Evolution of a bistable genetic system in fluctuating and nonfluctuating environments.

Epigenetic mechanisms can generate bacterial lineages capable of spontaneously switching between distinct phenotypes. Currently, mathematical models and simulations propose epigenetic switches as a mechanism of adaptation to deal with fluctuating environments. However, bacterial evolution experiments for testing these predictions are lacking. Here, we exploit an epigenetic switch in Salmonella enterica, the opvAB operon, to show clear evidence that OpvAB bistability persists in changing environments but not in stable conditions. Epigenetic control of transcription in the opvAB operon produces OpvABOFF (phage-sensitive) and OpvABON (phage-resistant) cells in a reversible manner and may be interpreted as an example of bet-hedging to preadapt Salmonella populations to the encounter with phages. Our experimental observations and computational simulations illustrate the adaptive value of epigenetic variation as an evolutionary strategy for mutation avoidance in fluctuating environments. In addition, our study provides experimental support to game theory models predicting that phenotypic heterogeneity is advantageous in changing and unpredictable environments.

Eco-evolutionary dynamics of structured populations in periodically fluctuating environments: a G function approach.

Understanding the ecological and evolutionary dynamics of populations is critical for both basic and applied purposes in a variety of biological contexts. Although several modeling frameworks have been developed to simulate eco-evolutionary dynamics, many fewer address how to model structured populations. In a prior paper, we put forth the first modeling approach to simulate eco-evolutionary dynamics in structured populations under the G function modeling framework. However, this approach does not allow for accurate simulation under fluctuating environmental conditions. To address this limitation, we draw on the study of periodic differential equations to propose a modified approach that uses a different definition of fitness more suitable for fluctuating environments. We illustrate this method with a simple toy model of life history trade-offs. The generality of this approach allows it to be used in a variety of biological contexts.

Dynamics of ecosystem services along ecological network seascapes

Human societies depend on services provided by ecosystems, from local needs as clean water and pest control to global services like ozone layer and the ocean biological pump. Ecosystem services are intrinsically linked to the states of the ecosystem, which are, in turn, governed by a complex web of ecological interactions. These interactions and, consequently, the services they support, are increasingly under threat from environmental changes driven by human activities. Therefore, safeguarding these vital services require an understanding of how the structure and dynamics of ecological interactions are affected by environmental change. A critical step towards this goal is the development of an integrative theoretical framework that can elucidate how ecosystem services are sustained or impaired by interactions within these complex ecosystems in fluctuating environments. Recent years have seen significant progress in quantitatively characterizing the organization and the dynamics of ecological interactions through the study of ecological networks. However, linking temporally varying network structure in fluctuating environments, the seascapes of ecological networks, and their impact on ecosystem services remains a challenge. We propose an approach based upon merging empirical ecological network analysis with Boolean functions and modeling techniques accounting for fluctuating environments to tackle how ecosystem services are affected by the changing structure and dynamics of ecological networks. The approach aims to contribute to the study of how the organization of ecological interactions affects the persistence of ecosystem services. Specifically, we discuss how this approach can be used provide new insights into how environmental change affect the relationship between ecological networks and ecosystem services. The combination of information on ecosystem services, Boolean networks and fluctuating environments might allow to enhance the research around conservation strategies for preserving biodiversity and ecosystem services in the face of ongoing environmental change.

Photorespiration - emerging insights into photoprotection mechanisms.

Two recent studies reinvestigated the phenomenon of photorespiration as a photoprotective mechanism. Smith et al. suggest alleviated negative feedback regulation of chloroplast ATP synthase as an alternative hypothesis. Von Bismarck et al. discuss how photorespiration-impaired mutants cope somewhat better with fluctuating light (FL) environments because of downregulated photosynthesis and complex metabolic re-routing.

Population size shapes trade-off dilution and adaptation to a marginal niche unconstrained by sympatric habitual conditions.

