This dataset consists of a file geodatabase containing the digitized ecotone boundaries between mangroves and freshwater marsh in 2013 and 2019 at 14 systematically selected segments in Big Cypress National Preserve and Everglades National Park (southwest Florida, USA).

This data was collected as part of a sampling protocol to monitor ecotonal movement of mangroves and upslope freshwater marshes in Everglades National Park and Big Cypress National Preserve. Remote sensing approaches are used to delineate the physical location of the ecotone (boundaries) between mangroves and freshwater marsh. Fourteen 3 kilometer (1.9 mile [mi]) segments are systematically placed along the ecotone within the two parks. Aerial imagery is used to digitize the mangrove-marsh ecotone in each segment and must be 1 meter (3.3 feet [ft]) or better resolution and have positional accuracy of ± 3 meters (9.8 feet [ft]) or better. Four ground-truth field point locations (marker points) are established approximately 1 kilometer (0.62 miles [mi]) apart along the ecotone of each segment to provide field-based measurements and ground-truthing of the digitized line. Vegetation data is collected at each sampling point, with this vegetation coverage determining where the placement of the ecotone should be. generally, this is where mangrove cover drops below 50% cover. The vegetation data also verifies if it is mangroves (typical Red) that is the dominant tree on the tress side of the ecotonal edge. The vegetation data also indicated the dominant graminoid on the more inland side of the ecotone. We have found 3 major groups for the marsh dominant vegetation type. This could be important mitigating factor or a indicator of future conditions. NOTE - Data for this data release was pulled from the mangrove marsh ecotone database and preliminarily cleaned and organized in May 2025. The data should undergo further QAQC before being used in analysis.

The Everglades National Park (EVER) and Big Cypress National Preserve (BICY) vegetation mapping project is part of the Comprehensive Everglades Restoration Plan (CERP). It is a cooperative effort between the South Florida Water Management District (SFWMD), the United States Army Corps of Engineers (USACE), and the National Park Service (NPS) Vegetation Mapping Inventory Program (VMI). The goal of this project is to produce a spatially and thematically accurate vegetation map of EVER and BICY prior to the completion of restoration efforts. The vegetation map will serve as a record of baseline conditions to: (1) document changes to the spatial extent, pattern, and proportion of plant communities within these two federally managed units as they respond to hydrologic modifications resulting from the implementation of CERP; and (2) provide vegetation and land-cover information to NPS park managers and scientists for use in park management, resource management, research, and monitoring. This project covers an area of approximately 7,400 square kilometers (1.84 million acres [ac]) and consists of seven mapping regions: four regions in EVER, Regions 1–4; and three in BICY, Regions 5–7 (Figure 1). The report that follows focuses on the mapping effort associated with Region 2, the Southeast Saline Everglades (SESE); an area that is geographically centered on southern Taylor Slough in Everglades NP. Region 2 encompasses a total area of 591.4 square kilometers (228.2 square miles [mi2] and 146,138 ac) and is bounded by Shark River Slough/Long Pine Key (Region 1) to the north, U.S Highway 1 to the east, Florida Bay to the south, and Flamingo (Region 3) to the west. Photo-interpretation was performed by superimposing a 50 × 50 meter (164 × 164 feet [ft] or .25 hectare [.61 ac]) grid cell vector matrix over stereoscopic, 0.30 centimeter (11.8 inches [in]) spatial resolution, color-infrared aerial imagery on a digital photogrammetric workstation. Photo-interpreters identified the dominant community in each cell by applying majority rule algorithms, recognizing community specific spectral signatures alongside an aerial photograph interpretation key, and referencing an extensive ground-truth database. The dominant vegetation community within in each grid cell was classified using a hierarchical classification system developed specifically for this project. In addition, at each grid cell photo-interpreters noted any evidence of disturbance as either anthropogenic, fire, freeze, or windstorm and categorized the absolute cover of cattail (Typha sp.) and any exotic species present as either: Sparse (10–49%), Dominant (50–89%), or Monotypic (90–100%). A total of 129 unique vegetation classes were identified within Region 2. The most common vegetation type was Red Mangrove Scrub-Open Marsh. This community accounted for approximately 17.3% of the map area. Other notable classes include Short Sawgrass Marsh-Dense (8.6%), Transitional Bayhead Shrubland (7.2%), Red Mangrove Scrub-Sawgrass Marsh (5.4%), Red Mangrove Scrub-Spikerush Marsh (4.6%), Spikerush Marsh (3.5%), and Transitional Bayhead Swamp Scrub-Sawgrass Marsh (2.5%). These seven classes and water (23.0%) account for 72.2% of the entire area mapped within Region 2. Based on 229 randomly selected points, the Region 2 map accuracy was determined to be 88.6% with a lower 90th percentile confidence level of 84.6%.

