When is a change for the better?

Metamorphosis — the process by which animals undergo substantial changes to become an adult — can involve a complete redesign of the body plan. While not all transitions are as dramatic as the metamorphosis from larvae to adult, animals that undergo transitions as they move toward the adult stage are described as having complex life cycles. But why did animals evolve such complex life cycles?

In 1986 a scientist named Earl Werner proposed an explanation that has been widely cited since. Werner said that as an individual grows, energy demands increase faster than energy uptake. But, switching body plans (which usually means better access to food sources) enables individuals to continue growing and to reach the reproductive stage more efficiently and in better health. Werner’s model predicts the size at which an individual will transition as the size that minimises the chance of dying compared to its growth rate. Werner assumed the mass of the individual won’t change as a result of transition to the new phase of the life cycle.

Emily Richardson and her supervisors Dustin Marshall and Craig White wondered if this was true. If not, and there was a cost/benefit of transition, then the optimal size to change body plan might differ from Werner’s predictions.

Emily set about reviewing the literature to find out if there were any changes in mass that related to transitioning from one life stage to the next. Emily found data for 100 species and 343 life stages where she was able to record changes in growth rate and mass.

It turned out that across all taxa, as Werner predicted, growth rates were maintained or increased after switching to a new phase. But Werner hadn’t accounted for the change in mass that Emily and her supervisors observed in most taxa. On average amphibians lost 28%, insects 32% and crustaceans 8% of their mass during metamorphosis. During changes from one larval stage to another, fish and crustaceans actually gained mass and fish gained even more mass during metamorphosis. These increases in mass are likely to reflect more subtle life-history transitions where feeding is possible and transitioning is not as energetically costly.

These plots show Werner’s hypothetical predictions for the mass at which an individual should switch body plans when (A) growth rate is included and (B) when mortality is also included – note the optimal size at switching is larger when mortality is included. The dashed green curve in (C) represents one possible outcome if Werner’s model incorporates change in mass during transition to a new phase—in this example, the new curve shifts to the right and size at switching predicted by the new model is larger than predicted by Werner’s original model.

Either way, the team found that when changes in mass during transition are accounted for, the optimal size for transition will deviate from Werner’s predictions. For species that gain mass during a transition to a new phase, individuals should switch at a smaller size, while for species that lose mass, Emily and her supervisors predict they will transition at a larger size compared to Werner’s current theory.

To better understand the optimal size where transition will maximise fitness, we need to incorporate the change in mass that happens during this transition. And to test Werner’s theory further, the team highlight the need to estimate mortality rates in the field, including the risk of dying when transitioning to a new stage.

This research is published in the journal Functional Ecology.

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)

Significance

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.

Abstract

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

Abstract

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

Winners and losers: how does metabolic rate affect the outcomes of competition?

An individual’s success in competitive environments is often closely aligned with its metabolic rate. When resources are scarce, individuals with lower metabolic rates are expected to grow larger and dominate while individuals with higher metabolic rates will struggle if their energy demands cannot be met. Increasing population density can increase competition for a finite pool of resources and so lower metabolic rate individuals may do better in more competitive environments.

Lukas Schuster and supervisors Craig White and Dustin Marshall noted that investigations into the relationships between metabolic rate and competitive interactions have mainly taken place in the laboratory. They wanted to know how metabolic rate affected competitive interactions in a more realistic field situation. So, they designed an experiment using the model species Bugula neritina, a colonial marine animal that, crucially, does not move allowing survival, growth, and reproductive output to be easily measured in the field.

Lukas settled Bugula larvae on to acetate sheets and after two weeks of growth in the field he brought them back to the lab to measure metabolic rates. Each colony with a known metabolic rate was then assigned to become either a ‘focal’ colony or a ‘neighbour’ colony. Colonies were glued on to small plates and focal colonies either had a neighbour colony placed 1 cm away, or were left alone on the plate to determine the baseline relationship between metabolic rate and performance. Plates were distributed across 5 panels and returned to the field site and Lukas monitored focal individuals bi-weekly for survival, growth and reproductive output.

To the teams surprise they found a range of responses on the different panels despite their relative proximity. They concluded that each panel experienced a different microenvironment that, in turn, influenced the effects of metabolic rates on competitive outcomes. While the presence of a neighbour did reduce performance of focal colonies on most panels, the effects of metabolic rates of both focal colonies and neighbours were much more complex.

Bugula neritina individuals were attached to small plates either alone or with a neighbour and these plates were then attached to larger panels and hung in the marina. Despite their proximity, the team suspect differences in microclimate around each panel contributed to the variable outcomes of metabolic rate on competitive interactions.

Low metabolic rate colonies were larger overall, presumably because of their lower maintenance costs but, in general, the metabolic rate of the neighbour seemed more important to performance of the focal colony than its own metabolic rate. Lukas and his supervisors speculate that focal colonies benefited from being adjacent to fast-growing, low metabolic rate neighbours on panels where flow was higher because the larger neighbours slowed down currents allowing greater access to resources for the focal individual. In low flow environments the opposite may be true; resources are not replaced quickly enough and so low metabolic rate larger neighbours reduce resource access.

Lukas, Craig and Dustin recommend that future studies on the ecological effects of metabolism look at competition both within and among species and are field experiments wherever possible.

