This dissertation develops an optimization framework for conservation planning and illustrates the framework using case studies from Alaska, Balcones Canyonlands National Wildlife Refuge (BCNWR) in central Texas, and Mexico. The common theme of the chapters is the use of optimization models to design conservation areas. Chapter 1 explains how the subsequent chapters are related to one another. Chapter 2 develops a framework for measuring how the cost of establishing conservation areas changes over time. When this method is applied to a data set on Mexican mammals, it is shown that twice as much land would have to be set aside to protect adequate mammal habitat today than would have been required in 1970 due to ongoing deforestation. Chapter 3 presents an optimization model for planning the establishment of conservation areas that incorporates forecasts of species' responses to global warming. The model is applied to analyze endangered birds and the polar bear (Ursus maritimus) on the Arctic coast of Alaska. Chapter 4 discusses the modeling of habitat for two endangered bird species, the Black{capped Vireo (Vireo atricapillus) and the Golden{cheekedWarbler (Dendroica chrysoparia), at BCNWR using a machine{learning algorithm (Maxent). These habitat models serve as part of the input for a one{stage optimization model for acquiring land to expand BCNWR. Chapter 5 uses graph theory to select corridors to establish connectivity between conservation areas in Mexico. The planning method presented in Chapter 5 is implemented in a free software package for corridor design, LQGraph. / text