We calibrated a spatially-explicit individual-based forest dynamics model SORTIE-ND to conifer-broadleaved mixed stands in the University of Tokyo Hokkaido Forest, and evaluated its accuracy of reconstructing past stand structure development under a single-tree selection system. We also modified the model so that it would be applicable under various geographic conditions by incorporating variables that were derived from the Digital Elevation Model (DEM). We used inventory data collected from 12 permanent plots to estimate the model parameters. The analysis involved 23 tree species and species groups. The model consisted of five submodels: light, growth, mortality, snag dynamics, and recruitment. After the calibration, we evaluated model accuracy on a stand scale. The results of the evaluation showed that SORTIE-ND fairly accurately reconstructed the past development of basal area, diameter class distribution, and species composition. It was indicated that SORTIE-ND can be flexibly adapted to the regional characteristics of the study site, and has a large potential for exploring single-tree selection regimes that allow for the conservation of stand structure in conifer-broadleaved mixed stands.

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Functional-Structural Plant Models (FSPM) are becoming important tools for modeling the structure and growth of plants, including complex organisms like trees. These models combine the advantages of empirical, mechanistic, and structural models to simulate the growth of individual plant structures (branches, buds, leaves, etc.). This approach enables realistic evaluation of the plant's response including changes in structure and growth to different environmental conditions. We demonstrate the potential use of these models to evaluate individual tree growth under different management regimes (pruning). The data used in this study was obtained from 3-D measurements taken with a FASTRAK Polhemus digitizer, with specific attention given to bud creation and branching. Each branch segment was analyzed to estimate its age, enabling us to document annual structural changes. We use the XL programming language and a GroIMP environment to simulate and compare different pruning scenarios.

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In developing incentives and protocols to reduce carbon emissions and increase carbon sequestration, one important omission stands out. Policy makers have ignored or minimized the importance of carbon storage in wood products and the associated secondary emissions. In this paper, I present the results from a discrete dynamic programming model used to determine the optimal harvest decision for a forest stand that provides benefits from timber harvest, carbon sequestered in forest and carbon storage in wood products. This study is distinguishable from previous studies because it considers varying levels of starting dead organic matter (DOM) and wood product stocks. This is important because it allows one to establish a threshold level for determining if a landowner is better off participating in the type of carbon market considered in this study. The results of the study suggest that the optimal decision to harvest is independent on the carbon stocks in the wood product pool but significantly affects economic returns to carbon management. The results also indicate that economic returns decrease with increasing initial levels of carbon in wood product and secondary carbon emissions have very little or no impact on the optimal decision to harvest. Contrary to the results from other studies, the results from this study reveal that increasing carbon price for a landowner to participate in the type of carbon market considered in this study will have the counterintuitive result of inducing the landowner to manage for carbon, if the wood product pool is considered.

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In the present work the cork oak tree spatial growth simulator CORKFITS is used to create candidate scenarios for generating a large set of regeneration regimes combining both time and intensity factors with the individual tree spatial information. An optimal regeneration regime under continuous crown cover requirements is sought by applying a dynamic programming algorithm. It is shown that the crown cover constraint influences the total cork production potential in a negative way. The target cover constraint of 50% decreases the cork production by 66% from the potential in 40 years in our mature plot, and approximately 43% in our young plot. Higher crown cover constraint of 70% decreases the potential cork production approximately by 54% in the mature plot and does not have any influence on the younger plot. The observed losses in cork production in relation with the potential with the crown cover constrains need to be compensated economically by the higher availability of growing space for the grazing and livestock part of the montado/dehesa production system.

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The objective of this study was to develop a tree mortality prediction model using a semi-parametric survival model based on longitudinal data derived from permanent plots. Here, tree mortality data derived from four permanent plots of Cryptomeria japonica planted forest and the Cox proportional hazards model was applied to this data using two time-independent covariates and seven time-dependent covariates. Relative spacing, which is a time-dependent covariate, was selected as the best single predictor for the tree mortality model, while, site index, which is a time-independent covariate, was better single predictors than other time-dependent variables. Through a model selection procedure, the tree mortality model that included site index (time-independent) and stand density and cumulative number of decreased trees (time-dependent) was selected as the best model.

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Akaike's Noise Contribution Ratio (NCR) has been used for the analysis of causality of two-variable settings of biological time series in Neuroscience. In contrast to the conventional correlation definition, this methodology is able to detect the direction of the influence between two variables. However, if a third series intervention is taken into account, the validity of causality is questionable, since possible feedback with third series can induce spurious or indirect causality. In this paper, we introduce a modification to NCR that accounts for partial directed causality for the case of more than two variables (pNCR). We also extend this methodology for the case of non-stationary time series by means of the use of the sliding windows technique, which provides a time-frequency approach. This methodology produces a 2D matrix (time and frequency) of pNCR coefficients, which is difficult to interpret and visualize. To facilitate the visualization and interpretation of the pNCR for the case of non-stationary time series, we summarize the information of the spectrum of the pNCR as the area under the curve (pNCA), which projects this 2D matrix into the 1D space (a vector of coefficients), which shows the time course rate of influence from one variable to another in both directions.

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This study follows the introduction of community forestry in Bangladesh and uses secondary information sources to analyze its effectiveness as a means of fostering sustainable forest management. We found that current forest management practices in Bangladesh have evolved from an emphasis primarily on production to a more people-centric model designed to support the conservation of forest resources. First introduced in the late 1970's, community forestry has proven a successful model for reforestation, afforestation, and diversifying economic opportunities in rural communities. A total of 30,666 ha of woodlot plantations, 8,778 ha of agroforestry plantations, and 48,420 km of strip plantations have been established by the Forest Department under community forestry programs since the mid-1980's. Furthermore, some mature plantations have been harvested and the benefits distributed among key stakeholders. The 1994 Forest Policy, the Forest (Amendment) Act of 2000 and the 2004 Social Forestry Rules are considered milestone achievements for the implementation of community forestry in Bangladesh. A Tree Farming Fund (TFF) has been established to provide a sustainable revenue stream for community forestry projects. Bangladesh has succeeded in reducing distrust and conflict between forestry officials and local farmers, encroachment on government lands, and the deforestation rate. But, program implementation has faced roadblocks that stem from a top-down bureaucratic approach and poor governance system. A number of NGO’s are also working to promote community forestry with notable success, despite short-comings that include strong profit motive, poor coordination with government bodies, lack of transparency, and non-uniform benefit sharing mechanisms. However, a traditional community-based forest management model known as village common forests (VCF) practiced by indigenous people of the Chittagong Hill Tracts (CHT) may be a useful guide for policymakers looking for ways to support sustainable forest management that involves local people.

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We use a mean-reverting stochastic model to demonstrate a procedure for calculating the reverted mean and asymptotic stationary distribution of sawlog price data. The data used for this study comes from a local auction market in the Fukuoka Prefecture, Japan where 4m long sugi (Cryptomeria japonica) and hinoki (Chamercypress obtusa) are commonly traded. Parameter estimation is completed using a quasi-maximum likelihood method based on a local linearization scheme. The stationary distribution for our stochastic model is numerically constructed using a generalized Pearson system.

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