Macroevolutionary patterns in marine hermaphroditism

Authors: George C Jarvis, Craig R White, and Dustin J Marshall

Published in: Evolution

Abstract

Most plants and many animals are hermaphroditic; whether the same forces are responsible for hermaphroditism in both groups is unclear. The well-established drivers of hermaphroditism in plants (e.g., seed dispersal potential, pollination mode) have analogues in animals (e.g., larval dispersal potential, fertilization mode), allowing us to test the generality of the proposed drivers of hermaphroditism across both groups.

Here, we test these theories for 1,153 species of marine invertebrates, from three phyla. Species with either internal fertilization, restricted offspring dispersal, or small body sizes are more likely to be hermaphroditic than species that are external fertilizers, planktonic developers, or larger.

Plants and animals show different biogeographical patterns, however: animals are less likely to be hermaphroditic at higher latitudes — the opposite to the trend in plants.

Overall, our results suggest that similar forces, namely, competition among offspring or gametes, shape the evolution of hermaphroditism across plants and three invertebrate phyla.

Jarvis GC, White CR, Marshall DJ (2022) Macroevolutionary patterns in marine hermaphroditism. Evolution PDF DOI

Changing lanes: can we reconcile the ways we measure reproduction so we can make meaningful comparisons across animal species?

Reproduction is perhaps the only truly unambiguous measure of fitness and yet we measure it in different ways. Biologists working on birds tend to measure clutch size as number of eggs per clutch, while mammal biologists focus on litter size measured in mass. These differences only become obvious when researchers want to move out of their accustomed lanes and ask broader questions applicable to a wide range of animal species. One unequivocal measure of reproduction is reproductive mass per year but how often do researchers measure this?

Reproductive mass per year combines the number of offspring per reproductive bout with the mass of the offspring and, importantly, the number of reproductive bouts per year. We know that some species can have a few large offspring and only reproduce once per year whilst other species can produce many small offspring numerous times per year. So which species puts in the most resources to reproduction? Only by combining measures of offspring mass over time can we really compare reproductive effort across species.

How often are all three components of reproductive mass per year – number of offspring per reproductive bout, offspring mass, and the number of reproductive bouts per year – provided for animals?

PhD student, Sam Ginther, is interested in the energetic costs of reproduction and wondered how feasible it would be to collate reproduction data for a wide range of species. Could he translate the existing data into a consistent and biologically relevant measure of reproductive mass per year?

Sam and supervisors Dustin Marshall, Craig White and Hayley Cameron created a ‘systematic map’ of reproductive trait data that exist in online databases. They used this unbiased approach to collate and describe:

  1. how common is the measure reproductive mass per year in databases, and
  2. how well did more ambiguous reproductive measures (i.e., fecundity per bout, fecundity per year, and reproductive mass per bout) represent a truly comparable measure of reproductive effort – reproductive mass per year.

So, can we use other measures as proxies for reproductive mass per year? While most reproductive measures are poor predictors of reproductive effort, reproductive mass per bout is the exception.

Reproductive databases are amazing resources and represent centuries of work in the field of reproductive biology. However, to unlock their full potential Sam and his colleagues feel that the best way forward is to encourage researchers to measure reproduction in a way that allows us to reconstruct reproductive mass per year; that is, tie reproductive measures to temporal- and volumetric-dimensions. But where this is unrealistic in terms of time and effort then measuring reproductive mass per bout is the next best thing.

This research is published in the journal Global Ecology and Biogeography.

Avoiding growing pains in reproductive trait databases: the curse of dimensionality

Authors: Samuel C Ginther, Hayley Cameron, Craig R White, and Dustin J Marshall

Published in: Global Ecology and Biogeography

Abstract

Aim: Reproductive output features prominently in many trait databases, but the metrics describing it vary and are often untethered to temporal and volumetric dimensions (e.g., fecundity per bout). The use of such ambiguous reproductive measures to make broad-scale comparisons across taxonomic groups will be meaningful only if they show a 1:1 relationship with a reproductive measure that explicitly includes both a volumetric and a temporal component (i.e., reproductive mass per year). We sought to map the prevalence of ambiguous and explicit reproductive measures across taxa and to explore their relationships with one another to determine the cross-compatibility and utility of reproductive metrics in trait databases.

Location: Global.

Time period: 1990–2021.

Major taxa studied: We searched for reproductive measures across all Metazoa and identified 19,785 vertebrate species (Chordata), and 440 invertebrate species (Arthropoda, Cnidaria or Mollusca).

Methods: We included 37 databases, from which we summarized the commonality of reproductive metrics across taxonomic groups. We also quantified scaling relationships between ambiguous reproductive traits (fecundity per bout, fecundity per year and reproductive mass per bout) and an explicit measure (reproductive mass per year) to assess their cross-compatibility.

Results: Most species were missing at least one temporal or volumetric dimension of reproductive output, such that reproductive mass per year could be reconstructed for only 4,786 vertebrate species. Ambiguous reproductive measures were poor predictors of reproductive mass per year; in no instance did these measures scale at 1:1.

Main conclusions: Ambiguous measures systematically misestimate reproductive mass per year. Until more data are collected, we suggest that researchers should use the clade-specific scaling relationships provided here to convert ambiguous reproductive measures to reproductive mass per year.

Ginther SC, Cameron H, White CR, Marshall DJ (2022) Avoiding growing pains in reproductive trait databases: the curse of dimensionality. Global Ecology and Biogeography PDF DOI

Carry-over effects and fitness trade-offs in marine life histories: The costs of complexity for adaptation

Authors Dustin J Marshall and Tim Connallon

Published in Evolutionary Applications

Abstract

Most marine organisms have complex life histories, where the individual stages of a life cycle are often morphologically and ecologically distinct. Nevertheless, life-history stages share a single genome and are linked phenotypically (by “carry-over effects”). These commonalities across the life history couple the evolutionary dynamics of different stages and provide an arena for evolutionary constraints. The degree to which genetic and phenotypic links among stages hamper adaptation in any one stage remains unclear and yet adaptation is essential if marine organisms will adapt to future climates.

Here, we use an extension of Fisher’s geometric model to explore how both carry-over effects and genetic links among life-history stages affect the emergence of pleiotropic trade-offs between fitness components of different stages. We subsequently explore the evolutionary trajectories of adaptation of each stage to its optimum using a simple model of stage-specific viability selection with nonoverlapping generations.

We show that fitness trade-offs between stages are likely to be common and that such trade-offs naturally emerge through either divergent selection or mutation. We also find that evolutionary conflicts among stages should escalate during adaptation, but carry-over effects can ameliorate this conflict.

Carry-over effects also tip the evolutionary balance in favor of better survival in earlier life-history stages at the expense of poorer survival in later stages. This effect arises in our discrete-generation framework and is, therefore, unrelated to age-related declines in the efficacy of selection that arise in models with overlapping generations.

Our results imply a vast scope for conflicting selection between life-history stages, with pervasive evolutionary constraints emerging from initially modest selection differences between stages. Organisms with complex life histories should also be more constrained in their capacity to adapt to global change than those with simple life histories.

Marshall DJ, Connallon T (2022) Carry‐over effects and fitness trade‐offs in marine life histories: The costs of complexity for adaptation. Evolutionary Applications PDF DOI

Metabolic scaling is the product of life-history optimization

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

Published in: Science

Abstract

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 

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