Power of faecal pellet count and camera trapping indices to monitor mammalian herbivore activity
Naomi E. Davis
A B * , Julian Di Stefano C , Jim Whelan D , John Wright B , Lorraine Taylor B , Graeme Coulson A and Holly Sitters C
+ Author Affiliations
- Author Affiliations
A School of BioSciences, The University of Melbourne, Vic. 3010, Australia.
B Parks Victoria, Environment and Science Division, Level 10, 535 Bourke Street, Melbourne, Vic. 3000, Australia.
C School of Ecosystem and Forest Sciences, University of Melbourne, 4 Water Street, Creswick, Vic. 3363, Australia.
D Parks Victoria, Eastern Region, Meeniyan-Promontory Road, Yanakie, Vic. 3960, Australia.
Wildlife Research 49(8) 686-697 https://doi.org/10.1071/WR21135
Submitted: 8 September 2021 Accepted: 28 February 2022 Published: 7 June 2022
© 2022 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: Monitoring spatial and temporal change in relative abundance using statistically powerful designs is a critical aspect of wildlife management. Many indices of relative abundance are available, but information regarding their influence on statistical power is limited.
Aims: We compared the statistical power associated with occurrence-based and frequency-based indices derived from faecal pellet counts and camera trapping to detect changes in the activity of five mammalian herbivores.
Methods: We deployed camera traps and counted faecal pellets in native vegetation subjected to four management treatments in south-eastern Australia. We used simulation coupled with generalised linear mixed models to investigate the statistical power associated with a range of effect sizes for each combination of species, survey method and data type.
Key results: The index derived from camera frequency data provided the greatest statistical power to detect species’ responses and was the only index capable of detecting small effect sizes with high power. The occurrence index from camera trapping did not provide the same level of statistical power. Indices derived from faecal pellet frequency data also detected spatial and temporal changes in activity levels for some species, but large numbers of plots were required to detect medium to large effect sizes. High power to detect medium to large effects could be achieved using occurrence indices derived from pellet presence–absence data, but required larger sample sizes compared to the camera frequency index.
Conclusions: Both camera trapping and pellet counts can be applied to simultaneously monitor the activity of multiple mammalian herbivore species with differing activity patterns, behaviour, body size and densities, in open and closed habitat. However, using frequency indices derived from camera trapping may improve management outcomes by maximising the statistical power of monitoring programs to detect changes in abundance and habitat use.
Implications: Frequency indices derived from camera trapping are expected to provide the most efficient method to detect changes in abundance. Where the use of cameras is cost prohibitive, occurrence indices derived from pellet presence–absence data can be used to detect medium to large effect sizes with high power. Nonetheless, the cost-effectiveness of camera trapping will improve as equipment costs are reduced and advances in automated image recognition and processing software are made.
Keywords: Axis porcinus, cost-effective, Macropus giganteus, mammal, management, monitoring, Oryctolagus cuniculus, sampling methods, survey methods, Vombatus ursinus, Wallabia bicolor.
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