长白落叶松人工林心材变化规律

doi:10.13287/j.1001-9332.201807.017

应用生态学报 ›› 2018, Vol. 29 ›› Issue (7): 2277-2285.doi: 10.13287/j.1001-9332.201807.017

长白落叶松人工林心材变化规律

贾炜玮, 朱飞燕, 李凤日^*

东北林业大学林学院, 哈尔滨 150040

收稿日期:2017-12-28 出版日期:2018-07-18 发布日期:2018-07-18
通讯作者: *E-mail: fengrili@126.com
作者简介:贾炜玮, 男, 1978年生, 副教授. 主要从事森林经理学研究. E-mail: jiaww2002@163.com
基金资助:
本文由国家重点研发计划项目(2017YFD0600404-2)、中央高校基本科研业务费专项(2572014CA17)和国家自然科学基金项目(31570626)资助.

Change pattern of heartwood of Larix olgensis plantation.

JIA Wei-wei, ZHU Fei-yan, LI Feng-ri^*

College of Forestry, Northeast Forestry University, Harbin 150040, China

Received:2017-12-28 Online:2018-07-18 Published:2018-07-18
Contact: *E-mail: fengrili@126.com
Supported by:
This work was supported by the National Key Research and Development Program of China (2017YFD0600404-2), the Fundamental Research Funds for the Central Universities (2572014CA17), and the National Natural Foundation of China (31570626).

摘要/Abstract

摘要： 依据黑龙江省孟家岗林场49株人工落叶松1179个圆盘和轮盘数据,分析了心材半径的纵向变化规律.结果表明: 心材半径随树高增高而逐渐减小,与树干外形基本一致,其中去皮半径(XR)、胸径(DBH)及形成层年龄(CA)与心材半径之间关系较显著,利用逐步回归分析建立落叶松心材半径(HR)和面积(HA)模型:HR=b₁+b₂XR²+b₃CA+b₄XR, HA=b₁+b₂DBH·XR+b₃CA+b₄DBH·XR².应用AIC、BIC、对数似然值以及似然比检验等模型评价指标,对利用样地、样木效应拟合的心材半径和面积模型进行比较.当考虑样木效应拟合心材半径和面积模型时,将b₁、b₂、b₃作为混合参数得出的模型最好.混合模型的预测精度高于基本模型.在应用上,总体心材半径和面积可以通过混合模型来预测.采用Beta回归模型模拟了心材比例,模型中各参数均显著,决定系数较高,模型模拟效果较好.

关键词: 人工落叶松林, Beta回归模型, 心材面积, 混合模型, 心材半径

Abstract: Based on the data of 1179 discs and whorls of 49 trees from larch (Larix olgensis) plantations located in Mengjiagang forest farm in Heilongjiang Province, China, we analyzed the longitudinal variation pattern of heartwood radius. The results showed that the heartwood radius decreased with the increases of tree height, which was basically the same as the trunk shape. The relationship between the xylem radius (XR), diameter at breast height (DBH) and cambial age (CA) with the heartwood radius was significant. The stepwise regression analysis was used to develop heartwood radius (HR) and heartwood area (HA) models: HR=b₁+b₂XR²+b₃CA+b₄XR, HA=b₁+b₂DBH·XR+b₃CA+b₄DBH·XR². We used the evaluation statistics such as AIC, BIC, Log Likelihood and Likelihood ratio test to compare the heartwood radius and heartwood area models which fitted with the plot effect and tree effect. The heartwood radius and heartwood area models with parameters b₁, b₂, b₃ as mixed effects performed best when the tree effect was considered. The prediction accuracy of the mixed model was better than that of the basic model. In the application, the total heartwood radius and area could be predicted by the mixed model. Beta regression model was used to simulate the heartwood proportion. In this model, all parameters were significant, and the coefficients of determination were relatively high, with a good simulation effect.

Key words: heartwood area, mixed model, Beta regression model, Larix olgensis plantation, heartwood radius

贾炜玮, 朱飞燕, 李凤日. 长白落叶松人工林心材变化规律[J]. 应用生态学报, 2018, 29(7): 2277-2285.

JIA Wei-wei, ZHU Fei-yan, LI Feng-ri. Change pattern of heartwood of Larix olgensis plantation.[J]. Chinese Journal of Applied Ecology, 2018, 29(7): 2277-2285.

