A comparison of methods for monitoring a sparse population of the red fox (Vulpes vulpes) subject to lethal control using GPS telemetry, camera traps and sand plots
Andrew Carter A B * , Joanne M. Potts C , Joanne Stephens A and David A. Roshier A DA Australian Wildlife Conservancy, PO Box 8070, Subiaco East, WA 6008, Australia.
B Gulbali Institute of Agriculture, Water and Environment, Charles Sturt University, PO Box 789, Albury, NSW 2640, Australia.
C The Analytical Edge Pty Ltd, PO Box 47, Blackmans Bay, Tas. 7052, Australia.
D School of Animal and Veterinary Science, University of Adelaide, Roseworthy, SA 5371, Australia.
Wildlife Research 50(5) 366-380 https://doi.org/10.1071/WR22017
Submitted: 5 February 2022 Accepted: 23 August 2022 Published: 14 October 2022
© 2023 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: The introduced red fox has driven the decline or extinction of numerous wildlife species in Australia, yet little information exists on the population densities of foxes in most ecosystems. Fox monitoring programs will differ widely depending on the goals of management, which, in turn, will determine whether the appropriate metric is a density estimate, or some proxy thereof, and the time and resources required.
Aims: This study aims to assist wildlife managers to design fit-for-purpose monitoring programs for foxes by providing a better understanding of the utility and precision of various monitoring methods.
Methods: We surveyed foxes monthly over four consecutive years in a semi-arid region of Australia by using sand plots, camera traps and GPS telemetry. The resultant data were used to produce population estimates from one count-based method, two spatially explicit methods, and two activity indices.
Key results: The incorporation of GPS-collar data into the spatial capture–recapture approaches greatly reduced uncertainty in estimates of abundance. Activity indices from sand plots were generally higher and more variable than were indices derived from camera traps, whereas estimates from N-mixture models appeared to be biased high.
Conclusions: Our study indicated that the Allen–Engeman index derived from camera-trap data provided an accurate reflection of change in the underlying fox density, even as density declined towards zero following introduction of lethal control. This method provides an efficient means to detect large shifts in abundance, whether up or down, which may trigger a change to more laborious, but precise, population monitoring methods. If accuracy is paramount (e.g. for reintroduction programs) spatially explicit methods augmented with GPS data provide robust estimates, albeit at a greater cost in resources and expertise than does an index.
Implications: Our study demonstrated that the shorter the survey period is, the greater is the likelihood that foxes are present but not detected. As such, if limited resources are available, longer monitoring periods conducted less frequently will provide a more accurate reflection of the underlying fox population than do shorter monitoring periods conducted more often.
Keywords: canid pest ejector, fox baiting, mark–resight, N-mixture model, population index, predator control, sodium fluoroacetate, spatially explicit.
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