Site Classification And Evaluation Of Pine-oak Forests On The Southern Slope Of The Middle Qinling Mountains

Forest site classification and evaluation research is crucial to forest management and stand growth simulation.Focusing on the pine-oak forests,the study analyzed the height growth process of Pinus tabulaeformis,Pinus armandii and Ouercus aliena.Based on forest type and production,site index tables and site form tables were established for forest site evaluation.Impacts of multi-source data on model construction and predictions were explored.Main research content and results including:(1)Height-Diameter models for Pinus tabulaeformis,Pinus armandii and Quercus aliena were constructed.For different site conditions,six theoretical growth equations were compared to fit the height growth processes.These equations were extended by taking forest types as dummy variables.The fitting results shows that the extended Schumacher equation was best for Pinus tabulaeformis and Pinus armandii growth simulations.And extended Logistic equation was best for Ouercus aliena.According to Height-Diameter growth processes,forests types of similar production were combined.Based on former forest type studies,Pinus armandii stands were classified as hillside-valley bottom stands,Pyrola-bamboo stands and herbage stands.Pinus tabulaeformis stands were classified as bamboo-broadleaved stands,Oak-Pinus tabulaeformis stands and redge stands.Lespedeza-Ouercus aliena stands and bamboo-Ouercus aliena were combined as one forest type,although they have different volume.(2)Based on former site study of Huoditang forest farm,more data from different forest region of Qinling Mountains was collected.Site index tables and site form tables were established to evaluate forest productivity of the southern slope of middle Qinlin Mountains.The Chi-square tests showed that those tables are proper for practical applications.(3)Multiple types of inventory data on pine-oak forests were collected,including the temporal angle gauge plots,the permanent rectangle plots and stem analysis data.Impacts of multi-source data on model construction and predictions were analyzed.For different age gradations,the height curves,which were based on three types of inventory data,showeddifferent tendencies.Based on multi-source data,site evaluation models will provide more accurate results.