基于种源和气候效应的日本落叶松树高生长模型研究

盖军鹏; 陈东升; 贾炜玮; 王政

doi:10.12302/j.issn.1000-2006.202112005

盖军鹏, 陈东升, 贾炜玮, 王政

南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (4) : 51-60.

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南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (4) : 51-60. DOI: 10.12302/j.issn.1000-2006.202112005

专题报道：第三届中国林草计算机应用大会论文精选（Ⅱ）（执行主编李凤日）

基于种源和气候效应的日本落叶松树高生长模型研究

盖军鹏 ¹^,² ,
陈东升 ³^,^* ,
贾炜玮 ¹ ,
王政 ¹^,²

作者信息 +

Developing height growth model of Larix kaempferi based on genetic and climate effects

GAI Junpeng ¹^,² ,
CHEN Dongsheng ³^,^* ,
JIA Weiwei ¹ ,
WANG Zheng ¹^,²

Author information +

文章历史 +

摘要

【目的】研究遗传效应和气候变化对日本落叶松(Larix kaempferi)树高生长的影响,为开展精准立地质量评价和制定合理的经营方案提供支持。【方法】基于湖北省建始县长岭岗林场5~18年生日本落叶松树高生长数据,以Logistic作为基本理论生长模型,将体现遗传效应的种源变量和气候变量引入,以重复作为随机效应的随机参数,构建基于遗传和气候效应的日本落叶松树高生长模型,并分析遗传效应和气候变化对树高生长的影响。【结果】温度和降水是影响该地区树高生长的主要气候因子,引入种源哑变量和气候变量后,模型的拟合精度高于基础模型;以重复作为随机效应构建的非线性混合模型的拟合效果(R_adj²=0.820 3)优于考虑遗传和气候因素的生长模型(R_adj²=0.806 2)及Logistic基础模型(R_adj²=0.798 9);不同种源树高生长均符合“慢—快—慢”的生长规律,但达到速生点的时间t₀不同,各时间节点上不同种源树高生长存在极显著差异。【结论】遗传和气候效应对日本落叶松树高生长存在一定的影响,构建基于遗传和气候效应的混合模型,能有效提高模型的拟合精度。

Abstract

【Objective】 This study provides supports for accurate site quality evaluation and reasonable management plans for Larix kaempferi by studying the effects of genetic and climate changes on plant height. 【Method】 Using height growth data from L. kaempferi trees aged from 5 to 18 years in the Changlinggang Forest Farm in Jianshi County, Hubei Province and the Logistic equation as the basic theoretical growth model, we introduced provenances and climate variables reflecting genetic effects and used repetition as random parameters to construct a tree height growth model. Using this model, we were then able to analyze the effects of genetic and climate changes on tree height growth. 【Result】 Temperature and precipitation were the main climatic factors affecting L. kaempferi tree height growth in this area. Furthermore, the fitting accuracy of the model with temperature and precipitation inputs was higher than that of the basic model. Additionally, nonlinear mixed model based on repetition as a random effect (R_adj²=0.820 3) fit better than did the growth model considering genetic and climatic factors (R_adj²=0.806 2) and the basic logistic model (R_adj²= 0.798 9). The height growth of different provenances was in accordance with the law of ‘slow-fast-slow’ growth; however, the time to reach the fast-growing point varied, and there were significant discrepancies in height growth among different provenances at different time nodes. 【Conclusion】 Genetic and climatic factors affected the height of L. kaempferi. Furthermore, the construction of a mixed model based on genetic and climatic effects can effectively improve the fitting accuracy of a model.