The Everglades National Park (EVER) and Big Cypress National Preserve (BICY) vegetation mapping project is part of the Comprehensive Everglades Restoration Plan (CERP). It is a cooperative effort between the South Florida Water Management District (SFWMD), the United States Army Corps of Engineers (USACE), and the National Park Service (NPS) Vegetation Mapping Inventory Program (VMI). The goal of this project is to produce a spatially and thematically accurate vegetation map of Everglades NP and Big Cypress NP prior to the completion of restoration efforts. The vegetation map will serve as a record of baseline conditions to: (1) document changes to the spatial extent, pattern, and proportion of plant communities within these two federally-managed units as they respond to hydrologic modifications resulting from the implementation of the Comprehensive Everglades Restoration Plan and the Western Everglades Restoration Project; and (2) provide vegetation and land-cover information to NPS park managers and scientists for use in park management, resource management, research, and monitoring. This project covers an area of approximately 7,400 square kilometers (1.84 million acres [ac]) and consists of seven mapping regions: four regions in Everglades NP, Regions 1–4, and three in Big Cypress NP, Regions 5–7 (Figure 1). The report that follows focuses on the mapping effort associated with Region 3, the Southwest Coastal Everglades (SWCE); an area geographically centered around Whitewater Bay in Everglades NP. Region 3 encompasses a total area of 990.7 square kilometers (382.5 square miles, 244,816 ac) and is bounded by Shark River Slough/Long Pine Key (Region 1) to the northeast, Taylor Slough (Region 2) to the east, and the Northwest Coastal Everglades (Region 4) to the north. Photo-interpretation was performed by superimposing a 50 × 50 meter (164 × 164 feet or 0.25 hectare [0.61 ac]) grid cell vector matrix over stereoscopic, 0.30 centimeter (11.8 inches) spatial resolution, color-infrared aerial imagery on a digital photogrammetric workstation. Photo-interpreters identified the dominant community in each cell by applying majority-rule algorithms, recognizing community-specific spectral signatures alongside an aerial photograph interpretation key, and referencing an extensive ground-truth database. The dominant vegetation community within in each grid cell was classified using a hierarchical classification system developed specifically for this project. Photo-interpreters additionally noted any evidence of disturbance in each grid cell as either anthropogenic, fire, freeze, or windstorm and categorized the absolute cover of cattail (Typha sp.) and any exotic species present as either: Sparse (10–49%), Dominant (50–89%), or Monotypic (90–100%). A total of 169 thematic classes were used to map Region 3. The most common vegetation class was Mixed Mangrove Forest. This community accounted for approximately 8% of the area mapped. Other notable classes include Short Sawgrass Marsh-Dense (6.1%), Red Mangrove Forest (5.0%), Black Mangrove-Red Mangrove Forest (4.5%), and Red Mangrove Scrub-Open Marsh (4.5%). These five classes plus water, e.g., ponds, lakes, bays, rivers, etc., (26%) account for approximately 54% of the entire area mapped within Region 3. Based on 245 randomly selected points, the accuracy of the Region 3 map was determined to be 89.4% with a lower 90th percentile confidence level of 85.6%.

The Everglades National Park vegetation mapping project is part of the Comprehensive Everglades Restoration Plan (CERP). It is a cooperative effort between the South Florida Water Management District (SFWMD), the United States Army Corps of Engineers (USACE), and the National Park Service Vegetation Mapping Inventory Program (NPS VMI). The goal of this project is to produce a spatially and thematically accurate vegetation map of Everglades National Park (EVER) prior to the completion of restoration efforts associated with CERP. This spatial product will serve as a record of baseline vegetation conditions for the purpose of: (1) documenting changes to the spatial extent, pattern, and proportion of plant communities within EVER as they respond to hydrologic modifications resulting from the implementation of the CERP; and (2) providing vegetation and land-cover information to NPS park managers and scientists for use in resource management, research, and monitoring. The vegetation map of EVER covers an area of 4,482.2 square kilometers (1.108 million acres [ac]) and consists of four mapping regions: Region 1 – Shark River Slough/Long Pine Key; Region 2 – The Southeast Saline Everglades; Region 3 – The Southwest Coastal Everglades; and Region 4 – The Northwest Coastal Everglades. Region 1 was mapped by the SFWMD and USACE while Regions 2-4 were mapped by the South Florida Caribbean Network (SFCN). Photo-interpretation on the map was performed by superimposing a 50 × 50-meter (164 × 164-feet [ft] or 0.25 hectare [0.61 ac]) grid cell vector matrix over stereoscopic, 30 centimeters (11.8 inches) spatial resolution, color-infrared aerial imagery, acquired by the SFWMD in 2009, on a digital photogrammetric workstation. Photo-interpreters identified the dominant community in each cell by applying majority-rule algorithms, recognizing community-specific spectral signatures, and referencing an extensive ground-truth database. The dominant vegetation community within each grid cell was classified using a hierarchical classification system developed for this project. Additionally, photo-interpreters categorized the absolute cover of invasive species and cattails (Typha sp.) detected as either: Sparse (10–49%), Dominant (50–89%), or Monotypic (90–100%).

