A comprehensive evaluation of forest land quality using multi tree site form index

doi:10.12302/j.issn.1000-2006.202103007

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2021, Vol. 45 ›› Issue (6): 81-89.doi: 10.12302/j.issn.1000-2006.202103007

Previous Articles Next Articles

A comprehensive evaluation of forest land quality using multi tree site form index

LI Qingshun¹^,²(), JIN Wanzhou¹, WANG Dejun¹^,², SUN Jingmei¹^,², LI Hongtao¹^,²

1. Northwest Surveying,Planning and Designing Institute of National Forestry and Grassland Administration,Xi’an 710048, China
2. Key Laboratory of National Forestry and Grassland Administration on Ecological Hydrology and Disaster Prevention in Arid Regions,Xi’an 710048, China

Received:2021-03-03 Accepted:2021-05-31 Online:2021-11-30 Published:2021-12-02

Abstract

Abstract:

【Objective】 The site form index of three common tree species birch, poplar and Picea crassifolia in the Huangshui Large-scale Forest Farm in Qinghai Province was used to analyze the landform, aspect, slope, soil type, soil thickness, and annual average temperature, annual rainfall, annual solar radiation, and other factors of the growing area. The site quality evaluation of large-scale forest farms was carried out, and a comprehensive database of forestland quality evaluation was constructed to achieve the goal of guiding the scientific afforestation and management of forest farms and maximizing the value of forest land productivity and ecological services. 【Method】 First, according to the type of inventory data within the modeling area, the advantage of each plot was obtained, and the site form index of the plot was obtained. Following this, to analyze its relationship with landform, aspect, slope, soil type, soil thickness, annual average temperature, annual rainfall, annual solar radiation, and other factors, the factor analysis was used to select the dominant factors affecting the topographic index, and a regression model was established. According to the calculated average of the site form index of the three common tree species, the cluster analysis was carried out, and the forest land was divided into five grades: Ⅰ, Ⅱ, Ⅲ, Ⅳ and Ⅴ, and the forest land quality distribution map was prepared. Finally, according to the classification, the results were verified, and corresponding management measures were proposed. 【Result】 Grade Ⅰ forest land area was 3 409.37 hm ², accounting for 1.39% of the total forest land area; Grade Ⅱ forest land area was 38 765.07 hm ², accounting for 15.77%; Grade Ⅲ forest land area was 78 989.17 hm ², accounting for 32.14%; Grade Ⅳ forest land area was 77 102.74 hm ², accounting for 31.38%; and Grade Ⅴ forest land area was 47 477.50 hm ², accounting for 19.32%. Based on the overall classification results, the forest land quality grade of large-scale forest farms was low, mainly Ⅲ and Ⅳ forest land. The corrected rate of on-site verification quality grade was 88%, and the corrected rate was high. 【Conclusion】 It is feasible to obtain high advantages through the standard wood, sample wood bank, and sample base bank in the first type of inventory data. Following this, the topographic factors, soil factors, and meteorological factors can be selected as the evaluation factors. The introduction of multiple factors makes the evaluation results more objective and improves the accuracy of the evaluation. Using multi-tree species site form indexes for a comprehensive evaluation, especially the evaluation of site quality of non-forest land is a more effective method.

Key words: multi-tree species, site form index, site quality, management measure, comprehensive evaluation

CLC Number:

S757

LI Qingshun, JIN Wanzhou, WANG Dejun, SUN Jingmei, LI Hongtao. A comprehensive evaluation of forest land quality using multi tree site form index[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2021, 45(6): 81-89.

