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c 2009 Institute for Scientific ° Computing and Information INTERNATIONAL JOURNAL OF INFORMATION AND SYSTEMS SCIENCES Volume 5, Number 3-4, Pages 528–531 THE APPLICATION OF QUANTIFICATION THEORY I IN SITE QUALITY EVALUATION OF JAPANESE LARCH-TREE (LARIX KAEMFERI) SHURONG HUI, ZHENZHEN LI, FANG YANG, QIANG LIU, AND LIFENG LI Abstract. We chose 6 vertical factors and utilized the method of quantification theory I in the comprehensive analysis of the influence of Larch-tree(Larix kaempferi) growth environment factors. This paper constructed the model of eastern part of Liaoning Province , and the result of examination indicated that the model met the precision requirements. Using this model to appraise the eastern part of Liaoning Province area Japanese Larch-tree(Larix kaempferi) vertical quality , it provided the theory basis for eastern part of Liaoning province Japanese Larch-tree(Larix kaempferi)management of cultivation production. Key Words. Japanese larch-tree(larix kaempferi), Quantification theory I, Site quality evaluation. 1. Introduction Forest site is a collectivity of environments that have signality for forest in some space, including physiognomy, climate, soil, ect. Site quality evaluation is a basic work in foresty industry[1]. The effect of forest management depends upon the quality of woodland and reasonable using and exploiting directly[2]. Site quality evaluation evaluates suitability and competitive strength on some specific sit plot for choosing proper tree species, taking reasonable management measure, and bringing into play the industry potential of site[3][5]. This research investigated and analysed 168 sampled stands in the east part of Liaoning province, and evaluated site quality of Japanese Larch-tree in the eastern part of Liaoning province scientific. The paper got a method of site quality evaluation for Japanese Larch-tree in the east part of Liaoning province. That provided a scientific and dependable theory for practice[4]. 2. Site quality evaluation 2.1. Choose sampled stands and factor of environment. All sampled stands were growning normally pure Japanese Larch-tree. We chose 168 Japanese Larchtree sampled stands that has canopy density above 0.2, area 0.60-1.00ha, and more than 100 trees in each sampled stands. Some environment factors should be measured: aspect, slope position, soil type, slope degree, altitude, soil depth. Then each site factor is standarded. There are 19 categories in total(table 1). Received by the editors May 14, 2008 and, in revised form, October 1, 2008. 2000 Mathematics Subject Classification. 35R35, 49J40, 60G40. This research was supported by liaoning university scientific research plan projects(2008626). 528 THE APPLICATION OF QUANTIFICATION 529 Table 1. Standard division of item and category for each site factor Item Variable Category 1 Aspect x1 Adret Slope Position x2 Ridgetop Soil Type x3 Sandy Loam Slope Degree x4 > 25◦ Altitude x5 500m Soil Depth x6 > 60cm Category 2 Category 3 Category 4 Ubac Middle Bottom Light Loam Medium Loam Weight Loam 5◦ 25◦ < 5◦ 200m-500m < 200m 30cm-60cm < 30cm 2.2. Quantification theory I approach. Every site factors are items, and each levels are actegories. We sign different variable according to principle of Quantification theory I. δ(j,k) = { 1 j th item is chosed 1 not The mean dominant height of sample plot is dependent variable, and environment factors and age are independent variable. We can get the model of Quantification theory I. (1) yi = ri m X X bj,k δ(j,k) + blgA + εi j=1 k=1 with: yi is independent variable, δj,k is the mean dominant height of i th sample plot. bik is the score of j th item and k th category. b is the score of the age of stand. A is the age of stand.εi is random error. i =1,2,. . . ,n is the numbers of sample plot;j =1,2,. . . ,m is the number of item.i =1,2,. . . ,ri is the number of category. (Table 2) Undetermined coefficient can get from the method above. The standard age is 20 years. We can get the regression equation. y = −0.89867δ(1,1) + 0.13501δ(2,1) + 0.70058δ(2,2) + 0.26208δ(3,1,) + 1.13315δ(3,2) (2) +0.90594δ(3,3) + 2.66827δ(4,1) + 2.01263δ(4,2) + 3.72503δ(5,1) + 4.84854δ(5,2) +0.64677δ(6,1) − 0.53705δ(6,2) + 10.379641 2.3. Model Validation. The model was verified the reliability with t test of multiple correlation coefficient and partial correlation coefficient. r (3) t=r n−m−1 , 1 − r2 with: n is the numbers of sample plot;m is the number of item;r is multiple(partial) correlation coefficient. The result is in table 2. t0 = 32.62618 > t0.05 = 1.64485That mean average dominant height have close relation with the six environment factors. 