An non-loglinear enzyme-driven law of photosynthetic scaling in two representative crop seedlings under different water conditions

  • 1.

    Jenkins, D. G. & Pierce, S. General allometric scaling of net primary production agrees with plant adaptive strategy theory and has tipping points. J. Ecol. 105, 1094–1104 (2017).

    Article  Google Scholar 

  • 2.

    Kerkhoff, A. J. & Enquist, B. J. Ecosystem allometry: the scaling of nutrient stocks and primary productivity across plant communities. Ecol. Lett. 9, 419–427 (2006).

    Article  Google Scholar 

  • 3.

    Coomes, D. A., Lines, E. R. & Allen, R. B. Moving on from metabolic scaling theory: hierarchical models of tree growth and asymmetric competition for light. J. Ecol. 99, 748–756 (2011).

    Article  Google Scholar 

  • 4.

    Michaletz, S. T., Cheng, D., Kerkhoff, A. J. & Enquist, B. J. Convergence of terrestrial plant production across global climate gradients. Nature 512, 39–43 (2014).

    ADS  CAS  Article  Google Scholar 

  • 5.

    Hatton, I. A. et al. The predator-prey power law: biomass scaling across terrestrial and aquatic biomes. Science 349, 1070 (2015).

    CAS  Article  Google Scholar 

  • 6.

    Peng, Y., Niklas, K. J., Reich, P. B. & Sun, S. Ontogenetic shift in the scaling of dark respiration with whole-plant mass in seven shrub species. Funct. Ecol. 24, 502–512 (2010).

    Article  Google Scholar 

  • 7.

    Reich, P. B., Tjoelker, M. G., Machado, J. & Oleksyn, J. Universal scaling of respiratory metabolism, size and nitrogen in plants. Nature 439, 457–461 (2006).

    ADS  CAS  Article  Google Scholar 

  • 8.

    Cheng, D. L., Li, T., Zhong, Q. L. & Wang, G. X. Scaling relationship between tree respiration rates and biomass. Bio Lett. 6, 715–717 (2010).

    Article  Google Scholar 

  • 9.

    Xu, K. et al. Indirect effects of water availability in driving and predicting productivity in the Gobi desert. Sci. Total Environ. 133952 (2019).

  • 10.

    Lopez-Urrutia, A., San Martin, E., Harris, R. P. & Irigoien, X. Scaling the metabolic balance of the oceans. Proc. Natl. Acad. Sci. USA 103, 8739–8744 (2006).

    ADS  CAS  Article  Google Scholar 

  • 11.

    Chen, X. & Li, B. Testing the allometric scaling relationships with seedlings of two tree species. Acta Oecol. 24, 125–129 (2003).

    ADS  Article  Google Scholar 

  • 12.

    Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004).

    Article  Google Scholar 

  • 13.

    Norin, T. & Gamperl, A. K. Metabolic scaling of individuals vs. populations: evidence for variation in scaling exponents at different hierarchical levels. Funct. Ecol. 32, 379–388 (2018).

    Article  Google Scholar 

  • 14.

    Li, H. T., Han, X. G. & Wu, J. G. Lack of evidence for 3/4 scaling of metabolism in terrestrial plants. J. Integr. Plant Biol. 47, 1173–1183 (2005).

    Article  Google Scholar 

  • 15.

    Hoppeler, H. Scaling functions to body size: theories and facts. J. Exp. Biol. 208, 1573–1574 (2005).

    Article  Google Scholar 

  • 16.

    West, G. B., Brown, J. H. & Enquist, B. J. A general model for the origin of allometric scaling laws in biology. Science 276, 122–126 (1997).

    CAS  Article  Google Scholar 

  • 17.

    Hui, D. & Jackson, R. B. Uncertainty in allometric exponent estimation: a case study in scaling metabolic rate with body mass. J. Theor. Biol. 249, 168–177 (2007).

    MathSciNet  Article  Google Scholar 

  • 18.

    Patterson, M. R. A mass-transfer explanation of metabolic scaling relations in some aquatic invertebrates and algae. Science 255, 1421–1423 (1992).

    ADS  CAS  Article  Google Scholar 

  • 19.

    Dodds, P. S., Rothman, D. H. & Weitz, J. S. Re-examination of the ’ “3/4-law” of metabolism. J. Theor. Biol. 209, 9–27 (2001).

    CAS  Article  Google Scholar 

  • 20.

    Kozlowski, J. & Konarzewski, M. West, Brown and Enquist’s model of allometric scaling again: the same questions remain. Funct. Ecol. 19, 739–743 (2005).

    Article  Google Scholar 

  • 21.

    Packard, G. C. & Birchard, G. F. Traditional allometric analysis fails to provide a valid predictive model for mammalian metabolic rates. J. Exp. Biol. 211, 3581–3587 (2008).

