Reliability of environmental DNA surveys to detect pond occupancy by newts at a national scale
Buxton, Andrew, Diana, Alex, Matechou, Eleni, Griffin, Jim and Griffiths, Richard (2022) Reliability of environmental DNA surveys to detect pond occupancy by newts at a national scale. Scientific reports. ISSN 2045-2322
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Buxton et al 2022 Reliability of eDNA surveys to detect pond occupancy by newts at a national scale.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
The distribution assessment and monitoring of species is key to reliable environmental impact assessments and conservation interventions. Considerable efort is directed towards survey and monitoring of great crested newts (Triturus cristatus) in England. Surveys are increasingly undertaken using indirect methodologies, such as environmental DNA (eDNA). We used a large data set to estimate national pond occupancy rate, as well as false negative and false positive error rates, for commercial eDNA protocols. Additionally, we explored a range of habitat, landscape and climatic variables as predictors of pond occupancy. In England, 20% of ponds were estimated to be occupied by great crested newts. Pond sample collection error rates were estimated as 5.2% false negative and 1.5% false positive. Laboratory error indicated a negligible false negative rate when 12 qPCR replicates were used. Laboratory false positive error was estimated at 2% per qPCR replicate and is therefore exaggerated by high levels of laboratory replication. Including simple habitat suitability variables into the model revealed the importance of fish, plants and shading as predictors of newt presence. However, variables traditionally considered as important for newt presence may need more precise and consistent measurement if they are to be employed as reliable predictors in modelling exercises.
| Item Type: | Article |
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| Keywords: | Ecological modelling Ecology Molecular ecology Wetlands ecology |
| Divisions: | Real Estate and Land Management |
| Depositing User: | Dr Andrew Buxton |
| Date Deposited: | 31 Jan 2022 09:28 |
| Last Modified: | 31 Jan 2022 09:30 |
| URI: | https://rau.repository.guildhe.ac.uk/id/eprint/16513 |
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