Poškodbe drevja zaradi abiotskih naravnih motenj na bukovih rastiščih v Sloveniji s poudarkom na snegolomih

IF 0.3 Q4 FORESTRY
Blanka Klinar, Matija Klopčič, Andrej Bončina
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引用次数: 1

Abstract

We studied snow damage to individual trees in beech stands in Slovenia. The analysis included 22,609 compartments with at least 10 % of European beech ( Fagus sylvatica ) in the total growing stock. In salvage harvesting due to snow and wind damage, conifers represented a higher proportion than deciduous species, yet their proportions were similar after ice damage. Mainly younger and middle-aged trees of 20–40 cm in dbh were damaged by heavy snow load. On a sample of 363 compartments, for which data on daily snow precipitation were obtained, a binary logistic regression model to predict the probability of snow damage occurrence was developed. The sum of snow cover in spring months, phytogeographical region, rockiness, slope inclination, and bedrock were statistically significant predictors; the key predictor was the sum of snow cover in spring months. The relatively high salvage felling in forests on beech sites can partly be explained by alterations in forests due to the admixture of Norway spruce ( Picea abies ), since beech is less susceptible to snow damage compared to spruce. To improve stand resist-ance, classical thinnings from above should be frequent and of lower intensity, or alternative types of crop tree situational thinning should be applied in younger and middle-aged even-aged stands.
斯洛文尼亚山毛榉林因非生物自然干扰对树木造成的损害,重点是雪锥
我们研究了斯洛文尼亚山毛榉林中积雪对单个树木的损害。该分析包括22,609个室,其中欧洲山毛榉(Fagus sylvatica)在总生长存量中至少占10%。在雪害和风害的救助采伐中,针叶树的比例高于落叶树种,而冰害后两者的比例基本相同。雪害主要发生在20 ~ 40 cm的幼树和中树。以363个单元为样本,利用逐日降雪数据,建立了预测雪害发生概率的二元logistic回归模型。春季积雪总量、植被地理区域、岩石度、坡度和基岩是具有统计学意义的预测因子;关键的预测因子是春季积雪总量。由于挪威云杉(Picea abies)的混合导致了森林的变化,因此山毛榉在山毛榉地的森林中相对较高的补救性砍伐可以部分解释,因为与云杉相比,山毛榉不太容易受到雪的损害。为了提高林分的抗逆性,从上面进行传统的疏林应该频繁和低强度,或者在年轻和中年甚至年龄的林分上采用其他类型的作物树木情况疏林。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
33.30%
发文量
2
审稿时长
10 weeks
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