Probability of recent bark stripping damage by red deer (Cervus elaphus) on Norway spruce (Picea abies) in a low mountain range in Germany – a preliminary analysis
Kiffner C., Rössiger E., Trisl O., Schulz R., Rühe F. (2008). Probability of recent bark stripping damage by red deer (Cervus elaphus) on Norway spruce (Picea abies) in a low mountain range in Germany – a preliminary analysis. Silva Fennica vol. 42 no. 1 article id 269. https://doi.org/10.14214/sf.269
Abstract
Red deer (Cervus elaphus) can cause considerable damage to forest stands by bark stripping. Here, we examined the probability of bark stripping of susceptible Norway spruce (Picea abies) during winter in relation to local environmental characteristics in the western Harz Mountains, Lower Saxony, Germany. We present the results of a multiple logistic regression model for recent bark stripping damage by red deer which we developed from two systematic cluster sampling inventories after two winter periods along with associated meteorological data and records of bagged deer. Our model suggests that the risk of bark stripping increased significantly (P 0.05) with rising slope angle, cumulating snow depth and increasing index values of red deer population density. Spruces growing in closed forest stands were debarked at a higher probability than spruces located close to forest edges. Further on, spruce stands on eastern slopes had a lower probability of bark damage than spruce stands on northern slopes. Other tested variables (altitude, length of daily solar irradiation, duration of snow cover, age of spruce stand within the age range of 16–50 years) had no significant effect on the probability of new bark stripping. We conclude that red deer in the western Harz Mountains seem to use bark as food resource at preferred locations and in times of low food availability. To improve fit and predictive power of bark stripping models we recommend including stand characteristics. We propose to reduce the population size of red deer in order to diminish bark stripping damages to an economically acceptable level.
Keywords
forest management;
logistic regression;
wildlife management
Received 4 June 2007 Accepted 16 October 2007 Published 31 December 2008
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