Sensitivity Analysis of Populations: New Models, New Applications

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Population models provide estimates of such important quantities as population growth rate, short- and long-term population dynamics, population structure, and extinction risk. In all these cases, it is important to evaluate the sensitivity of model results to changes in parameters, such as rates of birth, growth, death, and movement. Such changes can result from environmental change, evolutionary change, management actions, or revised estimates from new data. This project will produce new mathematical tools for the sensitivity analysis of nonlinear population models. The results will be developed using matrix calculus, and will be applied to spatial models, epidemic models, harvest models, and models for breeding and pair formation. Sensitivity analysis is significant to several areas of population biology. In evolutionary biology, sensitivity analysis shows the fitness consequences of changes in life histories. In population management (including the conservation of threatened species, the control of pests, and the harvest of resources) it is used to evaluate the effects of management strategies. The mathematical methods developed here will also be of value in many other areas of ecology. The project will have broader impacts through educational outreach, advice to government agencies concerned with population management, and training of a post-doctoral researcher.