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S37.4: Modelling the deterioration of the Baden‐Württemberg forest as a function of soil and tree characteristics
Author(s) -
Musio Monica,
Augustin Nicole
Publication year - 2004
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.200490134
Subject(s) - library science , citation , function (biology) , computer science , tree (set theory) , information retrieval , forestry , operations research , geography , mathematics , combinatorics , biology , evolutionary biology
During the past 30 years an increase in forest damage has been observed in the forest of Baden-Württemberg, a federal state in the\udSouthwest region of Germany. Forest damage has been frequently related to acid rain resulting in accerlerated soil acidification and\udinduced nutritional deficiency. In some of the areas of Baden-Württemberg the soils are already acidic, e.g. in the Black Forest\udwhere the geology is mainly siliceous bedrock such granite and gneiss and does not have a high buffer capacity against the acids.\udHowever, it is difficult to make a direct linkage between acidic deposition and forest health because trees are exposed to many\uddiverse stresses. Causes of forest decline can be grouped into two categories. One category posits direct damage to forest canopy\udthat is reversible. The other category posits indirect damage to soil quality changes that may be irreversible and slow to recover. A\udmodel for the forest status is proposed which try to take into account of these two different sources of damage. We use the methodology\udof generalised additive mixed models, also called geoadditive models, to accomplish this task. The available data are from\udthe survey of emission impact and forest nutrition (IWE) carried out by the Forest Research Centre Baden-Württemberg (FVA) in\ud1994 and the Chemical soil condition survey (BZE) carried out in 1992, which have a different spatial resolution. Variables collected\udin these survey includes nutrients in the needles and in the soils (Mg, Ca K, Mn ,P and N); Tree characteristics such as the\udpercentage of needle losses, the age and the type of tree (fir/spruce); Soil characteristics such as altitude, geological area, direction/\udtype of slope, gradient of slope, relief, type of situation, soil texture, soil type, soil depth, soil water budget, nutrient balance\udand humus form