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Effects of size and temperature on developmental time

Author

Listed:
  • James. F. Gillooly

    (The University of New Mexico)

  • Eric L. Charnov

    (The University of New Mexico)

  • Geoffrey B. West

    (Santa Fe Institute
    MS B285, Los Alamos National Laboratory)

  • Van M. Savage

    (Santa Fe Institute
    MS B285, Los Alamos National Laboratory
    Washington University)

  • James H. Brown

    (The University of New Mexico
    Santa Fe Institute)

Abstract

Body size and temperature are the two most important variables affecting nearly all biological rates and times1,2,3,4,5,6,7. The relationship of size and temperature to development is of particular interest, because during ontogeny size changes and temperature often varies8,9,10,11,12. Here we derive a general model, based on first principles of allometry and biochemical kinetics, that predicts the time of ontogenetic development as a function of body mass and temperature. The model fits embryonic development times spanning a wide range of egg sizes and incubation temperatures for birds and aquatic ectotherms (fish, amphibians, aquatic insects and zooplankton). The model also describes nearly 75% of the variation in post-embryonic development among a diverse sample of zooplankton. The remaining variation is partially explained by stoichiometry, specifically the whole-body carbon to phosphorus ratio. Development in other animals at other life stages is also described by this model. These results suggest a general definition of biological time that is approximately invariant and common to all organisms.

Suggested Citation

  • James. F. Gillooly & Eric L. Charnov & Geoffrey B. West & Van M. Savage & James H. Brown, 2002. "Effects of size and temperature on developmental time," Nature, Nature, vol. 417(6884), pages 70-73, May.
    • Handle: RePEc:nat:nature:v:417:y:2002:i:6884:d:10.1038_417070a
    DOI: 10.1038/417070a
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    Cited by:

    1. Usaku Reuben & Ahmad F. Ismail & Abdul L. Ahmad & Humphrey M. Maina & Aziah Daud, 2019. "Occupational and Environmental Risk Factors Influencing the Inducement of Erythema among Nigerian Laboratory University Workers with Multiple Chemical Exposures," IJERPH, MDPI, vol. 16(8), pages 1-13, April.
    2. Sun, Yajun & Wells, Mathew G., 2015. "The application of life-history and predation allometry to population dynamics to predict the critical density of extinction," Ecological Modelling, Elsevier, vol. 312(C), pages 136-149.
    3. Johnson, Scott N. & Zhang, Xiaoxian & Crawford, John W. & Gregory, Peter J. & Young, Iain M., 2007. "Egg hatching and survival time of soil-dwelling insect larvae: A partial differential equation model and experimental validation," Ecological Modelling, Elsevier, vol. 202(3), pages 493-502.
    4. Ha Kyung Lee & So Jeong Lee & Min Kyung Kim & Sang Don Lee, 2020. "Prediction of Plant Phenological Shift under Climate Change in South Korea," Sustainability, MDPI, vol. 12(21), pages 1-14, November.
    5. Hendriks, A. Jan, 2007. "The power of size: A meta-analysis reveals consistency of allometric regressions," Ecological Modelling, Elsevier, vol. 205(1), pages 196-208.
    6. Antonio S Gliozzi & Caterina Guiot & Pier Paolo Delsanto, 2009. "A New Computational Tool for the Phenomenological Analysis of Multipassage Tumor Growth Curves," PLOS ONE, Public Library of Science, vol. 4(4), pages 1-7, April.

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