中南林业科技大学学报

江西省杉木林碳储量模型研建

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毛旭鹏 ¹ , 田立新 ¹ , 陆禹 ² , 叶道碧 ³ , 臧颢 ⁴

中南林业科技大学学报 | 林学 2026,46(5): 48-58

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中南林业科技大学学报 |林学 2026 , 46 (5) : 48 -58

江西省杉木林碳储量模型研建

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毛旭鹏¹, 田立新¹, 陆禹², 叶道碧³, 臧颢⁴

作者信息

^1.江西省林业资源监测中心，江西　南昌　330046

^2.国家林业和草原局中南调查规划院，湖南　长沙　410014

^3.江西省国土空间调查规划研究院，江西　南昌　330025

^4.江西农业大学　林学院，江西　南昌　330045

通讯作者:

臧颢（b12345abba@163.com），副教授，博士，硕士研究生导师。

作者简介:

毛旭鹏（maoxupeng1988@163.com），工程师，硕士。

Stand-level model construction for carbon stock of Cunninghamia lanceolata forest in Jiangxi Province

Xupeng MAO¹, Lixin TIAN¹, Yu LU², Daobi YE³, Hao ZANG⁴

Affiliations

^1.Jiangxi Forestry Resources Monitoring Center, Nanchang 330046, Jiangxi, China

^2.Central South Academy of Inventory and Planning of National Forestry and Grassland Administration, Changsha 410014, Hunan, China

^3.Jiangxi Institute of Land Space Survey and Planning, Nanchang 330025, Jiangxi, China

^4.College of Forestry, Jiangxi Agricultural University, Nanchang 330045, Jiangxi, China

出版时间: 2026-05-25 doi: 10.14067/j.cnki.1673-923x.2026.05.006

文章导航

摘要

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【目的】

基于国家标准《主要树种立木生物量模型与碳计量参数》（GB/T 43648—2024），构建适用于江西省的杉木林分水平碳储量估算模型，以提升估算结果的精度和可靠性。

【方法】

以Logistic、修正Weibull和Gompertz 3个理论生长方程为基础模型，分别引入反映林分密度的2种幂函数结构ND_g^φ和N^δD_g^φ，构建6个可变密度林分水平碳储量模型，并将常用的幂律异速生长方程纳入模型对比体系。采用非线性加权最小二乘方法进行参数拟合，通过模型评价和检验确定最优模型。为进一步验证所建模型的有效性，将最优模型与传统方法的预估结果进行了系统比较。

【结果】

1）纳入幂函数结构ND_g^φ的修正Weibull方程具有最大的确定系数（R²=0.973）以及最小的估计值标准差（SEE为3.004 t·hm^-2）、总相对误差（TRE为0.06%）、平均系统误差（MSE为-0.07%）、平均预估误差（MPE为1.77%）、平均百分标准误差（MPSE为8.99%）和赤池信息准则（AIC为920.6），TRE和MSE均控制在±3%以内，MPE和MPSE分别满足小于3%和15%的一般精度要求，模型残差在异方差性和正态性方面得到了显著改善。2）与传统方法相比，修正Weibull方程的预估值与观测值线性拟合的R²（0.978）和参数m（0.950）均为最大，参数n与0无显著差异（P>0.1），TRE（2.89%）的绝对值最小，预估值与观测值之间的系统偏差不显著（P>0.1）。在传统方法中，BEF法的R²为0.974，参数m为0.934，参数n与0无显著差异（P>0.1），TRE为10.57%，预估值存在系统性低估（P<0.001），比观测值平均低了1.427 t·hm^-2；CBEF1法和CBEF2法的R²分别为0.792和0.872，参数m分别为0.575和0.681，参数n分别为10.921和8.715，TRE分别为-13.17%和-12.36%，预估值均存在严重系统性高估（P<0.05），分别比观测值平均高了4.227 t·hm^-2和3.673 t·hm^-2。

【结论】

基于国家标准构建的修正Weibull方程为研究区杉木林碳储量估算的最优模型，其估算结果的精度和可靠性优于传统方法，具备较好的实际应用价值。

关键词

林分碳储量 / 杉木林 / 理论生长方程 / BEF法 / CBEF法 / 江西省

Abstract

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【Objective】

This study aims to construct a stand-level model for estimating the carbon stock of Cunninghamia lanceolata forests applicable to Jiangxi Province based on the national standard “Tree Biomass Models and Related Parameters to Carbon Accounting for Major Tree Species” (GB/T 43648-2024), to improve the accuracy and reliability of the estimation.

