Abstract

Each year damage to forests caused by snow and wind causes high economic losses. In Sweden, approximately 4 million m(3) are damaged annually by snow and wind, roughly corresponding to a value of US$150 million, and in Europe, the damage amounts to hundreds of millions of US dollars each year. To help to reduce these losses, tools for risk assessment within forest management have been developed. Predictions were developed of the risk of damage from snow and wind to Scots pine (Pinus sylvestris L.), Norway spruce [Picea abies (L.) Karst.] and Birch (Betula spp. L.) plots using tree, stand, and site characteristics. The data were obtained from 6756 permanent sample plots within the Swedish National Forest Inventory, which were inventoried twice at five-year intervals between 1983 and 1992. input data for model development used measurements from the first inventory of tree characteristics for the largest sample tree, stand, and site data, and records of snow and wind damage from the second inventory. Models were developed for three different regions for pine- and spruce-dominated sites, while models for the whole country were developed for birch sites. In general the estimated proportion of damaged plots was highly overestimated (31.7%-56.2%), compared with the observed proportion of 3.4%-11.9%. The models for Norway spruce comprising tree, stand, and site data show the best predictability of damaged plots, with 60.6%-67.6% of plots correctly classified. It is concluded that the models developed can be used to detect sites with a high probability of damage from snow and wind, and thus be used as tools to reduce future damage and costs in practical forestry.

Keywords

birch; Norway spruce; risk assessment; risk management; Scots pine; silviculture

Published in

Environmental Management
1999, Volume: 24, number: 2, pages: 209-217
Publisher: SPRINGER VERLAG

SLU Authors

• Valinger, Erik

  • Department of Silviculture, Swedish University of Agricultural Sciences
    

• Fridman, Jonas

  • Department of Forest Ecology and Management, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Forest Science


Publication identifier

DOI: https://doi.org/10.1007/s002679900227

Permanent link to this page (URI)

https://res.slu.se/id/publ/41048