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Layer: FDOT Wildlife Crossings (0)

Name: FDOT Wildlife Crossings

Display Field: NAME

Type: Feature Layer

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Description: This dataset contains the midpoint of a wildlife facility that crosses under or over a roadway. It provides spatial locations of wildlife roadway crossings and the purpose and physical characteristics such as the target species, type of crossing (e.g., bridge, culvert), dimensions, and additional location information. This data represents the information collected and reported as of the most recent inventory performed and may not reflect the current conditions.

Copyright Text: Florida Department of Transportation (FDOT), Office of Environmental Management

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Layer: FDOT Panther Crossing Sign Locations (1)

Name: FDOT Panther Crossing Sign Locations

Display Field: NAME

Type: Feature Layer

Geometry Type: esriGeometryPoint

Description: This dataset contains the location of panther related signage along Florida roadways. The signs represent panther warnings, nighttime speed zone signs, and select bear crossing sign locations. The data includes only existing signs.

Copyright Text: Florida Department of Transportation

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Layer: FWC Bear Crossing Sign Locations (2)

Name: FWC Bear Crossing Sign Locations

Display Field: COUNTY

Type: Feature Layer

Geometry Type: esriGeometryPoint

Description: This shapefile contains the locations of bear crossing signs throughout Florida, as of June 2019. The data were obtained from a conbination of FDOT (Florida Department of Transportation) and FWC (Florida Fish and Wildlife Conservation Commission) field staff.

Copyright Text: Bethan Roberts (FWC Bear Management Program)

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Layer: FWC Bear Fencing Opportunities (3)

Name: FWC Bear Fencing Opportunities

Display Field: STREET_NAME

Type: Feature Layer

Geometry Type: esriGeometryPoint

Description: This dataset contains priority bridge locations based on vehicle-bear collisions. The FWC examined the location of vehicle-bear collisions that occurred between 2012 and 2016 to determine where high-density concentrations, or ‘hotspots’, of collisions were consistently occurring to identify specific areas for potential mitigation measures. The FWC used FDOT bridge data to identify all existing bridges within 100 meters of a hotspot. These 350+ bridges were then examined by FWC staff through aerial imagery and the “street view” function on Google Earth to identify those with the potential to become wildlife underpasses. FWC identified 28 bridges statewide with the potential to act as wildlife underpasses in areas where vehicle-bear collisions are common. Many of the bridges identified are near or within wildlife conservation areas. The FWC classified each of the 28 potential bridges into one of three categories based on priority, including ‘high’, ‘moderate’, and ‘low’ priority levels based on the bridge’s proximity to the 1 km and 5 km hotspot locations throughout the state. For more information, please see this report: https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/FWC_DOT%20_Underpass_%20Fencing_Proposal_FINAL.pdf

Copyright Text:

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Layer: Crossing Opportunities at Large Animal Hotspots (4)

Name: Crossing Opportunities at Large Animal Hotspots

Display Field: ROAD_NAME_NUMBER

Type: Feature Layer

Geometry Type: esriGeometryPoint

Description: The large animal-vehicle collision hotspots come from a statewide Animal-Vehicle Collisions Hotspot Analysis that was performed for FDOT in 2022. The analysis calculated average number of incidences (animal-vehicle collisions) per one mile road segment and distance from the mean to determine relative level of significance. The analysis was performed using the ArcGIS (ESRI, Inc), Getis-Ord Gi Hotspot Analysis Tool. Hotspots were placed in three tiers of relative significance (based on confidence levels): Top 1% (99%), Top 5% (95%), Top 10% (90%). Each structure contained in this data layer was evaluated in the field for suitability as a large animal wildlife crossing. We used ArcGIS Survey123 to record data collected in the field. The evaluation included assessments of site characteristics including structure dimensions, fencing, vegetation, substrate, adjacent land use/cover and signs of animal use. Detailed notes were taken in many cases. This information was used to rank the general suitability of each structure to function as a large animal wildlife crossing (categories: high, moderate, low).

Copyright Text:

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Layer: Wildlife Permeability Along Interstate 4 (PRIT) (5)

Name: Wildlife Permeability Along Interstate 4 (PRIT)

Display Field: NAME

Type: Feature Layer

Geometry Type: esriGeometryPolyline

Description: This dataset contains large mammal permeability across the I-4 transportation corridor. This data is based on the Transportation SubTeam Report to Florida Panther Recovery Implementation Core Team and US Fish and Wildlife Service. For the report, please see this link: https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/I-4_Wildlife_Permeability_report_final.pdf

Copyright Text: Transportation SubTeam Report to Florida Panther Recovery Implementation Core Team and US Fish and Wildlife Service

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Layer: Florida Panther Least Cost Paths (6)

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Description: This dataset contains lines representing the output of a Least Cost-Path (LCP) analysis for the Florida Panther within South-Central Florida. This layer is meant to be used in conjunction with the FGDL layer FLORIDA_PANTHER_CORRIDORS_DEC22.

