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a Dep. of Forest Resources, Univ. of Idaho, Moscow, ID 83844-1133 USA
b Dep. of Geography, Univ. of California, Santa Barbara, CA 93106 USA
c Dep. of Ecology, Evolution & Marine Biology, Univ. of California, Santa Barbara, CA, 93106 USA
paulg{at}uidaho.edu
Soillandscape 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 soillandscape variables and explanatory digital terrain attributes are used to develop quantitative soillandscape 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.
Abbreviations: CEC, cation-exchange capacity CTI, compound topographic index Cmass, profile total C mass DEM, digital elevation model GIS, geographic information system GPS, global positioning system NPP, net primary productivity
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