IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0163205.html
   My bibliography  Save this article

Dinosaur Metabolism and the Allometry of Maximum Growth Rate

Author

Listed:
  • Nathan P Myhrvold

Abstract

The allometry of maximum somatic growth rate has been used in prior studies to classify the metabolic state of both extant vertebrates and dinosaurs. The most recent such studies are reviewed, and their data is reanalyzed. The results of allometric regressions on growth rate are shown to depend on the choice of independent variable; the typical choice used in prior studies introduces a geometric shear transformation that exaggerates the statistical power of the regressions. The maximum growth rates of extant groups are found to have a great deal of overlap, including between groups with endothermic and ectothermic metabolism. Dinosaur growth rates show similar overlap, matching the rates found for mammals, reptiles and fish. The allometric scaling of growth rate with mass is found to have curvature (on a log-log scale) for many groups, contradicting the prevailing view that growth rate allometry follows a simple power law. Reanalysis shows that no correlation between growth rate and basal metabolic rate (BMR) has been demonstrated. These findings drive a conclusion that growth rate allometry studies to date cannot be used to determine dinosaur metabolism as has been previously argued.

Suggested Citation

  • Nathan P Myhrvold, 2016. "Dinosaur Metabolism and the Allometry of Maximum Growth Rate," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-35, November.
  • Handle: RePEc:plo:pone00:0163205
    DOI: 10.1371/journal.pone.0163205
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0163205
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0163205&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0163205?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Tom Kolokotrones & Van Savage & Eric J. Deeds & Walter Fontana, 2010. "Curvature in metabolic scaling," Nature, Nature, vol. 464(7289), pages 753-756, April.
    2. Pekka Kaitaniemi, 2008. "How to Derive Biological Information from the Value of the Normalization Constant in Allometric Equations," PLOS ONE, Public Library of Science, vol. 3(4), pages 1-4, April.
    3. Gregory M. Erickson & Peter J. Makovicky & Philip J. Currie & Mark A. Norell & Scott A. Yerby & Christopher A. Brochu, 2004. "Gigantism and comparative life-history parameters of tyrannosaurid dinosaurs," Nature, Nature, vol. 430(7001), pages 772-775, August.
    4. Langford E. & Schwertman N. & Owens M., 2001. "Is the Property of Being Positively Correlated Transitive?," The American Statistician, American Statistical Association, vol. 55, pages 322-325, November.
    5. Gregory M. Erickson & Kristina Curry Rogers & Scott A. Yerby, 2001. "Dinosaurian growth patterns and rapid avian growth rates," Nature, Nature, vol. 412(6845), pages 429-433, July.
    6. Nathan P Myhrvold, 2013. "Revisiting the Estimation of Dinosaur Growth Rates," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-24, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Eva Maria Griebeler & Jan Werner, 2018. "Formal comment on: Myhrvold (2016) Dinosaur metabolism and the allometry of maximum growth rate. PLoS ONE; 11(11): e0163205," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-18, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eva Maria Griebeler & Jan Werner, 2018. "Formal comment on: Myhrvold (2016) Dinosaur metabolism and the allometry of maximum growth rate. PLoS ONE; 11(11): e0163205," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-18, February.
    2. Eva Maria Griebeler & Nicole Klein & P Martin Sander, 2013. "Aging, Maturation and Growth of Sauropodomorph Dinosaurs as Deduced from Growth Curves Using Long Bone Histological Data: An Assessment of Methodological Constraints and Solutions," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-17, June.
    3. Nathan P Myhrvold, 2013. "Revisiting the Estimation of Dinosaur Growth Rates," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-24, December.
    4. Gorbunova, A.V. & Lebedev, A.V., 2022. "Nontransitivity of tuples of random variables with polynomial density and its effects in Bayesian models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 181-192.
    5. Zhang, Chunming & Li, Jialiang & Meng, Jingci, 2008. "On Stein's lemma, dependent covariates and functional monotonicity in multi-dimensional modeling," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2285-2303, November.
    6. Soichiro Kawabe & Seiji Matsuda & Naoki Tsunekawa & Hideki Endo, 2015. "Ontogenetic Shape Change in the Chicken Brain: Implications for Paleontology," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-16, June.
    7. Mokhtarian, Patricia L., 2016. "Presenting the Independence of Irrelevant Alternatives property in a first course on logit modeling," Journal of choice modelling, Elsevier, vol. 21(C), pages 25-29.
    8. Morris, Stephen, 2007. "The impact of obesity on employment," Labour Economics, Elsevier, vol. 14(3), pages 413-433, June.
    9. Frooman, Jeff, 2021. "Where MLM Intersects MFA: Morally Suspect Goods and the Grounds for Regulatory Action," Business Ethics Quarterly, Cambridge University Press, vol. 31(1), pages 138-161, January.
    10. Wiseman, Nathan & Sorensen, Todd A., 2017. "Bounds with Imperfect Instruments: Leveraging the Implicit Assumption of Intransitivity in Correlations," IZA Discussion Papers 10646, Institute of Labor Economics (IZA).
    11. Xu, Meng & Jiang, Mengke & Wang, Hua-Feng, 2021. "Integrating metabolic scaling variation into the maximum entropy theory of ecology explains Taylor's law for individual metabolic rate in tropical forests," Ecological Modelling, Elsevier, vol. 455(C).
    12. Michail Fragkias & José Lobo & Deborah Strumsky & Karen C Seto, 2013. "Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-8, June.
    13. Chen, Shi & Bao, Forrest Sheng, 2015. "Linking body size and energetics with predation strategies: A game theoretic modeling framework," Ecological Modelling, Elsevier, vol. 316(C), pages 81-86.
    14. Mitchell G Newberry & Daniel B Ennis & Van M Savage, 2015. "Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-18, August.
    15. Milotti, Edoardo & Vyshemirsky, Vladislav & Stella, Sabrina & Dogo, Federico & Chignola, Roberto, 2017. "Analysis of the fluctuations of the tumour/host interface," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 587-594.
    16. Witting, Lars, 2017. "The natural selection of metabolism and mass selects allometric transitions from prokaryotes to mammals," Theoretical Population Biology, Elsevier, vol. 117(C), pages 23-42.
    17. Riet Bork & Raoul P. P. P. Grasman & Lourens J. Waldorp, 2018. "Unidimensional factor models imply weaker partial correlations than zero-order correlations," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 443-452, June.
    18. David G Jenkins & Pedro F Quintana-Ascencio, 2020. "A solution to minimum sample size for regressions," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-15, February.
    19. Elif Tekin & David Hunt & Mitchell G Newberry & Van M Savage, 2016. "Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-28, November.
    20. Shing Chih Tsai & Jun Luo & Chi Ching Sung, 2017. "Combined variance reduction techniques in fully sequential selection procedures," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(6), pages 502-527, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0163205. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.