Nonsampling error in vegetation surveys: understanding error types and recommendations for reducing their occurrence


Observer error is ubiquitous in vegetation sampling. Observer error, along with other types of related nonsampling error, may result in species richness being artificially underestimated (i.e., false-negative errors) or artificially overestimated (i.e., false-positive errors). Because of the manner in which observer error is usually quantified, there exists a strong bias against the discovery of false positives. At least seven different types of nonsampling errors can occur when surveying vegetation species composition: overlooking, misidentification, cautious, mythical, anecdotal, transcription, and relocation. Six of these error types can result in false negatives and five can result in false positives. Another type of observer error that can occur in plant surveys is estimation error, which occurs when abundances are not accurately estimated. There are many potential underlying causes of nonsampling error. Humans observers, even when highly trained and experienced, are prone to commit errors through slips, lapses, and mistakes. A number of contributing factors of observer error have been identified, including characteristics associated with the vegetation, the environment, and the observers themselves; design-based flaws may also occur. Although it may not be possible to eliminate all sources of nonsampling error, most can be reduced through understanding the mechanisms underlying the various types of error, followed by training exercises and the consistent use of appropriate operating procedures.



Document Type




Cautious error, Misidentification error, Mythical error, Nonsampling error, Observer error, Overlooking error

Publication Date


Journal Title

Plant Ecology