Abstract
Soil–landscape patterns result from the integration of short‐ and long‐term pedogeomorphic processes. A 2‐ha hillslope catena in California shows short‐distance variation in A horizon depth from 8 to 80 cm and in soil depth from 8 to >450 cm in convex to concave positions. Similar variations in net primary productivity (NPP) and soil C represent significant information often not captured by soil survey maps. Strong correlations between these measured soil–landscape variables and explanatory digital terrain attributes are used to develop quantitative soil–landscape models. We were able to account for between 52 and 88% of soil property variance using easily computed terrain variables such as slope and flow accumulation. Spatial implementation of the models suggest lateral redistribution processes resulting in differential accumulation of C and soil mass in convergent and divergent landscape positions. The models are explicit and quantitative, which enables their use for testing hypotheses about the spatial distribution of fine‐scale landscape and ecosystem processes and for parameterizing spatially distributed hydrological and ecosystem simulation models.
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