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Above- and belowground production in coastal wetlands are important contributors to carbon accumulation and ecosystem sustainability. As sea level rises, we can expect shifts to more salt-tolerant communities, which may alter these ecosystem functions and services. Although the direct influence of salinity on species-level primary production has been documented, we lack an understanding of the landscape-level response of coastal wetlands to increasing salinity. What are the indirect effects of sea-level rise, i.e. how does primary production vary across a landscape gradient of increasing salinity that incorporates changes in wetland type? We measured above- and belowground production in four wetland types that span...
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Above- and belowground production in coastal wetlands are important contributors to carbon accumulation and ecosystem sustainability. As sea level rises, we can expect shifts to more salt-tolerant communities, which may alter these ecosystem functions and services. Although the direct influence of salinity on species-level primary production has been documented, we lack an understanding of the landscape-level response of coastal wetlands to increasing salinity. What are the indirect effects of sea-level rise, i.e. how does primary production vary across a landscape gradient of increasing salinity that incorporates changes in wetland type? We measured above- and belowground production in four wetland types that span...
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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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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...
Coastal ecosystems in the Eastern U.S. have been severely altered by processes associated with human development, including drainage of wetlands, changes in hydrology, land clearing, agricultural and forestry activity, and the construction of structures that “harden” the coast. Sea-level rise and the changing frequency of extreme events associated with climate change are now further degrading the capacity of those ecological and social systems to remain resilient. As custodians of ecological goods and services valued by society, coastal National Wildlife Refuges (NWRs) have a particularly important role to play in helping socio-ecological systems adapt to global-change processes. To help refuges address this challenge,...
In the Pacific Northwest, coastal wetlands support a wealth of ecosystem services including habitat provision for wildlife and fisheries and flood protection. The tidal marshes, mudflats, and shallow bays of coastal estuaries link marine, freshwater, and terrestrial habitats and provide economic and recreational benefits to local communities. Climate change effects such as sea-level rise are currently altering these habitats, but we know little about how these areas will change over the next 50-100 years. Our study examined the effects of sea-level rise on nine tidal marshes in Washington and Oregon, with the goal of providing scientific data to support future coastal planning and conservation. We compiled physical...
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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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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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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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The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the...
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This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
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This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios...
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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
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The goal of this project is to provide a preliminary overview, at a National scale, the relative susceptibility of the Nation's coast to sea- level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of regions where physical changes are likely to occur due to sea-level rise.
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Coastal wetlands store more carbon than most ecosystems globally. However, little is known about the mechanisms that control the loss of organic matter in coastal wetlands at the landscape scale, and how sea-level rise will impact this important ecological function.
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Above- and belowground production in coastal wetlands are important contributors to carbon accumulation and ecosystem sustainability. As sea level rises, we can expect shifts to more salt-tolerant communities, which may alter these ecosystem functions and services. Although the direct influence of salinity on species-level primary production has been documented, we lack an understanding of the landscape-level response of coastal wetlands to increasing salinity. What are the indirect effects of sea-level rise, i.e. how does primary production vary across a landscape gradient of increasing salinity that incorporates changes in wetland type? We measured above- and belowground production in four wetland types that span...
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This dataset contains projections of shoreline positions and uncertainty bands for future scenarios of sea-level rise. Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model forced with global-to-local nested wave models and assimilated with lidar-derived shoreline vectors. Read metadata carefully.


map background search result map search result map Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (2 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (A1B mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (1 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (B1 mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2025 (A1B maximum scenario) Tidal Range Data for the Gulf of Mexico Probability of Predicted Elevation with respect to projected sea levels for the Northeastern U.S. from Maine to Virginia for the 2020s, 2030s, 2050s and 2080s (Albers, NAD 83) Litter quality Primary production across a coastal wetland landscape in Louisiana, U.S.A. (2012-2014) Primary production across a coastal wetland landscape in Louisiana, U.S.A. above- and belowground primary production (2012-2014) data Primary production across a coastal wetland landscape in Louisiana, U.S.A. environmental data (2012-2014) CoSMoS Central California v3.1 projections of shoreline change due to 21st century sea level rise CoSMoS v3.1 flood hazard projections: 20-year storm in San Luis Obispo County CoSMoS v3.1 flood depth and duration projections: 1-year storm in San Luis Obispo County CoSMoS v3.1 water level projections: 1-year storm in Santa Barbara County CoSMoS v3.1 ocean-currents hazards: average conditions in San Luis Obispo County CoSMoS v3.1 wave-hazard projections: 1-year storm in San Mateo County CoSMoS v3.1 flood depth and duration projections: 100-year storm in San Francisco County CoSMoS v3.1 wave-hazard projections: 1-year storm in San Mateo County CoSMoS v3.1 water level projections: 1-year storm in Santa Barbara County CoSMoS v3.1 flood hazard projections: 20-year storm in San Luis Obispo County CoSMoS v3.1 flood depth and duration projections: 1-year storm in San Luis Obispo County CoSMoS v3.1 ocean-currents hazards: average conditions in San Luis Obispo County Primary production across a coastal wetland landscape in Louisiana, U.S.A. (2012-2014) Primary production across a coastal wetland landscape in Louisiana, U.S.A. above- and belowground primary production (2012-2014) data Primary production across a coastal wetland landscape in Louisiana, U.S.A. environmental data (2012-2014) Litter quality CoSMoS Central California v3.1 projections of shoreline change due to 21st century sea level rise Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (2 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (A1B mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (1 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (B1 mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2025 (A1B maximum scenario) Tidal Range Data for the Gulf of Mexico Probability of Predicted Elevation with respect to projected sea levels for the Northeastern U.S. from Maine to Virginia for the 2020s, 2030s, 2050s and 2080s (Albers, NAD 83)