Background： A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection...Background： A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system. Methods： The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model. Results： Diameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. Conclusions： The model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design.展开更多
The artificial pure and mixed Korean pine (Pinus koraiensis) forests were investigated at Dailing Forestry Bureau in Xiaoxing'an mountains from 1990 to 1992. Depending on the distance between the samplings of Kore...The artificial pure and mixed Korean pine (Pinus koraiensis) forests were investigated at Dailing Forestry Bureau in Xiaoxing'an mountains from 1990 to 1992. Depending on the distance between the samplings of Korean pine and their neighbor trees, the neighbor tree height, the size of neighbor tree canopy, and dimension of neighbor tree. The forest structure was classified into three types: (1) prowth of a tree in the light (open), (2) Growth of a tree in the canopy gap (Gap), (3)Growth of a tree under broad-leaved tree canopy. The frequeney, height, and age of stem divergence of Korean pine tree were investigated by sampling trees. The temporal and spatial model of the tree growth was applied on basis of the height of stem divergence, ratio of height and DBH, and character of tree stem.The morphology and growth character of Korean pine trees during different development stage were forecasted.展开更多
Background： Growth and yield models are important tools for forest planning. Due to its geographic location, topology, and history of management, the forests of the Adirondacks Region of New York are unique and compl...Background： Growth and yield models are important tools for forest planning. Due to its geographic location, topology, and history of management, the forests of the Adirondacks Region of New York are unique and complex. However, only a relatively limited number of growth and yield models have been developed and/or can be reasonably extended to this region currently. Methods： in this analysis, 571 long-term continuous forest inventory plots with a total of 10 - 52 years of measurement data from four experimental forests maintained by the State University of New York College of Environmental Science and Forestry and one nonindustrial private forest were used to develop an individual tree growth model for the primary hardwood and softwood species in the region. Species-specific annualized static and dynamic equations were developed using the available data and the system was evaluated for long-term behavior. Results： Equivalence tests indicated that the Northeast Variant of the Forest Vegetation Simulator （FVS-NE） was biased in its estimation of tree total and bole height, diameter and height increment, and mortality for most species examined. In contrast, the developed static and annualized dynamic, species-specific equations performed quite well given the underlying variability in the data. Long-term model projections were consistent with the data and suggest a relatively robust system for prediction. Conclusions： Overall, the developed growth model showed reasonable behavior and is a significant improvement over existing models for the region. The model also highlighted the complexities of forest dynamics in the region and should help improve forest planning efforts there.展开更多
文摘Background： A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system. Methods： The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model. Results： Diameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. Conclusions： The model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design.
文摘The artificial pure and mixed Korean pine (Pinus koraiensis) forests were investigated at Dailing Forestry Bureau in Xiaoxing'an mountains from 1990 to 1992. Depending on the distance between the samplings of Korean pine and their neighbor trees, the neighbor tree height, the size of neighbor tree canopy, and dimension of neighbor tree. The forest structure was classified into three types: (1) prowth of a tree in the light (open), (2) Growth of a tree in the canopy gap (Gap), (3)Growth of a tree under broad-leaved tree canopy. The frequeney, height, and age of stem divergence of Korean pine tree were investigated by sampling trees. The temporal and spatial model of the tree growth was applied on basis of the height of stem divergence, ratio of height and DBH, and character of tree stem.The morphology and growth character of Korean pine trees during different development stage were forecasted.
文摘Background： Growth and yield models are important tools for forest planning. Due to its geographic location, topology, and history of management, the forests of the Adirondacks Region of New York are unique and complex. However, only a relatively limited number of growth and yield models have been developed and/or can be reasonably extended to this region currently. Methods： in this analysis, 571 long-term continuous forest inventory plots with a total of 10 - 52 years of measurement data from four experimental forests maintained by the State University of New York College of Environmental Science and Forestry and one nonindustrial private forest were used to develop an individual tree growth model for the primary hardwood and softwood species in the region. Species-specific annualized static and dynamic equations were developed using the available data and the system was evaluated for long-term behavior. Results： Equivalence tests indicated that the Northeast Variant of the Forest Vegetation Simulator （FVS-NE） was biased in its estimation of tree total and bole height, diameter and height increment, and mortality for most species examined. In contrast, the developed static and annualized dynamic, species-specific equations performed quite well given the underlying variability in the data. Long-term model projections were consistent with the data and suggest a relatively robust system for prediction. Conclusions： Overall, the developed growth model showed reasonable behavior and is a significant improvement over existing models for the region. The model also highlighted the complexities of forest dynamics in the region and should help improve forest planning efforts there.
