The Land Use and Carbon Scenario Simulator (LUCAS) model was used to develop a baseline carbon (C) budget for the Great Dismal Swamp, VA., using an annualized Stock-Flow approach. The model infrastructure will be used going forward to assist with future land management and ecosystem services assessments.
Project Description
The Great Dismal Swamp (GDS) project is an application of USGS LandCarbon, in support of DOI land management activities. The GDS project uses the Land Use and Carbon Scenario Simulator (LUCAS) model to produce local-scale carbon estimates (including fluxes, net ecosystem balance, and long-term sequestration rates) to include in an ecosystem service assessment at the GDS National Wildlife Refuge.
LUCAS integrates a state-and-transition simulation model with a carbon stock-flow model to characterize key controlling processes (i.e. hydrology and fire) and their associated effects on land-management activities (i.e. re-wetting, forest restoration, and fire management).
Methods
LUCAS model calibration consisted of running the model for a 300-year period in order to validate the forest age to biomass relationships, annual stock and flow transfer rates, and emission rates followed by disturbance.
To test the utility of the LUCAS model application for the Great Dismal Swamp, we modeled the historic time period of 1985-2015, using the calibrated forest growth curves, stock and flow rates, and known fire data (spatial location, patch size, and year/severity of disturbance). Results from the model testing are compared to the recent C loss estimates from the South One and Lateral West fire events (Reddy, 2015).
For more information on the project go to The Great Dismal Swamp Project website and the Land Use and Climate Change Team website.
Below are publications associated with this project.
A carbon balance model for the great dismal swamp ecosystem
Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR
- Overview
The Land Use and Carbon Scenario Simulator (LUCAS) model was used to develop a baseline carbon (C) budget for the Great Dismal Swamp, VA., using an annualized Stock-Flow approach. The model infrastructure will be used going forward to assist with future land management and ecosystem services assessments.
(Credit: Landsat 5, USGS. Public domain.)Landsat 5 image of the Lateral West fire Project Description
The Great Dismal Swamp (GDS) project is an application of USGS LandCarbon, in support of DOI land management activities. The GDS project uses the Land Use and Carbon Scenario Simulator (LUCAS) model to produce local-scale carbon estimates (including fluxes, net ecosystem balance, and long-term sequestration rates) to include in an ecosystem service assessment at the GDS National Wildlife Refuge.
LUCAS integrates a state-and-transition simulation model with a carbon stock-flow model to characterize key controlling processes (i.e. hydrology and fire) and their associated effects on land-management activities (i.e. re-wetting, forest restoration, and fire management).
Methods
LUCAS model calibration consisted of running the model for a 300-year period in order to validate the forest age to biomass relationships, annual stock and flow transfer rates, and emission rates followed by disturbance.
To test the utility of the LUCAS model application for the Great Dismal Swamp, we modeled the historic time period of 1985-2015, using the calibrated forest growth curves, stock and flow rates, and known fire data (spatial location, patch size, and year/severity of disturbance). Results from the model testing are compared to the recent C loss estimates from the South One and Lateral West fire events (Reddy, 2015).
(Public domain.)Carbon budget for the Great Dismal Swamp. For more information on the project go to The Great Dismal Swamp Project website and the Land Use and Climate Change Team website.
- Publications
Below are publications associated with this project.
A carbon balance model for the great dismal swamp ecosystem
BackgroundCarbon storage potential has become an important consideration for land management and planning in the United States. The ability to assess ecosystem carbon balance can help land managers understand the benefits and tradeoffs between different management strategies. This paper demonstrates an application of the Land Use and Carbon Scenario Simulator (LUCAS) model developed for local-scalQuantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR
Peatlands are a major reservoir of global soil carbon, yet account for just 3% of global land cover. Human impacts like draining can hinder the ability of peatlands to sequester carbon and expose their soils to fire under dry conditions. Estimating soil carbon loss from peat fires can be challenging due to uncertainty about pre-fire surface elevations. This study uses multi-temporal LiDAR to obtai