Advanced search
    Wang Tao, Dong Lingbo, Liu Zhaogang, Zhang Lingyu, Chen Ying. Optimization of replanting space of natural secondary forest in Daxing’anling Mountains of northeastern China[J]. Journal of Beijing Forestry University, 2019, 41(5): 127-136. DOI: 10.13332/j.1000-1522.20190025
    Citation: Wang Tao, Dong Lingbo, Liu Zhaogang, Zhang Lingyu, Chen Ying. Optimization of replanting space of natural secondary forest in Daxing’anling Mountains of northeastern China[J]. Journal of Beijing Forestry University, 2019, 41(5): 127-136. DOI: 10.13332/j.1000-1522.20190025

    Optimization of replanting space of natural secondary forest in Daxing’anling Mountains of northeastern China

    More Information
    • Received Date: January 14, 2019
    • Revised Date: March 03, 2019
    • Available Online: May 07, 2019
    • Published Date: April 30, 2019
    • ObjectiveThis paper aims to optimize the spatial structure of stand, improve the quality of existing stands, accelerate the restoration of forest ecosystems, accelerate the succession of forest communities to top communities in the Daxing’anling Mountains of northeastern China, and determine the replanting species and replanting sites of natural secondary forests.
      MethodTaking three typical forest types of birch, birch-larch mixed forest and larch coniferous mixed forest in the Daxing’anling area as an example, based on the natural regeneration of the secondary forest, the Voronoi diagram was used to determine the spatial unit and correct the edge by Voronoi nodal. The inverse distance weighted method was used to visualize the spatial structure parameters of the forest, and the spatial structure information of the forest area was not included in the forest stand and it was used as the basis for replanting. The entropy method was used to determine the weight of each spatial structure parameter, and the image interpolated by spatial structure parameters was weighted superimposed. With the non-spatial structure as the constraint and the optimization of the stand structure, we discussed the species and location of replanting trees under canopy of secondary forest, and provide theoretical support and methods for forest management in the Daxing'anling Mountains.
      Result(1) Larix gmelinii was selected as replanting tree species. The number of replanting trees of each forest type was 660, 1 970, 315, respectively. (2) After the replanting, the mingling degree of birch seedings and saplings in the pure birch forest increased to 0.52, and that of other tree species seedings and saplings increased to 0.51. The mingling degree of birch seedings and saplings in larch and birch mixed forest increased to 0.84, and that of other tree species seedings and saplings increased to 0.70; the mingling degree of birch species seedings and saplings in larch mixed coniferous forest increased to 0.78, and the mingling degree of other tree species seedings and saplings increased to 0.50. (3) After replanting, the coefficients of variation of the Voronoi diagram polygons of forest seedings and saplings under canopy of each forest type were 1.31, 1.41, 1.36, and they were all in random distribution state. The variation coefficient of the Voronoi diagram polygon of larch tree seedings and saplings in the pure birch forest, larch and birch mixed forest and larch mixed coniferous forest was 1.27, 1.40 and 1.37, respectively, they were also all in random distribution state.
      ConclusionHarvesting and replanting are two opposite spatial optimization methods. The inverse distance weight of the spatial structure parameters of trees can predict the spatial structure parameters of non-forest areas in forests. The interpolated image pixel size can be set to the forest area for replanting trees. According to the optimization goal of stand spatial structure and the regulation goal of replanting quantity, extracting the spatial structure parameter value of forest area that does not contain tree, we can determine the species and location of the replanted forest under the canopy.
    • [1]
      Fang J. Changes in forest biomass carbon storage in China between 1949 and 1998[J]. Science, 2001, 292: 2320−2322. doi: 10.1126/science.1058629
      [2]
      吕英. 大兴安岭林区生态可持续发展问题研究[D]. 北京: 中国农业科学院, 2009.

      Lü Y. Research on sustainable development strategy for Daxing ’anling forests region[D]. Beijing: Gradeuate School of Chinese Academy Agricultural Sciences, 2009.
      [3]
      Yu D, Zhou L, Zhou W, et al. Forest management in Northeast China: history, problems, and challenges[J]. Environmental Management, 2011, 48(6): 1122−1135. doi: 10.1007/s00267-011-9633-4
      [4]
      于立忠, 刘利芳, 王绪高, 等. 东北次生林生态系统保护与恢复技术探讨[J]. 生态学杂志, 2017, 36(11):3243−3248.

      Yu L Z, Liu L F, Wang X G, et al. Discussion on the protcetion and restoration technology of secondary forest esosystems in Northeast China[J]. Chinese Journal of Ecology, 2017, 36(11): 3243−3248.
      [5]
      Deng X Z, Jiang Q, Zhan J Y, et al. Simulation on the dynamics of forest area changes in Northeast China[J]. Journal of Geographical Sciences, 2010, 20(4): 495−509. doi: 10.1007/s11442-010-0495-0
      [6]
      赵春燕, 李际平. 基于Voronoi图与Delaunay3角网的杉木人工纯林林木补植位置与空间配置[J]. 中南林业科技大学学报, 2017, 37(2):1−8.