How does niche expansion occur when the habitual (high-productivity) and marginal (low-productivity) niches are simultaneously available? Without spatial structuring, such conditions should impose fitness maintenance in the former while adapting to the latter. Hence, adaptation to a given marginal niche should be influenced by the identity of the simultaneously available habitual niche. This hypothesis remains untested. Similarly, it is unknown if larger populations, which can access greater variation and undergo more efficient selection, are generally better at niche expansion. We tested these hypotheses using a large-scale evolution experiment with Escherichia coli. While we observed widespread niche expansion, larger populations consistently adapted to a greater extent to both marginal and habitual niches. Owing to diverse selection pressures in different habitual niches (constant vs. fluctuating environments; environmental fluctuations varying in both predictability and speed), fitness in habitual niches was significantly shaped by their identities. Surprisingly, despite this diversity in habitual selection pressures, adaptation to the marginal niche was unconstrained by the habitual niche's identity. We show that in terms of fitness, two negatively correlated habitual niches can still have positive correlations with the marginal niche. This allows the marginal niche to dilute fitness trade-offs across habitual niches, thereby allowing costless niche expansion. Our results provide fundamental insights into the sympatric niche expansion.

Physiological differences between wild and captive animals: a century-old dilemma.

Laboratory-based research dominates the fields of comparative physiology and biomechanics. The power of lab work has long been recognized by experimental biologists. For example, in 1932, Georgy Gause published an influential paper in Journal of Experimental Biology describing a series of clever lab experiments that provided the first empirical test of competitive exclusion theory, laying the foundation for a field that remains active today. At the time, Gause wrestled with the dilemma of conducting experiments in the lab or the field, ultimately deciding that progress could be best achieved by taking advantage of the high level of control offered by lab experiments. However, physiological experiments often yield different, and even contradictory, results when conducted in lab versus field settings. This is especially concerning in the Anthropocene, as standard laboratory techniques are increasingly relied upon to predict how wild animals will respond to environmental disturbances to inform decisions in conservation and management. In this Commentary, we discuss several hypothesized mechanisms that could explain disparities between experimental biology in the lab and in the field. We propose strategies for understanding why these differences occur and how we can use these results to improve our understanding of the physiology of wild animals. Nearly a century beyond Gause's work, we still know remarkably little about what makes captive animals different from wild ones. Discovering these mechanisms should be an important goal for experimental biologists in the future.

Eco-evolutionary maintenance of diversity in fluctuating environments.

Growing evidence suggests that temporally fluctuating environments are important in maintaining variation both within and between species. To date, however, studies of genetic variation within a population have been largely conducted by evolutionary biologists (particularly population geneticists), while population and community ecologists have concentrated more on diversity at the species level. Despite considerable conceptual overlap, the commonalities and differences of these two alternative paradigms have yet to come under close scrutiny. Here, we review theoretical and empirical studies in population genetics and community ecology focusing on the 'temporal storage effect' and synthesise theories of diversity maintenance across different levels of biological organisation. Drawing on Chesson's coexistence theory, we explain how temporally fluctuating environments promote the maintenance of genetic variation and species diversity. We propose a further synthesis of the two disciplines by comparing models employing traditional frequency-dependent dynamics and those adopting density-dependent dynamics. We then address how temporal fluctuations promote genetic and species diversity simultaneously via rapid evolution and eco-evolutionary dynamics. Comparing and synthesising ecological and evolutionary approaches will accelerate our understanding of diversity maintenance in nature.

Experimental evolution of evolutionary potential in fluctuating environments.

Variation is the raw material for evolution. Evolutionary potential is determined by the amount of genetic variation, but evolution can also alter the visibility of genetic variation to natural selection. Fluctuating environments are suggested to maintain genetic variation but they can also affect environmental variance, and thus, the visibility of genetic variation to natural selection. However, experimental studies testing these ideas are relatively scarce. In order to determine differences in evolutionary potential we quantified variance attributable to population, genotype and environment for populations of the bacterium Serratia marcescens. These populations had been experimentally evolved in constant and two fluctuating environments. We found that strains that evolved in fluctuating environments exhibited larger environmental variation suggesting that adaptation to fluctuations has decreased the visibility of genetic variation to selection.

Do microbes have a memory? History-dependent behavior in the adaptation to variable environments.

