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Australian Journal of Zoology Australian Journal of Zoology Society
Evolutionary, molecular and comparative zoology
RESEARCH ARTICLE

The development of an improved scat survey method for koalas (Phascolarctos cinereus)

Alex Jiang A , Andrew Tribe B and Peter Murray https://orcid.org/0000-0003-1143-1706 A C
+ Author Affiliations
- Author Affiliations

A Wildlife Science Unit, School of Agriculture and Food Sciences, The University of Queensland, Gatton, Qld 4343, Australia.

B Turner Family Foundation, PO Box 108, Fortitude Valley, Qld 4006, Australia.

C Corresponding author. Email: peter.murray@uq.edu.au

Australian Journal of Zoology 67(3) 125-133 https://doi.org/10.1071/ZO20006
Submitted: 6 February 2020  Accepted: 26 May 2020   Published: 12 June 2020

Abstract

Koala scat surveys are important tools for determining koala presence and distribution in large forested areas where it is impractical to conduct direct observation surveys. However, current scat survey methods are problematic due to lack of either accuracy or feasibility, i.e. they are either biased or very time-consuming in the field. This study aimed to establish a new koala scat survey method with improved accuracy compared with existing methods, and practical in the field. We developed a new Balanced Koala Scat Survey method (BKSS), and evaluated it in the field by analysing scat detectability variations and comparing it with a current survey method, the Spot Assessment Technique (SAT), to determine scat searching accuracy. The results revealed that current methods were biased by assigning consistent searching effort for all trees, because effective searching time to detect the first scat was significantly affected by Koala Activity Level (KAL – the proportion of trees found with scats among all 30 trees in a survey site). Compared with BKSS, SAT tended to yield more false negative outcomes; SAT may miss up to 46% of trees with scats when KAL was low. The application of BKSS is expected to greatly enhance the reliability of koala scat surveys in determining koala distribution and thus improve their conservation management.


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