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

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...

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Bibliographic Details
Published in:Proceedings of the Royal Society. B, Biological sciences Biological sciences, 2006-07, Vol.273 (1594), p.1705-1713
Main Authors: Shaw, M.W, Harwood, T.D, Wilkinson, M.J, Elliott, L
Format: Article
Language:English
Subjects:
Air Pollution
Brassica napus
Brassica rapa - physiology
Canola
Ecological modeling
Epidemic
Fat-Tailed Dispersal
Fourier Analysis
fungal diseases of plants
Fungal spores
Gene flow
Genetic Modification
Genetically Modified Crops
Invasion
landscaping
mathematical models
Modeling
Oilseeds
Point sources
Pollen
Pollen - physiology
Risk Assessment
Spatial
spore dispersal
Spores, Fungal - physiology
Transgenic plants
United Kingdom
Wind
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Summary: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).
ISSN:0962-8452
1471-2954
DOI:10.1098/rspb.2006.3491