      Zhao C Y, Li J P. Spatial location and allocation of replanting trees on pure Chinese fir plantation based on Voronoi diagram and Delaunay triangulation[J]. Journal of Central South University of Forestry & Technology, 2017, 37(2): 1−8.
      [7]
      Nordlander G, Hellqvist C, Hjelm K. Replanting conifer seedlings after pine weevil emigration in spring decreases feeding damage and seedling mortality[J]. Scandinavian Journal of Forest Research, 2017, 32(1): 60−67. doi: 10.1080/02827581.2016.1186220
      [8]
      Sofawi A B, Rozainah M Z, Normaniza O, et al. Mangrove rehabilitation on Carey Island, Malaysia: an evaluation of replanting techniques and sediment properties[J]. Marine Biology Research, 2017, 13(4): 390−401. doi: 10.1080/17451000.2016.1267365
      [9]
      宋启亮, 董希斌. 大兴安岭低质阔叶混交林不同改造模式综合评价[J]. 林业科学, 2014, 50(9):18−25.

      Song Q L, Dong X B. Comprehensive evaluation of different transformation models of low-quality broadleaved mixed forest in Daxing ’an Mountains[J]. Scientia Silvae Sincae, 2014, 50(9): 18−25.
      [10]
      汤孟平, 唐守正, 雷相东, 等. 林分择伐空间结构优化模型研究[J]. 林业科学, 2004, 40(5):25−31. doi: 10.3321/j.issn:1001-7488.2004.05.004

      Tang M P, Tang S Z, Lei X D, et al. Study on spatial structure optimizing model of stand selection cuttuing[J]. Scientia Silvae Sincae, 2004, 40(5): 25−31. doi: 10.3321/j.issn:1001-7488.2004.05.004
      [11]
      姜廷山, 董灵波, 刘兆刚, 等. 不同抚育强度对兴安落叶松林空间结构的影响[J]. 东北林业大学学报, 2018, 46(12):9−14. doi: 10.3969/j.issn.1000-5382.2018.12.002

      Jiang T S, Dong L B, Liu Z G, et al. Effects of different intermediate cutting intensities on the spatial structure of Larix gmelinii forest[J]. Journal of Northeast Forestry University, 2018, 46(12): 9−14. doi: 10.3969/j.issn.1000-5382.2018.12.002
      [12]
      李际平, 封尧, 赵春燕, 等. 基于Voronoi图的杉木生态公益林空间结构量化分析[J]. 北京林业大学学报, 2014, 36(4):1−7.

      Li J P, Feng Y, Zhao C Y, et al. Quantitative analysis of stand spatial structure of Cunninghamia lanceolate non-commercial forest based on Voronoi diagram[J]. Journal of Beijing Forestry University, 2014, 36(4): 1−7.
      [13]
      刘帅, 张江, 李建军, 等. 森林空间结构分析中基于Voronoi图的样地边缘校正[J]. 林业科学, 2017, 53(1):28−37.

      Liu S, Zhang J, Li J J, et al. Edge correction of voronoi diagram in forest spatial structure analysis[J]. Scientia Silvae Sincae, 2017, 53(1): 28−37.
      [14]
      董灵波, 刘兆刚, 马妍, 等. 天然林林分空间结构综合指数的研究[J]. 北京林业大学学报, 2013, 35(1):16−22.

      Dong L B, Liu Z G, Ma Y, et al. A new composite index of stand spatial structure for natural forest[J]. Journal of Beijing Forestry University, 2013, 35(1): 16−22.
      [15]
      汤孟平, 陈永刚, 施拥军, 等. 基于Voronoi图的群落优势树种种内种间竞争[J]. 生态学报, 2007, 27(11):4707−4716. doi: 10.3321/j.issn:1000-0933.2007.11.039

      Tang M P, Chen Y G, Shi Y J, et al. Intranspecific and interspecific competition analysis of community dominant plant populations based on Voronoi diagram[J]. Acta Ecologica Sinica, 2007, 27(11): 4707−4716. doi: 10.3321/j.issn:1000-0933.2007.11.039
      [16]
      汤孟平, 周国模, 陈永刚, 等. 基于Voronoi图的天目山常绿阔叶林混交度[J]. 林业科学, 2009, 45(6):1−5. doi: 10.3321/j.issn:1001-7488.2009.06.001

      Tang M P, Zhu G M, Chen Y G, et al. Mingling of evergreen broad-leaved forests in Tianmu Mountain[J]. Scientia Silvae Sincae, 2009, 45(6): 1−5. doi: 10.3321/j.issn:1001-7488.2009.06.001
      [17]
      张弓乔, 惠刚盈. Voronoi多边形的边数分布规律及其在林木格局分析中的应用[J]. 北京林业大学学报, 2015, 37(4):1−7.

