Name: Percent Change in Forest Carbon Stocks (2020-2070, RCP 8.5-SSP-2)
Display Field: NAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data layer provides baseline estimates and future projections of carbon by county. Baseline carbon estimates for 2020 were derived by the FIA carbon team based on the most recent inventories for each state. Projections based on the baseline estimates were developed by the Resources Planning Act (https://www.fs.usda.gov/research/inventory/rpaa) team where forest area and total carbon estimates were provided for the year 2070, RCP 8.5, SSP2 (for information on RPA models and future scenarios see Langner et al. 2020: https://doi.org/10.2737/RMRS-GTR-412). Projections include the effects of land use change, climate, socioeconomics, timber harvest, fire, other disturbance, and forest growth. Counties were clipped to National Forest boundaries for display purposes. Scenario = RCP8.5-SSP2 combination (high warming, moderate growth), mean/min/max of 5 climate models used in RPA Assessment; another three RCP-SSP combinations are available from the information source. This uses the following five climate models: Least Warm-MRI-CGCM3; Hot-HadGEM2-ES; Dry-IPSL-CM5A-MR; Wet-CNRM-CM5; Middle-NorESM1-M (https://www.fs.usda.gov/research/treesearch/60113) Learn more at: U.S. Department of Agriculture, Forest Service. 2023. Future of America’s Forest and Rangelands: Forest Service 2020 Resources Planning Act Assessment. Gen. Tech. Rep. WO-102. Washington, DC. [in press] https://doi.org/10.2737/WO-GTR-102. Spatial Extent: CONUSUnits: Percent change in C stocks
Name: Percent Change in Forest Carbon Stocks (2020-2070, RCP 4.5-SSP-1)
Display Field: NAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data layer provides baseline estimates and future projections of carbon by county. Baseline carbon estimates for 2020 were derived by the FIA carbon team based on the most recent inventories for each state. Projections based on the baseline estimates were developed by the Resources Planning Act (https://www.fs.usda.gov/research/inventory/rpaa) team where forest area and total carbon estimates were provided for the year 2070, RCP 4.5, SSP1 (for information on RPA models and future scenarios see Langner et al. 2020: https://doi.org/10.2737/RMRS-GTR-412). Projections include the effects of land use change, climate, socioeconomics, timber harvest, fire, other disturbance, and forest growth. Counties were clipped to National Forest boundaries for display purposes. Scenario = RCP4.5-SSP1 combination (low warming, moderate growth), mean/min/max of 5 climate models used in RPA Assessment; another three RCP-SSP combinations are available from the information source. This uses the following five climate models: Least Warm-MRI-CGCM3; Hot-HadGEM2-ES; Dry-IPSL-CM5A-MR; Wet-CNRM-CM5; Middle-NorESM1-M (https://www.fs.usda.gov/research/treesearch/60113) Learn more at: U.S. Department of Agriculture, Forest Service. 2023. Future of America’s Forest and Rangelands: Forest Service 2020 Resources Planning Act Assessment. Gen. Tech. Rep. WO-102. Washington, DC. [in press] https://doi.org/10.2737/WO-GTR-102. Spatial Extent: CONUSUnits: Percent change in C stocks
Name: Percent Change in Forest Carbon Stocks Sum by Admin Forest - (2020-2070, RCP 8.5-SSP-2)
Display Field: FORESTNAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data layer provides baseline estimates and future projections of carbon by forest. Baseline carbon estimates for 2020 were derived by the FIA carbon team based on the most recent inventories for each state. Projections based on the baseline estimates were developed by the Resources Planning Act (https://www.fs.usda.gov/research/inventory/rpaa) team where forest area and total carbon estimates were provided for the year 2070, RCP 8.5, SSP2 (for information on RPA models and future scenarios see Langner et al. 2020: https://doi.org/10.2737/RMRS-GTR-412). Projections include the effects of land use change, climate, socioeconomics, timber harvest, fire, other disturbance, and forest growth. Counties were clipped to National Forest boundaries for display purposes. Scenario = RCP8.5-SSP2 combination (high warming, moderate growth), mean/min/max of 5 climate models used in RPA Assessment; another three RCP-SSP combinations are available from the information source. This uses the following five climate models: Least Warm-MRI-CGCM3; Hot-HadGEM2-ES; Dry-IPSL-CM5A-MR; Wet-CNRM-CM5; Middle-NorESM1-M (https://www.fs.usda.gov/research/treesearch/60113) Learn more at: U.S. Department of Agriculture, Forest Service. 2023. Future of America’s Forest and Rangelands: Forest Service 2020 Resources Planning Act Assessment. Gen. Tech. Rep. WO-102. Washington, DC. [in press] https://doi.org/10.2737/WO-GTR-102. Spatial Extent: CONUSUnits: Percent change in C stocks
Name: Percent Change in Forest Carbon Stocks Sum by Admin Forest - (2020-2070, RCP 4.5-SSP-1)
