SE-GAP Vertebrate Predicted Habitat

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Originator: Southeast Gap Analysis Project
Publication_Date: 20100401
Title: SE-GAP Vertebrate Predicted Habitat
Geospatial_Data_Presentation_Form: raster digital data
Biodiversity and Spatial Information Center, North Carolina State University, Raleigh, North Carolina 27695
Alabama Gap Project, Alabama Cooperative Fish & Wildlife Research Unit, Auburn University, Alabama 36839
Spatial Analysis Laboratory, University of Georgia, Athens Georgia 30602
Edition: 1.0
Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog
This raster map represents the presence/absence of predicted habitat of a single terrestrial vertebrate species. Since it is one of 602 species whose predicted distributions were modeled by SE-GAP, the processes used to create this raster map may differ from other species in this dataset. Processes were unique because while a majority of models incorporated land use/land cover data as the primary input, several other environmental features were incorporated for specific species depending on life history and habitat requirements noted both in published literature and expert review with biologists.
This data set was developed by the Southeast GAP Analysis Project to be used as a coarse filter in determining the location of species' habitats in the Southeast United States for conservation planning purposes. Seasonal known ranges for 602 vertebrate species (131 amphibians, 253 birds, 95 mammals and 123 reptiles) were modeled by SE-GAP based on existing state, regional and national references. This data was prepared in compliance with the National GAP effort.
Southeast Gap Analysis Predicted Habitat Development
One of the major objectives of the National GAP program is to document the representation of native vertebrate species in regional assesments. In order to meet this objective, we developed a spatial database of predicted species distributions throughout the region. While we don't have the resources to conduct a complete survey for every species, we do have access to a tremendous knowledge base that allows us to model distrubutions based on known range and habitat relationships.
The composition and structure of the dominant vegetation is an important and easily described measure of habitat for animals (Scott et al. 1993) and has long been used as an indirect indicator of animal distributions (Austin 1991). Other biotic and abiotic factors (i.e. elevation, wetland type, and distance from standing water) can also play a major role in defining a particular species' habitat. Many studies of vertebrate species have been conducted over the years documenting this type of information. In addition, data on known ranges for vertebrate species has also been collected. This includes not only survey data records, but the cumulative field experiences of biologists who work with these species on a daily basis. If we take a habitat description, break it down into vegetative communities and other environmental factors (e.g. elevation, wetland type, etc.), and then identified those areas within a known range, we would be creating a predicted distribution map. That is essentially what we did for each terrestrial vertebrate species modeled in the Southeast. The final step was to overlay those maps together to get a representation of biodiversity.
Why did we model only terrestrial vertebrates? Again, its a matter of resources. Realistically, we can only model a subset of all species. Terrestrial vertebrates are a logical choice because we generally know more about their habitat relationships and range extents than those of other taxa. Even so, there are over 600 terrestrial vertebrates modeled. The key to filling in the 'gaps' in the documented data is to have a thorough review by experts at every stage.
Species List Development Selection Criteria
Gap Analysis predicted distribution maps are being created for all vertebrate species that breed in the Southeastern U.S. or use habitat there for an important part of their life history. Decisions were made on which species' habitats will be mapped based on standard Gap Analysis guidelines. Species lists have been created for each of the southeastern states by state-level Gap projects; these lists were compiled and pared down to remove some subspecies and domesticated species. Subspecies were only included when supported as distinct and non-overlapping with either the full species or other subspecies. The final list includes amphibians, mammals, reptiles, breeding birds, and wintering waterfowl.
After review, 602 species remained for habitat modeling: 131 Amphibian species, 253 Avian species, 95 Mammalian species, and Reptilian species.
Predictive Modeling of Habitat
Models of presence/absence for a species' predicted distribution may include a number of spatially explicit data sources. GAP models typically involve land use/land cover data as the primary input. However, other environmental features that make up the landscape constituting species' habitats can be valuable inputs to modeling. The SE-GAP project has attempted to use a number of data layers (ancillary data) other than land cover to develop species models. Many of these data layers act as surrogates for one or more aspects of a species' habitat that may only be inferred from available, remotely sensed information. The following document is meant to describe these data layers and their development, their range of parameters, and usage in modeling species' predicted distributions.
NOTE: The term "map unit" will be used throughout the document to mean the individual class or category mapped to represent land use and land cover, i.e. ecological systems.
Developing Known Range
All 602 terrestrial vertebrate species' geographic range extents were delineated as single or multiple polygons. Migratory species were primarily represented by breeding season ranges, however, wintering ranges for waterfowl and migratory bats were also delineated (33 species) Processes used to create range polygons were unique because information on the current geographic range of a species varies widely. However, a generalized approach used a variety of sources to develop species' ranges including sources of information in two broad categories: 1) species location records and range maps available digitally or in print, and 2) digital spatial data of environmental parameters described in later sections of this document.
Usage in Modeling
Species ranges were used as model delimiters in predicted distribution models.
Land Cover Development
Ecological systems and land use mapped for the SE-GAP project are the primary input to species models. The development of these data is described in detail in subsequent documents. However, derivatives of these data were developed separately to further refine species models.
Primary and secondary (auxiliary) map units, and patch size (contiguous and non-contiguous patches) are parameters utilized as a model proceeds. That is, they are not stand-alone, independently created data layers. As such, they would not be considered "ancillary" data.
Usage in Modeling Primary & Secondary Map Units
Primary map units are those land cover types critical for nesting, rearing young, and/or optimal foraging.
Secondary or auxiliary map units are those land cover types generally not critical for breeding, but are typically used in conjunction with primary map units for foraging, roosting, and/or sub-optimal nesting locations. These map units are selected only when located within a specified distance from primary map units.
Patch Size The type and size of clusters of habitat can be assessed with spatial modeling. As a final step to the distribution modeling process, we used these parameters for species shown to require minimum amounts of habitat. This includes not only directly adjacent habitats, but those that are contextually adjacent. Both these parameters are utilized as the final step in a predicted distribution and therefore incorporate all other modeling inputs.
Contiguous Patch Minimum Size (ha) - This parameter is set using the most conservative values explicitly stated in the literature. It applies only to the Southeastern portion of a species' range. FROM Buffer - 0, 30, 60, 120, 250, 500, 1000 meters. TO Buffer - 0, 30, 60, 120, 250, 500, 1000 meters.

Non-Contiguous Patch The non-contiguous patch parameter is used to imply landscape context, i.e utilized habitats within a matrix of other habitats. It is measured as a percentage within a given area.
Forest & Edge Habitats
The edge or ecotone between forested and non-forested environments can be a critical aspect of the habitat landscape. We grouped map units into forested, non-forested, and shrubland/woodland land cover types to create unique data layers. These data layers can then be buffered at specified distances to identify species' habitats. Development
All map units categorized as forest, non-forest, and shrubland/woodland were aggregated into separate data layers. Aggregated map units can be compared and contrasted to identify areas of transition between these broad categories. They can also be used to identify "core" areas or contiguous blocks of similar type (i.e. interior) through buffering procedures.
Forested map units were defined as those ecological systems and land uses that correspond to the National Land Cover Dataset (NLCD) forest/woodland classes (Homer et al. 2004) (Appendix A). These included NLCD classes "deciduous forest", "evergreen forest", "mixed forest", "palustrine forested wetland", and "estuarine forested wetland" (class values 41, 42, 43, 91 and 93 respectively). Non-forested map units were defined as those ecological systems and land uses not categorized as forest using the criteria stated above. Woodland/shrubland map units were defined as those ecological systems and land uses containing a majority of short, scrubby, woody vegetation or sparsely canopied treed vegetation (Appendix B). Unlike the forested map units, the woodland/shrubland layer was not explicitly derived from NLCD classes but was selected individually based on attributes defined by the systems and land uses.
Once these data layers were created, buffering procedures created unique datasets containing unique categories of distance: > 4000, 4000, 2000, 1000, 500, 250, 120, 60, and 30 meters into and away from the specified feature.