      Zhang G Q, Hui G Y. Analysis and application of polygon side distribution of Voronoi diagram in tree patterns[J]. Journal of Beijing Forestry University, 2015, 37(4): 1−7.
      [18]
      董灵波, 刘兆刚. 樟子松人工林空间结构优化及可视化模拟[J]. 林业科学, 2012, 48(10):77−85. doi: 10.11707/j.1001-7488.20121013

      Dong L B, Liu Z G. Visual management simulation for Pinus sylvestris var. mongolica plantation based on optimized spatial structure[J]. Scientia Silvae Sincae, 2012, 48(10): 77−85. doi: 10.11707/j.1001-7488.20121013
      [19]
      张家诚, 陈力, 蒋有绪, 等. 演替顶极阶段森林群落优势树种分布的变动趋势研究[J]. 植物生态学报, 1999, 23(3):256−268. doi: 10.3321/j.issn:1005-264X.1999.03.008

      Zhang J C, Chen L, Jiang Y X, et al. Research on the chang treed of dominant tree population distribution patterns during development process of climax forest communities[J]. Acta Phytoecologica Sinica, 1999, 23(3): 256−268. doi: 10.3321/j.issn:1005-264X.1999.03.008
      [20]
      惠刚盈, Klaus von Gadow, Matthias Albert. 角尺度: 一个描述林木个体分布格局的结构参数[J]. 林业科学, 1999, 35(1):37−42. doi: 10.3321/j.issn:1001-7488.1999.01.006

      Hui G y, von Gadow K, Albert M. The neighbourhood pattern: a new structure papameter for describing distribution of forest tree position[J]. Scientia Silvae Sincae, 1999, 35(1): 37−42. doi: 10.3321/j.issn:1001-7488.1999.01.006
      [21]
      惠刚盈, 胡艳波. 混交林树种空间隔离程度表达方式的研究[J]. 林业科学研究, 2001, 14(1):23−27. doi: 10.3321/j.issn:1001-1498.2001.01.004

      Hui G Y, Hu Y B. Study on the expression of spatial isolation degree of mixed forest tree species[J]. Forest Research, 2001, 14(1): 23−27. doi: 10.3321/j.issn:1001-1498.2001.01.004
      [22]
      惠刚盈, Klaus von Gadow, Matthias Albert. 一个新的林分空间结构参数: 大小比数[J]. 林业科学研究, 1999, 12(1):1−6. doi: 10.3321/j.issn:1001-1498.1999.01.001

      Hui G Y, von Gadow K, Albert M. A new stand space structure parameter: neighborhood comparsion[J]. Forest Research, 1999, 12(1): 1−6. doi: 10.3321/j.issn:1001-1498.1999.01.001
      [23]
      吕勇, 臧颢, 万献军, 等. 基于林层指数的青椆混交林林层结构研究[J]. 林业资源管理, 2012(3):81−84. doi: 10.3969/j.issn.1002-6622.2012.03.018

      Lü Y, Zang H, Wan X J, et al. Storey structure study of Cyclobalanopsis Myrsinaefolia mixed stand based on storey index[J]. Forest Resources Management, 2012(3): 81−84. doi: 10.3969/j.issn.1002-6622.2012.03.018
      [24]
      Pielou E C. Segregation and symmetry in two-species populations as studied by nearest-neighbour relationships[J]. Journal of Ecology, 1961, 49(2): 255−269. doi: 10.2307/2257260
      [25]
      von Gadow K. Zur bestandesbeschreibung in der forsteinrichtung[J]. Forst und Holz, 1993, 48(21): 602−606.
      [26]
      牟乃夏. ARCGIS 10地理信息系统教程[M]. 北京: 测绘出版社, 2012.

      Mou N X. ARCGIS 10 GIS tutorial[M]. Beijing: Surveying and Mapping Publishing House, 2012.
      [27]
      高真, 叶学义, 周天琪, 等. 基于反距离加权插值的水声数据可视化算法[J]. 计算机工程, 2015, 41(9):266−270. doi: 10.3969/j.issn.1000-3428.2015.09.049

      Gao Z, Ye X Y, Zhou T Q, et al. Visualization algorithm of underwater acoustic data based on inverse distance weught interpolation[J]. Computer Engineering, 2015, 41(9): 266−270. doi: 10.3969/j.issn.1000-3428.2015.09.049
      [28]
      肖进胜, 饶天宇, 贾茜, 等. 基于图切割的拉普拉斯金字塔图像融合算法[J]. 光电子·激光, 2014, 25(7):1416−1424.

