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Heteroresistance (HR) in bacteria describes a subpopulational phenomenon of antibiotic resistant cells of a generally susceptible population. Here, we investigated the molecular mechanisms and phenotypic characteristics underlying HR to ceftazidime (CAZ) in a clinical Enterobacter cloacae complex strain (ECC). We identified a plasmid-borne gene duplication-amplification (GDA) event of a region harbouring an ampC gene encoding a β-lactamase bla DHA-1 as the key determinant of HR. Individual colonies exhibited variations in the copy number of the genes resulting in resistance level variation which correlated with growth onset (lag times) and growth rates in the presence of CAZ. GDA copy number heterogeneity occurred within single resistant colonies, demonstrating heterogeneity of GDA on the single-cell level. The interdependence between GDA, lag time and antibiotic treatment and the strong plasticity underlying HR underlines the high risk for misdetection of antimicrobial HR and subsequent treatment failure., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Environmental stochasticity is a key determinant of population viability. Decades of work exploring how environmental stochasticity influences population dynamics have highlighted the ability of some natural populations to limit the negative effects of environmental stochasticity, one of the strategies being demographic buffering. Whilst various methods exist to quantify demographic buffering, we still do not know which environmental components and demographic mechanisms are most responsible for the demographic buffering observed in natural populations. Here, we introduce a framework to explore the relative impacts of environmental components (i.e., temporal autocorrelation and variance in demographic rates) on demographic buffering and the demographic mechanisms that underly these impacts (i.e., population structure and demographic rates). Using integral projection models, we show how demographic buffering is more sensitive to environmental variance relative to environmental autocorrelation. In addition, environmental autocorrelation and variance impact demographic buffering through distinct demographic mechanisms-i.e., population structure and demographic rates, respectively., (© 2025 The Author(s). Ecology Letters published by John Wiley & Sons Ltd.)

Cell growth and gene expression are heterogeneous processes at the single-cell level, leading to the emergence of multiple physiological states within bacterial populations. Aging is a known deterministic driver of growth asymmetry; however, its role in gene expression heterogeneity remains elusive. Here, we show that aging mother cells undergo a progressive decline in old pole activity, generating asymmetry in protein partitioning, gene expression, and cell morphology. We demonstrate that mother cells, when compared to their daughters, exhibit lower product inheritance and gene expression rates independently of promoter dynamics. The declining activity of maternal old poles generates gene expression gradients that manifest as mother-daughter asymmetry upon division, showing that asymmetry is progressively built over time within the maternal intracellular environment. Moreover, old pole aging correlates with a gradual increase in cell length, leading to morphological asymmetry. These findings provide further evidence for aging as a mechanism to enhance phenotypic heterogeneity in bacterial populations, with possible consequences for stress response and survival.

More than 50% of all animal species are insects that undergo complete metamorphosis. The key innovation of these holometabolous insects is a pupal stage between the larva and adult when most structures are completely rebuilt. Why this extreme lifestyle evolved is unclear. Here, we test the hypothesis that a trade-off between growth and differentiation explains the evolution of this novelty. Using a comparative approach, we find that holometabolous insects grow much faster than hemimetabolous insects. Using a theoretical model, we then show how holometaboly evolves under a growth-differentiation trade-off and identify conditions under which such temporal decoupling of growth and differentiation is favored. Our work supports the notion that the holometabolous life history evolved to remove developmental constraints on fast growth, primarily under high mortality., Competing Interests: Competing interests statement:The authors declare no competing interest.

Non-heritable, phenotypic drug resistance toward antibiotics challenges antibiotic therapies. Characteristics of such phenotypic resistance have implications for the evolution of heritable resistance. Diverse forms of phenotypic resistance have been described, but phenotypic resistance characteristics remain less explored than genetic resistance. Here, we add novel combinations of single-cell characteristics of phenotypic resistant E. coli cells and compare those to characteristics of susceptible cells of the parental population by exposure to different levels of recurrent ampicillin antibiotic. Contrasting expectations, we did not find commonly described characteristics of phenotypic resistant cells that arrest growth or near growth. We find that under ampicillin exposure, phenotypic resistant cells reduced their growth rate by about 50% compared to growth rates prior to antibiotic exposure. The growth reduction is a delayed alteration to antibiotic exposure, suggesting an induced response and not a stochastic switch or caused by a predetermined state as frequently described. Phenotypic resistant cells exhibiting constant slowed growth survived best under ampicillin exposure and, contrary to expectations, not only fast-growing cells suffered high mortality triggered by ampicillin but also growth-arrested cells. Our findings support diverse modes of phenotypic resistance, and we revealed resistant cell characteristics that have been associated with enhanced genetically fixed resistance evolution, which supports claims of an underappreciated role of phenotypic resistant cells toward genetic resistance evolution. A better understanding of phenotypic resistance will benefit combatting genetic resistance by developing and engulfing effective anti-phenotypic resistance strategies., Importance: Antibiotic resistance is a major challenge for modern medicine. Aside from genetic resistance to antibiotics, phenotypic resistance that is not heritable might play a crucial role for the evolution of antibiotic resistance. Using a highly controlled microfluidic system, we characterize single cells under recurrent exposure to antibiotics. Fluctuating antibiotic exposure is likely experienced under common antibiotic therapies. These phenotypic resistant cell characteristics differ from previously described phenotypic resistance, highlighting the diversity of modes of resistance. The phenotypic characteristics of resistant cells we identify also imply that such cells might provide a stepping stone toward genetic resistance, thereby causing treatment failure., Competing Interests: The authors declare no conflict of interest.

