山西中条山林局油松纯林碳汇潜力

doi:10.11707/j.1001-7488.LYKX20240543

林业科学 ›› 2025, Vol. 61 ›› Issue (5): 74-84.doi: 10.11707/j.1001-7488.LYKX20240543

山西中条山林局油松纯林碳汇潜力

何潇¹,罗光成^1,²,高文强¹,李海奎¹,曾伟生³,段福军⁴,雷相东^1,*()

1. 林木资源高效生产全国重点实验室　国家林业和草原局森林经营与生长模拟实验室　中国林业科学研究院资源信息研究所　北京 100091
2. 北京林业大学林学院　北京 100083
3. 国家林业和草原局调查规划设计院　北京 100714
4. 山西省中条山国有林管理局　侯马 043003

收稿日期:2024-09-19 出版日期:2025-05-20 发布日期:2025-05-24
通讯作者: 雷相东 E-mail:xdlei@ifrit.ac.cn
基金资助:
国家重点研发计划课题“典型人工林立地质量评价与生产力提升技术（2022YFD2200501）”；国家自然科学基金青年科学基金项目“针阔混交林碳汇能力的密度和结构效应研究”（32301588）。

Carbon Sequestration Potentiality of Pinus tabuliformis Pure Forest in Zhongtiaoshan Forestry Bureau of Shanxi Province

Xiao He¹,Guangcheng Luo^1,²,Wenqiang Gao¹,Haikui Li¹,Weisheng Zeng³,Fujun Duan⁴,Xiangdong Lei^1,*()

1. State Key Laboratory of Efficient Production of Forest Resources　Key Laboratory of Forest Management and Growth Modelling，National Forestry and Grassland Administration　Institute of Forest Resource Information Techniques，CAF　Beijing 100091
2. College of Forestry, Beijing Forestry University　Beijing 100083
3. Academy of Inventory and Planning, National Forestry and Grassland Administration　Beijing 100714
4. Zhongtiaoshan State-Owned Forest Administration of Shanxi　Houma 043000

Received:2024-09-19 Online:2025-05-20 Published:2025-05-24
Contact: Xiangdong Lei E-mail:xdlei@ifrit.ac.cn

摘要/Abstract

摘要：

目的: 建立包含固碳等级、林分密度指数和林龄的碳储量分级生长模型系，提出一种森林碳汇潜力估计方法，估计森林经营单位尺度碳汇潜力，为森林经营增汇提供依据。方法: 基于山西省森林资源清查油松纯林固定样地数据和理论生长模型，采用双重迭代分级算法确定固碳等级，并建立碳储量分级生长模型系：平均单株碳储量分级生长模型、林分碳储量分级生长模型、平均单株断面积分级生长模型和林分断面积分级生长模型，使用确定系数（R²）、均方根误差、相对均方根误差等指标评价模型。以最大林分碳储量连年生长量（碳汇潜力）为目标函数，以林分密度为决策变量，通过优化方法求解碳汇潜力最大时的最优林分密度。基于山西省中条山林局油松纯林小班调查数据，评估其现实碳汇量、碳汇潜力和碳汇提升空间。结果: 山西省油松纯林平均单株碳储量分级生长模型和平均单株断面积分级生长模型的R²分别为0.920和0.903，林分碳储量分级生长模型和林分断面积分级生长模型的R²分别为0.966和0.985，模型的拟合效果较好；林分碳汇潜力随林龄的增加先增加后降低、随固碳等级的增加而升高；中条山林局油松纯林单位面积的碳汇潜力平均值为1.59 t·hm^?2a^?1，单位面积的现实碳汇量平均值为0.97 t·hm^?2a^?1，单位面积的相对碳汇提升空间平均值为29.08%。结论: 本研究建立的油松纯林碳储量分级生长模型系可应用于碳储量生长预测，提出的碳汇潜力估计方法具有通用性和可靠性。建议通过林分密度调整，提升油松纯林的现实碳汇量，该方法可为油松及其他类型森林固碳增汇经营提供依据。