      Xiao J S, Rao T Y, Jia Q, et al. An image fusion algorithm of Laplacian pyramid based on graph cutting[J]. Journal of Optoelectronics·Laser, 2014, 25(7): 1416−1424.
      [29]
      汪玉美, 陈代梅, 赵根保. 基于目标提取与拉普拉斯变换的红外和可见光图像融合算法[J]. 激光与光电子学进展, 2017(1):104−112.

      Wang Y M, Chen D M, Zhao G B. Image fusion algorithm of infrared and visible images based on target extraction and laplace transformation[J]. Laser & Optoelectronics Progress, 2017(1): 104−112.
      [30]
      Tsujino R, Yumoto T. Spatial distribution patterns of trees at different life stages in a warm temperate forest[J]. Journal of Plant Research, 2007, 120(6): 687−695. doi: 10.1007/s10265-007-0111-2
      [31]
      Li L P, Cadotte M W, Martínez-Garza C, et al. Planting accelerates restoration of tropical forest but assembly mechanisms appear insensitive to initial composition[J]. Journal of Applied Ecology, 2018, 55(26): 986−996.
      [32]
      杨朝应. 大兴安岭天然落叶松森林健康经营模式研究[D]. 哈尔滨: 东北林业大学, 2014.

      Yang C Y. Study on forest healthy management in nature Larix dahurica in Great Xing ’an Mountain[D]. Harbin: Northeast Forestry University, 2014.
    • Related Articles

      [1]Zhang Lanqi, Li Li, Yang Hua, Xie Yi. Stand structure optimization and adjustment of natural forest in Changbai Mountains based on AHP-CRITIC combination weight method[J]. Journal of Beijing Forestry University, 2023, 45(8): 74-83. DOI: 10.12171/j.1000-1522.20220479
      [2]Liu Zhe, Zheng Xi. Parametric design of close-to-nature forest landscape spatial structure[J]. Journal of Beijing Forestry University, 2023, 45(6): 100-107. DOI: 10.12171/j.1000-1522.20220010
      [3]Sheng Qi, Dong Lingbo, Liu Zhaogang. Stand spatial structure optimization combined with habitat suitability of great spotted woodpecker[J]. Journal of Beijing Forestry University, 2021, 43(5): 24-32. DOI: 10.12171/j.1000-1522.20200141
      [4]Lin Fucheng, Wang Weifang, Men Xiuli, Sun Yusen, Li Guochun, Liu Dandan. Spatial structure optimal of Larix gmelinii plantation[J]. Journal of Beijing Forestry University, 2021, 43(4): 68-76. DOI: 10.12171/j.1000-1522.20200228
      [5]He Jingyuan, Wang Xinjie, Wang Kai, Guo Weiwei, Liu Li, Wang Fuzeng. Multivariate distribution of spatial structure parameters of Populus davidiana-Betula platyphylla secondary forest[J]. Journal of Beijing Forestry University, 2021, 43(2): 22-33. DOI: 10.12171/j.1000-1522.20200076
      [6]Chen Keyi, Zhang Huiru, Zhang Bo, He Youjun. Spatial distribution simulation of recruitment trees of natural secondary forest based on geographically weighted regression[J]. Journal of Beijing Forestry University, 2021, 43(2): 1-9. DOI: 10.12171/j.1000-1522.20200157
      [7]Hu Xuefan, Zhang Huiru, Zhou Chaofan, Zhang Xiaohong. Effects of different thinning patterns on the spatial structure of Quercus mongolica secondary forests[J]. Journal of Beijing Forestry University, 2019, 41(5): 137-147. DOI: 10.13332/j.1000-1522.20190037
      [8]Zhang Ganggang, Liu Ruihong, Hui Gangying, Zhang Gongqiao, Zhao Zhonghua, Hu Yanbo. N-variate distribution and its annotation on forest spatial structural parameters: a case study of Quercus aliena var. acuteserrata natural mixed forest in Xiaolong Mountains, Gansu Province of northwestern China[J]. Journal of Beijing Forestry University, 2019, 41(4): 21-31. DOI: 10.13332/j.1000-1522.20180228
      [9]LÜ Yan-jie, YANG Hua, ZHANG Qing, WANG Quan-jun, SUN Quan. Effects of spatial structure on DBH increment of natural spruce-fir forest[J]. Journal of Beijing Forestry University, 2017, 39(9): 41-47. DOI: 10.13332/j.1000-1522.20170184
      [10]DONG Ling-bo, LIU Zhao-gang, MA Yan, NI Bao-long, LI Yuan. A new composite index of stand spatial structure for natural forest.[J]. Journal of Beijing Forestry University, 2013, 35(1): 16-22.
    • Cited by

      Periodical cited type(99)

