title: An algorithm for estimating potential deposition of corn pollen for environmental assessment.
abstract: The safety and impact on the environment of transgenic crops are important issues, and studies have shown that pollen from transgenic Bt (Bacillus thuringiensis) corn (Zea mays L.) may kill nontarget insects. To develop an algorithm for assessing the environmental effect of transgenic crops, we arranged a field experiment in Tsukuba, Japan. Pollen dispersal and deposition were measured inside and outside a cornfield throughout the flowering period. Weather conditions such as wind speed and direction were measured at the same time. Pollen dispersal peaked 1 week after the start of flowering and continued for 12 days thereafter. The variation in daily pollen dispersal was similar at all observation points. Both pollen dispersal and deposition decreased exponentially with distance from the cornfield on all days. We estimated potential pollen deposition with a quasi-mechanistic model that incorporates the effects of wind direction, wind speed, and flowering intensity. The daily potential deposition was summed over the flowering period, and then the relationship between distance from the cornfield and the integrated potential deposition was estimated. It was possible to show the effective area of the environmental risk zone posed by genetically modified pollen by combining the distance/deposition relationship with the dose/response relationship derived from a laboratory assay. The algorithm described here can be applied to various wind-pollinated plants to estimate both potential and integrated pollen deposition.
authors: National Institute for Agro-Environmental Sciences 3-1-3 Kannondai, Tsukuba 305-8604, Japan. sig@affrc.go.jp
authors: Shigeto
authors: S
authors: Kawashima
authors: Kazuhito
authors: K
authors: Matsuo
authors: Mingyuan
authors: M
authors: Du
authors: Yuichi
authors: Y
authors: Takahashi
authors: Satoshi
authors: S
authors: Inoue
authors: Seiichiro
authors: S
authors: Yonemura
mesh_terms: D000465:Algorithms; D000818:Animals; D001413:Bacillus thuringiensis / Q000472:pathogenicity; D005828:Genetics, Population; D007313:Insecta; D008685:Meteorological Concepts; D010571:Pest Control; D030821:Plants, Genetically Modified; D011058:Pollen; D018570:Risk Assessment; D012449:Safety; D014919:Wind; D003313:Zea mays / Q000235:genetics*