欢迎访问林草资源研究
Technical Application

Construction of Compatibility Models for Aboveground Biomass of Individual Trees in Larix gmelinii var.principis-rupprechtii plantation

  • Yuan MA ,
  • Zhibo WANG ,
  • Dongmei YE ,
  • Fengling LIU
Expand
  • 1. Forestry College,Inner Mongolia Agricultural University,Hohhot 010019,China
    2. Inner Mongolia Academy of Forestry Sciences,Hohhot 010010,China
    3. Forestry and Grassland Bureau of Keshiketeng Banner;Chifengshi 02400,Inner Mongolia,China

Received date: 2024-05-30

  Revised date: 2024-10-30

  Online published: 2025-04-18

Abstract

Based on the measured biomass data from 44 Larix gmelinii principis-rupprechtii trees in Sumushan Forest Farm of Inner Mongolia,different tree measurement factors were used to construct a single-tree independent basic model and a compatibility model under three methods(total direct control adjustment method,total direct control simultaneous equations method and algebraic sum control method).1)The determination coefficient of the optimal independent basic model and the compatibility model with DBH as the independent variable ranged from 0.766 to 0.943,the root mean square error(RMSE)was less than 20.030 kg,the total relative error was within±1.905%,and the absolute value of the average relative error was less than 16.905%.The prediction accuracy of each biomass model ranged from 93.7% to 95.6%.2)The determination coefficient of the optimal independent basic model,the compatibility model with DBH,and tree height as independent variables was from 0.767 to 0.985,the RMSE was less than 11.636 kg,the total relative error was less than 1.893%,and the absolute value of the average relative error was less than 16.823%.The prediction accuracy of each biomass model was 93.7%~97.9%.3)All models showed a good fitting effect,no significant systematic deviation,strong degree of fit with the sample points,and high prediction accuracy.4)All models could well predict the biomass of Larix gmelinii,var.principis-rupprechtii and the binary model was better than the unary model.The compatibility model could effectively solve the problem of incompatibility between the total aboveground biomass and the components of each organ,and the algebraic and control methods were better than the other two methods.Considering the modeling efficiency and accuracy,it is recommended to use the binary compatible biomass model of algebra and control method as the biomass prediction model of larch plantation in this area.

Cite this article

Yuan MA , Zhibo WANG , Dongmei YE , Fengling LIU . Construction of Compatibility Models for Aboveground Biomass of Individual Trees in Larix gmelinii var.principis-rupprechtii plantation[J]. Forest and Grassland Resources Research, 2024 , 0(6) : 129 -139 . DOI: 10.13466/j.cnki.lczyyj.2024.06.015