      1. 许馨元,田刚,唐铭野. 中俄两国森林碳汇合作潜力及绿色效应研究. 商业经济. 2025(01): 80-83 .
      2. 段晓梅,章程,李松青,甘晓丽. 岩溶碳汇产品价值实现路径研究. 生态经济. 2025(02): 22-28 .
      3. 刘贤赵,罗政英,王一笛. 长株潭绿心区碳汇能力时空格局及多情景预测. 应用生态学报. 2025(02): 559-568 .
      4. 胡茸茸,郭杨,欧阳勋志,刘军,潘萍. 赣中杉木林碳密度空间分布格局及其影响因素. 生态学杂志. 2025(02): 365-372 .
      5. 辛守英,王晓红,焦琳琳. 基于遥感数据和优化Blending算法的人工林地上生物量估算研究. 西北林学院学报. 2025(02): 207-219 .
      6. 付甜,杨佳伟,王晓荣,胡兴宜,陈明震,漆小兵,胡定邦. 基于森林资源二类调查数据的县域森林碳汇估算及潜力预测. 环境生态学. 2025(03): 43-47+90 .
      7. 聂薇,邓华锋. 使用二类调查数据对森林碳储量评估及多因素预测. 东北林业大学学报. 2024(02): 52-59 .
      8. 裴薇薇,杨喆,王云英,王新,杜岩功. 祁连山区青海云杉林碳汇特征及调控因子. 中国农业科技导报. 2024(01): 226-233 .
      9. 徐思若,成志影,那雪迎,张栩嘉,马大龙,张鹏. 黑龙江省森林碳汇及其经济价值的变化分析与潜力预测. 生态学杂志. 2024(01): 197-205 .
      10. 王立国,朱海,叶炎婷,贺焱,宋薇. 中国省域旅游业碳中和时空分异与模拟. 生态学报. 2024(02): 625-636 .
      11. 高怡凡,杨志衍,彭荣开,孙子芸,高培超,宋长青. 森林蓄积量的碳达峰行动目标与经济发展期望对福建省土地利用/覆被的权衡影响. 北京师范大学学报(自然科学版). 2024(01): 129-137 .
      12. 李郊,王冰,王晨,高鹤,吴辉龙,郑鑫,彭华福. 2005—2020年江西省森林碳储量时空变化趋势及影响因素. 林草资源研究. 2024(01): 17-24 .
      13. 游景晖,欧阳勋志,李坚锋,毛述震,潘萍. 闽楠天然次生林不同林层碳密度变化特征及其影响因素. 东北林业大学学报. 2024(04): 89-94 .
      14. 石铁矛,高杨,王迪. 双碳目标下城市空间碳固存与增汇路径研究. 沈阳建筑大学学报(自然科学版). 2024(02): 193-202 .
      15. 杨俊豪,张皓东,李永昌,刘书敏. 基于可加性模型的云南松和华山松碳储量模型构建. 昆明理工大学学报(自然科学版). 2024(02): 140-150 .
      16. 张自强,周伟,杨重玉. 碳中和背景下森林采伐限额对中国森林碳汇影响的空间效应. 统计与决策. 2024(08): 84-88 .
      17. 陈文汇,李华. 林草生态系统固碳增汇的增长潜力及交易机制. 科技导报. 2024(07): 93-102 .
      18. 刘世荣,王晖,李海奎,余振,栾军伟. 碳中和目标下中国森林碳储量、碳汇变化预估与潜力提升途径. 林业科学. 2024(04): 157-172 .
      19. 蔡为民,王燕秋,林国斌,霍长宝,孙晓兵,王萌萌. 基于“资源-资产-资本-资金”转化路径的森林碳汇价值实现机制. 中国人口·资源与环境. 2024(03): 60-67 .
      20. 吕洁华,杨廷瑜. 基于“脱碳”视角的中国省际低碳效率时空分异研究. 生态经济. 2024(06): 13-20+29 .
      21. 孙晓驰,朱洁,周松. 京津冀城市群碳足迹压力空间关联网络结构及影响因素研究. 统计与管理. 2024(03): 4-17 .
      22. 黄超群,梁波,何英姿,李震,刘春花. 广西国有七坡林场森林碳汇价值评价. 林业调查规划. 2024(03): 71-75 .
      23. 袁天健,霍礼鑫,王芳,过建春,柯佑鹏. “两山”理念下海南省森林固碳量与影响因素分析. 林业经济问题. 2024(01): 51-58 .
      24. 那雪迎. 中国森林碳储量变化及固碳潜力的研究. 现代园艺. 2024(15): 59-63 .
      25. 王春晓,邓孟婷,汪雪飞,洪武扬. 基于PLUS-InVEST模型的碳储量时空演变与预测模拟. 中国园林. 2024(06): 70-76 .
      26. 肖嘉文,刘金福,郑雯,王智苑,方梦凡,洪宇,谭芳林. 1974—2018年福建省森林碳储量特征及动态变化. 植物资源与环境学报. 2024(04): 101-108 .
