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Revisiting the Estimation of Dinosaur Growth Rates

Overview of attention for article published in PLOS ONE, December 2013
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Title
Revisiting the Estimation of Dinosaur Growth Rates
Published in
PLOS ONE, December 2013
DOI 10.1371/journal.pone.0081917
Pubmed ID
Authors

Nathan P. Myhrvold

Abstract

Previous growth-rate studies covering 14 dinosaur taxa, as represented by 31 data sets, are critically examined and reanalyzed by using improved statistical techniques. The examination reveals that some previously reported results cannot be replicated by using the methods originally reported; results from new methods are in many cases different, in both the quantitative rates and the qualitative nature of the growth, from results in the prior literature. Asymptotic growth curves, which have been hypothesized to be ubiquitous, are shown to provide best fits for only four of the 14 taxa. Possible reasons for non-asymptotic growth patterns are discussed; they include systematic errors in the age-estimation process and, more likely, a bias toward younger ages among the specimens analyzed. Analysis of the data sets finds that only three taxa include specimens that could be considered skeletally mature (i.e., having attained 90% of maximum body size predicted by asymptotic curve fits), and eleven taxa are quite immature, with the largest specimen having attained less than 62% of predicted asymptotic size. The three taxa that include skeletally mature specimens are included in the four taxa that are best fit by asymptotic curves. The totality of results presented here suggests that previous estimates of both maximum dinosaur growth rates and maximum dinosaur sizes have little statistical support. Suggestions for future research are presented.

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Geographical breakdown

Country Count As %
United States 2 2%
Australia 1 <1%
Netherlands 1 <1%
Canada 1 <1%
United Kingdom 1 <1%
Unknown 106 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 19 17%
Student > Ph. D. Student 18 16%
Researcher 14 13%
Student > Master 13 12%
Other 8 7%
Other 21 19%
Unknown 19 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 30%
Earth and Planetary Sciences 27 24%
Biochemistry, Genetics and Molecular Biology 6 5%
Medicine and Dentistry 5 4%
Physics and Astronomy 4 4%
Other 13 12%
Unknown 23 21%