Geodesign Technologies conducted an initial assessment of the development likelihood and conservation priority for the Everglades Headwaters National Wildlife Refuge and Conservation Area study region in central Florida. Geodesign used two prior analyses as the basis for this assessment, both of which are at a statewide Florida scale. The University of Florida's CLIP3 (Critical Lands and Waters Identification Project 3.0; Oetting et. al 2014) was the basis for the biodiversity assessment, and their prior statewide scenario simulations (Vargas et al. 2014) were used as an indicator of likelihood of development under a suite of divergent statewide policies. References: 1. Oetting, J., T. Hoctor, and M. Volk. 2014. Critical Lands and Waters Identification Project (CLIP): Version 3.0. Technical Report - February 2014. 110 pp. 2. Vargas, J.C., Flaxman, and B. Fradkin. 2014. Landscape Conservation and Climate Change Scenarios for the State of Florida: A Decision Support System for Strategic Conservation. Summary for Decision Makers. GeoAdaptive LLC, Boston, MA and Geodesign Technologies Inc., San Francisco CA. 22 pp.

Geodesign Technologies conducted an initial assessment of the development likelihood and conservation priority for the Everglades Headwaters National Wildlife Refuge and Conservation Area study region in central Florida. Geodesign used two prior analyses as the basis for this assessment, both of which are at a statewide Florida scale. The University of Florida's CLIP3 (Critical Lands and Waters Identification Project 3.0; Oetting et. al 2014) was the basis for the biodiversity assessment, and their prior statewide scenario simulations (Vargas et al. 2014) were used as an indicator of likelihood of development under a suite of divergent statewide policies. References: 1. Oetting, J., T. Hoctor, and M. Volk. 2014. Critical Lands and Waters Identification Project (CLIP): Version 3.0. Technical Report - February 2014. 110 pp. 2. Vargas, J.C., Flaxman, and B. Fradkin. 2014. Landscape Conservation and Climate Change Scenarios for the State of Florida: A Decision Support System for Strategic Conservation. Summary for Decision Makers. GeoAdaptive LLC, Boston, MA and Geodesign Technologies Inc., San Francisco CA. 22 pp.

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%).

Restoration of the Florida Everglades, a substantial wetland ecosystem within the United States, is one of the largest ongoing restoration projects in the world. Decision-makers and managers within the Everglades ecosystem rely on ecological models forecasting indicator wildlife response to changes in the management of water flows within the system. One such indicator of ecosystem health, the presence of wading bird communities on the landscape, is currently assessed using three species distribution models that assume perfect detection and report output on different scales that are challenging to compare against one another. We sought to use current advancements in species distribution modeling to improve models of Everglades wading bird distribution. Using a joint species distribution model that accounted for imperfect detection, we modeled the presence of nine species of wading bird simultaneously in response to annual hydrologic conditions and landscape characteristics within the Everglades system. Our resulting model improved upon the previous model in three key ways: 1) the model predicts probability of occupancy for the nine species on a scale of 0-1, making the output more intuitive and easily comparable for managers and decision-makers that must consider the responses of several species simultaneously; 2) through joint species modeling, we were able to consider rarer species within the modeling that otherwise are detected in too few numbers to fit as individual models; and 3) the model explicitly allows detection probability of species to be less than 1 which can reduce bias in the site occupancy estimates. These improvements are essential as Everglades restoration continues and managers require models that consider the impacts of water management on key indicator wildlife such as the wading bird community.

Restoration of the Florida Everglades, a substantial wetland ecosystem within the United States, is one of the largest ongoing restoration projects in the world. Decision-makers and managers within the Everglades ecosystem rely on ecological models forecasting indicator wildlife response to changes in the management of water flows within the system. One such indicator of ecosystem health, the presence of wading bird communities on the landscape, is currently assessed using three species distribution models that assume perfect detection and report output on different scales that are challenging to compare against one another. We sought to use current advancements in species distribution modeling to improve models of Everglades wading bird distribution. Using a joint species distribution model that accounted for imperfect detection, we modeled the presence of nine species of wading bird simultaneously in response to annual hydrologic conditions and landscape characteristics within the Everglades system. Our resulting model improved upon the previous model in three key ways: 1) the model predicts probability of occupancy for the nine species on a scale of 0-1, making the output more intuitive and easily comparable for managers and decision-makers that must consider the responses of several species simultaneously; 2) through joint species modeling, we were able to consider rarer species within the modeling that otherwise are detected in too few numbers to fit as individual models; and 3) the model explicitly allows detection probability of species to be less than 1 which can reduce bias in the site occupancy estimates. These improvements are essential as Everglades restoration continues and managers require models that consider the impacts of water management on key indicator wildlife such as the wading bird community.

