【作者】 龙滕周；

【导师】 孟永庆；

【作者基本信息】 中国林业科学研究院 ， 森林培育， 2008， 硕士

【摘要】 本文以Richards等6种理论生长方程为基础,利用14年生的不同栽培密度尾巨桉(E. urophylla×E. grandis)人工林固定样地多次林分生长量调查资料,采用Marquardt叠代法对林分的树高、胸径和蓄积量的平均生长过程进行了拟合,同时构建并分析了不同栽培密度林分在62个月、110个月和161个月时的直径累积结构方程。以建立的林分蓄积量生长方程为基础,对比分析了不同栽培密度处理下林分的年均蓄积生长量和连年蓄积生长量的变化规律,为尾巨桉人工林的合理经营提供了一定的参考依据。得出的主要结论如下:1.不同林龄的尾巨桉人工林林分的平均树高、平均胸径和平均蓄积量在不同栽培密度处理间均表现出一定的差异。总的趋势是平均树高和平均胸径在不同栽培密度处理间的差异随林龄的增大而增大,平均蓄积生长量在不同栽培密度处理间的差异主要表现在林分8年生以前,以后,平均蓄积量在不同栽培密度处理间的差异开始不明显。2. Marquardt叠代法可用于对理论生长方程参数的拟合。理论生长方程对林分生长过程的模拟表现出了较高模拟效果(相关系数均在0.95以上)。总的来看,Korf方程对林分树高、胸径和蓄积量平均生长过程的模拟精度最高,Richards方程次之;理论生长方程对林分树高和胸径平均生长过程的模拟精度均随栽培密度的增大而增加,对林分平均蓄积量生长过程的模拟精度在不同栽培密度间没有明显变化;各理论方程对林分生长中期(约50～100个月)的模拟精度高于前期(约0～49个月)和后期(约101～161个月)。3.理论生长方程拟合所得的平均树高、平均胸径的理论最大值随栽培密度的减小而增大,林分平均蓄积量的理论最大值在不同栽培密度间则没有表现出明显的差异;平均树高的最大瞬时增长速率随栽培密度的增大而增大,平均胸径的最大瞬时增长速率则随栽培密度的增大而减小,平均蓄积量的最大瞬时增长速率在不同栽培密度间没有表现出规律性的变化;高栽培密度林分具有较高的平均树高生长速率,但持续的时间相对较短;低栽培密度林分平均树高生长速率相对较低,但持续的时间较长。4. Weibull方程对林分直径累积结构的模拟精度最高,Richards方程和Logistic方程依次次之;各理论方程对林分直径累积结构的模拟精度均表现出随栽培密度的增大而升高的趋势;883株/ha和667株/ha两种栽培密度下的林分径阶结构呈现整体跃迁。5.基于Korf方程拟合得出的林分平均蓄积量生长模型,计算得出不同栽培密度林分的年均蓄积生长量和连年蓄积生长量,并确定了各栽培密度林分的数量成熟龄。通过分析,林分的数量成熟龄随栽培密度的增加而提前,最大栽培密度林分(2222株/ha)的数量成熟龄为6年左右,最低栽培密度林分(667株/ha)则需10年左右。6.栽培密度为2222株/ha,1667株/ha,1250株/ha的林分适于作为短周期的纸浆材或者旋切板材人工林经营,栽培密度为883株/ha和667株/ha的林分可用于生产大径级的锯材产品。研究认为,最优栽培模式是采用较高的初植密度(1667株/ha以上),在林分经营的过程中实施间伐。更多还原

【Abstract】 Stand growth processes on average height, average diameter at breast height (DBH) and average stand volume of Eucalyptus urophylla×E.grandis plantation with 6 spacing treatments aged at14-year-old were represented with 6 theoretic growth equations (Korf, Logistic, Richards, Schumacher and Weibull). Levenberg-Marquardt iteration method was used to estimate the parameters of equations and achieved a good precision. Stand cumulative diameter distribution equations at the 62nd month, 110th month and 161st month were represented with three theoretic growth equations (Logistic, Richards and Weibull). Several suggestions on the plantation management were proposed. Conclusions are followed:1. There were differences in average height of stand trees and DBH among 6 treatments at the same age. With the stand growth, the differences among each treatment became more significant. The differences of stand volume among each treatment only presented before 8 years old. And then, there were not significant differences of stand volume among 6 spacing treatments.2. Levenberg-Marquardt iteration method could be adopted to estimate the parameters of the theoretic growth equations precisely and each theoretic growth equation fit the growth process of stands with high precision and correlation. The coefficient of determination of each equation was more than 0.95. In total, Korf equation and Richards equation were much better than the other theoretic growth equations. To fit the average height and DBH growth process of dense stands, the precisions of each equation were much higher than sparser ones. The similarity trends did not present when modeled the stand volume of the same object. The mean residual of each equation aged from 50 to 100 month was smaller than younger and elder ones.3. The theoretic maximums of height and DBH of sparse stands estimated with the theoretic equations were higher than denser ones. But, there were not significant differences of the theoretic maximum of stand volume estimated with the theoretic equations among 6 spacing treatments. With the planting density increase, the intrinsic rate of increase of height growth equations became bigger, the intrinsic rate of increase of DBH growth equations become smaller, and significant differences of intrinsic rate of increase of stand volume growth equations were not presented. The rates of increment of tree height of denser stands were much higher, but lasting time was short.4. To represent the stand cumulative diameter distribution, the modeling precision of Weibull equation was the highest, Richards equation and Logistic equation were lower, respectively. The precisions of cumulative diameter distribution equations of denser stands were higher than the sparser ones. The DBH classes of stands with 883 trees/ha and 667 trees/ha transferred holistically, the others were not.5. Age of quantitative maturity of every treatment stands were estimated. It showed that the ages of quantitative maturity were delayed with the planting density increase. The age of quantitative maturity of the densest stand with 2222 trees/ha was 6 years and the sparest stands (667 trees/ha) would be 10 years.6. Stands with 2222 trees/ha, 1667trees/ha and 1250 trees/ha are reasonable for production of pulp and veneer. Stands with 883 trees/ha and 667 trees/ha might be for sawtimber production. It is much more economy to establish plantation with initial density of more than 1667 trees/ha, and thinning should be made.更多还原