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Barrier islands provide important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism (Barbier and others, 2011; Feagin and others, 2010). These islands tend to be dynamic due to their location along the estuarine-marine interface. Besides gradual changes caused by constant forces, such as currents and tides, barrier islands face numerous threats including hurricanes, accelerated sea-level rise, oil spills, and anthropogenic impacts (Pilkey and Cooper, 2014). These threats are likely to influence the future of barrier islands in the latter part of the 21st century, especially as climate-related threats to coastal areas are expected to increase...
This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s Timucuan Ecological and Historic Preserve. These datasets were developed using 1-m digital elevation model (DEM) from 2018 with reduced elevation error in coastal wetlands (McHenry and others, 2023). This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2050 and 2100 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major high tide flooding...
This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s San Juan National Historic Site. These datasets were developed using 1-m digital elevation model (DEM) from the 3D Elevation program. This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2050 and 2100 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major high tide flooding thresholds defined by the National Oceanic and Atmospheric...
This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s De Soto National Memorial. These datasets were developed using 1-m digital elevation model (DEM) from the 3D Elevation program. This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2050 and 2100 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major high tide flooding thresholds defined by the National oceanic and Atmospheric Administration...
This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s Biscayne National Park. For information on the digital elevation model (DEM) source used to develop these datasets refer to the corresponding spatial metadata file (Danielson and others, 2023). This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2040 and 2080 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major hight tide flooding...
A barrier island habitat prediction model was used to forecast barrier island habitats (for example, beach, dune, intertidal marsh, and woody vegetation) for Dauphin Island, Alabama, based on potential island configurations associated with a variety of restoration measures and varying future conditions of storminess and sea-levels. In this study, we loosely coupled a habitat model framework with decadal hydrodynamic geomorphic model outputs to forecast habitats for 2 potential future conditions related to storminess (that is, "medium" storminess and "high" storminess based on storm climatology data) and 4 sea-level scenarios (that is, a "low" increase in sea level 0.3 m by around 2030 and 2050 and 1.0 m by around...
This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s Big Cypress National Preserve. For information on the digital elevation model (DEM) source used to develop these datasets refer to the corresponding spatial metadata file (Danielson and others, 2023). This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2050 and 2100 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major high tide flooding...
Global climate change is leading to large-scale shifts in species’ range limits. For example, rising winter temperatures are shifting the abundance and distributions of tropical, cold sensitive plant species towards higher latitudes. Coastal wetlands provide a prime example of such shifts, with tropical mangrove forests expanding into temperate salt marshes as winter warming alleviates past geographic limits set by cold intolerance. These rapid changes are dynamic and challenging to monitor, and uncertainty remains regarding the extent of mangrove expansion near poleward range limits. Here, we synthesized existing datasets and expert knowledge to assess the current (i.e., 2021) distribution of mangroves near dynamic...
Categories: Data;
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Tags: Alabama,
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Florida,
Gulf of Mexico,
This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s Dry Tortugas National Park. These datasets were developed using digital elevation model (DEM) from National Oceanic and Atmospheric Administration (NOAA). This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2050 and 2100 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major high tide flooding thresholds defined by NOAA. We estimated...
High-resolution elevation data provide a foundational layer needed to understand regional hydrology and ecology under contemporary and future-predicted conditions with accelerated sea-level rise. While the development of digital elevation models (DEMs) from light detection and ranging data has enhanced the ability to observe elevation in coastal zones, the elevation error can be substantial in densely vegetated coastal wetlands. In response, we developed a machine learning model to reduce vertical error in coastal wetlands for a 1-m DEM from 2018 that covered Nassau and Duval Counties, Florida. Error was reduced by using a random forest regression model within situ observations and predictor variables from optical...
This dataset includes probabilistic outputs for estimating areal coverage of current wetland coverage and potential wetland migration under various relative sea-level rise scenarios in Nassau and Duval Counties, which includes the City of Jacksonville and the U.S. National Park Service's Timucuan Ecological and Historic Preserve. These data contain potential migration for regularly oceanic-flooded wetlands (that is, flooded by oceanic water daily) and irregularly oceanic-flooded wetlands (that is, flooded by oceanic water less frequently than daily). The products in this data release were created using an approach that involved digital elevation model error reduction in wetlands (that is, overestimation of elevation...
Climate change is altering the frequency and intensity of extreme weather events. Quantifying ecosystem responses to extreme events at the landscape scale is critical for understanding and responding to climate-driven change but is constrained by limited data availability. Here, we integrated remote sensing with ground-based observations to quantify landscape-scale vegetation damage from an extreme climatic event. We used ground- and satellite-based black mangrove (Avicennia germinans) leaf damage data from the northern Gulf of Mexico (USA and Mexico) to examine the effects of an extreme freeze in a region where black mangroves are expanding their range. The February 2021 event produced coastal temperatures as low...
Dunes with a high relative topography can often be easily distinguished in high-resolution lidar-based digital elevation models (DEMs). Thus, researchers have begun using relative topography metrics, such as the topographic position index (TPI; Weiss, 2001), to identify ridges and upper slopes for extracting dunes from lidar-based DEMs (Wernette et al., 2016; Halls et al. 2018). DEMs are often used for automated delineations of intertidal and supratidal habitats in coastal applications despite issues related to vertical uncertainty. However, the level of vertical uncertainty from data collected with conventional aerial topographic lidar systems has been found to be as high as 60 cm in densely vegetated emergent...
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