Several methods are available to assess the plantation timber volume at their maturity. However, most of those methods can not be applied to the teak (Tectona grandis L.f) plantations of Sri Lanka, due to different site qualities and different management practices since planting. Therefore it is essential to carry out a comparative study of commercial log production managed under different conditions. For this purpose, the use of height-diameter and relative taper curves for estimation and prediction of planted teak stands in dry and intermediate zones of Sri Lanka were evaluated. Even-age mature plantations which are subjected to clear fell was selected randomly. Standing tree measurements of 164 trees were taken at three sites to build up the height-diameter curve. At the same time, 158 trees were felled and took diameter measurements along the felled log to construct the relative taper curve. The resulted models are useful in generating accurate and localized predictions of standing tree height, total timber volume, commercial timber volume which would eventually lead to better estimations on differently managed teak plantation sites. By measuring the diameter at breast height alone, the developed log diameter-length tables could estimate the commercial log length according to specific diameter values which would finally lead to better commercial log estimation to compete with increasing demand along with different site conditions.

Most survival analyses in forest science have been applied to planted forests where tree age usually had no dispersal on one stand, while there have been few reports about the age-based survival analyses in natural forests. The purpose of this study was to perform survival analyses of individual tree populations in natural forest stands to evaluate the matured states of forest stands. We used a combination of tree-ring and census data from the three preserved permanent plots in pan-mixed and sub-boreal natural forests, Hokkaido, northern Japan. All the living trees (diameter at breast height ≥ 5 cm in 1989) were targeted to identify tree ages using a RESISTOGRAPH. Periodical tree age data with a 10-year age class were used during the observation periods of 1989-1999, 1999-2009, and 2009-2019, and all the changes (i.e., death and new ingrowth) during the periods were recorded. In the analyses, first, we applied survival analyses to find out multi-temporal age distributions and non-parametric estimates. Secondly, we applied parametric Weibull distributions to calculate age-related metrics such as mean lifetime and mean age of stands. Finally, we evaluated these calculated metrics from the viewpoints of matured states of forest stands. The results of non-parametric survival analyses showed the age distribution of multi-modal and exponential shapes. We also found the differences in survival probabilities among periods were not significant except for one plot. We also compared the relationship among estimated mean lifetime, biological lifetime, and mean age of stands derived from parametric survival analyses with the Weibull distribution and evaluated the matured states of stands considering all these aspects. It was implied that the study stands might not get enough matured yet, but some plots showed further progress toward the matured state than others.

Scientifically sound methods are essential to estimate the survival of trees, as they can substantially support sustainable management of natural forest resources. Tree mortality assessments have mainly been based on forest inventories and are mostly limited to planted forests; few studies have conducted age-based survival analyses in natural forests. We performed survival analyses of individual tree populations in natural forest stands to evaluate differences in the survival of two coniferous species (Abies sachalinensis (F. Schmidt) Mast. and Picea jezoensis var. microsperma) and all broad-leaved species. We used tree rings and census data from four preserved permanent plots in pan-mixed and sub-boreal natural forests obtained over 30 years (1989–2019). All living trees (diameter at breast height ≥ 5 cm in 1989) were targeted to identify tree ages using a Resistograph. Periodical tree age data, for a 10-year age class, were obtained during three consecutive observation periods. Mortality and recruitment changes were recorded to analyze multi-temporal age distributions and mean lifetimes. Non-parametric survival analyses revealed a multi-modal age distribution and exponential shapes. There were no significant differences among survival probabilities of species in different periods, except for broad-leaved species, which had longer mean lifetimes in each period than coniferous species. The estimated practical mean lifetime and diameter at breast height values of each coniferous and broad-leaved tree can be applied as an early identification system for trees likely to die to facilitate the Stand-based Silvicultural Management System of the University of Tokyo Hokkaido Forest. However, the survival probabilities estimated in this study should be used carefully in long-term forest dynamic predictions because the analysis did not include the effects of catastrophic disturbances, which might significantly influence forests. The mortality patterns and survival probabilities reported in this study are valuable for understanding the stand dynamics of natural forests associated with the mortality of individual tree populations.

Predicting future stand conditions based on tree age is crucial for natural forest management. The objective of this study was to model and predict the future age distribution of Picea jezoensis, Abies sachalinensis, and broad-leaved trees by assessing the past and current survival trends of preserved stands located at the University of Tokyo Hokkaido Forests (UTHF), Furano, Japan. This study analyzed forest census data of four plots (927 trees) in a preserved permanent area over 30 years (1989–2019). Individual tree-ring data were identified using a resistograph to determine the current tree age of the targeted trees. The predicted age distributions nearly converged to the shape of the survival probability curve. Among the scenario predictions, the multimodal age class distribution of P. jezoensis was predominant among all prediction scenarios. In contrast, the exponential shape of A sachalinensis and the age distribution of broad-leaved trees in the 100% scenario gradually shifted to the multimodal shape at the 50% scenario prediction. The species composition of conifer and broad-leaved trees and their age distribution would reach stable states in the long run by reaching a climax state. Therefore, it is theoretically possible to maintain stands under the pre-climax stage by allowing high growth rates at the stand level. The suggested age class-prediction of living and dead trees can improve the natural forest management of UTHF.

In forests, tree mortality is strongly determined by complex interactions between multiple biotic and abiotic factors, and analysis of tree mortality is widely implemented in forest management. However, age-based tree mortality remains poorly evaluated quantitatively at the stand scale of the uneven-aged forests. The objective of this study is to predict the age distribution 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 panmixed 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 tree ages using a RESISTOGRAPH, a semi non-destructive device. Periodical tree age data with a 10year age class were used during the observation periods of 2009-2019, and all the changes (i.e., death and new in-growth) during the periods were recorded. We found the time stabilities of survival functions between periods in advance. The results showed that the parametric survival analysis with Weibull distribution successfully yielded the mortality rate, mortality probability, and survival probability in each plot. Finally, we predicted the future age class distribution of living and dead trees of each plot based on the survival analyses results and discussed its management implications. We recommended that the estimated mean lifetime was facilitated to make decisions on the selection of harvesting trees in the uneven forest management based on selective cutting.