意大利和乌克兰人们对林分特征的认知和偏好的比较。

O. Pelyukh, A. Paletto, L. Zahvoyska
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引用次数: 5

摘要

了解人们对林分特征的看法和偏好可以在短期内给森林管理者带来许多好处。本研究旨在确定和比较意大利Trentino省和乌克兰Rakhiv地区人们对林分特征的感知和偏好。选择这些地区作为研究区域主要有两个原因:它们都位于山区,当地社区对森林资源的依赖程度很高。数据是通过对当地居民样本进行问卷调查收集的。对收集到的数据进行统计分析,以突出与不同林分特征相关的首选林分类型。对比分析的结果证实了社会人口特征在塑造受访者偏好方面的重要性。结果表明,在这两个案例研究中,受访者更喜欢不同直径大小树木随机分布的混交林。然而,来自特伦蒂诺省的受访者更喜欢开放森林,而来自Rakhiv地区的受访者更喜欢封闭森林。本研究提高了人们对意大利和乌克兰不同林分特征偏好的认识水平。决策者(森林管理者和规划人员)可以利用这些信息来提高林分的娱乐吸引力。
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Comparison between people's perceptions and preferences towards forest stand characteristics in Italy and Ukraine.
Understanding people’s perceptions and preferences towards forest stand characteristics can bring many benefits to forest managers in the short term. This study aims to identify and compare people’s perception and preferences of forest stand characteristics in Trentino province (Italy) and Rakhiv region (Ukraine). These regions were chosen as study areas for two main reasons: both are in mountain areas and local communities are strictly dependent on the forest resource. Data were collected through a questionnaire administered to a sample of local people. The collected data were statistically analysed to highlight the preferred type of forests related to different stand characteristics. The results of comparative analysis confirmed the importance of socio-demographic characteristics in shaping respondents’ preferences. The results show that respondents in both case studies prefer mixed forests with a random distribution of trees with different diameter sizes. However, respondents from Trentino province prefer open forests, while respondents from Rakhiv region prefer closed one. The present study increased the level of knowledge about people's preferences in Italy and Ukraine for different forest stand characteristics. This information can be used by decision makers (forest managers and planners) to improve the recreational attractiveness of forest stands.
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来源期刊
Annals of Silvicultural Research
Annals of Silvicultural Research Agricultural and Biological Sciences-Forestry
CiteScore
2.70
自引率
0.00%
发文量
0
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