“Visiting scientist effect”? Exploring the impact of time‐lags in the digitization of 2D landmark data

Measurement error (ME) in geometric morphometrics has been the subject of countless articles, but none specific to the effect of time lags on landmark digitization error. Yet, especially for visiting scientists working on museum collections, it is not uncommon to collect data in multiple rounds, wit...

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Vydané v:Anatomical record (Hoboken, N.J. : 2007) Ročník 308; číslo 12; s. 3230 - 3258
Hlavný autor: Cardini, Andrea
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Hoboken, USA John Wiley & Sons, Inc 01.12.2025
Wiley Subscription Services, Inc
Predmet:
Allometry
Anatomic Landmarks - anatomy & histology
Animals
Data collection
Digitization
Female
geometric morphometrics
Image Processing, Computer-Assisted - methods
Male
measurement error
Museums
precision
Procrustes
Sex Characteristics
Sexual dimorphism
Skull
Skull - anatomy & histology
Time Factors
measurement error
data collection
geometric morphometrics
precision
Procrustes
ISSN:1932-8486, 1932-8494, 1932-8494
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Shrnutí:Measurement error (ME) in geometric morphometrics has been the subject of countless articles, but none specific to the effect of time lags on landmark digitization error. Yet, especially for visiting scientists working on museum collections, it is not uncommon to collect data in multiple rounds, with interruptions of weeks or years. To explore the impact of time lags on Procrustes shape analysis, I repeatedly digitized the same landmarks, on photographs of crania of adult yellow‐bellied marmots, at progressively longer time intervals, ranging from a few hours to days, weeks and, in one case, many years. Using a battery of methods, I found that there is indeed a time‐related systematic ME suggesting the possibility of a “visiting scientist effect” biasing shape patterns. However, the relationship between time lags and the magnitude of the bias is not simple and linear, but complex. Interestingly, the impact of the bias on the results of tests of sexual dimorphism and allometry is modest, and mostly negligible, unless the design of the data collection is highly unbalanced. When this happens, as in a simulated case where females are digitized first and males only later (or vice versa), the effect of the bias on tests of biological variation becomes important and can even lead to opposite conclusions on group differences. I will discuss when systematic ME in landmark data is more problematic and how to try to mitigate the impact of a potential “visiting scientist effect” on shape analyses.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1932-8486
1932-8494
1932-8494
DOI:10.1002/ar.25649