185 17 706 4 2745 document 706 Austen_etal_ 2018_PeerJ_Newt_Expert_data.xlsx application/vnd.openxmlformats-officedocument.spreadsheetml.sheet f1afffaf0c8c792717c6107987c7547d MD5 43456 2018-01-18 15:46:08 https://data.kent.ac.uk/185/1/Austen_etal_%202018_PeerJ_Newt_Expert_data.xlsx 185 1 1 application/vnd.openxmlformats-officedocument.spreadsheetml.sheet application/vnd.ms-excel Survey results en public cc_by_4

Austen_etal_ 2018_PeerJ_Newt_Expert_data.xlsx

data archive 3365 disk0/00/00/01/85 2021-08-05 14:16:52 2025-06-03 08:38:21 2021-08-05 14:16:52 data_collection show g.e.austen@kent.ac.uk Austen Gail E. g.e.austen@kent.ac.uk 0000-0001-6005-4869 Bindemann Markus m.bindemann@kent.ac.uk 0000-0002-9608-4186 Griffiths Richard A. r.a.griffiths@kent.ac.uk 0000-0002-5533-1013 Roberts David L. d.l.roberts@kent.ac.uk 0000-0001-6788-2691 BF QH QH541 QH75 QL 51300 71000 52100 public This dataset was moved to KDR. The original location of this item was https://kar.kent.ac.uk/65753 Emerging technologies have led to an increase in species observations being recorded via digital images. Such visual records are easily shared, and are often uploaded to online communities when help is required to identify or validate species. Although this is common practice, little is known about the accuracy of species identification from such images. Using online images of newts that are native and non-native to the UK, this study asked holders of great crested newt (Triturus cristatus) licences (issued by UK authorities to permit surveying for this species) to sort these images into groups, and to assign species names to those groups. All of these experts identified the native species, but agreement among these participants was low, with some being cautious in committing to definitive identifications. Individuals’ accuracy was also independent of both their experience and self-assessed ability. Furthermore, mean accuracy was not uniform across species (69–96%). These findings demonstrate the difficulty of accurate identification of newts from a single image, and that expert judgements are variable, even within the same knowledgeable community. We suggest that identification decisions should be made on multiple images and verified by more than one expert, which could improve the reliability of species data. 2021-07-28 University of Kent dataset https://kar.kent.ac.uk/65753/ publication 10.7717/peerj.4157 DOI https://kar.kent.ac.uk/65785/ https://doi.org/10.7717/peerj.4157 IsSupplementTo pub 2018-01-18 published 2021-08-05 2018-01-18 2021-02-16 13100 School of Anthropology and Conservation 2021-02-16 13100/1 Biodiversity Conservation Group 2021-02-16 13100/2 Biodiversity Management Group 2021-02-16 13100/7 DICE (Durrell Institute of Conservation and Ecology) 2021-02-16 13600 School of Psychology 2021-02-16 13600/2 Applied Psychology 2022-04-14 13100 0 School of Anthropology and Conservation 2022-04-14 13100/1 1 Biodiversity Conservation Group 2022-04-14 13100/2 2 Biodiversity Management Group 2022-04-14 13100/7 3 DICE (Durrell Institute of Conservation and Ecology) 2022-04-14 13600 4 School of Psychology 2022-04-14 13600/2 5 Applied Psychology 2025-06-03 15100 School of Anthropology and Conservation 2025-06-03 15110 DICE (Durrell Institute of Conservation and Ecology) 2025-06-03 15400 School of Psychology English 2018-01-18 University of Kent Academic Repository KAR 10.22024/UniKent/01.01.185