|Area:||Inventory and Planning|
|Sponsor:||Alberta-Pacific Forest Industries Inc.|
Object & Deliverables
The primary purpose of this project was to explore the dynamics of white spruce existence and distribution in the understory of forest stands as an aid to enhance mixed wood management. Predictive analysis was used to test the relationship between white spruce (Sw) understory density and the characteristics of the overstory.
The objectives included characterizing attributes of stands with and without conifer understories; spatial linking conifer understories to seed sources; quantifying potential relationships between overstory, understory, and seed source attributes; and exploring the potential for developing predictive algorithms for forecasting conifer understories.
The existence and distribution of coniferous understories were determined using leaf-off infrared air photos that were interpreted to enhance the Alberta Vegetation Inventory (AVI) information for selected forest management units (FMUs) within Alberta-Pacific Forest Industries Inc. forest management agreement (FMA) area. The attribute data includes overstory and understory descriptions of species, species composition, crown closure, height and stem density. This attribute set was used to determine the following: the overstory types that are most likely to have Sw understories; and overstory characteristics such as, height, age, and stem density that might affect the quantitative characteristics of Sw understories.
Stands were split into the following four groups: 1) Aspen; 2) Aspen-White Spruce; 3) White Spruce-Aspen; and 4) White Spruce.
Canopy species composition is an important attribute associated with occurrence and characteristics of Sw understory. The frequency of Sw understory is higher in pure aspen or aspen-leading stands when compared to Sw leading stands. When logistic regression models are compared with observed data, the predictive models appear to adequately simulate the patterns of Sw understory in aspen-Sw mixedwood. Although the exact density of Sw understory is very hard to predict, results from the Sw prediction at different levels, along with logistic regression, can be applied to mixedwood management practices.