Forest Ecosystem Health Assessment on the Basis of Fuzzy Comprehensive Evaluation Model

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1 Agricultural Science Volume, Issue 4 (03), 9-35 ISSN E-ISSN 9-448X Publishe by Science an Eucation Centre of North America Forest Ecosystem Health Assessment on the Basis of Fuzzy Comprehensive Evaluation Moel Jianshe Zhang, *, Yonglin Feng, *, Yong Wang 3, *, Jinliang Shen, Wen Shao, Gang Wang, Gang Wang** College of Forestry, Sichuan Agriculture University, Chengu, China College of Business, Sichuan Agriculture University, Chengu, China 3 Institute of Mountain Hazars an Environment, Chinese Acaemy of Sciences, Chengu, China *These authors contribute equally **Corresponence: Gang Wang, Sichuan Agriculture University, Chengu 630, China. Tel: ; @qq.com Abstract: Both of qualitative an quantitative methos are applie to screen the inicators for forest ecosystem health assessment in nature reserves in Beichuan County. The inicator weights are obtaine by Principal Component Analysis, an the Fuzzy Moel is built to assess the forest ecosystem health. The values show that the forest ecosystem is of sub-health with the health value.77, an the elevation is the most influential element to forest ecosystem health. Keywors: forest ecosystem health assessment, principal component analysis, grey correlation analysis, fuzzy comprehensive evaluation. Introuction Forest health characterizing a forest far from the state of the isease, evaluating specific areas of forest health, it s the basis of the work carrie out forest management. Forest health has become a Forestry Science an Technology in a new irection, an gets more an more wiely recognize (Kong, Zao, Ji, Lu, Deng, Ma, & Zhang, 00). Forest ecosystem health assessment has become an important issue uring the recent years (Ma, Kong, Guan, & Fu, 00; Wang, Xiao, & Zhang, 007). Nature reserves in Beichuan County ha been estroye uring Wenchuan Earthquake, which resulte in the egraation of the forest ecosystem function in some areas (Hilty & Merenlener, 000); consequently, it is significant to evaluate the status of forest ecosystem health after the earthquake. In this article takes Beichuan nature reserves as the stuy area, to buil the fuzzy comprehensive evaluation moel to assess the status of forest ecosystem health, in orer to contribute to further research an post-quake reconstruction of forest ecosystem as well as sustainable evelopment.. Stuy Area Nature reserves stuie are locate in latitue 30 4 ~3 4 north, an longitue ~ 04 4 east in Beichuan county, Sichuan province, China. The lan is hilly with ravines an gullies, high in Science an Eucation Centre of North America 9

2 Jianshe Zhang et al. Submitte on September 30, 03 the north-west an low in the south-east, an 540~4769m above sea level. The annual average temperature is C, the annual rainfall is 399.mm, the annual average frost-free perio is 44~8 ays, an the average sunshine uration is 93.~.5 hours. The vegetation types have subtropical evergreen broa-leave forest, subtropical eciuous broa-leave forest, bamboo forest an subtropical evergreen coniferous forest. In aition, it is with rich water resources. 3. Methoology 3. Sampling Survey Base on fiel survey, 0 samples were set up in accorance with the types of forest, growth an istribution. Stanarize quarat of 0m 0m has been set in vegetation survey, to take the recor of elevation, slope irection, isturbance an soil, to scale each tree with height more than.3m, an to take the recor of tree species, number of trees, height an iameter. 5 shrub quarats of m m have been set along the iagonal line within selecte samples, while 4 grass quarats of m m have been set in the four corners, in orer to take the recor of variety, number, shae ensity an coverage(cui &Yang, 00). 3. The Inicators Consiering the status of Beichuan nature reserves, 8 inicators at three levels have been selecte. Due to the relevance among the inicators primarily selecte, these inicators shoul not be integrate irectly (Cui & Yang, 003). This stuy combines the qualitative an quantitative inicators, an further selects the inicators for assessment. Analysis of principal components has been aopte in quantitative selection on 8 primary inicators. An SPSS has been applie to analyze the samples stuie, an the values in table,combine with qualitative screening,there are 3 categories an 9 inicators for forest ecosystem health assessment of Beichuan nature reserves. Principal components Table.Values an variance contribution rate for partial principal components Value Primary Values contribution rate (% ) Etraction of Factor Loaing Accumulate contribution rate (% ) Value contribution rate (% ) Accumulate contribution rate (% ) 3.3 Ientify the Weight of Inicators In the present stuy grey relative moel has been use to efine the weight of inicators. The etaile steps are as followe (Chen, Dai, Ji, Deng, Hao, & Wang, 004): 30 Science an Eucation Centre of North America

