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arxiv: 2606.28418 · v1 · pith:CLDWGPZ6new · submitted 2026-06-25 · 🧬 q-bio.QM · physics.bio-ph

Metabolic scaling, von Bertalanffy growth and an exponent equation

Pith reviewed 2026-06-30 01:16 UTC · model grok-4.3

classification 🧬 q-bio.QM physics.bio-ph
keywords metabolic scalingvon Bertalanffy growthenergy allocationscaling exponentsdevelopmental growthgrowth curvesmetabolic investment
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The pith

Metabolic energy allocation among maintenance and growth produces von Bertalanffy curves while constraining scaling exponents.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper treats developmental growth as the division of metabolic energy between baseline maintenance and growth processes. From an explicit allocation rule it derives direct mathematical relations that connect the mass-growth exponent, the length-based exponent, the metabolic scaling exponent, and the geometric mass-length exponent. These relations fix the metabolic investment exponent, which in turn sets the shape of the growth-allocation function over time. Requiring the allocation fraction to remain between zero and one then supplies upper limits on developmental velocity and on the characteristic masses that mark transitions between growth phases. The result is an energy-based account of phenomenological growth curves in which metabolic scaling, geometric scaling, and growth dynamics appear as interdependent parts of one allocation scheme.

Core claim

By specifying how metabolic energy is partitioned among maintenance, growth, and other processes, the authors obtain an exponent equation that relates the mass-growth exponent, length-based exponent, metabolic scaling exponent and geometric exponent. The metabolic investment exponent governs the qualitative behaviour of the growth-allocation function. Feasibility of the allocation fraction then yields constraints on developmental velocity and mass scales, furnishing a physical interpretation of von Bertalanffy growth within a unified scaling framework.

What carries the argument

The metabolic energy allocation framework that partitions energy into baseline maintenance, growth, and other processes, together with the resulting exponent relations among scaling parameters.

If this is right

  • The growth-allocation function is controlled by a single metabolic investment exponent derived from the four scaling exponents.
  • Biologically feasible allocations impose upper bounds on developmental velocity.
  • Characteristic mass scales at which growth phases occur are fixed by the exponent set.
  • Metabolic scaling, geometric scaling, and growth dynamics are interdependent through one allocation rule.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Growth trajectories could be predicted from measured metabolic rates and body-size scaling alone.
  • The same allocation logic may extend to other life-history traits such as timing of reproduction or senescence.
  • Direct experimental measurement of allocation fractions would turn the feasibility constraints into immediate empirical tests.

Load-bearing premise

The framework that specifies how metabolic energy is allocated among baseline maintenance, growth, and other processes is a valid and complete description of developmental growth.

What would settle it

A measured growth trajectory in which the inferred allocation fraction to growth falls outside [0,1] or violates the derived velocity and mass-scale constraints for the observed scaling exponents.

Figures

Figures reproduced from arXiv: 2606.28418 by Hana Krakovsk\'a, Klaus Stiefel, Rudolf Hanel.

Figure 1
Figure 1. Figure 1: FIG. 1. Growth curve (black) and scaled investment ratios [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
read the original abstract

In this work, we interpret developmental growth as a metabolic energy allocation problem and link the von Bertalanffy growth model to metabolic energy investments into the growth channel. Using a framework that specifies how metabolic energy is allocated among baseline maintenance, growth, and other processes, we analyse the resulting growth allocation patterns and derive direct relationships between key scaling exponents: the mass-growth exponent, the length-based exponent, the metabolic scaling exponent, and the geometric exponent, which describes the mass-length relationship. These exponents determine the metabolic investment exponent, which controls the qualitative behaviour of the growth-allocation function. Requiring the inferred allocation fraction to remain biologically feasible, we derive constraints on developmental velocity and characteristic mass scales. This provides a physical, energy-based interpretation of phenomenological growth curves and clarifies how metabolic scaling, geometric scaling, and growth dynamics are interrelated within a single allocation framework.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. The manuscript interprets developmental growth as a metabolic energy allocation problem and connects the von Bertalanffy growth model to investments in the growth channel. Within an explicit framework that partitions metabolic energy among baseline maintenance, growth, and other processes, the authors derive algebraic relationships among four scaling exponents—the mass-growth exponent, the length-based exponent, the metabolic scaling exponent, and the geometric (mass-length) exponent—that together determine a metabolic investment exponent governing the qualitative form of the growth-allocation function. Requiring the inferred allocation fraction to remain biologically feasible then yields constraints on developmental velocity and characteristic mass scales, supplying an energy-based reading of phenomenological growth curves.

