Journal
FORESTRY CHRONICLE
Volume 86, Issue 4, Pages 511-519Publisher
CANADIAN INST FORESTRY
DOI: 10.5558/tfc86511-4
Keywords
boreal forest; forest classification; forest dynamics; stand structure; silviculture
Categories
Funding
- NSERC-Universite Laval Industrial Research Chair in Silviculture and Wildlife
- National Sciences and Engineering Research Council of Canada
- Canada Economic Development
- Fondation de la faune du Quebec
- Abitibi Bowater Inc.
- Kruger Inc.
- Produits forestiers Arbec Inc.
- Gestion Remabec Inc.
- FPInnovations
- Ministere des Ressources naturelles et de la Faune du Quebec
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In the North American boreal forest, the adoption of forest ecosystem management strategies usually increases the number of forest stands to be treated with irregular or uneven-aged silvicultural systems. However, it is difficult to properly target the stands most appropriate for partial cut treatments in remote areas where road access is limited, because current inventory data do not include an assessment of key stand characteristics for silvicultural prescriptions, such as the abundance of small stems in the understory. In this study, we present a forest classification performed using classification and ordination methods, based on ground-measured structural and compositional stand characteristics, in a region of eastern Quebec, Canada. This classification resulted in six forest types, which range in composition and structure from relatively regular post-fire stands dominated by black spruce (Picea mariana) to relatively irregular stands co-dominated by balsam fir (Abies balsamea) and black spruce. This classification was linked with cartographic information currently available to forest managers. Information from a fine-scale forest map predicted slightly better the presence of forest types with irregular stand structures compared with a coarse-scale forest map complemented with a fire map. Thus, areas most suitable for the implementation of uneven-aged silvicultural systems can be roughly delineated from existing cartographic information, which will facilitate their integration into large-scale and long-term forest management plans.
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