Biophysical settings describe site-specific physical and biotic conditions from which landscape composition, structure and function can be predicted, and represent a key starting point on the road to predicting fire regimes across landscapes. Previous efforts to map biophysical settings typically have included characterizing elevation, aspect, slope, and soil characteristics. In addition to these variables that indirectly affect ecological processes, we incorporated geospatial output from weather and ecosystem simulation models (WX-FIRE and LF-BGC), which calculate ecophysiological gradients that, in turn, can describe unique biophysical settings. Our main challenges included integrating spatial data at multiple scales, and developing methods to efficiently build moderate resolution spatial data (30-m) across very large landscapes (ranging from 6 to 10 million ha.). We used the resulting ecophysiological gradients to classify landscapes into an array of distinct areas with similar biophysical conditions, using hierarchical cluster analyses along with the See5 spatial classifier. These biophysical settings then provided a link for extrapolating the ecological process of succession across landscapes. Here, we describe several novel approaches to creating moderate resolution environmental gradients, and how these gradients are used to predict climax plant communities.