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Developmental cost theory predicts thermal environment and vulnerability to global warming


Metazoans must develop from zygotes to feeding organisms. In doing so, developing offspring consume up to 60% of the energy provided by their parent. The cost of development depends on two rates: metabolic rate, which determines the rate that energy is used; and developmental rate, which determines the length of the developmental period. Both development and metabolism are highly temperature-dependent such that developmental costs should be sensitive to the local thermal environment. Here, we develop, parameterize and test developmental cost theory, a physiologically explicit theory that reveals that ectotherms have narrow thermal windows in which developmental costs are minimized (Topt). Our developmental cost theory-derived estimates of Topt predict the natural thermal environment of 71 species across seven phyla remarkably well (R2 ~0.83). Developmental cost theory predicts that costs of development are much more sensitive to small changes in temperature than classic measures such as survival. Warming-driven changes to developmental costs are predicted to strongly affect population replenishment and developmental cost theory provides a mechanistic foundation for determining which species are most at risk. Developmental cost theory predicts that tropical aquatic species and most non-nesting terrestrial species are likely to incur the greatest increase in developmental costs from future warming.

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Fig. 1: Graphical representation of temperature-dependent developmental cost theory.
Fig. 2: Development costs across temperatures for developing ectotherms.
Fig. 3: Effect of developmental environment on mismatch between Topt and Tmid for 71 ectotherms.
Fig. 4: Change in performance associated with a 20% increase (relative to the range experienced by that species) in temperature relative to the thermal optimum.

Data availability

The data used in these meta-analyses are available from Dryad:


  1. Mueller, C. A., Joss, J. M. P. & Seymour, R. S. The energy cost of embryonic development in fishes and amphibians, with emphasis on new data from the Australian lungfish, Neoceratodus forsteri. J. Comp. Physiol. B 181, 43–52 (2011).

    Article  Google Scholar 

  2. Bennett, C. E. & Marshall, D. J. The relative energetic costs of the larval period, larval swimming and metamorphosis for the ascidian Diplosoma listerianum. Mar. Freshwat. Behav. Physiol. 38, 21–29 (2005).

    Article  Google Scholar 

  3. Pettersen, A. K., White, C. R., Bryson-Richardson, R. J. & Marshall, D. J. Linking life-history theory and metabolic theory explains the offspring size-temperature relationship. Ecol. Lett. 22, 518–526 (2019).

    Article  Google Scholar 

  4. Kamler, E. Early Life History of Fish—An Energetics Approach, Vol. 4 (Chapman and Hall, 1992).

  5. Kamler, E. Parent–egg–progeny relationships in teleost fishes: an energetics perspective. Rev. Fish Biol. Fish. 15, 399–421 (2005).

    Article  Google Scholar 

  6. Zuo, W. Y., Moses, M. E., West, G. B., Hou, C. & Brown, J. H. A general model for effects of temperature on ectotherm ontogenetic growth and development. Proc. R. Soc. B 279, 1840–1846 (2012).

    Article  Google Scholar 

  7. Gillooly, J. F., Charnov, E. L., West, G. B., Savage, V. M. & Brown, J. H. Effects of size and temperature on developmental time. Nature 417, 70–73 (2002).

    Article  CAS  Google Scholar 

  8. Pinsky, M. L., Eikeset, A. M., McCauley, D. J., Payne, J. L. & Sunday, J. M. Greater vulnerability to warming of marine versus terrestrial ectotherms. Nature 569, 108–111 (2019).

    Article  CAS  Google Scholar 

  9. Pechenik, J. A. Larval experience and latent effects—metamorphosis is not a new beginning. Integr. Comp. Biol. 46, 323–333 (2006).

    Article  Google Scholar 

  10. Marshall, D. J., Pettersen, A. K. & Cameron, H. A global synthesis of offspring size variation, its eco-evolutionary causes and consequences. Funct. Ecol. 32, 1436–1446 (2018).

