DNA from carrion flies reveals which animals live nearby

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CC-0. https://pxhere.com/en/photo/364845

DNA sampled from carrion flies can reveal which animals live in an area, according to Australian and international researchers. They captured 920 flies from within a zoo and along an area extending 4 km away from it. Sampling the DNA, they detected 28 species of animals, nine of which lived in the zoo. The researchers say their findings highlight how DNA sampling techniques can be used to monitor biodiversity. 

Media release

From: The Royal Society

Analysing the effects of distance, taxon, and biomass on vertebrate detections using bulk-collected carrion fly iDNA

Invertebrate-derived DNA (iDNA) metabarcoding from carrion flies is a powerful, non-invasive tool that has value for assessing vertebrate diversity. However, unknowns exist around the factors that influence vertebrate detections, such as spatial limits to iDNA signals or if detections are influenced by taxonomic class or estimated biomass of the vertebrates of interest. Using a bulk-collection method, we captured flies from within a zoo and along transects extending 4 km away from this location. From 920 flies, we detected 28 vertebrate species. Of the 28 detected species, we identified nine species kept at the zoo: eight mammals and one bird, but no reptiles. iDNA detections were highly geographically localised, and only a few zoo animals were detected outside the zoo setting. However, due to the low number of detections in our dataset, we found no influence of the taxonomic group or the estimated biomass of animals on their detectability. Our data suggest that iDNA detections from bulk-collected carrion flies, at least in urban settings in Australia, are predominantly determined by geographic proximity to the sampling location. This study presents an important step in understanding how iDNA techniques can be used in biodiversity monitoring. 

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Royal Society Open Science
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Organisation/s: Curtin University, University of Otago
Funder: This work was supported by computational resources provided by the Pawsey Supercomputing Centre with funding from the Australian Goevrnment and the Government of Western Australia
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