碳中和背景下的中国碳汇林业生产效率时空分异及影响因素研究

doi:10.12302/j.issn.1000-2006.202312007

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南京林业大学学报（自然科学版） ›› 2025, Vol. 49 ›› Issue (3): 254-264.doi: 10.12302/j.issn.1000-2006.202312007

碳中和背景下的中国碳汇林业生产效率时空分异及影响因素研究

师玮¹(), 赵思雪¹, 乔富伟², 安怡¹, 王维鹃¹, 张国炜¹

1.西北师范大学地理与环境科学学院, 甘肃兰州 730070
2.西北师范大学经济学院, 甘肃兰州 730070

收稿日期:2023-12-05 接受日期:2023-12-29 出版日期:2025-05-30 发布日期:2025-05-27
作者简介:
师玮(shiwei0716@163.com),副教授。
基金资助:
甘肃省自然科学基金项目(22JR5RA155);甘肃省高等教育创新基金项目(2021B-087);教育部人文社会科学研究规划基金项目(23YJA630080)

Spatiotemporal differentiation and influencing factors of forestry production efficiency with carbon sequestration in China under the context of carbon neutrality

SHI Wei¹(), ZHAO Sixue¹, QIAO Fuwei², AN Yi¹, WANG Weijuan¹, ZHANG Guowei¹

1. College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
2. School of Economics, Northwest Normal University, Lanzhou 730070, China

Received:2023-12-05 Accepted:2023-12-29 Online:2025-05-30 Published:2025-05-27

摘要/Abstract

摘要：

【目的】探讨碳汇林业生产效率并探究其关键影响因素是助力中国林业高质量发展的重要出发点,可为制定差异化林业发展政策提供必要的依据,也为有效促进中国林业资源优化配置和区域协同均衡发展提供参考。【方法】采用蓄积量拓展法、SBM(Slack-Based Measure)模型、Dagum基尼系数和Tobit模型等方法,分析了2003—2018年中国31个省份的碳汇林业经济价值和各项效率水平,并在此基础上深入分析了综合效率、纯技术效率和规模效率动态变化及其时空分异情况,探究其关键影响因素。【结果】中国的林业碳汇储存量整体上水平较高,其中林业碳汇经济价值最高的3个省区依次为西藏、四川、云南;综合效率、纯技术效率与规模效率呈现出显著的区域性差异,具有明显的空间集聚特征;区域间差异和区域内差异是中国碳汇林业生产效率的区域差异主要来源;林业产值比重与林业人力资本投入对中国碳汇林业生产效率起促进作用,而人均GDP和森林病虫鼠害发生情况对碳汇林业生产效率起抑制作用。【结论】中国林业发展可通过推进林业资源的高效利用、缩小区域发展的效率差异以及把握关键影响因素,从而实现碳汇林业的高质量发展。

关键词: 碳汇林业, 生产效率, SBM模型, Dagum基尼系数, Tobit模型

Abstract:

【Objective】This study aims to investigate the production efficiency of carbon sequestration forestry and identify its key influencing factors. This exploration serves as a crucial foundation for the high-quality development of forestry in China. It not only provides essential insights for formulating differentiated forestry development policies but also facilitates the optimal allocation of forestry resources and promotes coordinated and balanced regional development across the country.【Method】The economic value and efficiency levels of carbon sequestration forestry in 31 provinces of China from 2003 to 2018 were evaluated using the volume expansion method, SBM model, Dagum Gini coefficient, and Tobit model. Building on this analysis, the study delved into the dynamic changes in comprehensive efficiency, pure technical efficiency, and scale efficiency, as well as their spatiotemporal differentiation. Additionally, the key influencing factors were systematically explored.【Result】The findings revealed that China’s forestry carbon sequestration storage level was relatively high, with Xizang, Sichuan, and Yunnan being the top three provincial area in terms of forestry carbon sequestration economic value. Comprehensive efficiency, pure technical efficiency, and scale efficiency exhibited significant regional disparities and demonstrated distinct spatial agglomeration characteristics. Both inter-regional and intra-regional differences were identified as the primary sources of regional variations in the production efficiency of carbon sequestration forestry in China. The proportion of forestry output value and investment in forestry human capital were found to positively influence the production efficiency of China’s carbon sequestration forestry, whereas per capita GDP and the incidence of forest diseases, pests, and rodents exerted a restraining effect.【Conclusion】China’s forestry development can achieve high-quality growth in carbon sequestration forestry by enhancing the efficient utilization of forestry resources, reducing regional efficiency disparities, and addressing key influencing factors. This approach will contribute to the sustainable and balanced advancement of the forestry sector.

