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.

Reproductive hyperallometry and managing the world’s fisheries

Authors: Dustin J Marshall, Michael Bode, Marc Mangel, Robert Arlinghaus, and EJ Dick

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

Significance

We find that a ubiquitous assumption in fisheries models for predicting population replenishment introduces systematic overestimates of replenishment in fished populations.

For 32 of the world’s major fisheries, these biases result in harvest thresholds being set too high: in most cases, reference points based on spawning potential ratios are more than 2.5 times higher than those necessary to achieve the desired level of replenishment.

When we use the more biologically appropriate assumption of reproductive hyperallometry, we find that management tools such as spatiotemporal closures and harvest slots can outperform traditional approaches in terms of yield.

Failing to consider reproductive hyperallometry overestimates the efficacy of traditional fisheries management and underestimates the benefits of approaches that create reservoirs of larger individuals.

Abstract

Marine fisheries are an essential component of global food security, but many are close to their limits and some are overfished. The models that guide the management of these fisheries almost always assume reproduction is proportional to mass (isometry), when fecundity generally increases disproportionately to mass (hyperallometry).

Judged against several management reference points, we show that assuming isometry overestimates the replenishment potential of exploited fish stocks by 22% (range: 2% to 78%) for 32 of the world’s largest fisheries, risking systematic overharvesting.

We calculate that target catches based on assumptions of isometry are more than double those based on assumptions of hyperallometry for most species, such that common reference points are set twice as high as they should be to maintain the target level of replenishment.

We also show that hyperallometric reproduction provides opportunities for increasing the efficacy of tools that are underused in standard fisheries management, such as protected areas or harvest slot limits. Adopting management strategies that conserve large, hyperfecund fish may, in some instances, result in higher yields relative to traditional approaches.

We recommend that future assessment of reference points and quotas include reproductive hyperallometry unless there is clear evidence that it does not occur in that species.

Marshall DJ, Bode M, Mangel M, Arlinghaus R, Dick EJ (2021) Reproductive hyperallometry and managing the world’s fisheries. Proceedings of the National Academy of Sciences of the United States of America PDF DOI

Mind the gap: a systematic map of light variation in algal aquaculture allows us to identify research gaps

Algae need light to grow but how much light and how it should be delivered are important questions in aquaculture. Even in nature, light does not fall evenly; cloud cover, shading, water movement, water depth can all affect the amount of light algae experience and the time frame it is experienced over. So, what is the best light delivery regime to maximise yield in algal aquaculture? And, importantly, do we have the information to answer this question?

PhD student Belinda Comerford, under the supervision of Nick Paul and Dustin Marshall, has assessed what studies exist that look at variation in light and, crucially, where the gaps in research are. She used a systematic mapping technique where she followed a strict protocol with clearly articulated methods so other researchers will be able to add to the ‘map’ as the field develops.

Once she had settled on her search terms she entered them into the Web of Science database and assessed all the returned studies against the inclusion criteria. From the 10,000 studies returned from initial searches, she retained 212 for further analysis.

Belinda wanted to know what scale light manipulations happened (was it seconds or weeks?) and how long experiments lasted for. What pattern did researchers use when they manipulated light; was it square (light on or off), sinusoidal (gradual increase and decrease in light intensities) or sawtooth (jagged)? How big were the culture vessels used in the experiments? How many generations of algae were subject to the light manipulations?

Once she had coded all the studies that had met the inclusion criteria for her questions of interest, Belinda was able to determine areas where a rich knowledge-base ripe for further synthesis exists and, conversely, where we don’t have enough evidence to reliably assess impacts of variable light regimes on algal yield.

Belinda found that we have a good understanding of light variation on the immediate growth dynamics of microalgae over short time scales – milliseconds to day/night cycles.  But we don’t know the long-term implications of this light variation on algal cultures.

After completing the systematic map, Belinda can confidently point to where research is best directed to inform aquaculture. She recommends future studies focus on larger scale culture vessels and light variation regimes (sinusoidal and sawtooth) that better mimic production settings. Experiments that vary light on the scale of seconds, minutes and hours and that last for multiple months using cultures where biomass is kept relatively constant, through harvesting, will be particularly relevant for industry.

While Belinda recognises that some of these recommendations are demanding, she hopes by identifying the knowledge gaps, it will encourage researchers to tackle the formidable challenge of working at larger scales.

This research is published in the Journal of Applied Phycology.

Belinda recommends that future studies focus on larger culture vessels and light variation regimes that better mimic production settings.

Effects of light variation in algal cultures: a systematic map of temporal scales

Authors: Belinda Comerford, Nicholas Paul, and Dustin J Marshall

Published in: Journal of Applied Phycology

Abstract

Algal aquaculture is a rapidly growing field, with a proliferation of studies exploring algal growth. The expansion of the field not only presents opportunities for synthesis, but also creates challenges in identifying where the strengths and knowledge gaps exist.

One tool for formally quantifying the state of knowledge is a systematic map, already useful in many fields, but underutilised in algal research. We used a systematic map to describe variable light regimes in algal cultures.

Light variation is ubiquitous in algal cultures and spans a range of temporal scales (microseconds to months), but it is unclear which scales have been explored.

We characterised 1393 experiments according to the temporal scale of light variation that was manipulated. Intensely studied light variation frequencies were either very short (< seconds) or long (diel cycles); the prominent gap was frequencies between these extremes (seconds to hours), especially for experiments that lasted for long durations (> months). Experiments that lasted for days were most common, while few studies lasted for months or more. Most studies were conducted in small culture vessels, used instantaneous changes in light regimes, and few studies reported initial stocking density metrics consistently.

Our map highlights that the field has accumulated a rich knowledge base that is ripe for synthesis in some areas, particularly very short or relatively long frequency light variation. The map indicates that the key priorities are explorations of intermediate frequencies and our understanding of their effects is limited. Similarly, our understanding of evolutionary responses to variable light regimes of all scales is lagging.

Comerford B, Paul N, Marshall D (2021) Effects of light variation in algal cultures: a systematic map of temporal scales. Journal of Applied Phycology PDF DOI