Stand carbon stock growth model system for <i>Larix olgensis</i> plantation

He Xiao; Zhou Chaofan; Lei Xiangdong; Li Haikui

doi:10.12171/j.1000-1522.20210040

Journal of Beijing Forestry University > 2021 > 43(11): 1-10. > DOI: 10.12171/j.1000-1522.20210040

He Xiao, Zhou Chaofan, Lei Xiangdong, Li Haikui. Stand carbon stock growth model system for Larix olgensis plantation[J]. Journal of Beijing Forestry University, 2021, 43(11): 1-10. DOI: 10.12171/j.1000-1522.20210040

Citation:

PDF (918 KB)

Stand carbon stock growth model system for Larix olgensis plantation

Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Key Laboratory of Forest Management and Growth Modelling, National Forestry and Grassland Administration, Beijing 100091, China

More Information

Received Date: February 04, 2021
Revised Date: April 19, 2021
Available Online: October 19, 2021
Published Date: November 29, 2021

Graphical Abstract

Abstract

Abstract

Objective There are knowledge gaps on stand carbon stock growth model at present. This study developed a stand-level carbon stock growth model system to provide a method for dynamic estimation of regional forest carbon storage with time.
Method Taking Larix olgensis plantation in Jilin Province of northeastern China as the research object, the site quality classification algorithm was used to divide all sample plots into three site grades, which were introduced into the model system as dummy variables. The stand carbon stock growth model system was established by simultaneous equations to link stand average height, basal area growth model and stand carbon stock model. The adjusted coefficient of determination ( ${{R}}_{{\text{adj}}}^2$ ), the standard error of the estimated value (SEE) and the average prediction error (MPE) were used to evaluate model performance. The growth process of stand carbon stock under different site grades and stand density index (SDI), and the influence of stand basal area and average height on stand carbon stock were analyzed.
Result (1) The ${{R}}_{{\text{adj}}}^2$ of stand average height growth model, basal area growth model and carbon stock model were 0.892, 0.979 and 0.960, respectively, and the MPEs were both less than 2%. (2) Both procedures in the model system (inventory- and model-derived stand average height and basal area) could accurately estimate the stand carbon stock, and the difference was only 0.02 t/ha, so the model system had great generality and stability. (3) Stand carbon stock growth increased with the increasing site grade of sample plots. When the site grade was the same, the growth was slow with SDI less than 1 500 plant/ha; but there were no differences in the growth process among different SDIs larger than 1 500 plant/ha after 40 years, and the optimal SDI for maximum stand carbon stock was about 1 500−2 000 plant/ha. (4) The stand carbon stock increased with the increase of stand basal area and average height, and stand basal area had larger effects on stand carbon than stand average height.
Conclusion The growth of stand carbon stock is closely related to the site grade, stand average age, density, basal area and average height. The modeling approach of simultaneous equations is a feasible method for developing the stand carbon stock growth model system. The stand carbon stock growth model system developed by this study could effectively predict stand carbon stock, which providing a tool for understanding the growth of stand carbon stock and forest carbon sink assessment.
- stand carbon stock model,
- growth process,
- site grade,
- stand density,
- Larix olgensis plantation

FullText(HTML)

References (42)

