Metropolitan Open‐Space Protection with Uncertain Site Availability

Urban planners acquire open space to protect natural areas and provide public access to recreation opportunities. Because of limited budgets and dynamic land markets, acquisitions take place sequentially depending on available funds and sites. To address these planning features, we formulated a two-period site selection model with two objectives: maximize the expected number of species represented in protected sites and maximize the expected number of people with access to protected sites. These objectives were both maximized subject to an upper bound on area protected over two periods. The trade-off between species representation and public access was generated by the weighting method of multiobjective programming. Uncertainty was represented with a set of probabilistic scenarios of site availability in a linear-integer formulation. We used data for 27 rare species in 31 candidate sites in western Lake County, near the city of Chicago, to illustrate the model. Each trade-off curve had a concave shape in which species representation dropped at an increasing rate as public accessibility increased, with the trade-off being smaller at higher levels of the area budget. Several sites were included in optimal solutions regardless of objective function weights, and these core sites had high species richness and public access per unit area. The area protected in period one depended on current site availability and on the probabilities of sites being undeveloped and available in the second period. Although the numerical results are specific for our study, the methodology is general and applicable elsewhere.