Satellite Symposium 5: Molecular Breeding
Description
In order to predict the potential unintended ecological impacts of genetically modified (GM) grasses, we must understand how the engineered traits, in this case herbicide resistance, are expressed in an ecological context. It would be a daunting task to experimentally evaluate the full multiplicity of potential pair-wise interactions between GM plants and native plants under a broad variety of actual environmental conditions. We have employed the modelling methodology of cellular automata (CA), where a plant's distribution within a two-dimensional environmental grid is determined by rules relating to phenomena such as seed dispersal, clonal expansion and interactions with adjacent plants. We have used CA simulation to model interactions between GM grasses and the natural environment by describing the plants and the effect of the GM trait in terms of plant functional types. This approach takes the external factors which limit the amount of plant material present in any habitat and classifies them into two categories: (1) stress, defined with regard to the availability of nutrients and (2) disturbance, which refers to the destruction of plant material. The ecological characteristics of all the plants can be described based on three functional types C (competitor), S (stress-tolerator) and R (ruderal) as determined by their quantifiable physiological relationships to stress and disturbance. By ascribing the large number of plant ecological characteristics to a smaller number of functional types the problem, of describing how the engineered trait of herbicide resistance is expressed in an ecological context, becomes tractable.
Included in
Agricultural Science Commons, Agronomy and Crop Sciences Commons, Plant Biology Commons, Plant Pathology Commons, Soil Science Commons, Weed Science Commons
Use of Cellular Automata Modelling Approaches to Understand Potential Impacts of GM Grasses on Grassland Communities
In order to predict the potential unintended ecological impacts of genetically modified (GM) grasses, we must understand how the engineered traits, in this case herbicide resistance, are expressed in an ecological context. It would be a daunting task to experimentally evaluate the full multiplicity of potential pair-wise interactions between GM plants and native plants under a broad variety of actual environmental conditions. We have employed the modelling methodology of cellular automata (CA), where a plant's distribution within a two-dimensional environmental grid is determined by rules relating to phenomena such as seed dispersal, clonal expansion and interactions with adjacent plants. We have used CA simulation to model interactions between GM grasses and the natural environment by describing the plants and the effect of the GM trait in terms of plant functional types. This approach takes the external factors which limit the amount of plant material present in any habitat and classifies them into two categories: (1) stress, defined with regard to the availability of nutrients and (2) disturbance, which refers to the destruction of plant material. The ecological characteristics of all the plants can be described based on three functional types C (competitor), S (stress-tolerator) and R (ruderal) as determined by their quantifiable physiological relationships to stress and disturbance. By ascribing the large number of plant ecological characteristics to a smaller number of functional types the problem, of describing how the engineered trait of herbicide resistance is expressed in an ecological context, becomes tractable.
