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Simulating Fire Disturbance Impact Using Gridded Biome-BGC in Boreal Forests

This study demonstrates the use of the Gridded Biome-BGC model to explicitly simulate fire disturbances in boreal forests, particularly during the BOREAS project. We elucidate the modifications made to the Biome-BGC for fire disturbance simulation, integrating spatial and temporal data to generate gridded outputs. The research includes a comprehensive batch run using real fire mortality data and assesses various climate change scenarios, providing insights into the effects of fire and CO2 variability on forest dynamics.

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Simulating Fire Disturbance Impact Using Gridded Biome-BGC in Boreal Forests

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  1. Gridded Biome-BGC Simulation with Explicit Fire-disturbance Sinkyu Kang, John Kimball, Steve W. Running Numerical Terradynamic Simulation Group, School of Forestry, Univeristy of Montan

  2. Purpose Demonstrate Gridded Biome-BGC run in BOREAS. Illustrate Biome-BGC modification for explicit fire-disturbance simulation

  3. Process of Gridded BGC • Batch run of Biome-BGC combined with input and output module • Using IDL (Interactive Data Language) Spatial & temporal data INI, EPC, MET file for point Biome BGC run Batch run of point Biome BGC Generate gridded outputs

  4. Considering Explicit Fire-Disturbance Raw Data Size and location Before 1959: constant fire mortality After 1959: fire mortality from raw data

  5. Considering Explicit Fire-Disturbance Generate fire grid Year cell[i,j] annual fire file 83 84 85 86 87

  6. Considering Explicit Fire-Disturbance Modifed INI & EPC files 1.0 (DIM) multiplier for shortwave radiation CO2_CONTROL (keyword - do not remove) 1 (flag) 0=constant 1=vary with file 2=constant, file for Ndep 286.923 (ppm) constant atmospheric CO2 concentration kco21862.txt (file) annual variable CO2 filename FIRE_CONTROL (keyword - do not remove) 1 (flag) 0=constant fire mortality 1=vary with file fire-5-14.txt (file) annual variable fire mortality (year fire_mortality) SITE (keyword) start of site physical constants block Run Modified Biome-BGC ECOPHYS ENF-cool (wet conifer) 1 (flag) 1 = WOODY 0 = NON-WOODY ……………………………………………………. 0.005 (1/yr) annual whole-plant mortality fraction 0.005 (1/yr) mean annual fire mortality fraction 0.26 (1/yr) annual carbon fraction consumed by fire 1.5 (ratio) (ALLOCATION) new fine root C : new leaf C 1.1 (ratio) (ALLOCATION) new stem C : new leaf C

  7. ET (mm/y) & NPP (gC/m2/y) LAI (m2/m2) Daily fire mortality Constant fire mortality > 1959 < Explicit fire occurrence Internal fire-disturbance External fire-disturbance

  8. Modification of Biome-BGC • Biome-BGC v.411 • 47 source files • 8 header files • 2 library files • In this study, even this small change required • modification of 7 source files • modification of 4 header files • addition of a new subroutine source file

  9. Application to the Boreal Forest Biome Experimental Design Grid size (simulation unit): 66 columns and 60 rows Each simulation uses • identical land cover and soil property over the entire grid • identical spatial meteorological variable (1994~1996) Every simulation differs in • land cover types (DBF, Grass, DC, WC) • constant or varying ambient CO2 and internal or external fire-disturbance • Nine climate change scenario (control, 2oC, 20% precipitation) Total 108 cases of gridded Biome-BGC runs

  10. Land Cover 300km 660km

  11. Topography

  12. Climate (3-yr mean) Tmax Tmin Precipitation Radiation

  13. Sample Result 1 – Land cover DBF Grass DC WC

  14. Sample Result 2 – CO2 Difference Const. CO2 – Increasing CO2 WC, Const. CO2 WC, Increasing CO2

  15. Sample Result 3 - Fire Difference External fire – Increasing CO2 WC, Increasing CO2 WC, External fire

  16. Sample Result 4 – Climate Change PRCP*TEMP: PRCP(-1,0,+1), TEMP(-1,0,+1), EX: +1-1 (1.2*prcp & -2 of Temp.) 00 +10 -10 +1+1 +1-1 -1+1 -1-1 DBF, Const. CO2

  17. Climate Scenario Difference to Control (precipitation, temperature) (1,0)-(0,0) (-1,0)-(0,0) (1,1)-(0,0) (1,-1)-(0,0) (-1,1)-(0,0) (-1,-1)-(0,0)

  18. Future consideration • Combining Biome-BGC with an explicit routing hydrology model (DHSVM?) • Model Initialization Spin-up run: • initialize soil and vegetation state variable at steady-state condition • time consuming process Extrapolation from field or satellite measurement: • satellite-driven LAI  initialize vegetation carbon variables using allometry rules (Landsat & MODIS in watershed and regional scale) • field measurement  initialize soil variables using empirical relationships (ex. Soil depth – topographic index,White et al. 1988)

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