    Article  Google Scholar 

  11. Vance, R. R. On reproductive strategies in marine benthic invertebrates. Am. Nat. 107, 339–352 (1973).

    Article  Google Scholar 

  12. Shine, R. Manipulative mothers and selective forces: the effects of reproduction on thermoregulation in reptiles. Herpetologica 68, 289–298 (2012).

    Article  Google Scholar 

  13. Goller, M., Goller, F. & French, S. S. A heterogeneous thermal environment enables remarkable behavioral thermoregulation in Uta stansburiana. Ecol. Evol. 4, 3319–3329 (2014).

    Article  Google Scholar 

  14. Steele, J. H. A comparison of terrestrial and marine ecological systems. Nature 313, 355–358 (1985).

    Article  Google Scholar 

  15. Melampy, R. M. & Willis, E. R. Respiratory metabolism during larval and pupal development of the female honeybee (Apis mellifica L.). Physiol. Zool. 12, 302–311 (1939).

    Article  CAS  Google Scholar 

  16. Seebacher, F., White, C. R. & Franklin, C. E. Physiological plasticity increases resilience of ectothermic animals to climate change. Nat. Clim. Change 5, 61–66 (2014).

    Article  Google Scholar 

  17. Berrigan, D. & Partridge, L. Influence of temperature and activity on the metabolic rate of adult Drosophila melanogaster. Comp. Biochem. Physiol. A 118, 1301–1307 (1997).

    Article  CAS  Google Scholar 

  18. Alton, L. A., Condon, C., White, C. R. & Angilletta, M. J. Jr Colder environments did not select for a faster metabolism during experimental evolution of Drosophila melanogaster. Evolution 71, 145–152 (2017).

    Article  Google Scholar 

  19. Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1-101 (2011).

  20. Nakagawa, S. & Lagisz, M. Visualizing unbiased and biased unweighted meta-analyses. J. Evol. Biol. 29, 1914–1916 (2016).

    Article  CAS  Google Scholar 

  21. Orme, D. The caper Package: Comparative Analysis of Phylogenetics and Evolution in R. R package version 5 (2013).

  22. Michonneau, F., Brown, J. W. & Winter, D. J. rot1: an R package to interact with the Open Tree of Life data. Methods Ecol. Evol. 7, 1476–1481 (2016).

    Article  Google Scholar 

  23. Hinchliff, C. E. et al. Synthesis of phylogeny and taxonomy into a comprehensive tree of life. Proc. Natl Acad. Sci. USA 112, 12764–12769 (2015).

    Article  CAS  Google Scholar 

  24. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. & The, P. G. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6, e1000097 (2009).

    Article  Google Scholar 

  25. Pagel, M. Inferring the historical patterns of biological evolution. Nature 401, 877–884 (1999).

    Article  CAS  Google Scholar 

  26. Hadfield, J. D. & Nakagawa, S. General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters. J. Evol. Biol. 23, 494–508 (2010).

    Article  CAS  Google Scholar 

  27. Quinn, G. P. & Keough, M. J. Experimental Design and Data Analysis for Biologists (Cambridge Univ. Press, 2002).

Download references


We thank B. Comerford, M. Parascandalo and L. Morris for assistance. This work was supported by funding to the Centre for Geometric Biology, Monash University.

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Authors and Affiliations



D.J.M. conceived the study, collected and analysed the data and wrote the first draft. M.B. developed the mathematical theory. D.J.M. and A.K.P. collected the data. D.J.M. and C.R.W. analysed the data. All authors contributed to subsequent drafts.

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Correspondence to Dustin J. Marshall.

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Supplementary text 1–3, Tables 1–4, Figs. 1–3 and references.

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Marshall, D.J., Pettersen, A.K., Bode, M. et al. Developmental cost theory predicts thermal environment and vulnerability to global warming. Nat Ecol Evol 4, 406–411 (2020).

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