Canadian Forest Service Publications
Pinus banksiana (Picea mariana) / Kalmia angustifolium (Rhododendron groenlandicum) / Cladina spp. Jack Pine (Black Spruce) / Sheep Laurel (Common Labrador Tea) / Reindeer Lichens. 2016. Baldwin, K.B.; Chapman, K. ; Saucer, J.-P. Great Lakes Forestry Centre, Sault Ste. Marie, Ontario. Association CNVC00201. 10p.
Issued by: Great Lakes Forestry Centre
Catalog ID: 37522
Availability: PDF (download)
Plain Language Summary
The Canadian National Vegetation Classification (CNVC) is an ecological classification of natural and semi-natural Canadian vegetation. The classification is a hierarchical taxonomy, describing vegetation conditions at different levels of generalization from global to local. The purpose of the CNVC is to act as a “dictionary” of vegetation units with standardized names, specific definitions, and factsheet descriptions. All products will be published on the CNVC website (cnvc-cnvc.ca). Natural Resources Canada – CFS (GLFC) is leading the development of the forest and woodland component of the CNVC. Factsheets for CNVC (CFEC) forest types are being published in 2 series (English & French), using standardized templates and terminological conventions. Each factsheet contains information on vegetation and environmental characteristics of the type, as well as geographic distributions within Canada and linkages to similar provincial classifications that are used for forest management purposes. The CNVC provides a consistent framework for applying ecological knowledge of Canadian forests to land management, research, monitoring and reporting activities. It helps to establish Canada as a world leader in the use of ecosystem-based information for sustainable forest management, including both timber and non-timber values. A hierarchical classification is essential for relating ecological information between local, regional, national and international scales. The classification enhances the interpretive value of spatial information products (e.g., the National Forest Inventory) by linking them to ground-derived ecological attributes.