导出引用

盖军鹏, 陈东升, 贾炜玮, 等. 基于种源和气候效应的日本落叶松树高生长模型研究[J]. 南京林业大学学报（自然科学版）. 2023, 47(4): 51-60 https://doi.org/10.12302/j.issn.1000-2006.202112005

GAI Junpeng, CHEN Dongsheng, JIA Weiwei, et al. Developing height growth model of Larix kaempferi based on genetic and climate effects[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2023, 47(4): 51-60 https://doi.org/10.12302/j.issn.1000-2006.202112005

中图分类号： S757

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]	马常耕. 从世界落叶松遗传改良现状论我国落叶松良种化的对策[J]. 世界林业研究, 1992, 5(1):57-65. MA C G. The present state of genetic improvement of larchs in the world and the future developmental strategies in China[J]. World For Res, 1992, 5(1):57-65.DOI: 10.13348/j.cnki.sjlyyj.1992.01.010. 本文引用 [1]

[2]	AHTIKOSKI A, AHTIKOSKI R, HAAPANEN M, et al. Economic performance of genetically improved reforestation material in joint production of timber and carbon sequestration:a case study from Finland[J]. Forests, 2020, 11(8):847.DOI: 10.3390/f11080847. 本文引用 [1]

[3]	JOO S, MAGUIRE D, JAYAWICKRAMA K, et al. Estimation of yield gains at rotation-age from genetic tree improvement in coast Douglas-fir[J]. For Ecol Manag, 2020, 466(5-6):117930.DOI: 10.1016/j.foreco.2020.117930. 本文引用 [1]

[4]	AHTIKOSKI A, HAAPANEN M, HYNYNEN J, et al. Genetically improved reforestation stock provides simultaneous benefits for growers and a sawmill,a case study in Finland[J]. Scand J For Res, 2018, 33(5):484-492. 本文引用 [1]

[5]	卢晨升. 不同种源邓恩桉遗传变异分析及选择[D]. 南宁: 广西大学, 2018. LU C S. Genetic variation analysis and selection of Eucalyptus dunnii from different provenances[D]. Nanning: Guangxi University, 2018. 本文引用 [2]

[6]	伍汉斌, 段爱国, 张建国. 杉木地理种源不同林龄生长变异及选择[J]. 林业科学, 2019, 55(10):181-192. WU H B, DUAN A G, ZHANG J G. Growth variation and selection effect of Cunninghamia lanceolata provenances at different stand ages[J]. Sci Silvae Sin, 2019, 55(10):181-192.DOI: 10.11707/j.1001-7488.20191018. 本文引用 [1]

[7]

李培, 阙青敏, 欧阳昆唏, 等. 不同种源红椿SRAP标记的遗传多样性分析[J]. 林业科学, 2016, 52(1):62-70.

, QUE

Q M

, OUYANG

K X

, et al. Genetic diversity of Toona ciliata from different provenances based on sequence-related amplified polymorphism (SRAP) markers[J]. Sci Silvae Sin, 2016, 52(1):62-70.DOI: 10.11707/j.1001-7488.20160108.

本文引用 [1]

[8]	王亚南. 基于哑变量和非线性混合模型方法研究华山松种源对树高生长模型参数的影响[D]. 郑州: 河南农业大学, 2013. WANG Y N. Based on dummy variable and nonlinear mixed model method,the influence of Pinus armandii provenance on tree height growth model parameters was studied[D]. Zhengzhou: Henan Agricultural University, 2013. 本文引用 [2]

[9]	PAN Y Y, LI S C, WANG C L, et al. Early evaluation of growth traits of Larix kaempferi clones[J]. J For Res, 2018, 29(4):1031-1039.DOI: 10.1007/s11676-017-0492-6. 本文引用 [2]

[10]	LIANG D Y, DING C J, ZHAO G H, et al. Variation and selection analysis of Pinus koraiensis clones in northeast China[J]. J For Res, 2018, 29(3):611-622.DOI: 10.1007/s11676-017-0471-y. 本文引用 [2]

[11]	XIA H, ZHAO G H, ZHANG L S, et al. Genetic and variation analyses of growth traits of half-sib Larix olgensis families in northeastern China[J]. Euphytica, 2016, 212(3):387-397.DOI: 10.1007/s10681-016-1765-4. 本文引用 [1]

[12]	孙晓梅. 日本落叶松纸浆材优良家系选择及家系生长模型的研究[D]. 北京: 中国林业科学研究院, 2003. SUN X M. Study on the selection of superior families of Larix kaempferi pulp wood and family growth model[D]. Beijing: Chinese Academy of Fores-try, 2003. 本文引用 [1]

[13]

肖锐, 陈东升, 李凤日, 等. 基于两水平混合模型的杂种落叶松胸径和树高生长模拟[J]. 东北林业大学学报, 2015, 43(5):33-37.

