Filters: Tags: Pohnpei (X)
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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...
Aboveground Biomass Data from Pohnpei, Federated States of Micronesia. Plot data includes X and Y location, downed dead wood (DDW) count, mangrove species identification, and site descriptions. Species information was recorded for Bruguiera gymnorhiza, Sonneratia alba, Xylocarpus granatum, Lumnitzera littorea, Rhizophora apiculata, Rhizophora lamarckii, Rhizophora mucronata, Rhizophora stylosa and Ceriops tagal. Mangroves were inventoried for species identification, diameter at breast height (DBH), height, and dead status.
Categories: Data;
Tags: Biomass,
Carbon Sinks,
Ecosystem Management,
Federated States of Micronesia,
Field Inventory and Monitoring,
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.
Categories: Data;
Tags: Pacific Ocean,
Pohnpei,
Senyavin Islands,
Tidal Mangrove Forest,
environment,
U.S. Geological Survey (USGS) scientists conducted field work efforts during February 15-23, 2017 and April 10-25, 2019 in the mangrove forests of Pohnpei, Federated States of Micronesia (FSM) with logistical assistance from the Micronesia Conservation Trust (MCT) and field assistance from the Conservation Society of Pohnpei and the Pohnpei Department of Forestry. The field team combined the surveying technologies and techniques of Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) surveying, total station surveying, and differential leveling to measure elevations on critical features in the mangrove forests, including the elevations of water level recorders, sediment coring locations, and Surface...
Categories: Data;
Tags: Alohkapw,
Climate Change Adaptation,
Differential Leveling,
Dolopwail,
Ecology,
Surface elevation of the mangrove forest is important for understanding current and future vulnerability to sea-level rise. Due to the lack of LiDAR data and insufficient accuracy of space-borne synthetic aperture radar-derived elevation models, we leveraged data from differential leveling surveys to generate a digital elevation model (DEM) for the mangrove forest of Pohnpei. We created a general slope model with a shore-normal transect of elevation and a general additive model (GAM) spine. To create a continuous DEM, the GAM spline was then stretched across a grid representing the width of mangrove, created using digitized boundaries of the seaward and interior mangrove edge. This simplified approach assumes that...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Pacific Ocean,
Pohnpei,
Senyavin Islands,
Tidal Mangrove Forest,
digital elevation model,
Future sea-level rise poses a risk to mangrove forests. To better understand potential vulnerability, we developed a new numerical model of soil elevation for mangrove forests. We used the model to generate projections of elevation and mangrove forest composition change under four sea-level rise scenarios through 2100 (37, 52, 67, and 117 cm by 2100). We employed a data-driven modeling approach, utilizing new and existing data to inform model parameters. The model was calibrated using dated soil cores and used a spin-up period to establish the soil column prior to future projections. Additional field data, including water level monitoring and elevation surveys, were used to estimate the initial elevation of the...
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