      27. 朱娘金,钟德君,李海滨,罗攀峰,刘荣杰,吴林芳,张蒙. 莲花山白盆珠省级自然保护区2017年——2023年森林动态变化研究. 热带林业. 2024(02): 77-81 .
      28. 吴伟光,许骞骞,羊凌玉,刘宇. 林业增汇潜力及其对中国碳中和的经济影响分析. 农业技术经济. 2024(08): 128-144 .
      29. 李元会,吴富雨,刘燕云,余海清,文嫱,刘韩. 甘孜州林业碳汇资源分析及开发策略. 现代农业科技. 2024(16): 76-80+95 .
      30. 张启航,张亚连,谭桂菲,黄崇超,袁宝龙. 中国林业碳汇效率时空演化特征——基于三阶段超效率数据包络分析模型. 生态学报. 2024(15): 6769-6782 .
      31. 卫格冉,李明泽,全迎,王斌,刘建阳,明烺. 基于地理加权随机森林的黑龙江省森林碳储量遥感估测. 中南林业科技大学学报. 2024(07): 64-76 .
      32. 游欣,冯晓菁,魏绪英,柯琳琳,蔡军火,陈美玲. 南昌市土地利用碳储量变化及多情景预测. 南方林业科学. 2024(05): 30-38 .
      33. 白念森,吴超,勾啸,崔嘉辰,李炜桢,贾朋,赵志刚. 珠江三角洲城市公益林资源分布差异. 林业与环境科学. 2024(05): 130-136 .
      34. 卢昆,李汉瑾,Hui Yu,王健,吴春明,孙祥科. 中国海洋产业蓝碳源汇识别与碳汇发展潜力初探. 中国海洋经济. 2024(02): 188-215+222-223 .
      35. 张灵蕤,刘辉,邓岚,李群. “双碳”目标下我国农林业碳排放效率的时空演变及影响因素分析. 林业经济. 2024(08): 59-83 .
      36. 张子璇,张颖,孙剑锋,孟娜. 森林碳汇计量研究进展与展望. 北京林业大学学报(社会科学版). 2024(04): 52-61 .
      37. 朱念福,郑晔施,童冉,原文文,刘道平,洪奕丰,吴统贵. 长三角地区乔木林碳汇及其对“双碳”目标贡献预测. 生态学杂志. 2024(12): 3817-3827 .
      38. 陈周光,崔伟伟,龙飞. 交通基础设施能影响森林碳汇增长吗?. 兰州财经大学学报. 2023(01): 81-91 .
      39. 史茂源,杜珊,田乐宇,余雪标,周华,吴金群. 海南屯昌不同林龄槟榔人工林地下部分碳储量的分布特征. 海南大学学报(自然科学版). 2023(01): 38-47 .
      40. 姚永华,赵泽新,熊安华. 基于森林资源二类调查的县域森林碳汇及其价值估算研究——以湖北省当阳市为例. 湖北林业科技. 2023(01): 36-42 .
      41. 朱安明,洪奕丰,张旭峰,于海霞,王洪涛,王雅梅,于文吉. 全生命周期木/竹产品碳足迹研究进展. 林产工业. 2023(02): 83-87 .
      42. 刘雨欣. 间伐保留密度对杉木中龄林碳储量的影响. 福建林业科技. 2023(01): 17-22+30 .
      43. 解瑞丽,田丹宇,刘伯翰,柴麒敏. 生态系统碳汇特征分析及对我国生态系统碳汇发展的启示. 环境保护. 2023(03): 30-34 .
      44. 胡勐鸿,李万峰,吕寻. 日本落叶松自由授粉家系选择和无性繁殖利用. 温带林业研究. 2023(01): 7-16 .
      45. 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. 世界林业研究. 2023(02): 132-137 .
      46. 汤颖颖,吴秀芹. 广西岩溶碳汇对气候变化和石漠化治理措施的响应. 北京大学学报(自然科学版). 2023(02): 189-196 .
      47. 陈治中,昝梅,杨雪峰,董煜. 新疆森林植被碳储量预测研究. 生态环境学报. 2023(02): 226-234 .
      48. 牛晓耕,李莹,屈秋实. 碳达峰碳中和目标下河北省森林碳汇估算与潜力预测. 保定学院学报. 2023(03): 18-25 .
      49. 魏玺,邵亚,蔡湘文,林珍铭,肖连刚,刘泽昊. 漓江流域陆地生态系统碳储量时空特征与预测. 环境工程技术学报. 2023(03): 1223-1233 .
      50. 董瑞林,侯艳闯,丁宇婷. 基于饱和发生率、人工防治时滞等非线性变化特征的松材线虫病生态侵染模型构建研究. 南开大学学报(自然科学版). 2023(03): 92-102 .
      51. 徐彩瑶,任燕,孔凡斌. 浙江省土地利用变化对生态系统固碳服务的影响及其预测. 应用生态学报. 2023(06): 1610-1620 .
      52. 肖君. 福州市主要森林类型林下灌木层生物量和碳密度研究. 林业勘察设计. 2023(01): 1-4 .
