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 Near Term Deliverables Long Term Plans
Courtesy of Perry et al. In Prep Atlas of US Forests Forest Carbon Cycle in Context of US Emissions
86%≈15% Why inventory?
That 15% Might Get Larger
Past, Current, and Future C
Inform Policy At Various Scales Vs. Biogenic emissions Post-2020 Emission Targets National Forest NEPA
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)
Differences in dead tree carbon 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 Decay class 5 Decay class 1 Decay class 2 Decay class 3 Decay class 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 Harmon et al NRS-RP-15 Domke et al CBM Woodall et al Forestry
Downed Dead Wood Woodall et al FEM Domke et al PLoS One
Imputing Carbon Density to Landscape Presented in 2014 NGHGI 3 rd Most Downloaded Research Dataset in FS: RDS Most Accessed Article on Journal Website Wilson et al CBM
Modeling of Dead Wood Residency Woodall et al FEM; Russell et al Ecol. Model.; Russell et al Ecosystems
Climate and Dead Wood? Russell et al. In review
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
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
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
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
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
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 ( ) P2 plots = 4,859
Future Vision: Synergy Attribution Land Use Change Disaggregation Planned Improvements AK/HI Reduce uncertainty Alaska Land Use Change Forecasting Farm Bill: “Report information on renewable biomass supplies and carbon stocks at the local, State, regional, and national level, including by ownership type”
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)
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
Most Everything Feeds into Biomass/Carbon ICE LCMS National Vol/Biomass Study TPO/Utilization Interior AK Woodlands P2+/P3
Questions?