关键词: 生长模型, 固碳等级, 碳汇潜力, 林分密度优化

Abstract:

Objective: The aim of this study was to develop a carbon storage growth graded model system incorporating carbon sequestration grade, stand density index, and stand age, and put forward a method for estimating carbon sequestration potentiality, which can be used to assess the carbon sequestration potentiality at forest management unit scale, thereby providing a basis for forest management to increase carbon sequestration. Method: Based on the data of permanent sample plots of Pinus tabuliformis pure forest of Shanxi Province and theoretical growth model, a double iterative grading algorithm was used to ascertain the carbon sequestration grade and to develop the carbon storage graded growth model system. This model system includes mean individual tree carbon storage graded, stand carbon storage graded, mean individual tree basal area graded and stand basal area graded growth models. Models were evaluated by the coefficient of determination (R²), root mean square error and relative root mean square error. The optimization method was applied to determine the optimal stand density that maximizes carbon sequestration potentiality, with the maximum stand carbon storage annual increment as the objective function and stand density as the decision variable. The realized carbon sequestration, potential carbon sequestration, and the gap between them were analyzed based on the sub-compartment survey data from Zhongtiaoshan Bureau of Shanxi Province. Result: The R² values were 0.920 and 0.903 for mean individual tree carbon storage graded growth model and basal area graded growth model respectively, and 0.966 and 0.985 for stand carbon storage graded growth model and basal area graded growth model, respectively, indicating a good fit for all growth models. Stand carbon sequestration potentiality increases initially and then decreases with stand age, and it rises with an increase of carbon sequestration grade. The average potential and realized carbon sequestration for P. tabuliformis pure forests was 1.59 and 0.97 t·hm^?2a^?1 at unit area, respectively, with an average relative carbon sequestration growth gap was 29.08% in Zhongtiaoshan Bureau. Conclusion: This study successfully established a carbon storage graded growth model system for P. tabuliformis pure foresr that can predict carbon storage growth process. It is recommended to make stand density adjustment for P. tabuliformis plantations to increase realized carbon sequestration. This approach can serve as a reference for carbon management aimed at increasing carbon sequestration in both P. tabuliformis forests and other forest types.

Key words: growth model, carbon sequestration grade, carbon sequestration potentiality, stand density optimization

中图分类号:

S757

何潇,罗光成,高文强,李海奎,曾伟生,段福军,雷相东. 山西中条山林局油松纯林碳汇潜力[J]. 林业科学, 2025, 61(5): 74-84.

Xiao He,Guangcheng Luo,Wenqiang Gao,Haikui Li,Weisheng Zeng,Fujun Duan,Xiangdong Lei. Carbon Sequestration Potentiality of Pinus tabuliformis Pure Forest in Zhongtiaoshan Forestry Bureau of Shanxi Province[J]. Scientia Silvae Sinicae, 2025, 61(5): 74-84.

图/表 7

表1

表2

表3

碳储量分级生长模型系的评价指标①"

模型 Model	模型表达式 Model expression	评价指标 Evaluation indices
模型 Model	模型表达式 Model expression	确定系数 Coefficient of determination (R²)	均方根误差 Root mean square error (RMSE)	相对均方根误差 Relative root mean square error (rRMSE) (%)
平均单株碳储量分级生长模型 Carbon storage graded growth model of mean individual tree	${C}_{\text{m}}\text{=}\left\{\begin{array}{l}\text{300}\text{.000}{\left[\text{1}-\text{exp(}-\text{0}\text{.027}T\text{)}\right]}^{\text{3}\text{.266}}\text{ }，l=1\\ \text{204}\text{.804}{\left[\text{1}-\text{exp(}-\text{0}\text{.027}T\text{)}\right]}^{\text{3}\text{.435}}\text{ }，l=2\\ \text{109}\text{.609}{\left[\text{1}-\text{exp(}-\text{0}\text{.027}T\text{)}\right]}^{\text{3}\text{.603}}\text{ }，l=3\end{array}\right. $	0.920	11.319 kg	25.74

