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Estimating the probability of survival of individual shortleaf pine (Pinus echinata Mill.) trees.

机译:估计单个短叶松树(Pinus echinata Mill。)树木存活的可能性。

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摘要

An individual tree survival model was developed for shortleaf pine ( Pinus echinata Mill.) trees. Prediction of the probability of survival of an individual tree is essential when considering growth and yield of a stand. Data for this study were from more than 200 permanently established plots on even-aged natural shortleaf pine stands that were located in the Ozark and Ouachita National Forests. Plots were established during the period of 1985-1987. Plots have been remeasured every 4, 5 or 6 years, and individual tree survival or mortality was recorded at each measurement. These plots were selected to represent a range of ages, densities and site qualities. Logistic regression was used to find the best sets of significant predictor variables in which the response variable was a binary variable `1' for the survival tree and `0' for the mortality tree. Significant variables found in predicting the survival were mid-period basal area per acre (Mid-BA), inverse of ratio of quadratic mean diameter to diameter at breast height (DBH) (DRINV), their interaction and square of DBH. Parameters of the logistic equation were estimated using iteratively re-weighted nonlinear regression. A nonlinear mixed-effects approach was also applied to investigate the plot level effect on the model. Model performance was evaluated using Chi-square goodness-of-fit test, and it was found that the model worked better while estimating the parameters using iteratively reweighted non linear regression than with the nonlinear mixed model. This individual tree survival model can be used to predict the annual survival rate of individual trees of even-aged shortleaf pine forests located in Ozark and Ouachita National Forests and in the surrounding regions.
机译:针对短叶松(Pinus echinata Mill。)树木开发了单独的树木生存模型。在考虑林分的生长和产量时,预测单个树木存活的可能性至关重要。这项研究的数据来自位于奥索卡克(Ozark)和瓦希塔国家森林(Wuachita National Forests)的200个永久建立的均匀老化的短叶天然松林地块。地块是在1985-1987年期间建立的。每4、5或6年重新测量一次图,并在每次测量时记录单个树木的存活率或死亡率。选择这些图以代表年龄,密度和站点质量的范围。 Logistic回归用于找到最佳的重要预测变量集,其中响应变量对于生存树是二进制变量“ 1”,对于死亡率树是二进制变量“ 0”。在预测存活率时发现的重要变量是每英亩的中期基础面积(Mid-BA),二次平均直径与乳房高度直径(DBH)的比值(DRINV)的倒数,它们的相互作用和DBH的平方。使用迭代重新加权非线性回归估计逻辑方程的参数。还使用非线性混合效应方法来研究情节水平对模型的影响。使用卡方拟合优度检验评估模型性能,发现与非线性混合模型相比,使用迭代加权加权非线性回归模型在估计参数时效果更好。该个体树生存模型可用于预测位于Ozark和Ouachita国家森林以及周边地区的均匀年龄的短叶松树林的个体树的年生存率。

著录项

  • 作者

    Shrestha, Sudip.;

  • 作者单位

    Oklahoma State University.;

  • 授予单位 Oklahoma State University.;
  • 学科 Statistics.;Natural Resource Management.
  • 学位 M.S.
  • 年度 2010
  • 页码 69 p.
  • 总页数 69
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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