Abstract
Routinely collected booking records of salvaged timber from the period 1979–2008 were used to empirically model the (1) storm damage probability; (2) proportions of storm-damaged timber and (3) endemic storm damage risk in the forest area of the German federal state of Baden-Wuerttemberg by applying random forests. Results from cross-validated predictor importance evaluation demonstrate that the relative impact of modeled gust speed fields on the predictive accuracy of the random forests models was greatest compared to the impact of forest and soil features. Forest areas prone to storm damage occurring within a period of five years were mainly located in mountainous upland regions where maximum gust speed exceeds 31 m/s in a five-year return period and conifers dominate the tree species composition. While mean storm damage probability continuously increased with increasing statistical gust speed proportions of storm-damaged timber peaked at a statistical maximum gust speed value of 29 m/s occurring in a five-year return period. Combining the statistical gust speed field with daily gust speed fields of two exceptional winter storms improved model accuracy and considerably increased the explained variance. Endemic storm damage risk was calculated from endemic storm damage probability and proportions of endemically storm-damaged timber. In combination with knowledge of local experts the storm damage risk modeled in a 50 m × 50 m resolution raster dataset can easily be used to identify areas prone to storm damage and to adapt silvicultural management regimes to make forests more windfirm.
Highlights
Storms influence forest ecosystems at multiple levels
Results from OOB-evaluation of DAMmod-model performance are presented in Table 4 (DAMOOB)
random forests (RF)-Model accuracy clearly increased for DAMOOB,3 and DAMOOB,5 from mean squared error (MSE) = {0.08, 0.10} and R2 = {0.25, 0.22} to MSE = {0.07, 0.07} and R2 = {0.36, 0.41}
Summary
Storms influence forest ecosystems at multiple levels. They are key factors for forest composition, structure, demography, growth and ecosystem processes [1,2,3]. 18.5 million m3 of damaged timber per year over the period 1950–2000 [4]. At least 65% of all forest storm damage is caused by winter storms associated with the passage of high-impact low pressure fronts over Europe during the months November to January [5]. Exceptional winter storms that impacted Central Europe during the past decades were “Wiebke”. With respect to the amount of damaged timber, storm Lothar, which passed Southwest Germany [9] and Switzerland [10]
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