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Comparison of sensitivity of landscape- fire-succession models to variation in terrain, fuel pattern...
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Comparison of sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern and climate
GCTE Task 2.2.2
Relationships between Global Change and Fire Effects at Landscape Scales
ContributorsGeoff Cary Australian National UniversityRobert Keane USDA Forest ServiceRobert Gardner Appalachian Laboratory, U. Maryland Sandra Lavorel Université Joseph Fourier, FranceMike Flannigan Canadian Forest ServiceIan Davies Australian National UniversityChao Li Canadian Forest ServiceJim Lenihan USDA Forest ServiceScott Rupp University of AlaskaFlorent Mouillot Carnegie Inst. of Washington, Stanford
Context
• Interactions between fire, climate and vegetation strongly influence landscape dynamics
• Simulation models are a critical tool for understanding these dynamics
• There has never been a uniform comparison that objectively evaluates model behaviour
Context
• Inherent difficulties in comparing models that were developed for a variety of purposes:
• Difficulty in obtaining validation data
• Difficulty in removing bias from the context in which the model was originally developed
Approach
• Unique approach to resolving these difficulties
• Standardise the variation in terrain, fuel pattern and climate
• Compare the sensitivity of model output to variation in terrain, fuel pattern and climate (i.e. not validation)
Models and native landscapes
EMBYR Yellowstone NP
FIRESCAPE South-east Australia
LAMOS-DS Generic (Corsica)
LANDSUM North-west US
SEM-LAND West-central Alberta
Models and native landscapes
• Lattice models
• Link fire ignition, fire spread, succession and fire effects
• Large landscapes, long duration
• Represent a variation in LFSM formulation
Experimental design
Treatment Levels Replicates
Terrain Flat 1 map/levelRollingMountainous
Fuel clumping Fine 10 maps/levelCoarse
Climate Observed 10 single yearsWarmer & wetter /levelWarmer & Drier
Terrain
Valley
Mid slope
Peak
50 km
Elevation range
Flat 1250 m
Rolling 625 – 1875 m
Mts 0 – 2500 m
Landscape position
Fuel clumping
Low
Moderate
High
50 km
Fine25 ha clumps
Fuel loads
Coarse625 ha clumps
Weather – Glacier National Park
1
1.5
2
2.5
3
9 10 11 12 13 14 15
Average daily maximum T (oC)
Ave
rage
dai
ly p
pt (
mm
)
weather repsall years
Climate scenarios
Temperature Precipitation
Warmer / Wetter + 3.6 oC x 1.2
Warmer/ + 3.6 oC x 0.8 Drier
Replication and simulations
Terrain (3 levels) 1 map / levelFuel clumping (2 levels) 10 maps / levelClimate (3 levels) 10 single years / level
3 x 2 x 10 x 3 x 10 = 1800 single year simulations / model
• Fires affected fuel load/age• Vegetation succession “removed”
Analysis
• Sensitivity of ln (area burned) to
TerrainFuel patternClimate changeInter-annual variation in climate
… and their interactions
• Variance in area burned explained (r2) by factors and interactions amongst them
• determined from fully factorial GLM (SAS)
Results
• Variation in climate explained considerable total variance for some models
Model Weather replicate r2
EMBYR 0.33*
FIRESCAPE 0.09*
LAMOS-DS 0.04*
LANDSUM 0.33*
SEM-LAND 0.54*
Climate
• Climate change explained considerable total variance in area burned for most models
Model Climate r2 Effect
EMBYR 0.03* (0.04) WW < WD = OB
FIRESCAPE 0.42* (0.46) OB < WW = WD
LAMOS-DS 0.28* (0.29) OB < WW = WD
LANDSUM 0.18* (0.27) OB < WW < WD
SEM-LAND 0.37* (0.81) OB < WW < WD
Fuel
• Fuel explained considerable total variance in area burned for EMBYR
Model Fuel r2 Effect
EMBYR 0.21* (0.32) Fine < Coarse
FIRESCAPE 0.02* Fine < Coarse
LAMOS-DS 0.00
LANDSUM 0.00* Fine < Coarse
SEM-LAND 0.01
Terrain
• Terrain explained considerable total variance in area burned for FIRESCAPE
Model Terrain r2 Effect
EMBYR 0.00FIRESCAPE 0.29* (0.32) Flat < Rolling < Mountainous
LAMOS-DS 0.00
LANDSUM 0.00
SEM-LAND 0.00
SummarySource No. models where: r2 > 5% Pr > F (0.001)
Terrain 1 1Fuel 1 4Terrain * fuelWeather replicate 4 5Terrain * weather replicateFuel * weather replicateTerrain * fuel * weather replicateClimate 4 5Terrain * climateFuel * climateTerrain * fuel * climateClimate * weather replicate 3 5Terrain * climate * weather replicateFuel * climate * weather replicateTerrain * fuel * climate * weather replicate
Conclusion
• Models largely sensitive to annual variability in weather
• Important to understand changes in climate variability
• Importance might diminish with particular changes in climate
Conclusion
• Models generally more sensitive to climate than fuel pattern or terrain
• Warmer/wetter and warmer/drier climates result in significant increases in area burned
• More important to understand climate trends and annual variability in weather, than fuel pattern or terrain, in explaining variation in area burned at the landscape scale
Conclusion
• Individual models sensitive to fuel pattern and weather because key processes represented in them.