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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

lizmorris66

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.
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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

lizmorris66

Mother-offspring conflicts: temperature can change selection on offspring size

We know offspring size varies enormously and understanding this variation is a long-standing goal of life history theoreticians and ecologists alike. A particularly interesting facet of offspring size is the fact it affects the fitness of both mothers and offspring simultaneously, so selection acts on both. This can lead to conflict over the amount of provisioning mothers provide to offspring. Selection on offspring usually favours bigger sizes, but mothers should only produce larger offspring where there is a marked benefit in performance for these offspring – there is a cost associated with this extra provisioning.

Temperature has a fairly reliable relationship with offspring size – higher temperatures are associated with smaller offspring. But what happens next? Does the relationship between offspring size and adult performance change with temperature?

There are few studies exploring these relationships in the field because it is an onerous undertaking. Repeated estimates of selection across multiple seasons and years are required to determine whether the relationship between offspring size and adult performance varies with natural temperature fluctuations

Professor Dustin Marshall designed a long-term study aimed at filling that gap. Using the model marine invertebrate species Bugula neritina, his research group deployed over 6000 individuals of known offspring size into the field over a period of 4 years. In total Dustin had 28 cohorts, each of approximately 240 individuals, where he had measures of survival, growth and reproduction of all individuals and water temperature data for the entire period.

Using the data collected in this study Dustin ran a simple ‘optimisation’ model which predicts cooler temperatures favour mothers producing larger offspring, while higher temperatures favour mothers producing smaller offspring. And, this works the other way around too. Larger offspring are favoured at cooler temperatures, smaller offspring are favoured at higher temperatures. In other words, at higher and lower temperatures, selection pressures on both mothers and offspring are the same; their interests are aligned.

But, there was a catch. At intermediate temperatures a conflict emerged. From around 18-22 degrees it is still better to be larger from the offspring’s perspective. Larger offspring had higher survival and growth than smaller offspring but the benefits were not enough to offset the costs to the mother of producing larger offspring. At these temperatures, mothers are better served by producing smaller offspring. This means at intermediate temperatures we would predict different offspring sizes to be favoured, depending on which perspective is taken.

Dustin also estimated the temporal autocorrelation of selection on offspring size among cohorts. In other words, knowing the selection coefficient on offspring size of one cohort, could he predict the selection coefficient of the next? Surprisingly, the answer was yes. But maybe even more surprising was that selection during one cohort was negatively correlated with selection two cohorts from now. So, it seems that selection varies from one generation to the next but this variation is not entirely random.

Estimating temporal autocorrelation is a notoriously data-hungry exercise which is exacerbated here because Dustin is interested in selection in each cohort. This means he only has selection estimates for 28 cohorts despite the scope of the study. Dustin plans to resume estimating selection on offspring size to see whether these patterns persist, as soon as Covid-19 obstacles are removed.

At the same time, he will see whether the relationships between offspring size, adult performance and temperature, change when offspring settle within a community. Does the presence of other species tip the balance in selection on offspring size?

This research is published in the journal Functional Ecology.

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Temperature-mediated variation in selection on offspring size: A multi-cohort field study

Author: Dustin J Marshall

Published in: Functional Ecology

Abstract

Offspring size is a key life-history trait that often covaries negatively with temperature. Most studies focus on how temperature alters selection on offspring size during early life-history stages such as embryos or larvae. The degree to which temperature alters the relationship between offspring size and post-metamorphic performance remains unclear as field studies across multiple temperature regimes are rare.

I deployed over 6,000 individuals of known offspring size, into the field across 28 cohorts spanning 4 years for the model marine invertebrate, Bugula neritina and monitored their survival, growth and reproduction.

Offspring size closely tracked the local environmental temperature across cohorts. This offspring size–temperature covariance appeared to be adaptive, at least from the perspective of mothers. When temperatures were warmer, the relationship between offspring size and performance was weak; when temperatures were cooler, the relationship was strongly positive.

The estimates of selection based on maternal fitness differed from those based on offspring fitness, suggesting temperature-mediated parent–offspring conflict over offspring provisioning exists. I also found evidence for temporal autocorrelation in temperature and selection on offspring size.

The fact that temperature affects the relationship between offspring size and post-metamorphic performance further complicates the challenge in understanding the ubiquitous covariance between offspring size and temperature.

Marshall DJ (2021) Temperature‐mediated variation in selection on offspring size: A multi‐cohort field study. Functional Ecology PDF DOI

lizmorris66

Challenging the karyoplasmic ratio: bigger cells, smaller nuclei

A new publication finally puts paid to a long-held belief that the ratio between nucleus size and cell size (NS:CS) is approximately constant. This is called the karyoplasmic ratio and, while recently it has been recognised that nucleus size and cell size are not inexorably bound, the idea of a constant NS:CS ratio remains pervasive in biology. Not least in cancer biology where the karyoplasmic ratio is used in both diagnosis and prognosis for certain tumour types.

