Modeling Soil–Landscape and Ecosystem Properties Using Terrain Attributes
P.E. Gesslera,
O.A. Chadwickb,
F. Chamranb,
L. Althousec and
K. Holmesb
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
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Fig. 1 Study site at the University of California Sedgwick Natural Reserve in Santa Barbara County, California. The study site is shown both (a) as a drape of a digital orthophoto over a 30-m digital elevation model and (b) with the individual soil pit locations displayed on a 1-m contour shade map of the hillslope
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Fig. 2 Organic C percentage and N percentage depth plots with major horizon breaks for subset of nine soil pits selected for sampling
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Fig. 3 Log organic C/N ratio depth plots and linear regression model fits to two visually distinct soil pit sample subsets. Numbers next to the sample points represent the soil pit from which the sample was collected
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Fig. 4 Exploratory scatterplot matrix and local regression smoother fits for four measured soil properties vs. varied grid-spacing resolution CTI terrain variable
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Fig. 5 Predicted soil–landscape model surfaces implemented from predictive models as indicated in Table 3
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Copyright © 2000 by the Soil Science Society of America.
