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NSW Koala Baseline Likelihood Map 2016

The map presents the distribution of the likelihood of koala occurrence across NSW based on publicly available data held in the Atlas of NSW Wildlife (www.bionet.nsw.gov.au). The proportion (’p’ column) of koalas (‘Koala’ column) recorded relative to a suite of arboreal mammals is presented in a 10 kilometre grid across NSW. A separate 5 kilometre grid is also available for Koala Management Area (KMA) 1 – North Coast. A measure of the confidence (‘Conf’ column) in the likelihood estimate is also presented. In KMA 1 Atlas of NSW Wildlife (Bionet) record data has been supplemented with data from koala spot assessment (SAT) survey along with “rapid SAT” method undertaken where major data deficiencies remained. SAT surveys observation efforts and resulting koala records were used in the same manner as arboreal mammal records. This map can be used to inform the likely occurrence of koalas and informing decisions on mitigation of activities such as native forestry.

Distance

Koala Likelihood Mapping 5 km - 5 km Grid Cell

Koala Likelihood Mapping 10 km - 10 km Grid Cell

Data and Resources

Metadata Summary What is metadata?

Field Value
Data Type Vector
Alternative Title 5km and 10km Koala Baseline
Metadata Date 06/02/2017
Date Created 18/07/2016
Edition 2016 including SAT data
Purpose Native Forestry Regulation on State Forests
License Creative Commons Attribution 4.0
Update Frequency Data is updated as deemed necessary
Keywords koala,likelihood,occurrence,baseline,native forestry
Field of Research Ecology
Spatial

Dataset extent

Geospatial Topic Biota
Language English
Temporal Coverage From 01/01/1990 - 11/02/2016
Datum GDA94 Geographic (Lat\Long)
Landing page https://datasets.seed.nsw.gov.au/dataset/10km-nsw-koala-baseline-likelihood-map-2016
Legal Disclaimer Read
Attribution Environment Protection Authority (EPA) asserts the right to be attributed as author of the original material in the following manner: "© State Government of NSW and Environment Protection Authority (EPA) 2016"