A approach for natural forest site quality evaluation based on site productive potential has been proposed by Fu, et al. This approach could be used to evaluate the productive of different site types quantitatively by combining of environmental and stand variables in theory. This study mainly focusing on the forest growth models in this approach by using stand basal area in the whole Jilin province, detailed modelling approaches of growth models, such as model selection, model parameterization, parameter estimation and model evaluation, have been proposed.
The computational formula for the current annual increment of basal area in the two situations with the basal area models containing age directly or indirectly had been derived using mathematical theory by assuming identity trees growth in stand. A criterion for testing the relationship of basal area current annual increment and stand density site whether being the monotonic function was proposed. The effects of different categorical variables on basal area were descripted by dummy variable approach, namely model parameterization. The parameters in the basal area growth model with parameterization were estimated by modified least square method. Stand basal area models were developed based on the four continuous measured data from 3 634 permanent plots with size of 0.06 hm2 in Jilin province.
The relationship of basal area annual increment and stand density site whether being the monotonic function was tested effectively using the approach proposed in this study, which would provide an important criterion for model selection. Considering parameterization in the developed model not only explained the differences among different levels in variables effectively but also improved the precision of the developed models. The parameters in the dummy models could be estimated effectively by modified least square approach.
The approach for developing natural forest growth model proposed in this study could be used as a technical support for Fu et al. natural site quality evaluation approach.