Key words: carbon sequestration forestry, production efficiency, SBM model, Dagum Gini coefficient, Tobit model

中图分类号:

S7-9

师玮,赵思雪,乔富伟,等. 碳中和背景下的中国碳汇林业生产效率时空分异及影响因素研究[J]. 南京林业大学学报（自然科学版）, 2025, 49(3): 254-264.

SHI Wei, ZHAO Sixue, QIAO Fuwei, AN Yi, WANG Weijuan, ZHANG Guowei. Spatiotemporal differentiation and influencing factors of forestry production efficiency with carbon sequestration in China under the context of carbon neutrality[J].Journal of Nanjing Forestry University (Natural Science Edition), 2025, 49(3): 254-264.DOI: 10.12302/j.issn.1000-2006.202312007.

图/表 9

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参考文献 34

[1]	邓诗宇, 张明芳, 侯怡萍, 等. 气候变化下川西地区森林碳储量对森林管理措施和干扰的长期响应[J]. 生态学报, 2025, 45(1):210-226.
	DENG S Y, ZHANG M F, HOU Y P, et al. Long-term response of forest carbon storage to forest management measures and disturbances in western Sichuan under climate change[J]. Acta Ecologica Sinica, 2025, 45(1):210-226. DOI:10.20103/j.stxb.202404030719.
[2]	吴恒, 吕大伟, 汪圣云, 等. “双碳”战略背景下的多尺度森林碳储量年度监测研究进展与思考[J]. 世界林业研究, 2024, 37(1):59-64.
	WU H, LV D W, WANG S Y, et al. Research progress and thinking on annual monitoring of multi-scale forest carbon storage under the background of “dual carbon” strategy[J]. World Forestry Research, 2024, 37(1):59-64. DOI:10.13348/j.cnki.sjlyyj.2024.0001.y.
[3]	CHU X, ZHAN J Y, LI Z H, et al. Assessment on forest carbon sequestration in the Three-North Shelterbelt Program region,China[J]. Journal of Cleaner Production, 2019, 215:382-389.DOI: 10.1016/j.jclepro.2018.12.296.
[4]	DIXON R K, SOLOMON A M, BROWN S, et al. Carbon pools and flux of global forest ecosystems[J]. Science, 1994, 263(5144):185-190.DOI: 10.1126/science.263.5144.185.
[5]	LI W, ZHANG S H, LU C. Exploration of China’s net CO₂ emissions evolutionary pathways by 2060 in the context of carbon neutrality[J]. Science of The Total Environment, 2022,831:154909.DOI: 10.1016/j.scitotenv.2022.154909.
[6]	LI L, HAO T T, CHI T. Evaluation on China’s forestry resources efficiency based on big data[J]. Journal of Cleaner Production, 2017, 142:513-523.DOI: 10.1016/j.jclepro.2016.02.078.
[7]	包蕊, 李涛, 张欣怡, 等. 森林生态系统损害评估体系与管理制度研究[J]. 生态学报, 2021, 41(3):924-933.
	BAO R, LI T, ZHANG X Y, et al. Study on the assessment and management system of forest ecosystem damage[J]. Acta Ecologica Sinica, 2021, 41(3):924-933.DOI: 10.5846/stxb202003100474.
[8]	LIN B Q, GE J M. To harvest or not to harvest? Forest management as a trade-off between bioenergy production and carbon sink[J]. Journal of Cleaner Production, 2020,268:122219.DOI: 10.1016/j.jclepro.2020.122219.
[9]	石小亮, 陈珂, 曹先磊, 等. 森林生态系统管理研究综述[J]. 生态经济, 2017, 33(7):195-201.
	SHI X L, CHEN K, CAO X L, et al. Review of forest ecosystem management[J]. Ecological Economy, 2017, 33(7):195-201.
[10]	刘亚, 黄安胜. 森林碳汇环境库兹涅茨曲线特征及其影响因素分析[J]. 世界林业研究, 2023, 36(2):132-137.
