| A number of recent reports from the scientific and public interest group communities called for risk analyses to be carried out for complex ecological systems subject to different environmental stressors. These stressors include the introduction of genetically modified crops, global warming, and non-native species bio-invasion. The complexity of ecological systems makes them different from many other well defined engineered systems. Hence they bring considerable challenges when attempting to assess potential risks as well as the inevitable uncertainties and ambiguities associated with existing data. Based on the level of complexity, uncertainty and ambiguity, the traditional methodologies of risk analysis do not apply any more.; The main objective of the dissertation presented in this dissertation is to combine the fields of ecology and Ecological Risk Assessment (ERA), in order to develop a novel and more holistic in silico complement to ERAs that simulates the structure and dynamics of complex ecological networks. This new approach is intended to estimate and predict the risk under various environmental stressors, such as non-indigenous species invasions to native communities and global warming. This approach will provide a more general, synthetic, integrated, and holistic model to help decision makers and the public estimate and predict long-term ecological risks associated with environmental stressors. Here, we present a new approach for exploring the interplay of complex trophic interactions and consumption of multiple nutrients among producer species using nonlinear and non-equilibrium numerical simulations. Additionally, new perspectives and methods for risk assessment and management for complex bio-systems were explored. In this dissertation, we use genetically modified crops as a case study to develop novel ideas and solutions regarding risk monitoring and risk management for complex ecological systems. |
