Related Experiment Video
Updated: Jun 19, 2025
Software-Assisted Quantitative Measurement of Osteoarthritic Subchondral Bone Thickness
Published on: March 18, 2022
Inter- and intra-observer variation in phytolith morphometry
Welmoed A Out1, Rand Evett2, Kristýna Hošková3
1Department of Archaeological Science and Conservation, Moesgaard Museum, 8270, Højbjerg, Denmark.
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.
