Use of the metapopulation theory and individual-based models to improve pest control

The tsetse fly complex (Glossina spp.) is widely recognized as a key contributor to the African continent's continuing struggle to emerge from deep economic, social and political problems. Control efforts for the fly have resulted in both successes and failures and good decision-making tools are imperative in tsetse control programs. In this paper I use spatial network structure combined with classic metapopulation modeling in order to explore how extinction probabilities differ from simpler formulations that do not take into account spatial structure. The model shows how that as network connectivity increases, metapopulation persistence also increases, and the probability of extinction decreases. In addition, agent-based systems have become very important to understanding the complex interactions of organisms in ecological and evolutionary systems. Like the complexity found in natural systems, these models allow complexity to bubble-up from lower-level scales as digital organisms allow representation at multiple spatial and temporal scales. These types of models present several challenges to understanding how a simulation represents the real world and what role it can play in scientific discourse and adaptive management in insect control programs