3 Agricultural Science Vol., Issue 4, 03 () Base on the value of inicators, the combine matri R has been etermine. R={r i }m n, m as the number of samples, n as the number of inicators. () As the matri above, the combine matri is a sequence of numbers for assessment. This stuy takes the worst status {0,0,0, } as the reference sequence of numbers, gives a place of prominence to the factors of worse health status with impacts on entire forest ecosystem health, an then calculate the relevance between the reference sequence an the assessment sequence of numbers (Li, An, Cheng, Wang, Zhuo, & Qin, 00). The formula for calculation is escribe below. ξi( = min min i( k ma ma i( i i( k ma ma i( i i N γi = ξi N = ( In the formula above, ζ i ( is the grey correlation coefficient of the inicator of No. ; i(= (- i (, i ( is the reference sequence of numbers, an ( is the assessment sequence of numbers; k is the resolution ratio, for instance, the grey scale of [0, ] is 0.5; γi is the grey correlation coefficient of the inicator of No. in the reference sequence of numbers, N as the number of samples. (3) Normalization of the grey correlation coefficient of all inicators, this is the weight R for the assessment inicators. Follow the steps above to efine the weight of inicators at ifferent levels. The specific results are as table below. Table. The weight of the inicators for assessment Layer of Goal Layer of Components Layer of Inicators Vitality of forest ecosystem(0.0) Volume(0.0) Forest Ecosystem Health Assessment Forest ecosystem structure(0.73) Forest ecosystem resistiblity(0.7) Shrub richness(0.7) Grass richness(0.9) Degree of closure(0.09) Soil thickness(0.04) Elevation(0.8) Slope (0.03) Level of pest an isease(0.07) Degree of isturbance(0.09) 3.4 Builing Fuzzy Comprehensive Evaluation Moel The assessment base on the fuzzy mathematics theory (Wang, 005): B=RoA In the formula, B is the fuzzy subset for all levels, R is the set of weight, A is the fuzzy relation matri on egree of membership through membership function X, an o is the operation of arithmetic prouct of fuzzy matri. Parameters of membership function are efine as follows. The overall principle is to follow the Science an Eucation Centre of North America 3

4 Jianshe Zhang et al. Submitte on September 30, 03 3 Science an Eucation Centre of North America national or international stanars, so as to Main Technical Guieline on Forest Resources Design an Planning by the State Forestry Aministration (Lackey, 00; Allen, 00), take the value of eisting ecosystem with minor or none isturbance as the stanar value in the same geographic region. Therefore, the stanar value of 5 categories of the assessment inicators, in terms of very healthy, healthy, sub-healthy an sick, has been efine with the consieration of the current status of nature reserves in Beichuan. The assessment criteria for all inicators are as table 3. Table 3. Assessment criteria for all inicators Inicators I II III IV V Volume(m 3 /400m ) Shrub richness Grass richness Degree of closure Soil thickness/cm Elevation/m Slope/ Level of pest an isease Degree of isturbance The respective membership functions in line with 5 categories are as below. For category I, when =, = 0,,, ) ( A For category II, III, IV, when =, 3, 4, = 0,,, 0, () A For category V, when =5,

5 Agricultural Science Vol., Issue 4, 03 0, 4 4 A ( ) =, 4 5, 5 5 In the formula, is the original statistical value for each assessment inicator, an is the classification value for the respective classification criteria (Yuan, Liu, & Lu, 00) Results an Analysis 4. The Forest Ecosystem Health Assessment of all Samples Table 4 inicates that the overall status of forest ecosystem health is between II an III, an approaches to III, an emonstrates the tren from II of healthy status to III of sub-healthy status. Among 0 samples stuie, the assessment value of No. sample is the minimum of between I an II, while the assessment value of No. 0 sample is the maimum of between III an IV. Table 4. The values of forest ecosystem health Assessment in all samples Samples I II III IV V values of assessment General values.77 Science an Eucation Centre of North America 33

