Inter- and intra-observer variation in phytolith morphometry

生物 植硅岩 变化(天文学) 进化生物学 解剖 植物 花粉 天体物理学 物理
作者
Welmoed A. Out,Rand R. Evett,Kristýna Hošková,Robert C. Power,Javier Ruiz-Pérez,Monica Tromp,Luc Vrydaghs,Kali Wade,Mario Hasler
出处
期刊:Annals of Botany [Oxford University Press]
被引量:1
标识
DOI:10.1093/aob/mcae116
摘要

Abstract Background Archaeobotanists and palaeoecologists use geometric morphometrics extensively to identify plant opal phytoliths. Particularly when applied to assemblages of phytoliths from concentrations retrieved from closed contexts, morphometric data from archaeological phytoliths compared with similar data from reference material can allow taxonomic attribution. Observer variation is one aspect of phytolith morphometry that has received little attention but might be an important source of error and a potential cause of misidentification of plant remains. Scope To investigate inter- and intra-observer variation in phytolith morphometry, eight researchers (observers) from different laboratories measured 50 samples each from three phytolith morphotypes (Bilobate, Bulliform flabellate and Elongate dendritic) three times, under the auspices of the International Committee for Phytolith Morphometrics (ICPM). Methods Data for 17 size and shape variables were collected for each phytolith by manually digitizing a phytolith outline (mask) from a photograph, followed by measurement of the mask with open-source morphometric software. Key results Inter-observer variation ranged from 0 to 23 % difference from the mean of all observers. Intra-observer variation ranged from 0 to 9 % difference from the mean of individual observers per week. Inter- and intra-observer variation was generally higher among inexperienced researchers. Conclusions Scaling errors were a major cause of variation and occurred more with less experienced researchers, which is likely to be related to familiarity with data collection. The results indicate that inter- and intra-observer variation can be reduced substantially by providing clear instructions for and training with the equipment, photograph capturing, software, data collection and data cleaning. In this paper, the ICPM provides recommendations to minimize variation. Advances in automatic data collection might eventually reduce inter- and intra-observer variation, but until this is common practice, the ICPM recommends that phytolith morphometric analyses adhere to standardized guidelines to assure that measured phytolith variables are accurate, consistent and comparable between different researchers and laboratories.
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