DBH class structure and arbor biomass of Juglans mandshurica secondary forest
-
摘要:目的 了解东北不同山脉胡桃楸次生林径级结构和乔木生物量情况，为后续次生林相关研究及该地区林分合理经营提供科学依据。方法 本研究在张广才岭、长白山、老爷岭和龙岗山山脉21个典型区域内共设置样地202块，应用三参数Weibull分布、Johnson’s SB分布和负指数分布对调查样地内乔木直径进行拟合，并进行相对偏差和均方根误差的精度检验，同时根据调查数据和参考乔木异速生物量方程计算各样地每公顷生物量。结果 4个山脉的林分径级结构基本相近，均表现出逐渐降低的趋势，总体呈现出倒“J”型分布，中小径级的林木株数较多，主要集中在6 ~ 14 cm径级，张广才岭每公顷林木株数要多于长白山、老爷岭和龙岗山；根据参数和模型拟合，以及实测株数和模拟株数之间的相对偏差和均方根误差的比较，3种模型模拟效果与实际值均较为接近，其中三参数Weibull分布模拟效果在4个山脉中均较其他两种曲线更好，且张广才岭三参数Weibull函数拟合效果优于其他山脉；各山脉每公顷所有树种地上部分和总生物量大小顺序均为长白山 > 龙岗山 > 张广才岭 > 老爷岭，长白山和龙岗山生物量大小相似，显著高于张广才岭和老爷岭（P < 0.05），胡桃楸地上部分和总生物量大小关系为长白山 > 龙岗山 > 张广才岭 > 老爷岭，且长白山林分内胡桃楸生物量显著高于其他山脉（P < 0.05）。结论 4个山脉林分更新状况良好，林分径级结构模拟均以三参数Weibull函数拟合效果最好，且林分中所有树种和胡桃楸单个树种的生物量均在长白山表现最优。Abstract:Objective This paper aims to study the DBH class structure and arbor biomass of Juglans mandshurica secondary forests in different mountains in northeastern China, then provide scientific basis for follow-up related research on secondary forests and reasonable forest management in this area.Method A total of 202 sample plots were set up in 21 typical areas of Zhangguangcai Mountain, Changbai Mountain, Laoyeling Mountain and Longgang Mountain of northeastern China in this study, and the three-parameter Weibull distribution, Johnson’s SB distribution and negative exponential distribution were used to fit the tree DBH in the survey sample plots. The relative deviation and root-mean-square error were tested for accuracy, and the biomass per hectare of each sample plot was calculated based on the survey data and the reference arbor allometric biomass equation.Result DBH class structure of forest stands in the four mountain ranges was basically similar, showing a trend of decreasing gradually and an inverted “J”-shaped distribution. There were more trees in the middle and small DBH classes, mainly in the 6−14 cm DBH class. The number of trees per hectare in Zhangguangcai Mountain was more than that in Changbai Mountain, Laoyeling Mountain and Longgang Mountain. According to the parameters and model fitting, as well as the comparison of the relative deviation and the root mean square error between the measured plant number and the simulated plant number, the simulation effects of three models were relatively close to the actual values, among which, the three-parameter Weibull distribution simulation effect was better than the other two curves in the four mountains, and the three-parameter Weibull function fitting effect of Zhangguangcai Mountain was better than other mountains. The order of the aboveground part biomass and total biomass per hectare of all species in each mountain range was Changbai Mountain > Longgang Mountain > Zhangguangcai Mountain > Laoyeling Mountain. The biomasses of Changbai Mountain and Longgang Mountain were similar, significantly higher than those of Zhangguangcai Mountain and Laoyeling Mountain (P < 0.05 ). The order of aboveground part biomass and total biomass of Juglans mandshurica was Changbai Mountain > Longgang Mountain > Zhangguangcai Mountain > Laoyeling Mountain, and the biomass of Juglans mandshurica in the forests of Changbai Mountain was significantly higher than those in other mountains (P < 0.05).Conclusion The renewal status of the forest stands in the four mountains is good, the simulation of the stand DBH class structure is the best with the three-parameter Weibull function, and the biomass of all tree species in the stand and a single tree species of Juglans mandshurica have the best performance in Changbai Mountain of northeastern China.