Significance. If the derivations are correct, the work supplies a direct, algebraic bridge between metabolic scaling, geometric scaling, and growth dynamics inside a single allocation model, together with explicit feasibility constraints on velocity and mass. This is a substantive attempt to move from phenomenological curves to mechanistic energy accounting and is noteworthy for producing parameter-free exponent relations once the allocation fractions are granted. The approach could be useful for interpreting comparative growth data across taxa provided the framework receives independent empirical anchoring.

minor comments (3)
  1. [Abstract] The abstract and introduction would benefit from an explicit statement of the allocation fractions (e.g., the symbols used for maintenance, growth, and residual channels) before the exponent relations are introduced.
  2. [§3] Notation for the four scaling exponents and the derived metabolic investment exponent should be introduced once in a dedicated table or equation block and then used consistently; occasional redefinition of symbols across sections reduces readability.
  3. [§4.2] The feasibility constraints on velocity and mass scales are presented as inequalities; adding a short numerical example (e.g., for a reference organism) would help readers assess the practical range of the constraints.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their careful reading and positive assessment of the manuscript. The referee summary accurately captures the core contribution: deriving algebraic relations among the mass-growth, length-based, metabolic scaling, and geometric exponents within an energy-allocation model for von Bertalanffy growth, together with feasibility constraints on developmental parameters. The recommendation for minor revision is noted; however, the report contains no enumerated major comments.

Circularity Check

0 steps flagged

No significant circularity identified

full rationale

The paper derives algebraic relationships among four scaling exponents (mass-growth, length-based, metabolic, geometric) and a metabolic investment exponent inside an explicit energy-allocation model, then obtains feasibility constraints on velocity and mass scales. No equations or self-citations are supplied that reduce any claimed prediction to a fitted parameter or to a prior result by the same authors; the derivation is presented as direct consequences of the allocation fractions once those fractions are granted. The framework is introduced as an assumption rather than derived from the target exponents, so the central claim retains independent content from its inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review; no specific free parameters, axioms, or invented entities can be extracted or verified from the provided text.

pith-pipeline@v0.9.1-grok · 5679 in / 1081 out tokens · 39569 ms · 2026-06-30T01:16:14.055921+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

33 extracted references

  1. [1]

    M. R. Kearney, What is the status of metabolic theory one century after P¨ utter invented the von Bertalanffy growth curve?, Biological Reviews 96, 557 (2021)

  2. [2]

    von Bertalanffy, Quantitative laws in metabolism and growth, The Quarterly Review of Biology 32, 217 (1957)

    L. von Bertalanffy, Quantitative laws in metabolism and growth, The Quarterly Review of Biology 32, 217 (1957)

  3. [3]

    P¨ utter, Studien ¨ uber physiologische ¨Ahnlichkeit VI

    A. P¨ utter, Studien ¨ uber physiologische ¨Ahnlichkeit VI. Wachstums¨ ahnlichkeiten, Pfl¨ uger’s Archiv f¨ ur die Gesamte Physiologie des Menschen und der Tiere 180, 298 (1920)

  4. [4]

    Froese and D

    R. Froese and D. Pauly, FishBase, World Wide Web elec- tronic publication, www.fishbase.org ( 04/2025 ) (2025)

  5. [5]

    Stiefel and A

    K. Stiefel and A. A. Bucol, What determines the mini- mum body size for vertebrates? (2022)

  6. [6]

    Halbersleben and F

    D. Halbersleben and F. Mussehl, Relation of egg weight to chick weight at hatching., Poultry Science 1, 143 (1922)

  7. [7]

    C. M. Dmitriew, The evolution of growth trajectories: what limits growth rate?, Biological Reviews 86, 97 (2011)

  8. [8]

    Sarrus and J

    F. Sarrus and J. Rameaux, Rapport sur une m´ emoire adress´ e ´ a l’acad´ emic royale de M´ edecine, Bulletin de l’Acad´ emie Royale de M´ edecine de Paris3, 1094 (1838)

  9. [9]

    Rubner, ¨Uber den einfluss der k¨ orpergr¨ osse auf stoff- und kraftwechsel, Zeitschrift f¨ ur Biologie19, 536 (1883)

    M. Rubner, ¨Uber den einfluss der k¨ orpergr¨ osse auf stoff- und kraftwechsel, Zeitschrift f¨ ur Biologie19, 536 (1883)

  10. [10]

    Kleiber, Body size and metabolism, Hilgardia 6, 315 (1932)

    M. Kleiber, Body size and metabolism, Hilgardia 6, 315 (1932)

  11. [11]

