1. Forest Growth Model and Data Linkage Issues Limei Ran Carolina Environmental Program UNC Steve McNulty Jennifer Moore Myers Southern Global Change Program, USDA FS

2. PEcon Model Use the PEcon Model developed at SGCP to simulate forest growth and fire harvesting from 1990 to 2050. Use the PEcon Model developed at SGCP to simulate forest growth and fire harvesting from 1990 to 2050. The PEcon model is a coupled computer modeling system which includes: The PEcon model is a coupled computer modeling system which includes: 1. Economic model that simulates forest resources and timber supply (SRTS) 2. Ecological process model of forest productivity, species composition, and hydrology (PnET II) from the FIA plot to the regional scale. The window-based system is implemented in Microsoft Visual Basic 6 and SQL Server 7. The window-based system is implemented in Microsoft Visual Basic 6 and SQL Server 7. The system was installed on a PC at CEP about a month ago. The system was installed on a PC at CEP about a month ago.

3. PEcon Testing and Code Modifications Understand the codes and run tests using existing PEcon data base tables (on going). Understand the codes and run tests using existing PEcon data base tables (on going). Modify codes to fit our project. Modify codes to fit our project. Change forest productivity output from computed FIA plot level to county-level. Change forest productivity output from computed FIA plot level to county-level. Change forest productivity output. Change forest productivity output. Current PEcon output only has wood NPP. Current PEcon output only has wood NPP. Need all PnET II model output: foliar NPP, wood NPP, root NPP, and runoff. Need all PnET II model output: foliar NPP, wood NPP, root NPP, and runoff. Modify codes with climate data input. Modify codes with climate data input. Current model uses historic climate before 1994 and Hadley model output from 1994. Current model uses historic climate before 1994 and Hadley model output from 1994. This project intends to use CCSM climate data for future years and available historic climate data such as NCEP North American Regional Reanalysis (32km, 25 years). This project intends to use CCSM climate data for future years and available historic climate data such as NCEP North American Regional Reanalysis (32km, 25 years).

4. Model input data preparation Study area: 11 southeastern states. Study area: 11 southeastern states. Use SGCP PEcon data base tables with some updates related to cell information and climate. Use SGCP PEcon data base tables with some updates related to cell information and climate. Update site information table from VEMAP grid cell to county cell. Update site information table from VEMAP grid cell to county cell. location, elevation, water holding capacity, cell area, and land are location, elevation, water holding capacity, cell area, and land are Update spatial table which includes plot, survey unit, state, county, and model cell. Update spatial table which includes plot, survey unit, state, county, and model cell. Update climate tables to new climate data. Update climate tables to new climate data. Prepare harvesting tables to simulate fire harvesting in the future years. Prepare harvesting tables to simulate fire harvesting in the future years.

5. Model Simulations Run and test the modified model. Run and test the modified model. Validate the model output with FIA data and other regional biomass data. Validate the model output with FIA data and other regional biomass data. Compare biomass output with the biomass computed from FIA data for selected states. Compare biomass output with the biomass computed from FIA data for selected states. Compare biomass output with the biomass data generated from satellite images such as FIA Remote Sensing Band biomass map data. Compare biomass output with the biomass data generated from satellite images such as FIA Remote Sensing Band biomass map data.

6. Linkage with BEIS3 Issues BEIS3 computes biogenic emission rates by county based on area weighted land use specific emission factors using BELD3 data. Leaf area and foliar biomass per area are computed within BEIS3. BEIS3 computes biogenic emission rates by county based on area weighted land use specific emission factors using BELD3 data. Leaf area and foliar biomass per area are computed within BEIS3. BELD3 land cover data in the 37 eastern states came from EWFIADB (1km, 193 forest species). BELD3 land cover data in the 37 eastern states came from EWFIADB (1km, 193 forest species). SGCP PnET model will output monthly cumulative and incremental biomass (county, 203 forest species). SGCP PnET model will output monthly cumulative and incremental biomass (county, 203 forest species). Issue: how to compute biogenic emissions from county-based biomass for the 203 forest species as modeled by PnET II? Issue: how to compute biogenic emissions from county-based biomass for the 203 forest species as modeled by PnET II? Modify PnET Model to output LAI. Modify PnET Model to output LAI. Modify BEIS3 model to take LAI and foliar biomass from PnET for forest species in emission rate computation. Modify BEIS3 model to take LAI and foliar biomass from PnET for forest species in emission rate computation.

7. Linkage with BlueSky Issues BlueSky uses a fuel load table containing live fuel load and DWM with different diameter sizes (1km, forest species) to estimate fire emissions. BlueSky uses a fuel load table containing live fuel load and DWM with different diameter sizes (1km, forest species) to estimate fire emissions. Since 2001 FIA has DWM inventory for estimating DWM components: coarse woody, fine woody, litter, herb/shrubs, slash, duff, and fuelbed depth. Since 2001 FIA has DWM inventory for estimating DWM components: coarse woody, fine woody, litter, herb/shrubs, slash, duff, and fuelbed depth. Most research in DWM component prediction is remote-sensed image or regression-based analysis. Most research in DWM component prediction is remote-sensed image or regression-based analysis. No one has done DWM prediction based on biomass because DWM is more related to stand disturbances and climate rather than its ability to produce biomass. No one has done DWM prediction based on biomass because DWM is more related to stand disturbances and climate rather than its ability to produce biomass.

8. Linkage with BlueSky Questions How to compute DWM in the future forest canopy as modeled by PnET? How to compute DWM in the future forest canopy as modeled by PnET? Build a good prediction model for county-based DWM based on FIA DWM, PnET biomass output, other FIA variables, site variables, and climate data? Build a good prediction model for county-based DWM based on FIA DWM, PnET biomass output, other FIA variables, site variables, and climate data? If not, what other models should we use to project DWM? If not, what other models should we use to project DWM? How to convert county-based biomass to 1-km fuel loads with different diameter sizes for a species? How to convert county-based biomass to 1-km fuel loads with different diameter sizes for a species?