Modelling of windstorm damage on Kastamonu forests using maximum entropy methodology
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Abstract (EN)
Since climatic anomalies create conditions to which living organisms are not accustomed, unexpected results are likely to be expected. One such anomaly, excessive wind, when experienced unexpectedly, constitute serious damage in tree(s) as well as in stands. The level of the damage changes from uprooting to breakage and lean. When the other meteorological factors contribute further, the results can become catastrophic. The coniferous stands are more susceptible to strong winds. The slyvicultural practices may exacerbates the damage further because the continuity of the stand dynamics is broken as the management strategies are applied. Since there is no way of eliminating or altering the meteorological phenomena's, it will be best to understand the factors affecting the damage, so decision makers will have a upper hand in shaping the management strategies. The extend of the damage can be reduced, employing the precautions. Both coniferous and deciduous stand might face such destruction during any stage of their development cycle. In this particular study, the environmental factors affecting the outcome of fierce wing occurred on the 15 March 2013 were analyzed. The results showed, the site index, precipitation and the stand characteristics were the important factors, deteriorating the devastation. The site class I was the hardest hit according to the environmental factor evaluation. Precipitation was found significant because heavy precipitation consecutively occurred three days prior to the damage, saturated the soil weakening the bond trees had with the soil. Variations including coniferous tree species were also the ones affected heavily from the storm damage. It was concluded that it would be best not to categorize the damage types and run such models depending upon the spatial distribution of similar damages.
Author
Pakize Torun
How to Cite
Pakize Torun (Master Thesis). Modelling of windstorm damage on Kastamonu forests using maximum entropy methodology, 2018, Kastamonu University.
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