Copyright Text: University of Central Florida, Dept. of Biology, Science and Planning in Conservation Ecology (SPICE) Lab

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Description: This dataset contains polygons representing the output of a Least Cost-Corridor (LCC) analysis for the Florida Panther within South-Central Florida. This layer was developed by the University of Central Florida for the U.S. Fish and Wildlife Service and the Florida Panther Recovery Implementation Team. The aim of this data is to identify potential pathways and corridors that panthers are likely to use under existing land cover/land use conditions from the current species core range (south of the Caloosahatchee River) to large habitat hubs north of Interstate 4 (The Green Swamp and Ocala National Forest). The focus is on predicted panther movements and natural range expansion within the south-central Florida region.

Copyright Text: University of Central Florida, Dept. of Biology, Science and Planning in Conservation Ecology (SPICE) Lab

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Layer: Southwest Florida Road Hot Spots (PRIT) (8)

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Description: This dataset contains Florida Panther vehicle collisions (PVC) hot spots. This data is a selection of panther vehicle collisions from the Florida Fish and Wildlife Conservation Commission (FWC) Panther Mortality and Injury Master List for all years of available data. For more information on this dataset, please see this document: https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/2021_Hot_Spot_Update_Summary_submittal.pdf

Copyright Text: Florida Department of Transportation

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Layer: Panther and Bear Vehicle Collision Hotspot Analysis (9)

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Description: This dataset contains large animal-vehicle collisions (AVCs) hotspots by Florida Department of Transportation District. The analysis calculates average number of AVC incidences per one mile road segment and distance from the mean to determine relative level of significance. It's based on an evaluation of available crash data, from the FWC, for 2 large animal species (Florida panther, Florida black bear). Using the ArcGIS (ESRI, Inc), Getis-Ord Gi Hotspot Analysis Tool, three tiers of relative significance (based on confidence levels) were identified: Top 1% (99%), Top 5% (95%), Top 10% (90%). Data sources used in the analysis include: Florida panther road mortality locations (FWC 2025) and Florida black bear road mortality locations (FWC 2025). Florida panther and black bear mortalities were weighted at 1.4 and 1.2 respectively to reflect their conservation priority and highway safety risk.

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Layer: Small Animal Upland (Fine Scale) (11)

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Description: This data set represents small animal-vehicle collision road hotspots on roadways in upland habitats presented at fine-scale. This layer is a result of merging district level fine-scale layers into 1 statewide layer. The analysis used Florida Fish and Wildlife Conservation Commission (FWC) species-habitat predictive models to identify and rank the likelihood of the presence of representative small animal upland species. Results were presented using a buffered, one-mile, road-segment base layer. The following 9 representative species predictive models: Florida mouse, Eastern diamondback rattlesnake, stern indigo snake, Florida pine snake, Southern hognose snake, Florida gopher frog, Flatwoods salamander, Striped newt, Tiger salamander. Gopher tortoise (an affinity +/- model was used for coarse validation). The predictive models rank potential habitat suitability on a continuous scale from 0 to 1, with one representing the highest probability. For detailed information on the analysis, please see this report: https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/Small_Animal_Uplands_Road_Hotspots_Model.pdf

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Description: This data set represents small animal-vehicle collision road hotspots on roadways in wetland habitats presented at fine-scale. This layer is a result of merging district level fine-scale layers into 1 statewide layer. The analysis used data layers of important aquatic and wetland resources vital for sustaining populations of wetland and aquatic species. The intent was to use the resource data layers to indicate locations where road conflicts are most likely to occur. Results were presented using a buffered, one-mile, road-segment base layer. Using ArcGIS (ESRI, Inc) we performed the analysis on the following Florida Natural Areas Inventory (FNAI) resource data: Significant Surface Waters, Functional Wetlands, Natural Floodplain. These data layers were created as part of the Florida Forever Conservation Needs Assessment and establish conservation priorities for each respective resource type. These layers provide a scale and means of ranking liklihood of presence of important wetland and aquatic species that may be adversely impacted by roads: Relative water resource quality, Potential habitat suitability, Priorities for conservation. For more detailed descriptions of these data layers, visit FFCNA_TechReport_v4_4.pdf (fnai.org). Observation point data (American Alligator and American Crocodile) and Affinity (+/-) habitat models (Alligator, Crocodile, River Otter, Spotted Turtle) were used for coarse validation of the results. https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/Small_Animal_Wetlands_Road_Hotspots_Model.pdf

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Layer: Small Animal Upland (Coarse Scale) (13)

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Description: This data set represents small animal-vehicle collision road hotspots on roadways in upland habitats presented at a statewide coarse-scale. The analysis used Florida Fish and Wildlife Conservation Commission (FWC) species-habitat predictive models to identify and rank the likelihood of the presence of representative small animal upland species. Results were presented using a buffered, one-mile, road-segment base layer. The following 9 representative species predictive models: Florida mouse, Eastern diamondback rattlesnake, stern indigo snake, Florida pine snake, Southern hognose snake, Florida gopher frog, Flatwoods salamander, Striped newt, Tiger salamander. Gopher tortoise (an affinity +/- model was used for coarse validation). The predictive models rank potential habitat suitability on a continuous scale from 0 to 1, with one representing the highest probability. For detailed information on the analysis, please see this report: https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/Small_Animal_Uplands_Road_Hotspots_Model.pdf

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