Display Field: FORESTNAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data layer provides baseline estimates and future projections of carbon by forest. Baseline carbon estimates for 2020 were derived by the FIA carbon team based on the most recent inventories for each state. Projections based on the baseline estimates were developed by the Resources Planning Act (https://www.fs.usda.gov/research/inventory/rpaa) team where forest area and total carbon estimates were provided for the year 2070, RCP 4.5, SSP1 (for information on RPA models and future scenarios see Langner et al. 2020: https://doi.org/10.2737/RMRS-GTR-412). Projections include the effects of land use change, climate, socioeconomics, timber harvest, fire, other disturbance, and forest growth. Counties were clipped to National Forest boundaries for display purposes. Scenario = RCP4.5-SSP1 combination (low warming, moderate growth), mean/min/max of 5 climate models used in RPA Assessment; another three RCP-SSP combinations are available from the information source. This uses the following five climate models: Least Warm-MRI-CGCM3; Hot-HadGEM2-ES; Dry-IPSL-CM5A-MR; Wet-CNRM-CM5; Middle-NorESM1-M (https://www.fs.usda.gov/research/treesearch/60113) Learn more at: U.S. Department of Agriculture, Forest Service. 2023. Future of America’s Forest and Rangelands: Forest Service 2020 Resources Planning Act Assessment. Gen. Tech. Rep. WO-102. Washington, DC. [in press] https://doi.org/10.2737/WO-GTR-102. Spatial Extent: CONUSUnits: Percent change in C stocks
Name: Carbon Density (2023) and Percent Carbon Stock Change (2005-2023)
Display Field: FORESTNAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data layer provides estimates of carbon density in 2023 and the percent change in carbon stocks from 2005 to 2023 for the sum of five forest carbon pools (aboveground biomass, belowground biomass, soil organic carbon, litter, dead wood) for each National Forest System unit based on information from the FIA program - https://www.fs.usda.gov/sites/default/files/fs_media/fs_document/GHG-emissions-removals-2022.pdf. These estimates were used to make maps portraying trends in carbon stock change and carbon density by joining estimates by National Forest to the Forest Service administrative boundary layer.Spatial Extent: NFS system landsUnits: Total forest C stocks by year (Tg), C pools (%), C stock change (Tg/yr), average C stock density by year (Mg/ha), HWP C storage over time (Tg) [regional summary], % forest disturbance by year, C loss by disturbance type over time (Mg/ha), % reduction in non-soil C by disturbance, stand age distribution in 2011, NPP-stand age curves (Mg C/ha/yr), accumulated C over time (Tg).
Copyright Text: USDA Forest Service: Forest Inventory and Analysis (FIA)
Unique Value Renderer: Field 1: C_Desc Field 2: N/A Field 3: N/A Field Delimiter: ; Default Symbol:
N/A
Default Label: N/A UniqueValueInfos:
Value: High Carbon Density, Greater Than 10% Increase in Carbon Stock Label: High Carbon Density, Greater Than 10% Increase in Carbon Stocks Description: N/A Symbol:
Value: High Carbon Density, Less Than 10% Increase in Carbon Stock Label: High Carbon Density, Less Than 10% Increase in Carbon Stocks Description: N/A Symbol:
Value: High Carbon Density, Less Than 10% Decrease in Carbon Stock Label: High Carbon Density, Less Than 10% Decrease in Carbon Stocks Description: N/A Symbol:
Value: High Carbon Density, Greater Than 10% Decrease in Carbon Stock Label: High Carbon Density, Greater Than 10% Decrease in Carbon Stocks Description: N/A Symbol:
Value: Low Carbon Density, Less Than 10% Increase in Carbon Stock Label: Low Carbon Density, Less Than 10% Increase in Carbon Stocks Description: N/A Symbol:
Value: Low Carbon Density, Less Than 10% Decrease in Carbon Stock Label: Low Carbon Density, Less Than 10% Decrease in Carbon Stocks Description: N/A Symbol:
Name: Ratio of Live Aboveground Carbon to Dead (2023)
Display Field: FORESTNAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data layer provides annualized estimates (1990-2023) for seven forest carbon pools (aboveground live, belowground live, soil organic carbon, forest floor, down dead wood, standing dead trees, understory vegetation) for each National Forest System unit based on information from the FIA program and the Carbon Calculation Tool (CCT) - https://www.nrs.fs.usda.gov/pubs/2394 . These estimates were used to make maps portraying trends in live to dead tree ratios by joining CCT estimates to the Forest Service administrative boundary layer. Spatial Extent: NFS system landsUnits: Total forest C stocks by year (Tg), C pools (%), C stock change (Tg/yr), average C stock density by year (Mg/ha), HWP C storage over time (Tg) [regional summary], % forest disturbance by year, C loss by disturbance type over time (Mg/ha), % reduction in non-soil C by disturbance, stand age distribution in 2011, NPP-stand age curves (Mg C/ha/yr), accumulated C over time (Tg).
Copyright Text: USDA Forest Service: Forest Inventory and Analysis (FIA)