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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
This dataset consists of the current distribution (2000s) of mangrove forests in the southeastern U.S. This dataset was created from the current best available mangrove data on a state specific basis. Florida mangrove data was extracted from Florida Landuse Land Cover Classification System (FLUCCS). For Louisiana, we used observations of mangrove stands from aerial surveys by Michot et al. (2010). Mangrove presence in Texas came from maps produced by Sherrod & McMillan (1981) and the NOAA Benthic Habitat Atlas of Coastal Texas (Finkbeiner et al. 2009). Please note that this map depicts the distribution of mangrove forests and not mangrove individuals. More detailed information on this dataset is available in Osland...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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OBIS-USA brings together marine biological occurrence data – recorded observations of identifiable marine species at a known time and place, collected primarily from U.S. Waters or with U.S. funding. Coordinated by the Core Science, Analytics, Synthesis, and Libraries (CSAS&L) Program of the United States Geological Survey (USGS), OBIS-USA, strives to meet national data integration and dissemination needs for marine data about organisms and ecosystems. OBIS-USA is part of an international data sharing network (Ocean Biogeographic Information System, OBIS) coordinated by the Intergovernmental Oceanographic Commission, of UNESCO (United Nations Educational, Science and Cultural Organization International Oceanographic...
Tags: Arctic Ocean, Atlantic Ocean, Bay of Fundy, Beaufort Sea, Bering Sea, All tags...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
‚ÄčThis project takes advantage of an existing helicopter platform on St. Lawrence that will be used to collect ShoreZone imagery of the island. This project is leveraging contributions by the Oil Spill Recovery Institute, the Alaska Department of Natural Resources, the Alaska Department of Environmental Conservation, and NOAA Fisheries to collect imagery in the summer of 2013. The ABSI LCC will provided $10K to map the highest priority section of the St. Lawrence Island coastline.The ShoreZone mapping system has been in use since the early 1980s and has been applied to more than 40,000 km of shoreline in Washington and British Columbia. Through partnerships with other agencies and organizations, portions of southeastern...
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This data set consists of four images showing seasonal sea surface temperature (SST) averages for the entire earth. Data for the years 1985-2001 are averaged to produce each seasonal image. The seasons are January-March (sst001i4km.tif), April-June (sst002i4km.tif), July-September (sst003i4km.tif), and October-December (sst004i4km.tif). These SST data are the result of the 4 km Pathfinder effort at the National Oceanic and Atmospheric Administration (NOAA) National Oceanographic Data Center (NODC) and the University of Miami's Rosenstiel School of Marine and Atmospheric Science (RSMAS), which uses data from the NOAA-9, NOAA-11, NOAA-14, and NOAA-16 satellites. The 4 km Pathfinder effort at NODC is an improvement...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...


map background search result map search result map Seasonal Sea Surface Temperature Averages, 1985-2001 Chesapeake Bay region sea-level rise modelling - Habitat classification, 1996 Pacific Northwest sea-level rise modelling - Habitat classification for the Columbia River estuary (2100, 2 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for the Columbia River estuary (2050, 1.5 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2075, A1B mean scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (1980) Pacific Northwest sea-level rise modelling - Habitat classification for site two (1977) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2100, 1 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2075, 2 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2050, A1B maximum scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2025, 1.5 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2025, 1.5 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2075, A1B mean scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (1980) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2025, 1.5 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site two (1977) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2100, 1 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2075, 2 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2050, A1B maximum scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2025, 1.5 meter rise scenario, dikes removed) Chesapeake Bay region sea-level rise modelling - Habitat classification, 1996 Seasonal Sea Surface Temperature Averages, 1985-2001