530 S. HUI, Z. LI, F. YANG, Q. LIU, AND L.LI Table 2. Quantified score of each site fator Item Aspect Slioe Position Soil Type Slope Degree Attitude Soil Depth Category Adret Ubac Ridgetop Middle Bottom Sandy Loam Light Loam Medium Loam Weight Loam > 25◦ 5◦ − 25◦ < 5◦ > 500m 200m − 500m < 200m > 60cmm 30cm − 60cm < 30cm Age Score -0.89867 Score range 0.89867 C.P.C. 0. 1997704 t Value 2.578901 0. 13501 0.70058 0 0. 26208 1.13315 0.90594 0 2. 66827 2.01263 0 3. 72503 4. 84854 0 0. 64677 -0.537050 0 23.00977 0. 70058 0. 1510598 1.932953 1. 13315 0. 1421746 1.816838 2. 66827 0. 1503214 1.923286 4. 84854 0. 5817446 9.046975 1. 18382 0. 2120812 2.745084 0. 8912763 24.86181 The model fit data well, and the result is accurately. It can be used put into practice. 2.4. Site Quality Evaluation. Levels of different site quality evaluation base on score of every sampled stand according to under prerequisites. Results all sampled stands are divided into three categories as good, average and bad. if y ≥ ȳ + ∆s,valuation is good; if ȳ + ∆s > y ≥ ȳ − ∆s,valuation is average; if y < ȳ − ∆s,valuation is bad. with: y is the score of sampled stand; ȳ is average value of all samplde stands;∆ s is standard deviation.The result is in table 3. Table 3. Levels of different site quality evaluation Level Good ≥ 18.4907 Average(14.2483 − 18.4907) Bad(< 14.2483) Number Of Sampled Stand 5, 58, 73, 74,. . . ,164, 167, 168 3, 4, 6, 7,. . . ,165, 166, 169 2, 9, 23, 100,. . . ,145, 146, 147 Number 26 109 33 3. Results and Discussion The research constructed a method of site quality evaluation for Japanese Larchtree(Larix kaemferi) in eastern part of Liaoning province, basiced on analysing comprehensively the influence of Japanese Larch-tree(Larix kaempferi) growth environment factors, chosed six environment factors such as:aspect, slope position, soil type, slope degree, altitude, soil depth, and used the method of quantification theory I. The Japanese Larch-tree(Larix kaemferi) site evaluation modle fit the original data well. It can be used for scientific management of Lach-tree(Larix kaemferi) in eastern part of Liaoning province. That can help to improve the production THE APPLICATION OF QUANTIFICATION 531 potential of forest land, and enhance the ability of forestation and management. According to the result of the model, every factor has some influence for Japanese Larch-tree(Larix kaemferi). The order is altitude, soil depth, aspect, slope position, slope degree, There are 26 score of plots is above 18.4907, 109 score of plots are above14.2483 and under 18.4907. They are comfortable for Japanese Larch-tree(Larix kaemferi). There are 33 score of plots are under 14.2483. They are not comfortable for Japanese Larch-tree(Larix kaemferi). Other tree species should be consider for better effect of management. References [1] You Yin,Meng Wang, Research on Forest Site Classification and Evaluation , Journal of Anhui Agri.Sci., china, 2007. [2] Weiji Yang,Xiuru Wang, Analysis on the Study of Site Quality Evaluation in China, Research of Soil and Water Conservation, 2004. [3] Xiaohong Fan,Dong Xu, Forest Site Classification and Evaluation,Journal of Sichuan Forestry Science and Technology,1995. [4] Zhiyuan Ni,Guiqiao Lu,S.C. Zhang,X.Li, Study on Site Quality Evaluation of Walnut in the Mountainous Area of Hebei Province, Journal of Forestry and Orchard Research,2006. [5] Harrington, Constance A. , A Method of Site Quality Evaluation for Red Alder, U.S. Department of Agrculture, 1986. college of science, shenyang agricultural university, liaoning, 100161, china E-mail: [email protected] No. 77, Shenyang Agriculture University, Shenyang, Liaoning, China E-mail: [email protected]. No. 77, Shenyang Agriculture University, Shenyang, Liaoning, China E-mail: [email protected] College of Information and Electrical Engineering, Shenyang Agriculture University, Shenyang, Liaoning, China E-mail: [email protected] College of Science, Shenyang Agricultural University, Liaoning, 100161, China