Keywords
FISC, Dinamica EGO, interactions between fire, land-use and climate
Start Date
16-9-2020 2:00 PM
End Date
16-9-2020 2:20 PM
Abstract
Wildfires, spurred by interactions between extreme weather events and land-use change, threaten to revert the capacity of Amazon forests to store carbon. To address the question of how climate and land-use change may affect fire regimes in Amazonia, we developed and applied a coupled ecosystem-fire model to quantify how committed regional drying and warming for the southern Brazilian Amazon would affect wildfires and associated greenhouse gas (GHG) emissions. Our fire model, named FISC (Fire Ignition, Spread and Carbon cycling) simulates monthly fire ignition and spread at a resolution of 25 ha for the Amazon region, while our ecosystem model simulates monthly forest carbon dynamics as a function of climatic variables. FISC, developed using Dinamica EGO platform, simulates fire propagation using a cellular automation approach. Fire spread occurs as a function of wind intensity and direction; fine fuel loads and microclimate within the forest estimated by the carbon cycling model; terrain features such as upslope direction, obstacles, and different land uses. The fire spread module was calibrated and validated using fire scar maps. Our validation shows that FISC captures the spatial-temporal variability in fire scars across the southern Amazon during the 2000s. Results indicate that projected climatic changes for the region will double the area burned by wildfires, affecting up to 16% of the region’s forests by 2050. Although these fires could emit as much as 23.5 Pg of CO2 equivalent to the atmosphere, avoiding new deforestation could cut burned area and total net fire emissions in half and help prevent fires escaping into protected areas and indigenous lands. Amazon fire regimes will intensify under climate scenarios representing both low and high GHG emissions, underscoring the need for novel mitigation measures. Aggressive regional efforts to eliminate ignition sources and increase wildfire suppression will be critical to conserve Amazon forests.
Modelling fire regimes in southern Amazonia
Wildfires, spurred by interactions between extreme weather events and land-use change, threaten to revert the capacity of Amazon forests to store carbon. To address the question of how climate and land-use change may affect fire regimes in Amazonia, we developed and applied a coupled ecosystem-fire model to quantify how committed regional drying and warming for the southern Brazilian Amazon would affect wildfires and associated greenhouse gas (GHG) emissions. Our fire model, named FISC (Fire Ignition, Spread and Carbon cycling) simulates monthly fire ignition and spread at a resolution of 25 ha for the Amazon region, while our ecosystem model simulates monthly forest carbon dynamics as a function of climatic variables. FISC, developed using Dinamica EGO platform, simulates fire propagation using a cellular automation approach. Fire spread occurs as a function of wind intensity and direction; fine fuel loads and microclimate within the forest estimated by the carbon cycling model; terrain features such as upslope direction, obstacles, and different land uses. The fire spread module was calibrated and validated using fire scar maps. Our validation shows that FISC captures the spatial-temporal variability in fire scars across the southern Amazon during the 2000s. Results indicate that projected climatic changes for the region will double the area burned by wildfires, affecting up to 16% of the region’s forests by 2050. Although these fires could emit as much as 23.5 Pg of CO2 equivalent to the atmosphere, avoiding new deforestation could cut burned area and total net fire emissions in half and help prevent fires escaping into protected areas and indigenous lands. Amazon fire regimes will intensify under climate scenarios representing both low and high GHG emissions, underscoring the need for novel mitigation measures. Aggressive regional efforts to eliminate ignition sources and increase wildfire suppression will be critical to conserve Amazon forests.
Stream and Session
false