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Anthropogenic resource subsidies determine space use by Australian arid zone dingoes: an improved resource selection modelling approach

Newsome, Thomas M., Ballard, Guy-Anthony, Dickman, Christopher R., Fleming, Peter J.S. and Howden, Chris 2013, Anthropogenic resource subsidies determine space use by Australian arid zone dingoes: an improved resource selection modelling approach, PLoS one, vol. 8, no. 5, pp. 1-11, doi: 10.1371/journal.pone.0063931.

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Title Anthropogenic resource subsidies determine space use by Australian arid zone dingoes: an improved resource selection modelling approach
Author(s) Newsome, Thomas M.ORCID iD for Newsome, Thomas M. orcid.org/0000-0003-3457-3256
Ballard, Guy-Anthony
Dickman, Christopher R.
Fleming, Peter J.S.
Howden, Chris
Journal name PLoS one
Volume number 8
Issue number 5
Article ID e63931
Start page 1
End page 11
Total pages 11
Publisher PLoS
Place of publication San Francisco, Calif.
Publication date 2013
ISSN 1932-6203
Keyword(s) Animals
Australia
Behavior, Animal
Ecosystem
Environment
Female
Geographic Information Systems
Geographic Mapping
Geography
Human Activities
Humans
Male
Models, Statistical
Predatory Behavior
Remote Sensing Technology
Spatio-Temporal Analysis
Wolves
Summary Dingoes (Canis lupus dingo) were introduced to Australia and became feral at least 4,000 years ago. We hypothesized that dingoes, being of domestic origin, would be adaptable to anthropogenic resource subsidies and that their space use would be affected by the dispersion of those resources. We tested this by analyzing Resource Selection Functions (RSFs) developed from GPS fixes (locations) of dingoes in arid central Australia. Using Generalized Linear Mixed-effect Models (GLMMs), we investigated resource relationships for dingoes that had access to abundant food near mine facilities, and for those that did not. From these models, we predicted the probability of dingo occurrence in relation to anthropogenic resource subsidies and other habitat characteristics over ∼ 18,000 km(2). Very small standard errors and subsequent pervasively high P-values of results will become more important as the size of data sets, such as our GPS tracking logs, increases. Therefore, we also investigated methods to minimize the effects of serial and spatio-temporal correlation among samples and unbalanced study designs. Using GLMMs, we accounted for some of the correlation structure of GPS animal tracking data; however, parameter standard errors remained very small and all predictors were highly significant. Consequently, we developed an alternative approach that allowed us to review effect sizes at different spatial scales and determine which predictors were sufficiently ecologically meaningful to include in final RSF models. We determined that the most important predictor for dingo occurrence around mine sites was distance to the refuse facility. Away from mine sites, close proximity to human-provided watering points was predictive of dingo dispersion as were other landscape factors including palaeochannels, rocky rises and elevated drainage depressions. Our models demonstrate that anthropogenically supplemented food and water can alter dingo-resource relationships. The spatial distribution of such resources is therefore critical for the conservation and management of dingoes and other top predators.
Language eng
DOI 10.1371/journal.pone.0063931
Field of Research 050206 Environmental Monitoring
MD Multidisciplinary
Socio Economic Objective 0 Not Applicable
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2013, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089974

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.