Towards more efficient large-scale DNA-based detection of terrestrial mammal predators from scats

Sumaiya Quasim, Anna J. MacDonald, Stephen D. Sarre

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The DNA detection of wildlife from environmental samples has the potential to contribute significantly to wildlife management and ecological research. In terrestrial ecosystems, much work has focused on the identification of mammal predators from faecal (scat) samples. However, the relatively high time and financial costs of collecting and analysing scat DNA remain barriers to more widespread implementation of such DNA detection methods, especially for high-throughput surveys. Here, we evaluate methods used for DNA extraction from scats, as applied to detection of the Australian red fox, an introduced predator. We compare the relative costs of two approaches: the method previously used to screen thousands of scat samples in surveys over several years, and a modified version which involves swabbing scats at the time of collection and using a mechanised liquid handling platform to extract DNA from the swabs. We demonstrate that mechanised DNA extraction from swabs is more efficient than manual DNA extraction from whole scats, in terms of both time and resources. This provides a means for rapid, high-throughput screening of scats for the presence of mammal predators, enabling time-effective management responses to non-invasive surveys.

Original languageEnglish
Pages (from-to)387-393
Number of pages7
JournalMammal Research
Volume63
Issue number3
DOIs
Publication statusPublished - 1 Jul 2018

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mammal
predator
mammals
predators
DNA
feces
wildlife management
Vulpes vulpes
detection method
detection
terrestrial ecosystem
cost
sampling
wildlife
methodology
screening
liquid
liquids
extracts
resource

Cite this

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Towards more efficient large-scale DNA-based detection of terrestrial mammal predators from scats. / Quasim, Sumaiya; MacDonald, Anna J.; Sarre, Stephen D.

In: Mammal Research, Vol. 63, No. 3, 01.07.2018, p. 387-393.

Research output: Contribution to journalArticle

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