江西分宜杉木人工林生物量与死亡有机质碳库动态耦合对轮伐期和林地期望价值的影响

doi:10.11707/j.1001-7488.LYKX20250732

Abstract

Abstract:

Objective: Cunninghamia lanceolata (Chinese fir) plantations in Fenyi City, Jiangxi Province were targeted. A land expectation value (LEV) model integrating the dynamic coupling between biomass and dead organic matter carbon pools was constructed to clarify the regulatory effect of the carbon pool coupling mechanism on the optimal rotation period and land expectation value of Chinese fir plantations, as well as the effects of key parameters, so as to provide quantitative support for the synergistic management of timber production and carbon sequestration in Chinese fir plantations. Method: Based on 40-year continuous positioning observation data from Chinese fir plantations in Fenyi City, Jiangxi Province, the classic Faustmann model was used as the framework to incorporate the dynamic coupling process of biomass and dead organic matter carbon pools, and set three scenarios: baseline (no carbon sequestration revenue, no nutrient-driven positive feedback, with biomass and dead organic matter carbon pools independent of each other), static carbon sequestration (with carbon sequestration revenue but no nutrient-driven positive feedback), and dynamic coupling (with carbon sequestration revenue and nutrient-driven positive feedback, with two carbon pools dynamically coupled). The dynamic characteristics of carbon pools and LEV under different scenarios were simulated. Furthermore, sensitivity analysis was conducted on three core parameters, carbon price (P_c), nutrient feedback coefficient (λ), and dead organic matter decomposition rate (α), to quantify the influence of key parameters on the optimal rotation period and LEV. Result: 1) The optimal rotation period for all three scenarios was 21 years, but the LEV in the dynamic coupling scenario was the highest (62 555 yuan·hm^?2), which was 169 yuan·hm^?2 higher than that in the baseline scenario and 21 yuan·hm^?2 higher than that in the static carbon sequestration scenario. The revenue increment came from two aspects: firstly, the direct carbon sequestration revenue brought by the increase in total carbon pool storage; secondly, the timber revenue increment driven by nutrient-driven positive feedback that promoted biomass growth and increased the proportion of large-diameter timber. 2) In the dynamic coupling scenario, the nutrient-driven positive feedback loop between the two carbon pools significantly improved the carbon pool accumulation efficiency. At age 21, the biomass carbon pool, dead organic matter carbon pool, and total carbon pool of Chinese fir plantations increased by 8.3%, 7.8%, and 8.2%, respectively, compared with the static scenario. Carbon pool accumulation showed obvious stage characteristics: nutrient cycling and synergistic accumulation between carbon pools were weak during the young forest stage, the difference expanded rapidly in the fast-growing stage, and the carbon pool in the dynamic scenario maintained steady growth in the near-mature stage, with long-term carbon sequestration capacity significantly superior to that in the static scenario. 3) Sensitivity analysis showed that within the range of realistic parameters, key parameters had no impact on the determination of the optimal rotation period, but their effects on LEV were clear: LEV increased significantly with the rise of λ, while the positive impact of P_c on LEV and the negative impact of α on LEV were both very small, with the magnitude of the impact was within 0.05%. Conclusion: Under the current timber-dominated management mode, the dynamic coupling effect between biomass and dead organic matter carbon pools does not change the widely adopted 21-year optimal rotation period of Chinese fir plantations. The dynamic coupling of the two carbon pools offset the discount loss of carbon sequestration through nutrient-driven positive feedback, realizing the coordinated improvement of carbon sequestration and timber revenue. Optimizing understory management of Chinese fir plantations and providing reasonable carbon price subsidies are effective approaches to activate the carbon pool coupling effect and thereby improve plantation management efficiency. This model exhibits strong adaptability to the ecological gradient differences in southern Chinese fir production areas and can provide quantitative technical support for the synergistic management of timber production and carbon sequestration in Chinese fir plantations.

Key words: Cunninghamia lanceolata plantations, land expectation value, optimal rotation period, dynamic coupling of carbon pools, nutrient feedback

CLC Number:

S7-9
F307.2

Lin Liu,Honggang Sun. Effects of Dynamic Coupling Between Biomass and Dead Organic Matter Carbon Pools on Rotation Period and Forest Land Expectation Value of Cunninghamia lanceolata Plantations in Fenyi, Jiangxi Province[J]. Scientia Silvae Sinicae, 2026, 62(5): 16-26.

Figures/Tables 6

Table 1

Estimation formula for stand carbon sequestration"

碳库类型 Carbon pool type	计算公式 Calculation formula	变量说明与参数设置 Variable explanations and parameter Settings	来源 Sources
基准生物量碳库 Base biomass carbon pool （B₀）	B₀=0.5BEF（aV_t+b）	a: 蓄积量转换系数，0.475 4 Volume conversion coefficient, 0.475 4; b: 截距项，30.630 3 Intercept term, 30.630 3; BEF: 生物量扩展因子，1.546 0 Biomass expansion factor, 1.546 0; 0.5：生物量碳含量 Carbon content of biomass	徐冰等，2020、余智涵等，2022

