Population Dynamics and Community Organization -- As a Ph.D. student in the laboratory of Dr. George Batzli, I conducted field experiments to test predictions generated by our multifactorial model of vole population dynamics. The causes of multi-annual cycles in vole population density have eluded ecologists for decades, and single-factor approaches (such as those based on simple predator-prey or plant-herbivore relationships) have been applied widely but have proven unsatisfactory. The goal of this NSF-funded research was to study simultaneously the direct, indirect, and interactive effects of multiple factors. We hypothesized that observed dynamics are the result of interactions between factors that are extrinsic (environmental) and intrinsic (behavioral) to populations. We manipulated three extrinsic factors, food quality, predation, and interspecific competition and then monitored the responses of individuals and subsequent population dynamics. We predicted not only direct effects of changes in food quality and predation on vole population density, but also interactions of these factors with responses to the presence of interspecific competitors. From theories of social regulation, we expected increased rates of agonistic encounters with competitors to cause increased dispersal rates and decreased population density. We also predicted less dispersal when predators were present because they inhibit vole movements and less dispersal when supplemental food was present because it reduces aggressive behavior. Our model was partially supported. Interactive effects of competition did occur as expected, but the presence of predators and supplemental food increased, rather than decreased, the effects of competitors due to indirect effects on population density. We concluded that behavioral factors had much weaker effects on population dynamics than did environmental factors in this system. While multifactorial models have been criticized for being too general and untestable, this research clearly demonstrated their feasibility. I believe that investigations into the complex interrelationships among multiple factors can serve as a foundation for improved understanding of population and community dynamics. In my future research, I plan to continue employing small mammals as a model system, and also hope to apply this approach to other systems that are amenable to experimental manipulation.