A large number of wild plant species and the vast majority of fruits and vegetables, some forage and oil producing crops require insects for pollination and seed production. Insect pollinators transfer pollen as they move from flower to flower. They move genes during this process which can lead to the escape of genetically engineered (GE) genes and create adventitious presence (unwanted gene flow), for example when they move from a genetically engineered (GE) to a
conventional or organic field. Genetically engineered genes may also move to feral or wild populations. A better understanding of the relationships between pollinator foraging behavior and the potential for pollen dispersal and gene flow would not only improve predictions of gene flow risk (movement of pollen resulting in a mature seed) in insect-pollinated plants but it could guide the development of pollinator management strategies to reduce the risk of transgene escape. Reduced gene flow would facilitate the coexistence of different markets and limit the potential for introgression of transgenes into wild or feral populations.
We first examined the potential differential impact of distinct pollinator species on pollen dispersal and gene flow in the Rocky Mountain columbine (Aquilegia coerulea). This system was selected because bumblebees and hawkmoths could be contrasted, with bees visiting the plants mostly during the day and hawkmoths at dusk. We showed that distinct pollinators can differentially affect the outcrossing rate of plants (Brunet and Sweet 2006, Evolution) and, using genetic markers, that these different pollinators may differentially move pollen long distances (Brunet and Holmquist 2009, Molecular Ecology).
To examine the potential impact of the landscape on gene flow, we switched to alfalfa (Medicago sativa). Honey bees and leaf cutting bees are used as managed pollinators of alfalfa in seed production fields and bumble bees are used for breeding. We have demonstrated how features of the agricultural landscape, so far plant density, may differentially affect gene flow for distinct bee species (Brunet and Stewart 2010, Psyche: A Journal of Entomology).
Our ultimate goal is to link pollinator behavior to gene flow and to develop a model of gene flow by insect pollinators. In collaboration with Dr. Murray Clayton in the departments of Statistics and Plant Pathology at the University of Wisconsin in Madison, we are developing a simulation model that links pollinator behavior to gene flow over the agricultural landscape. Such model will help predict gene flow and the risk of transgene escape for alfalfa seed production fields and for other insect-pollinated crops.