Mj. Lexer et K. Honninger, Estimating physical soil parameters for sample plots of large-scale forestinventories, FOREST ECOL, 111(2-3), 1998, pp. 231-247
The use of data from large-scale forest inventories for the development and
application of explanatory ecosystem models is often hampered by a lack of
quantitative site data. To circumvent such limitations, we describe a meth
od to estimate soil water-holding capacity (SWC), a key parameter in many e
cosystem simulation models, for the sample plots of the Austrian Forest Inv
entory (AFI). In accordance with the limited soil data which are customaril
y recorded by forest inventories, a functional model for the calculation of
SWC from soil depth, coarse fractions in two soil layers, water-holding ca
pacity of the fine fraction and the organic carbon content of the mineral s
oil is developed. Bayesian probability theory is employed to establish rela
tionships between measured site attributes of the AFI and the soil paramete
rs required for calculating SWC. More detailed site and soil data of 514 sa
mple plots of the Austrian Forest Soil Survey (AFSS) which can be considere
d a subsample of the AFI are used for model calibration. As explanatory var
iables orientation, slope, elevation, topography, soil-type and humus-type
are included in the predictive models for the estimation of the required so
il parameters. Model performance in reproducing the calibration dataset was
evaluated by means of intraclass correlation coefficients. A predictabilit
y index from the field of information theory is used to evaluate the contri
bution of the independent variables in explaining the variability (entropy)
of the dependent variables. A preliminary model validation with a subset o
f AFSS data indicated good agreement of observed and predicted values for t
he individual soil parameters as well as for the composite parameter SWC. (
C) 1998 Elsevier Science B.V.