Several social dimensions including social integration, status, early-life adversity, and their interactions across the life course can predict health, reproduction, and mortality in humans. Accordingly, the social environment plays a fundamental role in the emergence of phenotypes driving the evolution of aging. Recent work placing human social gradients on a biological continuum with other species provides a useful evolutionary context for aging questions, but there is still a need for a unified evolutionary framework linking health and aging within social contexts. Here, we summarize current challenges to understand the role of the social environment in human life courses. Next, we review recent advances in comparative biodemography and propose a biodemographic perspective to address socially driven health phenotype distributions and their evolutionary consequences using a nonhuman primate population. This new comparative approach uses evolutionary demography to address the joint dynamics of populations, social dimensions, phenotypes, and life history parameters. The long-term goal is to advance our understanding of the link between individual social environments, population-level outcomes, and the evolution of aging., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Extreme climatic events may influence individual-level variability in phenotypes, survival and reproduction, and thereby drive the pace of evolution. Climate models predict increases in the frequency of intense hurricanes, but no study has measured their impact on individual life courses within animal populations. We used 45 years of demographic data of rhesus macaques to quantify the influence of major hurricanes on reproductive life courses using multiple metrics of dynamic heterogeneity accounting for life course variability and life-history trait variances. To reduce intraspecific competition, individuals may explore new reproductive stages during years of major hurricanes, resulting in higher temporal variation in reproductive trajectories. Alternatively, individuals may opt for a single optimal life-history strategy due to trade-offs between survival and reproduction. Our results show that heterogeneity in reproductive life courses increased by 4% during years of major hurricanes, despite a 2% reduction in the asymptotic growth rate due to an average decrease in mean fertility and survival by that is, shortened life courses and reduced reproductive output. In agreement with this, the population is expected to achieve stable population dynamics faster after being perturbed by a hurricane ( ρ = 1.512 ; 95% CI: 1.488, 1.538), relative to ordinary years ρ = 1.482 ; 1.475 , 1.490 . Our work suggests that natural disasters force individuals into new demographic roles to potentially reduce competition during unfavourable environments where mean reproduction and survival are compromised. Variance in lifetime reproductive success and longevity are differently affected by hurricanes, and such variability is mostly driven by survival., (© 2023 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

Simple demographic events, the survival and reproduction of individuals, drive population dynamics. These demographic events are influenced by genetic and environmental parameters, and are the focus of many evolutionary and ecological investigations that aim to predict and understand population change. However, such a focus often neglects the stochastic events that individuals experience throughout their lives. These stochastic events also influence survival and reproduction and thereby evolutionary and ecological dynamics. Here, we illustrate the influence of such non-selective demographic variability on population dynamics using population projection models of an experimental population of Plantago lanceolata. Our analysis shows that the variability in survival and reproduction among individuals is largely due to demographic stochastic variation with only modest effects of differences in environment, genes, and their interaction. Common expectations of population growth, based on expected lifetime reproduction and generation time, can be misleading when demographic stochastic variation is large. Large demographic stochastic variation exhibited within genotypes can lower population growth and slow evolutionary adaptive dynamics. Our results accompany recent investigations that call for more focus on stochastic variation in fitness components, such as survival, reproduction, and functional traits, rather than dismissal of this variation as uninformative noise., (© 2021. The Author(s).)