Usage in Modeling
Forest Interior This data layer constitutes unique aggregations of forest and non-forest map units. Non-forest map units include water, pasture/hay, agricultural areas, urban/developed, marshes, beaches, etc... Utilizes Forest Interior - For species that require interior forest. Buffer distances must be identified to utilize this input. Avoids Forest Interior - For species that avoid interior forest. Buffer distances must be identified to utilize this input. FROM Buffer - 0, 30, 60, 120, 250, 500, 1000, 2000, 4000, and 9999 (> 4000 m) INTO Buffer - 0, 30, 60, 120, 250, 500, 1000, 2000, 4000, and 9999 (> 4000 m)
Edge/Ecotone Type & Width Forest/Open Ecotone Only - This data layer represents the transitional areas between forest and open, non-forested habitats. Open, non-forested habitats include water, pasture/hay, prairies, agricultural areas, urban/developed, marshes, beaches, etc... Forest/Open Ecotone + Woodlands/Shrublands - The forest/open only ecotone does not consider environments with sparse canopies or scrubby vegetation. In order to account for these additionally complex ecotones, this data layer includes woodland and shrubland map units that would otherwise be ignored. Ecotone Width - This distance represents a swath of symmetrically buffered edge. The parameter is measured in increments of 0, 30, 60, 120, 250, 500, and 1000 meters. For example, an ecotone width of 500 meters includes 250 meters into forest and 250 meters into open).
Hydrologic Unit Codes (HUCs) Development
The HUC is part of a hierarchical classification system for surface water drainage in the US (Seaber et al. 1987). The numerical code represents a "cataloging unit" of delineation approximately larger than 1800 square kilometers. Within the SE-GAP project boundary there are 577 8-digit HUCs. Vector format (i.e. polygon) data were compiled from United States Geological Survey (USGS) sources. No ancillary data was produced directly from HUCs, but they were utilized in numerous other ancillary data layer processes. Most notably, HUCs allow for partitioned processing when scripting complex spatial analysis tasks.
Usage in Modeling
HUCs were not used directly in species modeling. However, some species' geographic ranges were developed using the 8-digit hydrologic unit code polygons. This was only appropriate for species whose ranges would conceivably be limited to certain watershed drainages and their associated topographic distinctions. In most cases, these species were partially or entirely aquatic during some part of their life history (e.g. salamanders, turtles).
Ecoregions Development
Ecoregions developed by Omernik (1987, 1995) and available from the U.S. Environmental Protection Agency (US EPA 2007) were produced through an analysis of biotic and abiotic patterns relating to ecosystem differentiation. Although no ancillary date were created directly from ecoregions, they were utilized in numerous other primary and ancillary data layer processes including land cover/ecological systems, species' ranges, and landforms.
Usage in Modeling
Ecoregions were not used explicitly in predicted distribution models. However, Omernik Level III and Level IV ecoregions were used to help define polygon boundaries for some species' geographic ranges when appropriate. Some species are clearly restricted to the physiographic and geographic patterns and boundaries that ecoregions define. For these species, ecoregions were used as all or a portion of the polygon(s) delineation. If there was a doubt as to the limitations imposed by such boundaries, ecoregions were not used.
Soils Development
State geographic soils database (STATSGO) soil units polygons were developed by the U.S. Department of Agriculture's Natural Resource Conservation Service (NRCS) at a scale of 1:250,000 for the conterminous U.S. (USDA 1995). Although no ancillary date were created directly from soils, they were utilized in numerous other primary and ancillary data layer processes including land cover/ecological systems, species' ranges, and landforms.
Usage in Modeling
Soils were not used explicitly in predicted distribution models. However, soils were used to help define polygon boundaries for some species' geographic ranges when appropriate. Although ecoregions consider soils as an abiotic factor in their delineation, for certain species it was necessary to focus more narrowly on soil type to help define a range polygon. For species whose habitat requirements are restricted to certain soil types (particularly some reptiles), soil polygons were used to help delineate all or a portion of their range.
Roads Development
Roads data were compiled from the U.S. Census Bureau's TIGER/Line files (USCB 2007). As a preliminary and stand alone layer, road density grids were created so that they could be used for production of imperious surface data layers and, by proxy, land cover/land use map units, as well as in production of an avoidance mask for vertebrate modeling. Part of the procedure to develop road density required the summarization of the attribute code 'CFCC' within the TIGER database (see technical documentation for TIGER/Line files at the URL listed in the Literature Cited section for more information). In general, seven codes were combined into three road category types. A line density algorithm was used to calculate the linear length of roads within a circular neighborhood. The algorithm utilized a kernel smoothing function on a 30 meter cell size within a 564.19 meter radius (1 km2).
Usage in Modeling
Roads were not used explicitly in predicted distribution models. However, the road density data layer derived from roads was used to develop an avoidance mask as an index to human disturbance (see Urban).
Elevation Development
Elevation data are often represented in digital elevation models (DEMs). SE-GAP utilized the USGS compiled National Elevation Dataset (NED) as a primary source (USGS 2003). However, because of the varying quality of the data, it was necessary to incorporate other datasets to create an improved, region wide product. These included data from NASA's Shuttle Radar Topography Mission (SRTM) at 30 meter resolution (NASA 2007), Light Detection and Ranging (LIDAR) data from the North Carolina Floodplain Mapping Program (NCFMP 2007), and hypsography data from the USGS's Digital Line Graphs (DLGs) at 1:24,000 and 1:100,000 scales (USGS 2007a). Areas of inconsistent, erroneous, or systematically flawed data were identified visually and "tagged" for fixing. A number of algorithms were then used to reassign elevation values using interpolations based on the higher quality data. This essentially promoted the best available information for a given area using a number of sources, as opposed to re-interpolating data from the same flawed source.
Usage in Modeling
Some species respond to environments directly related to altitudinal variation. Elevation is easily implemented in spatial modeling by limiting the model to the minimum and maximum values explicitly stated in the literature. DEMs are utilized directly and are measured in meters above mean sea level.
Land Forms Development
Landforms are derived from DEMs, ecoregions and hydrography using a complex model of slope, aspect, location, elevation, flow direction and accumulation, and a variety of other interpolated data. These are meant to incorporate a mixture of environmental inputs important for species. The general steps involved in creating landforms are as follows:
Extract data inputs for a given region to process (mapping zones for example). Subdivide into smaller processing units (HUCs for example) that can be overlapped during iteration loops to facilitate merging during production of the final output. Calculate Topographic Relative Moisture Index (TRMI) based on a DEM and hydrography. TRMI is an estimate of potential moisture at a specific location created by combining relative slope position, aspect, slope and curvature from the DEM, and defining valley bottoms that correspond to high resolution hydrography data. Process the moisture index grid to reclassify it into binary categories of moist and dry; smoothing the output with a majority filter to remove single cells and linear artifacts. Calculate land position based on the inverse distance weighted elevation of each cell in relation to its neighbors. Calculate the landform for each processing unit by combining the moisture, land position, slope and aspect. Create the final landform for the region by combining landforms of overlapping processing units into a single output.
Usage in Modeling
Species distributions are restricted to the selected landforms. Landforms include: Cliffs, Steep Slopes, Slope Crests, Side Slopes, Upper Slopes, Flat Summits, Coves, Slope Bottoms, Moist Flats, Dry Flats, and Wet Flats.
Hydrography Development
Water and its location on the landscape is a very important aspect of species' habitats. SE-GAP used a number of water related data layers to refine species models. These include water type (i.e. flowing or open/standing), distance to and from water, and stream flow and underlying gradient.
The source for hydrographic data was the USGS National Hydrography Dataset (NHD)(USGS 2007b). The NHD is composed of the most up-to-date nationwide data of surface waters compiled at two scales: 1:24,000 and 1:100,000. SE-GAP began acquiring NHD data in 2003. At the time, NHD was available only in ArcInfo coverage format organized by 8-digit Hydrologic Unit Code (HUC). NHD 8-digit HUCs are a complex mixture of polygon and arc (and point) features with numerous related tables of attributes. These coverage data are vector data types, i.e. arcs, polygons, nodes etc. with their incumbent data tables.
Water Type We divided hydrographic features from NHD into three types: flowing water, standing water, and wet vegetation. These feature types were extracted from the NHD by selecting corresponding codes (the FCODE attribute) in data tables and creating separate datasets for each data type. To facilitate their use in spatial modeling, these feature types were converted to grids and combined into 16 categories where feature types overlapped.
Flowing Water - Flowing water represents hydrographic features such as streams, rivers, springs, etc... NHD was developed as a value added product to allow users to performing tasks such as routing, classification, segmentation, etc... Therefore, arcs which flow into waterbodies such as reservoirs need to be continuous from their origin to their terminus. These "connectors" or "artificial paths" were also extracted from the data to represent flowing water. Flowing water can be arc or polygon feature classes. This is particularly true for large rivers that are wide enough to be digitized as long, narrow polygons.
