Study on Growth Model of DBH and Height Based on Dummy Variable for Natural oak Forest in Qinba Mountain Area

doi:10.13466/j.cnki.lyzygl.2020.05.014

Abstract

Abstract:

Based on the national forest resources inventory data,this study takes the natural oak forest in Qinba mountain area as the research object.The dominant trees and their competitive grades were determined based on the competition index and the site quality grade was determined according to the dominant trees and site dominant factors.The competition grade and site quality grade were used as dummy variables in the fitting of the growth process of the DBH and tree height to obtain the optimal growth model.The results showed that the dominant site factors of oak natural forest were altitude,aspect and soil thickness;Gompertz model was the optimal basic model for the DBH and tree height growth model;the best fitting results were obtained when the dummy variable of competition grade was in parameters a and c,in which R ² value and P_a value were 0.834 and 98.17,respectively,13.16% and 0.59% higher than those of the basic model. The study found that the height growth model used Gompertz model when the dummy variables of site quality grade were in parameters a and b,the fitting results were the best.R ² value and P_a value were 0.717 and 98.26 respectively,which were 16.59% and 0.65% higher than those of the basic model.When the second kind of dummy variable is introduced into the DBH and tree height model,the accuracy of the model is improved,but the effect is not obvious.Based on the analysis of the DBH and tree height growth rules of natural oak forest under different growth conditions in Qinba mountain area,the stand growth model was established,which can provide important reference for the restoration of natural oak secondary forest and the improvement of stand quality.

Key words: natural oak, dummy variable, site quality, competitive index, growth model

CLC Number:

S792.18
S758

MIN Zhiqiang, HU Yunyun, WANG Dejun, SUN Jingmei, LI Hongtao, LI Weizhong. Study on Growth Model of DBH and Height Based on Dummy Variable for Natural oak Forest in Qinba Mountain Area[J]. FOREST RESOURCES WANAGEMENT, 2020, 0(5): 89-99.

Figures/Tables 13

Tab.1

Tab.2

Tab.3

Tab.4

Growth model of Height and DBH

模型	表达式
Richards	y=a× $(1 - e - c × A) b$
Gompertz	y=a× $e - b × e - c × A$
Logistic	y=a/(1+b×e^-^c^×^A)
Schumacher	$e - b × e - c × A$

Tab.4

Fig.1

Tab.5

Tab.6

Tab.7

Tab.8

Tab.9

Tab.10

Fig.2

Fig.3

References 29

[1]	孟宪宇. 测树学[M].3版. 北京: 中国林业出版社, 2006.
[2]	杨文姬, 王秀茹. 国内立地质量评价研究浅析[J]. 水土保持研究, 2004(3):289-292.
[3]	惠淑荣, 李丽锋, 刘强. 辽东地区日本落叶松立地分类和立地质量研究[J]. 西北林学院学报, 2011,26(3):139-142.
[4]	郭艳荣, 刘洋, 吴保国. 福建省宜林地立地质量的分级与数量化评价[J]. 东北林业大学学报, 2014,42(10):54-59.
[5]	马增旺, 毕君, 刘德章. 太行山栎类天然次生林立地类型划分[J]. 河北林业科技, 1996(4):20-23.
[6]	欧阳君祥, 曾思齐. 长江中上游低质低效次生栎林的分类与评价[J]. 林业资源管理, 2002(3):69-74.
[7]	高文韬, 丁伟, 李胜, 等. 长白山林区天然过伐林中蒙古栎适生立地研究[J]. 北华大学学报:自然科学版, 2000(1):77-81.
[8]	黄国胜, 马炜, 王雪军, 等. 基于一类清查数据的福建省立地质量评价技术[J]. 北京林业大学学报, 2014,36(3):1-8.
[9]	张思玉, 郑世群. 笔架山常绿阔叶林优势种群种内种间竞争的数量研究[J]. 林业科学, 2001,37(S1); 185-188.
[10]	Staebler G R. Growth and Spacing in An Even-Aged Stand of Douglas fir[M]. Michigan:University of Michigan, 1951.
[11]	李际平, 房晓娜, 封尧, 等. 基于加权Voronoi图的林木竞争指数[J]. 北京林业大学学报, 2015,37(3):61-68.
[12]	褚欣, 潘萍, 欧阳勋志, 等. 闽楠天然次生林林木综合竞争指数研究[J]. 西北林学院学报, 2019,34(4):199-205.
[13]	石振威, 曾思齐, 刘发林, 等. 基于地形与竞争因子的青冈栎次生林树高哑变量模型研究[J]. 西北林学院学报, 2020,35(1):196-202.
[14]	Hegyi F. A simulation model for managing jack-pine stands[M]//Growth models for tree and stand simulation. Stockholm.Sweden:Royal College of Forestry, 1974: 74-90.
[15]	覃阳平, 张怀清, 陈永富, 等. 改进的简单竞争指标在单木生长模型中的应用[J]. 东北林业大学学报, 2014,42(12):130-133.
[16]	李际平, 房晓娜, 封尧, 等. 基于加权Voronoi图的林木竞争指数[J]. 北京林业大学学报, 2015,37(3):61-68.
[17]	房晓娜, 李际平, 孙华, 等. 基于W_V_Hegyi竞争指数的杉木竞争生长模型研究——以湖南省福寿国有林场杉木生态公益林为例[J]. 林业资源管理, 2015(2):59-64.
[18]	颜伟, 段光爽, 王一涵, 等. 河南省栎类和杨树林分断面积和蓄积生长模型构建[J]. 北京林业大学学报, 2019,41(6):55-61.
[19]	朱光玉, 胡松, 符利勇. 基于哑变量的湖南栎类天然林林分断面积生长模型[J]. 南京林业大学学报:自然科学版, 2018,42(2):155-162.
[20]	曹梦, 潘萍, 欧阳勋志, 等. 基于哑变量的闽楠天然次生林单木胸径和树高生长模型研究[J]. 北京林业大学学报, 2019,41(5):88-96.
[21]	DAVID A, ROBERT B. Effects of size,competition and altitude on tree growth[J]. Journal of Ecology, 2007,95(5):1084-1097. doi: 10.1111/jec.2007.95.issue-5
[22]	国家林业和草原局. 中国森林资源报告(2014—2018)[M]. 北京: 中国林业出版社, 2019.
[23]	张文辉, 卢志军, 李景侠, 等. 秦岭北坡栓皮栎种群动态的研究[J]. 应用生态学报, 2003(9):1427-1432.
[24]	甄学渊, 郭敏, 胡晓静, 等. 秦巴山区陕南栎类生长特点及资源现状[J]. 西北植物学报, 2014,34(10):2101-2108.
[25]	黄秉维, 郑度, 赵名茶. 现代自然地理[M]. 北京: 科学出版社, 1999.
[26]	惠刚盈, 李丽, 赵中华, 等. 林木空间分布格局分析方法[J]. 生态学报, 2007(11):4717-4728.
[27]	周红敏, 惠刚盈. 林分空间结构分析中样地边界木的处理方法[J]. 林业科学, 2009,45(2):1-5. doi: 10.11707/j.1001-7488.200900201
[28]	唐守正, 郎奎建, 李海奎. 统计和生物数学模型计算:ForStat教程[M]. 北京: 科学出版社, 2009.
[29]	李丽霞, 郜艳晖, 张瑛. 哑变量在统计分析中的应用[J]. 数理医药学杂志, 2006(1):51-53.