Bacteria have been thought to flee senescence by dividing into two identical daughter cells, but this notion of immortality has changed over the last two decades. Asymmetry between the resulting daughter cells after binary fission is revealed in physiological function, cell growth, and survival probabilities and is expected from theoretical understanding. Since the discovery of senescence in morphologically identical but physiologically asymmetric dividing bacteria, the mechanisms of bacteria aging have been explored across levels of biological organization. Quantitative investigations are heavily biased toward Escherichia coli and on the role of inclusion bodies-clusters of misfolded proteins. Despite intensive efforts to date, it is not evident if and how inclusion bodies, a phenotype linked to the loss of proteostasis and one of the consequences of a chain of reactions triggered by reactive oxygen species, contribute to senescence in bacteria. Recent findings in bacteria question that inclusion bodies are only deleterious, illustrated by fitness advantages of cells holding inclusion bodies under varying environmental conditions. The contributions of other hallmarks of aging, identified for metazoans, remain elusive. For instance, genomic instability appears to be age independent, epigenetic alterations might be little age specific, and other hallmarks do not play a major role in bacteria systems. What is surprising is that, on the one hand, classical senescence patterns, such as an early exponential increase in mortality followed by late age mortality plateaus, are found, but, on the other hand, identifying mechanisms that link to these patterns is challenging. Senescence patterns are sensitive to environmental conditions and to genetic background, even within species, which suggests diverse evolutionary selective forces on senescence that go beyond generalized expectations of classical evolutionary theories of aging. Given the molecular tool kits available in bacteria, the high control of experimental conditions, the high-throughput data collection using microfluidic systems, and the ease of life cell imaging of fluorescently marked transcription, translation, and proteomic dynamics, in combination with the simple demographics of growth, division, and mortality of bacteria, make the challenges surprising. The diversity of mechanisms and patterns revealed and their environmental dependencies not only present challenges but also open exciting opportunities for the discovery and deeper understanding of aging and its mechanisms, maybe beyond bacteria and aging., Competing Interests: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Steiner.)

Changes in climate can alter individual body size, and the resulting shifts in reproduction and survival are expected to impact population dynamics and viability. However, appropriate methods to account for size-dependent demographic changes are needed, especially in understudied yet threatened groups such as amphibians. We investigated individual- and population-level demographic effects of changes in body size for a terrestrial salamander using capture-mark-recapture data. For our analysis, we implemented an integral projection model parameterized with capture-recapture likelihood estimates from a Bayesian framework. Our study combines survival and growth data from a single dataset to quantify the influence of size on survival while including different sources of uncertainty around these parameters, demonstrating how selective forces can be studied in populations with limited data and incomplete recaptures. We found a strong dependency of the population growth rate on changes in individual size, mediated by potential changes in selection on mean body size and on maximum body size. Our approach of simultaneous parameter estimation can be extended across taxa to identify eco-evolutionary mechanisms acting on size-specific vital rates, and thus shaping population dynamics and viability., Competing Interests: We declare no conflict of interest., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Major disturbance events can have large impacts on the demography and dynamics of animal populations. Hurricanes are one example of an extreme climatic event, predicted to increase in frequency due to climate change, and thus expected to be a considerable threat to population viability. However, little is understood about the underlying demographic mechanisms shaping population response following these extreme disturbances. Here, we analyse 45 years of the most comprehensive free-ranging non-human primate demographic dataset to determine the effects of major hurricanes on the variability and maintenance of long-term population fitness. For this, we use individual-level data to build matrix population models and perform perturbation analyses. Despite reductions in population growth rate mediated through reduced fertility, our study reveals a demographic buffering during hurricane years. As long as survival does not decrease, our study shows that hurricanes do not result in detrimental effects at the population level, demonstrating the unbalanced contribution of survival and fertility to population fitness in long-lived animal populations., Competing Interests: The authors declare no competing interests., (© 2020 The Authors.)

