Forest Type Classification and Ecological Characteristics for Areas of Cheonwangbong, Songnisan
2015
Chung, S.H., Korea Forest Research Institute, Seoul, Republic of Korea | Hwang, K.M., Kangwon National University, Chuncheon, Republic of Korea | Sung, J.H., Korea Forest Research Institute, Seoul, Republic of Korea | Kim, J.H., Kangwon National University, Chuncheon, Republic of Korea
We classified the forest type and figured out the ecological characteristics for each of the types in order to provide the basic informations for being induced ecologically efficient forest practice plan by vegetation units in the natural forest of Songnisan. We established the 250 sample points and collected the vegetation data of vertical distribution for each sample. A variety of multivariate statistical methods were applied to classify the forest types. The species diversity index were analyzed to estimate the stability and maturity for forest vegetation in each the type. The types were divided from two to ten clusters by cluster analysis. The appropriate number of clusters was estimated five clusters by indicator species analysis. It was verified through the multiple discriminant analysis that the estimated number of clusters had been suitable. Based on the species composition for each the type, this study site was classified into five forest types: 1) Quercus serrata and 2) mixed mesophytic forest in the valley area, 3) Q. mongolica forest in the main ridge, 4) Pinus densiflora forest in the sub-ridge extending from the main, and 5) Q. variabilis-P. densiflora forest between the sub-ridge and valley. The species diversity index of the pine forest that had been a simple species composition was the lowest while that of the mixed mesophytic forest of which the composition had been diverse was the highest. As the forest vegetation was more varied, the index showed a tendency to increase.
اظهر المزيد [+] اقل [-]الكلمات المفتاحية الخاصة بالمكنز الزراعي (أجروفوك)
المعلومات البيبليوغرافية
تم تزويد هذا السجل من قبل Korea Agricultural Science Digital Library