Canadian Forest Service Publications
Ecosite-based predictive modeling of black spruce (Picea mariana) wood quality attributes in boreal Ontario. 2014. Pokharel, B.; Dech, J.P.; Groot, A.; Pitt, D. Canadian Journal of Forest Research 44:465-475.
Issued by: Great Lakes Forestry Centre
Catalog ID: 35926
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Enhanced forest resources inventory systems delineate and define polygons based on fundamental ecological units such as ecosites, which are standard combinations of vegetation and substrate types. Our study objective was to model wood quality characteristics of individual black spruce (Picea mariana (Mill.) B.S.P.) trees across a representative boreal forest landscape in northeastern Ontario, Canada, based on relationships to ecosite and other stand-level variables. A total of 127 large (12 mm) increment core samples were extracted at breast height from dominant or co-dominant black spruce trees in forest stands representing a gradient from dry sandy to wet mineral and organic ecosites. Sample cores were prepared, processed, and analyzed using standard SilviScan protocols. Hierarchical classification models were then fitted using Random Forests to predict density and latewood percentage for black spruce stems at a reference age of 50 years. These models each explained over 32% of variance, with estimated root mean squared errors of 40.4 kg·m−3 and 5.6% for density and latewood percentage, respectively. Among tree-, site-, and stand-level covariates, ecosite group was the most important predictive variable. Knowledge of ecosite – wood quality relationships could support efficient planning for black spruce management by including an indication of potential use as a modeled variable in a forest inventory system.
Plain Language Summary
We wanted to model wood quality characteristics of individual black spruce trees in relation to their ecosite. Enhanced forest resources inventory systems delineate ecosites, which are standard combinations of vegetation and substrate types. Beneficial traits of softwood fibre include high density and long fibre length. Recently, emphasis has been placed on identifying and quantifying this fibre quality advantage as part of an overall value chain optimization in the Canadian forest sector. We found ecosite group was the most important predictive variable for density and latewood percentage. Knowledge of ecosite – wood quality relationships could support more efficient planning for black spruce management by including fibre qualities in the forest inventory system.