Individuals differ in their life courses, but how this diversity is generated, how it has evolved and how it is maintained is less understood. However, this understanding is crucial to comprehend evolutionary and ecological population dynamics. In structured populations, individual life courses represent sequences of stages that end in death. These life course trajectories or sequences can be described by a Markov chain and individuals diversify over the course of their lives by transitioning through diverse discrete stages. The rate at which stage sequences diversify with age can be quantified by the population entropy of a Markov chain. Here, we derive sensitivities of the population entropy of a Markov chain to identify which stage transitions generate - or contribute - most to diversification in stage sequences, i.e. life courses. We then use these sensitivities to reveal potential selective forces on the dynamics of life courses. To do so we correlated the sensitivity of each matrix element (stage transition) with respect to the population entropy, to its sensitivity with respect to fitness λ, the population growth rate. Positive correlation between the two sensitivities would suggest that the stage transitions that selection has acted most strongly on (high sensitivities with respect to λ) are also those that contributed most to the diversification of life courses. Using an illustrative example on a seabird population, the Thick-billed Murres on Coats Island, that is structured by reproductive stages, we show that the most influential stage transitions for diversification of life courses are not correlated with the most influential transitions for population growth. Our finding suggests that observed diversification in life courses is neutral rather than adaptive, note this does not imply that the life histories themselves are not adaptive. We are at an early stage of understanding how individual level dynamics shape ecological and evolutionary dynamics, and many discoveries await., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Jellyfish blooms are conspicuous demographic events with significant ecological and socio-economic impact. Despite worldwide concern about an increased frequency and intensity of such mass occurrences, predicting their booms and busts remains challenging. Forecasting how jellyfish populations may respond to environmental change requires considering their complex life histories. Metagenic life cycles, which include a benthic polyp stage, can boost jellyfish mass occurrences via asexual recruitment of pelagic medusae. Here we present stage-structured matrix population models with monthly, individual-based demographic rates of all life stages of the moon jellyfish Aurelia aurita L. (sensu stricto). We investigate the life-stage dynamics of these complex populations under low and high food conditions to illustrate how changes in medusa density depend on non-medusa stage dynamics. We show that increased food availability can be an important ecological driver of jellyfish mass occurrences, as it can temporarily shift the population structure from polyp- to medusa-dominated. Projecting populations for a winter warming scenario additionally enhanced the booms and busts of jellyfish blooms. We identify demographic key variables that control the intensity and frequency of jellyfish blooms in response to environmental drivers such as habitat eutrophication and climate change. By contributing to an improved understanding of mass occurrence phenomena, our findings provide perspective for future management of ecosystem health., (© 2019 British Ecological Society.)

Background: Human life expectancy continues to rise in most populations. This rise not only leads to longer lives but also is accompanied by improved health at a given age, that is, recent cohorts show a reduction of biological age for a given chronological age. Despite or even because of the diversity of biomarkers of aging, an accurate quantification of a general shift in biological age across time has been challenging., Methods: Here, we compared age perception of facial images taken in 2001 over a decade and related these changes in age perception to changes in life expectancy., Results: We show that age perception changes substantially across time and parallels the progress in life expectancy. In 2012, people aged more than 70 years needed to look 2.3 years younger to be rated the same age as in 2002., Conclusions: Our results suggest that age perception reflects the past life events better than predicts future length of life, that is, it is written in your face how much you have aged so far. We draw this conclusion as age perception among elderly individuals paralleled changes in life expectancy at birth but not changes in remaining life expectancies. We suggest that changes in age perception should be explored for younger age classes to inform on aging processes, including whether aging is delayed or slowed with increasing life expectancy., (© The Author(s) 2019. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

In many developed countries, human life expectancy has doubled over the last 180 years. Underlying this higher life expectancy is a change in how we age. Biomarkers of ageing are used to quantify changes in the aging process and to determine biological age. Perceived age is such a biomarker that correlates with biological age. Here we present a unique database rich with possibilities to study the human ageing process. Using perceived age enables us to collect large amounts of data on biological age through a citizen science project, where people upload facial pictures and guess the ages of other people at www.ageguess.org . The data on perceived age we present here span birth cohorts from the years 1877 to 2012. The database currently contains around 220,000 perceived age guesses. Almost 4500 citizen scientists from over 120 countries of origin have uploaded ~4700 facial photographs. Beyond studying the ageing process, the data present a wealth of possibilities to study how humans guess ages and who is better at guessing ages.

Organisms are faced with variable environments and one of the most common solutions to cope with such variability is phenotypic plasticity, a modification of the phenotype to the environment. These modifications are commonly modelled in evolutionary theories as adaptive, influencing ecological and evolutionary processes. If plasticity is adaptive, we would predict that the closer to fitness a trait is, the less plastic it would be. To test this hypothesis, we conducted a meta-analysis of 213 studies and measured the plasticity of each reported trait as a coefficient of variation. Traits were categorized as closer to fitness-life-history traits including reproduction and survival related traits, and farther from fitness-non-life-history traits including traits related to development, metabolism and physiology, morphology and behaviour. Our results showed, unexpectedly, that although traits differed in their amounts of plasticity, trait plasticity was not related to its proximity to fitness. These findings were independent of taxonomic groups or environmental types assessed. We caution against general expectations that plasticity is adaptive, as assumed by many models of its evolution. More studies are needed that test the adaptive nature of plasticity, and additional theoretical explorations on adaptive and non-adaptive plasticity are encouraged.