平均单株断面积分级生长模型 Basal area graded growth model of mean individual tree	$ \text{MBA =}\left\{\begin{array}{l}\text{914}\text{.301}{\left[\text{1}－\text{exp(}－\text{0}\text{.023}T\right]}^{\text{2}\text{.299}}\text{ }，l=1\\ \text{596}\text{.247}{\left[\text{1}－\text{exp(}－\text{0}\text{.023}T\right]}^{\text{2}\text{.197}}\text{ }，l=2\\ \text{375}\text{.472}{\left[\text{1}－\text{exp(}－\text{0}\text{.023}T\right]}^{\text{2}\text{.296}}\text{ }，l=3\end{array} \right. $	0.903	36.667 cm²	21.36

林分碳储量分级生长模型 Stand carbon storage graded growth model	$ C\text{ =}\left\{\begin{array}{l}\text{500}\text{.000}{\left[\text{1}-\text{exp(}-\text{0}\text{.013}{(\dfrac{\text{SDI}}{3\text{ }000})}^{\text{1}\text{.478}}T\right]}^{\text{0}\text{.774}}\text{ }，l=1\\ \text{3}7\text{9}\text{.163}{\left[\text{1}-\text{exp(}-\text{0}\text{.013}{(\dfrac{\text{SDI}}{3\text{ }000})}^{\text{1}\text{.478}}T\right]}^{\text{0}\text{.730}}\text{ }，l=2\\ \text{2}58.327{\left[\text{1}-\text{exp(}-\text{0}\text{.013}{(\dfrac{\text{SDI}}{3\text{ }000})}^{\text{1}\text{.478}}T\right]}^{\text{0}\text{.681}}\text{ }，l=3\end{array}\right. $	0.966	5.463 t?hm^?2	13.35

林分断面积分级生长模型 Stand basal area graded growth model	$ \text{BA=}\left\{\begin{array}{l}\text{7}7.565\left[\text{1}-\text{exp(}-\text{0}\text{.048}(\dfrac{\text{SDI}}{3\text{ }000})^{\text{3}\text{.075}}T\right]^{\text{0}\text{.341}}\text{ }，l=1 \\ \text{6}9.249\left[\text{1}-\text{exp(}-\text{0}\text{.048}(\dfrac{\text{SDI}}{3\text{ }000})^{\text{3}\text{.075}}T\right]^{\text{0}\text{.336}}\text{ }，l=2 \\ \text{5}6.928\left[\text{1}-\text{exp(}-\text{0}\text{.048}(\dfrac{\text{SDI}}{3\text{ }000})^{\text{3}\text{.075}}T\right]^{\text{0}\text{.318}}\text{ }，l=3\end{array}\right. $	0.985	1.162 m²?hm^?2	6.98

表3

图1

图2

表4

表5

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变量Variables	平均值 Mean	最小值 Minimum	最大值 Maximum	变异系数 Coefficient of variation, CV (%)
林龄 Stand age /a	43	12	91	40.46
林分密度Stand density (N) / （trees·hm^?2）	1173	300	6100	54.37
林分密度指数Stand density index (SDI)	628	56	1970	49.46
林分断面积Stand basal area (BA) / (m²?hm^?2)	16.65	0.97	55.49	56.27
林分平均胸径Stand mean DBH (D_g) / cm	14.1	5.8	30.8	32.63
林分蓄积Stand volume (V) / ( m³?hm^?2)	63.77	2.62	285.83	67.50
林分碳储量Stand carbon storage (C) / (t?hm^?2)	40.93	1.39	200.33	72.30
平均单株断面积Mean individual tree basal area (MBA) /cm²	171.67	26.70	747.51	68.14
平均单株碳储量Mean individual tree carbon storage C_m/ kg	43.98	3.79	255.85	90.80