参考文献 31

[1]	Guo Y-X (郭妍雪), Jiang L-C (姜立春). Variation of heartwood and sapwood and growth characteristics of artificial Dahurian larch. Journal of Northeast Forestry University (东北林业大学学报), 2015, 43(6): 93-97 (in Chinese)
[2]	Cui Z-Y (崔之益), Xu D-P (徐大平), Yang Z-J (杨曾奖), et al. A review of mechanism and artificial promotion of heartwood formation. World Forestry Research (世界林业研究), 2016, 29(6): 33-37 (in Chinese)
[3]	Pinto I, Pereira H, Usenius A. Heartwood and sapwood development within maritime pine (Pinus pinaster Ait.) stems. Trees, 2004, 18: 284-294
[4]	Wang Q-Y (王庆云). The temporal and spatial variation of the content and ring number of the heartwood and sapwood of the trees. Protection Forest Science and Technology (防护林科技), 2010(6): 70-74 (in Chinese)
[5]	Wang X-C (王兴昌), Wang C-K (王传宽), Zhang Q-Z (张全智), et al. Growth characteristics of heartwood and sapwood of the major tree species in northeastern China. Scientia Silvae Sinicae (林业科学), 2008, 44(5): 102-108 (in Chinese)
[6]	Long JN, Smith FW. Leaf area-sapwood area relations of lodgepole pine as influenced by stand density and site index. Canadian Journal of Forest Research, 1988, 18: 247-250
[7]	Hillis WE. Heartwood and Tree Exudates. Berlin: Springer Verlag, 1987
[8]	Yang KC, Chen YS, Chiu C, et al. Formation and vertical distribution of sapwood and heartwood in Cryptomeria japonica D. Don. Trees, 1994, 9: 35-40
[9]	Sellin A. Sapwood-heartwood proportion related to tree diameter, age, and growth rate in Picea abies. Canadian Journal of Forest Research, 1994, 24: 1022-1028
[10]	Miranda I, Gominho J, Pereira H. Variation of heartwood and sapwood in 18-year-old Eucalyptus globulus, trees grown with different spacings. Trees, 2009, 23: 367-372
[11]	Climent J, Chambel MR, Pérez E, et al. Relationship between heartwood radius and early radial growth, tree age, and climate in Pinus canariensis. Canadian Journal of Forest Research, 2002, 32: 103-111
[12]	Liu J-L (刘家霖), Wang C-K (王传宽), Zhang Q-Z (张全智). Spatial variations in stem heartwood and sapwood for Larix gmelinii trees with various differentiation classes. Scientia Silvae Sinicae (林业科学), 2014, 50(12): 114-121 (in Chinese)
[13]	Liu S (刘盛), Li G-W (李国伟). Tree structure based on pipe model theory. Journal of Northeast Forestry University (东北林业大学学报), 2006, 34(6): 15-16 (in Chinese)
[14]	Liu S (刘盛), Song Q-M (宋全民). Discussion on the vertical distribution of the sapwood in the trunk of Larix principis. Journal of Jilin Forestry Institute (吉林林学院学报), 1992(2): 57-60 (in Chinese)
[15]	Knapic S, Tavares F, Pereira H. Heartwood and sapwood variation in Acacia melanoxylon R. Br. trees in Portugal. Forestry, 2006, 79: 371-380
[16]	Climent J, Chambel MR, Gil L, et al. Vertical heartwood variation patterns and prediction of heartwood volume in Pinus canariensis Sm. Forest Ecology and Management, 2003, 174: 203-211
[17]	Flæte PO, Høibø O. Models for predicting vertical profiles of heartwood diameter in mature Scots pine. Canadian Journal of Forest Research, 2009, 39: 527-536
[18]	Li Z-A (李泽安), Ge J-F (葛建芳), Zhang Y-J (章雅娟). Application of Beta regression model for the data mining forecast. Journal of Nantong University (Natural Science) (南通大学学报: 自然科学版), 2009, 8(3): 83-85 (in Chinese)
[19]	Huang X-S (黄晓姗), Liu J-H (刘建华). The application of Beta regression model in the proportion of aging population in China. Journal of Mudanjiang Normal University (Natural Science) (牡丹江师范学院学报: 自然科学版), 2015(3): 9-11 (in Chinese)
[20]	Jia W-W (贾炜玮), Sun S-Q (孙守强), Li F-R (李凤日), et al. Branch dynamics for the Korean pine plantation based on linear mixed model. Bulletin of Botanical Research (植物研究), 2015, 35(3): 425-430 (in Chinese)
[21]	Ferrari S, Cribari-Neto F. Beta regression or modeling rates and proportions. Journal of Applied Statistics, 2004, 31: 799-815
[22]	Jiang L-C (姜立春), Zhang R (张锐), Li F-R (李凤日). Modeling branch length and branch angle with linear mixed effects for Dahurian larch. Scientia Silvae Sinicae (林业科学), 2012, 48(5): 53-60 (in Chinese)
[23]	Li Y-X (李耀翔), Jiang L-C (姜立春). Modeling wood density with two-level linear mixed effects models for Dahurian larch. Scientia Silvae Sinicae (林业科学), 2013, 49(7): 91-98 (in Chinese)
[24]	Dong L-H (董利虎), Li F-R (李凤日), Jia W-W (贾炜玮). Linear mixed modeling of branch biomass for Korean pine plantation. Chinese Journal of Applied Ecology (应用生态学报), 2013, 24(12): 3391-3398 (in Chinese)
[25]	Jiang L-C (姜立春), Li F-R (李凤日), Zhang R (张锐). Modeling branch diameter with linear mixed effects for Dahurian larch. Forest Research (林业科学研究), 2012, 25(4): 464-469 (in Chinese)
[26]	Li Y-X (李耀翔), Jiang L-C (姜立春), Li F-R (李凤日). Modeling microibril angle with mixed models for Dahurian larch. Scientia Silvae Sinicae (林业科学), 2012, 48(4): 81-86 (in Chinese)
[27]	Fan W (樊伟), Xu C-H (许崇华), Cui J (崔珺), et al. Comparisons of height-diameter models of Chinese fir based on mixed effect in Dabie Mountain area, China. Chinese Journal of Applied Ecology (应用生态学报), 2017, 28(9): 2831-2839 (in Chinese)
[28]	Xu H (许昊), Sun Y-J (孙玉军), Wang X-J (王新杰), et al. Simulation of the branch biomass for Chinese fir plantation using the linear mixed effects model. Chinese Journal of Applied Ecology (应用生态学报), 2015, 26(10): 2969-2977 (in Chinese)
[29]	Jiang L-C (姜立春), Du S-L (杜书立). Height and diameter growth modeling of Dahurian larch based on nonlinear mixed model in northeastern China. Forest Research (林业科学研究), 2012, 25(1): 11-16 (in Chinese)
[30]	Pinheiro JC, Bates DM. Mixed-Effects Models in S and S-Plus. New York: Springer, 2000
[31]	Fang Z, Bailey RL. Nonlinear mixed effects modeling for Slash pine dominant height growth following intensive silvicultural treatments. Forest Science, 2001, 47: 287-300