-
Keywords:
- Juglans mandshurica /
- secondary forest /
- DBH class structure /
- biomass
-
-
![]()
图 2 不同模型下径级与株数分布的实际值与预测值
柱状图为实测值，曲线图为预测值。A为张广才岭，B为长白山，C为老爷岭，D为龙岗山。The histogram is the measured value, and the curved line is the predicted value. A is Zhangguangcailing Mountain, B is Changbaishan Mountain, C is Laoyeling Mountain, D is Longgangshan Mountain.
Figure 2. Measured and predicted values of DBH class and plant number distribution under different models
表 1 样地基本情况表
Table 1 Basic situation of sample plots
项目 Item 张广才岭
Zhangguangcailing Mountain长白山
Changbaishan Mountain老爷岭
Laoyeling Mountain龙岗山
Longgangshan Mountain样地个数 Number of sample plot 28 31 37 106 海拔 Altitude/m 230 ~ 577 256 ~ 834 257 ~ 717 251 ~ 702 坡向 Aspect 阴坡、半阴坡
Shady slope and half-
shady slope阴坡、半阴坡
Shady slope and half-
shady slope阴坡、半阴坡
Shady slope and half-
shady slope阴坡、半阴坡
Shady slope and half-
shady slope坡度 Slope/(°) 0 ~ 21 0 ~ 21 0 ~ 21 0 ~ 21 坡位 Slope position 中下坡、坡底
Middle downhill and
bottom slope中下坡、坡底
Middle downhill and
bottom slope中下坡、坡底
Middle downhill and
bottom slope中下坡、坡底
Middle downhill and
bottom slope株数 Number of plant 598a 403b 307b 352b 平均胸径 Mean DBH/cm 15.7 16.9 17.1 17.8 最大胸径 Max. DBH/cm 51.9 55.6 53.5 54.8 注：不同小写字母表示不同山脉每公顷林木株数差异显著（P < 0.05）。Note: different lowercase letters indicate significant differences in the number of trees per hectare in varied mountains (P < 0.05). 
下载: 导出CSV
表 2 不同山脉林分径级分布模型拟合参数
Table 2 Fitting parameters of forest DBH class distribution model in different mountains
模型
Model参数
Parameter山脉 Mountain 张广才岭
Zhangguangcailing
Mountain长白山
Changbaishan
Mountain老爷岭
Laoyeling
Mountain龙岗山
Longgangshan
Mountain三参数威布尔 Three parameter Weibull(Weibull) a1 5.000 5.000 5.000 5.000 b1 12.194 9.455 8.132 8.563 c1 1.220 1.788 1.310 1.425 R2 0.969 0.939 0.957 0.947 负指数分布 Negative index distribution a3 415.551 456.774 159.395 155.179 b3 0.058 0.054 0.049 0.052 R2 0.817 0.804 0.817 0.800 Johnson’s SB a2 −40.722 −68.974 −8.741 −8.923 b2 0.260 0.375 0.219 0.293 c2 −20.900 −22.899 −25.933 −23.837 d2 4.644 −4.506 4.887 3.746 R2 0.780 0.769 0.778 0.723
下载: 导出CSV
表 3 不同山脉实测株数和模拟株数之间的相对偏差和均方根误差
Table 3 Relative biases and square root and mean error between the measured plant number andsimulated one in different mountains
指标 Index 张广才岭 Zhangguangcailing Mountain 长白山 Changbaishan Mountain Weibull 负指数 Negative index Johnson’s SB Weibull 负指数 Negative index Johnson’s SB Bias/% −0.179 0.314 −0.257 −0.213 0.388 −0.299 RMSE/% 1.025 1.476 1.256 1.468 1.899 1.612 指标 Index 老爷岭 Laoyeling Mountain 龙岗山 Longgangshan Mountain Weibull 负指数 Negative index Johnson’s SB Weibull 负指数 Negative index Johnson’s SB Bias/% −0.186 0.342 −0.289 −0.196 0.368 0.279 RMSE/% 1.234 1.873 1.468 1.314 1.892 1.582
下载: 导出CSV
表 4 不同地区林分乔木树种生物量
Table 4 Biomass of arbor species in different areas
项目 Item 张广才岭
Zhangguangcailing Mountain长白山
Changbaishan Mountain老爷岭
Laoyeling Mountain龙岗山
Longgangshan Mountain地上生物量/(t·hm−2) Aboveground biomass/(t·ha−1) 833.026 ± 4.352b 1 173.999 ± 5.262a 756.199 ± 4.681b 1 089.283 ± 5.039a 总生物量/(t·hm−2) Total biomass/(t·ha−1) 1 027.509 ± 5.012b 1 528.731 ± 4.981a 993.978 ± 4.672b 1 437.937 ± 5.883a 地上生物量占比 Proportion of aboveground biomass/% 81.07a 76.80b 76.08b 75.75b 注：同一行不同小写字母表示差异性显著，P < 0.05。下同。Notes: different lowercase letters in the same line indicate significant difference, P < 0.05. The same below.
