A Multicriteria Decision Analysis For Identifying Priority Conservation Areas For Grassland Birds

Biodiversity conservation frequently competes with the needs of society for agricultural production and development. However, properly designed and efficiently implemented conservation programs can be used to integrate wildlife and human needs. We tested the efficacy of multicriteria decision analysis as a tool to select priority areas for conservation in human-dominated landscapes using grassland birds in the northeastern US as a test case. We created detailed GIS layers including landscape- (forest, grassland, development, and roads within a 3000-m buffer around each grassland patch) and patch-level (size, management, and conservation status) criteria important in grassland bird habitat selection and conservation. We developed a set of 36 scenarios in which we varied the relative weights associated with different patch attributes. A sensitivity analysis showed that the habitat quality score for each patch was less sensitive to changes in weights at the landscape level, and more sensitive to changes at the patch level. Integrating the GIS dataset into a multicriteria decision analysis framework, we produced maps in which grassland patches were ranked based on habitat quality and used these maps to identify priority conservation areas. Grassland blocks of \u3e100 ha were mainly concentrated in 2 regions and were identified as priority sites that had the highest quality values for grassland bird conservation. This approach resulted in maps that managers can use to focus conservation efforts. The integration of GIS with multicriteria decision analysis can serve as a model for researchers to help set priorities for land conservation for other species and in other regions