The surface elevation table (SET)-marker horizon (MH) approach (SET-MH, together) is a method for quantifying surface elevation change through measurements of surface and subsurface processes that control wetland soil elevation. This dataset combines SET-MH data from five different U.S. Geological Survey efforts to monitor surface elevation change in the coastal wetlands of the Greater Everglades region of south Florida. Data from these efforts have been used in the publications by Cahoon and Lynch (1997), Whelan et al. (2005, 2009), Smith et al. (2009), McKee (2011), Breithaupt et al. (2020), Feher et al. (2020), Howard et al. (2020), and Osland et al. (2020). Although some of these data have previously been released on ScienceBase as individual datasets (see Feher et al. 2019, Howard et al. 2019, Cormier et al. 2020, and Lynch et al. 2020), the dataset presented here combines these individual data releases into one single product and also includes new data that were collected after the original release of these data. These data were combined with additional SET-MH data provided by collaborators at the South Florida Water Management District, Florida International University, U.S. Fish and Wildlife Service, and U.S. National Park Service to provide a regional synthesis of available data regarding surface elevation change dynamics in coastal wetlands of the Greater Everglades.

The Everglades Depth Estimation Network (EDEN) produces daily depth estimates for the Greater Everglades. This data release includes geospatial data to produce depth estimates for the EDEN from updated digital elevation models. The data release includes three main types of data: 1) 10-m digital elevation models (DEMs) with elevation uncertainty treatment; 2) 50-m DEMs with elevation uncertainty treatment; and 3) spatial metadata for the DEMs used. Specifically, this dataset includes accuracy information by zone. These data address elevation error by using Monte Carlo simulations with 1,000 iterations with observations of elevation error in vegetated wetlands and assumptions error in vegetated non-wetland areas and non-vegetated areas. On a per-pixel basis, we created raster surfaces that represented the minimum elevation, maximum elevation, and percentiles (1 to 99). We determined the “best” elevation percentiles for each EDEN zone (Haider and others, 2020) based on the mean bias error, which was calculated for the difference between the USGS high-accuracy elevation dataset (HAED; Jones and Price, 2007) and the DEM. In this case, the percentile DEM with the mean bias error closest to zero for each zone was selected. All zones were combined to create a seamless mosaic. For each zone, upper and lower elevation estimates were determined based on a general rule that selected the percentile that was the farthest from the “best” percentile but had a mean bias error that was within (+/-) 5 cm. Areas in lower and upper estimate DEMs that have “NoData” values indicate that the there was no percentile that could be used to satisfy this rule. For example, a zone may not have a lower estimate if the “best” estimate was the minimum raster. A zone may not have an upper estimate if the next percentile had a mean bias error that was greater than 5 cm.

Mangrove inventory data from J.N. Ding Darling National Wildlife Refuge, Sanibel Island, Florida, USA collected in 2016 and 2017. Plot data includes X and Y downed dead wood count, mangrove species information and site descriptions. Tree data includes the three species found on the refuge: Avicennia germinans (Black mangroves), Laguncularia racemosa (White mangroves) and Rhizophora mangle (Red mangroves). They were inventoried for diameter at breast height (DBH), height, and dead status.

The Comprehensive Everglades Restoration Plan (CERP) requires the use of ecological indicators to measure the success of restoration efforts. The Everglades amphibian community is ideal because amphibians are present in all habitats and under all hydrologic regimes. During Everglades restoration, hydrologic patterns will change and the response of ecological indicators will determine success. Fourteen amphibian species were detected through visual encounter surveys, vocalization surveys and trapping methods throughout the study and the occurrence information collected in this project database.

The Comprehensive Everglades Restoration Plan (CERP) requires the use of ecological indicators to measure the success of restoration efforts. The Everglades amphibian community is ideal because amphibians are present in all habitats and under all hydrologic regimes. During Everglades restoration, hydrologic patterns will change and the response of ecological indicators will determine success. Fourteen amphibian species were detected through visual encounter surveys, vocalization surveys and trapping methods throughout the study and the occurrence information collected in this project database.