Australian Mammalogy Australian Mammalogy Society
Journal of the Australian Mammal Society
RESEARCH ARTICLE

Spatial modelling of bilby (Macrotis lagotis) and rabbit (Oryctolagus cuniculus) pellets within a predator-proof enclosure

Gregory W. Lollback A C , J. Ernest Dunwoody B , Rachel Mebberson A , Jonathan D. Shuker A , Tahlie Page A , Sarann J. Hayles A , Nicolas Rakotopare A , Xiaoye Liu B and Jean-Marc Hero A
+ Author Affiliations
- Author Affiliations

A Environmental Futures Research Institute, Griffith University, Gold Coast, Qld 4222, Australia.

B School of Civil Engineering and Surveying, University of Southern Queensland, Toowoomba, Qld 4350, Australia.

C Corresponding author. Email: g.lollback@griffith.edu.au

Australian Mammalogy - https://doi.org/10.1071/AM16045
Submitted: 26 August 2016  Accepted: 11 May 2017   Published online: 31 July 2017

Abstract

A traditional design-reliant estimate of abundance is calculated by multiplying a density estimate obtained from transects to reflect the size of the study area. This type of estimate tells nothing about the nature of a species’ distribution between the samples. In contrast, model-based inference can better estimate abundance by interpolating transect estimates over the study area with the aid of covariates. This study used density surface modelling (DSM) to predict spatial distribution of greater bilby (Macrotis lagotis) and rabbit (Oryctolagus cuniculus) pellets within a predator-proof enclosure at Currawinya National Park, south-west Queensland. Pellets and latrines were counted using distance sampling and plot sampling on 30 PPBio plots during 2012 and 2014. Pellets and latrines were not strongly associated with habitat features, reflecting the generalist nature of both species. Bilby pellets were found on 23 plots in 2012 and 5 plots in 2014. Rabbit pellets were present on 29 plots in 2012 and 16 plots during 2014. These substantial declines in pellet abundances coincided with invasion of the feral cat (Felis catus) into the enclosure. While DSM modelling can allow managers to make informed decisions about applying survey effort or management practices, it is not suited to all species or situations.

Additional keywords: distance sampling, pellet, PPBio, predation.


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