Folders: ROOT > ScienceBase Catalog > National and Regional Climate Adaptation Science Centers > Southeast CASC > FY 2020 Projects > Science to Inform the Management of Mangrove Ecosystems Undergoing Sea Level Rise at Ding Darling National Wildlife Refuge, Sanibel Island, Florida > Approved DataSets ( Show all descendants )
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ROOT _ScienceBase Catalog __National and Regional Climate Adaptation Science Centers ___Southeast CASC ____FY 2020 Projects _____Science to Inform the Management of Mangrove Ecosystems Undergoing Sea Level Rise at Ding Darling National Wildlife Refuge, Sanibel Island, Florida ______Approved DataSets Filters
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This study monitored soil surface elevation change from mangrove forests fertilized with nitrogen and phosphorus from 2018-2021. The mangroves selected at Ding Darling National Wildlife Refuge (NWR) have been previously exposed to high nutrient loading from agricultural discharge into the Caloosahatchee River, which elevated soil phosphorus levels to 3-4 times ambient before treatments were impose. Sea-level rise vulnerability with additional nitrogen and phosphorus is a concern for these mangrove ecosystems.
Categories: Data;
Tags: Ecology,
Florida,
Gulf of Mexico,
Sanibel Island,
USGS Science Data Catalog (SDC),
Accurate elevation data in coastal wetlands is crucial for planning for sea-level rise. Elevation surveys were conducted across southwest Florida wetlands to provide ground validation of LiDAR as well as target long-term monitoring stations (surface elevation tables). Surveys were conducted in June 2021 across Ding Darling National Wildlife Refuge, Clam Bay, Rookery Bay National Estuarine Research Reserve, and Ten Thousand Islands National Wildlife Refuge. A combination of post-processed kinematic GPS and differential levelling survey techniques were employed, depending on the canopy cover.
Categories: Data;
Tags: Clam Bay,
Ding Darling National Wildlife Refuge,
Florida,
GPS measurement,
RTK GPS,
This study evaluated CO2 flux from soils and pneumatophores of Avicennia germinans mangrove trees subjected to nitrogen and phosphorus fertilization versus an unfertilized control with a basin mangrove ecosystem. Data were collected twice, once in the summer (June 2020) and once in the winter (November 2020) and will be used to help develop a carbon budget for basin mangroves on Sanibel Island, Florida. These data were presented as part of an M.S. Thesis (Florida Atlantic University, Natalie T. Faron, 2021), entitled “The impact of nutrient loading on the soil and root respiration rates of Florida mangroves”.
Elevation projections from the WARMER-Mangroves model for J N. "Ding" Darling National Wildlife Refuge across a range of sea-level rise scenarios (53, 115, and 183 cm by 2100). The model was calibrated using dated soil cores sampled from the basin hydrologic zone. These data support the following publication: Buffington, K.J., Thorne, K.M., Krauss, K.W., Conrad, J.K., Drexler, J.Z., and Zhu, Z., in-review. Vulnerability of Sanibel Island’s mangrove resources to sea-level rise (Florida, USA).
Mangrove inventory data from J.N. Ding Darling National Wildlife Refuge, Sanibel Island, Florida, USA collected in 2016 and 2017. Plot data includes X and Y downed dead wood count, mangrove species information and site descriptions. Tree data includes the three species found on the refuge: Avicennia germinans (Black mangroves), Laguncularia racemosa (White mangroves) and Rhizophora mangle (Red mangroves). They were inventoried for diameter at breast height (DBH), height, and dead status.
Sediment cores (1 m in depth) were collected at each of three mangrove sites at J.N. Ding Darling National Wildlife Refuge on Sanibel Island, Florida. At each site, one core was collected in the hydrogeomorphic zone called the fringe, which is the area directly adjacent to the ocean. The other core was collected in the zone called the basin, which is the large area, often behind a small berm, that receives less direct tidal energy. All cores were sectioned and measured for sectional volume, dry weight and % organic carbon (OC) by weight.
This study evaluated sap flow of neotropical mangrove species subjected to background nutrient loading, and well as fertilization with either nitrogen or phosphorus, at Ding Darling National Wildlife Refuge (NWR). Data collections were made seasonally to model stand water use by mangrove forests as a metric of ecosystem stress through alteration of water use potential at the stand level. Data on leaf-scale water use efficiency, and data from a partial weather station deployed near study sites, were included for enabling model development and calculation of stand water use.
Accurate elevation data in coastal ecosystems are crucial for understanding vulnerability to sea-level rise. Lidar has become increasingly available; however, in tidal wetlands such as mangroves and salt marsh, vertical bias from dense vegetation reduces accuracy of the delivered 'base earth' products. To increase accuracy of elevation models across south Florida, we applied the LEAN technique to six different lidar collections from 2007-2018. On average, LEAN correction increased DEM accuracy by 46.1 percent, reducing the vertical bias. After correction and post-processing, the DEMs were merged together with a bathymetric dataset to create a seamless topobathy product.
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