Standing Water - Standing water represents hydrographic features such as lakes, ponds, reservoirs, bays, inlets, etc... Standing water can be arc or polygon feature classes. Some canals and ditches are represented as arcs. However, most standing water features are polygons.
Wet Vegetation - Wet vegetation represents hydrographic features such as swamps, marshes, Carolina bays, etc... It is represented only as the polygon feature class.
Distance INTO and FROM Water Features We used 18 categories of distance from the water features flowing water, standing water and wet vegetation. A process was used to buffer hydrography at various distances and code grid cells based on a defined set of distances. Eighteen categories for buffer grids. Each water type has a region wide grid coded for buffer distance from that type of hydrography.
Exterior Buffers (from feature) Cell Value Buffer Distance from Hydrographic Feature (meters) 0 > 4000m 1 +2000m to +4000m 2 +1000m to +2000m 3 +500m to +1000m 4 +250m to +500m 5 +120m to +250m 6 +60m to +120m 7 +30m to +60m 8 0m to +30m Interior Buffers (into feature) Cell Value Buffer Distance from Hydrographic Feature (meters) 9 0m to -30m 10 -30m to -60m 11 -60m to -120m 12 -120m to -250m 13 -250m to -500m 14 -500m to -1000m 15 -1000m to -2000m 16 -2000m to -4000m 17 > 4000m
Velocity (Stream Gradient) Stream velocity (or more appropriately stream gradient) was derived from a combination of streams and slopes calculated from a digital elevation model (DEM). A process was developed that determined the cell-to-cell drop in elevation along a stream grid based on flow direction. The process created three categories of slope calculations for use as a surrogate for stream gradient/velocity. A double pass focal majority function was used to "smooth" the output.
Usage in Modeling
Water Type Flowing Water - This includes streams, rivers, springs, seeps, ditches with moving water etc... Open/Standing Water - This includes bays, estuaries, ocean, lakes, ponds, reservoirs, ditches with stagnant water etc... Wet Vegetation - This includes a collection of map units representing seasonally or tidally inundated woody and non-woody plants.
Distance INTO and FROM Water Features
Interior (INTO) and Exterior (FROM) buffers on water features measured in meters and represented as discrete, cumulative distances. For example, a 250 meter exterior buffer on flowing water includes all areas up to 250 meters from the flowing water feature. FROM Buffer - 0, 30, 60, 120, 250, 500, 1000, 2000, 4000, and 9999 (> 4000 m) INTO Buffer - 0, 30, 60, 120, 250, 500, 1000, 2000, 4000, and 9999 (> 4000 m)
Velocity (Stream Gradient)
For some aquatic species, this can represent an important aspect of their habitat such as oxygenation levels, presence of invertebrate prey, and amount of sediment within the water column and on streambed substrates. Slow Only - For species that require slow moving or almost stagnant sections of streams or rivers. Typically these are areas where the underlying topography is flat (0 % gradient). Fast Only - For species that require high velocity sections of streams or rivers. Typically these are areas where the underlying topography is steep. A threshold of > 5 % gradient was used. All Types - Species can utilize either fast or slow sections of streams or rivers.
Salinity Development
Water salinity is a major factor when considering habitat conditions for many species. However, the dynamic and complex nature of water systems makes the development of a highly refined and reliable datalayer impractical, if not impossible. Therefore, we developed three general categories to include in species habitat models.
Zones of water salinity were hand digitized using NLCD map units as a guide. All palustrine and upland map units were identified, as were all estuarine map units. A line was digitized between non-estuarine and estuarine map units and served as the boundary between fresh and brackish water. An additional line was digitized across all ocean inlets, essentially the shortest distance between two bodies of land. This second line served as the boundary between brackish and salt water.
Usage in Modeling
Freshwater Only - For species requiring water, this includes only fresh water. Brackish/Salt Water Only - For species requiring water, this includes only brackish/salt water. All Water - For species requiring water, this includes both brackish/salt water as well as freshwater.
Urban Environments Development
Environments dominated by human disturbance such as roads, cities, and the constructed materials that support human habitation have profound effects on species' distributions. Map units derived for SE-GAP include three categories of development intensity - high, medium and low. These classes rely on spectral signatures from satellite data in association with measurements of impervious surface. SE-GAP created an urban/avoidance data layer using a combination of road density (see Roads section above) and the three map units of development intensity. In effect, the derived data layer acts as an index for a species' intolerance to human environments.
Usage in Modeling
For most species, this data layer was used to "mask out" or exclude species from a portion of the landscape. However, some species respond favorably to human habitats. In this later case, the data layer was used in an inclusionary manner.
Level of Tolerance/Intolerance This parameter is ranked at three levels: high, medium, and low. No selection of this parameter indicates the species' model is not contingent on an index of human disturbance.
High Exclusionary - For species that are very intolerant of human disturbance. All portions of the landscape identified as being directly influenced by human disturbance are eliminated from the predicted distribution. High Inclusionary - For species that are associated with high levels of human disturbance. The predicted distribution is limited to all portions of the landscape identified as being directly influenced by human disturbance.
Medium Exclusionary - For species that are moderately intolerant of human disturbance. Only portions of the landscape identified as being highly or moderately influenced by human disturbance are eliminated from the predicted distribution. Medium Inclusionary - For species that are associated with moderate levels of human disturbance. The predicted distribution is limited to only portions of the landscape identified as being moderately or partially influenced by human disturbance.
Low Exclusionary - For species that are partially intolerant of human disturbance. Only portions of the landscape identified as being highly influenced by human disturbance are eliminated from the predicted distribution. Low Inclusionary - For species that are associated with partial levels of human disturbance. The predicted distribution is limited to only portions of the landscape identified as being partially influenced by human disturbance.

Literature Cited Austin, M.P. 1991. Vegetation: data collection and analysis. Pages 37-41 in C.R. Margules and M.P. Austin, eds. Nature conservation: cost effective biological surveys and data analysis. Australia CSIRO, East Melbourne.
Homer, C. C. Huang, L. Yang, B. Wylie and M. Coan. 2004. Development of a 2001 National Landcover Database for the United States. Photogrammetric Engineering and Remote Sensing, Vol. 70, No. 7, July 2004, pp. 829-840.
National Aeronautics and Space Administration. 2007. Jet Propulsion Laboratory, Califorinia Institute of Technology. Shuttle Radar Topography Mission. Available online, URL: <>.
North Carolina Floodplain Mapping Program. 2007. North Carolina Floodplain Mapping Information System. Available online, URL: <>.
Omernik, J.M. 1987. Ecoregions of the conterminous United States. Map (scale 1:7,500,000). Annals of the Association of American Geographers 77(1):118-125.
Omernik, J.M. 1995. Ecoregions: A spatial framework for environmental management. In: Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making. Davis, W.S. and T.P. Simon (eds.) Lewis Publishers, Boca Raton, FL. Pp. 49-62.
Scott, M., F. Davis, B. Csuti, R. Noss, B. Butterfield, C. Groves, H. Anderson, S. Caicco, F. D'Erchia, T.C. Edwards Jr., J. Ulliman and R.G. Wright. 1993. Gap Analysis: A geographic approach to protection of biological diversity. Wildlife Monographs, no. 123. The Journal of Wildlife Management. 57(1) 41pp.
Seaber, P.R., Kapinos, F.P., and Knapp, G.L., 1987, Hydrologic Unit Maps: U.S. Geological Survey Water-Supply Paper 2294, 63 p.
U.S. Census Bureau. 2007. Topologically Integrated Geographic Encoding and Referencing system. Available online, URL: <>. Documentation available online, URL: <>.
U.S. Department of Agriculture. 1995. State soil geographic (STATSGO) data base, data use information. NRCS National Soil Survey Center Miscellaneous Publication # 1492. Available on, URL: <>.
U.S. Environmental Protection Agency. 2007. Western Ecology Division, Corvallis, OR. Ecoregion Maps and GIS Resources. Available online, URL: <>.
U.S. Geological Survey. 2003. National Mapping Division EROS Data Center. National Elevation Dataset. Available online, URL: <>.
U.S. Geological Survey. 2007a. National Mapping Division EROS Data Center. Digital Line Graphs. Available online, URL: <>.
