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).
SECOND_STRUCTURE_NUMBER_IF_APP
(
type: esriFieldTypeDouble, alias: Second Structure Number
)
CLEAR_ZONE_WIDTH_FACING_S_OR_W
(
type: esriFieldTypeDouble, alias: Clear Zone Width (Facing S or W) (In Feet)
)
CLEAR_ZONE_VEGETATION_FACING_S
(
type: esriFieldTypeString, alias: Clear Zone Vegetation (Facing S or W), length: 255
, Coded Values:
[Grass_and_Shrubs: Grass and Shrubs]
, [Open_Grass_or_Other_Ground_Cove: Open Grass or Other Ground Cover]
, [Shrub_and_Tree_Cover: Shrub and Tree Cover]
, ...2 more...
)
MEDIAN_WIDTH_IN_FEET
(
type: esriFieldTypeDouble, alias: Median Width (In Feet)
)
FENCE_TYPE_FACING_S_OR_W
(
type: esriFieldTypeString, alias: Fence Type (Facing S or W), length: 255
, Coded Values:
[Chain_Link: Chain Link]
, [Farm_or_Field: Farm or Field]
, [Specialized_Wildlife: Specialized-Wildlife]
, ...2 more...
)
FENCE_TYPE_FACING_S_OR_W__OTHE
(
type: esriFieldTypeString, alias: Other - Fence Type (Facing S or W), length: 255
)
FENCE_HEIGHT_FACING_S_OR_W_IN_
(
type: esriFieldTypeDouble, alias: Fence Height (Facing S or W) (In Feet)
)
GENERAL_SUITABILITY
(
type: esriFieldTypeString, alias: General Suitability, length: 1000
)
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
Description: The Florida panther (Puma concolor coryi) mortality database contains all known and documented mortalities including known or likely causes. For source dates and inputs see metadata.
Description: This dataset contains the locations of Florida black bear (Ursus americanus floridanus) road mortality locations within the state of Florida that are contained in a database maintained by the Florida Fish and Wildlife Conservation Commission (FWC). In this shapefile, we used only those records maintained by the FWC from which we could obtain a geographic coordinate.
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
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)
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
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 for 4 large animal species (Florida panther, Florida black bear, white-tail deer, and American alligator). 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 2020), Florida black bear road mortality locations (FWC 2020), and reported accidents involving an animal (FDOT 2020). Florida panther and black bear mortalities were weighted at 1.4 and 1.2 respectively to reflect their conservation priority and highway safety risk. The 2020 roads base layer used in the analysis was obtained from FDOT. For detailed information on the analysis, please see this report: https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/HotspotsAnalysisFinalMethodsandResults10.19.21.pdf
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 for 4 large animal species (Florida panther, Florida black bear, white-tail deer, and American alligator). 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 2020), Florida black bear road mortality locations (FWC 2020), and reported accidents involving an animal (FDOT 2020). Florida panther and black bear mortalities were weighted at 1.4 and 1.2 respectively to reflect their conservation priority and highway safety risk. The 2020 roads base layer used in the analysis was obtained from FDOT. For detailed information on the analysis, please see this report: https://www.geoplan.ufl.edu/agol/pdf/Animal_Vehicle_Collisions/HotspotsAnalysisFinalMethodsandResults10.19.21.pdf
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
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
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
Description: This data set represents small animal-vehicle collision road hotspots on roadways in wetland habitats presented at a statewide coarse-scale. 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
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
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
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
Description: This data set contains the United States Fish and Wildlife Service Lower Keys Marsh Rabbit Consultation Area. Please refer to the Ecological Services Office website responsible for your area of interest for current information on this species: South Florida ESO (SF ESO): http://www.fws.gov/verobeach/ North Florida ESO (NF ESO): http://www.fws.gov/northflorida/ Panama City ESO (PC ESO): http://www.fws.gov/PanamaCity/
Description: This data set contains the United States Fish and Wildlife Service Key Deer Consultation Area. Please refer to the Ecological Services Office website responsible for your area of interest for current information on this species: South Florida ESO (SF ESO): http://www.fws.gov/verobeach/ North Florida ESO (NF ESO): http://www.fws.gov/northflorida/ Panama City ESO (PC ESO): http://www.fws.gov/PanamaCity/
Description: This dataset contains the United States Fish and Wildlife Service Florida Panther Consultation Area. Please refer to the Ecological Services Office website responsible for your area of interest for current information on this species: South Florida ESO (SF ESO): http://www.fws.gov/verobeach/ North Florida ESO (NF ESO): http://www.fws.gov/northflorida/ Panama City ESO (PC ESO): http://www.fws.gov/PanamaCity/