共查询到20条相似文献,搜索用时 62 毫秒
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《内蒙古林业调查设计》2015,(2)
文章通过对大兴安岭林区兴安落叶松生物量的测定,根据各样本的鲜重和含水率计算出样本各部分(干、根、枝、叶)的绝干重(生物量)和总生物量。通过对回归方程的检验,兴安落叶松单株生物量及各器官生物量均与林木的径阶呈显著的相关性。 相似文献
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兴安落叶松林风景资源十分丰富,美学价值很高。该文从兴安落叶松林的形态、色彩、声音、嗅味等几个方面对其进行了美学因素分析,旨在帮助人们认识兴安落叶松林的美学资源,为开发兴安落叶松林的旅游资源奠定基础。 相似文献
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立木度与郁闭度相比具有更准确的理论概念和数量化标准 ,在森林经理调查和营林生产中更具有指导意义 ,但目前在我国的使用仍属空白。文章根据其基本理论研制了兴安落叶松林立木度表 ,为引进推广立木度表做舆论先导和引荐作用。 相似文献
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兴安落叶松“老头林”经营利用的探讨 总被引:3,自引:0,他引:3
兴安落叶松“老头林”,是伊勒呼里山北坡寒温带连续冻土区常见的一种低产林分。林分主要分布在沟谷的水湿沼泽地和平缓山脊,坡地薄土层立地条件类型中。林分的主要特征为:林龄大(200年左 相似文献
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石塘—兴安落叶松林在几乎没有土壤的条件下,能够生长繁衍,一旦群落遭到破坏,是难以恢复的。通过分析石塘—兴安落叶松林的生长过程,发现其生长规律,为保护石塘—兴安落叶松林生态群落提供依据。 相似文献
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利用兴安落叶松解析木数据,比较了树干去皮直径预测的3种类型模型:Grosenbaugh的比率方程式、回归模型和削度方程。Grosenbaugh的比率方程式有很大的灵活性,没有参数不需要模型拟合。总体评价和模型分段比较表明,回归模型有较小的预测误差,尤其是Cao and Pepper提出的含有带皮直径、树高、相对树高、胸径处的带皮直径和去皮直径变量的模型。由于削度模型不含有带皮直径变量,因此产生较大的去皮直径预测误差。不同类型的模型在森林经营过程中都有一定的适应性。 相似文献
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以黑龙江省七台河市林业局金沙林场9株人工落叶松2 790个样品数据为例,选择6个常用方程进行非线性回归分析,把拟合精度最高的修正Logistic模型作为微纤丝角基础模型y=b1/[1+ exp(b2x)]+b3,然后,利用S-PLUS软件中的NLME过程,拟合非线性微纤丝角模型.采用AIC、BIC、对数似然值和似然比检验等模型评价统计指标对不同模型的精度进行比较分析.结果表明:当对微纤丝角-年龄关系进行拟合时,b1,b2,b3同时作为混合参数时模型拟合效果最好.把相关性结构包括复合对称结构(CS)、一阶自回归结构AR(1)、一阶移动平均结构MA(1)及一阶自回归与移动平均结构[ARMA(1,1)]加入到微纤丝角最优混合模型中,一阶自回归与移动平均模型[ ARMA(1,1)]显著提高了微纤丝角混合模型的拟合精度.模型检验结果表明:混合模型通过校正随机参数值能提高模型的预测精度.因此,混合模型在应用上不仅能反映总体微纤丝角预测,而且能通过方差协方差结构和误差相关性结构校正随机参数来反映个体微纤丝角差异. 相似文献
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In this study,the sample data was based on 2 790 samples of 9 trees from dahurian larch (Larix gmelinii) plantations located in Qitaihe Forest Bureau in Heilongjiang Province.The modified Logistic model y = b1 /[1 + exp(b2 x)]+ b3 was selected to modeling microfibril angle from six models based on nonlinear regression.Then,the logistic model was fitted using nonlinear mixed-effect modeling approach based on NLME of S-PLUS software.Evaluation statistics,such as AIC,BIC, Log Likelihood and Likelihood ratio test were used for model comparisons.The results showed that the Logistic model with parameters b1,b2,b3 as mixed effects showed the best performance.Correlation structures included compound-symmetry structure (CS),first-order autoregressive correlation structure AR(1),moving average correlation structure MA(1) and autoregressive-moving average correlation structure[ARMA(1,1)]were incorprated into the best microfibril angle mixed model.[ARMA(1,1)]significantly improved the precision of mixed model.Validation confirmed that the mixed model with calibration of random parameters could provide more accurate and precise prediction.Therefore,the application of mixed model not only showed the mean trends of microfibril angle,but also showed the individual difference based on variance-covariance structure and correlation structure. 相似文献
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In this study,the sample data was based on 2 190 branch length and angle samples of 30 trees from dahurian larch(Larix gmeiinii) plantations located in Wuying Forest Bureau in Heilongjiang Province.The stepwise regression techniques were used to develop branch length and branch angle models:BL= b1 + b2 DINC + b3 DINC2 + b4 DBH·DINC2,BA = b1 + b2 DINC + b3 DINC2 + b4 DBH·DINC.Then,the developed models were fitted using linear mixed-effects modeling approach based on LME procedure of S-PLUS software.Evaluation statistics,such as AIC,BIC, Log Likelihood and Likelihood ratio test were used for model comparisons.The results showed that the branch length and branch angle models with parameters b1,b2,b3 as mixed effects showed the best performance.Exponential and power functions were incorporated into mixed branch length and branch angle model.The addition of the exponential and power functions significantly improved the mixed-effects model.The plots of standardized residuals indicated that the mixed-effect model with exponential and power functions showed more homogeneous residual variance than the mixed-effects model.Validation confirmed that the mixed model with calibration of random parameters could provide more accurate and precise prediction.Therefore,the application of mixed model not only showed the mean trends of branch length and branch angle,but also showed the individual difference based on variance-covariance structure. 相似文献
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基于2层次线性混合模型的落叶松木材密度模拟 总被引:1,自引:0,他引:1
以黑龙江省七台河市林业局金沙林场9株人工落叶松432个样品密度数据为例,利用逐步回归技术构建落叶松木材密度模型:WD=β1+β2RN+β3RN2+β4h。利用S-PLUS软件中的LME过程,分别考虑单水平和多水平效应,拟合线性木材密度混合效应模型。结果表明:基于单水平和多水平效应的混合模型拟合精度高于传统的基本模型,并且考虑单水平树高效应和2层次效应时的混合模型精度高于考虑单水平样木效应影响的混合模型。模型检验结果表明:混合效应模型不但能反映总体平均木材密度变化趋势,还能反映分组之间的差异。 相似文献
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