Filters: partyWithName: U.S. Geological Survey - ScienceBase (X) > partyWithName: Karen M Thorne (X)
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Accurate input data are important for making site-specific projections of tidal wetlands into the future. We developed bias-corrected digital elevation models (DEM) using the LEAN approach (LiDAR Elevation Adjustment with NDVI). LEAN DEMs were used as the initial elevation for model projections. Further, we conducted elevation and vegetation surveys across each study site to characterize elevation profiles of dominant species, which were used to inform organic productivity functions in WARMER-2.
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,
To quantify the potential for landward migration at the estuary level, we developed a geospatial dataset for the conterminous United States (CONUS) that identifies the boundaries for estuarine drainage areas. Nine estuarine drainage areas in south Florida were delineated using data developed by the South Florida Water Management District (SFWMD 2018). For the rest of CONUS, we used information contained within the National Fish Habitat Action Plan (NFHAP) - Coastal Spatial Framework (CSF) (National Centers for Coastal Ocean Science 2021). The original NFHAP-CSF data included 612 drainage areas, which were too many for our purposes. Therefore, we merged smaller drainage areas with larger, adjacent drainage areas...
We quantified the potential area available for landward migration of tidal saline wetlands and freshwater wetlands due to sea-level rise (SLR) at the estuary scale for 166 estuarine drainage areas and at the state scale for 22 coastal states and District of Columbia. We used 2016 Coastal Change Analysis Program (C-CAP) data in combination with the future wetland migration data under the 1.5 m global SLR scenario to evaluate the potential for wetland migration into all the individual C-CAP classes and into the following six land cover categories: (1) freshwater forest (wetland); (2) freshwater marsh (wetland); (3) terrestrial forest (upland); (4) terrestrial grassland (upland); (5) agricultural croplands (upland);...
Digital elevation model outputs from wetland accreting rate model of ecosystem resilience (WARMER) at ten year intervals from 2010-2110. Baseline elevations were collected with RTK GPS units and LiDAR elevations in non-surveyed areas were also corrected using LEAN method. Historical accretion rates were collected at each salt marsh and used to parameterize WARMER, predicting future elevations. These data support the following publication: Rosencranz JA, Thorne KM, Buffington KJ, et al. Sea‐level rise, habitat loss, and potential extirpation of a salt marsh specialist bird in urbanized landscapes. Ecol Evol. 2018;00:1–11. https://doi.org/10.1002/ece3.4196
Types: Citation;
Tags: California,
Carpinteria,
Mugu Lagoon,
Remote Sensing,
Seal Beach National Wildlife Refuge,
Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for tidal marsh areas around San Francisco Bay using the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). Survey-grade GPS survey data (6614 points), NAIP-derived Normalized Difference Vegetation Index, and original 1 m lidar DEM from 2010 were used to generate a model of predicted bias across tidal marsh areas. The predicted bias was then subtracted from the original lidar DEM and merged with the NOAA...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Remote Sensing,
San Francisco Bay,
USGS Science Data Catalog (SDC),
biota,
digital elevation models,
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).
Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for Suisun marsh using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (6912 points, collected across public and private land in 2018), Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image (June 2018), a 1 m lidar DEM from September 2018, and a 1 m canopy surface model were used to generate models of predicted bias across the...
WARMER-2 Model Inputs and Projections for Three Tidal Wetland Sites Across San Francisco Bay Estuary
Understanding the rates and patterns of tidal wetland elevation changes relative to sea-level is essential for understanding the extent of potential wetland loss over the coming years. Using an enhanced and more flexible modeling framework of an ecosystem model (WARMER-2), we explored sea-level rise (SLR) impacts on wetland elevations and carbon sequestration rates through 2100 by considering plant community transitions, salinity effects on productivity, and changes in sediment availability. We incorporated local experimental results for plant productivity relative to inundation and salinity into a species transition model, as well as site-level estimates of organic matter decomposition. The revised modeling framework...
This data release includes monitoring data collected by the U.S. Geological Survey (USGS) Humboldt Bay Water Quality and Salt Marsh Monitoring Project. The datasets include continuous water levels collected at a 6-minute timestep collected in two study marshes (Mad River and Hookton). Surface deposition, elevation changes and carbon storage (in marsh edge environments) measured in five USGS study marshes (Mad River, Manila, Jacoby, White and Hookton). The monitoring data presented in this data release represent fundamental datasets needed to manage blue carbon stocks, assess marsh vulnerability, inform SLR adaptation planning, and build coastal resiliency to climate change in Humboldt Bay, CA Additional documentaton...
Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for wetlands throughout Collier county using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (15,223 points), NAIP-derived Normalized Difference Vegetation Index (2010), a 10 m lidar DEM from 2007, and a 10 m canopy surface model were used to generate a model of predicted bias across marsh, mangrove, and cypress habitats. The predicted bias was then subtracted from...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Collier county,
Remote Sensing,
USGS Science Data Catalog (SDC),
biota,
cypress,
These datasets provide information on plant alpha, beta, and gamma diversity, and plant species abundance at several spatial scales for tidal wetlands along a salinity gradient in the San Francisco Bay-Delta and an impounded brackish wetland complex in Suisun Marsh, California. Files include diversity metrics calculated at the patch, site, and region scales, average percent cover of wetland dominant plants at the patch scale, and average percent cover of all wetland plants at the site scale. These data support the following paper: Jones, S.F., Janousek, C.N., Casazza, M.L., Takekawa, J.Y. and Thorne, K.M., 2021. Seasonal impoundment alters patterns of tidal wetland plant diversity across spatial scales. Ecosphere,...
Categories: Data;
Tags: Botany,
California,
San Francisco Bay-Delta Estuary,
USGS Science Data Catalog (SDC),
biodiversity,
Model projections of mangrove species' relative composition (0-1) under low, moderate, high, and extreme (37, 52, 67, and 117 cm by 2100) sea-level rise. Species cover was modeled as a function of annual inundation time, using field observations of species occurrence and elevation to define species-specific zone of suitable habitat. Soil elevation changed in response to mineral and organic matter inputs and relative changes in sea-level. The model was calibrated using dated soil cores, extensive elevation and vegetation survey data, and water level observations around Pohnpei. Relative species composition values were output in 20 year intervals from 2020-2100. Further details on model development, calibration, and...
Habitat projections from the WARMER-2 model for four tidal wetland sites in San Francisco Bay estuary under the constant sediment scenario, plus 0.2 ppt per decade salinity scenario, and the community transition organic productivity function under a 99 cm by 2100 sea-level rise scenario. Results are the average from one hundred Monte Carlo simulations.
This dataset provides seedling density and site characteristics for 131 plots in Whiskeytown National Recreation Area in California, USA. Site characteristics include modeled seed availability and terrain indices calculated using a 1 meter resolution digital elevation model (DEM).
Categories: Data;
Tags: California,
Ecology,
Forestry,
Remote Sensing,
USGS Science Data Catalog (SDC),
Elevation change and surface deposition are important drivers of salt marsh ecological processes and represent two of the fundamental variables for determining marsh resilience to sea-level rise. Surface Elevation Tables with Marker Horizons (SET-MH) were used to measure plot-scale elevation change (SETs) and surface deposition (MHs) in five USGS study marshes located in Humboldt Bay, CA. SET-MHs were installed in 2014 (Mad River marsh and Manila marsh) and in 2015 (Jacoby marsh, White marsh, and Hookton marsh) and were measured during quarterly site visits. The SET-MH network includes two SETs and six MHs in each of the five study marshes. Measuring elevation change at the two SETs in each study marsh involves...
Water levels are an important driver of salt marsh processes. In 2016, pressure-transducing data loggers (LT Edge Model 3001, Solinst and Hobo Model U-20-001-01-Ti) and barometric-pressure loggers (Model 3001, Solinst) were deployed in two USGS study marshes (Mad River marsh and Hookton marsh) located in Humboldt Bay, CA. The loggers were placed as low in the tide frame as possible, while still maintaining access to the sensors at low tide. Sensors captured high tide water levels; but sensor elevation was too high to capture low tide water levels. Continuous measurements were collected on a 6-minute timestep. Sensor elevations were surveyed using Real-Time Kinematic GPS (Leica GS-15, Leica Geosystems, Norcross,...
Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for the area surrounding Blackwater National Wildlife Refuge in Chesapeake Bay using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (3699 points, collected across four tidal marsh sites in Chesapeake Bay (Eastern Neck, Martin, Bishops Head, and Blackwater) in 2010 and 2017. Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Chesapeake Bay,
biota,
digital elevation models,
estuary,
lidar,
This dataset contains avian survey observations across four tidal marsh areas around San Francisco Bay. Multiple surveys were conducted around both high and low tides during the winter of 2010/11. Each survey alternated between scan and focals. During scans, all observable birds were counted. During focals, the behavior of a single, randomly selected bird was observed. Water level data was collected concurrently at each site and is provided with the avian survey data. These data support the following publication: Thorne, K.M., Spragens, K.A., Buffington, K.J., Rosencranz, J.A. and Takekawa, J., 2019. Flooding regimes increase avian predation on wildlife prey in tidal marsh ecosystems. Ecology and evolution, 9(3),...
Categories: Data;
Tags: Ecology,
Emergent Tidal Marsh,
Petaluma River,
San Francisco Bay,
USGS Science Data Catalog (SDC),
Digital elevation model outputs from wetland accreting rate model of ecosystem resilience (WARMER) at ten year intervals from 2010-2110. Baseline elevations were collected with RTK GPS units and LiDAR elevations in non-surveyed areas were also corrected using LEAN method. Historical accretion rates were collected at each salt marsh and used to parameterize WARMER, predicting future elevations.
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