U.S. Geological Survey. 2007b. National Hydrography Dataset. Available online, URL: <>.
Currentness_Reference: ground condition
Calendar_Date: 2001
Progress: Complete
Maintenance_and_Update_Frequency: None planned
West_Bounding_Coordinate: -91.968789
East_Bounding_Coordinate: -74.436112
North_Bounding_Coordinate: 40.615542
South_Bounding_Coordinate: 23.806684
Place_Keyword: Southeast US
Place_Keyword: Alabama
Place_Keyword: Florida
Place_Keyword: Georgia
Place_Keyword: Kentucky
Place_Keyword: Mississippi
Place_Keyword: North Carolina
Place_Keyword: South Carolina
Place_Keyword: Tennessee
Place_Keyword: Virginia
Place_Keyword_Thesaurus: none
Theme_Keyword: Predicted Habitat
Theme_Keyword: Predicted Distribution
Theme_Keyword: Habitat Modeling
Theme_Keyword: Atlantic coast slimy salamander
Theme_Keyword: Apalachicola Dusky Salamander
Theme_Keyword: Allegheny Mountain Dusky Salamander
Theme_Keyword: American Toad
Theme_Keyword: Barking Treefrog
Theme_Keyword: Brimley's Chorus Frog
Theme_Keyword: Bird-voiced Treefrog
Theme_Keyword: Blackbelly Salamander
Theme_Keyword: Black Mountain Salamander
Theme_Keyword: Blue Ridge Dusky Salamander
Theme_Keyword: Blue Ridge Gray-cheeked Salamander
Theme_Keyword: Blue Ridge Two-lined Salamander
Theme_Keyword: Bullfrog
Theme_Keyword: Black Warrior Waterdog
Theme_Keyword: Carpenter Frog
Theme_Keyword: Cave Salamander
Theme_Keyword: Cheoah Bald Salamander
Theme_Keyword: Chamberlain's Dwarf Salamander
Theme_Keyword: Cope's Gray Treefrog
Theme_Keyword: Chattahoochee slimy salamander
Theme_Keyword: Carolina Mountain Dusky Salamander
Theme_Keyword: Cumberland Plateau Salamander
Theme_Keyword: Crawfish Frog
Theme_Keyword: Cuban Treefrog
Theme_Keyword: Dwarf Black-bellied Salamander
Theme_Keyword: Dusky Salamander
Theme_Keyword: Dwarf Salamander
Theme_Keyword: Dwarf Waterdog
Theme_Keyword: Eastern Newt
Theme_Keyword: Eastern Spadefoot
Theme_Keyword: Eastern Narrowmouth Toad
Theme_Keyword: Florida Bog Frog
Theme_Keyword: Flatwoods Salamander
Theme_Keyword: Four-toed Salamander
Theme_Keyword: Fowler's Toad
Theme_Keyword: Gray Treefrog
Theme_Keyword: Georgia Blind Salamander
Theme_Keyword: Gulf Coast Toad
Theme_Keyword: Gulf Coast Waterdog
Theme_Keyword: Greenhouse Frog
Theme_Keyword: Giant Toad
Theme_Keyword: Gopher Frog
Theme_Keyword: Green Frog
Theme_Keyword: Green Salamander
Theme_Keyword: Greater Siren
Theme_Keyword: Green Treefrog
Theme_Keyword: Hellbender
Theme_Keyword: Imitator Salamander
Theme_Keyword: Jefferson Salamander
Theme_Keyword: Junaluska Salamander
Theme_Keyword: Lesser Siren
Theme_Keyword: Little Grass Frog
Theme_Keyword: Longtail Salamander
Theme_Keyword: Mabee's Salamander
Theme_Keyword: Marbled Salamander
Theme_Keyword: Mountain Chorus Frog
Theme_Keyword: Mississippi Gopher Frog
Theme_Keyword: Many-lined Salamander
Theme_Keyword: Mole Salamander
Theme_Keyword: Mississippi slimy salamander
Theme_Keyword: Mudpuppy
Theme_Keyword: Mud Salamander
Theme_Keyword: Northern Cricket Frog
Theme_Keyword: Northern Dwarf Siren
Theme_Keyword: Northern Gray-cheeked Salamander
Theme_Keyword: Northern Leopard Frog
Theme_Keyword: Neuse River Waterdog
Theme_Keyword: Northern Two-lined Salamander
Theme_Keyword: Northern Zigzag Salamander
Theme_Keyword: Oak Toad
Theme_Keyword: Ornate Chorus Frog
Theme_Keyword: Ocoee Salamander
Theme_Keyword: Ocmulgee slimy salamander
Theme_Keyword: One-toed Amphiuma
Theme_Keyword: Pine Barrens Treefrog
Theme_Keyword: Pig Frog
Theme_Keyword: Pickerel Frog
Theme_Keyword: Pigeon Mountain Salamander
Theme_Keyword: Peaks of Otter Salamander
Theme_Keyword: Pine Woods Treefrog
Theme_Keyword: Pygmy Salamander
Theme_Keyword: Ravine Salamander
Theme_Keyword: Red-cheeked Salamander
Theme_Keyword: Red Salamander
Theme_Keyword: Redback Salamander
Theme_Keyword: Red Hills Salamander
Theme_Keyword: River Frog
Theme_Keyword: Red-legged Salamander
Theme_Keyword: Shenandoah Salamander
Theme_Keyword: Southern Cricket Frog
Theme_Keyword: South Carolina slimy salamander
Theme_Keyword: Southern Dusky Salamander
Theme_Keyword: Seal Salamander
Theme_Keyword: Seepage Salamander
Theme_Keyword: Southeastern slimy salamander
Theme_Keyword: Southern Gray-cheeked Salamander
Theme_Keyword: Shovelnose Salamander
Theme_Keyword: Southern Leopard Frog
Theme_Keyword: Slimy Salamander
Theme_Keyword: South Mountain Gray-cheeked Salamander
Theme_Keyword: Smallmouth Salamander
Theme_Keyword: Santeetlah Dusky Salamander
Theme_Keyword: Southern Toad
Theme_Keyword: Southern Redback Salamander
Theme_Keyword: Spring Peeper
Theme_Keyword: Southern Appalachian Salamander
Theme_Keyword: Spotted Salamander
Theme_Keyword: Squirrel Treefrog
Theme_Keyword: Southern Chorus Frog
Theme_Keyword: Spring Salamander
Theme_Keyword: Striped Newt
Theme_Keyword: Streamside Salamander
Theme_Keyword: Savannah slimy salamander
Theme_Keyword: Southern Two-lined Salamander
Theme_Keyword: Southern Zigzag Salamander
Theme_Keyword: Tennessee Cave Salamander
Theme_Keyword: Tellico Salamander
Theme_Keyword: Three-toed Amphiuma
Theme_Keyword: Three-lined Salamander
Theme_Keyword: Tiger Salamander
Theme_Keyword: Two-toed Amphiuma
Theme_Keyword: Valley and Ridge Salamander
Theme_Keyword: Western Chorus Frog
Theme_Keyword: Webster's Salamander
Theme_Keyword: Wehrle's Salamander
Theme_Keyword: White-spotted Salamander
Theme_Keyword: Weller's Salamander
Theme_Keyword: Wood Frog
Theme_Keyword: Woodhouse's Toad
Theme_Keyword: White-spotted slimy salamander
Theme_Keyword: Yonahlossee Salamander
Theme_Keyword: American Black Duck
Theme_Keyword: Acadian Flycatcher
Theme_Keyword: Alder Flycatcher
Theme_Keyword: American Bittern
Theme_Keyword: American Coot
Theme_Keyword: American Crow
Theme_Keyword: American Goldfinch
Theme_Keyword: American Kestrel
Theme_Keyword: American Oystercatcher
Theme_Keyword: American Redstart
Theme_Keyword: American Robin
Theme_Keyword: American Wigeon
Theme_Keyword: American Woodcock
Theme_Keyword: Anhinga
Theme_Keyword: Antillean Nighthawk
Theme_Keyword: Bachman's Sparrow
Theme_Keyword: Barred Owl
Theme_Keyword: Bald Eagle
Theme_Keyword: Barn Owl
Theme_Keyword: Bank Swallow
Theme_Keyword: Baltimore Oriole
Theme_Keyword: Barn Swallow
Theme_Keyword: Black-and-white Warbler