起源 Origin	小班数 Number of sub-compartment	变量Variables	平均值 Mean	最小值 Minimum	最大值 Maximum	变异系数 Coefficient of variation, CV (%)
天然 Natural	688	林龄 Stand age /a	37	5	82	36.33
		林分密度Stand density (N) / (trees·hm^?2)	602	105	3432	82.73
		林分密度指数Stand density index (SDI)	288	12	1270	81.00
		林分断面积Stand basal area (BA) / (m²?hm^?2)	7.20	0.17	32.96	86.73
		林分平均胸径Stand mean DBH (D_g) /cm	12.0	3.6	23.9	25.87
		林分蓄积Stand volume (V) / (m³?hm^?2)	52.90	2.31	220.33	58.77
		平均单株断面积Mean individual tree basal area (MBA) /cm²	119.67	10.18	448.63	51.81
人工 Plantation	3788	林龄 Stand age /a	33	7	60	25.59
		林分密度Stand density (N) / (trees·hm^?2)	716	100	5657	96.32
		林分密度指数Stand density index (SDI)	320	11	2368	98.27
		林分断面积Stand basal area (BA) / (m²?hm^?2)	7.78	0.14	81.14	101.81
		林分平均胸径Stand mean DBH (D_g) /cm	11.3	2.5	27.6	27.82
		林分蓄积Stand volume (V) / (m³?hm^?2)	48.42	0.60	258.00	56.21
		平均单株断面积Mean individual tree basal area (MBA) /cm²	109.26	4.91	598.28	56.37

尺度 Scale	项目 Item	固碳等级 Carbon sequestration class			总体 Total
尺度 Scale	项目 Item	l = 1 （n=507）	l = 2 （n=1 141）	l = 3 （n=2 828）	总体 Total
单位面积 Unit area	年现实碳汇量Realized carbon productivity increment (RCI) /(t·hm^?2a^?1)	2.32±1.81	1.42±1.23	0.63±0.65	1.02±1.16
	年碳汇潜力 Potential carbon productivity increment (PCI) /（t·hm^?2a^?1）	3.79±1.17	2.49±0.53	0.84±0.20	1.59±1.16
	碳汇提升空间Carbon productivity gap (CPG) / (t·hm^?2a^?1)	1.47±1.90	1.07±1.32	0.21±0.67	0.57±1.17
	相对碳汇提升空间 Relative carbon productivity gap （RCPG) (%)	37.19±51.6	41.22±53.87	22.73±81.75	29.08±73.04

森林经营单位 Forest management unit	年总现实碳汇量 Total realized carbon productivity increment (RCI) / (t·a^?1)	11 143	18 302	19 474	48 919
	年总碳汇潜力Total potential carbon productivity increment (PCI) / (t·a^?1)	20 087	33 767	25 072	78 925
	碳汇提升空间Carbon productivity gap (CPG) / (t·a^?1)	8 944	15 465	5 598	30 006
	相对碳汇提升空间Relative carbon productivity gap (RCPG) (%)	44.53	45.80	22.33	38.02

项目 Item	分组 Group	单位面积 Unit area	森林经营单位 Forest management unit
起源 Origin	天然林Natural forests	46.599±55.322	49.893
起源 Origin	人工林Plantations	25.891±75.382	35.858

龄组 Age group	幼龄林Young forests	44.687±59.423	43.350
	中龄林Middle-aged forests	20.340±79.411	31.539
	近熟林Near-mature forests	49.041±46.564	57.465
	成熟林Mature forests	61.272±25.492	62.712
	过熟林Over-mature forests	85.805	85.805

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山西中条山林局油松纯林碳汇潜力

Carbon Sequestration Potentiality of Pinus tabuliformis Pure Forest in Zhongtiaoshan Forestry Bureau of Shanxi Province

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