While they can’t say for sure, they suspect the variable outcomes of metabolic rate on competition relate to differences in current regimes and the delivery of resources.  Future studies manipulating food availability along with metabolic rates will help address this possibility.

This research is published in the journal Ecology and Evolution.

Biodiversity increases energy and biomass production but only in younger communities

Preserving biodiversity is important because species diversity affects the productivity of biological communities. Diverse communities can better use available resources and, thus, produce more biomass than species-poor communities. When diversity is high, communities are also more likely to contain very productive species which further increase biomass production.

While these positive biodiversity effects are seen across diverse ecosystems, from tropical forests to agricultural fields, the general mechanism through which biodiversity increases biomass production remains unclear. Energy is what fuels biological production but very few studies have directly measured energy fluxes and even fewer the effects of biodiversity on energy production. Furthermore, biodiversity effects are not fixed but change as communities grow older. So how does diversity affect the relationship between energy and biomass production over time?

We answer this question using marine phytoplankton in a laboratory study. Phytoplankton are an extremely diverse group of unicellular algae of great ecological importance because they sustain 50% of global oxygen production and carbon uptake. Using five phytoplankton species with different characteristics, we set up a total of 50 cultures across three levels of biodiversity (species alone, in pairs and in communities with all five species) and compare their energy and biomass production for ten days. Since phytoplankton reproduce daily, our experiment covers roughly ten generations.

Diversity initially boosts both energy and biomass production, so that five-species communities produce and accumulate more biomass than species alone or in pairs. But as biomass grows, energy production is limited by competition. This limitation occurs in all cultures but is stronger in diverse communities. Therefore, the positive effects of biodiversity decline over time as communities grow older, see below.

Diverse communities (solid lines) produce energy (magenta) and biomass (green) faster than low-diversity communities (dashed lines), thus accumulating more total biomass. But as biomass accumulates, species compete more intensely limiting energy and thus biomass production. These effects are stronger in more diverse communities so that the positive effects of biodiversity progressively reduce as communities grow older. (Image credit: Giulia Ghedini)

In nature, the positive effects of biodiversity might be sustained over much longer periods of time than what we observe because ecosystems are continuously disturbed by storms, arrival of new species or changes in nutrient availability. Since disturbances are so widespread our results help to compare the functioning of ecosystems of different age and with different levels of diversity.

This research was published in the journal Functional Ecology.

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

Abstract

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 

Challenging assumptions: how well do we understand how climate change will affect vector-borne diseases?

Diseases such as malaria and dengue fever are spread by intermediaries, in this case, mosquitoes. The health and economic burdens of such mosquito-borne diseases are enormous. We know that mosquitoes are expanding their ranges and invading new habitats in response to warmer temperatures. Accurately predicting changes in both the size and spread of mosquito populations is essential for anticipating changes in disease dynamics.

To model how changing environments will affect mosquito populations, we need to know how quickly a population can grow under different scenarios. To estimate changes in population growth rate scientists input measures of development time, survival, body size and reproductive output into their models. Body size and reproductive output are particularly difficult to measure directly in mosquito populations so researchers traditionally rely on the relationship between wing length, which is easier to measure, body size and reproductive output.

These are the relationships that the Centre for Geometric Biology are challenging. Underlying most models of mosquito distributions is the assumption that there is a directly proportional relationship between wing length, body size and reproductive output, or in other words, wing length and reproductive output increase at the same rate.

Scientists from the Centre analysed a range of existing data and found that this wasn’t true for most mosquito species.

In fact, explains Dr Louise Nørgaard, lead author on the study, larger females contribute disproportionately more to the replenishment of the population so it is not a straight-line relationship. And surprisingly, when we factor in this non-linear relationship smaller females are also contributing more to population replenishment than is assumed in current models.

This is important because increasing temperatures result in smaller females. So, temperatures where populations have been considered unviable, will, in fact, persist.

There is an additional complication when dealing with underlying assumptions of linearity; Jensen’s Inequality. This relates to a counter-intuitive mathematical rule that in non-linear relationships, such as this one, you can’t predict the mean reproductive output from the mean wing length in the same way you can for linear relationships. In fact, reproductive output in warmer climates will be even greater than predicted without accounting for Jensen’s Inequality.

This figure shows how reproductive output changes when the relationship between wing length and reproductive output is modelled as a isometric / linear relationship (blue) or hyperallometric / non-linear relationship (orange) (graph A). In this scenario a 15% reduction in wing length result in a 40% reduction in reproductive output when you consider both the shape of the relationship and Jensen’s Inequality (graph B). This contrasts to the 90% reduction in reproductive output that is predicted from an isometric / linear relationship and the 70% reduction in reproductive output if you don’t also account for Jensen’s Inequality (graph C).

There is another application of population models that will also be affected by these underlying assumptions. In the fight against Dengue fever, mosquitos that carry a bacteria called Wolbachia are bred in the lab and released into the wild to reduce the transmission of the dengue virus. Females released from the lab are bigger than their wild counterparts and so will contribute disproportionately more to the population when they breed. We are likely underestimating the impact of releasing Wolbachia-infected mosquitos in tackling this disease.

The authors conclude that to predict the response of disease vectors like mosquitos to global change we need to better represent the relationship between size and reproductive output.

This research was published in the journal Global Change Biology.

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

Abstract

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

Abstract

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