动态耦合的生物量碳库 Dynamically coupled biomass carbon pool （B）	年增量（B′）方程 Annual increment （B′）equation B′= dB₀/dt+λD′ 累积碳库方程 Cumulative carbon pool equation B=B₀（0）+∫₀^tB′（s）ds	B₀（0）：B₀的初始值 The initial value of B₀; dB₀/dt：基准生物量碳库的自然年增量 Natural annual increment of base biomass carbon pool； λ：养分反馈系数 Nutrient feedback coefficient； s：介于0~t之间的某个林龄 A stand age between 0 and t D′：有养分反馈的死亡有机质碳库年变化量 Annual variation of dead organic matter carbon pool with nutrient feedback	基于Fang等（2001）、Zhang等（2025）的研究整合得到 Integrated based on Fang et al. （2001）， Zhang et al. （2025）
死亡有机质碳库 Dead organic matter carbon pool	无养分反馈的碳库储量（D₀） Carbon pool storage without nutrient feedback（D₀） D₀=D₀（0）+∫₀^t[βB₀（s）?αD₀（s）]ds 无养分反馈的碳库年变化量(D₀') Annual variation of carbon pool without nutrient feedback (D₀′) D₀′=βB₀?αD₀ 有养分反馈的碳库储量（D） Carbon pool storage with nutrient feedback （D） D=D₀（0）+∫₀^t[βB（s）?αD（s）]ds 有养分反馈的碳库年变化量(D') Annual variation of carbon pool with nutrientfeedback (D′) D′=βB?αD	D₀（0）：D₀的初始值 The initial value of D₀; β：生物量年死亡比率 Annual mortality ratio of biomass; α：分解速率常数 Decomposition rate constant	参考熊鑫等（2016）、余智涵等（2022），本研究整合得到Integrated in this study with reference to Xiong et al. （2016）， Yu et al. （2022）

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指标 Index	单位 Unit	基准碳库情景 Baseline carbon pool scenario	静态碳库情景 Static carbon pool scenario	动态耦合情景 Dynamic coupling scenario
最优轮伐期 Optimal rotation period（T*）	a	21	21	21
21年生LEV峰值 Peak LEV of 21-year-old Chinese fir stands	yuan·hm^?2	62 386	62 534	62 555
21年生生物量碳库 Biomass carbon pool of 21-year-old Chinese fir stands	t·hm^?2	126.100	126.100	136.617
21年生死亡有机质碳库 Dead organic matter carbon pool of 21-year-old Chinese fir stands	t·hm^?2	—	27.889	30.048
21年生总碳库 Total carbon pool of 21-year-old Chinese fir stands	t·hm^?2	—	153.988	166.665
40年生LEV LEV of 40-year-old Chinese fir stands	yuan·hm^?2	23 346	23 359	23 361
40年生生物量碳库 Biomass carbon pool of 40-year-old Chinese fir stands	t·hm^?2	152.452	152.452	166.532
40年生死亡有机质碳库 Dead organic matter carbon pool of 40-year-old Chinese fir stands	t·hm^?2	—	36.856	40.227
40年生总碳库 Total carbon pool of 40-year-old Chinese fir stands	t·hm^?2	—	189.308	206.758

林龄 Stand age	静态碳库情景 Static carbon pool scenario			动态耦合情景 Dynamic coupling scenario
林龄 Stand age	基准生物量碳库储量Base biomass carbon pool storage （B₀）	无养分反馈的死亡有机质碳库储量Dead organic matter carbon pool storage without nutrient feedback （D₀）	碳库总储量Total carbon pool storage （TC）	动态耦合的生物量碳库储量 Dynamically coupled biomass carbon pool storage （B）	有养分反馈的死亡有机质碳库储量 Dead organic matter carbon pool storage with nutrient feedback （D）	碳库总储量Total carbon pool storage （TC）
5	38.508	4.509	43.018	40.135	4.647	44.782
10	80.586	12.649	93.235	85.226	13.258	98.484
15	107.164	21.041	128.205	114.999	22.384	137.383
20	123.574	26.970	150.543	133.727	29.009	162.736
21	126.100	27.889	153.988	136.617	30.048	166.665
25	134.496	30.897	165.394	146.208	33.463	179.671
40	152.452	36.856	189.308	166.532	40.227	206.758

参数 Parameter	基准碳库情景 Baseline carbon pool scenario		静态碳库情景 Static carbon pool scenario		动态耦合情景 Dynamic coupling scenario
参数 Parameter	T*/a	LEV/（yuan·hm^?2）	T*/a	LEV/（yuan·hm^?2）	T*/a	LEV/（yuan·hm^?2）
λ=0	21	62 386	21	62 386	21	62 386
λ=0.15	_	_	_	_	21	62 574
λ=0.20	_	_	_	_	21	62 588
P_c=30	_	_	21	62 438	21	62 459
P_c=77	_	_	21	62 520	21	62 574
P_c=120	_	_	21	62 595	21	62 678
α=0.22	_	_	21	62 542	21	62 568
α=0.25	_	_	21	62 534	21	62 555
α=0.34	_	_	21	62 521	21	62 533

[1]	Zhihan Yu,Hongqiang Yang. Research Frontier and Prospect of Forest Management Decision-Making Methodology Based on Generalized Faustmann Model [J]. Scientia Silvae Sinicae, 2024, 60(9): 170-182.
[2]	Lin Zhuo, Wu Chengzhen, Hong Wei, Hong Tao. Economic Benefits Analysis of Carbon Sequestration and Timber and Determination of Optimal Rotation Period for a Cunninghamia lanceolata Plantation——Based on Time Series Model [J]. Scientia Silvae Sinicae, 2016, 52(10): 134-145.

Effects of Dynamic Coupling Between Biomass and Dead Organic Matter Carbon Pools on Rotation Period and Forest Land Expectation Value of Cunninghamia lanceolata Plantations in Fenyi, Jiangxi Province

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