TAILIEUCHUNG - Constructing mortality models for natural forest state III in four provinces of the Central region, Vietnam

In this research, the dead trees were defined as the standing trees that died between the two occasions at which measurements were taken. The data on 300 subplots from 12 permanent sample plots were collected. The response variable was the number of dead trees per subplot. | Silviculture CONSTRUCTING MORTALITY MODELS FOR NATURAL FOREST STATE III IN FOUR PROVINCES OF THE CENTRAL REGION, VIETNAM Cao Thi Thu Hien Vietnam National University of Forestry In this research, the dead trees were defined as the standing trees that died between the two occasions at which measurements were taken. The data on 300 subplots from 12 permanent sample plots were collected. The response variable was the number of dead trees per subplot. The results suggest that we successfully developed the mortality model by using both generalized linear and generalized linear mixed models for count data to address the problem of overdispersion. Arithmetic mean diameter of the subplot, plot basal area, and provinces as a categorical variable were found to be the most significant explanatory variable. With the generalized linear model, we found that the Negative Binomial GLM was the most appropriate model for predicting the number of recruitment for three groups. From using the provinces as a grouping variable, we realized that the mean numbers of dead trees was different in the four different locations, namely the number of dead trees for group 1 and group 2 in Thua Thien Hue were the highest, while in Ha Tinh these were the lowest. With the generalized linear mixed model, the Negative Binomial GLMM solves overdispersion by treating a plot as a random effect. The GLMM with random intercept was selected as the equation for the direct prediction of dead trees across each of the two species groups, and for N. melliferum. The GLMM with a random slope was chosen for S. wightianum. Keywords: Generalized linear model, generalized linear mixed model, mortality model, Negative Binomial GLM, tropical rainforests. 1. INTRODUCTION Natural mortality of trees is a crucial process that determines forest dynamics (Rüger et al., 2011). When a tree dies, the reduced competition benefits the trees near the dead tree, positively affecting their growth (Yang et al, 2003); in addition, .

• Lâm nghiệp
• Generalized linear model
• Generalized linear mixed model
• Mortality model
• Negative Binomial GLM
• Tropical rainforests
• Bayesian multilevel generalized linear model
• Economic growth rate
• Sustainable economic growth
• Higher per capita income
• Worldwide governance indicators
• BMC Bioinformatics
• RNA Seq
• Power analysis
• Bivariate negative binomial
• Generalized linear mixed effects model
• Allelic imbalance
• Hierarchical generalized linear mixed model
• High throughput sequencing experiments
• Single nucleotide polymorphism
• Econometric analysis
• The linear regression model
• Least squares
• The least squares estimator
• Hypothesis tests
• Instrumental variable estimation
• The generalized regression model
• Báo cáo sinh học hay
• cách trình bày báo cáo
• báo cáo sinh học
• công trình nghiên cứu sinh học
• tài liệu về sinh học
• Genome Biology
• Cellular detection rate
• Co expression
• Empirical Bayes
• Gene set enrichment analysis
• Chromosome conformation capture
• Hi C normalization tool
• Read depth
• Copy number variation
• Quản lý tài nguyên rừng
• Tropical rainforest
• Kolmogorov–Smirnov test
• Diameter structure
• Continuous distribution
• Diameter increment
• Fixed effects model
• Linear mixed effects models
• Species group