基于GreenLab原理构建油松成年树的结构-功能 模型

doi:10.3724/SP.J.1258.2011.00422

摘要/Abstract

摘要：

林木的结构-功能模型(functional-structural tree modeling, FSTMs)是基于器官级组件构建的将植物结构和功能结合起来的一类模型, 在应用于成年树时需要解决拓扑结构复杂性和年轮分配模式普适性的问题。该文以18年生和41年生的油松(Pinus tabulaeformis)成年树为研究对象, 将GreenLab模型应用到成年树的模拟中。采用破坏性取样, 实测了2株油松成年树的形态结构, 利用子结构模型解决成年树拓扑结构复杂性的问题, 引入年轮影响系数λ, 将全局分配模式和Pressler模式结合起来, 解决年轮分配模式在不同年龄和环境条件下不同的问题。模型的直接参数通过实测数据获得, 隐含参数利用非线性最小二乘法拟合反求获得。通过实测数据与模拟数据的对比、模拟数据与经验模型模拟数据的对比, 对模型的模拟效果进行了评估, 发现节间总重、针叶总重、树高、树干节间重观测值和模型模拟值建立的回归方程的决定系数为0.84-0.98, 结构-功能模型与经验模型对总生物量模拟的决定系数为0.95, 表明该模型能较真实地反映油松的结构和生长过程。

关键词: 林木结构-功能模型, 油松, 年轮生长, 拓扑结构

Abstract:

Aims In functional-structural plant modeling, trees are composed of elements at the organ level and combined physiological processes and morphological structures. When it is applied to adult trees, we must deal with complexity of topology and consider ring growth. Our objective was to apply the functional structural model GreenLab to adult Pinus tabulaeformis trees and parameterize and validate the model.
Methods Destructive sampling was done to collect detailed data including structure and biomass measurements from one 18-year and one 41-year P. tabulaeformis. To extend its application in adult tree growth analysis, we used substructure model to simplify tree topology and introduce ring biomass allocation parameter λ to mix Pressler model and common pool model to analyze tree ring growth in different ages and different environments. Direct parameters were attained from the measurement data, and hidden parameters of the model were calibrated using the generalized least squares method. The model was validated by comparing simulation data with observed data and comparing simulation data to data calculated by empirical model.
Important findings Simulations of P. tabulaeformis growth based on the fitted parameters were reasonable. The coefficients of determination of linear regression equations between observations and predictions ranged from 0.84 to 0.98. The coefficient of determination of linear regression equations between GreenLab simulation data and empirical simulation data was 0.95. The results showed that the GreenLab model can be a new tool to simulate tree biomass at different growth cycles.

Key words: functional-structural tree modeling, Pinus tabulaeformis, ring growth, topological structure

国红, 雷相东, Veronique LETORT, 陆元昌. 基于GreenLab原理构建油松成年树的结构-功能模型. 植物生态学报, 2011, 35(4): 422-430. DOI: 10.3724/SP.J.1258.2011.00422

GUO Hong, LEI Xiang-Dong, Veronique LETORT, LU Yuan-Chang. A functional-structural model for adults of Pinus tabulaeformis based on GreenLab. Chinese Journal of Plant Ecology, 2011, 35(4): 422-430. DOI: 10.3724/SP.J.1258.2011.00422

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.plant-ecology.com/CN/10.3724/SP.J.1258.2011.00422

https://www.plant-ecology.com/CN/Y2011/V35/I4/422

图/表 10

图1 基于测量数据的子结构构建示意图。St(p), 生理年龄为p、实际年龄为t的子结构(p = 1, 2, 3, 4; t = 1, 2, 3, 4)。

Fig. 1 Construction of substructure based on measurement data. St(p) is the substructure whose physiological age is p and chorological age is t (p = 1, 2, 3, 4; t = 1, 2, 3, 4).

