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"Papua has been experiencing heavy logging activity in its forests for decades . However, only several studies focused on the effect of logging in the forest ecosystem. This research was aimed to analyze recovery processes of the forest ecosystem. The research was conducted in the logged tropical rainforest in South Papua using ecological approach which used tree communities as biotic and soil condition as abiotic indicators. Data were collected in the logging area of PT Tunas Timber Lestari located in the tropical rainforest of South Papua. There were five groups of forests used in this research i.e. unlogged, one year post selectively-logged, five years post selectively-logged, ten years post selectively-logged and fifteen years post selectively-logged forests. Thirty nested plots were laid on each forest group. Canonical Correspondence Analysis (CCA) was applied to analyze the understory and upperstory plant communities. Understory and upperstory plant communities formed different patterns due to logging. Plant communities in the ten and fifteen years post-selectively logged forests were not similar to those in the unlogged forest. Soil organic matter (SOM) content in the selectively logged forests was lower than that in the unlogged forest. These occurrences indicated that the selectively logged forests were still recovering and required more than fifteen years to be fully recovered."

"Natural mortality of trees is extremely variable due to the uncertainty and complexity of the functioning of forest ecosystems. The objective of this study was to develop a stand-level mortality model for Acacia mangium species by relating mortality to stand variables that affect the natural mortality process. The model was developed using data from l97 permanent sample plots measured periodically at 1-yr time intervals from 2-4 years until 8-11 years after planting in South Sumatra, Indonesia. The model consists of two complementary equations. The first equation is a logistic function predicting the probability of mortality incidence depending on stand density, site index and stand age. The second equation estimates the reduction in the number of surviving stems observed in a stand where natural mortality occurs. Nine equations were fitted using data from permanent sample plots where trees died over the time period and the best model was selected. Estimates from this second model were then adjusted by a factor equal to the probability of mortality applying three different approaches: probabilistic two-step, deterministic threshold and stochastic. All methods revealed no significant difference between the observed and the predicted number of surviving stems per ha. The probabilistic two-step approach, however, produced more consistent and the most accurate estimates. This method should provide reliable prediction when it is to be used in forest productivity prediction and management system for the species."