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The Great Dismal Swamp (GDS) project is an application of USGS LandCarbon, at the US Fish and Wildlife Service's (FWS) Great Dismal Swamp National Wildlife Refuge (NWR), and is designed to produce local-scale carbon estimates (including fluxes, ecosystem balance, and long-term sequestration rate) to include in an ecosystem service assessment in support of Department of Interior (DOI) land management activities. The project will improve the understanding of the effects of past drainage, logging, farming, and management on carbon sequestration and fire risk in peatlands. Broad Science Questions: How are ecosystem services (including carbon sequestration, wildlife viewing, water quality, and others) impacted by management...
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Plot-level field data were collected in the summer of 2014 to estimate aboveground and belowground biomass in the Great Dismal Swamp National Wildlife Refuge and Dismal Swamp State Park in North Carolina and Virginia. Data were collected at 85 plots. The location of the center of each plot was recorded with a Trimble ProXH global positioning system (GPS) and differentially corrected. Data files included 1: GDS_plots.csv, 2. GDS_FWD.csv, 3. GDS_LWD.csv, 4. GDS_Shrubs.csv, 5. GDS_Trees.csv, and 6. GDS_plot_summaries.csv. The data contained in GDS_plot_summaries.csv were calculated from the GDS_plots.csv, GDS_FWD.csv, GDS_LWD.csv, GDS_Shrubs.csv, GDS_Trees.csv files using the R statistical software environment (R Core...
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The disturbance team contributes to the goals of the LandCarbon project and conducts research focusing on 3 main components: (1) monitoring disturbance patterns and their impacts on carbon cycling, (2) understanding drivers creating the patterns and impacts, and (3) using scenarios of change to project future potential disturbance patterns, their interactions with other disturbances, and subsequent impacts on carbon cycling. Key research questions driving our work include: (1) Monitoring: How can remotely sensed, field-based, and other data best be used individually and synergistically to track changes in fire occurrence in ecosystem types with long fire-return intervals and the impacts on carbon? How do disturbances...
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 obtain pre- and post-fire elevations and estimate soil carbon loss caused by the 2011 Lateral West fire in the Great Dismal Swamp National Wildlife Refuge, VA, USA. We also determine how LiDAR elevation error affects uncertainty in our carbon loss estimate by randomly perturbing the LiDAR point elevations and recalculating elevation...
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Plot-level field data were collected in the summer of 2014 to estimate aboveground and belowground biomass in the Great Dismal Swamp National Wildlife Refuge and Dismal Swamp State Park in North Carolina and Virginia. Data were collected at 85 plots. The location of the center of each plot was recorded with a Trimble ProXH global positioning system (GPS) and differentially corrected. Data files included 1: GDS_plots.csv, 2. GDS_FWD.csv, 3. GDS_LWD.csv, 4. GDS_Shrubs.csv, 5. GDS_Trees.csv, and 6. GDS_plot_summaries.csv. The data contained in GDS_plot_summaries.csv were calculated from the GDS_plots.csv, GDS_FWD.csv, GDS_LWD.csv, GDS_Shrubs.csv, GDS_Trees.csv files using the R statistical software environment (R Core...


    map background search result map search result map Ecosystem disturbances monitoring an modeling Great Dismal Swamp Project Great Dismal Swamp field measurements for aboveground and belowground biomass Great Dismal Swamp field measurements for aboveground and belowground biomass Great Dismal Swamp field measurements for aboveground and belowground biomass Great Dismal Swamp Project Great Dismal Swamp field measurements for aboveground and belowground biomass Ecosystem disturbances monitoring an modeling