Developing a height-diameter relationship model with mixed random
 effects for Larix principis-rupprechtii natural secondary forests

doi:10.3969/j.issn.1000-2006.201703014

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2018, Vol. 42 ›› Issue (02): 163-169.doi: 10.3969/j.issn.1000-2006.201703014

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Developing a height-diameter relationship model with mixed random effects for Larix principis-rupprechtii natural secondary forests

DUAN Guangshuang^1,2,LI Xuedong³, FENG Yan⁴, FU Liyong^1*

1. Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China; 2.College of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, China; 3.Experimental Centre of Forestry in North China, Chinese Academy of Forestry, Beijing 102300, China; 4. Chinese Academy of Forestry, Beijing 100091, China

Online:2018-04-12 Published:2018-04-12

Abstract

Abstract: 【Objective】This study aimed to develop a height-diameter relationship model of Larix principis-rupprechtii natural secondary forests as technical support for sustainable forest management.【Method】Based on individual tree data for 116 plots of Larix principis-rupprechtii natural secondary forests, an optimal basic model was selected from 11 candidate models with biological significance. Taking into account the disturbance from regions and sample plots, a nonlinear mixed-effects model with dummy variables for height-diameter relationships based on 94 plots was constructed, and validation was implemented on 22 surplus plots.【Result】The optimal model of 11 alternative models was fitted to the total data with alogistic equation, and the coefficient of determination and root mean square error were 0.765 3, 3.279 4, respectively. After adjusting the precision of the mixed-effects model with dummy variables and random effects, established with the modeling data, the coefficient of determination and root mean square error were 0.915 2, 1.892 2, respectively, which is a distinctly improvment compared with the basic model. The prediction effects of this model were perfect with the use of the validation data.【Conclusion】The disturbance from plot level random effects significantly influenced the height-diameter relationship.The prediction accuracy of the height-diameter relationship model with these random effects was improved obviously. The prediction of tree height of other plots in Larix principis-rupprechtii natural secondary forests can be implemented with this nonlinear mixed-effects model with dummy variables.

CLC Number:

S758

DUAN Guangshuang,LI Xuedong, FENG Yan, FU Liyong. Developing a height-diameter relationship model with mixed random effects for Larix principis-rupprechtii natural secondary forests [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2018, 42(02): 163-169.

