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We chose a five-variable model (canopy closure, tree age, total basal area, volume of "large" wood and basal area of hardwoods) because it included the fewest variables and included only those that could be affected by management.
Some information about site conditions including elevation, slope inclination and soil pH, forest structure characteristics such as canopy closure, tree density and basal area, and human interference (numbers of stumps and footpaths) in the initial random sample plots was also collected.
They essentially summarize the complete set of weights determining the full closure tree.
Following from this, given a query network, closure tree algorithm starts aligning query to the root node.
This substantially simplifies the implementation and interpretation of related closed test procedures, as the closure tree of 2 m−1 intersection hypotheses is tested in only m steps.
The associated transition matrix is The graph in Figure 1 together with Algorithm 1 from above fully specify the 32 weights of the full closure tree, as summarized in Table 1.
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At Okiwa, for stands planted at a density of 1250 stems ha−1, the canopy radius of all seed lots increased at a similar rate of ~0.35 m per year such that the canopy of adjacent trees planted 2 m apart within a row touched within 3 years, and between-row closure (trees 4 m apart), would likely occur at about age 6 7 years.
Another method for graph database indexing is Closure-Tree (CTree) (He and Singh, 2006).
Closure-Tree organizes the networks in the database using a binary tree structure.
The suitable SWC measures identified for nearly 40% of the areas in the Blue Nile Basin is area closure and/or tree planting.
The wide range of the annual ET totals for the SRCs was determined mainly by the different rotation periods and ages of the stands, along with the leaf area index (LAI), the state of the canopy closure, and tree heights.
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