Determination of relations between plant species diversity and productivity in Brutian pine stands

M. Negiz, Serkan Özdemir, Oğuzhan Erfidan, Alican Çıvğa, Ö. Şentürk
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Abstract

This study examines the relationship between Brutian pine productivity and plant species diversity, focusing on its potential as a valuable resource. Data was collected from 101 natural Brutian pine stands in Muğla and Antalya through inventory studies. Age and height values were recorded for three selected Brutian pine trees in each plot, along with plant species diversity using the Braun-Blanquet scale. Site index values were used to assign productivity scores between 1 and 5 for each plot. Diversity values were adjusted to a scale of 1 to 9 according to Westhoff and Maarel (1973) to calculate alpha diversity indices (Shannon and Simpson) using BİÇEB software. Environmental variables such as elevation, slope, radiation index, annual mean temperature, and annual precipitation were also collected for further analysis. The Kolmogorov-Smirnov normality test was first applied to the data matrix. Since it was determined that the normality assumption was not met (p<0.05), the Kruskal-Wallis test, which is a non-parametric method, was used to determine whether there is a significant difference between the diversity values for the site index groups. Results indicated a statistically significant difference (p<0.05) in diversity values among these groups. Then, diversity values and environmental variables were correlated using principal component analysis method (PCA). At the same time, site index groups were also included in the PCA as class data. As a result, it was revealed that Shannon and Simpson diversity values have a negative relationship with elevation and slope and a positive relationship with total annual precipitation.
确定布鲁特松林中植物物种多样性与生产力之间的关系
本研究探讨了布鲁提亚松生产力与植物物种多样性之间的关系,重点关注其作为宝贵资源的潜力。通过清查研究,从穆拉和安塔利亚的 101 个天然布鲁提松林收集了数据。记录了每个地块中三棵选定的布鲁特松树的树龄和高度值,并使用布劳恩-布兰凯量表记录了植物物种多样性。现场指数值用于为每个地块分配 1 到 5 分的生产力分数。多样性值根据 Westhoff 和 Maarel(1973 年)的标准调整为 1 到 9,以使用 BİÇEB 软件计算阿尔法多样性指数(香农和辛普森)。此外,还收集了海拔、坡度、辐射指数、年平均气温和年降水量等环境变量,以作进一步分析。首先对数据矩阵进行了 Kolmogorov-Smirnov 正态性检验。由于确定不符合正态性假设(P<0.05),因此采用了非参数方法 Kruskal-Wallis 检验,以确定各地点指数组的多样性值之间是否存在显著差异。结果表明,各组之间的多样性值差异有统计学意义(P<0.05)。然后,利用主成分分析法(PCA)对多样性值和环境变量进行了相关分析。同时,地点指数组也作为类数据被纳入 PCA。结果表明,香农和辛普森多样性值与海拔和坡度呈负相关,与年降水量呈正相关。
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