2009
DOI: 10.1007/s00300-009-0649-7
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Inter- and intra-researcher variation in measurement of morphometrics on Steller sea lions (Eumetopias jubatus)

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Cited by 7 publications
(6 citation statements)
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“…This is a reminder that some errors could result from variation in direct measurements, as significant differences in inter‐researcher length measurements can occur (e.g. Waite & Mellish, ). CVs of repeat measurements were comparable to other laser photogrammetry studies (1.5–3.7%) (Rowe & Dawson, ; Deakos, ; Webster et al ., ) but were slightly higher than CVs for repeat physical measurements of adult dolphins (0.705%) (Read et al ., ).…”
Section: Discussionmentioning
confidence: 99%
“…This is a reminder that some errors could result from variation in direct measurements, as significant differences in inter‐researcher length measurements can occur (e.g. Waite & Mellish, ). CVs of repeat measurements were comparable to other laser photogrammetry studies (1.5–3.7%) (Rowe & Dawson, ; Deakos, ; Webster et al ., ) but were slightly higher than CVs for repeat physical measurements of adult dolphins (0.705%) (Read et al ., ).…”
Section: Discussionmentioning
confidence: 99%
“…The difference between the interobserver rates could be because two observers measured animals using the remote method during a single field season, whereas several researchers performed physical measurements over several field seasons from 1972 to 2014. Waite and Mellish [2009] emphasize that interobserver error rates in physical measurements are rarely compared with error rates in photogrammetry. In their study comparing these two measurement methods in sea lions, they found no significant differences between interobserver rates [Waite & Mellish, 2009].…”
Section: Comparison and Critiquementioning
confidence: 99%
“…For example, when the only phenotypic characteristics to use for distinguishing 2 photographs include color hue or saturation, these differences can be difficult for humans to see. As noted by other authors, using trained and qualified users may decrease the false acceptance rate (Huffard et al , Schofield et al , Waite and Mellish ), but we suggest that users use a test data set of known individuals to estimate false acceptance rate before using results from our approach to estimate population parameters. Users could test their false acceptance error by taking ≥2 photographs of the same individual, removing the background or other distinguishing characteristics within the photographs using photograph manipulation software, and testing their ability to match them among photographs of different individuals.…”
Section: Discussionmentioning
confidence: 62%