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IDF and ESSF Stand Structure: Using Stand Modelling to Identify Practices That Create and Maintain Desired Conditions. W. Klenner, I. Cameron, R. Walton, D. Lewis and D. Huggard Habitat Supply Modelling Workshop December 6, 2006. (1) Biologically, stand structure matters.
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IDF and ESSF Stand Structure:Using Stand Modelling to Identify Practices That Create and Maintain Desired Conditions W. Klenner, I. Cameron, R. Walton, D. Lewis and D. Huggard Habitat Supply Modelling Workshop December 6, 2006
(1) Biologically, stand structure matters. Why Model Stand Structure?? (2) Simultaneously track many structural indicators. (3) Track complex and often interacting managed [harvesting] and natural [e.g. spruce beetle] disturbances - models can be good accountants. (4) Explore the likely consequences of management actions before application. (5) Explore temporal consequences - the creation and maintenance of desired conditions. (6) Explicitly identify the assumptions and relationships that underlie an activity. (7) Extend the shelf life of old and/or injured field biologists.
Implications of Residual Stand Density on Understory Vegetation and Likely Timber Yields in an IDFdm Forest - examined tradeoff between stand density and indicators of understory vigor, stand structure and timber - used TASS (Tree and Stand Simulator) - pre-harvest conditions approximate a 130 year old stand - 10 residual density options examined
Managing IDF forests for a productive understory
Time Since Thinning IDF Crown Closure and Stand Density
Ground - Level Percent Above Canopy Light (PACL) and Crown Closure
Other Indicators of Stand Structure Base of Live Crown
Timber Productivity
Developing Stand Management Prescriptions to Maintain Abundant Lichen Forage for Mountain Caribou
Conceptual Representation of Canopy Structure and Light Conditions in an ESSF Stand
Effect of Selection Harvest on Canopy Structure, Light Conditions and Lichen Abundance in an ESSF Stand
Summary 1. Before management plans involving complex ecological - commodity tradeoffs are implemented, the short- and long-term likely consequences should be modelled as a decision support exercise to verify expectations and assumptions. 2. Models should help identify what we know, what we don’t and what we are uncertain about. They should complement, not replace field research. 3. Grandma was right….the devil is in the details! Remember... GIN → → GOUT