Comparison of methods to detect rare and cryptic species: a case study using the red fox (Vulpes vulpes) (original) (raw)

S. J. Vine A B , M. S. Crowther A C H , S. J. Lapidge D , C. R. Dickman A , N. Mooney E , M. P. Piggott F and A. W. English G

+ Author Affiliations

- Author Affiliations

A Institute of Wildlife Research, School of Biological Sciences, University of Sydney, NSW 2006, Australia.

B Present address: World Wildlife Fund-Australia, Level 13, 235 Jones Street, Ultimo, NSW 2007, Australia.

C Department of Environment and Climate Change (NSW), PO Box 1967, Hurstville, NSW 2220, Australia.

D Invasive Animals Cooperative Research Centre, 48 Oxford Terrace, Unley, SA 5601, Australia.

E Wildlife Management Branch and Fox Eradication Branch, Department of Primary Industries and Water, GPO Box 44, Hobart, Tas. 7001, Australia.

F Australian Centre for Biodiversity, School of Biological Sciences, Monash University, Clayton, Vic. 3800, Australia. Present address: The Fenner School of Environment and Society, Australian National University, Canberra, ACT 0200, Australia.

G Faculty of Veterinary Science, University of Sydney, Werombi Road, Camden, NSW 2570, Australia.

H Corresponding author. Email: m.crowther@usyd.edu.au

Wildlife Research 36(5) 436-446 https://doi.org/10.1071/WR08069
Submitted: 12 May 2008 Accepted: 4 May 2009 Published: 21 July 2009

Abstract

Choosing the appropriate method to detect and monitor wildlife species is difficult if the species is rare or cryptic in appearance or behaviour. We evaluated the effectiveness of the following four methods for detecting red foxes (Vulpes vulpes) on the basis of equivalent person hours in a rural landscape in temperate Australia: camera traps, hair traps (using morphology and DNA from hair follicles), scats from bait stations (using DNA derived from the scats) and spotlighting. We also evaluated whether individual foxes could be identified using remote collection of their tissues. Genetic analysis of hair samples was the least efficient method of detection among the methods employed because of the paucity of samples obtained and the lack of follicles on sampled hairs. Scat detection was somewhat more efficient. Scats were deposited at 17% of bait stations and 80% of scats were amplified with a fox-specific marker, although only 31% of confirmed fox scats could be fully genotyped at all six microsatellite loci. Camera trapping and spotlighting were the most efficient methods of detecting fox presence in the landscape. Spotlighting success varied seasonally, with fox detections peaking in autumn (80% of spotlighting transects) and being lowest in winter (29% of transects). Cameras detected foxes at 51% of stations; however, there was limited seasonality in detection, and success rates varied with camera design. Log-linear models confirmed these trends. Our results showed that the appropriate technique for detecting foxes varies depending on the time of the year. It is suggested that wildlife managers should consider both seasonal effects and species biology when attempting to detect rare or elusive species.

Acknowledgements

We thank the many volunteers who helped on the project, especially Jean Vine, Tom Newsome, James Hunter, Terry Hogan, and Steve Burgun, Brian Farrell and staff at Arthursleigh for assistance in the field. Special thanks go to Paul Meek, Bill Morris, Glen Saunders, Roger Pech and Eddy Gifford for their help, and Cici Legoe for veterinary supervision. Andrea Taylor and Chris Emms also provided invaluable input into the project. The Pest Animal Control and Invasive Animal CRCs, Australian Wool Innovation (through the OutFox II program) and the Tasmanian Fox Free Taskforce provided financial and logistical support, while the University of Sydney’s Animal Ethics Committee provided ethical approval (no. L04/6-2003/1/3370).

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