长白落叶松人工林心材变化规律

Change pattern of heartwood of Larix olgensis plantation.

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 31

相关文章 14

编辑推荐

Metrics

本文评价

[1]	李泽霖, 贾炜玮, 郭昊天, 敖子琦, 赵阳. 三种针叶树种节子属性通用方程的构建 [J]. 应用生态学报, 2023, 34(11): 2907-2918.
[2]	徐俊伟, 张波, 张崇良, 徐宾铎, 纪毓鹏, 任一平, 薛莹. 基于线性混合模型研究海州湾六丝钝尾虾虎鱼摄食生态 [J]. 应用生态学报, 2022, 33(9): 2563-2571.
[3]	陈旋, 李玉娥, 万运帆, 高清竹, 王斌, 秦晓波. 基于¹³C、¹⁵N和C/N识别南岳小流域沉积有机质的来源 [J]. 应用生态学报, 2021, 32(6): 1998-2006.
[4]	李蕾, 汪旭明, Rudi Schäufele, 蔡炳贵, 巩晓颖. 聚四氟乙烯塑料管研磨法对测定C4植物碳同位素比值的影响 [J]. 应用生态学报, 2021, 32(6): 1963-1970.
[5]	贾炜玮, 洪燕虎, 李凤日. 人工红松树干内部节子体积预测模型 [J]. 应用生态学报, 2020, 31(9): 2943-2954.
[6]	贾炜玮, 崔璨, 李凤日. 基于混合效应模型的人工红松节子属性 [J]. 应用生态学报, 2018, 29(1): 33-43.
[7]	樊伟, 许崇华, 崔珺, 王晶晶, 刘西军, 徐小牛. 基于混合效应的大别山地区杉木树高-胸径模型比较 [J]. 应用生态学报, 2017, 28(9): 2831-2839.
[8]	王冬至1,张冬燕1,2,蒋凤玲3,柏叶4,张志东1,黄选瑞**. 塞罕坝华北落叶松人工林地位指数模型 [J]. 应用生态学报, 2015, 26(11): 3413-3420.
[9]	许昊,孙玉军**,王新杰,方景,涂宏涛,刘素真. 利用线性混合效应模型模拟杉木人工林枝条生物量 [J]. 应用生态学报, 2015, 26(10): 2969-2977.
[10]	董灵波,刘兆刚**,李凤日,姜立春. 基于线性混合模型的红松人工林一级枝条大小预测模拟 [J]. 应用生态学报, 2013, 24(9): 2447-2456.
[11]	王春红,李凤日**,贾炜玮,董利虎. 基于非线性混合模型的红松人工林枝条生长 [J]. 应用生态学报, 2013, 24(7): 1945-1952.
[12]	董利虎,李凤日**,贾炜玮. 基于线性混合效应的红松人工林枝条生物量模型 [J]. 应用生态学报, 2013, 24(12): 3391-3398.
[13]	陈军锋, 裴铁璠, 陶向新, 刘四旦, 牛丽华. 河流两侧坡面非对称采伐森林对流域暴雨-径流过程的影响 [J]. 应用生态学报, 2000, (2): 210-214.
[14]	刘家冈, 裴铁璠, 范世香, 韩绍文, 牛丽华. 阔叶红松林枯枝落叶滞蓄地表径流作用的一维模型 [J]. 应用生态学报, 1990, 1(2): 107-113.