References

[1] 董利虎, 李凤日, 贾炜玮. 黑龙江省红松人工林立木生物量估算模型的研建[J]. 北京林业大学学报, 2012, 34(6):16-22.
[2] 王为斌, 党永峰, 曾伟生. 东北落叶松相容性立木材积和地上生物量方程研建[J]. 林业资源管理, 2012(2):69-73.
[3] 曹梦, 潘萍, 欧阳勋志, 等. 天然次生林中闽楠生物量分配特征及相容性模型[J]. 浙江农林大学学报, 2019, 36(4):764-773.
[4] 白志强, 李缓, 王文栋. 阿尔泰山优势树种的生物量模型构建及其生物量分配特征[J]. 林业资源管理, 2018(4):34-40.
[5] 肖生苓, 杨嘉龙. 大兴安岭北部兴安落叶松天然林单木地上生物量[J]. 林业科学, 2014, 50(8):22-29.
[6] 王柯人, 舒清态, 赵洪莹, 等. 高山松单木地上生物量模型不确定性研究[J]. 西南林业大学学报(自然科学), 2021, 41(2):100-106.
[7] 黄兴召, 孙晓梅, 张守攻, 等. 辽东山区日本落叶松生物量相容性模型的研究[J]. 林业科学研究, 2014, 27(2):142-148.
[8] 罗云建, 张小全, 王效科, 等. 森林生物量的估算方法及其研究进展[J]. 林业科学, 2009, 45(8):129-134.
[9] 刘琪璟. 嵌套式回归建立树木生物量模型[J]. 植物生态学报, 2009, 33(2):331-337.
[10] 郭孝玉, 孙玉军, 刘凤娇. 不同估算树冠生物量方法的比较:以长白落叶松林为例[J]. 林业资源管理, 2010(5):41-47.
[11] Chave J, Andalo C, Brown S, et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests[J]. Oecologia, 2005, 145(1):87-99.
[12] 刘秀红, 姜春前, 徐睿, 等. 相容性单木生物量模型估计方法的比较:以青冈栎为例[J]. 林业科学, 2020, 56(9):164-173.
[13] MUUKKONEN P. Generalized allometric volume and biomass equations for some tree species in Europe[J]. European Journal of Forest Research, 2007, 126(2):157-166.
[14] 贾炜玮, 李凤日, 董利虎, 等. 基于相容性生物量模型的樟子松林碳密度与碳储量研究[J]. 北京林业大学学报, 2012, 34(1):6-13.
[15] LAMBERT M C, UNG C H, RAULIER F, et al. Canadian national tree aboveground biomass equations[J]. Canadian Journal of Forest Research, 2005, 35(8):1996-2018.
[16] 洪奕丰, 陈东升, 申佳朋, 等. 长白落叶松人工林单木和林分水平的相容性生物量模型研究[J]. 林业科学研究, 2019, 32(4):33-40.
[17] 曾伟生, 唐守正. 利用度量误差模型方法建立相容性立木生物量方程系统[J]. 林业科学研究, 2010, 23(6):797-802.
[18] 张会儒, 赵有贤, 王学力, 等. 应用线性联立方程组方法建立相容性生物量模型研究[J]. 林业资源管理, 1999(6):63-67.
[19] 骆期邦, 曾伟生, 贺东北, 等. 立木地上部分生物量模型的建立及其应用研究[J]. 自然资源学报, 1999(3):80-86.
[20] 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(S1):19-27.
[21] 符利勇, 雷渊才, 曾伟生. 几种相容性生物量模型及估计方法的比较[J]. 林业科学, 2014, 50(6):42-54.
[22] 王志波, 季蒙, 李永乐. 华北落叶松人工林差分地位指数模型构建[J]. 林业资源管理, 2021(1):156-163.
[23] 王柯人, 罗文秀, 舒清态, 等. 龙竹人工林的含水率分析及地上生物量回归模型构建[J]. 西南林业大学学报(自然科学), 2021, 41(6):168-174.
[24] 姜鹏, 董树国, 隋玉龙, 等. 北沟林场华北落叶松生物量模型的研究[J]. 中南林业科技大学学报, 2013, 33(7):131-135.
[25] 常月梅, 张百川. 不同年龄阶段华北落叶松单株生物量的研究[J]. 河北林业科技, 2017(3):27-29.
[26] CASE B S, HALL R J. Assessing prediction errors of generalized tree biomass and volume equations for the boreal forest region of west-central Canada[J]. Canadian Journal of Forest Research, 2008, 38(6):878-889.
[27] 兰洁, 肖中琪, 李吉玫, 等. 天山雪岭云杉生物量分配格局及异速生长模型[J]. 浙江农林大学学报, 2020, 37(3):416-423.
[28] 黄光灿, 吴宏炜, 赖建明, 等. 福建木荷地上部分相容性生物量模型研究[J]. 西南林业大学学报(自然科学), 2020, 40(2):125-134.
[29] 尹惠妍, 张志伟, 李海奎. 中国主要乔木树种生物量方程[J]. 中南林业科技大学学报, 2019, 39(5):63-69.
[30] SALIS S M, ASSIS M A, MATTOS P P, et al. Estimating the aboveground biomass and wood volume of savanna woodlands inBrazil's Pantanal wetlans based on allometric correlations[J]. Forest Ecology and Management, 2006, 228(1):61-68.
[31] 刘坤, 曹林, 汪贵斌. 银杏生物量分配格局及异速生长模型[J]. 北京林业大学学报, 2017, 39(4):12-20.
[32] 符利勇, 雷渊才, 孙伟, 等. 不同林分起源的相容性模型构建. 生态学报, 2014, 34(6):1461-1470.
[33] 曾伟生. 加权回归估计中不同权函数的对比分析[J]. 林业资源管理, 2013(5):55-61.
[34] BERK N K. Validating regression procedures with new data[J]. Technometrics, 2012, 26(4):331-338.
[35] SHAO Jun. Linear model selection by cross-validation[J]. Journal of the American Statistical Association, 2012, 88(422):486-494.
[36] KOZAK A, KOZAK R. Does cross validation provide additional information in the evaluation of regression models?[J]. Canadian Journal of Forest Research, 2003, 33(6):976-987.
[37] 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.
[38] 郑雪婷, 仪律北, 李强峰, 等. 青藏高原典型人工林幼树生物量模型构建[J]. 应用生态学报, 2022, 33(11):2923-2935.
[39] 王微, 王冰, 张向龙, 等. 内蒙古大兴安岭天然白桦生物量估算模型[J]. 西北林学院学报, 2023, 38(6):180-188.
[40] 梁瑞婷, 王轶夫, 邱思玉, 等. 人工神经网络与相容性生物量模型预测单木地上生物量的比较[J]. 应用生态学报, 2022, 33(1):9-16.
Outlines

/