XIAO

, CHEN

D S

, LI

F R

, et al. Simulating DBH and height growth of trees for hybrid larch plantation with two-level mixed effect model[J]. J Northeast For Univ, 2015, 43(5):33-37.DOI: 10.13759/j.cnki.dlxb.20150522.025.

本文引用 [1]

[14]	LI C M, XIA H, BAI H, et al. Genetic variation of height growth rhythm between clones of Larix kaempferi × L. gmelini based on Logistic models[J]. J For Res, 2018, 29(5):1387-1394.DOI: 10.1007/s11676-017-0558-5. 本文引用 [1]

[15]	陈东升, 孙晓梅, 李凤日. 基于混合模型的落叶松树高生长模型[J]. 东北林业大学学报, 2013, 41(10):60-64. CHEN D S, SUN X M, LI F R. Predicting models of tree height growth for larch based on mixed model[J]. J Northeast For Univ, 2013, 41(10):60-64.DOI: 10.13759/j.cnki.dlxb.2013.10.021. 本文引用 [1]

[16]	PARMESAN C, YOHE G. A globally coherent fingerprint of climate change impacts across natural systems[J]. Nature, 2003, 421(6918):37-42.DOI: 10.1038/nature01286. 本文引用 [2]

[17]	臧颢. 区域尺度气候敏感的落叶松人工林林分生长模型[D]. 北京: 中国林业科学研究院, 2016. ZANG H. Growth model of Larix gmelinii plantation with climate sensitivity at regional scale[D]. Beijing: Chinese Academy of Forestry, 2016. 本文引用 [2]

[18]	吴梦婉. 辽宁章古台沙地樟子松人工林树木生长及其对气候的响应[D]. 北京: 北京林业大学, 2019. WU M W. Tree growth and its response to climate in Pinus sylvestris var.mongolica plantation in Zhanggutai sandy land,Liaoning Province[D]. Beijing: Beijing Forestry University, 2019. 本文引用 [1]

[19]	MÉLAINE A K, EMILY M. Climate impacts on tree growth in the sierra Nevada[J]. Multidisciplinary Digital Publishing Institute, 2017, 8(11):1190-1199. DOI:10.3390/f8110414. 本文引用 [1]

[20]	SHARMA M, SUBEDI N, TER-MIKAELIAN M, et al. Modeling climatic effects on stand height/site index of plantation-grown jack pine and black spruce trees[J]. For Sci, 2015, 61(1):25-34.DOI: 10.5849/forsci.13-190. 本文引用 [1]

[21]	王宇超, 陈逸飞, 林晨蕾, 等. 森林抚育间伐对杉木人工林温湿度的影响研究[J]. 森林工程, 2022, 38(1): 9-14, 26. WANG Y C, CHEN Y F, LIN C L, et al. Effects of forest tending and thinning on temperature and humidity of Chinese fir plantation[J]. Forest Engineering, 2022, 38(1): 9-14, 26. 本文引用 [2]

[22]	刘帅, 李建军, 卿东升, 等. 气候敏感的青冈栎单木胸径生长模型[J]. 林业科学, 2021, 57(1):95-104. LIU S, LI J J, QING D S, et al. A climate-sensitive individual-tree DBH growth model for Cyclobalanopsis glauca[J]. Sci Silvae Sin, 2021, 57(1):95-104.DOI: 10.11707/j.1001-7488.20210110. 本文引用 [2]

[23]	赵曦阳, 张志毅. 毛白杨种内杂交无性系苗期生长模型构建[J]. 北京林业大学学报, 2013, 35(5):15-21. ZHAO X Y, ZHANG Z Y. Model construction of seedling growth for hybrid clones of Populus tomentosa[J]. J Beijing For Univ, 2013, 35(5):15-21.DOI: 10.13332/j.1000-1522.2013.05.018. 本文引用 [1]

[24]

祖笑锋, 倪成才, NIGH

, 等. 基于混合效应模型及EBLUP预测美国黄松林分优势木树高生长过程[J]. 林业科学, 2015, 51(3):25-33.