Theme_Keyword: Black-billed Cuckoo
Theme_Keyword: Black-capped Chickadee
Theme_Keyword: Black-crowned Night-Heron
Theme_Keyword: Belted Kingfisher
Theme_Keyword: Bell's Vireo
Theme_Keyword: Bewick's Wren
Theme_Keyword: Blue-gray Gnatcatcher
Theme_Keyword: Brown-headed Cowbird
Theme_Keyword: Brown-headed Nuthatch
Theme_Keyword: Blue-headed Vireo
Theme_Keyword: Blackburnian Warbler
Theme_Keyword: Blue Grosbeak
Theme_Keyword: Blue Jay
Theme_Keyword: Black Rail
Theme_Keyword: Black Skimmer
Theme_Keyword: Black Vulture
Theme_Keyword: Black-necked Stilt
Theme_Keyword: Bobolink
Theme_Keyword: Brant
Theme_Keyword: Brown Creeper
Theme_Keyword: Brown Noddy
Theme_Keyword: Brown Pelican
Theme_Keyword: Bridled Tern
Theme_Keyword: Brown Thrasher
Theme_Keyword: Black-throated Blue Warbler
Theme_Keyword: Boat-tailed Grackle
Theme_Keyword: Black-throated Green Warbler
Theme_Keyword: Bufflehead
Theme_Keyword: Burrowing Owl
Theme_Keyword: Broad-winged Hawk
Theme_Keyword: Blue-winged Teal
Theme_Keyword: Black-whiskered Vireo
Theme_Keyword: Blue-winged Warbler
Theme_Keyword: Carolina Chickadee
Theme_Keyword: Cattle Egret
Theme_Keyword: Canada Goose
Theme_Keyword: Canvasback
Theme_Keyword: Carolina Wren
Theme_Keyword: Caspian Tern
Theme_Keyword: Canada Warbler
Theme_Keyword: Cedar Waxwing
Theme_Keyword: Cerulean Warbler
Theme_Keyword: Chipping Sparrow
Theme_Keyword: Chimney Swift
Theme_Keyword: Clapper Rail
Theme_Keyword: Cliff Swallow
Theme_Keyword: Common Ground-Dove
Theme_Keyword: Common Goldeneye
Theme_Keyword: Common Grackle
Theme_Keyword: Cooper's Hawk
Theme_Keyword: Common Merganser
Theme_Keyword: Common Moorhen
Theme_Keyword: Common Nighthawk
Theme_Keyword: Common Raven
Theme_Keyword: Common Tern
Theme_Keyword: Common Yellowthroat
Theme_Keyword: Chestnut-sided Warbler
Theme_Keyword: Chuck-will's-widow
Theme_Keyword: Double-crested Cormorant
Theme_Keyword: Dark-eyed Junco
Theme_Keyword: Dickcissel
Theme_Keyword: Downy Woodpecker
Theme_Keyword: Eastern Bluebird
Theme_Keyword: Eastern Kingbird
Theme_Keyword: Eastern Meadowlark
Theme_Keyword: Eastern Phoebe
Theme_Keyword: Eastern Screech-Owl
Theme_Keyword: Eastern Towhee
Theme_Keyword: Eastern Wood-Pewee
Theme_Keyword: Eurasian Collared-Dove
Theme_Keyword: European Starling
Theme_Keyword: Fish Crow
Theme_Keyword: Field Sparrow
Theme_Keyword: Florida Scrub-jay
Theme_Keyword: Forster's Tern
Theme_Keyword: Fulvous Whistling-Duck
Theme_Keyword: Gadwall
Theme_Keyword: Great Black-backed Gull
Theme_Keyword: Great Blue Heron
Theme_Keyword: Gull-billed Tern
Theme_Keyword: Great Crested Flycatcher
Theme_Keyword: Golden-crowned Kinglet
Theme_Keyword: Greater Flamingo
Theme_Keyword: Great Horned Owl
Theme_Keyword: Glossy Ibis
Theme_Keyword: Gray Kingbird
Theme_Keyword: Gray Catbird
Theme_Keyword: Great Egret
Theme_Keyword: Green Heron
Theme_Keyword: Greater Scaup
Theme_Keyword: Grasshopper Sparrow
Theme_Keyword: Green-winged Teal
Theme_Keyword: Golden-winged Warbler
Theme_Keyword: Hairy Woodpecker
Theme_Keyword: Herring Gull
Theme_Keyword: Henslow's Sparrow
Theme_Keyword: House Finch
Theme_Keyword: Horned Lark
Theme_Keyword: Hooded Merganser
Theme_Keyword: House Sparrow
Theme_Keyword: Hooded Warbler
Theme_Keyword: House Wren
Theme_Keyword: Indigo Bunting
Theme_Keyword: Kentucky Warbler
Theme_Keyword: Killdeer
Theme_Keyword: King Rail
Theme_Keyword: Laughing Gull
Theme_Keyword: Lark Sparrow
Theme_Keyword: Little Blue Heron
Theme_Keyword: Least Bittern
Theme_Keyword: Least Flycatcher
Theme_Keyword: Long-eared Owl
Theme_Keyword: Lesser Scaup
Theme_Keyword: Least Tern
Theme_Keyword: Limpkin
Theme_Keyword: Loggerhead Shrike
Theme_Keyword: Louisiana Waterthrush
Theme_Keyword: Long-tailed Duck
Theme_Keyword: Mangrove Cuckoo
Theme_Keyword: Magnificent Frigatebird
Theme_Keyword: Mallard
Theme_Keyword: Magnolia Warbler
Theme_Keyword: Marsh Wren
Theme_Keyword: Mississippi Kite
Theme_Keyword: Mourning Dove
Theme_Keyword: Mottled Duck
Theme_Keyword: Northern Bobwhite
Theme_Keyword: Northern Cardinal
Theme_Keyword: Northern Flicker
Theme_Keyword: Northern Harrier
Theme_Keyword: Northern Mockingbird
Theme_Keyword: Northern Parula
Theme_Keyword: Northern Pintail
Theme_Keyword: Northern Rough-winged Swallow
Theme_Keyword: Northern Shoveler
Theme_Keyword: Nelson's Sharp-tailed Sparrow
Theme_Keyword: Northern Saw-whet Owl
Theme_Keyword: Orchard Oriole
Theme_Keyword: Olive-sided Flycatcher
Theme_Keyword: Osprey
Theme_Keyword: Ovenbird
Theme_Keyword: Painted Bunting
Theme_Keyword: Pied-billed Grebe
Theme_Keyword: Peregrine Falcon
Theme_Keyword: Piping Plover
Theme_Keyword: Pine Warbler
Theme_Keyword: Pileated Woodpecker
Theme_Keyword: Prairie Warbler
Theme_Keyword: Prothonotary Warbler
Theme_Keyword: Purple Finch
Theme_Keyword: Purple Gallinule
Theme_Keyword: Purple Martin
Theme_Keyword: Rose-breasted Grosbeak
Theme_Keyword: Red-breasted Merganser
Theme_Keyword: Red-breasted Nuthatch
Theme_Keyword: Red-bellied Woodpecker
Theme_Keyword: Red-cockaded Woodpecker
Theme_Keyword: Red Crossbill
Theme_Keyword: Redhead
Theme_Keyword: Reddish Egret
Theme_Keyword: Red-eyed Vireo
Theme_Keyword: Red-headed Woodpecker
Theme_Keyword: Ring-necked Duck
Theme_Keyword: Ring-necked Pheasant
Theme_Keyword: Rock Pigeon
Theme_Keyword: Roseate Spoonbill
Theme_Keyword: Roseate Tern
Theme_Keyword: Royal Tern
Theme_Keyword: Red-shouldered Hawk
Theme_Keyword: Red-tailed Hawk
Theme_Keyword: Ruby-throated Hummingbird
Theme_Keyword: Ruddy Duck
Theme_Keyword: Ruffed Grouse
Theme_Keyword: Red-winged Blackbird
Theme_Keyword: Sandhill Crane
Theme_Keyword: Sandwich Tern
Theme_Keyword: Savannah Sparrow
Theme_Keyword: Scarlet Tanager
Theme_Keyword: Seaside Sparrow
Theme_Keyword: Sedge Wren
Theme_Keyword: Shiny Cowbird
Theme_Keyword: Snowy Egret
Theme_Keyword: Snow Goose
Theme_Keyword: Snail Kite
Theme_Keyword: Snowy Plover
Theme_Keyword: Sora
Theme_Keyword: Song Sparrow
Theme_Keyword: Sooty Tern
Theme_Keyword: Spotted Sandpiper
Theme_Keyword: Sharp-shinned Hawk
Theme_Keyword: Saltmarsh Sharp-tailed Sparrow
Theme_Keyword: Short-tailed Hawk
Theme_Keyword: Swallow-tailed Kite
Theme_Keyword: Summer Tanager
Theme_Keyword: Swainson's Warbler
Theme_Keyword: Tree Swallow
Theme_Keyword: Tricolored Heron
Theme_Keyword: Tundra Swan