But, Dr Martino Malerba and Prof Dustin Marshall found that bigger cells have relatively smaller nuclei; as cells get bigger the karyoplasmic ratio actually gets smaller.

It all started when Martino and Dustin noticed that their evolved lines of different size algae didn’t show a constant karyoplasmic ratio. This piqued their curiosity; were these cells unusual or had this been observed in other cells? They started compiling data on cell size and nucleus size in a range of species and started reviewing publications for statements about the karyoplasmic ratio. To their surprise, they found many publications referring to a constant ratio between nucleus size and cell size, but the data didn’t support that. It was enough to compel Martino and Dustin to formally assess the karyoplasmic ratio across a wide range of cell types and species.

They continued amassing data on cell size and nucleus size across as many species as they could find. They collected measurements from 879 species, ranging from microbes to mammals. Then they looked for data within a species and assembled 7,929 observations of both nucleus size and cell size in a diverse range of species including yeast, plants and metazoans. Finally, they returned to the artificially size-selected algae (small and large) and tracked nucleus size and cell size across 500 generations of evolution.

What they found was that while, yes, bigger cells had bigger nuclei, in relative terms bigger cells had smaller nuclei. At all three scales of biological organisation that they looked at (among-species, within-species, and among evolved lineages of the same species) they saw a systematic decrease in the karyoplasmic ratio with increasing cell size.

Martino and Dustin measured nucleus size in two different ways to double check that their observation of decreasing karyoplasmic ratio with increasing cell size was not due to the methods they had used. Here we see that regardless of the method of calculating nucleus size the ratio decreases across a range of different species as well as the large and small evolved algal lines of the same species.

Why do larger cells have relatively smaller nuclei? The authors surmise it might tie into the fact that larger cells also have relatively lower metabolisms. So, is it because larger cells, with their lower relative metabolic rates are able to meet all of their functional needs with relatively smaller nuclei? Or, conversely, is it because larger cells, with relatively smaller nuclei are only capable of sustaining relatively lower metabolic rates? We don’t know.

What we do know is that the decreasing karyoplasmic ratio with increasing cell size is remarkably consistent across a wide variety of life forms. Martino and Dustin hope that a universal driver for this relationship will be identified.

This research was published in the journal Evolution Letters.

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Larger cells have relatively smaller nuclei across the Tree of Life

Authors: Martino E Malerba and Dustin J Marshall

Published in: Evolution Letters

Abstract

Larger cells have larger nuclei, but the precise relationship between cell size and nucleus size remains unclear, and the evolutionary forces that shape this relationship are debated.

We compiled data for almost 900 species – from yeast to mammals – at three scales of biological organisation: among-species, within-species, and among-lineages of a species that was artificially selected for cell size.

At all scales, we showed that the ratio of nucleus size to cell size (the ‘N: C’ ratio) decreased systematically in larger cells. Size evolution appears more constrained in nuclei than cells: cell size spans across six orders of magnitude, whereas nucleus size varies by only three.

The next important challenge is to determine the drivers of this apparently ubiquitous relationship in N:C ratios across such a diverse array of organisms.

Malerba ME, Marshall DJ (2021) Larger cells have relatively smaller nuclei across the Tree of Life. Evolution Letters PDF DOI

lizmorris66

Plastic responses to changes in environment are not necessarily adaptive

Phenotypic plasticity is a term familiar to evolutionary biologists. It refers to the ability of an organism to respond to a changing environment by changing its physical properties – its phenotype. For example, metabolic rate changes with temperature and resource availability.

We usually assume that such changes are adaptive, that is, changes are in the same direction as selection and so will increase the fitness (reproductive output) of the organism in that environment. But, importantly, we don’t usually test for the adaptive significance of phenotypic plasticity because we don’t typically estimate selection in different environments when we assess plasticity.

Lukas Schuster and his supervisors, Craig White and Dustin Marshall, used the model species Bugula neritina to investigate whether changes in metabolic rates in response to different field environments are an example of adaptive phenotypic plasticity. To their surprise they found that, while Bugula exhibited plasticity in metabolic rate, it was not adaptive.

Bugula is a small filter feeding colonial bryozoan that is often found on the undersides of piers. It is also found on vertical surfaces such as pier pilings, although the increased UV radiation and sedimentation experienced on vertical surfaces combine to make this a more stressful living environment.

Lukas collected mature colonies of Bugula from the field and then spawned them in the laboratory and settled the larvae onto small acetate sheets. This allowed Lukas to deploy the Bugula on vertically or horizontally suspended panels (corresponding to harsh and benign environments respectively) and to return colonies to the laboratory to measure metabolic rates. They did two experimental runs to test the consistency of the results.

As a first step, Lukas and his supervisors had to determine how selection on metabolic rate varies across harsh and benign environments. In other words, they needed to establish the relationship between metabolic rate and reproductive output (fitness) in each environment.