References

[1] VARGASLARRETA B, CASTEDODORADO F, ÁLVAREZGONZÁLEZ J G, et al. A generalized height-diameter model with random coefficients for uneven-aged stands in El Salto, Durango(Mexico)[J]. Forestry, 2009, 84(4): 445-462.DOI:10.1093/forestry/cpp016.
[2] PENG C, ZHANG L, LIU J. Developing and validating nonlinear height-diameter models for major tree species of Ontario's boreal forests[J]. Northern Journal of Applied Forestry, 2001, 18(3): 87-94.
[3] TEMESGEN H, GADOW K V. Generalized height-diameter models: an application for major tree species in complex stands of interior British Columbia[J]. European Journal of Forest Research, 2004, 123(1): 45-51.DOI:10.1007/s10342-004-0020-z.
[4] ARABATZIS A A, BURKHART H E. An evaluation of sampling methods and model forms for estimating height-diameter relationships in loblolly pine plantations[J]. Forest Science, 1992, 38(1): 192-198.
[5] HUANG S, PRICE D S J T. Development of ecoregion-based height-diameter models for white spruce in boreal forests[J]. Forest Ecology & Management, 2000, 129(1): 125-141.DOI:10.1016/S0378-1127(99)00151-6.
[6] 马小欣,姜鹏,马娇娇,等.沿坝地区华北落叶松胸径-树高生长模型的研究[J].林业资源管理,2015(1):44-48.DOI:10.13466/j.cnki.lyzygl.2015.01.008. MA X X, JIANG P, MA J J, et al. Study on DBH-tree height growth model of Larix principis-rupprechtii along the DAM ecotone[J]. Forest Resources Management, 2015(1): 44-48.
[7] 王冬至,张冬燕,王方,等.塞罕坝主要立地类型针阔混交林树高曲线构建[J].北京林业大学学报,2016, 38(10):7-14.DOI:10.13332/j.1000--1522.20150359. WANG D Z, ZHANG D Y, WANG F, et al. Height curve construction of needle and broadleaved mixed forest under main site types in Saihanba,Hebei of northern China[J]. Journal of Beijing Forestry University, 2016, 38(10): 7-14.
[8] 王冬至,张冬燕,张志东,等.基于非线性混合模型的针阔混交林树高与胸径关系[J].林业科学,2016, 52(1):30-36.DOI:10.11707/j.1001-7488.20160104. WANG D Z, ZHANG D Y, ZHANG Z D, et al. Height-diameter relationship for conifer mixed forest based on nonlinear mixed-effects model[J]. Scientia Silvae Sinicae, 2016, 52(1): 30-36.
[9] 符利勇,何铮,刘应安.关帝山天然次生针叶林林隙大小模型研究[J].南京林业大学学报(自然科学版),2010, 34(5):51-54.DOI:10.3969/j.issn.1000-2006.2010.05.011. FU L Y, HE Z, LIU Y A. Study of the gap size model in a secondary coniferous forest of Guandi Mountain[J]. Journal of Nanjing Forestry University(Natural Sciences Edition), 2010, 34(5): 51-54.
[10] 菇文明,张峰.山西五台山种子植物区系分析[J].植物研究,2000, 20(1):36-47.DOI: 10.3969/j.issn.1673-5102.2000.01.007. GU W M, ZHANG F. Analysis on the flora of seed plants of Wutai Mountains, Shanxi[J]. Bulletin of Botanical Research, 2000, 20(1): 36-47.
[11] MEHTÄTALO L, DEMIGUEL S, GREGOIRE T G. Modeling height-diameter curves for prediction[J]. Canadian Journal of Forest Research, 2015, 45: 826-837.DOI:10.1139/cjfr-2015-0054.
[12] DANIEL L, JEFFERY G. A height-diameter curve for longleaf pine plantations in the GULF coastal plain[J]. Southern Journal of Applied Forestry, 2009, 33(4): 164-170. DOI:10.1007/s11258-009-9605-4.
[13] 李春明,唐守正.基于非线性混合模型的落叶松云冷杉林分断面积模型[J].林业科学,2010, 46(7):106-113.DOI:10.11707/j.1001-7488.20100716. LI C M, TANG S Z. The basal area model of mixed stands of Larix olgensis, Abies nephrolepis and Picea jezoensis based on nonlinear mixed model[J]. Scientia Silvae Sinicae, 2010, 46(7): 106-113.
[14] FANG Z, BAILEY R L. Nonlinear mixed effects modeling for slash pine dominant height growth following intensive silvicultural treatments[J]. Forest Science, 2001, 47(3): 287-300.DOI:10.1046/j.1439-0329.2001.00240.x.
[15] HALL D B, BAILEY R L. Modeling and prediction of forest growth variables based on multilevel nonlinear mixed models[J]. Forest Science, 2001, 47(3): 311-321.DOI:10.1046/j.1439-0329.2001.00240.x.
[16] FU L, SUN H, SHARMA R P, et al. Nonlinear mixed-effects crown width models for individual trees of Chinese fir(Cunninghamia lanceolata)in south-central China[J]. Forest Ecology & Management, 2013, 302(6): 210-220.DOI:10.1016/j.foreco.2013.03.036.
[17] MENG S, HUANG S. Improved calibration of nonlinear mixed-effects models demonstrated on a height growth function[J]. Forest Science, 2009, 55(3):238-248.
[18] FU L, ZHANG H, SHARMA R P, et al. A generalized nonlinear mixed-effects height to crown base model for Mongolian oak in northeast China[J]. Forest Ecology & Management, 2017,384(1):34-43.DOI:10.1016/j.foreco.2016.09.012.
[19] PINHEIRO J C, BATES D M. Mixed-effects models in S and S-PLUS[M]. New York: Springer, 2000.
[20] GREGOIRE T G. Generalized error structure for forestry yield models[J]. Forest Science, 1987, 33(2): 423-444.
[21] PINHEIRO J C, BATES D M. Approximations to the Log-Likelihood function in the nonlinear mixed-effects model[J]. Journal of Computational & Graphical Statistics, 1995, 4(1): 12-35.DOI:10.1080/10618600.1995.10474663.
[22] WOLFINGER R D. An example of using mixed models and PROC MIXED for longitudinal data[J]. Journal of Biopharmaceutical Statistics, 1997, 7(4): 481.DOI:10.1080/10543409708835203.
[23] 符利勇,张会儒,唐守正.基于非线性混合模型的杉木优势木平均高[J].林业科学,2012, 48(7):66-71.DOI:10.11707/j.1001-7488.20120711. FU L Y, ZHANG H R, TANG S Z. Dominant height for Chinese fir plantation using nonlinear mixed effects model based on linearization algorithm[J]. Scientia Silvae Sinicae, 2012, 48(7): 66-71.
[24] CALAMA R, MONTERO G. Interregional nonlinear height-diameter model with random coefficients for stone pine in Spain[J]. Canadian Journal of Forest Research, 2004, 34(1): 150-163.DOI:10.1139/x03-199.

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Developing a height-diameter relationship model with mixed random effects for Larix principis-rupprechtii natural secondary forests

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