• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>other >Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province China
【2h】

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province China

机译：福建省杉木杉木人工林碳含量的兼容模型

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D2H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D2H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well.
机译：我们试图建立中国东南部福建省杉木（Cunninghamia lanceolata（Lamb。）Hook。）人工林的兼容碳含量模型。通常，兼容性要求组件之和等于整棵树，这意味着从组件方程式计算得出的百分比之和应等于100％。因此，我们使用了多种方法来模拟树干，树枝，树叶，根和整个树木中的碳含量。这些方法包括（i）单一最佳拟合（SOF），（ii）比例非线性调整（NAP）和（iii）非线性看似无关的回归（NSUR）。这些方法与与乳房高度（D）和树高（H）的直径有关的变量结合使用，例如D，D 2 H，DH和D＆H（其中D＆H表示双变量中的两个独立变量）模型）。测试了幂函数，指数函数和多项式函数，并提出了新的通用函数模型。采用加权最小二乘回归模型消除异方差。通过使用平均残差，残差方差，均方误差和确定系数来评估模型性能。结果表明，具有二维变量（DH，D 2 H和D＆H）的模型始终优于具有单个变量（D）的模型。发现D＆H变量组合是最有用的预测指标。在所有方法中，SOF可以分别建立一个最佳模型，但是由于现有的不兼容性，估计结果存在偏差，而NAP和NSUR可以确保预测的兼容性。同时，我们发现新的通用模型比其他模型具有更好的准确性。总之，我们建议使用新的通用模型估算杉木的碳含量，并考虑其他植被类型的碳含量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号