References

[1]	Kindermann G, Obersteiner M, Sohngen B, et al. Global cost estimates of reducing carbon emissions through avoided deforestation[J]. Proceedings of the National Academy of Sciences of the United States of America, 2008, 105(30): 10302−10307. doi: 10.1073/pnas.0710616105
[2]	Pan Y, Birdsey R A, Fang J, et al. A large and persistent carbon sink in the world’s forests[J]. Science, 2011, 333: 988−993. doi: 10.1126/science.1201609
[3]	Dong L, Zhang L, Li F. Allometry and partitioning of individual tree biomass and carbon of Abies nephrolepis Maxim in northeast China[J]. Scandinavian Journal of Forest Research, 2016, 31(4): 399−411. doi: 10.1080/02827581.2015.1060257
[4]	Zhu H Y, Weng Y H, Zhang H G, et al. Comparing fast- and slow-growing provenances of Picea koraiensis in biomass, carbon parameters and their relationships with growth[J]. Forest Ecology and Management, 2013, 307: 178−185. doi: 10.1016/j.foreco.2013.06.024
[5]	Gao H, Dong L, Li F, et al. Evaluation of four methods for predicting carbon stocks of Korean pine plantations in Heilongjiang Province, China[J/OL]. PLoS One, 2015, 10(12): e0145017 [2020−12−19]. doi: 10.1371/journal.pone.0145017.
[6]	Gibbs H K, Brown S, Niles J O, et al. Monitoring and estimating tropical forest carbon stocks: making REDD a reality[J/OL]. Environmental Research Letters, 2007, 2(4): 045023 [2021−01−19]. https://iopscience.iop.org/article/10.1088/1748-9326/2/4/045023/meta.
[7]	Kauppi P E, Mielikäinen K, Kuusela K. Biomass and carbon budget of European forests, 1971 to 1990[J]. Science, 1992, 256: 70−74. doi: 10.1126/science.256.5053.70
[8]	Alexeyev V, Birdsey R, Stakanov V, et al. Carbon in vegetation of Russian forests: methods to estimate storage and geographical distribution[J]. Water, Air, & Soil Pollution, 1995, 82(1): 271−282.
[9]	Apps M J, Kurz W A, Beukema S J, et al. Carbon budget of the Canadian forest product sector[J]. Environmental Science and Policy, 1999, 2(1): 25−41. doi: 10.1016/S1462-9011(99)00006-4
[10]	李海奎, 雷渊才. 中国森林植被生物量和碳储量评估[M]. 北京: 中国林业出版社, 2010. Li H K, Lei Y C. Estimation and evaluation of forest biomass carbon storage in China[M]. Beijing: China Forestry Publishing House, 2010.
[11]	周丽, 张卫强, 唐洪辉, 等. 南亚热带中幼龄针阔混交林碳储量及其分配格局[J]. 生态环境学报, 2014, 23(4):568−574. doi: 10.3969/j.issn.1674-5906.2014.04.004 Zhou L, Zhang W Q, Tang H H, et al. Carbon storage and their allocation of young-and-middle aged conifer-broadleaf mixed forests in southern subtropical region[J]. Ecology and Environment Sciences, 2014, 23(4): 568−574. doi: 10.3969/j.issn.1674-5906.2014.04.004
[12]	胡海清, 罗碧珍, 魏书精, 等. 小兴安岭7种典型林型林分生物量碳密度与固碳能力[J]. 植物生态学报, 2015, 39(2):140−158. doi: 10.17521/cjpe.2015.0014 Hu H Q, Luo B Z, Wei S J, et al. Biomass carbon density and carbon sequestration capacity in seven typical forest types of the Xiaoxing’an Mountains, China[J]. Chinese Journal of Plant Ecology, 2015, 39(2): 140−158. doi: 10.17521/cjpe.2015.0014
[13]	胡海清, 罗碧珍, 魏书精, 等. 大兴安岭5种典型林型森林生物碳储量[J]. 生态学报, 2015, 35(17):5745−5760. Hu H Q, Luo B Z, Wei S J, et al. Estimating biological carbon storage of five typical forest types in the Daxing’anling Mountains, Heilongjiang, China[J]. Acta Ecologica Sinica, 2015, 35(17): 5745−5760.
[14]	何潇, 李海奎, 曹磊, 等. 退化森林生态系统中林分碳储量的驱动因素: 以内蒙古大兴安岭为例[J]. 林业科学研究, 2020, 33(2):69−76. He X, Li H K, Cao L, et al. The factors affecting carbon storage in degraded forest ecosystem: a case study from Daxing’anling areas of Inner Mongolia[J]. Forest Research, 2020, 33(2): 69−76.
[15]	贾炜玮, 孙赫明, 李凤日. 包含哑变量的黑龙江省落叶松人工林碳储量预测模型系统[J]. 应用生态学报, 2019, 30(3):814−822. Jia W W, Sun H M, Li F R. Prediction model system with dummy variables for carbon storage of larch plantation in Heilongjiang Province, China[J]. Chinese Journal of Applied Ecology, 2019, 30(3): 814−822.
[16]	黄晓强, 信忠保, 赵云杰, 等. 林龄和立地条件对北京山区油松人工林碳储量的影响[J]. 水土保持学报, 2015, 29(6):184−190. Huang X Q, Xin Z B, Zhao Y J, et al. Effects of stand ages and site conditions on carbon stock of Pinus tabuliformis plantations in Beijing mountainous area[J]. Journal of Soil and Water Conservation, 2015, 29(6): 184−190.
[17]	李娜娜, 牟长城, 郑瞳, 等. 立地类型对长白山天然白桦林生态系统碳储量的影响[J]. 林业科学研究, 2015, 28(5):618−626. doi: 10.3969/j.issn.1001-1498.2015.05.003 Li N N, Mu C C, Zheng T, et al. Effect of site types on carbon storage of natural white birch forest ecosystem in Changbai Mountains, Northeast China[J]. Forest Research, 2015, 28(5): 618−626. doi: 10.3969/j.issn.1001-1498.2015.05.003
[18]	郑瞳, 牟长城, 张毅, 等. 立地类型对张广才岭天然白桦林生态系统碳储量的影响[J]. 生态学报, 2016, 36(19):6284−6294. Zheng T, Mou C C, Zhang Y, et al. Effects of site condition on ecosystem carbon storage in a natural Betula platyphylla forest in the Zhangguangcai Mountains, China[J]. Acta Ecologica Sinica, 2016, 36(19): 6284−6294.
[19]	Reineke L H. Perfecting a stand-density index for even-aged forests[J]. Journal of Agricultural Research, 1933, 46(7): 627−638.
[20]	国家林业局. 立木生物量模型及碳计量参数落叶松(LY/T 2654−2016)[S]. 北京: 中国标准出版社, 2016. State Forestry Administration. Tree biomass models and related parameters to carbon accounting for Larix (LY/T 2654−2016)[S]. Beijing: China Standard Press, 2016.