	LIU Y, HUANG A S. Characteristics and influencing factors of environmental Kuznets curve for forest carbon sequestration[J]. World Forestry Research, 2023, 36(2):132-137.DOI: 10.13348/j.cnki.sjlyyj.2023.0011.y.
[11]	谢军安, 王爱霞. 完善森林管理增强碳汇能力[J]. 当代经济管理, 2011, 33(4):31-33.
	XIE J A, WANG A X. On the relationship between forest management and carbon sink[J]. Contemporary Economy & Management, 2011, 33(4):31-33.DOI: 10.13253/j.cnki.ddjjgl.2011.04.010.
[12]	李海萍, 李定恒, 李豪. 贵州省退耕还林还草潜在碳汇效益评估[J]. 生态学报, 2022, 42(23):9499-9510.
	LI H P, LI D H, LI H. Evaluation of potential carbon sink benefits of Grain for Green Project in Guizhou Province[J]. Acta Ecologica Sinica, 2022, 42(23):9499-9510.DOI: 10.5846/stxb202207172042.
[13]	HOUGHTON R A, HALL F, GOETZ S J. Importance of biomass in the global carbon cycle[J]. Journal of Geophysical Research:Biogeosciences, 2009, 114(G2):G00E03.DOI: 10.1029/2009JG000935.
[14]	方精云. 北半球中高纬度的森林碳库可能远小于目前的估算[J]. 植物生态学报, 2000, 24 (5):635-638.
	FANG J Y. The forest carbon pool in the middle and high latitudes in the Northern Hemisphere may be much smaller than the current estimate[J]. Chinese Journal of Plant Ecology, 2000, 24 (5):635-638.
[15]	FANG J Y, WANG G G, LIU G H, et al. Forest biomass of China:an estimate based on the biomass-volume relationship[J]. Ecological Applications,1998, 8(4):1084-1091.DOI: 10.1890/1051-0761(1998)008[1084:FBOCAE]2.0.CO;2.
[16]	康惠宁, 马钦彦, 袁嘉祖. 中国森林C汇功能基本估计[J]. 应用生态学报, 1996, 7(3):230-234.
	KANG H N, MA Q Y, YUAN J Z. Estimation of carbon sink function of forests in China[J]. Chinese Journal of Applied Ecology, 1996, 7(3):230-234.
[17]	李秀娟, 周涛, 何学兆. NPP增长驱动下的中国森林生态系统碳汇[J]. 自然资源学报, 2009, 24(3):491-497.
	LI X J, ZHOU T, HE X Z. Carbon sink of forest ecosystem driven by NPP increasing in China[J]. Journal of Natural Resources, 2009, 24(3):491-497.DOI: 10.11849/zrzyxb.2009.03.014.
[18]	LEBEL L G, STUART W B. Technical efficiency evaluation of logging contractors using a nonparametric model[J]. Journal of Forest Engineering, 1998, 9(2):15-24.DOI: 10.1080/08435243.1998.10702714.
[19]	VIITALA E J, HÄNNINEN H. Measuring the efficiency of public forestry organizations[J]. Forest Science, 1998, 44(2):298-307.DOI: 10.1093/forestscience/44.2.298.
[20]	SOWLATI T. Efficiency studies in forestry using data envelopment analysis[J]. Forest Products Journal, 2005, 55(1):49-57.
[21]	LEE J. Using DEA to measure efficiency in forest and paper companies[J]. Forest Products Journal, 2005, 55(1):58-66.
[22]	CHEN W H, XU D Y, LIU J C. The forest resources input-output model:an application in China[J]. Ecological Indicators, 2015, 51:87-97.DOI: 10.1016/j.ecolind.2014.09.007.
[23]	闵志强, 胡云云, 刘友林, 等. 延安市林草光伏互补建设空间适宜性及固碳减排效益研究[J]. 西北林学院学报, 2023, 38(5):57-66.
	MIN Z Q, HU Y Y, LIU Y L, et al. Suitability of forest grass PV complementary space and carbon fixation and reduction benefits in Yan’an[J]. Journal of Northwest Forestry University, 2023, 38(5):57-66.DOI: 10.3969/j.issn.1001-7461.2023.05.08.
