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WOODSHED ANALYSIS Mad River Valley Towns

WOODSHED ANALYSIS Mad River Valley Towns. Analysis by Marc Lapin, Chris Rodgers, & David Brynn Winter/Spring 2009. Purpose. To model the forest landbase suitable for sustainable harvest of forest biomass, and to estimate low-quality wood production on that landbase. General Methods.

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WOODSHED ANALYSIS Mad River Valley Towns

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  1. WOODSHED ANALYSISMad River Valley Towns Analysis by Marc Lapin, Chris Rodgers, & David Brynn Winter/Spring 2009

  2. Purpose To model the forest landbase suitable for sustainable harvest of forest biomass, and to estimate low-quality wood production on that landbase

  3. General Methods • Determine forestland sustainability criterion that can be utilized for spatial modeling • Construct spatial model to evaluate the landscape • Calculate the low-quality wood growth on the suitable forest landbase by applying several forest growth estimates to the suitable acreage

  4. Sustainability CriteriaApplicable to Spatial Modeling Ecological criteria for sustainability refer to forest health, productive capacity, soil and water, biodiversity, and carbon and nutrient budgets

  5. Soils • Forestland Value Group Exclude two least productive groups, representing limited & very limited forestry potential (available from NRCS soils surveys) • Slope Exclude slopes >60% Separate slopes 30-60%, which may present sustainability/operability constraints

  6. Water Quality and Wetlands • Exclude water bodies and wetlands • Exclude 75’ buffered area surrounding all water and wetlands • Fragile and ‘Significant’ Natural Communities • Exclude all lands above 2,500’ elevation • No reliable spatial data for significant natural communities, therefore exclude 10% of landbase to account for such features as well as for the forest access road network

  7. Conserved Lands • Exclude all lands where timber extraction is legally prohibited • Separate publically owned lands from privately owned lands for information purposes • Conserved lands GIS layer, GAP Protection Level data utilized

  8. Suitable Forestlands Results • 81% forested • 75% of forestlands suitable = 55,860 acres • 91% of suitable landbase privately owned • 5% forested landbase legally protected from extraction • 10% subtraction leaves 50,270 acres available

  9. Excluded Lands by Criterion Percentages include ‘overlap’ among criteria • Water, wetlands & their buffers – 10% • Forestland value group – 14% • Elevation – 6% • Slopes >60% – 0.4% • Potentially unsuitable slopes – 15%

  10. MORETOWN • Large acreage (most of the town) of suitable private forest landbase • Moderate amount of 30-60% slopes • Very small area with conservation easements

  11. FAYSTON • Large acreage of suitable private forest landbase • Substantial areas with 30-60% slopes • Small percentage with conservation easements • Small amount suitable public lands

  12. WAITSFIELD • Moderate acreage of suitable private forest landbase • Small to moderate amount of 30-60% slopes • Small to moderate percentage with conservation easements • Small amount suitable public lands

  13. WARREN • Moderate to large acreage of suitable private forest landbase • Substantial amount of 30-60% slopes • Small percentage with conservation easements • Largest amount of suitable public lands, but perhaps slope constraints

  14. Tree Growth Per Year • Leak et al. (1987) – Northern Hardwoods modeling • Intensively managed – 1.7 green tons per acre • Unmanaged – 1.2 green tons per acre • Sherman (2007) – based on FIA plot data • Washington County – 2.9 green tons per acre • Frieswyk and Widman (2000) – based FIA plot data • 1.25 green tons per acre • Frank and Bjorkbom (1973) – Spruce-Fir modeling • Best case scenario – 1.25 green tons per acre

  15. Estimated Low-Quality Wood Amounts in green tons/year • Most conservative estimate = ~29,000 • Lowest growth rate, lowest amount low-quality • Very believable • Approximately 1.8 cords/person/year • Mid-range estimate = ~49,600 • Middle growth rate, middle amount low quality • Perhaps, with more intensive management • About 3 cords/person/year • High estimate = ~99,100 • Highest growth rate, highest amount low quality • Not supported by recent data

  16. Unanswered Questions • How much of the available and future wood in the woodshed is/will be low-quality wood whose ‘best’ use after harvest would be for burning? • What is the actual growth per year? • The models show substantial variation • Without intensive field data collection in a specific woodshed, we don’t know how reliable the estimates are for any actual landscape

  17. Where to Place Confidence? • Leak et al. model for unmanaged forests and recent FIA-based estimates coincide rather closely • Sherman growth estimates appear too high • A whole lot depends on management intensity, which depends on balancing numerous values, not merely maximizing biomass for burning • Landowner choices are, perhaps, the greatest unknown

  18. What to Continue Questioning • Can our forests provide us with large amounts of biomass for energy while continuing to provide the other ecosystem functions and services we expect and hope for? • Will landowners opt for more intensive management to strive for greater forest biomass? • As management proceeds over many decades, centuries, how much will the proportion of the low-quality wood supply diminish?

  19. Thank you!&Time for Questions

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