Microbes are constantly confronted with changes and challenges in their environment. A proper response to these environmental cues is needed for optimal cellular functioning and fitness. Interestingly, past exposure to environmental cues can accelerate or boost the response when this condition returns, even in daughter cells that have not directly encountered the initial cue. Moreover, this behavior is mostly epigenetic and often goes hand in hand with strong heterogeneity in the strength and speed of the response between isogenic cells of the same population, which might function as a bet-hedging strategy. In this review, we discuss examples of history-dependent behavior (HDB) or "memory," with a specific focus on HDB in fluctuating environments. In most examples discussed, the lag time before the response to an environmental change is used as an experimentally measurable proxy for HDB. We highlight different mechanisms already implicated in HDB, and by using HDB in fluctuating carbon conditions as a case study, we showcase how the metabolic state of a cell can be a key determining factor for HDB. Finally, we consider possible evolutionary causes and consequences of such HDB.

Adaptive Potential of Epigenetic Switching During Adaptation to Fluctuating Environments.

Epigenetic regulation of gene expression allows for the emergence of distinct phenotypic states within the clonal population. Due to the instability of epigenetic inheritance, these phenotypes can intergenerationally switch between states in a stochastic manner. Theoretical studies of evolutionary dynamics predict that the phenotypic heterogeneity enabled by this rapid epigenetic switching between gene expression states would be favored under fluctuating environmental conditions, whereas genetic mutations, as a form of stable inheritance system, would be favored under a stable environment. To test this prediction, we engineered switcher and non-switcher yeast strains, in which the uracil biosynthesis gene URA3 is either continually expressed or switched on and off at two different rates (slow and fast switchers). Competitions between clones with an epigenetically controlled URA3 and clones without switching ability (SIR3 knockout) show that the switchers are favored in fluctuating environments. This occurs in conditions where the environments fluctuate at similar rates to the rate of switching. However, in stable environments, but also in environments with fluctuation frequency higher than the rate of switching, we observed that genetic changes dominated. Remarkably, epigenetic clones with a high, but not with a low, rate of switching can coexist with non-switchers even in a constant environment. Our study offers an experimental proof of concept that helps defining conditions of environmental fluctuation under which epigenetic switching provides an advantage.

Optimal control of a discrete-time plant-herbivore/pest model with bistability in fluctuating environments.

Motivated by regulating/eliminating the population of herbivorous pests, we investigate a discrete-time plant-herbivore model with two different constant control strategies (removal versus reduction), and formulate the corresponding optimal control problems when its dynamics exhibits varied types of bi-stability and fluctuating environments. We provide basic analysis and identify the critical factors to characterize the optimal controls and the corresponding plant-herbivore dynamics such as the control upper bound (the effectiveness level of the implementation of control measures) and the initial conditions of the plant and herbivore. Our results show that optimal control could be easier when the model has simple dynamics such as stable equilibrium dynamics under constant environment or the model exhibits chaotic dynamics under fluctuating environments. Due to bistability, initial conditions are important for optimal controls. Regardless of with or without fluctuating environments, initial conditions taken from the near the boundary makes optimal control easier. In general, the pest is hard to be eliminated when the control upper bound is not large enough. However, as the control upper bound is increased or the initial conditions are chosen from near the boundary of the basin of attractions, the pest can be manageable regardless of the fluctuating environments.

The Importance of Noise Colour in Simulations of Evolutionary Systems.

Simulations of evolutionary dynamics often employ white noise as a model of stochastic environmental variation. Whilst white noise has the advantages of being simply generated and analytically tractable, empirical analyses demonstrate that most real environmental time series have power spectral densities consistent with pink or red noise, in which lower frequencies contribute proportionally greater amplitudes than higher frequencies. Simulated white noise environments may therefore fail to capture key components of real environmental time series, leading to erroneous results. To explore the effects of different noise colours on evolving populations, a simple evolutionary model of the interaction between life-history and the specialism-generalism axis was developed. Simulations were conducted using a range of noise colours as the environments to which agents adapted. Results demonstrate complex interactions between noise colour, reproductive rate, and the degree of evolved generalism; importantly, contradictory conclusions arise from simulations using white as opposed to red noise, suggesting that noise colour plays a fundamental role in generating adaptive responses. These results are discussed in the context of previous research on evolutionary responses to fluctuating environments, and it is suggested that Artificial Life as a field should embrace a wider spectrum of coloured noise models to ensure that results are truly representative of environmental and evolutionary dynamics.

Slower environmental cycles maintain greater life-history variation within populations.

