Abstract
Archaeobotanists and palaeoecologists extensively use geometric morphometrics 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 may allow taxonomic attribution. Observer variation is one aspect of phytolith morphometry that has received little attention but may be an important source of error, and hence cause of potential misidentification of plant remains.BACKGROUNDArchaeobotanists and palaeoecologists extensively use geometric morphometrics 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 may allow taxonomic attribution. Observer variation is one aspect of phytolith morphometry that has received little attention but may be an important source of error, and hence cause of potential misidentification of plant remains.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).SCOPETo 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).Data for 17 size and shape variables were collected for each phytolith by manually digitising a phytolith outline (mask) from a photograph, followed by measurement of the mask with open-source morphometric software.METHODSData for 17 size and shape variables were collected for each phytolith by manually digitising a phytolith outline (mask) from a photograph, followed by measurement of the mask with open-source morphometric software.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.KEY RESULTSInter-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.Scaling errors were a major cause of variation and occurred more with less experienced researchers, which is likely related to familiarity with data collection. The results indicate that inter- and intra-observer variation can be substantially reduced by providing clear instructions for and training with the equipment, photo capturing, software, data collection and data cleaning. In this paper, the ICPM provides recommendations to minimise variation.Advances in automatic data collection may eventually reduce inter- and intra-observer variation, but until this is common practice, the ICPM recommends that phytolith morphometric analyses adhere to standardised guidelines to assure that measured phytolith variables are accurate, consistent and comparable between different researchers and laboratories.CONCLUSIONSScaling errors were a major cause of variation and occurred more with less experienced researchers, which is likely related to familiarity with data collection. The results indicate that inter- and intra-observer variation can be substantially reduced by providing clear instructions for and training with the equipment, photo capturing, software, data collection and data cleaning. In this paper, the ICPM provides recommendations to minimise variation.Advances in automatic data collection may eventually reduce inter- and intra-observer variation, but until this is common practice, the ICPM recommends that phytolith morphometric analyses adhere to standardised guidelines to assure that measured phytolith variables are accurate, consistent and comparable between different researchers and laboratories.