Understanding the tradeoffs between site quality and species presence in reserve site selection

A number of optimization models have been developed for natural reserve des ign and reserve site selection. The most common approach seeks to maximize the number of individual species that occur among chosen sites. A number of heuristics and mathematical programming algorithms have been applied to so lve this problem. Although attaining maximum overall species representation is important, the relative quality of representation [which could be affec ted by site attributes such as habitat value, adequate population size, pre sence of critical resources, existence (or lack thereof) of exotic competit ors, etc.] has been absent from most representation models. Yet issues of s ite quality should be considered in order to have any assurance of long-ter m species persistence in a reserve system. Here we present a multiobjective optimization model that addresses the issue of balancing species presence with habitat quality. One type of interesting alternative yields more high quality representation at the price of some reduction in overall representa tion. We present an application using a large dataset from California Gap A nalysis to demonstrate this and other tradeoffs. Optimal solutions are atta ined using commercial integer programming software with very reasonable com putational effort.