[A two-step approach for modeling tree mortality in Larix olgensis plantation based on effects of thinning]

Ten permanent plots of Larix olgensis plantation were established in 1972 and 1974 at Jiangshanjiao and Mengjiagang forest farms in Heilongjiang Province, respectively. The plots including 8 thinning plots and 2 control plots were measured annually. The effects of thinning on the probability of plot mortality and individual tree mortality were analyzed. Based on the binary logistic regression, two-step models of the probability of mortality were developed. The approach consisted of estimating the probability of mortality after thinning on a sample plot (1) and the mortality of individual tree within mortality plots (2). The generalized estimating equations (GEE) method was adopted to estimate the parameters of models. An optimal cutpoint was determined for each model by plotting the sensitivity curve and the specificity curve and choosing the cutpoint at which the specificity and sensitivity curves cross. The results showed that four models (models 1-4) were developed based on the data of plots which was divided into 4 groups by thinning times, respectively. The significant explicatory variables of model 1 were site index, the logarithm of stand age, thinning age and thinning intensity. Principal component analysis was used to develop models 2-4. The primal variables of the principal components were stand age, tree numbers per hectare, mean square diameter at breast height and thinning factors. This showed that thinning significantly affected the probability of plot mortality. The effect of thinning was not significant for the pro-bability of individual tree mortality. The significant variables of the individual tree mortality model were planting density, age, the inverse of diameter at breast height and the basal area of all trees larger than the subject tree. Hosmer and Lemeshow goodness of fit tests were not significant for the mortality models of plots and individual trees (P＞0.05). The areas under the receiver operating characteristic curve (AUC) of the models were all greater than 0.91, the accuracies were all above 80%, suggesting the fitting results of the models performed very well.