Study On The Evaluation Of Biodiversity Of Quercus Liaotungensis Forest Of Dong Ling Mountain By The Technology Of Radial Basis Function

Forest, whose species play the critical role in biosphere, is the main body of the terrestrial ecosystem. Due to historical reason that forest resources have been persistently exploited, forest resources in China are undergoing increasing pressure, thus fail to rehabilitate normally. Not only the number of natural forests sharply decreases but also their quality continues to decline. Forest ecosystem is still being seriously threatened since forest biodiversity is evidently descending and many specific species are facing the fate of extinction or even disappearance. Therefore, forest biodiversity conservation greatly influences the ecological environments in our country as well as world biodiversity.The variance regularity of Quercus liaotungensi biodiversity in Dong Ling Mountain is analyzed by the aid of a & indices of species diversity as well as RBF of artificial neural network in accordance with the principles of plant community, biodiversity and nonlinear ecology in this article withQuercus liaotungensis in Dongling Mountain, Beijing as the research objective. The changes of diversity indices of shrub and arbor species mQuercus liaotungensiare also compared in the article. Furthermore, the predictive evaluation towards the development of biodiversity of Quercus liaotungensishows that:a. The changing range is slight despite a diversity indices of shrub and arbor diversity in Quercus liaotungensi at various elevations gradually decreased. The composition of community species is favorable to simple.b. indices of arbor and shrub diversities in Quercus liaotungensi at various elevations reflect that arbor species and shrub species differently influence the biodiversity of liaotungensis.c. Quercus liaotungensi is a stable forest as a whole because of its low evolution rate of species and relatively stable species composition.d. Quercus liaotungensi is the single dominant community with complex environmental heterogeneity approved by prediction towards spatial heterogeneity of Quercus liaotungensis biodiversity by RBF as well as evaluation of the relationship between geographical environmental factors and biodiversity.e. The neural network model designed by radial basis function in this study, can calculate and simulate regional biodiversity indices so as to establish the nonlinear relationship between biodiversity indices and geographical environmental factors under any circumstance of geographical environments.f. RBF, as a kind of artificial neural network, is accessible to evaluate and predict forest biodiversity and objectively reflects the actual state of evaluated forests. The conclusions of the study may offer the initial evidence for evaluation of forest biodiversity as well as conservation and administration of plant resources.