Kochia pollen dispersion was measured during 24 and 48 h periods from a kochia population in an 8- by 10-m area in the center of a 1.6 ha fallow field. Pollen counts from traps at 50- and 100-cm heights declined rapidly with increasing distance from the pollen source. Pollen deposition was highest along the prevailing wind direction: up to 23 pollen grains cm–2 were recovered 50 m from the pollen source along the southeast (SE) vector. Nonlinear regression analysis of pollen deposition along the SE vector was used to estimate that 99.9% of shed pollen would be deposited within 154.4 m of the source. Viability of pollen from greenhouse- and field-grown plants was measured using staining and germination assays. of four pollen stains tested, only 1,2,3-triphenyl tetrazolium chloride gave consistent results and did not stain heat-killed pollen. Depending on environmental conditions, kochia pollen remained viable from less than 1 d to 12 d. Length of kochia pollen viability was shortest under high temperatures (22 and 28 C) and low relative humidity (7 and 32%). Less than 0.5% germination was observed in 1.1% agar media with various additions; however, up to 17.8% germination was observed after incubation at 28 C in 100% relative humidity.

We comment on Zaida Lentini's summary of Session V (titled “Estimating Likelihood and Exposure”) of the 9th International Symposium on the Biosafety of Genetically Modified Organisms. We provide an explanation of the drawbacks of using empirical pollen dispersion models, based largely on the general representativeness of the data used to generate the empirical models. We exemplify the drawbacks by highlighting the limited data used to develop the empirical model of Gustafson (presented in the same Symposium session). We provide a discussion of the meaning of “worst-case” assessments for pollen dispersion, how “worst-case” assumptions are commonly used in environmental impact assessments and how regulators will view worst-case impact assessments differently from the regulated (biotech) community. Finally, we clarify the advantages and disadvantages of mechanistic models and explain why they are often used in preference to empirical models in environmental impact assessments.