Populations in nature are comprised of individual life histories, whose variation underpins ecological and evolutionary processes. Yet the forces of environmental selection that shape intrapopulation life-history variation are still not well-understood, and efforts have largely focused on random (stochastic) fluctuations of the environment. However, a ubiquitous mode of environmental fluctuation in nature is cyclical, whose periodicities can change independently of stochasticity. Here, we test theoretically based hypotheses for whether shortened ('Fast') or lengthened ('Slow') environmental cycles should generate higher intrapopulation variation of life history phenotypes. We show, through a combination of agent-based modelling and a multi-generational laboratory selection experiment using the tidepool copepod Tigriopus californicus, that slower environmental cycles maintain higher levels of intrapopulation variation. Surprisingly, the effect of environmental periodicity on variation was much stronger than that of stochasticity. Thus, our results show that periodicity is an important facet of fluctuating environments for life-history variation.

Fluctuating selection and global change: a synthesis and review on disentangling the roles of climate amplitude, predictability and novelty.

A formidable challenge for global change biologists is to predict how natural populations will respond to the emergence of conditions not observed at present, termed novel climates. Popular approaches to predict population vulnerability are based on the expected degree of novelty relative to the amplitude of historical climate fluctuations experienced by a population. Here, we argue that predictions focused on amplitude may be inaccurate because they ignore the predictability of environmental fluctuations in driving patterns of evolution and responses to climate change. To address this disconnect, we review major findings of evolutionary theory demonstrating the conditions under which phenotypic plasticity is likely to evolve in natural populations, and how plasticity decreases population vulnerability to novel environments. We outline key criteria that experimental studies should aim for to effectively test theoretical predictions, while controlling for the degree of climate novelty. We show that such targeted tests of evolutionary theory are rare, with marine systems being overall underrepresented in this venture despite exhibiting unique opportunities to test theory. We conclude that with more robust experimental designs that manipulate both the amplitude and predictability of fluctuations, while controlling for the degree of novelty, we may better predict population vulnerability to climate change.

Interplay of population size and environmental fluctuations: A new explanation for fitness cost rarity in asexuals.

Theoretical models of ecological specialisation commonly assume that adaptation to one environment leads to fitness reductions (costs) in others. However, experiments often fail to detect such costs. We addressed this conundrum using experimental evolution with Escherichia coli in several constant and fluctuating environments at multiple population sizes. We found that in fluctuating environments, smaller populations paid significant costs, but larger ones avoided them altogether. Contrastingly, in constant environments, larger populations paid more costs than the smaller ones. Overall, large population sizes and fluctuating environments led to cost avoidance only when present together. Mutational frequency distributions obtained from whole-genome whole-population sequencing revealed that the primary mechanism of cost avoidance was the enrichment of multiple beneficial mutations within the same lineage. Since the conditions revealed by our study for avoiding costs are widespread, it provides a novel explanation of the conundrum of why the costs expected in theory are rarely detected in experiments.

What Is the Storage Effect, Why Should It Occur in Cancers, and How Can It Inform Cancer Therapy?

Intratumor heterogeneity is a feature of cancer that is associated with progression, treatment resistance, and recurrence. However, the mechanisms that allow diverse cancer cell lineages to coexist remain poorly understood. The storage effect is a coexistence mechanism that has been proposed to explain the diversity of a variety of ecological communities, including coral reef fish, plankton, and desert annual plants. Three ingredients are required for there to be a storage effect: (1) temporal variability in the environment, (2) buffered population growth, and (3) species-specific environmental responses. In this article, we argue that these conditions are observed in cancers and that it is likely that the storage effect contributes to intratumor diversity. Data that show the temporal variation within the tumor microenvironment are needed to quantify how cancer cells respond to fluctuations in the tumor microenvironment and what impact this has on interactions among cancer cell types. The presence of a storage effect within a patient's tumors could have a substantial impact on how we understand and treat cancer.

Evolutionary dynamics of competing phenotype-structured populations in periodically fluctuating environments.

