Spatially explicit landscape spread model for wind-dispersed glyphosate-resistant Conyza canadensis seed

Wind-dispersed herbicide-resistant genes in the form of seeds can easily connect seemingly independent farmsteads through long-distance dispersal.  A spatially explicit model examined how increased adoption of glyphosate-resistant crops (corn, soybean, and alfalfa) facilitates spread of glyphosate-resistant Conyza canadensis.  A 10 km x 9 km aerial photo was partitioned into 360 irregular polygons (agricultural fields) and non-agricultural area.  A dispersal kernel derived from three years of empirical research defined interfiled movement via numerical integration.  Crop diversity effects were assessed for 2 crop (corn, soybean) and 3 crop (alfalfa, corn, and soybean) rotations.  Management diversity was incorporated by overlaying survivorship on cropping system (glyphosate-resistant crop with glyphosate = high Conyza survivorship; alternative management = low Conyza survivorship). Survivorship in alfalfa was always zero based on intraseason harvesting.  Under a 2 crop rotation with glyphosate-resistant crops, all fields were infested after 5 years, while reducing the survivorship by 1/2, reduced the number of infested fields from 360 to 20.  Under the same scenario, maximum distance from initial source to the farthest infested field decreased from 6700 m to 4800 m.  Even with glyphosate-resistant crops, adding alfalfa reduced the maximum distance by 1000 m and spread to 100 fewer fields after 5 years.  According to the model, reducing survivorship through alternative management scenarios has a greater impact than adding an additional crop.  The model revealed that diversifying crop rotation and weed management techniques will profoundly slow the invasion speed of herbicide resistant weeds.  Spatially explicit models can help explore future agricultural policy by predicting the potential impacts of certain management practices.