Figures/Tables 7

Table 1

Table 2

Fig.1

Table 3

Table 4

Fig.2

Table 5

References 21

[1]	BATHO A, GARCI A. De Perthuis and the origins of site index: a historical note[J]. FBMIS, 2006, 1:1-10.
[2]	GREEN R N, MARSHALL P L, KLINKA K. Estimating site index of Douglas-fir (Pseudotsuga menziesii [Mirb.]Franco) from ecological variables in southwestern British Columbia[J]. For Sci, 1989, 35(1):50-63.
[3]	SKOVSGAARD J P, VANCLAY J K. Forest site productivity:a review of the evolution of dendrometric concepts for even-aged stands[J]. Forestry (Lond), 2008, 81(1):13-31.DOI: 10.1093/forestry/cpm041. doi: 10.1093/forestry/cpm041
[4]	郑聪慧, 贾黎明, 段劼, 等. 华北地区栓皮栎天然次生林地位指数表的编制[J]. 林业科学, 2013, 49(2):79-85.
	ZHENG C H, JIA L M, DUAN J, et al. Establishment of site index table for Quercus variabilis natural secondary forest in north China[J]. Sci Silvae Sin, 2013, 49(2):79-85.DOI: 10.11707/j.1001-7488.20130212. doi: 10.11707/j.1001-7488.20130212
[5]	PERIN J, HÉBERT J, BROSTAUX Y, et al. Modelling the top-height growth and site index of Norway spruce in southern Belgium[J]. For Ecol Manag, 2013, 298:62-70.DOI: 10.1016/j.foreco.2013.03.009. doi: 10.1016/j.foreco.2013.03.009
[6]	刘东兰, 周宁, 郑小贤. 杉木人工林地位指数表简捷编制方法研究[J]. 林业资源管理, 2012(1):61-65.
	LIU D L, ZHOU N, ZHENG X X. The research on site index table construction method for Chinese fir plantation[J]. For Resour Manag, 2012(1):61-65.DOI: 10.13466/j.cnki.lyzygl.2012.01.017. doi: 10.13466/j.cnki.lyzygl.2012.01.017
[7]	李斌成, 杜超群, 袁慧, 等. 基于理论模型及其差分方程的湖北省杉木立地指数表研制[J]. 中南林业科技大学学报, 2019, 39(7):56-64.
	LI B C, DU C Q, YUAN H, et al. Development of site index table of Chinese fir in Hubei Province based on theoretical model and difference equation[J]. J Central South Univ For Technol, 2019, 39(7):56-64.DOI: 10.14067/j.cnki.1673-923x.2019.07.008. doi: 10.14067/j.cnki.1673-923x.2019.07.008
[8]	VANCLAY J K, HENRY N B. Assessing site productivity of indigenous cypress pine forest in Southern Queensland[J]. Commonw For Rev, 1988, 67(1):53-64.
[9]	HUANG S, TITUS S J. An index of site productivity for uneven-aged or mixed-species stands[J]. Can J For Res, 1993, 23(3):558-562.DOI: 10.1139/x93-074. doi: 10.1139/x93-074
[10]	FERNÁNDEZ B H, CAMPOS J J, KLEINN C. Site productivity estimation using height-diameter relationships in Costa Rican secondary forests[J]. Invest Agrar: Sist Recur For. 2004, 13(2):295-303.
[11]	陈永富, 杨彦臣, 张怀清, 等. 海南岛热带天然山地雨林立地质量评价研究[J]. 林业科学研究, 2000, 13(2):134-140.
	CHEN Y F, YANG Y C, ZHANG H Q, et al. A study on site quality evaluation of natural tropical mountainous rain forest in Hainan Island[J]. For Res, 2000, 13(2):134-140.DOI: 10.13275/j.cnki.lykxyj.2000.02.005. doi: 10.13275/j.cnki.lykxyj.2000.02.005
[12]	魏志刚, 夏德安, 王瑞琪, 等. 小兴安岭带岭地区不同类型次生林下红松种源试验研究[J]. 森林工程, 2021, 37(3):1-11.
	WEI Z G, XIA D A, WANG R Q, et al. Study on the provenance test of Pinus koraiensis under different natural secondary forests in dailing area of Xiaoxing’an Mountains[J]. Forest Engineering, 2021, 37(3):1-11.
[13]	李任君, 高懋芳, 李强, 等. 基于ANUSPLIN的降水空间插值方法研究[J]. 中国农业信息, 2019, 31(1):48-57.
	LI R J, GAO M F, LI Q, et al. Research on rainfall spatial interpolation method based on ANUSPLIN[J]. China Agric Inform, 2019, 31(1):48-57.
[14]	刘志红, MCVICAR T R, LI L T, 等. 基于ANUSPLIN的时间序列气象要素空间插值[J]. 西北农林科技大学学报(自然科学版), 2008, 36(10):227-234.
	LIU Z H, MCVICAR T R, LI L T, et al. Interpolation for time series of meteorological variables using ANUSPLIN[J]. J Northwest A & F Univ (Nat Sci Ed), 2008, 36(10):227-234.
[15]	钱永兰, 吕厚荃, 张艳红. 基于ANUSPLIN软件的逐日气象要素插值方法应用与评估[J]. 气象与环境学报, 2010, 26(2):7-15.
	QIAN Y L, LYU H Q, ZHANG Y H. Application and assessment of spatial interpolation method on daily meteorological elements based on ANUSPLIN software[J]. J Meteorol Environ, 2010, 26(2):7-15.DOI: 10.3969/j.issn.1673-503X.2010.02.002. doi: 10.3969/j.issn.1673-503X.2010.02.002
[16]	王洪波. 中国林地现代管理模式关键问题研究与实践探索[D]. 北京:北京林业大学, 2012.
	WANG H B. The study and practice of forestland modern management mode and the key issues in China[D]. Beijing:Beijing Forestry University, 2012.
[17]	卢志伟, 李清顺. 用林分生长模型更新松树小班平均胸径和树高因子研究[J]. 西南林学院学报, 2010, 30(4):6-10.
	LU Z W, LI Q S. Study on updating the average DBH and height indices of pine tree stands with stand growth model[J]. J Southwest For Univ, 2010, 30(4):6-10.
[18]	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.
	HUANG G S, MA W, WANG X J, et al. Forestland site quality evaluation of Fujian Province based on continuous forest inventory data[J]. J Beijing For Univ, 2014, 36(3):1-8.DOI: 10.13332/j.cnki.jbfu.2014.03.001. doi: 10.13332/j.cnki.jbfu.2014.03.001
[19]	RICHARD A, JOHNSON , DEAN W. Applied multivariate statical analysis[M]. Beijing: Pearson Education Asia LTD and Tsinghua University Press, 2007.
[20]	唐守正. 利用对偶回归和结构关系建立林分优势高和平均高模型[J]. 林业科学研究, 1991, 9(4):57-62.
	TANG S Z. Using dual regression and structural relationship to establish a model of stand dominance and average height[J]. For Res, 1991, 9(4):57-62.
[21]	王高峰. 森林立地分类研究评价[J]. 南京林业大学学报, 1986, 29(3):108-124.
	WANG G F. A review of the study of forest site classification[J]. J Nanjing For Univ, 1986, 29(3):108-124. DOI: 10.3969/j.issn,1000-2006.1986.030013. doi: 10.3969/j.issn