Living species, ranging from bacteria to animals, exist in environmental conditions that exhibit spatial and temporal heterogeneity which requires them to adapt. Risk-spreading through spontaneous phenotypic variations is a known concept in ecology, which is used to explain how species may survive when faced with the evolutionary risks associated with temporally varying environments. In order to support a deeper understanding of the adaptive role of spontaneous phenotypic variations in fluctuating environments, we consider a system of non-local partial differential equations modelling the evolutionary dynamics of two competing phenotype-structured populations in the presence of periodically oscillating nutrient levels. The two populations undergo heritable, spontaneous phenotypic variations at different rates. The phenotypic state of each individual is represented by a continuous variable, and the phenotypic landscape of the populations evolves in time due to variations in the nutrient level. Exploiting the analytical tractability of our model, we study the long-time behaviour of the solutions to obtain a detailed mathematical depiction of the evolutionary dynamics. The results suggest that when nutrient levels undergo small and slow oscillations, it is evolutionarily more convenient to rarely undergo spontaneous phenotypic variations. Conversely, under relatively large and fast periodic oscillations in the nutrient levels, which bring about alternating cycles of starvation and nutrient abundance, higher rates of spontaneous phenotypic variations confer a competitive advantage. We discuss the implications of our results in the context of cancer metabolism.

Fluctuations in nutrient composition affect male reproductive output in Drosophila melanogaster.

Insects are known to selectively balance their intake of protein and carbohydrate to optimize reproduction and survival. For insects who feed on decomposing fruit, fluctuations in macronutrient composition occur as fruits ripe and decomposition progresses which may challenge optimal resource allocation. Using Drosophila melanogaster, we tested the effect of macronutrient fluctuations and the variability of these fluctuations on starvation resistance and components of reproductive output; traits known to be sensitive to different protein to carbohydrate (P:C) ratios in the diet. For 8 days, flies were fed the same protein to carbohydrate (P:C) ratio (constant feeding), or fed diets with fluctuations in P:C ratio on each day; these fluctuations being regular (predictably fluctuating) or irregular (unpredictably fluctuating). The three feeding regimes yielded the same average P:C ratio across the duration of the experiment. We found no difference in starvation resistance across the feeding regimes. Interestingly, there was a sexual dimorphism in the effect on reproductive output with males performing worst in the unpredictable feeding regime, and with no effect of feeding regime on female performance. Our study provides evidence for means of adapting to fluctuating macronutrient composition and suggests females are more tactful than males in storing and allocating resources for reproduction.

How differing modes of non-genetic inheritance affect population viability in fluctuating environments.

Different modes of non-genetic inheritance are expected to affect population persistence in fluctuating environments. We here analyse Caenorhabditis elegans density-independent per capita growth rate time series on 36 populations experiencing six controlled sequences of challenging oxygen level fluctuations across 60 generations, and parameterise competing models of non-genetic inheritance in order to explain observed dynamics. Our analysis shows that phenotypic plasticity and anticipatory maternal effects are sufficient to explain growth rate dynamics, but that a carryover model where 'epigenetic' memory is imperfectly transmitted and might be reset at each generation is a better fit to the data. We further find that this epigenetic memory is asymmetric since it is kept for longer when populations are exposed to the more challenging environment. Our analysis suggests that population persistence in fluctuating environments depends on the non-genetic inheritance of phenotypes whose expression is regulated across multiple generations.

Environment-to-phenotype mapping and adaptation strategies in varying environments.

Biological organisms exhibit diverse strategies for adapting to varying environments. For example, a population of organisms may express the same phenotype in all environments ("unvarying strategy") or follow environmental cues and express alternative phenotypes to match the environment ("tracking strategy"), or diversify into coexisting phenotypes to cope with environmental uncertainty ("bet-hedging strategy"). We introduce a general framework for studying how organisms respond to environmental variations, which models an adaptation strategy by an abstract mapping from environmental cues to phenotypic traits. Depending on the accuracy of environmental cues and the strength of natural selection, we find different adaptation strategies represented by mappings that maximize the long-term growth rate of a population. The previously studied strategies emerge as special cases of our model: The tracking strategy is favorable when environmental cues are accurate, whereas when cues are noisy, organisms can either use an unvarying strategy or, remarkably, use the uninformative cue as a source of randomness to bet hedge. Our model of the environment-to-phenotype mapping is based on a network with hidden units; the performance of the strategies is shown to rely on having a high-dimensional internal representation, which can even be random.