下载: 导出CSV
表 5 不同地区林分胡桃楸树种生物量
Table 5 Biomass of Juglans mandshurica species in different areas
项目 Item 张广才岭
Zhangguangcailing Mountain长白山
Changbaishan Mountain老爷岭
Laoyeling Mountain龙岗山
Longgangshan Mountain地上生物量/(t·hm−2) Aboveground biomass/(t·ha−1) 89.882 ± 2.571b 132.336 ± 3.251a 68.292 ± 1.982c 102.72 ± 1.988b 总生物量/(t·hm−2) Total biomass/(t·ha−1) 118.236 ± 2.319b 174.845 ± 1.892a 86.921 ± 1.678c 137.864 ± 1.885b 地上生物量占比 Proportion of aboveground biomass/% 76.02a 75.69a 78.57a 74.51a
下载: 导出CSV
-
[1] 王志鸣, 郭秋菊, 艾训儒, 等. 恩施州不同海拔马尾松天然次生林林分结构特征研究[J]. 西南林业大学学报(自然科学), 2019, 39(1):114−122. Wang Z M, Guo Q J, Ai X R, et al. Structure characteristics of Pinus massoniana natural secondary forest at different altitude of Enshi[J]. Journal of Southwest Forestry University (Natural Sciences), 2019, 39(1): 114−122.
[2] 张今朝, 刘健, 余坤勇, 等. 福建陈大国有林场生态公益林林分结构特征及优化调整[J]. 西南林业大学学报(自然科学), 2017, 37(4):132−139. Zhang J Z, Liu J, Yu K Y, et al. Stand structure and optimized adjustment of ecological public welfare forest in Chenda State-Owned Forest Farm of Fujian Province[J]. Journal of Southwest Forestry University (Natural Sciences), 2017, 37(4): 132−139.
[3] 孟宪宇. 测树学[M]. 北京: 中国林业出版社, 2006. Meng X Y. Forest mensuration[M]. Beijing: China Forestry Publishing House, 2006.
[4] 龚直文, 亢新刚, 杨华, 等. 长白山杨桦次生林直径结构研究[J]. 西北林学院学报, 2009, 24(3):1−6. Gong Z W, Kang X G, Yang H, et al. Diameter structure of polar-birch secondary forests in Changbai Mountain[J]. Journal of Northwest Forestry University, 2009, 24(3): 1−6.
[5] 谢小魁, 苏东凯, 刘正纲, 等. 长白山原始阔叶红松林径级结构模拟[J]. 生态学杂志, 2010, 29(8):1477−1481. Xie X K, Su D K, Liu Z G, et al. Modeling diameter distribution of primary broadleaf-Korean pine mixed forest in Changbai Mountains[J]. Chinese Journal of Ecology, 2010, 29(8): 1477−1481.
[6] 铁牛. 长白落叶松人工林林分直径分布研究[J]. 林业资源管理, 2014(6):95−98. Tie N. Simulation model of stand diameter structure for planted Larix olgensis forest[J]. Forest Resources Management, 2014(6): 95−98.
[7] 董莉莉, 赵济川, 汪成成, 等. 抚育间伐后蒙古栎阔叶混交林径级结构及生长动态研究[J]. 西南林业大学学报(自然科学), 2019, 39(6):98−104. Dong L L, Zhao J C, Wang C C, et al. Study on diameter structure and growth dynamics of mixed Quercus mongolica broad-leaved natural stands after tending thinning[J]. Journal of Southwest Forestry University (Natural Sciences), 2019, 39(6): 98−104.
