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首页> 外文期刊>Polish Journal of Environmental Studies. >Using the Non-Parametric Classifier CART to Model Lebanon Cedar {Cedrus libani A. Rich) Distribution in a Mountain Mediterranean Forest District
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Using the Non-Parametric Classifier CART to Model Lebanon Cedar {Cedrus libani A. Rich) Distribution in a Mountain Mediterranean Forest District

机译:使用非参数分类器CART建模地中海山区森林中的黎巴嫩雪松(Cedrus libani A. Rich)分布

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This study was conducted to define indicator species of Lebanon cedar {Cedrus libani A. Rich) and to build its potential distribution model in the Yukarigokdere Forest District of Turkey's Mediterranean region. In the study, the data were collected from 119 sample plots. To define indicator species of Lebanon cedar, interspecific correlation analysis (ICA) was employed. The findings obtained from ICA showed that thermo-Mediterranean elements (Pistacia terebinthus subsp. palaestina, Quercus coccifera, and Styrax officinalis) are the most significant negative indicator species of Lebanon cedar, while Its most significant positive indicator plants are supra- and mountain-Mediterranean elements (Acer hyrcanum subsp. sphaeroccaryum, Berberis crataegiana, Amelanchier parviflora, Fraxinus ornus subsp. cilicica, and Sorbus umbellate). By using climatic and topographical data as explanatory variables, visual assessment of the potential distribution probability of Lebanon cedar based on classification and regression technique (CART) was performed. Ten-fold cross validation was run for selection of the optimal tree. The variables building the tree model were elevation, head index, annual precipitation, slope degree, landform category, and topographical position index. Among them, elevation was found to be the most significant factor on the distribution of Lebanon cedar.
机译:进行这项研究的目的是确定黎巴嫩雪松的指标物种(雪松libani A. Rich),并在土耳其地中海地区的Yukarigokdere森林区建立其潜在的分布模型。在这项研究中,数据是从119个样地中收集的。为了定义黎巴嫩雪松的指示剂种类,采用了种间相关分析(ICA)。从ICA获得的结果表明,热地中海元素(黄ista藜亚种palaestina,栎栎和拟南芥)是黎巴嫩雪松最显着的阴性指示物,而其最重要的阳性指示植物是地中海上和山地。元素(Acer hyrcanum sphaeroccaryum,Berberis crataegiana,Amelanchier parviflora,Fraxinus ornus cilicica和Sorbus umbellate)。通过使用气候和地形数据作为解释变量,基于分类和回归技术(CART)对黎巴嫩雪松的潜在分布概率进行了可视化评估。运行十倍交叉验证以选择最佳树。建立树模型的变量是海拔,海拔指数,年降水量,坡度,地形类别和地形位置指数。其中,海拔升高是影响黎巴嫩雪松分布的最重要因素。

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