Metabolic scaling is the product of life-history optimization

Authors: Craig R White, Lesley A Alton, Candice L Bywater, Emily J Lombardi and Dustin J Marshall

Published in: Science


Organisms use energy to grow and reproduce, so the processes of energy metabolism and biological production should be tightly bound. On the basis of this tenet, we developed and tested a new theory that predicts the relationships among three fundamental aspects of life: metabolic rate, growth, and reproduction.

We show that the optimization of these processes yields the observed allometries of metazoan life, particularly metabolic scaling. We conclude that metabolism, growth, and reproduction are inextricably linked; that together they determine fitness; and, in contrast to longstanding dogma, that no single component drives another.

Our model predicts that anthropogenic change will cause animals to evolve decreased scaling exponents of metabolism, increased growth rates, and reduced lifetime reproductive outputs, with worrying consequences for the replenishment of future populations.

White CR, Alton LA, Bywater CL, Lombardi EJ, Marshall DJ (2022) Metabolic scaling is the product of life-history optimization. Science DOI

Travelling in time: an experimental evolution experiment challenges what we thought we knew about size and the cost of production

Time travel has been made possible by a long-term evolution experiment with the bacteria Escherichia coli. In 1988 a biologist at Michigan State University, Richard Lenski, set up 12 flasks of E. coli and his group has maintained and followed their evolution ever since. Periodically, subsamples are frozen enabling scientists to compare the bacteria at different points in time by bringing them back to life.

Over time, the evolving E. coli have grown bigger; after 60,000 generations, cells are roughly twice the size of their ancestors. But has this increase in size been accompanied by changes we expect to see in metabolism and population size and growth rates? Researchers at the Centre for Geometric Biology have collaborated with Richard Lenski to find out.

Metabolism dictates the rate at which organisms transform energy into maintenance and production. While larger species have higher metabolic rates, they are actually more efficient and so have lower metabolic rates relative to their size. So, while smaller species have higher population densities and can reach those densities faster, total population mass is greater in larger species (think mice and elephants).

But does the above hold true within a species? Often the size range within a species isn’t particularly large, making inferences about size difficult to test. The aptly named ‘Lenski Lines’ circumvent this problem. Richard’s lab sent frozen samples of the original E. coli – the ancestors, plus samples from 10,000 and 60,000 generations of evolution. Project leads at Monash University, Dustin Marshall and Mike McDonald, set about reviving the cells and measuring cell size, metabolism, population size and population growth.

The team found that as the cells grew bigger through evolutionary time, metabolic rates increased but were lower relative to their size, as predicted by theory. Also anticipated by theory, populations of larger cells had lower population densities but higher biomass’ than their smaller ancestors. The big surprise and in stark contrast to theory, was that populations of larger cells, despite their relatively lower metabolism grew faster than smaller cells.

The research team found that, as expected, larger cells had lower population densities (b) but greater biomass (c and d) but to their surprise larger cells also had a faster rate of population growth than the smaller cells (a).

We often assume that the energy required to produce a new individual is directly proportional to its mass but as this experiment has shown it is not necessarily the case. Why then, would a larger cell be cheaper to build and maintain

E. coli cells use up a lot of energy maintaining ion gradients across cell membranes. As larger cells have smaller surface areas relative to mass they should also have lower maintenance costs than smaller cells. The evolved cells also have slightly smaller genomes than the smaller ancestral cells so the costs of genome replication are lower for larger cells. What is more, the evolved cells have fine-tuned their genetic components in this highly predictable environment, reducing the costly expression of unneeded transcripts and proteins.

Remarkably, it seems evolution can decouple the costs of production from size; there is no downside to increasing growth rates for the larger evolved cells in terms of yield.

This research is published in Proceedings of the National Academy of Sciences of the United States of America.

Long-term experimental evolution decouples size and production costs in Escherichia coli

Authors: Dustin J Marshall, Martino Malerba, Thomas Lines, Aysha L Sezmis, Chowdhury M Hasan, Richard E Lenski, and Michael J McDonald

Published in: Proceedings of the National Academy of Sciences of the United States of America (PNAS)


Populations of larger organisms should be more efficient in their resource use, but grow more slowly, than populations of smaller organisms.

The relations between size, metabolism, and demography form the bedrock of metabolic theory, but most empirical tests have been correlative and indirect.

Experimental lineages of Escherichia coli that evolved to make larger cells provide a unique opportunity to test how size, metabolism, and demography covary. Despite the larger cells having a relatively slower metabolism, they grow faster than smaller cells. They achieve this growth rate advantage by reducing the relative costs of producing their larger cells.

That evolution can decouple the costs of production from size challenges a fundamental assumption about the connections between physiology and ecology.


Body size covaries with population dynamics across life’s domains. Metabolism may impose fundamental constraints on the coevolution of size and demography, but experimental tests of the causal links remain elusive.

