A comparison of mark–recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos
Rachel M. Fewster A C and Anthony R. Pople BA Department of Statistics, University of Auckland, Private Bag 92019, Auckland, New Zealand.
B Biosecurity Queensland, Department of Primary Industries and Fisheries, GPO Box 46, Brisbane, Qld 4001, Australia.
C Corresponding author. Email: r.fewster@auckland.ac.nz
Wildlife Research 35(4) 320-330 https://doi.org/10.1071/WR07078
Submitted: 29 June 2007 Accepted: 14 December 2007 Published: 27 June 2008
Abstract
Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark–recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark–recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark–recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark–recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km–2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.
Acknowledgements
We thank two referees and the editor for their constructive comments on this manuscript. We are grateful to the Queensland Parks and Wildlife Service for financial and logistical survey support, and to Geoff Lundie-Jenkins and Gordon Maag for acting as observers and organising survey logistics. We thank Mark Read for piloting the surveys, and Josie Carwardine for transcribing tapes. This project was also supported by an Australian Research Council Linkage grant to Hugh Possingham.
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