Deriving population scaling rules from individual-level metabolism and life history traits

Rémy Denechere*, P. Daniël van Denderen, Ken H. Andersen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Individual metabolism generally scales with body mass with an exponent around 3/4. From dimensional arguments it follows that maximum population growth rate (rmax) scales with a −1/4 exponent. However, the dimensional argument implicitly assumes that offspring size is proportional to adult size. Here we calculate rmax from metabolic scaling at the level of individuals within size-structured populations while explicitly accounting for offspring size. We identify four general patterns of how rmax scales with adult mass based on four empirical life-history patterns employed by groups of species. These life-history patterns are determined by how traits of somatic growth rate and/or offspring mass relate to adult mass. One life-history pattern – constant adult:offspring mass ratio and somatic growth rate independent of adult mass – leads to the classic −1/4 scaling of rmax. The other three life-history patterns lead either to non-metabolic population growth scaling with adult mass or do not follow a power-law relationship at all. Using life-history data of five marine taxa and terrestrial mammals, we identify species groups that belong to one of each case. We predict that elasmobranchs, copepods, and mammals follow standard −1/4 power-law scaling, whereas teleost fish and bivalves do not have a pure power-law scaling. Our work highlights how taxa may deviate from the classic −1/4 metabolic scaling pattern of maximum population growth. The approach is generic and can be applied to any taxa.
Original languageEnglish
JournalAmerican Naturalist
Volume199
Issue number4
ISSN0003-0147
DOIs
Publication statusPublished - 2022

Keywords

  • Individual mass scaling
  • Metabolic theory of ecology
  • Population growth rate
  • Offspring size
  • Somatic growth rate
  • Marine taxa
  • Life history strategy

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