Assessing species misidentification rates through quality assurance of vegetation monitoring
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Most studies of observer discrepancies in vegetation recording have beenlimited in the extent to which they can separate different sources of error. Itis straightforward to quantify the degree of disparity between two specieslistsbut not clear how to allocate a particular discrepancy to a specific cause.Misidentification is especially difficult to detect, and is rarely discussed inthe literature. The vegetation monitoring protocol devised by the UnitedKingdomEnvironmental Change Network (ECN) splits each plot to be recorded into cells,within each of which a species list is compiled. This provides an objectivemeasure of the frequency of occurrence of individual species, in place of themore subjective estimation of cover, and allows within-plot variation to bequantified. An added advantage of the ECN methodology is that botanicalexpertise and the use of cells can be combined in quality assurance (QA)studiesto detect instances of consistent misidentification of species, therebyincreasing the repeatability of vegetation recording and enhancing thepossibility of detecting change.This paper reports an analysis of the data obtained from a 1996 ECN QA exerciseand describes the methods used to pinpoint the most likely sources ofdiscrepancies between the original site surveys and the QA survey. Overall itisestimated that 5.9% of specimens were misidentified at species level and 1.9%atgenus level, though it is detectable that sites employing consultant surveyorsachieved slightly better results. Misidentification rates are particularly highfor the lower plants and for woodland plots. The number of unmatched records(the pseudoturnover rate) is high, 24%, but comparable to other studies. Thisdoes not seem to be the result, to any great extent, of seasonal changes oridentification problems, but appears to be largely due to overlooking andpartlya result of relocation problems. The overall percentage agreement betweensurveyors was 57%, also comparable with other studies.
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- Assessing species misidentification rates through quality assurance of vegetation monitoring
Volume 165, Issue 1 , pp 101-115
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