6 Jianshe Zhang et al. Submitte on September 30, Key Factors Influencing the Forest Ecosystem Health Table 3 inicates that among the three layers, the structure of forest ecosystem with the weight of 0.73, ha the highest impacts, while resistibility of forest ecosystem comes to the net, an vitality of forest ecosystem with minimum impacts on forest ecosystem health. Therefore, the structure hols a leaing position, as the most important factor influencing forest ecosystem health. Moreover, the environmental factors are with the weight of 0.43, an elevation with weight of 0.38 as the most influential factor among the three environmental factors. Figure reveals that the assessment values are increasing with the ascening of elevation, an consequently, the overall health status of forest ecosystem in the stuy area ecreases with the ascening of elevation. The maor causes coul be the features of vertical istribution for the vegetation in nature reserves, an ecrease percentage of trees an ecline plant iversity as well as egree of stan closure with the rising of elevation, which results on reuce stability of the structure. Nevertheless, the overall health status at the elevation of 00~600m is superior to those of 700~00m, which probably be because of the higher egree of isturbance at the elevation of 700~00m. Figure. The relationship between elevation an the assessment result 5. Conclusions an Discussion The weights efine base on ata of 0 samples inicate that, elevation is the key factor to influence the forest ecosystem health. The negative general health of nature reserve increase with elevation, but the general health at an altitue of 500 to 800 meters is better than that of 400 to 500 meters, the perhaps reason is the human isturbance at an altitue of 400 to 500 meters is larger than that of 500 to 800 meters. Generally, the forest ecosystem health is of sub-health, which is mainly cause by the low stability of the forest structure in nature reserves. Therefore, it was essential to enhance management of nature reserve to improve the status of forest ecosystem health in Beichuan. However, there are some ifficulties in quantification of some inicators an selection of ynamic factors ue to the comple of forest ecosystem an not perfection of relative theories, an there are no unifie assessment criteria for some inicators an various criteria aopte by ifferent researchers. Moreover, there is ifference among ifferent regions, which may result in the ifference in selection of membership function an assessment values of forest ecosystem health, therefore selection of more appropriate membership function shall be further stuie. 34 Science an Eucation Centre of North America

7 Agricultural Science Vol., Issue 4, 03 Acknowlegments The authors are thankful to the Protection of giant panas an other animal habitat recovery moe an Benefit Evaluation (Beichuan county government procurement teners (0) No.030 an (0) No.099). References [] Allen, E. (00). Forest health assessment in Canaa. Ecosystem Health, 7(), [] Chen, G., Dai, L., Ji, L., Deng, H., Hao, Z., & Wang, Q. (004). Assessing forest ecosystem health IMoel, metho, an ine system. Chinese Journal of Applie Ecology, 5(0), [3] Cui, B., & Yang, Z. (00). Inicator system for wetlan ecosystem health assessment. Acta Ecologica Sinica, (7), [4] Cui, B., & Yang, Z. (003). Temporal-spatial scale characteristic of wetlan ecosystem health. Chinese Journal of Applie Ecology, 4(), -5. [5] Hilty, J., & Merenlener, A. (000). Faunal inicator taa selection for monitoring ecosystem health. Biological Conservation, 9(), oi:0.06/s (99)0005-x [6] Kong, H., Zao, J., Ji, L., Lu, Z., Deng, H., Ma, K., & Zhang, P. (00). Assessment metho of ecosystem health. Chinese Journal of Applie Ecology, 3(4), [7] Li,., An, S., Cheng, X., Wang, Y., Zhuo, Y., & Qin, F. (00). Avances in Assessment of Ecosystem Health. Chinese Joural of Plant Ecology, 5(6), [8] Ma, K., Kong, H., Guan, W., & Fu, B. (00). Ecosystem health assessment: methoology an tren. Acta Ecologica Sinica, (), oi:0.33/.issn: [9] Lackey, R. T. (00). Values, policy an ecosystem health. BioScience, 5(6), [0] Wang, Y. (005). Assessment of forest ecosystem health in Taniang watershe Guangong. Ph.D paper of Zhongshan Univversity. [] Wang, Y., Xiao, W., & Zhang, X. (007). Current Status an Development Tenency of Forest Health Monitoring an Evaluation. Scientia Silvae Sinicae, 43(7), oi:0.33/.issn: [] Yuan, X., Liu, H., & Lu, J. (00). Assessment of ecosystem health - concept framework an inicator selection. Chinese Journal of Applie Ecology, (4), [3] Yong, W., Gang, W., & Feng, S. (0). The Dynamic Moel Preiction Stuy of the Forest Disease, Insect Pest an Rat Base on BP Neural Networks. Journal of Agricultural Science, 4(3), Science an Eucation Centre of North America 35