Estimating and validating koala Phascolarctos cinereus density estimates from acoustic arrays using spatial count modelling
Brad Law
A * , Leroy Gonsalves A , Joanna Burgar B , Traecey Brassil A , Isobel Kerr A , Lachlan Wilmott C , Kylie Madden C , Martin Smith C , Valentina Mella D , Mathew Crowther D , Mark Krockenberger D , Adrian Rus D , Rod Pietsch C , Anthony Truskinger E , Phil Eichinski E and Paul Roe E
+ Author Affiliations
- Author Affiliations
A NSW Primary Industries, Forest Science, NSW, Australia.
B University of British Columbia, Vancouver, Canada.
C Department of Planning, Industry and Environment, NSW, Australia.
D University of Sydney, NSW, Australia.
E Queensland University of Technology, Qld, Australia.
Wildlife Research 49(5) 438-448 https://doi.org/10.1071/WR21072
Submitted: 30 April 2021 Accepted: 5 November 2021 Published: 20 December 2021
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing.
Abstract
Context: It is notoriously difficult to estimate the size of animal populations, especially for cryptic or threatened species that occur in low numbers. Recent advances with acoustic sensors make the detection of animal populations cost effective when coupled with software that can recognise species-specific calls.
Aims: We assess the potential for acoustic sensors to estimate koala, Phascolarctos cinereus, density, when individuals are not identified, using spatial count models. Sites were selected where previous independent estimates of density were available.
Methods: We established acoustic arrays at each of five sites representing different environments and densities of koalas in New South Wales. To assess reliability, we compared male koala density estimates derived from spatial count modelling to independently derived estimates for each site.
Key results: A total 11 312 koala bellows were verified across our five arrays. Koalas were detected at most of our sample locations (96–100% of sensors; n = 130), compared with low detection rates from rapid scat searches at trees near each sensor (scats at <2% of trees searched, n = 889, except one site where scats were present at 69% of trees, n = 129). Independent estimates of koala density at our study areas varied from a minimum of 0.02 male koalas ha−1 to 0.32 ha−1. Acoustic arrays and the spatial count method yielded plausible estimates of male koala density, which, when converted to total koalas (assuming 1:1 sex ratio), were mostly equivalent to independent estimates previously derived for each site. The greatest discrepancy occurred where the acoustic estimate was larger (although within the bounds of uncertainty) than the independent mark–recapture estimate at a fragmented, high koala-density site.
Conclusions: Spatial count modelling of acoustic data from arrays provides plausible and reliable estimates of koala density and, importantly, associated measures of uncertainty as well as an ability to model spatial variations in density across an array. Caution is needed when applying models to higher-density populations where home ranges overlap extensively and calls are evenly spread across the array.
Implications: The results add to the opportunities of acoustic methods for wildlife, especially where monitoring of density requires cost-effective repeat surveys.
Keywords: abundance, auditory communication, conservation ecology, passive acoustics, population modelling, threatened species, wildlife management.
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