      53. 刘晓曼,王超,高吉喜,袁静芳,黄艳,王斌,彭阳. 服务双碳目标的中国人工林生态系统碳增汇途径. 生态学报. 2023(14): 5662-5673 .
      54. 曾霞,张勰,廖德志,唐洁,杨艳,黎蕾,李永进,曾梦雪,吉悦娜,刘珉,赵文,易平英,阳涛,徐建军. 不同经营模式杉木人工林乔木层碳储量研究. 湖南林业科技. 2023(04): 45-50 .
      55. 陈科屹,林田苗,王建军,何友均,张立文. 天保工程20年对黑龙江大兴安岭国有林区森林碳库的影响. 生态环境学报. 2023(06): 1016-1025 .
      56. 刘建霞,杨文静,肖宇胜,徐舟,张利,邹胜,刘千里. 阿坝州实现碳达峰碳中和现状分析及发展建议. 四川农业科技. 2023(09): 95-97 .
      57. 王韦韦,吕茂奎,胥超,陈光水. 亚热带常绿阔叶林和杉木人工林有机碳流失动态特征对降雨的响应. 生态学报. 2023(18): 7474-7484 .
      58. 佘生斌,李小华,李海俊,张义伟. 双碳经济下林业发展探讨. 现代农业科技. 2023(20): 90-93 .
      59. 黄占兵. 做好“四篇文章”提升内蒙古林业碳汇能力. 北方经济. 2023(09): 14-16 .
      60. 王岩,管子隆,李菲,刘园. 秦岭北麓(西安段)碳排放和碳汇分析与预测研究. 西北水电. 2023(05): 15-20+25 .
      61. 韩雪莲,张加龙,刘灵,廖易,唐金灏,韩东阳. 基于遥感特征变量的高山松碳储量抽样估算. 西南林业大学学报(自然科学). 2023(06): 117-124 .
      62. 韩艺,张峰. 北京市不同功能分区的乔木林储碳功能对比研究. 林业调查规划. 2023(05): 26-31 .
      63. 马浩然. 公益林生态效益补偿单位采用蓄积及其增量的探索. 浙江农林大学学报. 2023(06): 1273-1281 .
      64. 胡景心,沙青娥,刘慧琳,张雪驰,郑君瑜. 珠江三角洲二氧化碳源汇演变特征及驱动因素. 环境科学. 2023(12): 6643-6652 .
      65. 田晓霞,包庆丰. 森林碳汇发展潜力时空演变与障碍因子诊断——基于31个省份. 中国林业经济. 2023(06): 111-117 .
      66. 张雅薇,王允磊,韩启峰,石晓龙. 碳达峰碳中和背景下提升新疆森林碳汇功能的思考. 温带林业研究. 2023(04): 78-80 .
      67. 曹先磊,许骞骞,吴伟光. 碳交易框架下我国林业增汇潜力及对区域碳减排成本的影响研究. 农业技术经济. 2023(12): 96-110 .
      68. 赵桐,蒙吉军. 基于土地利用变化的成都平原经济区碳储量时空演变与情景模拟. 山地学报. 2023(05): 648-661 .
      69. 蔡宇泽. 林业碳汇服务信托应用于林业企业融资的研究. 林业经济问题. 2023(06): 578-585 .
      70. 易昌民,付伟,赵春艳. 基于CiteSpace的中国林业碳汇研究进展与趋势分析. 林草政策研究. 2023(03): 89-96 .
      71. Zheng-Meng Hou,Ying Xiong,Jia-Shun Luo,Yan-Li Fang,Muhammad Haris,Qian-Jun Chen,Ye Yue,Lin Wu,Qi-Chen Wang,Liang-Chao Huang,Yi-Lin Guo,Ya-Chen Xie. International experience of carbon neutrality and prospects of key technologies: Lessons for China. Petroleum Science. 2023(02): 893-909 .
      72. 杨礼旦. 适应气候变化的人工林多目标经营与管理对策. 温带林业研究. 2022(01): 12-17 .
      73. 洪李斌,卿蕴贤,田佳赫,康洁敏,卢伟. 基于混合效应模型的塞罕坝华北落叶松人工林单木去皮胸径生长预测. 林业与生态科学. 2022(02): 127-133 .
      74. 张桂莲,仲启铖,张浪. 面向碳中和的城市园林绿化碳汇能力建设研究. 风景园林. 2022(05): 12-16 .
      75. 杨鑫,高雯雯,李莎,李冠衡. 基于遥感影像估算的北京中心城区碳储量与气候环境关联性研究. 风景园林. 2022(05): 31-37 .
      76. 张颖,易爱军. 承德市森林碳汇价值核算及其相关问题研究. 创新科技. 2022(05): 83-92 .
