摘要
森林碳储量是评价森林生态系统生态效益的重要指标,准确估计立木各器官(树干、树枝、树叶和树根)含碳量是其基础。基于黑龙江省44株人工红松各器官生物量和含碳量的实测数据,采用非线性联立方程组构建了相容性立木生物量和含碳量模型,比较了两种方法(直接法和间接法)估计红松立木含碳量的精度。直接法是通过构建各器官相容性含碳量模型,直接预估立木各器官含碳量。间接法是由各器官相容性生物量模型,结合3种形式的含碳率(平均含碳率0.5、林木实测平均含碳率,各器官实测平均含碳率)来预估树木各器官含碳量。研究结果表明:相容性生物量和含碳量模型的相关指数R2为0.76—0.99,模型的拟合效率(EF)为0.80—0.98。直接法中树干、树枝、树叶、树根和总量的含碳量预估精度分别为91.03%、80.02%、70.24%、87.10%、93.08%;间接法中采用平均含碳率0.5的预估精度与直接法相比,各器官及总量分别下降1.39%、1.5%、0.13%、1.09%和2.2%,而采用另外两种形式的含碳率其预估精度降幅在0.3%以内。依据文中推导的相对误差积累公式可知,间接法的预估精度主要与Ci%/珔C%(Ci%为单木各器官含碳率,珔C%为实测平均含碳率)有关。显然,直接法是预估红松立木含碳量的最佳方法。通常使用的碳含量转换系数0.5与实测含碳率有明显差异,因此间接法中采用0.5的含碳率其预估精度最低,而使用各器官实测的含碳率可以明显提高预估精度。
Forest carbon stock is an important indicator for evaluating the ecological benefits of forest ecosystem. Thus,accurately estimating the carbon stocks for the different components（ i.e. stem,branches,foliages,and roots） of individual trees is essential and necessary. In this study,a total of 44 Korean pine（ Pinus koraiensis） trees were sampled from the plantations in Heilongjiang province, China. The biomass and carbon stocks data were collected for different tree components. Based on the theory of non-linear simultaneous equations,the compatible models of the biomass and carbon stocks were developed for the whole tree and each tree component（ i.e. stem,branches,foliages,and roots） by using the proc model procedure of SAS9.22 software to estimate the model coefficients. The prediction accuracy of two methods（ i.e.,direct and indirect methods） for predicting the Korean pine carbon stocks was compared. The direct method directly predicted the carbon stocks of the tree components using the developed compatible models of carbon stocks. The indirect method predicted the carbon stocks in two steps：（ 1） predicting the biomass of the tree components using the developed compatible models of biomass,and（ 2） multiplying the estimated biomass by carbon content percentages to obtain the carbon stocks. Three kinds of carbon content percentages were used（ a） the carbon content conversion factor 0.5 commonlyused in the literature over the past decades;（ b） the average carbon content percentage of individual trees measured from the sampled trees; and（ c） the average carbon percentages of tree components measured from the sampled trees. The results indicated that the coefficients of determination（ R2） of both compatible biomass and carbon stocks models ranged 0.76—0. 99,and the modeling efficiency（ EF） of the two models were 0.80—0.98. The prediction accuracy of carbon stocks by the direct method was 91.03% for stem,70. 24% for foliages,80. 02% for branches,87. 10% for roots,and 93. 08% for total,respectively. In comparison,the prediction accuracy of the indirect method using the common carbon content conversion factor 0.5 decreased 1.39% for stem,0.13% for foliages,1.5% for branches,1.09% for roots,and 2.2% for total amount,respectively. On the other hand,the indirect method using the measured carbon content percentages reduced the prediction accuracy within 0. 3% for each tree component and the total. We also investigated the error sources for predicting carbon stocks and found that the prediction accuracy was mainly dependent on the factor of Ci% / 珔C%（ where Ci%represents the carbon content percentage of tree components and 珔C% is the average carbon content percentage of individual trees）. It was evident that the direct method was the best for predicting the tree carbon stocks of Korean pine. The commonly used carbon content conversion factor 0.5 was significantly different from the measured carbon content percentages. Thus,the indirect method using the factor 0.5 performed poorly for predicting the carbon stocks,while using the measured carbon content percentages of tree components as the indirect method would greatly improve the prediction accuracy. The results of this study will provide basic models and direct method to predict carbon stocks of stand or large scale forest for Korean pine plantation.
出处
《生态学报》
CAS
CSCD
北大核心
2014年第24期7365-7375,共11页
Acta Ecologica Sinica
基金
林业公益性行业科研专项(201204320)
长江学者和创新团队发展计划资助(IRT1054)
关键词
红松
生物量
含碳量
非线性联立方程组
相容性模型
预估精度
Korean pine（Pinus koraiensis）
biomass
carbon stocks
non-linear simultaneous equations
compatible model
prediction accuracy
