Optimisation and constraint: explaining metabolic patterns in biology

Author:

White Craig R.1ORCID,Marshall Dustin J.1

Affiliation:

1. School of Biological Sciences and Centre for Geometric Biology, Monash University , Clayton 3800, VIC 3800 , Australia

Abstract

ABSTRACT Constraint-based explanations have dominated theories of size-related patterns in nature for centuries. Explanations for metabolic scaling – the way in which metabolism changes with body mass – have been based on the geometry of circulatory networks through which resources are distributed, the need to dissipate heat produced as a by-product of metabolic processes, and surface-area-to-volume constraints on the flux of nutrients or waste. As an alternative to these constraint-based approaches, we recently developed a new theory that predicts that metabolic allometry arises as a consequence of the optimisation of growth and reproduction to maximise fitness within a finite life. Our theory is free of physical geometric constraints that limit the possibilities available to evolution, and we therefore argue that metabolic allometry can be explained without the need to invoke any of the assumed constraints traditionally imposed by metabolic theories. Our findings also suggest that metabolism, growth and reproduction have co-evolved to maximise fitness (i.e. lifetime reproduction) and that the observed patterns in these fundamental characteristics of life can similarly be explained by optimisation rather than constraint. In this Centenary Commentary, we present an overview of our approach and a critique of its limitations. We propose a suite of empirical tests that we hope will move the field forward, discuss the dangers of model overparameterisation and highlight the need to remain open to non-adaptive hypotheses for the origin of biological patterns.

Funder

Australian Research Council

Publisher

The Company of Biologists

Subject

Insect Science,Molecular Biology,Animal Science and Zoology,Aquatic Science,Physiology,Ecology, Evolution, Behavior and Systematics

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