We leverage a 60,000-generation experiment in which Escherichia coli populations evolved larger cells to examine intraspecific metabolic scaling and correlations with demographic parameters.

Over the course of their evolution, the cells have roughly doubled in size relative to their ancestors. These larger cells have metabolic rates that are absolutely higher, but relative to their size, they are lower.

Metabolic theory successfully predicted the relations between size, metabolism, and maximum population density, including support for Damuth’s law of energy equivalence, such that populations of larger cells achieved lower maximum densities but higher maximum biomasses than populations of smaller cells. The scaling of metabolism with cell size thus predicted the scaling of size with maximum population density. In stark contrast to standard theory, however, populations of larger cells grew faster than those of smaller cells, contradicting the fundamental and intuitive assumption that the costs of building new individuals should scale directly with their size.

The finding that the costs of production can be decoupled from size necessitates a reevaluation of the evolutionary drivers and ecological consequences of biological size more generally.

Marshall DJ, Malerba M, Lines T, Sezmis AL, Hasan CM, Lenski RE, McDonald MJ (2022) Long-term experimental evolution decouples size and production costs in Escherichia coli. Proceedings of the National Academy of Sciences of the United States of America PDF DOI

A comparative analysis testing Werner’s theory of complex life cycles

Authors: Emily L Richardson, Craig R White, and Dustin J Marshall

Published in: Functional Ecology


A popular theoretical model for explaining the evolution of complex life cycles (CLCs) was provided by Earl Werner. The theory predicts the size at which an individual should switch stages to maximise growth rate relative to mortality rate across the life history.

Werner’s theory assumes that body size does not change during the transition from one phase to another (e.g. from larva to adult) — a key assumption that has not been tested systematically but could alter the predictions of the model.

We quantified how growth rate and mass change across larval stages and metamorphosis for 105 species of fish, amphibians, insects, crustaceans and molluscs. Across all taxonomic groups, we found support for Werner’s assumption that growth rates are maintained or increase around transitions. We found that changes in growth and mass were greatest during metamorphosis, and change in growth correlated with development time. Importantly, most species either gained or lost mass when switching to a new stage — a direct contradiction of Werner’s assumption. When we explored the consequences of energy loss and gain in a numerical model, we found that individuals should switch stages at a larger and smaller size, respectively, relative to what Werner’s standard theory predicts.

Our results suggest that while there is support for Werner’s assumption regarding growth rates, mass changes profoundly alter the timing of transitions that are predicted to maximise fitness, and therefore the original model omits an important component that may contribute to the evolution of CLCs. Future studies should test for conditions that alter the costs of transitions, so that we can have a better understanding of how mass loss or gain affects fitness.

Richardson EL, White CR, Marshall DJ (2022) A comparative analysis testing Werner’s theory of complex life cycles. Functional Ecology PDF DOI

Metabolic phenotype mediates the outcome of competitive interactions in a response-surface field experiment

Authors: Lukas Schuster, Craig R White, and Dustin J Marshall

Published in: Ecology and Evolution


Competition and metabolism should be linked. Intraspecific variation in metabolic rates and, hence, resource demands covary with competitive ability. The effects of metabolism on conspecific interactions, however, have mostly been studied under laboratory conditions.

We used a trait-specific response-surface design to test for the effects of metabolism on pairwise interactions of the marine colonial invertebrate, Bugula neritina in the field.

Specifically, we compared the performance (survival, growth, and reproduction) of focal individuals, both in the presence and absence of a neighbor colony, both of which had their metabolic phenotype characterized.

Survival of focal colonies depended on the metabolic phenotype of the neighboring individual, and on the combination of both the focal and neighbor colony metabolic phenotypes that were present.

Surprisingly, we found pervasive effects of neighbor metabolic phenotypes on focal colony growth and reproduction, although the sign and strength of these effects showed strong microenvironmental variability.

Overall, we find that the metabolic phenotype changes the strength of competitive interactions, but these effects are highly contingent on local conditions. We suggest future studies explore how variation in metabolic rate affects organisms beyond the focal organism alone, particularly under field conditions.

Schuster L, White CR, Marshall DJ (2021) Metabolic phenotype mediates the outcome of competitive interactions in a response‐surface field experiment. Ecology and Evolution PDF DOI 

Predicting the response of disease vectors to global change: The importance of allometric scaling

Authors: Louise S Nørgaard, Mariana Álvarez-Noriega, Elizabeth McGraw, Craig R White, and Dustin J Marshall

Published in: Global Change Biology


The distribution of disease vectors such as mosquitoes is changing. Climate change, invasions and vector control strategies all alter the distribution and abundance of mosquitoes.