[24]	范正根, 邓超, 范雨琪, 等. “双碳” 目标视角下耕地利用生态效率测度及其时空特征:以长江中下游粮食主产区为例[J]. 生态经济, 2023, 39(11):119-127.
	FAN Z G, DENG C, FAN Y Q, et al. Measurement of eco-efficiency for cultivated land use and its spatial-temporal characteristics from the perspective of “double carbon” target:taking the main grain producing areas in the mid and lower reaches of the Yangtze River as an example[J]. Ecol-ogical Economy, 2023, 39(11):119-127.
[25]	郗婷婷, 李顺龙. 黑龙江省森林碳汇潜力分析[J]. 林业经济问题, 2006, 26(6):519-522,526.
	XI T T, LI S L. Analysis of forestry carbon mitigation potential in Heilongjiang Province[J]. Problems of Forestry Economics, 2006, 26(6):519-522,526.DOI: 10.16832/j.cnki.1005-9709.2006.06.008.
[26]	CHEN L, JIA G Z. Environmental efficiency analysis of China’s regional industry:a data envelopment analysis (DEA) based approach[J]. Journal of Cleaner Production, 2017, 142:846-853.DOI: 10.1016/j.jclepro.2016.01.045.
[27]	COOPER W W, SEIFORD L M, ZHU J. Handbook on data enve-lopment analysis[M]. Cham: Springer US, 2011.DOI: 10.1007/978-1-4419-6151-8.
[28]	CHARNES A, COOPER W W, RHODES E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, 2(6):429-444.DOI: 10.1016/0377-2217(78)90138-8.
[29]	施琪, 王玉玲. 基于超效率SBM模型的中国林业产业绩效评价研究[J]. 中国林业经济, 2022(1):17-23.
	SHI Q, WANG Y L. Research on performance evaluation of China forestry industry based on super-efficiency SBM model[J]. China Forestry Econ-omics, 2022(1):17-23.DOI: 10.13691/j.cnki.cn23-1539/f.2022.01.004.
[30]	杨旭, 屈志光, 邓远建. 中国省域林业生产技术效率的空间收敛性及分异特征[J]. 资源科学, 2021, 43(10):1947-1960.
	YANG X, QU Z G, DENG Y J. Spatial convergence and differentiation of forestry production technology efficiency in 30 provinces of China[J]. Resources Science, 2021, 43(10):1947-1960.DOI: 10.18402/resci.2021.10.02.
[31]	支玲, 许文强, 洪家宜, 等. 森林碳汇价值评价:三北防护林体系工程人工林案例[J]. 林业经济, 2008, 30(3):41-44.
	ZHI L, XU W Q, HONG J Y, et al. Evaluation of forest carbon-sink:a case study on artificial plantation of the three-north shelterbelt forest system program in China[J]. Forestry Economics, 2008, 30(3):41-44.DOI: 10.13843/j.cnki.lyjj.2008.03.008.
[32]	吕洁华, 付思琦, 张滨. 黑龙江省国有重点林区林业经济投入产出效率研究[J]. 林业经济问题, 2019, 39(3):300-306.
	LYU J H, FU S Q, ZHANG B. Study on the input-output efficiency of forestry in key state-owned forest areas of Heilongjiang Province[J]. Issues of Forestry Economics, 2019, 39(3):300-306.DOI: 10.16832/j.cnki.1005-9709.2019.03.012.
[33]	WANG J F, SHI K H, HU M X. Measurement of forest carbon sink efficiency and its influencing factors empirical evidence from China[J]. Forests, 2022, 13(11):1909.DOI: 10.3390/f13111909.
[34]	李文博. 江西省林业产业投入产出效率及其影响因素研究:基于DEA-Tobit模型[D]. 南昌: 江西农业大学, 2021.
	LI W B. Study on input-output efficiency of forestry industry in Jiangxi Province and its influencing factors:based on DEA-Tobit model[D]. Nanchang: Jiangxi Agricultural University, 2021.DOI: 10.27177/d.cnki.gjxnu.2021.000474.