    Article  Google Scholar 

  • 22.

    Glazier, D. S. Beyond the “3/4 power-law”: Variation in the intra- and interspecific scaling of metabolic rate in animals. Biol. Rev. 80, 611–662 (2005).

    Article  Google Scholar 

  • 23.

    Strauss, R. E. & Huxley, J. S. The study of allometry since Huxley. In: Problems of Relative Growth (Johns Hopkins University Press, Baltimore, 1993).

  • 24.

    Knell, R. J. On the analysis of non-linear allometries. Ecol. Entomol. 34, 1–11 (2009).

    Article  Google Scholar 

  • 25.

    Stumpf, M. P. H. & Porter, M. A. Critical truths about power laws. Science 335, 665–666 (2012).

    ADS  MathSciNet  CAS  Article  Google Scholar 

  • 26.

    Kolokotrones, T., Savage, V., Deeds, E. J. & Fontana, W. Curvature in metabolic scaling. Nature 464, 753–756 (2010).

    ADS  CAS  Article  Google Scholar 

  • 27.

    Packard, G. C. Why allometric variation in mammalian metabolism is curvilinear on the logarithmic scale. J. Exp. Zoo A Ecol. Integr. Physiol. 327, 537–541 (2017).

    Google Scholar 

  • 28.

    Hou, C. et al. Energy uptake and allocation during ontogeny. Science 322, 736–739 (2008).

    ADS  CAS  Article  Google Scholar 

  • 29.

    Ledder, G. The basic dynamic energy budget model and some implications. Lett. Biomath. 1, 221–233 (2014).

    Article  Google Scholar 

  • 30.

    Glazier, D. S. A unifying explanation for diverse metabolic scaling in animals and plants. Biol. Rev. 85, 111–138 (2010).

    Article  Google Scholar 

  • 31.

    Ballesteros, F. J. et al. On the thermodynamic origin of metabolic scaling. Sci. Rep. 8, 1448 (2018).

    ADS  Article  Google Scholar 

  • 32.

    Li, L. & Wang, G. Enzymatic origin and various curvatures of metabolic scaling in microbes. Sci. Rep. 9 (2019).

  • 33.

    Imaizumi, N., Usuda, H., Nakamoto, H. & Ishihara, K. Changes in the rate of photosynthesis during grain filling and the enzymatic activities associated with the photosynthetic carbon metabolism in rice panicles. Plant Cell Physiol. 31, 835–843 (1990).

    CAS  Google Scholar 

  • 34.

    Langdale, J. A. & Nelson, T. Spatial regulation of photosynthetic development in C4 plants. Trends Genet. 7, 191–196 (1991).

    CAS  Article  Google Scholar 

  • 35.

    Deng, J. et al. Insights into plant size-density relationships from models and agricultural crops. Proc. Natl. Acad. Sci. 109, 8600–8605 (2012).

    ADS  CAS  Article  Google Scholar 

  • 36.

    Deng, J. et al. Plant mass-density relationship along a moisture gradient in north-west China. J. Ecol. 94, 953–958 (2006).

    Article  Google Scholar 

  • 37.

    Webb, J. L. Enzyme and Metabolic Inhibitors (Academic Press, New York, 1966).

    Google Scholar 

  • 38.

    Killen, S. S., Atkinson, D. & Glazier, D. S. The intraspecific scaling of metabolic rate with body mass in fishes depends on lifestyle and temperature. Ecol. Lett. 13, 184–193 (2010).

    Article  Google Scholar 

  • 39.

    Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723 (1974).

    ADS  MathSciNet  Article  Google Scholar 

  • 40.

    Mori, S. et al. Mixed-power scaling of whole-plant respiration from seedlings to giant trees. Proc. Natl. Acad. Sci. 107, 1447–1451 (2010).

    ADS  CAS  Article  Google Scholar 

  • 41.

    Scott, M., Gunderson, C. W., Mateescu, E. M., Zhang, Z. & Hwa, T. Interdependence of cell growth and gene expression: origins and consequences. Science 330, 1099–1102 (2010).

    ADS  CAS  Article  Google Scholar 

  • 42.

    Li, L. R. W. W. the regulation of ribulose-1, 5-biosphosphate carboxylase activation in alealfa leaves. Acta Phytophysiol. Sin. 33–39 (1986).

  • 43.

    Yonghua D., J. S. G. L. Effect of ABA and 6-BA on activity of key enzymes in carbon assimilation in maize seedlings under water stress. Plant Nutr. Fert. Sci. 182–188 (1997).

  • 44.

    Yamaoka, K., Nakagawa, T. & Uno, T. Application of Akaike’s information criterion (AIC) in the evaluation of linear pharmacokinetic equations. J. Pharmacokinet. Biopharm. 6, 165–175 (1978).

    CAS  Article  Google Scholar 

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