【Method】

Three theoretical growth equations—Logistic, Modified Weibull, and Gompertz—were used as the base models for this study. Two types of power function form, referred to as ND_g^φ and N^δD_g^φ, were introduced to reflect the density of the stand, resulting in six models for estimating carbon stock in variable-density stands. Additionally, the commonly used power-law allometric equation was included in the model comparison framework. The nonlinear weighted least squares method was employed for parameter fitting, and the optimal model was established through model evaluation and testing. To further validate the effectiveness of the constructed model, a systematic comparison was conducted between the estimates from the optimal model and those obtained using traditional methods.

【Result】

1) The modified Weibull equation, incorporating the power function form ND_g^φ, achieves the highest coefficient of determination (R²=0.973) and the lowest standard error of estimate (SEE=3.004 t·hm^-2). Additionally, it demonstrates minimal values for total relative error (TRE=0.06%), mean systematic error (MSE=-0.07%), mean prediction error (MPE=1.77%), mean percent standard error (MPSE=8.99%), and Akaike Information Criterion (AIC=920.6). TRE and MSE are maintained within ±3%, while MPE and MPSE meet the general accuracy requirements of less than 3% and 15%, respectively. Furthermore, the model's residuals show significant improvements in heteroscedasticity and normality; 2) Compared with the traditional methods, the modified Weibull equation demonstrates the best performance with an R² of 0.978 and a parameter m of 0.950. The parameter n is not significantly different from 0 (P>0.1), and the absolute value of TRE is the lowest at 2.89%. Additionally, the systematic bias between the predicted values and the observed values is not significant (P>0.1). Among traditional methods, the BEF method shows an R² of 0.974 and a parameter m of 0.934. Like the modified Weibull equation, its parameter n is not significantly different from 0 (P>0.1). However, the TRE is 10.57%, indicating a significant systematic underestimation of the predicted values (P<0.001), with an average of 1.427 t·hm^-2 lower than the observed values. In contrast, the CBEF1 and CBEF2 methods yield R² of 0.792 and 0.872, respectively. Their parameter m values are 0.575 and 0.681, with parameter n values of 10.921 and 8.715. The TRE for CBEF1 and CBEF2 methods are -13.17% and -12.36%, respectively, indicating a significant systematic overestimation of the predicted values (P<0.05). On average, the predicted values exceed the observed values by 4.227 t·hm^-2 and 3.673 t·hm^-2, respectively.

【Conclusion】

The modified Weibull equation, developed according to the national standard, is optimal for estimating carbon stock in Cunninghamia lanceolata forests within the study area. Its estimation results are more accurate and reliable than those of traditional methods, offering greater practical value in application.

Key words

stand carbon stock / Cunninghamia lanceolata forest / theoretical growth equation / BEF method / CBEF method / Jiangxi Province

引用本文

毛旭鹏, 田立新, 陆禹, 叶道碧, 臧颢. 江西省杉木林碳储量模型研建. 中南林业科技大学学报, 2026 , 46 (5) : 48 -58 . DOI: 10.14067/j.cnki.1673-923x.2026.05.006

Xupeng MAO, Lixin TIAN, Yu LU, Daobi YE, Hao ZANG. Stand-level model construction for carbon stock of Cunninghamia lanceolata forest in Jiangxi Province[J]. Journal of Central South University of Forestry & Technology, 2026 , 46 (5) : 48 -58 . DOI: 10.14067/j.cnki.1673-923x.2026.05.006

基金

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国家自然科学基金项目(31960313; 31700563)
江西省林业科技创新专项(〔2019〕01号)

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2026年第46卷第5期

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文章信息

doi: 10.14067/j.cnki.1673-923x.2026.05.006

接收时间：2025-05-20
首发时间：2026-10-30
出版时间：2026-05-25

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出版历史

收稿日期：2025-05-20
修回日期：2025-07-24

基金

国家自然科学基金项目(31960313; 31700563)

江西省林业科技创新专项(〔2019〕01号)

作者信息

^1.江西省林业资源监测中心，江西　南昌　330046

^2.国家林业和草原局中南调查规划院，湖南　长沙　410014

^3.江西省国土空间调查规划研究院，江西　南昌　330025

^4.江西农业大学　林学院，江西　南昌　330045

通讯作者:

臧颢（b12345abba@163.com），副教授，博士，硕士研究生导师。

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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