Browsing by Subject "snow damage"

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  • Suvanto, Susanne; Henttonen, Helena M.; Nöjd, Pekka; Mäkinen, Harri (2018)
    Storms cause major forest disturbances in Europe. The aim of this study was to model tree-level storm damage probability based on the properties of a tree and its environment and to examine whether fine-scale topographic information is connected to the damage probability. We used data documenting effects of two autumn storms on over 17 000 trees on permanent Finnish National Forest Inventory plots. The first storm was associated with wet snowfall that damaged trees, while exceptionally strong winds and gusts characterized the second storm. During the storms, soils were unfrozen and deciduous trees were without leaves. Generalized linear mixed models were used to study how topographical variables calculated from digital elevation models (DEM) with resolutions of 2 and 10 m (TOPO2 and TOPO10, respectively) were related to damage probability, in addition to variable groups for tree (TREE) and stand (STAND) characteristics. We compared models containing different variable groups with Akaike information criteria. The best model contained the variable groups TREE, STAND, and TOPO2. Increase in slope steepness calculated from the high-resolution DEM decreased tree-level damage probability significantly in the model. This suggests that the local topography affects the tree-level damage probability and that high-resolution topographical data improves the tree-level damage probability models.
  • Lehtonen, Ilari (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 133
    The aim of this work was to study the climate change impact on two specific abiotic risks affecting forests in Finland: fires and heavy snow loads. Approximately 1000 forest fires occur annually in Finland, but thanks to effective fire suppression, the average size of fires is only about 0.5 ha. Occasionally, heavy snow loading causes forest damage, which reduces stand quality in boreal forests experiencing cold winters. In Finnish forests, snow damage occurs most commonly in the eastern and northern parts of the country. The basic tools used in this work to evaluate the climate change impact were climate models. In addition, observational weather data and fire statistics were used. In evaluating the forest fire risk, the Canadian Fire Weather Index (FWI) system was used. Snow load amounts were estimated mainly by applying a snow load model developed at the Finnish Meteorological Institute (FMI). The results indicate that forest fire risk will most likely increase in the future due to increasing temperature and enhanced evaporation. However, there is large uncertainty regarding the rate of change, which originates from the differences between climate model responses to the same radiative forcing. Moreover, an increase in forest fire risk will at the same time increase the risk of onflagrations. Crown snow loads were projected to become heavier in northern Finland and in the regions of Kainuu and North Karelia next to the Russian border. In southern and western Finland the risk of snow damage is expected to decrease. The largest decrease in the risk is projected to occur in coastal areas. In the areas expected to experience increased risk of snow damage, conditions favouring oth heavy wet snow loading and rime accretion were predicted to become more common. The results of this work can be utilized when considering climatically-driven risks in forest management.