Derivation and analysis of new stand‐level mortality models based on existing growth equations

Abstract

Considering that, the temporal trend in stocking, expressed as number of trees per unit area, is the opposite of that of growth, and that both trajectories are sigmoidal, we derived a temporal trajectory of density decrease by reversing the temporal trend of a generalized growth function. We derived and analysed twelve stand‐level mortality models by using four data sets from monospecific even‐aged stands. Stand dominant height rather than stand age was incorporated as an indicator of the growth stage and a careful examination of the models conformity with the essential logical properties of the stand‐level survival models was conducted. We first tested the models adequacy and general predictive performance by fitting them to parameterization data sets and subsequently assessing them with validation data. The regression equations were re‐fitted afterwards over the total data sets to make use of all available information in the final parameter estimates. Nine model formulations were successfully fitted and four of them were the most adequate in describing stand density decrease with dominant height growth. The site‐specific effect was incorporated in the newly derived models through the predictor variable and the stand‐specific starting density was accounted for through a specific model parameter. These new dominant height‐dependent mortality equations can be considered for inclusion in the framework of stand‐level growth models as transition functions.