Stand-Age Derived Competition Indices Influence Individual Tree Mortality Model Prediction for Naturally Occurring Even-Aged Shortleaf Pine Stands

Pradip Saud,James M Guldin,Sudip Shrestha,Thomas B Lynch

doi:10.3390/f13020314

Abstract

To understand the influence of competition indices and post-thinning effects in predicting individual tree mortality, we developed two models, one without the effect of thinning and another, with the effect of thinning for naturally occurring even-aged natural shortleaf pine (Pinus echinata Mill.) stands in the Ozark and Ouachita National Forests in Oklahoma and Arkansas, USA. Over the period of 25 years, six re-measurements of an individual tree from each plot were collected between 1985 and 2014. The logistic function was used to model the probability of mortality for which the binary response variable was, ‘0’ for living and ‘1’ for dead trees, using iteratively weighted regression and mixed-effects model. Stand-age derived competition indices such as, the ratio of stand basal area to stand age (SBAG), ratio of individual diameter to stand age (DAG), and the quadratic mean diameter (QMD), were found significant in predicting the probability of mortality. These variables were also found to be effective in the thinning effect model. However, excluding the thinning variable resulted in better performance with the chi-square test based on mortality within mid-diameter classes. Thus, the mortality model suggests that over time, individual tree mortality is influenced more greatly by competition modified by stand age rather than by a post-thinning effect in even-aged naturally occurring shortleaf pine trees.

Highlights

Tree mortality is part of an integral system in forest development that modifies a stand development which alters forest ecosystem services such as wildlife habitats, biodiversity maintenance, wood supply, and the atmospheric carbon (C) cycle [1,2,3]
The highest mortality rate occurred for the lower dbh class during the second measurement period (Table 1), which could be due to the effects of competition as the density increased on the plots
Our findings suggest that an independent variable that provides variation in the point estimates of their associated parameters, either relatively small or very large in the combination of the other variables in a model, might be helpful to predict the better mortality probability of an individual tree

Summary

Introduction

Tree mortality is part of an integral system in forest development that modifies a stand development which alters forest ecosystem services such as wildlife habitats, biodiversity maintenance, wood supply, and the atmospheric carbon (C) cycle [1,2,3]. Modeling tree mortality (death of trees) helps predict the stand development and project the future trajectory of forest ecosystem services. As a result of the self-thinning of the lower canopy due to stand competition and other disturbance factors, tree mortality could occur at different stages of stand development [7]. Modeling the potential factors affecting tree survival helps predict the tree mortality or survival of individual trees in a forest stand [3,8,9,10]. The mortality probability of an individual tree is primarily influenced by its vigor, stand density, species composition, site quality, and competition indices [11,12,13]. Mortality is related to individual tree attributes [5,6,11,12,13], and it is often influenced by the long-term effects of applied treatment [4,14]

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