About

Log in?

DTU users get better search results including licensed content and discounts on order fees.

Anyone can log in and get personalized features such as favorites, tags and feeds.

Log in as DTU user Log in as non-DTU user No thanks

DTU Findit

Journal article

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

From

Centre for Ocean Life, National Institute of Aquatic Resources, Technical University of Denmark1

National Institute of Aquatic Resources, Technical University of Denmark2

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.

Language: English
Year: 2022
ISSN: 15375323 and 00030147
Types: Journal article
DOI: 10.5281/zenodo.5531628
ORCIDs: Denechere, Rémy , van Denderen, P. Daniël and Andersen, Ken H.

DTU users get better search results including licensed content and discounts on order fees.

Log in as DTU user

Access

Analysis