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Characterisation of false-positive observations in botanical surveys
- Source :
- PeerJ, PeerJ, Vol 5, p e3324 (2017)
- Publication Year :
- 2017
- Publisher :
- PeerJ, 2017.
-
Abstract
- Errors in botanical surveying are a common problem. The presence of a species is easily overlooked, leading to false-absences; while misidentifications and other mistakes lead to false-positive observations. While it is common knowledge that these errors occur, there are few data that can be used to quantify and describe these errors. Here we characterise false-positive errors for a controlled set of surveys conducted as part of a field identification test of botanical skill. Surveys were conducted at sites with a verified list of vascular plant species. The candidates were asked to list all the species they could identify in a defined botanically rich area. They were told beforehand that their final score would be the sum of the correct species they listed, but false-positive errors counted against their overall grade. The number of errors varied considerably between people, some people create a high proportion of false-positive errors, but these are scattered across all skill levels. Therefore, a person’s ability to correctly identify a large number of species is not a safeguard against the generation of false-positive errors. There was no phylogenetic pattern to falsely observed species, however, rare species are more likely to be false-positive as are species from species rich genera. Raising the threshold for the acceptance of an observation reduced false-positive observations dramatically, but at the expense of more false negative errors. False-positive errors are higher in field surveying of plants than many people may appreciate. Greater stringency is required before accepting species as present at a site, particularly for rare species. Combining multiple surveys resolves the problem, but requires a considerable increase in effort to achieve the same sensitivity as a single survey. Therefore, other methods should be used to raise the threshold for the acceptance of a species. For example, digital data input systems that can verify, feedback and inform the user are likely to reduce false-positive errors significantly.
- Subjects :
- 0106 biological sciences
Rarity
Rare species
lcsh:Medicine
Plant Science
Phylogenetic signal
Biology
010603 evolutionary biology
01 natural sciences
General Biochemistry, Genetics and Molecular Biology
Sensitivity
Habitat survey
Statistics
Common knowledge
Set (psychology)
Ecology
Shropshire
010604 marine biology & hydrobiology
General Neuroscience
lcsh:R
Field identification
Type 1 errors
nutritional and metabolic diseases
General Medicine
Biodiversity
15. Life on land
nervous system diseases
Identification (information)
Phylogenetic Pattern
Specificity
General Agricultural and Biological Sciences
False-presence
Global biodiversity
Type I and type II errors
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- PeerJ, PeerJ, Vol 5, p e3324 (2017)
- Accession number :
- edsair.doi.dedup.....d458595ba4f67121867bab40ec6a4bb5
- Full Text :
- https://doi.org/10.7287/peerj.preprints.2927