GeneScape: Agent Based model of Gene Flow from crops and its implications for sustainability of Genetic Modification

Abstract

If Genetic Modification is to be accepted as a sustainable technological development its social, ecological and economical impacts must be understood.
One important tool in determining the environmental and human risks of a technological development such as Genetical Modification (GM), is the Quantitative Risk Analysis (QRA). QRA can quantify the risks of a new technology, so that the society can make a choice whether the benefits outweigh the risks. Only if the risk of a new technological development is very small and acceptable, can it be sustainable. One of the main risks from GMOs is the spread of their genes through Gene Flow into wild populations causing genetic pollution and potentially ecosystem disruption. The current QRA is based on mass flow models. It does not consider the fact that law of conservation of mass does not hold for genes, which are essentially information. QRA also dos not take the imbedded open feedback loops present in life forms, i.e. the ability to self-amplify and reproduce, into consideration. Because of these shortcomings, the current risk assessment tools are probably inadequate to answer the question whether Genetic Modification is a sustainable technological development. Next to the lack of scientific knowledge about the impacts, there is a lack of societal acceptance of GM. Part of the reason for the lack of acceptance is the unacceptability of the tools for risk prediction. There is a need for a risk analysis tool that is both acceptable and able to describe key aspects of life. Agent Based Models (ABMs) are a candidate modeling framework for such a tool because they are isomorphic to living organisms. Furthemore, they are intuitive and easy to understand, forming a basis for societal acceptance. By defining evolutionary processes and plant entities in Agent terms an Agent Based Model called GeneScape has been developed. The model explicitly describes Plants as entities with states and interactions. Plants populate a geometry, the Field, through which the environment, The World, enforces the rules for pollen distribution, mating and genetic inheritance. The World also determines how the information content of the plant, its genome, is to be translated into a fitness, and thus power to reproduce. While there is a shortage of good experimental data for validation, GeneScape is evaluated and found to be coherent and biologically sound. It is however not a quantitative prediction tool for Gene Flow, but an explicitand graphical representation of the mental models of Darwinian selection, Gene Flow and plant ecology. Its strength lies in the fact that it allows
the visualization of thought experiments on the behavior of GMO crops and the neighboring plant populations. It can serve as a basis for further development of a tool for risk assessment for GMOs. GeneScape can only be useful for answering questions about the sustainability of Genetic Modification if it is socially acceptable itself. Therefore, a societal acceptance hypothesis is formulated. The hypothesis states that GeneScape is not yet societally acceptable because it is too complex and the outcomes are open to interpretation. However, it is easily understandable and illustrative, which forms a basis for acceptance. The most important conclusion from the use of GeneScape is the insightinto the importance of the environment a GMO gene is placed in. The most important variables governing Gene Flow (Pollen spread distance, fitness increase by the GMO gene and the relatedness level of the urrounding populations) are dependent on environmental factors. Since the environment can not be controlled Genetically Modified Organisms can only be sustainable in a closed, controlled environment.