X F

, NI

C C

, NIGH

, et al. Based on mixed-effects model and empirical best linear unbiased predictor to predict growth profile of dominant height[J]. Sci Silvae Sin, 2015, 51(3):25-33.DOI: 10.11707/j.1001-7488.20150304.

本文引用 [1]

[25]	魏辉. 亚热带木荷生长过程及其年轮气候学研究[D]. 长沙: 中南林业科技大学, 2017. WEI H. Study on growth process and dendroclimatology of Schima superba in subtropical zone[D]. Changsha: Central South University of Forestry & Technology, 2017. 本文引用 [1]

[26]	郑淑霞, 上官周平. 树木年轮与气候变化关系研究[J]. 林业科学, 2006, 42(6):100-107. ZHENG S X, SHANGGUAN Z P. Study on relationship between tree-ring and climatic change[J]. Sci Silvae Sin, 2006, 42(6):100-107.DOI: 10.3321/j.issn:1001-7488.2006.06.017. 本文引用 [1]

[27]	罗元, 孙琪, 蔡年辉, 等. 云南松不同种源1年生播种苗木生长节律分析[J]. 西南林业大学学报, 2016, 36(3):23-29. LUO Y, SUN Q, CAI N H, et al. Growth rhythm analysis on annual planting seedlings of Pinus yunnanensis from different provenances[J]. J Southwest For Univ, 2016, 36(3):23-29. 本文引用 [1]

[28]

吴宏炜, 张伟志, 田意, 等. 基于哑变量的湿地松林分断面积生长模型[J]. 中南林业科技大学学报, 2021, 41(1):117-123,150.

H W

, ZHANG

W Z

, TIAN

, et al. Basal area growth model for Pinus elliottii forest based on dummy variables[J]. J Central South Univ For Technol, 2021, 41(1):117-123,150.DOI: 10.14067/j.cnki.1673-923x.2021.01.012.

本文引用 [1]

[29]	贾炜玮, 罗天泽, 李凤日. 基于抚育间伐效应的红松人工林枝条密度模型[J]. 北京林业大学学报, 2021, 43(2):10-21. JIA W W, LUO T Z, LI F R. Branch density model for Pinus koraiensis plantation based on thinning effects[J]. J Beijing For Univ, 2021, 43(2):10-21.DOI: 10.12171/j.1000-1522.20200057. 本文引用 [1]

[30]	王冬至, 张冬燕, 李永宁, 等. 基于贝叶斯法的针阔混交林树高与胸径混合效应模型[J]. 林业科学, 2019, 55(11):85-94. WANG D Z, ZHANG D Y, LI Y N, et al. Height-diameter relationship for conifer mixed forest based on Bayesian nonlinear mixed-effects model[J]. Sci Silvae Sin, 2019, 55(11):85-94.DOI: 10.11707/j.1001-7488.20191110. 本文引用 [1]

[31]	TIMILSINA N, STAUDHAMMER C L. Individual tree-based diameter growth model of slash pine in Florida using nonlinear mixed modeling[J]. For Sci, 2013, 59(1):27-37.DOI: 10.5849/forsci.10-028. 本文引用 [1]

[32]	王伟峰, 廖为明, 王强, 等. 樟子松人工林树高生长对气候因子的响应研究[J]. 江西林业科技, 2009, 37(3):1-5. WANG W F, LIAO W M, WANG Q, et al. Studies on the respond of height growth to the climate factors in Pinus sylvestris plantation[J]. Jiangxi For Sci Technol, 2009, 37(3):1-5.DOI: 10.16259/j.cnki.36-1342/s.2009.03.008. 本文引用 [1]

[33]	周晏平. 辽宁章古台樟子松树高生长影响因素分析[D]. 阜新: 辽宁工程技术大学, 2019. ZHOU Y P. Analysis of influencing factors on height growth of Pinus sylvestris var.mongolica in Zhanggutai,Liaoning Province[D]. Fuxin:Liaoning Technical University, 2019. 本文引用 [1]