[8] 孟宪宇. 使用 Weibull 分布对人工林油松林直径分布的研究[J]. 北京林学院学报, 1985, 7(1):30−39. Meng X Y. A study on diameter distribution of some artificial Pinus tabulaeformis stands by using the Weibull function[J]. Journal of Beijing Forestry College, 1985, 7(1): 30−39.
[9] 崔启武, Lawson G. 一个新的种群增长数学模型:对经典的 Logistic 方程和指数方程的扩充[J]. 生态学报, 1982, 2(4):403−415. Cui Q W, Lawson G. A new model of single-species population:by extending of the logistic and exponential equations with several limiting conditions[J]. Acta Ecologica Sinica, 1982, 2(4): 403−415.
[10] 张少昂, 王冬梅. Richards 方程的分析和一种新的树木理论生长方程[J]. 北京林业大学学报, 1992, 14(3):99−105. Zhang S A, Wang D M. New theoretical growth model based on analysis of Richards equation[J]. Journal of Beijing Forestry University, 1992, 14(3): 99−105.
[11] 惠刚盈, 盛炜彤. 林分直径结构模型的研究[J]. 林业科学研究, 1995, 8(2):127−131. Hui G Y, Sheng W T. Study on stand diameter structure model[J]. Forest Research, 1995, 8(2): 127−131.
[12] Campo M, Vcca S, Luyssar S, et al. Biomass production efficiency controlled by management in temperate and boreal ecosystems[J]. Nature Geoscience, 2015, 8: 843−846. doi: 10.1038/ngeo2553
[13] di Cosmo L, Gasparini P, Tabacchi G. A national-scale, stand-level model to predict total above-ground tree biomass from growing stock volume[J]. Forest Ecology and Management, 2016, 361: 269−276. doi: 10.1016/j.foreco.2015.11.008
[14] Stephy M, Abbie C, David S, et al. Allometry for biomass estimation in jatropha trees planted as boundary hedge in farmers’ fields[J]. Forests, 2013, 4(2): 218−233. doi: 10.3390/f4020218
[15] 何怀江, 叶尔江·拜克吐尔汉, 张春雨, 等. 吉林蛟河针阔混交林12个树种生物量分配规律[J]. 北京林业大学学报, 2016, 38(4):53−62. He H J, Yeerjiang Baiketuerhan, Zhang C Y, et al. Biomass allocation of twelve tree species in coniferous and broad-leaved mixed forest in Jiaohe, Jilin Province, northeast China[J]. Journal of Beijing Forestry University, 2016, 38(4): 53−62.
[16] Alamgir M, Al-Amin M. Allometric models to estimate biomass organic carbon stock in forest vegetation[J]. Journal of Forestry Research, 2008, 19(2): 101−106. doi: 10.1007/s11676-008-0017-4
[17] 左舒翟, 任引, 翁闲, 等. 亚热带常绿阔叶林9个常见树种的生物量相对生长模型[J]. 应用生态学报, 2015, 26(2):356−362. Zuo S Z, Ren Y, Weng X, et al. Biomass allometric equations of nine common tree species in an evergreen broadleaved forest of subtropical China[J]. Chinese Journal of Applied Ecology, 2015, 26(2): 356−362.
[18] 何怀江. 采伐干扰对吉林蛟河针阔混交林碳储量和碳平衡的影响[D]. 北京: 北京林业大学, 2018. He H J. Effects of thinning disturbance on carbon storage and carbon balance in coniferous and broad-leaved mixed forest in Jiaohe, Jilin Province[D]. Beijing: Beijing Forestry University, 2018.
[19] Woods K D, Feiveson A H, Botkin D B. Statistical error analysis for biomass density and leaf area index estimation[J]. Canadian Journal of Forest Research, 1991, 21(7): 974−989. doi: 10.1139/x91-135
[20] Mosseler A, Major J E, Labrecque M, et al. Allometric relationships in coppice biomass production for two North American willows (Salix spp.) across three different sites[J]. Forest Ecology & Management, 2014, 320: 190−196.