[21]	陈传国, 朱俊凤. 东北主要林木生物量手册[M]. 北京: 中国林业出版社, 1989. Chen C G, Zhu J F. Biomass tables for main tree species in northeast China[M]. Beijing: China Forestry Publishing House, 1989.
[22]	Wang C. Biomass allometric equations for 10 co-occurring tree species in Chinese temperate forests[J]. Forest Ecology and Management, 2006, 222(1−3): 9−16. doi: 10.1016/j.foreco.2005.10.074
[23]	IPCC. IPCC guidelines for national greenhouse gas inventories[M]. Tokyo: Institute for Global Environmental Strategies (IGES), 2006.
[24]	唐守正. 广西大青山马尾松全林整体生长模型及其应用[J]. 林业科学研究, 1991, 4(增刊): 8−13. Tang S Z. Integrated stand growth model and its application of masson pine in Guangxi Daqingshan[J]. Forest Research, 1991, 4(Suppl.): 8−13.
[25]	Li H, Zhao P. Improving the accuracy of tree-level aboveground biomass equations with height classification at a large regional scale[J]. Forest Ecology and Management, 2013, 289: 153−163. doi: 10.1016/j.foreco.2012.10.002
[26]	雷相东, 唐守正, 符利勇. 森林立地质量定量评价: 理论、方法、应用[M]. 北京: 中国林业出版社, 2020. Lei X D, Tang S Z, Fu L Y. Quantitative evaluation of forest site quality: theory, method, application[M]. Beijing: China Forestry Publishing House, 2020.
[27]	唐守正, 张会儒, 胥辉. 相容性生物量模型的建立及其估计方法研究[J]. 林业科学, 2000, 36(增刊):19−27. Tang S Z, Zhang H R, Xu H. Study on establish and estimate method of compatible biomass model[J]. Scientia Silvae Sinicae, 2000, 36(Suppl.): 19−27.
[28]	董利虎, 李凤日, 宋玉文. 东北林区4个天然针叶树种单木生物量模型误差结构及可加性模型[J]. 应用生态学报, 2015, 26(3):704−714. Dong L H, Li F R, Song Y W. Error structure and additivity of individual tree biomass model for four natural conifer species in Northeast China[J]. Chinese Journal of Applied Ecology, 2015, 26(3): 704−714.
[29]	唐守正, 郎奎建, 李海奎. 统计和生物数学模型计算(ForStat教程) [M]. 北京: 科学出版社, 2009. Tang S Z, Lang K J, Li H K. Statistics and computation of biomathematical models (ForStat textbook)[M]. Beijing: Science Press, 2009.
[30]	曾伟生, 唐守正. 非线性模型对数回归的偏差校正及与加权回归的对比分析[J]. 林业科学研究, 2011, 24(2):137−143. Zeng W S, Tang S Z. Bias correction in logarithmic regression and comparison with weighted regression for non-linear models[J]. Forest Research, 2011, 24(2): 137−143.
[31]	曾伟生, 唐守正. 立木生物量方程的优度评价和精度分析[J]. 林业科学, 2011, 47(11):106−113. doi: 10.11707/j.1001-7488.20111117 Zeng W S, Tang S Z. Goodness evaluation and precision analysis of tree biomass equations[J]. Scientia Silvae Sinicae, 2011, 47(11): 106−113. doi: 10.11707/j.1001-7488.20111117
[32]	曹磊, 刘晓彤, 李海奎, 等. 广东省常绿阔叶林生物量生长模型[J]. 林业科学研究, 2020, 33(5):61−67. Cao L, Liu X T, Li H K, et al. Biomass growth models for evergreen broadleaved forests in Guangdong[J]. Forest Research, 2020, 33(5): 61−67.
[33]	Yuan Z, Ali A, Jucker T, et al. Multiple abiotic and biotic pathways shape biomass demographic processes in temperate forests[J/OL]. Ecology, 2019, 100(5): e02650 [2021−01−14]. doi: 10.1002/ecy.2650.
[34]	Cannell M G R. Woody biomass of forest stands[J]. Forest Ecology and Management, 1984, 8(3−4): 299−312. doi: 10.1016/0378-1127(84)90062-8
[35]	Rahman M M, Kabir M E, Akon A S M J U, et al. High carbon stocks in roadside plantations under participatory management in Bangladesh[J]. Global Ecology and Conservation. 2015, 3: 412−423.
[36]	Khan M N I, Shil M C, Azad M S, et al. Allometric relationships of stem volume and stand level carbon stocks at varying stand density in Swietenia macrophylla King plantations, Bangladesh[J]. Forest Ecology and Management, 2018, 430: 639−648. doi: 10.1016/j.foreco.2018.09.002
[37]	Khan M N I, Islam M R, Rahman A, et al. Allometric relationships of stand level carbon stocks to basal area, tree height and wood density of nine tree species in Bangladesh[J/OL]. Global Ecology and Conservation, 2020, 22: e01025 [2021−01−17]. doi: 10.1016/j.gecco.2020.e01025.
[38]	Dong L, Zhang L, Li F. Evaluation of stand biomass estimation methods for major forest types in the eastern Daxing’an Mountains, northeast China[J/OL]. Forests, 2019, 10(9): 715 [2021−01−12]. https://doi.org/10.3390/f10090715.
[39]	Castedo-Dorado F, Gómez-García E, Diéguez-Aranda U, et al. Aboveground stand-level biomass estimation: a comparison of two methods for major forest species in northwest Spain[J]. Annals of Forest Science, 2012, 69(6): 735−746. doi: 10.1007/s13595-012-0191-6
[40]	Wu H, Xiang W, Fang X, et al. Tree functional types simplify forest carbon stock estimates induced by carbon concentration variations among species in a subtropical area[J]. Scientific Reports, 2017, 7(1): 1−11. doi: 10.1038/s41598-016-0028-x
[41]	雷相东, 符利勇, 李海奎, 等. 基于林分潜在生长量的立地质量评价方法与应用[J]. 林业科学, 2018, 54(12):116−126. doi: 10.11707/j.1001-7488.20181213 Lei X D, Fu L Y, Li H K, et al. Methodology and applications of site quality assessment based on potential mean annual increment[J]. Scientia Silvae Sinicae, 2018, 54(12): 116−126. doi: 10.11707/j.1001-7488.20181213
[42]	王秀云, 孙玉军, 马炜. 不同密度长白落叶松林生物量与碳储量分布特征[J]. 福建林学院学报, 2011, 31(3):221−226. doi: 10.3969/j.issn.1001-389X.2011.03.007 Wang X Y, Sun Y J, Ma W. Biomass and carbon storage distribution of different density in Larix olgensis plantation[J]. Journal of Fujian College of Forestry, 2011, 31(3): 221−226. doi: 10.3969/j.issn.1001-389X.2011.03.007

