This file was created by scanning the printed publication. Errors identified by the software have been corrected; however, some errors may remain. A Landscape Approach to Monitoring and Assessing Ecological Condition - San Pedro Case Study1 William G. Kepner2 , Kurt H. Ritters3 , Christopher Watts 4 , David C. Goodrich5 , Russell Scott5 , and Ghani Chehbouni 4 The U.S. Environmental Protection Agency has initiated a national approach to assess ecological risk relative to exposure to environmental stressors. A key component of this framework enlists landscape ecology as a theoretical basis from which to assess cumulative exposure to stress at multiple spatial and temporal scales. This project has focused its research into developing a system of landscape composition and pattern indicators which can be used to estimate current status, trend, and changes in ecological and hydrological condition. Specifically, it is designed to determine ecosystem vulnerability relative to large-scale natural or man-induced disturbances (e.g. climatic change and livestock grazing, respectively) using a system of landscape pattern metrics derived from remote sensing, spatial statistics, and geographic information systems technology. The program has proposed a strategy of utilizing triplicate Landsat Multi-spectral Scanner imagery from the early 1970s, mid-1980s, and early 1990s, in addition to finer resolution imagery (i.e. Landsat-TM, SPOT, and aerial photography) to generate land cover data and establish 20-year trends in condition for selected geographic areas. This process has been tested in a small community-based watershed in southeast Arizona and northern Sonora and has been particularly related to land degradation and habitat modeling for selected wildlife species in the Upper San Pedro Watershed. Very little quantitative information on a regional or watershed scale is available on status of land degradation for rangelands. Rangelands, such as those that occur in the San Pedro Watershed, are the most extensive land use of the world dry lands. Nearly 85 of the North American rangelands are estimated to be in degraded condition; more than any other continent in the world. Landscape composition, connectivity, and patch sizes and number were used to evaluate ecosystem resilience and changes in land cover extent and wildlife habitat suitability over a 13-year period in the San Pedro River basin. The evaluation determined that extensive grassland areas with high connectivity were the most vulnerable ecosystem to fragmentation due to encroachment of woody shrubs and cacti. For example, the number of grassland patches increased 61% and the average grassland patch size decreased 60% between 1974 and 1987. The preliminary results of this project are presented to 1) illustrate both the indicator and change detection strategy; 2) demonstrate the value of the approach to ecosystem and watershed management; and 3) demonstrate the potential application of the approach for developing a 1 2 3 4 5 Abstract of a poster presented at the conference. U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas NV. Tennessee Valley Authority, Environmental Research Center, Norris TN. Centro de lnvestigacion y Desarrollo de los Recursos Naturales de Sonora, Hermosillo, Sonora. USDA Agricultural Research Service, Southwest Watershed Research Center, Tucson AZ. 243 national, regional, and watershed program for systematic assessment of ecological condition, especially in regard to land degradation in arid and semi-arid regions of the world. This research is one component of a multinational long-term monitoring and modeling proposal entitled the Semi-Arid Land Surface-Atmosphere (SALSA) Program. Results of the landscape analysis listed above will be integrated with other related projects within SALSA to determine the consequences of natural and human-induced change on the water balance and ecological diversity of the Upper San Pedro Watershed at multiple temporal and spatial scales. (Also see http://www.hwr.arizona. edu/salsa/salsa_l.html and http://www/epa.gov/crdlvweb). 244