title: Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment.
abstract: 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).
authors.affiliation: School of Biological Sciences, The University of Reading, 2 Earley Gate, Whiteknights, Reading RG6 6AU, UK. m.w.shaw@reading.ac.uk
authors.forename: M W
authors.initials: MW
authors.lastname: Shaw
authors.forename: T D
authors.initials: TD
authors.lastname: Harwood
authors.forename: M J
authors.initials: MJ
authors.lastname: Wilkinson
authors.forename: L
authors.initials: L
authors.lastname: Elliott
mesh_terms: D000397:Air Pollution; D029741:Brassica rapa / Q000502:physiology; D005583:Fourier Analysis; D011058:Pollen / Q000502:physiology*; D018570:Risk Assessment; D013172:Spores, Fungal / Q000502:physiology*; D006113:United Kingdom; D014919:Wind