Graduation date: 2007Wildlife managers are on the front lines of the effort to conserve wildlife and are required to do so cost-effectively. This dissertation consists of three manuscripts that integrate economics and ecology to inform cost-effective wildlife management. The first and second manuscripts focus on identifying cost-effective wildlife management plans. The third manuscript considers wildlife management under uncertainty. The first manuscript integrates economic and ecological principles to identify cost-effective management plans. Bio-physical simulation and regression analysis are paired to approximate response functions for an important duck species, the mallard (Anas platyrhynchos). Response functions are then included in an economic optimization model to estimate management cost functions. Approximated response functions indicate that mallard response is non-linear due to diminishing marginal productivity and interdependence of management activities. This results in non-linear cost functions, which imply that the standard approach of treating ecological production and economic costs independently may result in inefficient management. The second manuscript extends the first by incorporating landscape heterogeneity. The same modeling approach is replicated for three landscapes that differ in their ecological and economic productivity. This approach demonstrates that taking advantage of landscape heterogeneity can generate cost savings if managers target multiple landscapes simultaneously. Additionally, management activities that do not interfere with agriculture are found to be highly cost-effective, suggesting that common ground exists between conservationist and private landowners. The first and second manuscripts assume that managers can predict wildlife response with certainty. The third manuscript illustrates the tradeoff between the risk and return to management when response is uncertain. Financial portfolio theory is adapted to account for diminishing marginal productivity and interdependence of management activities. An analytical model is used to determine how these properties alter the standard derivation of mean-variance efficient portfolios. This has implications for addressing uncertainty in many renewable resource contexts. Simulated data on mallards are used to apply the portfolio model to wildlife management. Results indicate that portfolio theory provides practical insights about managing wildlife under uncertainty.