Related Articles 15

[1]	LI Bingjun, LIU Pin, HAN Yongzhen, RONG Jundong, CHEN Liguang, ZHENG Yushan. Evaluation of site quality of Fokienia hodginsii plantation based on site index method [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2024, 48(2): 191-198.
[2]	FAN Xiaoyun, GUO Sujuan, LI Yanhua, JIANG Xibing. Study on correlation between browning degree of chestnut fruit and total phenols and flavonoids [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2023, 47(6): 159-166.
[3]	ZHANG Yunqi, DONG Ningguang, HAO Yanbin, CHEN Yonghao, ZHANG Junpei, HOU Zhixia, SU Shuchai, WU Jiaqing, QI Jianxun. Nuts’ phenotypic diversity analysis and character evaluation of 109 high-yield walnut individual trees [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2023, 47(3): 87-96.
[4]	LIANG Wenchao, BU Xing, LUO Siqian, XIE Yinfeng, ZHANG Wangxiang, HU Jialin. Effects of nitrogen, phosphorus and potassium compound fertilization on the physiological characteristics of Chaenomeles speciosa ‘Changshouguan’ after processing of warming in the post floral stage [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2022, 46(5): 81-88.
[5]	ZHAO Xiaojun, CHENG Fang, ZHANG Kang, HUANG Kaidong, NI Yun, MENG Xiao, TANG Luozhong. Root morphology of different poplar clone stecklings under waterlogging and flooding treatment [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(5): 1-8.
[6]	ZHAI Dacai, FANG Zhen, WU Jinfei, YAO Qi, BAI Xiaohui, YANG Lichun, HAO Qingqing, ZHANG Yan. Analysis on the character diversity of Ormosia hosiei seeds from different producing regions [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(04): 63-69.
[7]	YANG Yifan, ZHOU Ting, FAN Junjun, MU Qian, ZHANG Jing, ZHANG Wangxiang, YU Zhongming. Cultivar evaluation and selection in ornamental crabapple for cut flower application [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(04): 70-76.
[8]	HUANG Zhengjin, WEI Yunli, ZHANG Chunhong, LYU Lianfei, LI Weilin, WU Wenlong. Comprehensive evaluation of five blackberry hybrid strains by analytic hierarchy process(AHP) [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(01): 135-140.
[9]	PU Jing,ZHANG Jing, ZHAO Cong, FAN Junjun, JIANG Wenlong, ZHANG Wangxiang,WANG Gaiping. Analysis and evaluation on flower color characteristics of the Malus ‘Purple Prince' half-sib progenies [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(01): 18-24.
[10]	WANG Jin, NIE Ying. A comprehensive evaluation method of Chinese rosin trade risk [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2018, 42(02): 207-212.
[11]	ZHANG Wangxiang, FAN Junjun, YANG Ping, ZHOU Ting,PU Jing, CAO Fuliang. Analysis of phenotypic characteristics of the Malus ‘Purple Prince’ half-sib progenies at the seedling stage [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2017, 41(06): 33-40.
[12]	CAO Yuanshuai, SUN Yujun. Generalized algebraic difference site index model for Chinese fir plantation [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2017, 41(05): 79-84.
[13]	WU Zhen, WANG Wei, WANG Hao. Comprehensive evaluation of landscape resources in hydrographic net region of southern Jiangsu Province based on GIS [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2017, 41(04): 202-208.
[14]	ZHU Ling, ZHOU Yuxin, TANG Luozhong, TONG Tingting. A review on the management models and comprehensive evaluation methods for agroforestry in China [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2015, 39(04): 149-156.
[15]	HAN Yangyang, WANG Yan, YE Jianren, LI Yuxiou, LIN Sixi. Invasion risk analysis of Pierces’ disease of grapevine to Shanghai [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2015, 39(03): 172-178.