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models, web applications, and decision support tools that generates daily water-level data and derived hydrologic data across the freshwater part of south Florida's Greater Everglades. EDEN provides continuous daily water-level and depth surfaces on a 400-meter grid using an interpolation algorithm, a network of over 200 gaging stations, and a digital elevation model (DEM). The water-level surfaces cover an area of 9,132 square kilometers and the water depth surfaces cover an area of 7,491 square kilometers. For a subset of gaging stations, ground elevation measurements were taken to better understand the elevation in the area surrounding the gaging station. The mean, maximum, and minimum ground elevation measurements are provided for the area within a 10-meter radius of the water level gaging station. The major vegetation community type was also recorded. Within a 400-meter radius, a secondary vegetation community type was recorded when possible, along with mean, maximum, and minimum ground elevation measurements.

Mid-sized mammals (i.e., mesomammals) fulfill important ecological roles, serving as essential scavengers, predators, pollinators, and seed dispersers in the ecosystems they inhabit. Consequently, declines in mesomammal populations have the potential to disrupt ecological processes and degrade ecosystems. However, ecosystems characterized by high functional redundancy, where multiple species can fulfill similar ecological roles, may be less impacted by the loss of mesomammals and other vertebrates. The Greater Everglades Ecosystem in southern Florida is a historically biodiverse region that has recently been impacted by multiple anthropogenic threats, most notably the introduction of the Burmese python (Python bivittatus). Since pythons became established, mesomammal populations have become greatly reduced. To assess whether these declines in mesomammals have affected two critical ecosystem functions—scavenging and frugivory—we conducted experiments in areas where mesomammals were present and absent. After passive sampling had concluded at each site, we conducted scavenging and frugivory experiments to quantify how mesomammal presence affected frugivory and scavenging rates. To assess these processes, we monitored the persistence of carrion and fruit using motion triggered cameras. We reviewed photos to identify species and determine if they consumed carrion/fruit. To quantify scavenging rates, we secured carrion to a 40 x 40 cm board at each station and recorded detection time (the elapsed time between deployment and the first scavenger’s arrival) and consumption time (the elapsed time between deployment and the complete consumption of the carcass).

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).

The Everglades National Park and Big Cypress National Preserve 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’s (NPS) Vegetation Mapping Inventory Program (VMI). The goal of this project is to produce a spatially and thematically accurate vegetation map of Everglades National Park and Big Cypress National Preserve 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 these two federally-managed units 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 park management, resource management, research, and monitoring. This mapping 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 National Park, Regions 1–4, and three in Big Cypress National Preserve, Regions 5–7. The report focuses on the mapping effort associated with the Northwest Coastal Everglades (NWCE), Region 4 , in Everglades National Park. The NWCE encompasses a total area of 1,278 square kilometers (493.7 square miles [sq mi], or 315,955 ac) and is geographically located to the south of Big Cypress National Preserve, west of Shark River Slough (Region 1), and north of the Southwest Coastal Everglades (Region 3). Photo-interpretation 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 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 specifically for this project. Additionally, photo-interpreters categorized the absolute cover of cattail (Typha sp.) and any invasive species detected as either: Sparse (10–49%), Dominant (50–89%), or Monotypic (90–100%). A total of 178 thematic classes were used to map the NWCE. The most common vegetation classes are Mixed Mangrove Forest-Mixed and Transitional Bayhead Shrubland. These two communities accounted for about 10%, each, of the mapping area. Other notable classes include Short Sawgrass Marsh-Dense (8.1% of the map area), Mixed Graminoid Freshwater Marsh (4.7% of the map area), and Black Mangrove Forest (4.5% of the map area). The NWCE vegetation map has a thematic class accuracy of 88.4% with a lower 90th Percentile Confidence Interval of 84.5%.

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%.