Mathematical model of animal growth shows life is defined by biology, not physics
Juvenile lobster cockroaches Nauphoeta cinerea. Lobster cockroaches weigh around 5 mg when they hatch, and increase in mass by two orders of magnitude to 0.5 g as they grow to adult size. Credit: Monash University

Conventional wisdom says that physical constraints explain biological patterns.

The researchers presented a mathematical model of animal growth in a study published today in Science.

Despite the fact that living organisms can't break the laws of physics, evolution has shown itself to be very clever at finding loopholes.

There is a problem with the relationship between energy metabolism and size.

Professor White said that finding that an animal's metabolism can be explained without using physical constraints means that we've been looking in the wrong place.

He believes that physical constraints don't drive as much of the biology that we observe as previously thought and that evolution has a wider range of options.

When compared gram-for- gram, large animals burn less energy and require less food than small ones, as a result of an increase in size.

Small mammals such as shrews need to eat as much as three times their body weight in food each day, whereas the largest baleen whales only eat 20% of their body weight.

Professor White said that their study argued against the conventional wisdom that allometric scaling occurs because of physical constraints.

He said that they created a mathematical model of animal growth that describes how animals shift their energy allocation from growth to reproduction as they increase in age and size.

Our model doesn't use physical or geometric constraints to explain the pattern. Classic theories argue that animals have the best metabolisms because they must.

The study showed that allometric scaling doesn't have to be a result of physical limits. Natural selection prefers allometric scaling.

More information: Craig R. White et al, Metabolic scaling is the product of life-history optimization, Science (2022). DOI: 10.1126/science.abm7649 Journal information: Science