Faculty of Forestry, Forest Yield and Biometry Department, Istanbul University- Cerrahpaşa, Bahçeköy/Sarıyer, İstanbul, Turkey.
Environ Monit Assess. 2021 May 25;193(6):357. doi: 10.1007/s10661-021-09128-5.
In this study, the basal area increment models were developed to be both age dependent and independent with a stepwise multiple regression analysis for coppice-originated pure sessile oak stands in the Marmara region, which is located in north-western Turkey. Data was obtained from a total of 73 sample trees, which were sampled from coppice-originated pure sessile oak stands over different growth periods and in different site conditions. The most suitable competition variable was determined by examining the correlations between the 24 competition index values and calculated using different approaches and the basal area increment. The individual tree basal area increment models were obtained as functions of tree size, competition, age, and site characteristics. The most important variables that affect the basal area increment in the age-dependent model were the diameter at breast height (DBH) (36.1%), competition index (26.4%), and age (10%). For the age-independent model, the variables are the competition index (32.6%), DBH (30.3%), and the site index (3%), according to the relative importance values. The age-dependent model explained the increased variation of 10% and predicted a 13% decrease in error in the basal area increment than the age-independent model.
本研究采用逐步多元回归分析方法,针对土耳其西北部马尔马拉地区萌生的栓皮栎纯林,建立了既依赖年龄又独立于年龄的底面积增量模型。该数据来自于 73 株样本树,这些样本树分别取自不同生长时期和不同立地条件的萌生的栓皮栎纯林。通过检验 24 个竞争指数值与使用不同方法计算的底面积增量之间的相关性,确定了最合适的竞争变量。单株树木的底面积增量模型是作为树木大小、竞争、年龄和立地特征的函数来获得的。在依赖年龄的模型中,影响底面积增量的最重要变量是胸径(DBH)(36.1%)、竞争指数(26.4%)和年龄(10%)。对于独立于年龄的模型,根据相对重要性值,变量是竞争指数(32.6%)、DBH(30.3%)和林分指数(3%)。依赖年龄的模型解释了 10%的增量变化,并预测了底面积增量的误差减少了 13%,而独立于年龄的模型则没有。