[1]	Jiang Jun, Chen Changqi, Chen Beibei, Wang Hao, Hu Dongyang, Zhang Yong, Zhang Yongfu, Li Jie, Zheng Junpeng. Effects of stand density on carbon, nitrogen, and phosphorus stoichiometry and nutrient resorption of Platycladus orientalis plantations in rocky mountainous area of Beijing[J]. Journal of Beijing Forestry University, 2024, 46(10): 33-41. DOI: 10.12171/j.1000-1522.20240011
[2]	Jin Xiaojuan, Sun Yujun, Pan Lei. Prediction model of base diameter of primary branch for Larix olgensis based on mixed effects[J]. Journal of Beijing Forestry University, 2020, 42(10): 1-10. DOI: 10.12171/j.1000-1522.20200133
[3]	Wang Yansong, Ma Baoming, Gao Haiping, Wang Baitian, Li Sha, Dong Xiuqun. Response of soil nutrients and their stoichiometric ratios to stand density in Pinus tabuliformis and Robinia pseudoacacia plantations in the loess region of western Shanxi Province, northern China[J]. Journal of Beijing Forestry University, 2020, 42(8): 81-93. DOI: 10.12171/j.1000-1522.20190287
[4]	Jia Weiwei, Feng Wanju, Li Fengri. Number of missing-rings in branch of Larix olgensis plantation based on knots’ section data analysis[J]. Journal of Beijing Forestry University, 2020, 42(3): 87-98. DOI: 10.12171/j.1000-1522.20190038
[5]	Jin Suo, Bi Haojie, Liu Jia, Liu Yuhang, Wang Yu, Qi Jinqiu, Hao Jianfeng. Effects of stand density on community structure and species diversity of Cupressus funebris plantation in Yunding Mountain, southwestern China[J]. Journal of Beijing Forestry University, 2020, 42(1): 10-17. DOI: 10.12171/j.1000-1522.20190202
[6]	WANG Man-lin, DONG Li-hu, LI Feng-ri. First-order branch number simulation for Larix olgensis plantation through Poisson regression mixed effect model[J]. Journal of Beijing Forestry University, 2017, 39(11): 45-55. DOI: 10.13332/j.1000-1522.20170204
[7]	SHAO Ying-nan, TIAN Song-yan, LIU Yan-kun, CHEN Yao, SUN Zhi-hu. Effects of density control on soil respiration in Larix olgensis plantation.[J]. Journal of Beijing Forestry University, 2017, 39(6): 51-59. DOI: 10.13332/j.1000-1522.20170029
[8]	NA Meng, LIU Ting-yan, ZHANG Yan-dong, FENG Chen-xin, LIU Dao-kun. Effects of stock density on carbon storage in Fraxinus mandshurica plantations[J]. Journal of Beijing Forestry University, 2017, 39(1): 20-26. DOI: 10.13332/j.1000-1522.20160111
[9]	LIU Yu, GUO Jian-bin, WANG Yan-hui, LIU Ze-bin, DENG Xiu-xiu, ZHANG Tong, XIONG Wei, ZUO Hai-jun. Hydrological effects of forest litter of Larix principis-rupprechtii plantations with varying densities in Liupan Mountains of Ningxia, China.[J]. Journal of Beijing Forestry University, 2016, 38(8): 36-44. DOI: 10.13332/j.1000-1522.20160007
[10]	XU Cheng-yang, ZHANG Hua, JIA Zhong-kui, XUE Kang, DU Peng-zhi, WANG Jing-guo. Effects of stand density and site types on root characteristics of Platycladus orientalis plantations in Beijing mountainous area[J]. Journal of Beijing Forestry University, 2007, 29(4): 95-99. DOI: 10.13332/j.1000-1522.2007.04.022

