AI Summary & Key Takeaways
AI InsightBased on the results, the improvement obtained by the inclusion of crown variables is not enough to justify the additional costs in measuring crown variables of standing trees for volume estimation.
📌 3 Key Takeaways
Abstract
Crown characteristics are an important component of growth and yield models. The stem form of a tree depends to a large extent on the tree crown dimensions. However, there is no unified agreement on whether crown variables (crown ratio and crown length) should be incorporated into taper models for accurate predictions of diameter and volume. The purpose of this study was to investigate the level of improvement that the incorporation of crown variables into taper equations for black pine (Pinus nigra J.F.Arnold subsp. pallasiana (Lamb.) Holmboe) gives to diameter and stem volume predictions. Linear and nonlinear crown variable functions were incorporated into a compatible volume and taper equation to evaluate their effect in model prediction accuracy. The inclusion of crown variables provided significantly different parameter estimates but only resulted in a modest reduction of fitting statistics for both diameter and volume with lower average bias and lower mean squared errors for all modified models, although the improvement in stem volume prediction was minimal. Based on the results, the improvement obtained by the inclusion of crown variables is not enough to justify the additional costs in measuring crown variables of standing trees for volume estimation.
Özet
Crown characteristics are an important component of growth and yield models. The stem form of a tree depends to a large extent on the tree crown dimensions. However, there is no unified agreement on whether crown variables (crown ratio and crown length) should be incorporated into taper models for accurate predictions of diameter and volume. The purpose of this study was to investigate the level of improvement that the incorporation of crown variables into taper equations for black pine (Pinus nigra J.F.Arnold subsp. pallasiana (Lamb.) Holmboe) gives to diameter and stem volume predictions. Linear and nonlinear crown variable functions were incorporated into a compatible volume and taper equation to evaluate their effect in model prediction accuracy. The inclusion of crown variables provided significantly different parameter estimates but only resulted in a modest reduction of fitting statistics for both diameter and volume with lower average bias and lower mean squared errors for all modified models, although the improvement in stem volume prediction was minimal. Based on the results, the improvement obtained by the inclusion of crown variables is not enough to justify the additional costs in measuring crown variables of standing trees for volume estimation.