Biodiversity loss is a major challenge. Over the past century, the average rate of vertebrate extinction has been about 100-fold higher than the estimated background rate and population declines continue to increase globally. Birth and death rates determine the pace of population increase or decline, thus driving the expansion or extinction of a species. Design of species conservation policies hence depends on demographic data (e.g., for extinction risk assessments or estimation of harvesting quotas). However, an overview of the accessible data, even for better known taxa, is lacking. Here, we present the Demographic Species Knowledge Index, which classifies the available information for 32,144 (97%) of extant described mammals, birds, reptiles, and amphibians. We show that only 1.3% of the tetrapod species have comprehensive information on birth and death rates. We found no demographic measures, not even crude ones such as maximum life span or typical litter/clutch size, for 65% of threatened tetrapods. More field studies are needed; however, some progress can be made by digitalizing existing knowledge, by imputing data from related species with similar life histories, and by using information from captive populations. We show that data from zoos and aquariums in the Species360 network can significantly improve knowledge for an almost eightfold gain. Assessing the landscape of limited demographic knowledge is essential to prioritize ways to fill data gaps. Such information is urgently needed to implement management strategies to conserve at-risk taxa and to discover new unifying concepts and evolutionary relationships across thousands of tetrapod species., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

Despite advances in aging research, a multitude of aging models, and empirical evidence for diverse senescence patterns, understanding of the biological processes that shape senescence is lacking. We show that senescence of an isogenic Escherichia coli bacterial population results from two stochastic processes. The first process is a random deterioration process within the cell, such as generated by random accumulation of damage. This primary process leads to an exponential increase in mortality early in life followed by a late age mortality plateau. The second process relates to the stochastic asymmetric transmission at cell fission of an unknown factor that influences mortality. This secondary process explains the difference between the classical mortality plateaus detected for young mothers' offspring and the near nonsenescence of old mothers' offspring as well as the lack of a mother-offspring correlation in age at death. We observed that lifespan is predominantly determined by underlying stochastic stage dynamics. Surprisingly, our findings support models developed for metazoans that base their arguments on stage-specific actions of alleles to understand the evolution of senescence. We call for exploration of similar stochastic influences that shape aging patterns beyond simple organisms., (© 2019 The Author(s). Evolution © 2019 The Society for the Study of Evolution.)

Heterogeneity in life courses among individuals of a population influences the speed of adaptive evolutionary processes, but it is less clear how biotic and abiotic environmental fluctuations influence such heterogeneity. We investigate principal drivers of variability in sequence of stages during an individual's life in a stage-structured population. We quantify heterogeneity by measuring population entropy of a Markov chain, which computes the rate of diversification of individual life courses. Using individual data of a primate population, we show that density regulates the stage composition of the population but that its entropy and the generating moments of heterogeneity are independent of density. This lack of influence of density on heterogeneity is due to neither low year-to-year variation in entropy nor differences in survival among stages but is rather due to differences in stage transitions. Our analysis thus shows that well-known classical ecological selective forces, such as density regulation, are not linked to potential selective forces governing heterogeneity through underlying stage dynamics. Despite evolution acting heavily on individual variability in fitness components, our understanding is poor whether observed heterogeneity is adaptive and how it evolves and is maintained. Our analysis illustrates how entropy represents a more integrated measure of diversity compared to the population structural composition, giving us new insights about the underlying drivers of individual heterogeneity within populations and potential evolutionary mechanisms.

Phenotypic plasticity is ubiquitous and generally regarded as a key mechanism for enabling organisms to survive in the face of environmental change. Because no organism is infinitely or ideally plastic, theory suggests that there must be limits (for example, the lack of ability to produce an optimal trait) to the evolution of phenotypic plasticity, or that plasticity may have inherent significant costs. Yet numerous experimental studies have not detected widespread costs. Explicitly differentiating plasticity costs from phenotype costs, we re-evaluate fundamental questions of the limits to the evolution of plasticity and of generalists vs specialists. We advocate for the view that relaxed selection and variable selection intensities are likely more important constraints to the evolution of plasticity than the costs of plasticity. Some forms of plasticity, such as learning, may be inherently costly. In addition, we examine opportunities to offset costs of phenotypes through ontogeny, amelioration of phenotypic costs across environments, and the condition-dependent hypothesis. We propose avenues of further inquiry in the limits of plasticity using new and classic methods of ecological parameterization, phylogenetics and omics in the context of answering questions on the constraints of plasticity. Given plasticity's key role in coping with environmental change, approaches spanning the spectrum from applied to basic will greatly enrich our understanding of the evolution of plasticity and resolve our understanding of limits.

