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 

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

Abstract

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

Significance

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.

Abstract

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

Fishing better to fish more

We have benchmarks for how to manage fisheries sustainably but what if the assumptions that go into setting those benchmarks are wrong?

In a previous study led by Diego Barneche and published in 2018, a research team looked at reproduction in more than 300 fish species. They found that contrary to a general perception, reproductive output did not increase in proportion with the size of the fish. Instead, the bigger the fish the disproportionately more eggs it produced. The mathematical term for this is hyperallometry.

This has clear implications for fisheries management and led Dustin and colleagues from Australia, USA and Germany to investigate assumptions around reproduction in fisheries management models.

Thirty-two of the world’s largest fisheries use management models that assume a proportional increase in reproductive output and fish size. These models estimate reproductive output from the total biomass of fish mature enough to spawn. This is because they are assuming that two 1 kg fish have the same reproductive output as one 2 kg fish. But the study led by Diego found that this was unlikely — 95% of the fish species they looked at had a hyperallometric relationship between size and reproduction — meaning the one big fish will produce many more eggs than the two smaller fish put together.

Does it matter? Well, yes. Dustin and his colleagues calculated that, for these fisheries, catches are set too high — in most cases, catches are twice what they should be in order to achieve the desired level of replenishment.

So, what happens when we get the biology right? Importantly, challenging assumptions about reproduction not only has ramifications for setting catch limits but has the potential to reset the way we manage fisheries. The team produced models that looked at retaining the largest and most reproductive members of the stock; through a temporary closure or protected area, or by setting size limits that focused on mid-size fish — leaving juveniles and the largest individuals unharvested.

The benefits of these different approaches vary depending on the species. Atlantic cod, for example, would benefit by switching to a fishery closure (either in space or time) with a predicted increase in long-term catch of ~25%

Dustin and his team acknowledge there are difficulties (both practical and social) with these approaches but also emphasise that any strategy that protects and retains larger fish in a population should provide a pay-off. Their models had some general assumptions of their own, however. When modelling fisheries that included protected areas where no fishing was allowed, they assumed that adult fish moved very little while larvae had the potential to replenish areas a long way away.

To check whether their results were too optimistic they did a more detailed study of the coral trout fishery in the Great Barrier Reef where they input data on larval movement. This reduced the catch increase from ~32% to ~16% suggesting that the more generic approach may overestimate benefits of fishery closures by ~12%.

A benefit of 16% is still non-trivial. Overall the results suggest that including hyperallometric reproduction in fisheries management models allows underused management tools such as marine protected areas to outperform traditional tools. This study highlights the role of reservoirs of large, highly reproductive individuals within a fishery.

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