政策。在本文中，我们以耐除草剂的转基因油菜作为模型作物，从 Ceddia 等人开发的模型开始。 [Ceddia, M.G.、Bartlett, M.、Perrings, C., 2007。景观基因流、共存和阈值效应：转基因耐除草剂油菜（甘蓝型油菜）案例。生态。模型。 205，第169-180页]使用蒙特卡罗实验生成数据，然后估计转基因田和常规田的数量、缓冲区的宽度和空间聚集程度（即“政策变量”）对景观层面外部性大小的影响。为了代表农业生产的现实条件，我们假设常规农产品中转基因材料的检测可能发生在田间水平（不发生谷物混合）或筒仓水平（发生来自景观中不同田地的谷物混合）。在前一种情况下，外部性的大小将取决于平均转基因存在高于某个阈值的常规田地的数量。在后一种情况下，外部性的大小将取决于所有常规领域的平均转基因存在是否超过阈值。为了量化相关“政策变量”的影响，我们计算边际效应和弹性。我们的结果表明，当依靠边际效应来评估不同“政策变量”的影响时，当在田间检测到转基因材料时，空间聚集要重要得多，这证实了先前的研究。然而，当使用弹性时，无论检测发生在现场级别还是筒仓级别，空间聚合在减少外部性方面的有效性几乎相同。我们的结果还表明，转基因种植面积是影响传统种植者外部性的最重要的“政策变量”，并且传统田地的缓冲区比转基因田的缓冲区更有效。讨论了结果对欧盟共存政策的影响。 (C) 2008 Elsevier B.V. 保留所有权利。
The development of genetically modified (GM) crops has led the European Union (EU) to put forward the concept of 'coexistence' to give fanners 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. Landscape gene flow, 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. (C) 2008 Elsevier B.V. All rights reserved.