Theme_Keyword: Tufted Titmouse
Theme_Keyword: Turkey Vulture
Theme_Keyword: Upland Sandpiper
Theme_Keyword: Veery
Theme_Keyword: Vesper Sparrow
Theme_Keyword: Virginia Rail
Theme_Keyword: Warbling Vireo
Theme_Keyword: White-breasted Nuthatch
Theme_Keyword: White-crowned Pigeon
Theme_Keyword: White-eyed Vireo
Theme_Keyword: Worm-eating Warbler
Theme_Keyword: White Ibis
Theme_Keyword: Whimbrel
Theme_Keyword: Willow Flycatcher
Theme_Keyword: Willet
Theme_Keyword: Wilson's Plover
Theme_Keyword: Wild Turkey
Theme_Keyword: Winter Wren
Theme_Keyword: Wood Duck
Theme_Keyword: Wood Stork
Theme_Keyword: Wood Thrush
Theme_Keyword: Whip-poor-will
Theme_Keyword: White-tailed Kite
Theme_Keyword: White-winged Dove
Theme_Keyword: Yellow-breasted Chat
Theme_Keyword: Yellow-billed Cuckoo
Theme_Keyword: Yellow-bellied Flycatcher
Theme_Keyword: Yellow-bellied Sapsucker
Theme_Keyword: Yellow-crowned Night-Heron
Theme_Keyword: Yellow-throated Vireo
Theme_Keyword: Yellow-throated Warbler
Theme_Keyword: Yellow Warbler
Theme_Keyword: American Black Bear
Theme_Keyword: Allegheny Woodrat
Theme_Keyword: American Beaver
Theme_Keyword: American Mink
Theme_Keyword: Appalachian Cottontail
Theme_Keyword: Big Brown Bat
Theme_Keyword: Brazilian Free-tailed Bat
Theme_Keyword: Black Rat
Theme_Keyword: Bobcat
Theme_Keyword: Cinereus Shrew
Theme_Keyword: Cotton Mouse
Theme_Keyword: Coyote
Theme_Keyword: Deer Mouse
Theme_Keyword: Eastern Chipmunk
Theme_Keyword: Eastern Cottontail
Theme_Keyword: Eastern Mole
Theme_Keyword: Eastern Pipistrelle
Theme_Keyword: Eastern Woodrat
Theme_Keyword: Eastern Fox Squirrel
Theme_Keyword: Eastern Gray Squirrel
Theme_Keyword: Eastern Harvest Mouse
Theme_Keyword: Elk
Theme_Keyword: Eastern Red Bat
Theme_Keyword: Eastern Small-footed Myotis
Theme_Keyword: Eastern Spotted Skunk
Theme_Keyword: Evening Bat
Theme_Keyword: Feral Hog
Theme_Keyword: Feral Horse
Theme_Keyword: Fulvous Harvest Mouse
Theme_Keyword: Fisher
Theme_Keyword: Florida Mouse
Theme_Keyword: Golden Mouse
Theme_Keyword: Gray Fox
Theme_Keyword: Gray Myotis
Theme_Keyword: Hairy-tailed Mole
Theme_Keyword: Hispid Cotton Rat
Theme_Keyword: Hoary Bat
Theme_Keyword: House Mouse
Theme_Keyword: Indiana Bat
Theme_Keyword: Jamaican Fruit-eating Bat
Theme_Keyword: Little Brown Bat
Theme_Keyword: Least Shrew
Theme_Keyword: Least Weasel
Theme_Keyword: Long-tailed Shrew
Theme_Keyword: Long-tailed Weasel
Theme_Keyword: Marsh Rabbit
Theme_Keyword: Meadow Vole
Theme_Keyword: Mexican Gray Squirrel
Theme_Keyword: Meadow Jumping Mouse
Theme_Keyword: Marsh Rice Rat
Theme_Keyword: Muskrat
Theme_Keyword: Northern Flying Squirrel
Theme_Keyword: Nine-banded Armadillo
Theme_Keyword: Northern Myotis
Theme_Keyword: Norway Rat
Theme_Keyword: Northern Raccoon
Theme_Keyword: Northern River Otter
Theme_Keyword: Northern Short-tailed Shrew
Theme_Keyword: Nutria
Theme_Keyword: Northern Yellow Bat
Theme_Keyword: Oldfield Mouse
Theme_Keyword: Prairie Vole
Theme_Keyword: Puma
Theme_Keyword: Pygmy Shrew
Theme_Keyword: Rafinesque's Big-eared Bat
Theme_Keyword: Red Fox
Theme_Keyword: Red Squirrel
Theme_Keyword: Red Wolf
Theme_Keyword: Round-tailed Muskrat
Theme_Keyword: Rock Vole
Theme_Keyword: Southern Bog Lemming
Theme_Keyword: Seminole Bat
Theme_Keyword: Southern Flying Squirrel
Theme_Keyword: Silver-haired Bat
Theme_Keyword: Sika Deer
Theme_Keyword: Smoky Shrew
Theme_Keyword: Snowshoe Hare
Theme_Keyword: Southeastern Myotis
Theme_Keyword: Southeastern Shrew
Theme_Keyword: Southeastern Pocket Gopher
Theme_Keyword: Southern Red-backed Vole
Theme_Keyword: Southern Short-tailed Shrew
Theme_Keyword: Star-nosed Mole
Theme_Keyword: Striped Skunk
Theme_Keyword: Swamp Rabbit
Theme_Keyword: Townsend's Big-eared Bat
Theme_Keyword: Velvety Free-tailed Bat
Theme_Keyword: Virginia Opossum
Theme_Keyword: Water Shrew
Theme_Keyword: Wagner's Bonneted Bat
Theme_Keyword: White-tailed Deer
Theme_Keyword: White-footed Mouse
Theme_Keyword: Woodland Jumping Mouse
Theme_Keyword: Woodchuck
Theme_Keyword: Woodland Vole
Theme_Keyword: American Alligator
Theme_Keyword: American Crocodile
Theme_Keyword: Alabama Map Turtle
Theme_Keyword: Alabama Redbelly Turtle
Theme_Keyword: Alligator Snapping Turtle
Theme_Keyword: Black-knobbed Map Turtle
Theme_Keyword: Black Kingsnake
Theme_Keyword: Black Pine Snake
Theme_Keyword: Barbour's Map Turtle
Theme_Keyword: Bog Turtle
Theme_Keyword: Brown Anole
Theme_Keyword: Broadhead Skink
Theme_Keyword: Brown Snake
Theme_Keyword: Black Swamp Snake
Theme_Keyword: Brown Water Snake
Theme_Keyword: Common Garter Snake
Theme_Keyword: Cosmopolitan House Gecko
Theme_Keyword: Chicken Turtle
Theme_Keyword: Common Map Turtle
Theme_Keyword: Common Musk Turtle
Theme_Keyword: Coachwhip
Theme_Keyword: Cooter
Theme_Keyword: Copperhead
Theme_Keyword: Coal Skink
Theme_Keyword: Corn Snake
Theme_Keyword: Cottonmouth
Theme_Keyword: Diamondback Terrapin
Theme_Keyword: Diamondback Water Snake
Theme_Keyword: Eastern Kingsnake
Theme_Keyword: Eastern Mud Turtle
Theme_Keyword: Eastern Box Turtle
Theme_Keyword: Eastern Coral Snake
Theme_Keyword: Eastern Diamondback Rattlesnake
Theme_Keyword: Eastern Glass Lizard
Theme_Keyword: Eastern Hognose Snake
Theme_Keyword: Eastern Ribbon Snake
Theme_Keyword: Eastern Milk Snake
Theme_Keyword: Escambia Map Turtle
Theme_Keyword: Eastern Spiny Softshell
Theme_Keyword: Eastern Rat Snake
Theme_Keyword: Florida Box Turtle
Theme_Keyword: Florida Crowned Snake
Theme_Keyword: Fence/prairie/plateau Lizard
Theme_Keyword: Florida Green Water Snake
Theme_Keyword: Five-lined Skink
Theme_Keyword: Florida Pine Snake
Theme_Keyword: Florida Softshell
Theme_Keyword: Flattened Musk Turtle
Theme_Keyword: False Map Turtle
Theme_Keyword: Florida Red-bellied Turtle
Theme_Keyword: Florida Scrub Lizard
Theme_Keyword: Florida Worm Lizard
Theme_Keyword: Gulf Coast Box Turtle
Theme_Keyword: Graham's Crayfish Snake
Theme_Keyword: Gulf Coast Smooth Softshell
Theme_Keyword: Gopher Tortoise
Theme_Keyword: Gulf Coast Spiny Softshell
Theme_Keyword: Green Anole
Theme_Keyword: Ground Skink
Theme_Keyword: Glossy Crayfish Snake
Theme_Keyword: Green Turtle
Theme_Keyword: Green Water Snake
Theme_Keyword: Island Glass Lizard
Theme_Keyword: Eastern Indigo Snake
Theme_Keyword: Kirtland's Snake
