Buxton, Andrew, Diana, Alex, Matechou, Eleni, Griffin, Jim, Griffiths, Richard A. (2022) Reliability of environmental DNA surveys to detect pond occupancy by newts at a national scale. Scientific Reports, 12 . Article Number 1295. E-ISSN 2045-2322. (doi:10.1038/s41598-022-05442-1) (KAR id:92844)
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Official URL: https://doi.org/10.1038/s41598-022-05442-1 |
Abstract
The distribution assessment and monitoring of species is key to reliable environmental impact assessments and conservation interventions. Considerable effort 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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DOI/Identification number: | 10.1038/s41598-022-05442-1 |
Additional information: | For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising |
Uncontrolled keywords: | newts, environmental DNA, eDNA, Ecological modelling, Ecology, Molecular ecology, Wetlands ecology |
Subjects: | Q Science > QH Natural history > QH75 Conservation (Biology) |
Divisions: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology) |
Funders: | Natural Environment Research Council (https://ror.org/02b5d8509) |
Depositing User: | Eleni Matechou |
Date Deposited: | 25 Jan 2022 12:25 UTC |
Last Modified: | 05 Nov 2024 12:58 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/92844 (The current URI for this page, for reference purposes) |
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