Major insights into the relationship between life-history features and fitness have come from Lotka's proof that population growth rate is determined by the level (expected amount) of reproduction and the average timing of reproduction of an individual. But this classical result is limited to age-structured populations. Here we generalize this result to populations structured by stage and age by providing a new, unique measure of reproductive timing (Tc) that, along with net reproductive rate (R0), has a direct mathematical relationship to and approximates growth rate (r). We use simple examples to show how reproductive timing Tc and level R0 are shaped by stage dynamics (individual trait changes), selection on the trait, and parent-offspring phenotypic correlation. We also show how population structure can affect dispersion in reproduction among ages and stages. These macroscopic features of the life history determine population growth rate r and reveal a complex interplay of trait dynamics, timing, and level of reproduction. Our results contribute to a new framework of population and evolutionary dynamics in stage-and-age-structured populations.

Understanding the evolution of reaction norms remains a major challenge in ecology and evolution. Investigating evolutionary divergence in reaction norm shapes between populations and closely related species is one approach to providing insights. Here we use a meta-analytic approach to compare divergence in reaction norms of closely related species or populations of animals and plants across types of traits and environments. We quantified mean-standardized differences in overall trait means (Offset) and reaction norm shape (including both Slope and Curvature). These analyses revealed that differences in shape (Slope and Curvature together) were generally greater than differences in Offset. Additionally, differences in Curvature were generally greater than differences in Slope. The type of taxon contrast (species vs. population), trait, organism, and the type and novelty of environments all contributed to the best-fitting models, especially for Offset, Curvature, and the total differences (Total) between reaction norms. Congeneric species had greater differences in reaction norms than populations, and novel environmental conditions increased the differences in reaction norms between populations or species. These results show that evolutionary divergence of curvature is common and should be considered an important aspect of plasticity, together with slope. Biological details about traits and environments, including cryptic variation expressed in novel environmental conditions, may be critical to understanding how reaction norms evolve in novel and rapidly changing environments.

Interest in stage-and age structured models has recently increased because they can describe quantitative traits such as size that are left out of age-only demography. Available methods for the analysis of effects of vital rates on lifespan in stage-structured models have not been widely applied because they are hard to use and interpret, and tools for age and stage structured populations are missing. We present easily interpretable expressions for the sensitivities and elasticities of life expectancy to vital rates in age-stage models, and illustrate their application with two biological examples. Much of our approach relies on trading of time and mortality risk in one stage for time and risk in others. Our approach contributes to the new framework of the study of age- and stage-structured biodemography., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Individuals within populations can differ substantially in their life span and their lifetime reproductive success but such realized individual variation in fitness components need not reflect underlying heritable fitness differences visible to natural selection. Even so, biologists commonly argue that large differences in fitness components are likely adaptive, resulting from and driving evolution by natural selection. To examine this argument we use unique formulas to compute exactly the variance in life span and in lifetime reproductive success among individuals with identical (genotypic) vital rates (assuming a common genotype for all individuals). Such individuals have identical fitness but vary substantially in their realized individual fitness components. We show by example that our computed variances and corresponding simulated distribution of fitness components match those observed in real populations. Of course, (genotypic) vital rates in real populations are expected to differ by small but evolutionarily important amounts among genotypes, but we show that such differences only modestly increase variances in fitness components. We conclude that observed differences in fitness components may likely be evolutionarily neutral, at least to the extent that they are indistinguishable from distributions generated by neutral processes. Important consequences of large neutral variation are the following: Heritabilities for fitness components are likely to be small (which is in fact the case), small selective differences in life histories will be hard to measure, and the effects of random drift will be amplified in natural populations by the large variances among individuals.

Understanding the static and dynamic expression of life history traits is a prerequisite for the development of a causal theory of the evolution of aging and of life histories. We analyzed the statics and dynamics of reproduction and survival in a wild population of the Northern Fulmar, Fulmarus glacialis (Procellaridae). Survival rate is most influenced by year as compared to age and cohort. When temporal variation is ignored, survival rate increases slowly with age and then declines more rapidly at late ages. Survival rate contingent upon reproductive "stratum" (producing an egg, hatching an egg, fledging a hatchling) also exhibits this pattern. Survival and reproduction have a positive static association in that survival rate increases as the apparent energy allocated to reproduction increases (as indexed by stratum). There is a broad distribution of realized lifetime reproductive success, which could be due to "fixed" heterogeneity, with some individuals always having low survival and reproduction and others always having high survival and reproduction, or be due to "dynamic" heterogeneity, with all individuals having the same expected reproductive and survival rates. Analysis of stochastic stratum dynamics indicates that individuals do not remain long in any given stratum and suggest that the variation among individuals with respect to lifetime reproductive success is due to dynamic heterogeneity. The probability of producing an egg increases with age for both sexes, whereas the probability of producing a fledgling initially declines with age and then increases. These results underscore the necessity of understanding the static and dynamic expression of demographic traits when making a causal claim about their evolution.

