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Height-Diameter Relationships in Sweetgum (Liquidambar styraciflua)-Dominated Stands

机译:甘蔗(甜菜碱)主导林分的高度-直径关系

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This report presents height-diameter equations for five hardwood species commonly associated with sweetgum (Liquidambar styraciflua L.) stands within the Piedmont and Coastal Plain regions of Alabama, Georgia, and South Carolina. Mixed-effects regression and the Chapman-Richards function were used to fit height-diameter equations for each species. Two equations were developed for each species, a base model with diameter as a predictor and a covariate model that included diameter and measures of stand structure. Compared with the base model, a marginal improvement in fit was seen in covariate models that include stand basal area and/or basal area of trees larger than a subject tree. Models were evaluated using an independent data set, and standwise calibration was used to estimate random parameters for the evaluation stands. Calibration improved prediction of tree height for all species, and increasing the number of sample trees used in the calibration beyond three had a minimal effect on improving prediction. This study supports previous findings that height prediction improves as one moves from a diameter-based model to a locally calibrated covariate model.
机译:本报告介绍了五个常见的硬木树种的高度-直径方程,这些树种与阿拉巴马州,乔治亚州和南卡罗来纳州的皮埃蒙特和沿海平原地区的甜木(Liquidambar styraciflua L.)站在一起。使用混合效应回归和Chapman-Richards函数拟合每个物种的身高-直径方程。针对每个物种开发了两个方程式,一个以直径作为预测变量的基本模型,以及一个包含直径和林分结构度量的协变量模型。与基础模型相比,在协变量模型中拟合度略有提高,该协变量模型包括比主题树大的树木的基础面积和/或基础面积。使用独立的数据集评估模型,并使用标准校准来估计评估台架的随机参数。校准改善了所有物种的树高预测,并且将用于校准的样本树数量增加到三个以上,对改善预测影响很小。这项研究支持以前的发现,即随着从基于直径的模型向本地校准的协变量模型转变,高度预测会提高。

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