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This data set contains decomposition rates for litter of Salicornia pacifica, Distichlis spicata, and Deschampsia cespitosa buried at 7 tidal marsh sites in 2015. Sediment organic matter values were collected at a subset of sites. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
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This data table contains mean decomposition rates and mean carbon:nitrogen ratios for different litter types buried in 7 marshes during 2015. Note that C:N data are repeated for low and high marsh areas at each site in the table. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
[Excerpt from Introduction] "The San Francisco Bay Estuary supports a large and diverse bird community. More than 50% of most Pacific flyway diving duck populations are found in the Estuary during the winter months (Trost 2002; U.S. Fish and Wildlife Service 2002). San Francisco Bay has been designated as a site of international importance for shorebirds (Western Hemisphere Shorebird Reserve Network), supporting millions of individuals (Morrison et al. 2001; Takekawa et al. 2001; Warnock et al. 2002), including species that use tidal marsh habitats. In total, the Bay’s tidal marshes support at least 113 bird species that represent 31 families (Takekawa et al., in press)..."
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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...
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This data release is comprised of tidal marsh biomass data and spatial predictions of peak biomass and Julian day of peak biomass using data from the Landsat archive. Aboveground biomass dry weight of mixed-species plots (25x50 cm) at a tidal marsh in Willapa Bay, Washington were used to establish a relationship between biomass and tasseled cap greeness (TCG). The julian day of annual peak greenness and the value of annual peak greenness for 32 years at Bandon National Wildlife Refuge (NWR), Grays Harbor NWR, and Nisqually NWR was calculated by fitting a Gaussian function to the TCG values for a given year. The value of each 30 meter pixel is the Julian day of maximum predicted TCG or the maximum predicted TCG....
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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...
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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
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This data table contains results for the 2014 mesocosm tests of inundation effects on decomposition. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
Abstract (from ScienceDirect): The interannual variability of tidal marsh plant phenology is largely unknown and may have important ecological consequences. Marsh plants are critical to the biogeomorphic feedback processes that build estuarine soils, maintain marsh elevation relative to sea level, and sequester carbon. We calculated Tasseled Cap Greenness, a metric of plant biomass, using remotely sensed data available in the Landsat archive to assess how recent climate variation has affected biomass production and plant phenology across three maritime tidal marshes in the Pacific Northwest of the United States. First, we used clipped vegetation plots at one of our sites to confirm that tasseled cap greenness provided...
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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...
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This data table contains summary data for temperature time series in near-surface sediments in high and low tidal marsh at 7 sites during 2015. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
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This table contains data on dry mass remaining in a subset of Salicornia pacifica and Deschampsia cespitosa litter bags removed over a series of time points spanning 6 months. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
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...
Mangrove forests are likely vulnerable to accelerating sea-level rise; however, we lack the tools necessary to understand their future resilience. On the Pacific island of Pohnpei, Federated States of Micronesia, mangroves are habitat to endangered species and provide critical ecosystem services that support local communities. We developed a generalizable modeling framework for mangroves that accounts for species interactions and the belowground processes that dictate soil elevation. The modeling framework was calibrated with extensive field datasets, including accretion rates derived from thirty 1-meter-deep soil cores dated with lead-210, more than 300 forest inventory plots, water-level monitoring, and differential...
Categories: Publication; Types: Citation
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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.
Stress gradients influence many ecosystem processes and properties, including ecosystem recovery from and resistance to disturbance. While recent analytical approaches have advanced multivariate metrics of ecosystem resilience that allow quantification of conceptual resilience models and identification of thresholds of state change, these approaches are not often translated to landscape scales. Using natural and restored salt marshes in Louisiana, USA, we quantified plant community recovery and resistance metrics along flooding stress gradients. n‐dimensional hypervolumes of plant community biomass and structure were simulated using field data collected from disturbance‐recovery experiments. The relationships between...
Categories: Publication; Types: Citation
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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),...
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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...
Model projections of mangrove soil elevation under a range of sea-level rise scenarios (37, 52, 67, and 117 cm by 2100). 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. Mean elevation for each region was calculated from 100 Monte Carlo simulations and were output annually from 2020-2100. Further details on model development, calibration, and validation are provided in the full report.
Water level was monitored at two mangrove forest sites across Pohnpei, Federated States of Microneisa. Water levels were recorded with pressure-transducing dataloggers (Solinst) for eight months (July 2016-March 2017). Elevation surveys (differential leveling) were used to convert water levels relative to the Earth Geoid Model of 2008.


map background search result map search result map Inundation Experiments, 2014 Decomposition rates and carbon:nitrogen ratios for different litter types, 2015 Litter Decomposition Rates, 2015 Sediment Temperature, 2015 Linear loss of litter over time, 2015 Digital elevation model outputs from wetland accreting rate model of ecosystem resilience (WARMER) at ten year intervals from 2010-2110 Seal Beach salt marsh digital elevation model output, sea-level rise scenarios, 2010-2110 Data for climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes LEAN-corrected San Francisco Bay digital elevation model, 2018 LEAN-Corrected DEM for Suisun Marsh San Francisco Bay Tidal Marsh Avian Predator Surveys, 2010 Blackwater LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 LEAN-Corrected Collier County DEM for wetlands Elevation Projections for Pohnpei Mangrove Forests Under a Range of Sea-level Rise Scenarios, 2020-2100 Water Level Across Two Mangrove Sites in Pohnpei, Federated States of Micronesia, July 2016 - March 2017 Species Composition Projections for Pohnpei Mangrove Forests Under Four Sea-level Rise Scenarios, 2020-2100 Seal Beach salt marsh digital elevation model output, sea-level rise scenarios, 2010-2110 Elevation Projections for Pohnpei Mangrove Forests Under a Range of Sea-level Rise Scenarios, 2020-2100 Water Level Across Two Mangrove Sites in Pohnpei, Federated States of Micronesia, July 2016 - March 2017 Species Composition Projections for Pohnpei Mangrove Forests Under Four Sea-level Rise Scenarios, 2020-2100 LEAN-Corrected DEM for Suisun Marsh Blackwater LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 LEAN-corrected San Francisco Bay digital elevation model, 2018 LEAN-Corrected Collier County DEM for wetlands Data for climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes Digital elevation model outputs from wetland accreting rate model of ecosystem resilience (WARMER) at ten year intervals from 2010-2110 Inundation Experiments, 2014 Decomposition rates and carbon:nitrogen ratios for different litter types, 2015 Litter Decomposition Rates, 2015 Sediment Temperature, 2015 Linear loss of litter over time, 2015