- Title
- A DNA toolbox for non-invasive genetic studies of sambar deer (Rusa unicolor)
- Creator
- Davies, Chris; Wright, Wendy; Wedrowicz, Faye; Hogan, Fiona
- Date
- 2020
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/171459
- Identifier
- vital:14325
- Identifier
-
https://doi.org/10.1071/am18032
- Identifier
- ISBN:0310-0049
- Abstract
- Invasive sambar deer (Rusa unicolor) are having significant detrimental impacts on natural environments in south-eastern Australia. Little, however, is known about their ecology, limiting evidence-based management strategies directed at reducing deer impacts. Genetic data, generated from DNA isolated from deer scats, can be used to fill ecological knowledge gaps. This study outlines a non-invasive genetic sampling strategy by which good-quality DNA from a single deer scat can be used to determine (1) species of origin, (2) sex and (3) a unique DNA profile. DNA from deer tissue and sambar deer scat samples were used to develop and optimise molecular methods to collect reliable genetic information. A DNA toolbox is presented that describes how to find, collect and store scat samples, isolate DNA and use molecular markers to generate informative genetic data. Generating genetic data using this approach will support studies aimed at acquiring ecological knowledge about sambar deer. Such knowledge will be critical for developing evidence-based recommendations to improve on-ground management decisions for sambar deer.
- Publisher
- CSIRO Publishing
- Relation
- Australian Mammalogy Vol. 42, no. 1 (2020), p. 58-66
- Rights
- Copyright @ Australian Mammal Society 2020
- Rights
- This metadata is freely available under a CCO license
- Rights
- Open Access
- Subject
- 0502 Environmental Science and Management; 0602 Ecology; 0608 Zoology; Cervidae; Genetics; Invasive species; Wildlife management; Cats felis-catus; Genotyping errors; Individual identification; Microsatellite markers; Defecation rate; Management; Impacts; Quality; Sex; Populations
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