Biodemography is increasingly focused on the large and persistent differences between individuals within populations in fitness components (age at death, reproductive success) and fitness-related components (health, biomarkers) in humans and other species. To study such variation we propose the use of dynamic models of observable phenotypes of individuals. Phenotypic change in turn determines variation among individuals in their fitness components over the life course. We refer to this dynamic accumulation of fitness differences as dynamic heterogeneity and illustrate it for an animal population in which longitudinal data are studied using multistate capture-mark-recapture models. Although our approach can be applied to any characteristic, for our empirical example we use reproduction as the phenotypic character to define stages. We indicate how our stage-structured model describes the nature of the variation among individual characteristics that is generated by dynamic heterogeneity. We conclude by discussing our ongoing and planned work on animals and humans. We also discuss the connections between our work and recent work on human mortality, disability and health, and life course theory.

1. Understanding the evolution of life histories requires an assessment of the process that generates variation in life histories. Within-population heterogeneity of life histories can be dynamically generated by stochastic variation of reproduction and survival or be generated by individual differences that are fixed at birth. 2. We show for the kittiwake that dynamic heterogeneity is a sufficient explanation of observed variation of life histories. 3. The total heterogeneity in life histories has a small contribution from reproductive stage dynamics and a large contribution from survival differences. We quantify the diversity in life histories by metrics computed from the generating stochastic process. 4. We show how dynamic heterogeneity can be used as a null model and also how it can lead to positive associations between reproduction and survival across the life span. 5. We believe our approach to identifying the nature of among-individual heterogeneity yields important insights into the forces that generate within-population variation of life-history traits. It provides an alternative to claims that fixed individual differences are a major determinant of heterogeneity in life histories.

Defence against predators is usually accompanied by declining rates of growth or development. The classical growth/predation risk tradeoff assumes reduced activity as the cause of these declines. However, in many cases these costs cannot be explained by reduced foraging effort or enhanced allocation to defensive structures under predation risk. Here, we tested for a physiological origin of defence costs by measuring oxygen consumption in tadpoles (Rana temporaria) exposed to predation risk over short and long periods of time. The short term reaction was an increase in oxygen consumption, consistent with the "fight-or-flight" response observed in many organisms. The long term reaction showed the opposite pattern: tadpoles reduced oxygen consumption after three weeks exposure to predators, which would act to reduce the growth cost of predator defence. The results point to an instantaneous and reversible stress response to predation risk. This suggests that the tradeoff between avoiding predators and growing rapidly is not caused by changes in metabolic rate, and must be sought in other behavioural or physiological processes.

Organisms are capable of an astonishing repertoire of phenotypic responses to the environment, and these often define important adaptive solutions to heterogeneous and unpredictable conditions. The terms 'phenotypic plasticity' and 'canalization' indicate whether environmental variation has a large or small effect on the phenotype. The evolution of canalization and plasticity is influenced by optimizing selection-targeting traits within environments, but inherent fitness costs of plasticity may also be important. We present a meta-analysis of 27 studies (of 16 species of plant and 7 animals) that have measured selection on the degree of plasticity independent of the characters expressed within environments. Costs of plasticity and canalization were equally frequent and usually mild; large costs were observed only in studies with low sample size. We tested the importance of several covariates, but only the degree of environmental stress was marginally positively related to the cost of plasticity. These findings suggest that costs of plasticity are often weak, and may influence phenotypic evolution only under stressful conditions.

Longitudinal data on natural populations have been analysed using multistage models in which survival depends on reproductive stage, and individuals change stages according to a Markov chain. These models are special cases of stage-structured population models. We show that stage-structured models generate dynamic heterogeneity: life-history differences produced by stochastic stratum dynamics. We characterize dynamic heterogeneity in a range of species across taxa by properties of the Markov chain: the entropy, which describes the extent of heterogeneity, and the subdominant eigenvalue, which describes the persistence of reproductive success during the life of an individual. Trajectories of reproductive stage determine survivorship, and we analyse the variance in lifespan within and between trajectories of reproductive stage. We show how stage-structured models can be used to predict realized distributions of lifetime reproductive success. Dynamic heterogeneity contrasts with fixed heterogeneity: unobserved differences that generate variation between life histories. We show by an example that observed distributions of lifetime reproductive success are often consistent with the claim that little or no fixed heterogeneity influences this trait. We propose that dynamic heterogeneity provides a 'neutral' model for assessing the possible role of unobserved 'quality' differences between individuals. We discuss fitness for dynamic life histories, and the implications of dynamic heterogeneity for the evolution of life histories and senescence.