Theme_Keyword: Leatherback
Theme_Keyword: Loggerhead Musk Turtle
Theme_Keyword: Loggerhead
Theme_Keyword: Mediterranean Gecko
Theme_Keyword: Mimic Glass Lizard
Theme_Keyword: Midland Smooth Softshell
Theme_Keyword: Mole Kingsnake
Theme_Keyword: Mole Skink
Theme_Keyword: Mud Snake
Theme_Keyword: Northern Pine Snake
Theme_Keyword: Northern Painted Turtle
Theme_Keyword: Northern Water Snake
Theme_Keyword: Ouachita Map Turtle
Theme_Keyword: Pine Woods Snake
Theme_Keyword: Pascagoula Map Turtle
Theme_Keyword: Prairie Kingsnake
Theme_Keyword: Plainbelly Water Snake
Theme_Keyword: Pygmy Rattlesnake
Theme_Keyword: Queen Snake
Theme_Keyword: Racer
Theme_Keyword: Rainbow Snake
Theme_Keyword: Redbelly Snake
Theme_Keyword: Reef Gecko
Theme_Keyword: Rough Earth Snake
Theme_Keyword: Redbelly Turtle
Theme_Keyword: Rough Green Snake
Theme_Keyword: River Cooter
Theme_Keyword: Ringneck Snake
Theme_Keyword: Red Milk Snake
Theme_Keyword: Ringed Map Turtle
Theme_Keyword: Rim Rock Crowned Snake
Theme_Keyword: Razorback Musk Turtle
Theme_Keyword: Sand Skink
Theme_Keyword: Scarlet Kingsnake
Theme_Keyword: Striped Crayfish Snake
Theme_Keyword: Southeastern Crowned Snake
Theme_Keyword: Smooth Earth Snake
Theme_Keyword: Southeastern Five-lined Skink
Theme_Keyword: Slender Glass Lizard
Theme_Keyword: Smooth Green Snake
Theme_Keyword: Southern Hognose Snake
Theme_Keyword: Six-lined Racerunner
Theme_Keyword: Slider
Theme_Keyword: Salt Marsh Snake
Theme_Keyword: Striped Mud Turtle
Theme_Keyword: Snapping Turtle
Theme_Keyword: Speckled Kingsnake
Theme_Keyword: Spotted Turtle
Theme_Keyword: Scarlet Snake
Theme_Keyword: Short-tailed Snake
Theme_Keyword: Southern Water Snake
Theme_Keyword: Three-toed Box Turtle
Theme_Keyword: Texas Horned Lizard
Theme_Keyword: Timber Rattlesnake
Theme_Keyword: Worm Snake
Theme_Keyword: Wood Turtle
Theme_Keyword: Western Ribbon Snake
Theme_Keyword: Yellow-blotched Map Turtle
Theme_Keyword: Plethodon chlorobryonis
Theme_Keyword: Desmognathus apalachicolae
Theme_Keyword: Desmognathus ochrophaeus
Theme_Keyword: Bufo americanus
Theme_Keyword: Hyla gratiosa
Theme_Keyword: Pseudacris brimleyi
Theme_Keyword: Hyla avivoca
Theme_Keyword: Desmognathus quadramaculatus
Theme_Keyword: Desmognathus welteri
Theme_Keyword: Desmognathus orestes
Theme_Keyword: Plethodon amplus
Theme_Keyword: Eurycea wilderae
Theme_Keyword: Rana catesbeiana
Theme_Keyword: Necturus alabamensis
Theme_Keyword: Rana virgatipes
Theme_Keyword: Eurycea lucifuga
Theme_Keyword: Plethodon cheoah
Theme_Keyword: Eurycea chamberlaini
Theme_Keyword: Hyla chrysoscelis
Theme_Keyword: Plethodon chattahoochee
Theme_Keyword: Desmognathus carolinensis
Theme_Keyword: Plethodon kentucki
Theme_Keyword: Rana areolata
Theme_Keyword: Osteopilus septentrionalis
Theme_Keyword: Desmognathus folkertsi
Theme_Keyword: Desmognathus fuscus
Theme_Keyword: Eurycea quadridigitata
Theme_Keyword: Necturus punctatus
Theme_Keyword: Notophthalmus viridescens
Theme_Keyword: Scaphiopus holbrookii
Theme_Keyword: Gastrophryne carolinensis
Theme_Keyword: Rana okaloosae
Theme_Keyword: Ambystoma cingulatum
Theme_Keyword: Hemidactylium scutatum
Theme_Keyword: Bufo fowleri
Theme_Keyword: Hyla versicolor
Theme_Keyword: Haideotriton wallacei
Theme_Keyword: Bufo valliceps
Theme_Keyword: Necturus beyeri complex
Theme_Keyword: Eleutherodactylus planirostris
Theme_Keyword: Bufo marinus
Theme_Keyword: Rana capito
Theme_Keyword: Rana clamitans
Theme_Keyword: Aneides aeneus
Theme_Keyword: Siren lacertina
Theme_Keyword: Hyla cinerea
Theme_Keyword: Cryptobranchus alleganiensis
Theme_Keyword: Desmognathus imitator
Theme_Keyword: Ambystoma jeffersonianum
Theme_Keyword: Eurycea junaluska
Theme_Keyword: Siren intermedia
Theme_Keyword: Pseudacris ocularis
Theme_Keyword: Eurycea longicauda
Theme_Keyword: Ambystoma mabeei
Theme_Keyword: Ambystoma opacum
Theme_Keyword: Pseudacris brachyphona
Theme_Keyword: Rana sevosa
Theme_Keyword: Stereochilus marginatus
Theme_Keyword: Ambystoma talpoideum
Theme_Keyword: Plethodon mississippi
Theme_Keyword: Necturus maculosus
Theme_Keyword: Pseudotriton montanus
Theme_Keyword: Acris crepitans
Theme_Keyword: Pseudobranchus striatus
Theme_Keyword: Plethodon montanus
Theme_Keyword: Rana pipiens
Theme_Keyword: Necturus lewisi
Theme_Keyword: Eurycea bislineata
Theme_Keyword: Plethodon dorsalis
Theme_Keyword: Bufo quercicus
Theme_Keyword: Pseudacris ornata
Theme_Keyword: Desmognathus ocoee
Theme_Keyword: Plethodon ocmulgee
Theme_Keyword: Amphiuma pholeter
Theme_Keyword: Hyla andersonii
Theme_Keyword: Rana grylio
Theme_Keyword: Rana palustris
Theme_Keyword: Plethodon petraeus
Theme_Keyword: Plethodon hubrichti
Theme_Keyword: Hyla femoralis
Theme_Keyword: Desmognathus wrighti
Theme_Keyword: Plethodon richmondi
Theme_Keyword: Plethodon jordani
Theme_Keyword: Pseudotriton ruber
Theme_Keyword: Plethodon cinereus
Theme_Keyword: Phaeognathus hubrichti
Theme_Keyword: Rana heckscheri
Theme_Keyword: Plethodon shermani
Theme_Keyword: Plethodon shenandoah
Theme_Keyword: Acris gryllus
Theme_Keyword: Plethodon variolatus
Theme_Keyword: Desmognathus auriculatus
Theme_Keyword: Desmognathus monticola
Theme_Keyword: Desmognathus aeneus
Theme_Keyword: Plethodon grobmani
Theme_Keyword: Plethodon metcalfi
Theme_Keyword: Desmognathus marmoratus
Theme_Keyword: Rana sphenocephala
Theme_Keyword: Plethodon glutinosus
Theme_Keyword: Plethodon meridianus
Theme_Keyword: Ambystoma texanum
Theme_Keyword: Desmognathus santeetlah
Theme_Keyword: Bufo terrestris
Theme_Keyword: Plethodon serratus
Theme_Keyword: Pseudacris crucifer
Theme_Keyword: Plethodon teyahalee
Theme_Keyword: Ambystoma maculatum
Theme_Keyword: Hyla squirella
Theme_Keyword: Pseudacris nigrita
Theme_Keyword: Gyrinophilus porphyriticus
Theme_Keyword: Notophthalmus perstriatus
Theme_Keyword: Ambystoma barbouri
Theme_Keyword: Plethodon savannah
Theme_Keyword: Eurycea cirrigera
Theme_Keyword: Plethodon ventralis
Theme_Keyword: Gyrinophilus palleucus
Theme_Keyword: Plethodon aureolus
Theme_Keyword: Amphiuma tridactylum
Theme_Keyword: Eurycea guttolineata
Theme_Keyword: Ambystoma tigrinum
Theme_Keyword: Amphiuma means
Theme_Keyword: Plethodon hoffmani
Theme_Keyword: Pseudacris triseriata
Theme_Keyword: Plethodon websteri
