20250507
15515100
1.0
FALSE
EE_Chytrid_Map3_Dis_Clip
002
Geographic
GCS_WGS_1984
Angular Unit: Degree (0.017453)
<GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WKT>GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4326]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4326</WKID><LatestWKID>4326</LatestWKID></GeographicCoordinateSystem>
20260512
00425400
20260512
00425400
Esri ArcGIS 13.3.0.52636
EE_Chytrid_Map3_Dis_Clip
<p>This layer shows the expert-derived probable distribution of chytrid fungus across Australia.</p><p>The map represents expert ecological knowledge identifying areas where the threat is considered likely to occur. The map is classified according to the number of experts who identified chytrid fungus as occurring within an area during the expert elicitation process. Higher classification values indicate that more experts identified the threat as being present in that location, while lower values indicate that fewer experts identified presence at a location. Values represent the count of expert assessments and should not be interpreted as a proportion of all experts consulted, as the number of participating experts varied between threats. </p><p>Expert review was undertaken as part of a structured elicitation process involving specialists from academia, government and non-government organisations. Unlike statistical threshold maps, which apply a mathematical threshold to habitat suitability predictions, expert threshold maps incorporate expert judgement regarding species ecology, known distributions, dispersal limitations, data gaps and other factors that may not be fully represented by the model. </p><p>The layer represents the best available estimate of the current distribution and extent of the threat based on information available at the time of development. It should not be interpreted as a map of confirmed presence or absence.</p><p>This dataset has been developed as part of the Threats Spatial Planner Tool (TSPT). </p><p>For detailed information on modelling methods and the expert elicitation process, please refer to the Methods page within the Threats Spatial Planner Tool. </p><p>For information on assumptions, limitations and appropriate use of the data, please refer to the Caveats page within the Threats Spatial Planner Tool. </p><p>This layer supports national-scale threat assessment, spatial planning, management prioritisation and decision-making by providing an expert-informed representation of the current distribution of chytrid fungus. </p><p>Geographic Extent: Australia</p><p>Data Currency: Current distribution based on occurrence records, habitat suitability modelling and expert review available at the time of development (2026).</p><p>Limitations: The layer represents an expert-informed estimate of distribution and should not be interpreted as confirmed presence or absence. Expert assessments are based on the best available information at the time of development and may change as new data become available. Knowledge gaps, incomplete occurrence records and uncertainty regarding species distributions may influence the mapped extent. The distribution shown may not fully capture recent range expansions, contractions or local management outcomes. The layer is intended for regional and national-scale planning and should be complemented by local knowledge where available.</p>
This map shows the expert-derived probable distribution of chytrid fungus across Australia.
The layer is based on interpretation and review of habitat suitability model outputs, occurrence records and expert knowledge of the threat's ecology and distribution. It represents the areas considered by experts to be most likely occupied by the threat under current conditions. Map classes indicate the count of experts that identified a threat as being present in a location.
<p>Creative Commons Attribution 4.0 International (CC BY 4.0).</p><p>Users must acknowledge the Department of Climate Change, Energy, the Environment and Water (DCCEEW) and all contributing data providers when using this dataset.</p>
EcologyEnvironment Information AustraliaThreats Spatial Planner ToolFAUNA exoticHAZARDS pestsThreatsInvasive Species; Biosecurity; Environmental ModellingChytrid fungus
File Geodatabase Feature Class
dataset
EPSG
6.2(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
EE_Chytrid_Map3_Dis_Clip
Feature Class
0
OBJECTID
OID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
Sum_Chytrid_Map3
Sum_Chytrid_Map3
Integer
4
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
20260512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