They deployed newly settled Bugula to a common, benign environment for three weeks before returning these colonies to the laboratory to measure metabolic rates. Half of the colonies were then deployed into the harsh environment and half was kept in the benign environment. Growth, survival and lifetime reproductive output were then tracked for each colony; this allowed the team to determine whether there was any fitness advantage associated with particular metabolic rates in each environment.

Surprisingly, they found no differences in selection on metabolic rates in the two environments. Instead, in one experimental run, they found evidence that smaller individuals with lower metabolic rates and larger individuals with higher metabolic rates went on to produce more offspring in both environments. This suggests that metabolic rate is unlikely to evolve independently of other traits.

To measure plasticity Lukas returned all colonies to the laboratory to measure metabolic rates for a second time. Colonies from the harsh environment had overall lower metabolic rates compared to colonies from the benign environment.

In the first experimental run the team found that smaller individuals with lower metabolic rates and larger individuals with higher metabolic rates went on to produce more offspring (red areas in graph) regardless of the environment they were in.
In the first experimental run the team found that smaller individuals with lower metabolic rates and larger individuals with higher metabolic rates went on to produce more offspring (red areas in graph) regardless of the environment they were in.

Given the strong and consistent metabolic response to the different environments that the team observed, it would have been tempting to infer that such a response increases fitness. While this seems intuitive, it is not consistent with what they know about selection on metabolic rate in the different environments. There was no difference in the relationship between metabolic rates and reproductive outputs in the two environments and so, although the changes they saw in metabolic rate with environment show that metabolic rate is plastic, their results show that such plasticity is not always adaptive.

Lukas and his supervisors emphasise the importance of assessing selection on a trait in the different environments before assuming that ‘plastic’ responses to different environments are necessarily adaptive. Instead, metabolic plasticity may merely represent a passive response due to correlations with other traits or there may be limits to physiological plasticity due to biochemical constraints. Nonetheless, further studies are needed in order to understand the drivers and consequences of metabolic plasticity in the field.

This research was published in the journal Oikos.

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Geographical bias in physiological data limits predictions of global change impacts

Authors: Craig R White, Dustin J Marshall, Steven L Chown, Susana Clusella‐Trullas, Steven J Portugal, Craig E Franklin and Frank Seebacher

Published in: Functional Ecology

Abstract

Climate affects all aspects of biology. Physiological traits play a key role in mediating these effects, because they define the fundamental niche of each organism.

Climate change is likely to shift environmental conditions away from physiological optima. The consequences for species are significant: they must alter their physiology through plasticity or adaptation, move, or decline to extinction. The ability to understand and predict such organismal responses to global change is, however, only as good as the geographical coverage of the data on which these predictions are based.

Geographical biases in the state of physiological knowledge have been identified, but it has not been determined if these geographical biases are likely to limit our capacity to predict the outcomes of global change. We show that current knowledge of physiological traits is representative of only a limited range of the climates in which terrestrial animals will be required to operate, because data for animals from only a limited range of global climates have been incorporated in existing compilations.

We conclude that geographical bias in existing datasets limits our capacity to predict organismal responses in the vast areas of the planet that are unstudied, and that this geographical bias is a much greater source of uncertainty than the difference between the current climate and the projected future climate. Addressing this bias is urgent to understand where impacts will be most profound, and where the need for intervention is most pressing.

White CR, Marshall DJ, Chown SL, Clusella‐Trullas S, Portugal SJ, Franklin CE, Seebacher F (2021) Geographical bias in physiological data limits predictions of global change impacts. Functional Ecology PDF DOI

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Plastic but not adaptive: habitat‐driven differences in metabolic rate despite no differences in selection between habitats

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

Published in: Oikos

Abstract

Metabolic plasticity in response to different environmental conditions is widespread across taxa. It is reasonable to expect that such plasticity should be adaptive, but only few studies have determined the adaptive significance of metabolic plasticity by formally estimating selection on metabolic rate under different environmental conditions.

We used a model marine colonial invertebrate, Bugula neritina to examine selection on metabolic rate in a harsh and a benign environment in the field, then tested whether these environments induced the expression of different metabolic phenotypes. We conducted two experimental runs and found evidence for positive correlational selection on the combination of metabolic rate and colony size in both environments in one run, whereas we could not detect any selection on metabolic rate in the second run.

Even though there was no evidence for different selection regimes in the different environments, colonies expressed different metabolic phenotypes depending on the environment they experienced. Furthermore, there was no relationship between the degree of plasticity expressed by an individual and their subsequent fitness.

In other words, we found evidence for phenotypic plasticity in metabolic rate, but there was no evidence that this plasticity was adaptive. In the absence of estimates of performance, changes in metabolic rate should not be assumed to be adaptive.

Schuster L, White CR, Marshall DJ (2021) Plastic but not adaptive: habitat‐driven differences in metabolic rate despite no differences in selection between habitats. Oikos PDF DOI