Theme_Keyword: Plethodon wehrlei
Theme_Keyword: Plethodon punctatus
Theme_Keyword: Plethodon welleri
Theme_Keyword: Rana sylvatica
Theme_Keyword: Bufo woodhousii
Theme_Keyword: Plethodon cylindraceus
Theme_Keyword: Plethodon yonahlossee
Theme_Keyword: Anas rubripes
Theme_Keyword: Empidonax virescens
Theme_Keyword: Empidonax alnorum
Theme_Keyword: Botaurus lentiginosus
Theme_Keyword: Fulica americana
Theme_Keyword: Corvus brachyrhynchos
Theme_Keyword: Carduelis tristis
Theme_Keyword: Falco sparverius
Theme_Keyword: Haematopus palliatus
Theme_Keyword: Setophaga ruticilla
Theme_Keyword: Turdus migratorius
Theme_Keyword: Anas americana
Theme_Keyword: Scolopax minor
Theme_Keyword: Anhinga anhinga
Theme_Keyword: Chordeiles gundlachii
Theme_Keyword: Aimophila aestivalis
Theme_Keyword: Strix varia
Theme_Keyword: Haliaeetus leucocephalus
Theme_Keyword: Tyto alba
Theme_Keyword: Riparia riparia
Theme_Keyword: Icterus galbula
Theme_Keyword: Hirundo rustica
Theme_Keyword: Mniotilta varia
Theme_Keyword: Coccyzus erythropthalmus
Theme_Keyword: Poecile atricapillus
Theme_Keyword: Nycticorax nycticorax
Theme_Keyword: Ceryle alcyon
Theme_Keyword: Vireo bellii
Theme_Keyword: Thryomanes bewickii
Theme_Keyword: Polioptila caerulea
Theme_Keyword: Molothrus ater
Theme_Keyword: Sitta pusilla
Theme_Keyword: Vireo solitarius
Theme_Keyword: Dendroica fusca
Theme_Keyword: Passerina caerulea
Theme_Keyword: Cyanocitta cristata
Theme_Keyword: Laterallus jamaicensis
Theme_Keyword: Rynchops niger
Theme_Keyword: Coragyps atratus
Theme_Keyword: Himantopus mexicanus
Theme_Keyword: Dolichonyx oryzivorus
Theme_Keyword: Branta bernicla
Theme_Keyword: Certhia americana
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This data set is not intended for site-specific analyses. Interpretations derived from its use are suited for regional and planning purposes only. These data are not intended to be used at scales larger than 1:100,000. Acknowledgment of Southeast Gap Analysis Project is appreciated.
Use_Constraints: No access restrictions; public domain.
Southeast Gap Analysis Project;
Biodiversity and Spatial Information Center, North Carolina State University, Raleigh, North Carolina 27695, Steven G. Williams, Matthew J. Rubino;
Alabama Gap Project, Alabama Cooperative Fish & Wildlife Research Unit, Auburn University, Alabama 36839, Amy L. Silvano;
Natural Resources and Spatial Analysis Laboratory, University of Georgia, Athens Georgia 30602, Matthew J. Elliott, Kacy Cook, Stacy Smith.
Contact_Person: Steven G. Williams
Biodiversity and Spatial Information Center, Dept. of Biology, NCSU
Contact_Position: Vertebrate Mapping Coordinator
Address_Type: mailing and physical address
Address: 127 David Clark Labs, Dept. of Biology, NCSU
City: Raleigh
State_or_Province: NC
Postal_Code: 27695-7617
Country: USA
Contact_Voice_Telephone: 919-513-7413
Contact_Facsimile_Telephone: 919-515-4454
Security_Classification: Unclassified

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time
Contact_Person: Steven G. Williams
Biodiversity and Spatial Information Center, Dept. of Biology, NCSU
Address_Type: mailing and physical address
City: Raleigh
State_or_Province: NC
Postal_Code: 27695-7617
Address: 127 David Clark Labs, Dept. of Biology, NCSU
Country: USA
Contact_Voice_Telephone: 919-513-7413
Contact_Position: Vertebrate Mapping Coordinator
Contact_Facsimile_Telephone: 919-515-4454
Metadata_Date: 20100401
Online_Linkage: <>
Profile_Name: ESRI Metadata Profile

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Format_Name: ESRI GRID
Network_Resource_Name: <>
Contact_Person: Steven G. Williams
Biodiversity and Spatial Information Center, Dept. of Biology, NCSU
Contact_Position: Vertebrate Mapping Coordinator
Address_Type: mailing and physical address
Address: 127 David Clark Labs, Dept. of Biology, NCSU
City: Raleigh
State_or_Province: NC
Postal_Code: 27695-7617
Country: USA
Contact_Voice_Telephone: 919-513-7413
Contact_Facsimile_Telephone: 919-515-4454
The digital data described by this metadata report were prepared by the Southeast Gap Analysis Project. Neither the States invovled nor any agency thereof, nor any of their employees, make any warranty, for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed in this report or media or represent that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the States. Any views and opinions of authors expressed herein do not necessarily state or reflect those of the States involved. Data on this media may have been derived from federal agencies or from other external sources or from data developed by the agencies involved . In those cases where data has been translated from one format to another or initially developed from map or other sources the agencies involved has made all reasonable efforts to preserve the data quality as originally developed, however no warranty, expressed or implied, is made by the agencies involved as to the completeness or accuracy of the data and related materials. The act of distribution does not constitute any such warranty, and no responsibility is assumed by the agencies involved in the use of this data, or related materials.

Direct_Spatial_Reference_Method: Raster
Raster_Object_Type: Grid Cell

Planar_Coordinate_Encoding_Method: coordinate pair
Planar_Distance_Units: meters
Abscissa_Resolution: 0.000835
Ordinate_Resolution: 0.000835
Map_Projection_Name: Albers Conical Equal Area
Standard_Parallel: 29.500000
Standard_Parallel: 45.500000
Longitude_of_Central_Meridian: -96.000000
Latitude_of_Projection_Origin: 23.000000
False_Easting: 0.000000
False_Northing: 0.000000
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257222

Entity_Type_Label: r_SppCode
Entity_Type_Definition: Predicted Habitat for Species
Attribute_Label: VALUE
Enumerated_Domain_Value: 0
Enumerated_Domain_Value_Definition: Not present
Enumerated_Domain_Value: 1
Enumerated_Domain_Value_Definition: Winter Habitat
Enumerated_Domain_Value: 2
Enumerated_Domain_Value_Definition: Summer Habitat
Enumerated_Domain_Value: 3
Enumerated_Domain_Value_Definition: Year-round Habitat
Attribute_Definition: Predicted Seasonal Habitat
Attribute_Label: COUNT

Generated by mp version 2.9.14 on Thu Oct 13 16:05:22 2011