Abstract
We investigated the relationship of stem diameter to tree, site and stand characteristics for six major tree species (trembling aspen, white birch, balsam fir, lodgepole pine, black spruce, and white spruce) in Alberta (Canada) with data from Alberta Sustainable Resource Development Permanent Sample Plots. Using non-linear mixed effects modeling techniques, we developed models to estimate diameter at breast height using height, crown and stand attributes. Mixed effects models (with plot as subject) using height, crown area, and basal area of the larger trees explained on average 95% of the variation in diameter at breast height across the six species with a root mean square error of 2.0 cm (13.4% of mean diameter). Fixed effects models (without plot as subject) including the Natural Sub-Region (NSR) information explained on average 90% of the variation in diameter at breast height across the six species with a root mean square error equal to 2.8 cm (17.9% of mean diameter). Selected climate variables provided similar results to models with NSR information. The inclusion of nutrient regime and moisture regime did not significantly improve the predictive ability of these models.
Highlights
Accurate measurements of diameter and height are of critical importance to forest managers and practitioners in the decision-making process, since these tree attributes allow the indirect estimation of stem volume, biomass, and site index
Natural Sub-Region (NSR) information into the base models significantly improved the model fit for all six species (Table 5)
The base models were significantly improved by the addition of crown area and basal area of the larger trees
Summary
Accurate measurements of diameter and height are of critical importance to forest managers and practitioners in the decision-making process, since these tree attributes allow the indirect estimation of stem volume, biomass, and site index. The information collected using LiDAR has already been widely used to estimate: tree height, height and diameter distribution, leaf area index, biomass and crown attributes of individual trees [4,5,6,7,8]. The challenge in developing widely applicable height estimation models is to effectively represent the influence of tree-, stand-, site- and regional-level variables. Edaphic and climatic variables have been shown to improve the estimation of forest growth projections [13], and may influence the tree allometry, including height-diameter relationships
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