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

Citation

Denéchère, Rémy; van Denderen, P. Daniël; Andersen, Ken Haste (2022), Deriving population scaling rules from individual-level metabolism and life history traits - Code and Data, Dryad, Dataset, https://doi.org/10.5061/dryad.kkwh70s5v

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.

Usage Notes

Description of the scripts and data
(Data are in both ".mat" and ".csv")

  1. Base_run function: contains all the scripts for the figures in Denéchère et al 2021.
  2. Parameters function: Data are loaded and processed from the parameter function that contains information about each data file: value, units, and definition of all the parameters. 
  3. Pop_growth_rate:  Contains the Rmax equation and associated parameters for each taxon.
  4. Grid function: used to create a log scale
  5. Ciplot function is used to create shadow areas. Created by: Raymond Reynolds 24/11/06; updated by Pham Thai Binh 12/06/2017.