Modeling survival of loblolly pine trees in thinned and unthinned plantations

Abstract

The probability of survival for an individual tree was modeled. A variable screening algorithm, screen, was used to find the best set of predictor variables. Stepwise procedures in SAS and BMDP were also used, and results were compared with those obtained from the SCREEN algorithm. The logistic model, with independent variables that were found to be significant through the SCREEN algorithm, was fitted to the data. The fitted models were validated by splitting the data and applying equations fitted to the estimation set to the data in the testing set. Two methods of data splitting were applied: (i) according to time period and (ii) at random. Validation statistics were similar for both cases. The final distance-dependent logistic model for the unthinned plots included the following independent variables: crown ratio (CR), total height/average height of dominant and codominant trees (HH), and competition index (CI). The logistic model with CR, HH, and quadratic mean diameter/DBH (DD) was used as the distance-independent model of survival for the unthinned plots. The final distance-dependent logistic model for the thinned plots included as predictor variables HH, CI, and CR 1.5 . For the thinned plots the final distance-independent model used DD, CI, and CR 1.5 as independent variables. The logistic models of survival obtained in this study were compared with survival models developed previously for distance-dependent and distance-independent stand simulators. Only slight improvement is shown by the logistic models.