Management Planning with Contemporary Harvest Scheduling Models

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Management Planning with Contemporary Harvest
Scheduling Models

• Alan R. Ek
• Professor and Head,
• Dept of Forest Resources
• University of Minnesota, St. Paul
• aek_at_umn.edu
• Presented to Rotation Length and Forest
  Management Symposium
• Madison, WI March 10, 2009

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The schedule

• Dynamics of forest change and timber supply in
  the region (WI MN, MI)
• Implications of change for management and
  outputsthe regulated forest
• Essentials of management and harvest scheduling
  what, why, how (and who)
• Examples of WI situation
• Synthesis

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Dynamics of forest change

• ? Post glacial forests
• ? Native American influence
• ? Forest Types
• -Northern Mixed forest
• pine, spruce, aspen, birch...
• -Southern Broadleaf forest
• oak, hickory, maple
• ? Early logging 1850 1930s
• ? Regrowth, restoration,
• ? Evolving forest industry and
• resource management
• ? Today
• Global forest based industry
• Sustainable forest management

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Northern Wisconsin 1912-1990s
1988
Yesforests do change!
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Change in WI Timberland acreage
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All SpeciesTimberland Acreage, WI
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Implications of Change

• Fluctuations in
• timber supply by species, size, quality
• investment potentials and investor interest
• income for landowners
• habitat within and across ownerships
• forest management costs

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Essentials of Harvest and management Scheduling
Models

• What? Yes! Harvest and management scheduling
  models
• Why?
• Develop much improved plans and operations as
  compared to simple regulation models and/or
  group grope approaches
• Provide a framework for guiding the planning
  process
• Facilitates incorporation of non timber
  considerations in the forest management situation
• Develop truly thoughtful and defensible plans
• Speed the planning process, especially for
  updates
• Allow sensitivity analysis on practices,
  constraints, and policies
• Compare alternative allowable harvest levels
• Consider alternative management investment
  strategies

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Planning as a management tool

• Some possible treatments / gains
• Site preparation
• Improved planting stock
• Early release from competition
• Pre-commercial thinning
• Commercial thinnings
• Final harvest
• Residual biomass harvest

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Planning as a management tool

• How? Optimization ModelsSpecialized algorithms
  for finding maxima and minima in complex resource
  allocation problems, e.g.,
• For say a 50 year planning period,
• the model chooses a set of stands to be treated,
  treatments to apply, and time periods for such
  applications,
• to maximize outputs ( or timber) compared to
  other alternatives,
• subject to constraints (e.g., limits or bounds on
  operational capabilities, timber flow, green up,
  location, habitat, etc.)

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Planning as a management tool

• Who?
• National and Global Companies
• Superior and Chippewa NF
• State of MN
• Minnesota counties (Interagency Info Coop)
• Nordic Countries
• New Zealand

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Planning as a management tool

• Models/Software
• Spectrum - USFS
• Habplan - NCASI
• Dual Plan DPSpace U of Minnesota
• Metla/JLP Finland
• FPS Western US

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Some WI Covertype Cases

• Problem areas
• Uneven distribution of acres by age class
• Reduced regeneration capacity by age
• Succession to other covertypes
• Forest health issues with aging
• Market fluctuations

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Example - Jack Pine
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Jack Pine Management
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Example - Red Pine
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Example - White pine
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Example - Black spruce
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Example - Tamarack
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Example - Northern white-cedar
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Oak-hickory group
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Example - Elm-ash-cottonwood group
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Example - Maple-beech-birch group
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Example - Paper birch
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Example - Aspen
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Aspen Management
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Harvesting Today
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Example of rotation age as a management question
that can be consider by scheduling modelsTrial
for WI Aspen for 100 yrsRotation age 30-100
years
Based on FACCS, a Forest Age Class Change
Simulator by A. Ek and G. Domke, U of Minnesota
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Trial for WI Aspen for 100 yrsRotation age
40-110 years
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Trial for WI Aspen for 100 yrsRotation age
50-120 years
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FACCS Model Rotation Age Trials for Aspen in WI
(100 yr period)Summary
ODT Oven dry tonsapproximately 1.2 cords
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Summary

• Forest planning is complex and requires forest
  planning model tools to achieve full
  effectiveness.
• Application of these tools to Wisconsin forest
  ownerships is appropriate and timely.
• Results of such model based planning applications
  is inclusive, defensible, and truly insightful
  planning that can avoid or mitigate many issues
  before they become problems and take advantage of
  opportunities for both ecological and economic
  interests.
• Go for it!
• Questions?

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References

• Ek, A. R. 2007. Strategies for Improving forest
  productivity in Minnesota. http//iic.gis.umn.edu/
  documents/forestproductivity.pdf
• G. M. Domke, A. R. Ek, M. A. Kilgore and A. J.
  David. 2008. Aspen in the Lake States A
  research review. NCASI Technical Bulletin No.
  955. Research Triangle Park, NC. 32p.
• Perry, C. H. and V. A. Everson. 2008.
  Wisconsins Forest Resources 2007. Res. Note.
  NRS-26. Newtown Square, PA USDA Forest Service,
  Northern Research Station. 4p.
• Remsoft? Inc. 2008. Remsoft Spatial Planning
  System 2008. Fredericton, NewBrunswick, Canada.
  
• Walters, D.K., A.R. Ek.1993. Whole Stand Yield
  and Density Equations for Fourteen Forest Types
  in Minnesota. Northern Journal of Applied
  Forestry, 10(2)75-85.
• Wisconsin DNR. Timber Harvest in Wisconsin.
  http//www.dnr.state.wi.us/forestry/um/pdf/report/
  TimberHarvestWisconsin.pdf

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NoteWI Aspen empirical yield/acre (ODT)from
2005 FIA Data