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Research about Great Dismal Swamp National Wildlife Refuge

Source-linked reports with geographic coverage including Great Dismal Swamp National Wildlife Refuge.

3 recordsLinked to original sources

Quantifying post-colonial peat carbon loss from a drained forested peatland, Great Dismal Swamp National Wildlife Refuge, USA

Peatland carbon storage is increasingly threatened by the combination of land-use change and climate variability, though carbon losses from land-use changes that span centuries are difficult to quantify, particularly in systems where little undisturbed area remains. Here we use a combination of vegetation change, fire history, and calculations of excess ash mass to quantify carbon loss in the Great Dismal Swamp National Wildlife Refuge (GDS NWR), USA, a highly impacted oligotrophic temperate peat swamp. Our results indicate that ditch construction that began in the Colonial Era in the late 1700s and continued into the mid-20th century across the swamp resulted in shifts from cypress-tupelo swamps to a combination of maple-gum and pine pocosin forests, consistent with drying surface conditions. Two large smoldering fires (2008, 2011) that were exacerbated by surface drainage, shifted vegetation from swamp to marsh, consumed peat over 25 km 2 , and caused losses of 1.05–1.34 Tg C due to peat burning. Across the Refuge as a whole, up to 48.2 Tg C has been lost to peat oxidation since ditch construction. Both stocks and rates of carbon loss remain higher than post-disturbance accumulation across most of GDS NWR, suggesting that existing efforts to block drainages to elevate water tables may not be enough to offset carbon losses. Rewetting heavily impacted surface peats may reduce peat oxidation and carbon loss, and shift vegetation toward hydrologic conditions preferred by pre-disturbance cypress-tupelo swamps.

North Carolina, Virginia↗

Benefits of the fire mitigation ecosystem service in the Great Dismal Swamp National Wildlife Refuge, Virginia, USA

The Great Dismal Swamp (GDS) National Wildlife Refuge delivers multiple ecosystem services, including air quality and human health via fire mitigation. Our analysis estimates benefits of this service through its potential to reduce catastrophic wildfire related impacts on the health of nearby human populations. We used a combination of high-frequency satellite data, ground sensors, and air quality indices to determine periods of public exposure to dense emissions from a wildfire within the GDS. We examined emergency department (ED) visitation in seven Virginia counties during these periods, applied measures of cumulative Relative Risk to derive the effects of wildfire smoke exposure on ED visitation rates, and estimated economic losses using regional Cost of Illness values established within the US Environmental Protection Agency BenMAP framework. Our results estimated the value of one avoided catastrophic wildfire in the refuge to be \$3.69 million (2015 USD), or \$306 per hectare of burn. Reducing the frequency or severity of extensive, deep burning peatland wildfire events has additional benefits not included in this estimate, including avoided costs related to fire suppression during a burn, carbon dioxide emissions, impacts to wildlife, and negative outcomes associated with recreation and regional tourism. We suggest the societal value of the public health benefits alone provides a significant incentive for refuge mangers to implement strategies that will reduce the severity of catastrophic wildfires.

North Carolina, Virginia↗

Quantifying 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 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 change and carbon loss, iterating this process 1000 times. We calculated a total loss using LiDAR of 1.10 Tg C across the 25 km 2 burned area. The fire burned an average of 47 cm deep, equivalent to 44 kg C/m 2 , a value larger than the 1997 Indonesian peat fires (29 kg C/m 2 ). Carbon loss via the First-Order Fire Effects Model (FOFEM) was estimated to be 0.06 Tg C. Propagating the LiDAR elevation error to the carbon loss estimates, we calculated a standard deviation of 0.00009 Tg C, equivalent to 0.008% of total carbon loss. We conclude that LiDAR elevation error is not a significant contributor to uncertainty in soil carbon loss under severe fire conditions with substantial peat consumption. However, uncertainties may be more substantial when soil elevation loss is of a similar or smaller magnitude than the reported LiDAR error.

Virginia↗