Cited By

Cited by

Periodical cited type(9)

1.	邹佳何，王海燕，李成铭，崔雪，赵晗，陈悦，董齐琪，侯文宁. 长白山北坡不同林分类型细根-土壤C、N、P化学计量特征. 生态学杂志. 2024(01): 170-177 .
2.	冉佳璇，戚玉娇. 黔中马尾松木荷混交林树高-胸径模型. 浙江农林大学学报. 2024(02): 343-352 .
3.	卢灵锋，林辉，龙江平. 不同经营目标下的芦头林场杉木人工林经济效益分析. 湖南林业科技. 2023(01): 63-72 .
4.	冯宜明，吕春燕，王零，赵维俊，马雪娥，杜军林，何俊龄. 不同林分密度青海云杉林碳氮储量及其分配格局. 干旱区地理. 2023(07): 1133-1144 .
5.	张凌宇，赵庆，吴晓君，许东先，罗皓，谢进金. 广东西樵山国家森林公园森林碳储量空间分布研究. 森林工程. 2023(05): 48-56 .
6.	曾予心，苏建兰. 碳汇造林投入产出效益研究综述. 山东林业科技. 2023(06): 119-124 .
7.	刘延坤，李云红，陈瑶，刘玉龙，田松岩. 坡位对不同密度长白落叶松人工林生态系统碳储量的影响. 贵州农业科学. 2022(07): 133-140 .
8.	王飞平，张加龙. 基于碳卫星的森林碳储量估测研究综述. 世界林业研究. 2022(06): 30-35 .
9.	冯宜明，王零，赵维俊，吕春燕. 不同林分密度云杉人工林碳储量及其分配格局. 中南林业科技大学学报. 2022(12): 112-121+174 .

Other cited types(9)

Get Citation

PDF

XML

Article views (1709) PDF downloads (366) Cited by(18)

Turn off MathJax

Article Contents

Abstract

References

Stand carbon stock growth model system for Larix olgensis plantation