    Brody and H

    S. Brody and H. A. Lardy, Bioenergetics and growth, The Journal of Physical Chemistry 50, 168 (1946)

  12. [12]

    D. S. Glazier, Beyond the ‘3/4-power law’: variation in the intra-and interspecific scaling of metabolic rate in animals, Biological Reviews 80, 611 (2005)

  13. [13]

    V. M. Savage, J. F. Gillooly, W. H. Woodruff, G. B. West, A. P. Allen, B. J. Enquist, and J. H. Brown, The predominance of quarter-power scaling in biology, Func- tional Ecology 18, 257 (2004)

  14. [14]

    R. H. Peters, The Ecological Implications of Body Size , Cambridge Studies in Ecology (Cambridge University Press, 1983)

  15. [15]

    P. S. Dodds, D. H. Rothman, and J. S. Weitz, Re- examination of the “3/4-law” of metabolism, Journal of Theoretical Biology 209, 9 (2001)

  16. [16]

    Heusner, Energy metabolism and body size i

    A. Heusner, Energy metabolism and body size i. is the 0.75 mass exponent of kleiber’s equation a statistical ar- tifact?, Respiration Physiology 48, 1 (1982)

  17. [17]

    C. R. White and R. S. Seymour, Mammalian basal metabolic rate is proportional to body mass 2/3, Pro- ceedings of the National Academy of Sciences 100, 4046 (2003)

  18. [18]

    H. A. Feldman and T. A. McMahon, The 3/4 mass ex- ponent for energy metabolism is not a statistical artifact, Respiration Physiology 52, 149 (1983)

  19. [19]

    D. S. Glazier, Variable metabolic scaling breaks the law: from ‘newtonian’ to ‘darwinian’ approaches, Proceedings of the Royal Society B: Biological Sciences289, 20221605 (2022)

  20. [20]

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

  21. [21]

    G. B. West, J. H. Brown, and B. J. Enquist, A general model for ontogenetic growth, Nature 413, 628 (2001)

  22. [22]

    C. Hou, W. Zuo, M. E. Moses, W. H. Woodruff, J. H. Brown, and G. B. West, Energy uptake and allocation during ontogeny, Science 322, 736 (2008)

  23. [23]

    A. M. Makarieva, V. G. Gorshkov, and B.-L. Li, Onto- genetic growth: models and theory, Ecological Modelling 176, 15 (2004)

  24. [24]

    Sibly and J

    R. Sibly and J. Brown, Toward a physiological explana- tion of juvenile growth curves, Journal of Zoology 311, 286 (2020)

  25. [25]

    L. Lee, D. Atkinson, A. G. Hirst, and S. J. Cornell, A new framework for growth curve fitting based on the von Bertalanffy growth function, Scientific Reports 10, 7953 (2020)

  26. [26]

    K. M. C. Tjørve and E. Tjørve, Shapes and functions of bird-growth models: how to characterise chick postnatal growth, Zoology 113, 326 (2010)

  27. [27]

    Renner-Martin, N

    K. Renner-Martin, N. Brunner, M. K¨ uhleitner, W. G. Nowak, and K. Scheicher, On the exponent in the von Bertalanffy growth model, PeerJ 6, e4205 (2018)

  28. [28]

    S. A. L. M. Kooijman, Dynamic energy budget theory for metabolic organisation (Cambridge University Press, 2010)

  29. [29]

    Nielsen, R

    J. Nielsen, R. B. Hedeholm, J. Heinemeier, P. G. Bush- nell, J. S. Christiansen, J. Olsen, C. B. Ramsey, R. W. Brill, M. Simon, K. F. Steffensen, and J. F. Steffensen, Eye lens radiocarbon reveals centuries of longevity in the Greenland shark (Somniosus microcephalus), Science 353, 702 (2016)

  30. [30]

    R. A. Morais and D. R. Bellwood, Global drivers of reef fish growth, Fish and Fisheries 19, 874 (2018)

  31. [31]

    Depczynski and D

    M. Depczynski and D. R. Bellwood, Extremes, plasticity, and invariance in vertebrate life history traits: Insights from coral reef fishes, Ecology 87, 3119 (2006)

  32. [32]

    Froese, J

    R. Froese, J. T. Thorson, and R. B. Reyes Jr, A bayesian approach for estimating length-weight relationships in fishes, Journal of Applied Ichthyology 30, 78 (2014)

  33. [33]

    C. L. Jerde, K. Kraskura, E. J. Eliason, S. R. Csik, A. C. Stier, and M. L. Taper, Strong evidence for an intraspe- cific metabolic scaling coefficient near 0.89 in fish, Fron- tiers in Physiology 10, 1166 (2019)