Vulnerability to wind damage in managed landscapes of the coastal Pacific Northwest

Wilson, Jeremy S.

doi:10.1016/j.foreco.2003.12.014

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…Dominant stand height and removal characteristics were selected as predictors in the four submodels of this modeling step. In contrast, other authors detected that catastrophic storm damage-similar to the total damage in our study-may be primarily driven by the wind field (Maccurrach 1991;Quine 1995;Wilson 2004). Their argumentation is based on the hypothesis that, on the one hand, endemic wind storms with medium wind speed selectively and partially damage forest stands and trees according to their stability properties.…”

Section: Discussioncontrasting

confidence: 65%

How does silviculture affect storm damage in forests of south-western Germany? Results from empirical modeling based on long-term observations

et al. 2010

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Storms represent the most important disturbance factor in forests of Central Europe. Using data from long-term growth and yield experiments in Baden-Wuerttemberg (south-western Germany), which permit separation of storm damage from other causes of mortality for individual trees, we investigated the influence of soil, site, forest stand, and tree parameters on storm damage, especially focusing on the influence of silvicultural interventions. For this purpose, a four-step modeling approach was applied in order to extract the main risk factors for (1) the general stand-level occurrence of storm damage, (2) the occurrence of total stand damage, and (3) partial storm damage within stands. The estimated stand-level probability of storm damage obtained in step 3 was then offset in order to describe the damage potential for the individual trees within each partially damaged stand (4). Generalized linear mixed models were applied. Our results indicate that tree species and stand height are the most important storm risk factors, also for characterizing the long-term storm risk. Additionally, data on past timber removals and selective thinnings appear more important for explaining storm damage predisposition than for example stand density, soil and site conditions or topographic variables.When quantified with a weighting method (summarizing the relative weight of single predictors or groups of predictors), removals could explain up to 20% of storm risk. The stepwise modeling approach proved an important methodological feature of the analysis, since it enabled consideration of the large number of observations without damage (''zero inflation'') in a statistically correct way. These results form a reliable basis for quantifying forest management's direct impact on the risk of storm damage.

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Section: Discussioncontrasting

confidence: 65%

How does silviculture affect storm damage in forests of south-western Germany? Results from empirical modeling based on long-term observations

et al. 2010

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“…More frequent extreme meteorological events will leave trees chronically stressed [28] and possibly more vulnerable to secondary damages [14,36] like those caused by bark beetles [17].…”

Section: Introductionmentioning

confidence: 99%

Heat and drought 2003 in Europe: a climate synthesis

et al. 2006

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“…One reason might be that by far the largest proportion of highest GS stat,Dec -values occurs at highest elevations in the southern Black Forest around the Feldberg. Therefore, decreasing proportions of storm-damaged timber at these elevations might be due to acclimative tree growth in response to recurrently high wind loading that increases tree stability against excessive wind exposure [20,[51][52][53][54]. Another reason might be the limited predictive accuracy of the applied gust speed model at elevations higher than 1200 m a.s.l.…”

Section: /23mentioning

confidence: 99%

The Role of Highly-Resolved Gust Speed in Simulations of Storm Damage in Forests at the Landscape Scale: A Case Study from Southwest Germany

et al. 2016

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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 mˆ50 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.

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Vulnerability to wind damage in managed landscapes of the coastal Pacific Northwest

Cited by 8 publications

References 28 publications

How does silviculture affect storm damage in forests of south-western Germany? Results from empirical modeling based on long-term observations

How does silviculture affect storm damage in forests of south-western Germany? Results from empirical modeling based on long-term observations

Heat and drought 2003 in Europe: a climate synthesis

The Role of Highly-Resolved Gust Speed in Simulations of Storm Damage in Forests at the Landscape Scale: A Case Study from Southwest Germany

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