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The US National Greenhouse Gas Inventory of Forests: Where We’ve Been and Where We’re Going

The US National Greenhouse Gas Inventory of Forests: Where We’ve Been and Where We’re Going. Christopher W. Woodall with Domke, Smith, Coulston, Healey, Gray U.S. Forest Service Forest Inventory and Analysis St. Paul, MN . Outline. Context Recent Science/Improvements

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The US National Greenhouse Gas Inventory of Forests: Where We’ve Been and Where We’re Going

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  1. The US National Greenhouse Gas Inventory of Forests: Where We’ve Been and Where We’re Going Christopher W. Woodall with Domke, Smith, Coulston, Healey, Gray U.S. Forest Service Forest Inventory and Analysis St. Paul, MN

  2. Outline • Context • Recent Science/Improvements • Near Term Deliverables • Long Term Plans

  3. Forest Carbon Cycle in Context of US Emissions Courtesy of Perry et al. In Prep Atlas of US Forests

  4. Why inventory? 86% ≈15%

  5. That 15% Might Get Larger

  6. Past, Current, and Future C

  7. Inform Policy At Various Scales Post-2020 Emission Targets National Forest NEPA Biogenic emissions Vs.

  8. Recent Enhancements of FIA’s Carbon Inventory • CRM adoption • Standing dead C estimation overhaul • Incorporation of P3 downed dead wood C • P2+ Inventories (i.e., greater sample intensity) • National utilization (i.e., life cycle analysis) • Dead wood residence time research • C density imputation (i.e., Wilson’s maps)

  9. Differences in dead tree carbon Harmon et al. 2011 NRS-RP-15 Domke et al. 2011 CBM Woodall et al. 2012 Forestry Decay class 1 Decay class 2 Decay class 3 Decay class 4 Decay class 5 Method CRM: CRM+DRF: CRM+DRF+SLA: 91.2 kg C 89.2 kg C 87.9 kg C 74.8 kg C 61.2 kg C 49.1 kg C 29.4 kg C 19.6 kg C 12.1 kg C 2.4 kg C 1.7 kg C 1.0 kg C 0.4 kg C 0.3 kg C 0.2 kg C

  10. Downed Dead Wood Woodall et al. 2013 FEM Domke et al. 2013 PLoS One

  11. Imputing Carbon Density to Landscape • Presented in 2014 NGHGI • 3rd Most Downloaded Research Dataset in FS:RDS-2013-0004 • Most Accessed Article on Journal Website Wilson et al. 2013. CBM

  12. Modeling of Dead Wood Residency Woodall et al. 2012 FEM; Russell et al. 2013. Ecol. Model.; Russell et al. 2014. Ecosystems

  13. Climate and Dead Wood? Russell et al. In review

  14. Near Term Deliverables • Carbon estimates from P2+/P3 Vegetation plots • New delineation of “managed” forest land in AK • Refined woodland vs forestland delineation • Forest floor C estimates from P3 data • Sources of stock estimation uncertainty

  15. Understory vegetation • Includes seedlings, shrubs, grasses, and forbs • Formerly: Function of forest type and overstory size (based on Birdsey 1996), See EPA Annex 3.12 • Cover and height by growth form “scales” estimates of maximum carbon Russell et al. In Revision Forestry

  16. Adding AK Forest to NGHGI • Per IPCC guidance…only forest potentially impacted by humans included in inventory • AK forests along transport corridors or in mining/gas areas Ogle et al. In Prep

  17. Woodlands vs Forest land • Beyond inventorying forests: woodlands and urban areas • Delineation based on maximum attainable height in situ (5m threshold) • ≈50 million acres Coulston et al. In Prep

  18. Forest Floor Carbon • Primary Goal: Update Smith and Heath (2002) models used in FIADB and NGHGI using extensive P3 observations • Progress: Initial modeling complete…integrate updated models in 2015 NGHGI

  19. Sources of Uncertainty • Objectives • Evaluate alternative estimation methods in DDW C • Quantify total uncertainty • Sources of Uncertainty • Measurement • Sampling • Model selection • Model parameter • Initial Results • Differences among methods may range up to 150% • Oregon (2001-2010) • P2 plots = 4,859

  20. Future Vision: Synergy Farm Bill: “Report information on renewable biomass supplies and carbon stocks at the local, State, regional, and national level, including by ownership type” • Attribution • Land Use Change • Disaggregation • Planned Improvements • AK/HI • Reduce uncertainty • Alaska • Land Use Change • Forecasting

  21. Increased Precision, Refined Data Distribution, and Application of RS/Biometrical Science • P2+ of Non-Live Tree Pools • Increased P2 Sample Intensity/Reduced Cycle Length • Continued Incorporation of Biomass/C Attributes into Online Tools • Consistent/Timely TPO/Utilization Information • Improved biometrics: forest floor, soils, understory vegetation, belowground • National Volume Biomass Study • Leverage Remote Sensing Technologies (e.g., ICE, LCMS)

  22. Improving Change Detection and 1990-Present Baselines • NASA Grant: Carbon Monitoring Systems • National biomass mapping based on LiDAR and FIA network • Landsat change detection informs attribution of C to disturbance

  23. National Vol/Biomass Study Most Everything Feeds into Biomass/Carbon ICE Interior AK P2+/P3 LCMS Woodlands TPO/Utilization

  24. Questions?

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