林分因子	最大值	最小值	平均值	标准差
年龄/a	95	6	33	19.0
胸径/cm	38.5	6	15.3	6.9
树高/m	24.2	4.2	11.0	3.6
蓄积量/(m³/hm²)	490.9	2.25	114.15	87.6
优势木生长量/(m³/hm²)	4.90	0.01	1.48	0.87

立地因子	编号	取值范围	优势木生长量/ (m³/hm²)	得分值
海拔	1	<500	0.037	1
	2	500~1000	0.0438	2
	3	1000~1500	0.0552	4
	4	1500~2000	0.059	5
	5	≥2000	0.0509	3
坡向	1	北	0.0408	1
	2	东北	0.0381	1
	3	东	0.0552	4
	4	东南	0.0626	5
	5	南	0.0554	4
	6	西南	0.0532	3
	7	西	0.0521	3
	8	西北	0.0497	2
	9	无坡向	0.0487	2
土壤厚度	1	厚	0.0606	5
	2	中	0.0517	3
	3	薄	0.0481	1

等级	Ⅰ级	Ⅱ级	Ⅲ级
分值	11~15	7~10	3~6
样地数/块	146	124	99

立地因子	主要成份
立地因子	1	2	3
地貌(LF)	0.777	0.544	0.098
海拔(ELE)	0.823	0.467	0.069
坡向(ASP)	0.089	0.246	-0.558
坡位(SLPP)	0.206	0.032	0.618
坡度(SLP)	-0.137	0.024	0.542
土壤类型(ST)	-0.592	0.642	-0.073
土壤质地(SQ)	-0.386	0.107	0.391
土壤厚度(SD)	0.686	-0.56	-0.048
腐殖质厚度(BUFF)	0.241	-0.114	0.021

因变量类别	模型	参数值						拟合指标				评价指标
因变量类别	模型	a		b		c		RMSE		R²		TRE		P_a
树高(H)	Richards		46.44		0.41		0.00		2.26		0.61		2.26		97.84
	Gompertz		21.23		1.37		0.02		2.23		0.62		2.08		97.63
	Logistic		13.23		1.81		0.08		2.51		0.51		0.98		97.63
	Schumacher		14.49		7.42				2.59		0.48		3.13		97.51
	Richards		25.66		0.03		0.82		3.98		0.66		3.36		97.24
胸径(DBH)	Richards		25.66		0.03		0.82		3.98		0.66		3.36		97.24
	Gompertz		49.67		2.15		0.02		3.52		0.74		2.20		97.59
	Logistic		21.14		3.53		0.08		4.19		0.63		1.58		97.15
	Schumacher		30.29		18.44				4.16		0.63		1.72		97.24