Why are some traits constitutive and others inducible? The term costs often appears in work addressing this issue but may be ambiguously defined. This review distinguishes two conceptually distinct types of costs: phenotypic costs and plasticity costs. Phenotypic costs are assessed from patterns of covariation, typically between a focal trait and a separate trait relevant to fitness. Plasticity costs, separable from phenotypic costs, are gauged by comparing the fitness of genotypes with equivalent phenotypes within two environments but differing in plasticity and fitness. Subtleties associated with both types of costs are illustrated by a body of work addressing predator-induced plasticity. Such subtleties, and potential interplay between the two types of costs, have also been addressed, often in studies involving genetic model organisms. In some instances, investigators have pinpointed the mechanistic basis of plasticity. In this vein, microbial work is especially illuminating and has three additional strengths. First, information about the machinery underlying plasticity--such as structural and regulatory genes, sensory proteins, and biochemical pathways--helps link population-level studies with underlying physiological and genetic mechanisms. Second, microbial studies involve many generations, large populations, and replication. Finally, empirical estimation of key parameters (e.g., mutation rates) is tractable. Together, these allow for rigorous investigation of gene interactions, drift, mutation, and selection--all potential factors influencing the maintenance or loss of inducible traits along with phenotypic and plasticity costs. Messages emerging from microbial work can guide future efforts to understand the evolution of plastic traits in diverse organisms.

Costs of phenotypic plasticity are important for the evolution of plasticity because they prevent organisms from shaping themselves at will to match heterogeneous environments. These costs occur when plastic genotypes have relatively low fitness regardless of the trait value expressed. We report two experiments in which we measured selection on predator-induced plasticity in the behaviour and external morphology of frog tadpoles (Rana temporaria). We assessed costs under stressful and benign conditions, measured fitness as larval growth rate or competitive ability and focused analysis on aggregate measures of whole-organism plasticity. There was little convincing evidence for a cost of phenotypic plasticity in our experiments, and costs of canalization were nearly as frequent as costs of plasticity. Neither the magnitude of the cost nor the variation around the estimate (detectability) was sensitive to environmental stress.

An organism's investment in different traits to reduce predation is determined by the fitness benefit of the defense relative to the fitness costs associated with the allocation of time and resources to the defense. Inherent tradeoffs in time and resource allocation should result in differential investment in defense along a resource gradient, but competing models predict different patterns of investment. There are currently insufficient empirical data on changes in investment in defensive traits or their costs along resource gradients to differentiate between the competing allocation models. In this study, I exposed tadpoles to caged predators along a resource gradient in order to estimate investment in defense and costs of defense by assessing predator-induced plasticity. Induced defenses included increased tail depth, reduced feeding, and reduced swimming activity; costs associated with these defenses were reduced developmental rate, reduced growth, and reduced survival. At low resource availability, these costs predominately resulted in reduced survival, while at high resource availability the costs yielded a reduced developmental rate. Defensive traits responded strongly to predation risk, but did not respond to resource availability (with the exception of feeding activity), whereas traits construed as costs of defenses showed the opposite pattern. Therefore, defensive traits were highly sensitive to predation risk, while traits construed as costs of defense were highly sensitive to resource allocation tradeoffs. This difference in sensitivity between the two groups of traits may explain why the correlation between the expression of defensive traits and the expression of the associated defense costs was weak. Furthermore, my results indicate that genetic linkages and mechanistic integration of multiple defensive traits and their associated costs may constrain time and resource allocation in ways that are not addressed in existing models.

Prey organisms are confronted with time and resource allocation trade-offs. Time allocation trade-offs partition time, for example, between foraging effort to acquire resources and behavioral defense. Resource allocation trade-offs partition the acquired resources between multiple traits, such as growth or morphological defense. We develop a mathematical model for prey organisms that comprise time and resource allocation trade-offs for multiple defense traits. Fitness is determined by growth and survival during ontogeny. We determine optimal defense strategies for environments that differ in their resource abundance, predation risk, and defense effectiveness. We compare the results with results of simplified models where single defense traits are optimized. Our results indicate that selection acts in favor of integrated traits. The selective advantage of expressing multiple defense traits is most pronounced at intermediate environmental conditions. Optimizing single traits generally leads to a more pronounced response of the defense traits, which implies that studying single traits leads to an overestimation of their response to predation. Behavioral defense and morphological defense compensate for and augment each other depending on predator densities and the effectiveness of the defense mechanisms. In the presence of time constraints, the model shows peak investment into morphological and behavioral defense at intermediate resource levels.