When disease vectors undergo a range shift, so do disease burdens. Predicting such shifts is a priority to adequately prepare for disease control. Accurate predictions of distributional changes depend on how factors such as temperature and competition affect mosquito life-history traits, particularly body size and reproduction.

Direct estimates of both body size and reproduction in mosquitoes are logistically challenging and time-consuming, so the field has long relied upon linear (isometric) conversions between wing length (a convenient proxy of size) and reproductive output. These linear transformations underlie most models projecting species’ distributions and competitive interactions between native and invasive disease vectors.

Using a series of meta-analyses, we show that the relationship between wing length and fecundity are nonlinear (hyperallometric) for most mosquito species. We show that whilst most models ignore reproductive hyperallometry (with respect to wing length), doing so introduces systematic biases into estimates of population growth. In particular, failing to account for reproductive hyperallometry overestimates the effects of temperature and underestimates the effects of competition. Assuming isometry also increases the potential to misestimate the efficacy of vector control strategies by underestimating the contribution of larger females in population replenishment.

Finally, failing to account for reproductive hyperallometry and variation in body size can lead to qualitative errors via the counter-intuitive effects of Jensen’s inequality. For example, if mean sizes decrease, but variance increases, then reproductive outputs may actually increase.

We suggest that future disease vector models incorporate hyperallometric relationships to more accurately predict changes in mosquito distribution in response to global change.

Nørgaard LS, Álvarez‐Noriega M, McGraw E, White CR, Marshall DJ (2021) Predicting the response of disease vectors to global change: The importance of allometric scaling. Global Change Biology PDF DOI 

Phytoplankton diversity affects biomass and energy production differently during community development

Authors: Giulia Ghedini, Dustin J Marshall, and Michel Loreau

Published in: Functional Ecology


Biodiversity determines the productivity and stability of ecosystems but some aspects of biodiversity–ecosystem functioning relationships remain poorly resolved. One key uncertainty is the inter-relationship between biodiversity, energy and biomass production as communities develop over time. Energy production drives biomass accumulation but the ratio of the two processes can change during community development. How biodiversity affects these temporal patterns remains unknown.

We empirically assessed how species diversity mediates the rates of increase and maximum values of biomass and net energy production in experimental phytoplankton communities over 10 days in the laboratory. We used five phytoplankton species to assemble three levels of diversity (monocultures, bicultures and communities) and we quantify their changes in biomass production and energy fluxes (energy produced by photosynthesis, consumed by metabolism, and net energy production as their difference) as the cultures move from a low density, low competition system to a high density, high competition system.

We find that species diversity affects both biomass and energy fluxes but in different ways. Diverse communities produce net energy and biomass at faster rates, reaching greater maximum biomass but with no difference in maximum net energy production. Bounds on net energy production seem stronger than those on biomass because competition limits energy fluxes as biomass accumulates over time.

In summary, diversity initially enhances productivity by diffusing competitive interactions but metabolic density dependence reduces these positive effects as biomass accumulates in older communities. By showing how biodiversity affects both biomass and energy fluxes during community development, our results demonstrate a mechanism that underlies positive biodiversity effects and offer a framework for comparing biodiversity effects across systems at different stages of development and disturbance regimes.

Ghedini G, Marshall DJ, Loreau M (2021) Phytoplankton diversity affects biomass and energy production differently during community development. Functional Ecology PDF DOI 

How does spawning frequency scale with body size in marine fishes?

Authors: Dustin J Marshall, Diego R Barneche, and Craig R White

Published in: Fish and Fisheries


How does fecundity scale with female size? Female size not only affects the number and size of offspring released in any one reproductive bout (i.e. batch fecundity) but also affects frequency of bouts that occur within a given spawning season (i.e. spawning frequency).

Previous studies have noted contrasting effects of female size on spawning frequency such that the effect of female size on reproductive output and total egg production of a population remains unclear. If smaller females spawn more frequently, this could effectively nullify hyperallometry—the disproportionate contribution of larger females to batch fecundity.

Here, we explore the relationship between female size and spawning frequency in marine fishes and test this relationship while controlling for phylogeny.

Within all of the species considered, spawning frequency scaled positively with body size. Comparing across species, the smallest species showed steeper scaling than the largest.

Considering only batch fecundity scaling probably underestimates the relationship between body size and absolute fecundity for many species; reproduction is likely to be more hyperallometric than is currently appreciated based on batch fecundity estimates. Second, an understanding of fecundity scaling depends on estimates of batch fecundity, spawning frequency and spawning duration—we have far more estimates of the first parameter than we do the others, and more studies are required.

Marshall DJ, Barneche DR, White CR (2021) How does spawning frequency scale with body size in marine fishes? Fish and Fisheries PDF DOI 

Does metabolic rate drive population size?

