Regression Analysis for Forest Inventory Data

In this paper the data of a forest health inventory are analysed. Since 1983 the degree of defoliation (damage), together with various explanatory variables (covariates) concerning stand, site, soil and weather, are recorded by the second of the two authors, in the forest district Rothenbuch (Spessart, Bavaria). The focus is on the space and time dependencies of the data. The mutual relationship of space-time functions on the one side and the set of covariates on the other is worked out. To this end we employ generalized linear models (GLMs) for ordinal response variables and employ semipara-metric estimation approaches and appropriate residual methods. It turns out that (i) the contribution of space-time functions is quantitatively comparable with that of the set of covariates, (ii) the data contain much more (timely and spatially) sequential structure than smooth space-time structure, (iii) a ne analysis of the individual sites in the area can be carried out with respect to predictive power of the covariates.