Prediction of Tree Age Distribution Based on Survival Analysis in Natural Forests: A Case Study of Preserved Permanent Plots in the University of Tokyo Hokkaido Forest, Northern Japan

Abstract

In forests, tree mortality is strongly determined by complex interactions between multiple biotic and abiotic factors, and the analysis of tree mortality is widely implemented in forest management. However, age-based tree mortality remains poorly evaluated quantitatively at the stand scale for unevenly aged forests. The objective of this study was to predict the age distributions of living and dead trees based on survival analyses. We used a combination of tree-ring and census data from the two preserved permanent plots in the University of Tokyo Hokkaido Forest in pan-mixed and sub-boreal natural forests, Hokkaido, northern Japan, to derive site-specific survival models. All the living trees (diameter at breast height, ≥5 cm in 2009) were targeted to identify the tree ages using a RESISTOGRAPH, a semi-nondestructive device. Periodical tree age data with a 10-year age class were used during the observation periods of 2009–2019, and all the changes (i.e., death and new ingrowth) during the periods were recorded. We determined the time stabilities of the survival functions between periods in advance. The results show that the parametric survival analysis with the Weibull distribution successfully yielded the mortality rate, mortality probability, and survival probability in each plot. Finally, we predicted the future age class distributions of living and dead trees of each plot based on the survival analysis results and discussed their management implications. We recommend that the estimated mean lifetimes facilitate making decisions on the selection of harvesting trees in uneven forest management based on selective cutting.