Three-dimensional prediction of maize pollen dispersal and cross-pollination, and the effects of windbreaks

Abstract

With the extensive adoption of transgenic crops, an understanding of transgene flow is essential to manage gene flow to non-GM crops. Thus, a flexible and accurate numerical model is required to assess gene flow through pollen dispersal. A three-dimensional atmospheric model combined with a diffusion transport model would be a useful tool for predicting pollen dispersal since it would be flexible enough to incorporate the effects of factors such as the spatial arrangement of crop combinations, land use, topography, windbreaks, and buildings. We applied such a model to field measurements of gene flow between two adjacent maize (Zea mays) cultivars, with suppression effects due to windbreaks, in an experimental cornfield in Japan. This combined model reproduced the measured cross-pollination distribution quite well in the case of maize plots with plant windbreaks slightly taller than the maize and without windbreaks, but the model underestimated the effect of a 6-m-tall windbreak net beyond 25 m from the donor pollen source on cross-pollination. The underestimation was most probably due to the problem of assimilated wind data. The model showed that the 6-m-tall windbreak and the plant wind break suppressed average cross-pollination rate by about 60% and 30%, respectively. Halftall and coarser mesh windbreak net suppressed cross-pollination rates by 40% by reducing the swirl of donor pollen by reduced wind speed.

A system model for estimating regional cross-pollination rates between GM and non-GM rice considering actual meteorological conditions and field distributions

“…pdhm2 uses a plume model, which is a kind of quasi-mechanistic model that has been widely used for the prediction of diffusion of atmospheric pollutants. The model has the advantage of rapid calculation time, in contrast to the Lagrangian model (Ushiyama et al, 2009), which traces the movement of each particle one by one. pdhm2 has flexibility with respect to grid size and calculation time from the beginning to the end of the flowering that is set by the header file pdhm.…”

“…Pollen flow from GM maize has also been well studied (Jarosz et al, 2003;Jarosz et al, 2005;Kawashima et al, 2004;Sanvido et al, 2008;Ushiyama et al, 2009), because Bt (Bacillus thuringiensis) maize has high productivity due to the reduction of insect damage and because cross-pollination can occur over long distances (hundreds of meters or more). Some of the above studies in Europe were conducted in projects that aim to promote the introduction of GM crops.…”

“…At the beginning stage, field studies were intensively conducted for many crops, especially maize (Kawashima et al, 2004). Later, Ushiyama et al (2009) used a Lagrangian model to calculate maize pollen dispersion more dynamically by using experimental data. Moreover, based on results from field experiments, Kawashima (2006) developed a prototype model to calculate rice pollen dispersion (see Section 2 of this paper).…”

Numerical study of the effective arrangements of windbreaks to suppress maize pollen dispersal and cross-pollination

“…1. ( 1993( Maki et al, 2004 ( Wang and Takle, 19951996Wang et al, 2001Bourdin and Wilson, 2008) (Cleugh, 1998Takahashi et al, 1998 (Ushiyama et al, 2009b) ( ) : Ushiyama et al, (2009b) 10 50 m 1 1 2 3 4 5…”

Reducing Pollen Dispersal using Forest Windbreaks

“…found that a vegetative border of a tall annual grass (sorghum-sudangrass hybrids) reduced pollen transport from a maize field. Ushiyama et al [2010] evaluated fences as windbreaks in maize fields, but found little effect on pollen dispersal. Although research has shown that pollen concentration decreases with distance from the source [Ecker et al, 2013, Chamecki and Meneveau, 2011, Okubo and Levin, 1989, there are no studies on the effect of typical farm windbreaks (one or more rows of cultivated trees or shrubs) or narrow forest stands on pollen dispersal.…”