Advancing methods for the biodemography of aging within social contexts.

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.

Hurricanes affect diversification among individual life courses of a primate population.

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.

Quantifying the effect of genetic, environmental and individual demographic stochastic variability for population dynamics in Plantago lanceolata.

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.

Demographic consequences of changing body size in a terrestrial salamander.

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.

Hurricane-induced demographic changes in a non-human primate population.

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.

Drivers of diversity in individual life courses: Sensitivity of the population entropy of a Markov chain.

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.

Parallel Progress in Perceived Age and Life Expectancy.

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.

Ecological drivers of jellyfish blooms - The complex life history of a 'well-known' medusa (Aurelia aurita).

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.

The AgeGuess database, an open online resource on chronological and perceived ages of people aged 5-100.

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.

Adaptive phenotypic plasticity for life-history and less fitness-related traits.

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.

Data gaps and opportunities for comparative and conservation biology.

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.

Two stochastic processes shape diverse senescence patterns in a single-cell organism.

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.

Drivers of Diversification in Individual Life Courses.

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.

Generation time, net reproductive rate, and growth in stage-age-structured populations.

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.

Evolutionary change in continuous reaction norms.

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.

Trading stages: life expectancies in structured populations.

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.

Static and dynamic expression of life history traits in the Northern Fulmar (Fulmarus glacialis).

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.

Dynamic heterogeneity and life histories.

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.

Dynamic heterogeneity and life history variability in the kittiwake.

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.