Metrics

Comments

www.nldxb.njfu.edu.cn

Edited ＆ Published by Editorial Department of Nanjing Forestry University(Natural Sciences Edition)
Address： No.159 Longpan Road,Nanjing 210037 Jiangsu,P.R.China
E-mail ：xuebao@njfu.edu.cn , xuebao@njfu.com.cn
Telephone +86-25-85428247,85427076
Distributed by China International Book Trading Corporation P.O. Box 399, Beijing ,P.R. China

统计量 statistic	桦木 birch					杨树 poplar					青海云杉 Picea crassifolia
统计量 statistic	D_a/cm	H_a/m	D_w/cm	D_p/cm	H_p/m	D_a/cm	H_a/m	D_w/cm	D_p/cm	H_p/m	D_a/cm	H_a/m	D_w/cm	D_p/cm	H_p/m
最小值 min.	5.5	3.0	5.0	5.3	4.3	5.2	4.0	5.0	5.7	4.6	5.8	3.7	5.0	2.5	1.5
最大值 max.	37.2	23.0	59.2	37.1	28.5	51.0	21.7	59.2	36.9	18.6	42.5	94.0	76.6	37.1	28.5
平均值 average	15.0	10.4	11.6	16.1	11.3	16.6	11.1	11.6	16.9	11.2	19.5	13.8	17.9	17.3	11.8
标准差 SD	5.8	3.3	5.7	6.3	4.3	6.8	3.9	5.7	6.0	3.8	8.8	8.3	10.2	7.3	5.2
变动系数/% CV	38.8	31.7	48.9	39.4	37.6	40.8	35.1	48.9	35.8	33.7	45.0	60.0	57.0	42.1	44.1

方程 equation	a	b	c	a%	b%	c%	决定系数 R²	均方根误差 RMES	赤池信息准则 AIC
Logistic	15.952	4.703	0.121	9.006	11.646	15.574	0.553	2.08	406.48
Mitscherlich	20.400		0.040	11.240		15.930	0.547	2.09	407.87
Gompertz	17.969	2.063	0.074	14.095	6.951	23.240	0.551	2.08	407.56
Korf	2 108.349	7.744	0.130	977.283	118.606	184.773	0.548	2.09	409.87
Richard	28.851	0.019	0.826	80.981	154.600	25.409	0.548	2.09	409.20

变量 variable	因子载荷 factor load		因子得分 factor score
变量 variable	F₁	F₂	F₁	F₂
土壤类型 soil type	-0.07	0.87^*	0.04	0.28
土壤厚度 soil thickness	-0.18	0.89^*	0.01	0.28
坡向 aspect	-0.13	0.93^*	0.03	0.29
坡度 slope	-0.08	0.88^*	0.04	0.28
年平均气温 annual average air temperature	0.97^*	-0.05	0.27	0.05
年最高气温 annual maximum air temperature	0.97^*	-0.05	0.27	0.05
年最低气温 annual minimum air temperature	0.99^*	-0.06	0.27	0.05
年降雨量 annual rainfall	-0.77^*	0.27	-0.19	0.03
年日照时数 annual sunshine hours	0.54	-0.11	0.14	0
特征值 eigenvalue	3.79	3.26
方差贡献率/% variance contribution rate	42.16	36.18
累积贡献率/% cumulative contribution rate	42.16	78.34