      77. Menghong HU,Jiying LI,Man SUN. Strong Seedlings of Improved Varieties and High-efficiency Cultivation of Artificial Forests Promotes the Early Realization of "Carbon Neutrality". Agricultural Biotechnology. 2022(04): 136-141 .
      78. 曾丽,吕寻,胡勐鸿. 良种是加速实现“碳中和”的有效保障措施——以甘肃省地方良种为例. 林业科技通讯. 2022(08): 35-39 .
      79. 林荣华. 森林经营管理对碳汇的影响及提高对策. 乡村科技. 2022(14): 120-123 .
      80. 沈德才,刘婷,莫罗坚,周海琪. 东莞市森林生态系统土壤有机碳含量的地统计学分析. 热带林业. 2022(03): 45-49 .
      81. 张俊飚,何可. “双碳”目标下的农业低碳发展研究:现状、误区与前瞻. 农业经济问题. 2022(09): 35-46 .
      82. 朱海,王立国. 江西省旅游业碳达峰与碳中和研究. 中国生态旅游. 2022(04): 617-631 .
      83. 薛春泉,陈振雄,杨加志,曾伟生,林丽平,刘紫薇,张红爱,苏志尧. 省市县一体化森林碳储量估测技术体系——以广东省为例. 林业资源管理. 2022(04): 157-163 .
      84. 曾莹,王雪萌,唐昊,廖笳妤,田蒙奎. 碳达峰碳中和战略科学内涵、实现路径及挑战. 现代化工. 2022(10): 1-4+10 .
      85. 张吉统,麦强盛. 云南省森林碳汇经济价值评估研究. 绿色科技. 2022(17): 264-268 .
      86. 原作强,王星,毛子昆,蔺菲,叶吉,房帅,王绪高,郝占庆. 典型温带树种固碳速率研究. 北京林业大学学报. 2022(10): 43-51 . 本站查看
      87. 范春楠,刘强,郑金萍,郭忠玲,张文涛,刘英龙,谢遵俊,任增君. 采伐强度对阔叶红松林生态系统碳密度恢复的影响. 北京林业大学学报. 2022(10): 33-42 . 本站查看
      88. 张颖,孟娜,姜逸菲. 中国森林碳汇与林业经济发展耦合及长期变化特征分析. 北京林业大学学报. 2022(10): 129-141 . 本站查看
      89. 王志恒,李仲堃,王融,孔杉,陈晓峰. 基于双重耦合模型的森林固碳综合价值评估. 广西林业科学. 2022(05): 617-625 .
      90. 陈科屹,王建军,何友均,张立文. 黑龙江大兴安岭重点国有林区森林碳储量及固碳潜力评估. 生态环境学报. 2022(09): 1725-1734 .
      91. 廖杨文科,张佩瑶,张清越,李孝刚. 盐碱地林木耐盐机制及造林技术研究进展. 南京林业大学学报(自然科学版). 2022(06): 96-104 .
      92. 荀文会. “碳中和”视角下的沈阳市国土空间规划路径. 规划师. 2022(10): 88-92 .
      93. 许骞骞,曹先磊,孙婷,朱颖,吴伟光. 中国森林碳汇潜力与增汇成本评估——基于Meta分析方法. 自然资源学报. 2022(12): 3217-3233 .
      94. 董战峰,毕粉粉,冀云卿. 中国陆地生态系统碳汇发展的现状、问题及建议. 科技导报. 2022(19): 15-24 .
      95. 肖军,雷蕾,曾立雄,李肇晨,马成功,肖文发. 不同经营模式对华北油松人工林碳储量的影响. 生态环境学报. 2022(11): 2134-2142 .
      96. 向晋含,余彬,陶志先,张利,刘顺. “碳中和”背景下国家储备林培育的优化路径. 林业科技通讯. 2022(12): 3-9 .
      97. 章敏,王健,韩天一,欧阳勋志,潘萍,刘冬冬. 基于CBM-CFS3模型的马尾松林碳密度特征及其影响因素. 林业资源管理. 2022(06): 44-53 .
      98. 赵哲,冯星,王佳音. 辽宁省林下产业富民的实践探索及发展策略. 中南林业科技大学学报(社会科学版). 2022(06): 64-70 .
      99. 刘海. 闽北典型森林类型植被层碳储量及分配特征. 林业勘察设计. 2022(03): 84-88 .

      Other cited types(57)

    Catalog

      Article views (1937) PDF downloads (105) Cited by(156)

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return