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Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment.

机译:组装花粉和孢子随风散布的空间显式景观模型,以进行风险评估。

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Models of windblown pollen or spore movement are required to predict gene flow from genetically modified (GM) crops and the spread of fungal diseases. We suggest a simple form for a function describing the distance moved by a pollen grain or fungal spore, for use in generic models of dispersal. The function has power-law behaviour over sub-continental distances. We show that air-borne dispersal of rapeseed pollen in two experiments was inconsistent with an exponential model, but was fitted by power-law models, implying a large contribution from distant fields to the catches observed. After allowance for this 'background' by applying Fourier transforms to deconvolve the mixture of distant and local sources, the data were best fit by power-laws with exponents between 1.5 and 2. We also demonstrate that for a simple model of area sources, the median dispersal distance is a function of field radius and that measurement from the source edge can be misleading. Using an inverse-square dispersal distribution deduced from the experimental data and the distribution of rapeseed fields deduced by remote sensing, we successfully predict observed rapeseed pollen density in the city centres of Derby and Leicester (UK).
机译:需要使用风吹花粉或孢子运动的模型来预测转基因(GM)作物的基因流和真菌疾病的传播。我们建议使用一种简单形式的函数来描述花粉粒或真菌孢子移动的距离,以用于通用的扩散模型。该功能在次大陆距离上具有幂律行为。我们显示,在两个实验中,油菜花粉的空气传播扩散与指数模型不一致,但是通过幂律模型拟合,这意味着从遥远的田地到观察到的渔获量有很大贡献。在通过使用傅立叶变换对远方和局部源的混合进行反卷积而允许这种“背景”存在之后,数据最适合幂指数在1.5和2之间的幂定律。我们还证明了对于简单的面积源模型,中值散布距离是场半径的函数,从源边缘的测量可能会产生误导。使用从实验数据推导出的平方反比分布和通过遥感推导的油菜田的分布,我们成功地预测了在德比和莱斯特(英国)市中心观察到的油菜花粉密度。

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