图2 节间生物量和针叶生物量的比例关系图。A, 18年生。B, 41年生。PAi, 第i个生理年龄(i = 1, 2, 3, 4)。

Fig. 2 Biomass ratio between internodes and needle. A, 18-year-old. B, 41-year-old. PAi, physiological age i (i = 1, 2, 3, 4).

表1 油松成年树的直接参数

Table 1 Directly measured parameters for adults of Pinus tabulaeformis

参数 Parameter	含义 Meaning	属性 Trait
		18年生 18-year-old				41年生 41-year-old
		PA₁	PA₂	PA₃	PA₄	PA₁	PA₂	PA₃	PA₄
P_e	节间汇强 Internode sink	0.10	0.11	0.03	0.01	0.10	0.05	0.02	0.003
P_a	针叶汇强 Needle sink	1.00	0.37	0.16	0.23	1.00	0.44	0.35	0.01
b_e	节间的比例系数 Scale coefficient of internodes		26.51	29.19	33.99		26.30	33.33	32.81
β	节间的形状系数 Form coefficient of internodes		0.04	-0.20	-0.36		-0.02	0.20	0.36
SLW	比叶重 Specific leaf weight	0.08 g·cm^-2

图3 油松成年树节间异速生长模型。A, 18年生。B, 41年生。PAi, 第i个生理年龄(i = 1, 2, 3, 4)。

Fig. 3 Internode allometric relationship of adults of Pinus tabulaeformis. A, 18-year-old. B, 41-year-old. PAi, physiological age i (i = 1, 2, 3, 4).

表2 油松成年树的隐含参数

Table 2 Hidden parameters of adults of Pinus tabulaeformis

参数 Parameter	含义 Meaning	18年生 18-year-old		41年生 41-year-old
参数 Parameter	含义 Meaning	参数值 Value	变异系数 CV (%)	参数值 Value	变异系数 CV (%)
r	水力阻抗 Water resistance	2.97	0.46	3.40	2.07
P₁	年轮分配斜率 Slope for ring compartment	2.60	2.60	5.40	0.51
λ	年轮生物量分配参数 Ring biomass allocation parameter	0.73	0.20	0.40	0.35
S_p	植株投影面积 Plant projection area	2.85 m²	0.49	78.00 m²	1.00

图4 油松节间总生物量和针叶总生物量拟合值和实际值的对比。

Fig. 4 Comparison of simulation and observed data for total internode biomass and total needle biomass of Pinus tabulae- formis.

图5 油松树干形态与生物量模拟数据与实际数据的对比。

Fig. 5 Comparison of simulation and observed data for stem structure and stem biomass of Pinus tabulaeformis.

表3 油松成年树模型误差校正参数值

Table 3 Parameters of model calibration for adults of Pinus tabulaeformis

年龄 Age		均方根误差 Root mean square error	平均相对误差绝对值 Average absolute relative error	r
18年生 18-year-old	树干节间生物量 Stem internode biomass	28.90	0.44	0.90
	树高 Tree height	16.70	0.28	0.96
	树干节间直径 Stem internode diameter	0.89	0.24	0.95
	一级枝节间生物量 Internode biomass of 1st level branch	1.20	0.68	0.70
	二级枝节间生物量 Internode biomass of 2nd level branch	2.00	0.80	0.75
	三级枝节间生物量 Internode biomass of 3rd level branch	1.30	1.10	0.56
41年生 41-year-old	树干节间生物量 Stem internode biomass	50.50	0.45	0.84
	树高 Tree height	28.21	0.22	0.99
	树干节间直径 Stem internode diameter	1.35	0.16	0.98
	一级枝节间生物量 Internode biomass of 1st level branch	54.41	0.57	0.68
	二级枝节间生物量 Internode biomass of 2nd level branch	1.52	0.76	0.79
	三级枝节间生物量 Internode biomass of 3rd level branch	1.10	2.02	0.50

图6 经验模型与GreenLab拟合总生物量的对比。

Fig. 6 Comparison between empirical model and GreenLab model for total biomass fitting.

图7 18年生(左)和41年生(右)油松的三维可视化模拟。

Fig. 7 3D simulation for 18-year-old (left) and 41-year-old (right) Pinus tabulaeformis.