省域 provincial area	森林蓄积量/ ×10⁴ m³ forest stock	碳汇量/ ×10⁸t carbon sinks	碳汇价值/ ×10⁸元 the value of carbon sinks	排序 rank
北京Beijing	1 347.31	0.16	10.19	28
天津Tianjing	283.73	0.03	2.17	30
河北Hebei	9 242.76	1.07	72.06	23
山西Shanxi	8 626.60	1.00	67.16	24
内蒙古Inner Mongoria	123 887.81	14.36	990.81	5
辽宁Liaoning	22 102.24	2.56	174.63	17
吉林Jilin	88 462.87	10.25	710.67	6
黑龙江Heilongjiang	156 940.69	18.19	1 253.33	4
上海Shanghai	173.28	0.02	1.20	31
江苏Jiangsu	4 166.38	0.48	32.50	26
浙江Zhejiang	18 113.07	2.10	140.09	19
安徽Anhui	14 732.27	1.71	115.24	20
福建Fujian	53 645.53	6.22	425.22	7
江西Jiangxi	36 580.01	4.24	291.20	10
山东Shandong	5 690.98	0.66	44.66	25
河南Henan	12 869.21	1.49	100.34	21
湖北Hubei	23 447.84	2.72	182.01	15
湖南Hunan	30 059.98	3.48	239.22	13
广东Guangdong	32 632.53	3.78	258.30	11
广西Guangxi	45 716.61	5.30	358.86	8
海南Hainan	9 513.04	1.10	73.01	22
重庆Chongqing	14 590.34	1.69	180.87	16
四川Sichuan	162 066.01	18.78	1 301.38	2
贵州Guizhou	25 276.31	2.93	196.86	14
云南Yunnan	158 717.28	18.39	1 266.35	3
西藏Xizang	201 601.32	23.36	1 663.19	1
陕西Shaanxi	37 125.18	4.30	293.96	9
甘肃Gansu	20 337.24	2.36	161.81	18
青海Qinghai	4 014.59	0.47	32.15	27
宁夏Ningxia	618.41	0.07	4.78	29
新疆Xinjiang	31 579.31	3.66	252.12	12
合计total	1 354 160.68	156.92	10 896.34

解释变量 explanatory variables	回归系数 regression coefficients	标准误差 standard error	t	P
X₁	-0.043^**	0.040	-1.610	0.002
X₂	0.080	0.056	0.840	0.159
X₃	0.046^**	0.005	2.680	<0.001
X₄	-0.017^**	0.029	-0.570	0.001
X₅	0.014^*	0.082	1.630	0.045
Cons	0.092	0.579	1.950	0.692

碳中和背景下的中国碳汇林业生产效率时空分异及影响因素研究

Spatiotemporal differentiation and influencing factors of forestry production efficiency with carbon sequestration in China under the context of carbon neutrality

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