计算过程 calculation process	杨树 poplar		青海云杉 Picea crassifolia
树高-胸径回归模型 tree height and DBH regression model	Logistic H=1.3+15.6/[1+7.101exp(-0.165 D)]		Logistic H=1.3+19.619/[1+17.228 1exp(-0.184D)]
树高-胸径回归模型 tree height and DBH regression model	95%显著水平下的t值为1.216,平均总相对误差-2.22%,相对总误差0.01%,预估精度98.56%		95%显著水平下的t值为1.518,平均总相对误差-0.79%, 相对总误差0.09%,预估精度98.56%
导向曲线 guide curve	Logistic H=1.3+15.221/[1+6.707exp(-0.251D)]		Logistic H=1.3+19.550/[1+22.273exp(-0.319D)]
生长量方程 growth equation	连年生长量	Z(D)=25.64exp[(-0.251D)]/ [1+6.707exp(-0.251D)]²	连年生长量	Z(D)=138.84exp[(-0.319D)]/ [1+22.273exp(-0.319D)]²
生长量方程 growth equation	平均生长量	θ(D)=15.221[1/[1+6.707× exp(-0.251D)]-0.130]/D	平均生长量	θ(D)=19.55[1/[1+22.273exp(-0.319D)]- 0.043]/D
立地形方程 site form equation	基准胸径 12 cm	S_I=(H-1.3)[1+6.707 exp(-0.251D₀)]/[1+6.707exp(-0.251D)]+1.3	基准胸径 16 cm	S_I=(H-1.3)[1+19.55exp(-0.319D₀)]/ [1+19.55exp(-0.319D)]+1.3
主导因子的选择 selection of dominant factors	年最低气温(T_zdw)、年降雨量(L_nj)、地貌(D_m)、土壤类型(X_tr)、土壤厚度(h_tr)、坡向(P_x)和坡度(P_d)		年最高气温(T_zgw)、年降雨量(L_nj)、海拔(H_b)、土壤类型(X_tr)、土壤厚度(h_tr)、坡向(P_x)和坡度(P_d)
立地形回归方程 regression equation of site form	S_杨=-0.393T_zdw-0.032L_nj+0.537D_m-2.659X_tr- 1.21h_tr-2.874P_x-0.296P_d+45.532		S_云=-0.373T_zgw+0.004L_nj-0.636H_b-3.363X_tr-1.092h_tr- 2.682P_x-1.312P_d+34.462

A comprehensive evaluation of forest land quality using multi tree site form index

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 21

Related Articles 15

Recommended Articles

Metrics

Comments

Author

Reader

Reviewer

小班编号 sub class No.	立地形指数 SF index	级别 level	验证立地形指数 verification SF	验证级别 verification level	是否跳级 skip grade	立地质量现场评价 site qualityon- side evaluation
1	13.90	Ⅳ	13.90	Ⅳ		差
2	20.21	Ⅰ	21.56	Ⅰ		良
3	12.87	Ⅳ	12.78	Ⅳ		良^*
4	19.07	Ⅱ	20.26	Ⅰ	√	优
5	10.63	Ⅴ	13.01	Ⅳ	√	差
6	10.56	Ⅴ	10.56	Ⅴ		差
7	17.77	Ⅱ	20.16	Ⅰ	√	优
8	18.77	Ⅱ	18.77	Ⅱ		优
9	16.44	Ⅲ	16.44	Ⅲ		中
10	19.02	Ⅱ	21.40	Ⅰ	√	优
11	18.16	Ⅱ	17.88	Ⅱ		良
12	21.23	Ⅰ	20.32	Ⅰ		优
13	18.54	Ⅱ	19.74	Ⅱ		优^*
14	19.74	Ⅱ	19.74	Ⅱ		良
15	18.38	Ⅱ	19.57	Ⅱ		良
16	18.49	Ⅱ	19.68	Ⅱ		良
17	19.72	Ⅱ	20.91	Ⅰ	√	优
18	18.51	Ⅱ	18.51	Ⅱ		良
19	11.18	Ⅴ	12.38	Ⅳ	√	差
20	16.74	Ⅲ	16.74	Ⅲ		良
21	19.79	Ⅱ	19.79	Ⅱ		良
22	13.43	Ⅳ	13.43	Ⅳ		劣^*
23	14.33	Ⅳ	14.33	Ⅳ		差
24	14.34	Ⅳ	14.34	Ⅳ		差
25	14.32	Ⅳ	14.32	Ⅳ		差