Using a state vegetation type map to predict legal koala habitat at large scale: a case study in the Mid North Coast region of NSW

Cristian Gabriel Orlando; Rebecca Montague-Drake; John Turbill; Allen McIlwee; Mathew S. Crowther

doi:10.1071/WR24188

RESEARCH ARTICLE (Open Access)

Previous Contents Vol 52(9)

Using a state vegetation type map to predict legal koala habitat at large scale: a case study in the Mid North Coast region of NSW

Cristian Gabriel Orlando

^A ^# ^* , Rebecca Montague-Drake ^B ^# , John Turbill ^B , Allen McIlwee ^C and Mathew S. Crowther

^A

+ Author Affiliations

- Author Affiliations

^A School of Life and Environmental Sciences, University of Sydney, Sydney, NSW 2006, Australia.

^B Threatened Species and Ecosystems, Environment and Heritage Group, Department of Climate Change, Energy, the Environment and Water NSW, Coffs Harbour, NSW, Australia.

^C Remote Sensing and Landscape Science, Environment and Heritage Group, Department of Climate Change, Energy, the Environment and Water NSW, Parramatta, NSW, Australia.

^* Correspondence to: cristian.orlando@sydney.edu.au

^# Authors contributed equally to this work and share first authorship

Handling Editor: Adam Stow

Wildlife Research 52, WR24188 https://doi.org/10.1071/WR24188

Submitted: 18 November 2024 Accepted: 23 August 2025 Published: 12 September 2025

© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Context

Habitat loss is a primary contributor to the decline in koala populations. While existing legislation aims to preserve koala habitats, on-ground surveys for habitat classification are time-consuming, potentially biased, and limited in scale. Leveraging plant community type (PCT) mapping for large-scale classification of koala habitat is promising but requires testing and clear methodological steps.

Aims

We describe and test a method (the ‘PCT/SEPP’ method) to use PCT mapping to predict legal koala habitat as defined under NSW State Environmental Planning Policy (Biodiversity and Conservation) 2021 (SEPP) in the Mid North Coast region of New South Wales (NSW).

Methods

We surveyed 195 sites (49 PCTs) and measured the frequency of koala use tree species (KTS) as outlined in the SEPP. Next, using the FIDEL tables for the NSW PCTs, we assigned the expected average frequency and median combined cover of KTS to each site, on the basis of its associated PCT (the ‘PCT/SEPP’ method). We assessed sites for legal (‘potential’) koala habitat by using field vegetation survey data and ‘PCT/SEPP’ data, comparing congruence. Finally, we evaluated the effectiveness of both methods in identifying contemporary occupied (‘core’) koala habitat by using records from dog and acoustic surveys, and BioNet Atlas (as per the SEPP).

Key results

Legal koala habitat, verified from on-ground field surveys, was best predicted by the ‘PCT/SEPP’ method which used a ‘15% frequency/15% cover’ rule for KTS. This rule was also the best matching for occupied koala habitat, outperforming the field method by a small margin.

Conclusions

Our study supports the effectiveness of the ‘PCT/SEPP’ method in predicting legal koala habitat in the Hastings–Macleay region. Further testing would be required before the approach can be extended to other regions.

Implications

The proposed method introduces a possible means for conducting large-scale assessment of land for legal koala habitat classification. In the future, the use of a standardized and reliable method, such as the one described here, should be considered in biodiversity conservation and land-use planning.

Keywords: acoustic survey, detection dog, FIDEL tables, Koala Habitat Suitability Model (KHSM), legal koala habitat, NSW State Vegetation Type Map (SVTM), Phascolarctos cinereus, plant community type mapping, State Environmental Planning Policy (Biodiversity and Conservation) 2021 (SEPP 2021).

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