All organisms must eat to sustain themselves, but some more so than others. Metabolic rates should determine how much food an organism needs and how quickly it can convert that food into growth. We have long suspected the reason mice populations grow faster than elephant populations has something to do with their different metabolisms – for their size, mice have much higher metabolisms. While higher metabolisms might mean faster population growth, there is a supposed downside – populations with relatively higher metabolisms should exhaust resources at a much lower population biomass due to their higher resource demands. Thus, mice populations can sustain more individuals (have larger population sizes) than elephants, but on a per gram basis, mice have far lower population biomasses. That’s the theory at least – in reality no-one really knows.

Remarkably, despite years of interest in this topic, there have been no experimental tests of how metabolism affects populations – instead we relied on mouse-and-elephant-type comparisons – looking for patterns across organisms of very different sizes. While these comparisons are useful, obviously, mice and elephants differ in far more than their metabolisms alone, and these other factors could easily be driving any differences we observe. What’s needed is an experiment that manipulates the metabolism of whole populations, without changing anything else – a difficult task.

Lukas Schuster and Hayley Cameron along with Craig White and Dustin Marshall, set out to do just that. Using more than 1000 individuals of a common fouling marine creature – which feeds by filtering food particles from the water column – the team created 172 experimental populations that differed in their metabolic rates and population densities. These populations were then hung from plastic panels at a local marina where they were left to grow. The team then followed these populations for their entire lifetimes; measuring survival, growth and reproduction.

As anticipated, populations with higher metabolisms grew more rapidly – but what was unexpected was that populations with moderately high metabolic rates actually supported more individuals than those with lower metabolic rates. The reasons are unclear, but what seems to be happening is that higher metabolisms result in more feeding activity, which allows these populations to access relatively more resources, sustaining a larger number of individuals than expected. Metabolic rates can get too high, however, such that populations with the highest metabolic rates showed the expected decline in population size – probably because they exhausted local resources at a greater rate than these resources could be replenished, such that further increases in metabolism had no effect on resource intake.

The results have some surprisingly far-reaching implications. Many of the assumptions about how climate change will affect the resource consumption of future populations are based on classic, but untested theory. Likewise, fisheries are sometimes managed based on expectations about metabolic rate and resource demands. This research shows that the fundamental theory on how metabolism affects population demography needs revision. Higher metabolisms don’t invariably lead to lower population densities and a key rule of life seems to partially broken – higher metabolism populations can have their cake (grow fast) and eat it too (achieve high densities) – up to point at least.

This research was published in Proceedings of the National Academy of Sciences of the United States of America.

In biology we call the density at which a population stops growing the ‘carrying capacity’. Theoretical models predict that there will be a steady decline in carrying capacity as metabolic rates increases (blue line). But the research team found a more complicated relationship (black line). Initially carrying capacity increased with increasing metabolic rate before starting to decline. At higher metabolic rates the rate of decline in carrying capacity was the same for the team’s experimental data as for theoretical predictions.

Metabolism drives demography in an experimental field test

Authors: Lukas Schuster, Hayley Cameron, Craig R White, and Dustin J Marshall

Published in: Proceedings of the National Academy of Sciences of the United States of America


Biology has long-standing rules about how metabolism and demography should covary. These rules connect physiology to ecology but remarkably, these rules have only ever been tested indirectly.

Using a model marine invertebrate, we created experimental field populations that varied in metabolic rate but not body size.

We show that metabolism qualitatively affects population growth and carrying capacity in ways predicted by theory but that scaling relationships for these parameters, as well as estimates of energy use at carrying capacity, depart from classic predictions.

That metabolism affects demography in ways that depart from canonical theory has important implications for predicting how populations may respond to global change and size-selective harvesting.


Metabolism should drive demography by determining the rates of both biological work and resource demand. Long-standing “rules” for how metabolism should covary with demography permeate biology, from predicting the impacts of climate change to managing fisheries.
Evidence for these rules is almost exclusively indirect and in the form of among-species comparisons, while direct evidence is exceptionally rare.

In a manipulative field experiment on a sessile marine invertebrate, we created experimental populations that varied in population size (density) and metabolic rate, but not body size. We then tested key theoretical predictions regarding relationships between metabolism and demography by parameterizing population models with lifetime performance data from our field experiment.

We found that populations with higher metabolisms had greater intrinsic rates of increase and lower carrying capacities, in qualitative accordance with classic theory. We also found important departures from theory—in particular, carrying capacity declined less steeply than predicted, such that energy use at equilibrium increased with metabolic rate, violating the long-standing axiom of energy equivalence.

Theory holds that energy equivalence emerges because resource supply is assumed to be independent of metabolic rate. We find this assumption to be violated under real-world conditions, with potentially far-reaching consequences for the management of biological systems.

Schuster L, Cameron H, White CR, Marshall DJ (2021) Metabolism drives demography in an experimental field test. Proceedings of the National Academy of Sciences of the United States of America PDF DOI