参考文献 16

[1]	Cournède PH, Kang MZ, Rostand-Mathieu A, Yan HP, Hu BG, de Reffye Ph (2006). Structural factorization of plants to compute their functional and architectural growth. Simulation, 82, 427-438.
[2]	de Reffye Ph, Blaise F, Chemouny S, Jaffuel S, Fourcaud T, Houllier F (1999). Calibration of a hydraulic architecture-based growth model of cotton plants. Agronomie, 19, 265-280.
[3]	Deleuze C, Houllier F (1997). A transport model for tree ring width. Silva Fennica, 31, 239-250.
[4]	Deleuze C, Houllier F (2002). A flexible radial increment taper equation derived from a process-based carbon partitioning model. Annals of Forest Science, 59, 141-154. DOI URL
[5]	Gao HZ (高红真), You LQ (尤立权), Wang C (王超) (2009). Study on individual biomass and productivity of Pinus tabulaeformis plantation in Yanshan mountain area. The Journal of Hebei Forestry Science and Technology (河北林业科技), (4), 7-9. (in Chinese with English abstract)
[6]	Guo H (国红), Lei XD (雷相东), Letort V, Lu YC (陆元昌), de Reffye Ph (2009). A functional-structural model GreenLab for Pinus tabulaeformis. Chinese Journal of Plant Ecology (植物生态学报), 33, 950-957. (in Chinese with English abstract)
[7]	Guo H, Letort V, Hong LX, Fourcaud T, Cournède PH, Lu YC, de Reffye Ph (2007). Adaptation of the Greenlab model for analyzing sink-source relationships in Chinese pine daplings. In: Fourcaud T, Zhang XP eds. Plant Growth Modeling and Applications PMA06. IEEE Computer Society, Los Alamitos, USA. 236-243.
[8]	Guo Y, Ma YT, Zhan ZG, Li BG, Dingkuhn M, Luquet D, de Reffye Ph (2006). Parameters optimization and field validation of the functional-structural model GreenLab for maize. Annals of Botany, 97, 217-230. DOI URL PMID
[9]	Houllier F, Leban JM, Colin F (1995). Linking growth modelling to timber quality assessment for Norway spruce. Forest Ecology and Management, 74, 91-102.
[10]	Hu BG, de Reffye Ph, Zhao X, Yan HP, Kang MZ (2003). GreenLab: a new methodology towards plant functional- structure model-structural. In: Hu BG, Jaeger M eds. Plant Growth Modeling and Applications PMA03. Tsinghua University-Springer Press, Beijing. 21-35.
[11]	Mitchell KJ (1975). Dynamics and simulated yield of Douglas-fir. Forest Science Monograph, 17, 39p.
[12]	Perttunen J, Nikinmaa E, Lechowicz MJ, Sievänen R, Messierk C (2001). Application of the functional-structural tree model LIGNUM to sugar maple saplings (Acer saccharum Marsh) growing in forest gaps. Annals of Botany, 88, 471-481.
[13]	Sievänen R, Nikinmaa E, Nygren P, Ozier-Lafontaine H, Perttunen J, Hakula H (2000). Components of functional- structural tree models. Annals of Forest Science, 57, 399-412.
[14]	Sun SX (孙时轩) (1992). Silviculture (造林学). China Forestry Publishing House, Beijing. (in Chinese)
[15]	Wang F (王峰) (2009). Modelling Functional-Structural Growth for Mongolian Scots Pine Trees (Pinus sylvestris var. mongolica) Using GreenLab Principle and Its Application (基于GreenLab原理的樟子松生长的功能-结构建模与应用). PhD dissertation, China Agriculture University, Beijing, 45-48. (in Chinese with English abstract)
[16]	Yan HP, Kang MZ, de Reffye Ph, Dingkuhn M (2004). A dynamic, architectural plant model simulating resource- dependent growth. Annals of Botany, 93, 591-602. DOI URL PMID