[21] Lauri M, Gregoire T G, Burkhart H E. Comparing strategies for modeling tree diameter percentiles from remeasured plots[J]. Environmetrics, 2008, 19(5): 529−548. doi: 10.1002/env.896
[22] 马炜, 孙玉军. 三种直径分布拟合模型在长白落叶松林分的实际应用[J]. 生物数学学报, 2012, 27(3):548−554. Ma W, Sun Y J. Modeling of stand diameter structure of Larix olgensis plantations[J]. Journal of Biomathematics, 2012, 27(3): 548−554.
[23] 江蓝, 何中声, 刘金福, 等. 戴云山黄山松种群径级结构的海拔分布格局[J]. 福建农林大学学报(自然科学版), 2019, 48(5):585−590. Jiang L, He Z S, Liu J F, et al. Distribution pattern of diameter structure of Pinus taiwanensis Hayata population along the elevation gradients in Daiyun Mountain[J]. Journal of Fujian Agriculture and Forestry University (Natural Science Edition), 2019, 48(5): 585−590.
[24] 巢林, 刘艳艳, 张伟东, 等. 沼泽交错带白桦个体生长动态及径级结构与种内种间竞争[J]. 生态学杂志, 2017, 36(3):577−583. Chao L, Liu Y Y, Zhang D W, et al. Diameter class structure, growth dynamic, intraspecific and interspecific competitions of Betula platyphylla on swamp ecotone[J]. Chinese Journal of Ecology, 2017, 36(3): 577−583.
[25] 孙越, 夏富才, 赵秀海, 等. 张广才岭温带次生针阔混交林物种组成和群落结构特征[J]. 生态学报, 2017, 37(10):3425−3436. Sun Y, Xia F C, Zhao X H, et al. The composition and community structure of coniferous and broadleaved mixed forest species in the Zhangguangcai Mountains, China[J]. Acta Ecologica Sinica, 2017, 37(10): 3425−3436.
[26] Marc P, Pukkala T, Blasco E, et al. Comparison of beta, Johnson’s SB, Weibull and truncated Weibull functions for modeling the diameter distribution of forest stands in Catalonia (northeast of Spain)[J]. European Journal of Forest Research, 2007, 126(4): 563−571. doi: 10.1007/s10342-007-0177-3
[27] 肖智慧, 李志洪, 薛春泉, 等. 梅县典型针阔混交林林分直径结构的动态变化规律[J]. 中南林业科技大学学报, 2013, 33(6):17−21. Xiao Z H, Li Z H, Xue C Q, et al. Diameter distribution and dynamics of typical coniferous and broadleaved mixed forests in Meizhou County, Guangdong Province[J]. Journal of Central South University of Forestry & Technology, 2013, 33(6): 17−21.
[28] Karczmarski J. DBH distribution structure in natural spruce stands of the upper montane belt in the Tatra and Beskid mountains in respect to the stages and phases of virgin type forest development[J]. Sylwan, 2005(3): 12−23.
[29] 杨锦昌. 单叶省藤和黄藤人工林的系统经营技术[D]. 北京: 中国林业科学研究院, 2004. Yang J C. System management of C. simplicifolius and D. margaritae plantations[D]. Beijing: Chinese Academy of Forestry, 2004.
[30] Wang X, Hao Z, Zhang J, et al. Tree size distributions in an old-growth temperate forest[J]. Oikos, 2009, 118: 25−36. doi: 10.1111/j.0030-1299.2008.16598.x
[31] 吕晓敏, 王玉辉, 周广胜, 等. 温度与降水协同作用对短花针茅生物量及其分配的影响[J]. 生态学报, 2015, 35(3):752−760. Lü X M, Wang Y H, Zhou G S, et al. Interactive effects of changing precipitation and elevated temperatures on plant biomass and its allocation of Stipa breviflora[J]. Acta Ecologica Sinica, 2015, 35(3): 752−760.
[32] Oleksyn J, Tjoelker M G, Reich P B. Growth and biomass partitioning of populations of European Pinus sylvestris L. under simulated 50° and 60°N daylengths: evidence for photoperiodic ecotypes[J]. New Phytologist, 2010, 120(4): 561−574.
[33] Oleksyn J, Tjoelker M G, Reich P B. Whole-plant CO2 exchange of seedlings of two Pinus sylvestris L. provenances grown under simulated photoperiodic conditions of 50° and 60°N[J]. Trees, 1992, 6(4): 225−231.
[34] 魏晶, 吴钢, 邓红兵. 长白山高山冻原植被生物量的分布规律[J]. 应用生态学报, 2004, 15(11):1999−2004. doi: 10.3321/j.issn:1001-9332.2004.11.003 Wei J, Wu G, Deng H B. Vegetation biomass distribution characteristics of alpine tundra ecosystem in Changbai Mountains[J]. Chinese Journal of Applied Ecology, 2004, 15(11): 1999−2004. doi: 10.3321/j.issn:1001-9332.2004.11.003
-
期刊类型引用(16)
1. 钟思琪，宁金魁，黄锦程，陈鼎泸，欧阳勋志，臧颢. 基于混合效应的杉木人工林冠幅模型. 森林与环境学报. 2024(02): 127-135 . 
百度学术
2. 段平，王云川，晋秋梅，李佳. 基于无人机可见光影像的单木胸径估算方法. 测绘与空间地理信息. 2023(01): 14-17 . 百度学术
3. 魏智海，魏姿芃. 基于单木分割及点云特征提取的单木胸径估测. 陕西林业科技. 2023(02): 18-23 . 百度学术
4. 王杰芬，夏磊，林露花，胡璐璐，徐怀兴，王聚中，徐小军. 结合放射线法和无人机影像提取冠幅估算杉木碳储量研究. 浙江林业科技. 2023(05): 42-50 . 百度学术
5. 夏洪涛，郭晓斌，张珍，田相林，郭福涛，孙帅超. 基于不同立地质量评价指标的杉木大径材林分树高-胸径模型. 中南林业科技大学学报. 2023(10): 80-88 . 百度学术
6. 肖德卿，罗芊芊，范辉华，邱群，周志春. 栽植模式对木荷幼林生长和形质性状家系变异影响. 林业科学. 2022(05): 85-92 . 百度学术
7. 王志波，季蒙，李永乐，李银祥，马世明，张海东. 华北落叶松人工林差分地位指数模型构建. 林业资源管理. 2021(01): 156-163 . 百度学术
8. 杨洋，尤龙辉，叶功富，聂森，程分生，余锦林. 沙质海岸基干林木麻黄幼林模拟抚育预测. 福建农林大学学报(自然科学版). 2021(02): 206-215 . 百度学术
9. 田红灯，申文辉，谭一波，郑威，何琴飞，朱慧，甘国娟. 不同林龄杉木人工林冠幅与生长因子的关系. 中南林业科技大学学报. 2021(05): 93-101 . 百度学术
10. 朱晋梅，朱光玉，易烜，杨琬珑，牟村，王琢玙. 湖南省栎类次生林冠幅—胸径模型模拟研究. 湖南林业科技. 2021(03): 46-51 . 百度学术
11. 赵保国，朱江，艾训儒，姚兰，郭秋菊，洪建峰. 水杉原生种群胸径树高与树冠的通径分析. 东北林业大学学报. 2021(10): 16-20 . 百度学术
12. 于晓池，李凤，欧阳，张鹏，郭小龙，肖遥，赵秋玲，杨桂娟，王军辉，麻文俊. 基于表型的灰楸核心种质构建. 林业科学研究. 2021(06): 38-45 . 百度学术
13. 贾鹏刚，夏凯，董晨，冯海林，杨垠晖. 基于无人机影像的银杏单木胸径预估方法. 浙江农林大学学报. 2019(04): 757-763 . 百度学术
14. 张冬燕，王冬至，范冬冬，张健东，李大勇. 不同立地类型华北落叶松人工林冠幅与胸径关系研究. 林业资源管理. 2019(04): 69-73 . 百度学术
15. 伍小敏，徐春，杨汉波，陈炙，郭洪英，黄振，王泽亮. 四川桤木天然林和人工林的单木生长模型研究. 四川林业科技. 2018(04): 8-11+44 . 百度学术
16. 周凤艳. 沙地樟子松不同林龄树高、胸径等生长指标的关系研究. 吉林林业科技. 2017(01): 12-15 . 百度学术
其他类型引用(13)
计量
- 文章访问数: 981
- HTML全文浏览量: 343
- PDF下载量: 99
- 被引次数: 29
