Ronald Lee

The long human lifespan enables long run forecasts of population size and age distribution. New methods include biodemographic research on upper limits to life expectancy and incorporation of early experiences affecting later life mortality such as smoking, obesity, and childhood health shocks. Some fertility forecasts incorporate education and quantum‐tempo insights. Statistical time series and Bayesian methods generate probabilistic forecasts. Yet recent decades have brought surprising changes in the economy, natural environment, and vital rates. In these changing circumstances we need new methods and the increasing use of probabilistic models and Bayesian methods incorporating outside information. The increasing use of microsimulation combined with aggregate forecasting methods is a very promising development enabling more detailed and heterogeneous forecasts. Some new uses of stochastic forecasts are interesting in themselves. Probabilistic mortality forecasts are used in finance and insurance, and a new Longevity Swap industry has been built on them. Random sample paths used to generate stochastic population forecasts can stress‐test public pension designs for fiscal stability and intergenerational equity. Population forecasting a few decades ago was a dull backwater of demographic research, but now it is increasingly important and is full of intellectual and technical challenges.

Life history theory has focused on the life cycle tradeoffs faced by individuals who are constrained by the energy they can forage for themselves at each age. However, humans are deeply social and adults transfer food to children for many years, freeing them from this energy constraint but also bringing the risk that parental death could entail the death of all dependent offspring. Multiple simultaneously dependent offspring also bring a family life cycle squeeze in which dependency ratio doubles. Food sharing and alloparenting ameliorate both problems, providing life insurance and smoothing the life cycle squeeze, while permitting humans to rely on food resources that would be too uncertain for isolated individuals. Food sharing and intergenerational transfers in turn affect the way natural selection shapes life histories. We use microsimulations to study evolution of life histories. Births inherit the mother’s genome subject to mutations. Individuals live under different social arrangements and forage with productivity depending on population density. Natural selection on life histories occurs. We examine the way the size and relatedness of sharing group arrangements alter the evolution of life history traits through mutation and natural selection. We consider which social arrangements, with their corresponding evolved life histories, are most successful in a group competition where all face the same density constraint. There is a tradeoff between costs and benefits of sharing. We find that intermediate levels are most successful, unless childhood conditions strongly influence later life productivity.

Human evolutionary demography combines research in evolutionary biology with the study of human demographic patterns and behaviors. Evolutionary biology and demography share many conceptual features that give rise to a natural complementarity, such as a focus on the population as a unit of study and emphasis on aggregate processes that have implications for individuals. They also have distinct strengths that further this natural partnership. Evolutionary approaches are often top-down and theory driven, while demographic ones are more often bottom-up and driven by data and robust estimation procedures. We suggest that human evolutionary demography reflects these areas of overlap and complementary strengths while emphasizing at least two main objectives: understanding the role of evolutionary processes in shaping population-level demographic patterns (e.g., the evolution of age-specific patterns of mortality or fertility), and using an evolutionary approach to understand contemporary variation between individuals in demographic patterns (e.g., how and why does fertility respond to environmental influences, and vary between and within populations?). Evolutionary demography is also inherently interdisciplinary. Interdisciplinary approaches are vital to furthering our understanding of the complex processes underlying demographic patterns, in part because such approaches can be a disruptive force challenging researchers to question assumptions and see the world differently. The papers in this volume demonstrate that integration of demography and evolutionary sciences strengthens both. This recognition by an ever-growing number of researchers has resulted in such a successful body of research that we are now able to showcase this field with this collection of papers, illustrating the vibrancy and diversity of research in human evolutionary demography.

A complete understanding of demographic patterns and behaviours is not possible without including the role of evolutionary processes. Many challenges in the social sciences, and in demography in particular, can be more readily met if they include the rich collection of perspectives, models, tools, and theories that evolutionary sciences can provide. Perhaps unexpectedly, the benefits of this inclusion can be indirect, as many benefits of an evolutionary perspective may take the form of a new way of approaching an old problem that leads to insights independent of any goal related to isolating the role of natural selection or adaptation. In other cases, the role of adaptation may have been under-appreciated and can lead to a different understanding of the mechanisms involved. To help human evolutionary demography improve going forward, we offer two general recommendations. One is improving the integration of contemporary developments in evolutionary thought about the role of culture and environment, such as dual-inheritance theory, epigenetics, and the role of social learning and cultural transmission. Many of these developments reflect an increasingly sophisticated understanding of cultural processes in and understanding of core concepts like fitness and heritability. The role of culture may be a productive point of contact between the social sciences and evolutionary social sciences given shared interests in this area. Second is a call to re-invigorate evolutionary demography with some of the classical ideas that come from life history theory and population ecology, such as the use of energy and resource budgets to structure tradeoffs, a focus on the role of ecological factors like density and resources, and the use of formal mathematical models.

Behind the steady march of progress toward longer life expectancy in many low‐mortality countries, there have been setbacks even before the Covid‐19 pandemic. In this paper, we use an exploratory approach to describe the temporal structure, age patterns, and geographic aspects of life expectancy reversals. We find that drops in life expectancy are often followed by larger than average improvements, which tells us that most reversals are transitory with little long‐term influence. The age structure of mortality decline when life expectancy falls is tilted toward older ages, a pattern that is quite different from the general pattern of mortality improvement. Geographic analysis shows that mortality reversals are correlated across neighboring countries like Italy and France, or Canada and the United States. These findings are consistent with contagious disease and weather being important causes of life expectancy reversals. We conclude with a discussion of implications for formal modeling and forecasting of mortality to accommodate these patterns that violate some standard assumptions.

The U.S. Department of Energy's Office of Scientific and Technical Information

Age patterns of female reproduction vary widely among iteroparous animal species with determinate growth. Often fertility declines with age, but in other cases, it may be flat or rise across age. Sometimes fertility ceases altogether, leaving a substantial post-reproductive life span. In this article, we discuss theories that may provide some insights into how these diverse patterns might evolve. We present a simple optimal life history model and consider circumstances in which fertility might rise or fall with age. In our model, without assuming that costs per birth rise with age, that foraging efficiency declines, or that net intergenerational transfers increase, we find that optimal fertility would tend to rise rather than decline. This happens because less energy would be allocated to survival at older ages, leaving more to allocate to fertility. In our analysis, optimal fertility could decline at older ages when an older female makes heavy net intergenerational transfers to multiple offspring or grandoffspring, reducing resources for her own reproduction. This pattern is more likely to evolve when costs of fertility at older ages are higher, when costs of reducing juvenile mortality are low, and when the level of juvenile mortality is high. We also derive conditions for the evolution of menopause, for determinate growth, and for juvenile mortality that declines with age. The optimal life history can exhibit a variety of age patterns of fertility, rising, flat, or falling, depending on the constraints and opportunities faced.

Evolutionary success requires both production (acquisition of food, protection and warmth) and reproduction. We suggest that both may increase disproportionately as group size grows, reflecting "increasing returns' or "group augmentation benefits', raising fitness in groups that cooperate in production and limit reproduction to one or a few high fertility females supported by non-reproductives, with high reproductive skew. In our optimisation theory both Allee effects (when individual fitness increases with group size or density) and reproductive skew arise when increasing returns determine optimal group size and proportion of reproductive females. Depending on which of food or maternal time is more important for reproduction, evolutionary trajectories of lineages may (1) reach a boundary constraint where only one female reproduces in a period (as with African wild dogs) or (2) reach a boundary where all females reproduce during their lifetimes but only during an early life stage (human menopause) or a late life stage (birds with non-dispersing helpers), where stage length optimises the proportion of females that is reproductive at any time or (3) reach the intersection of these boundary constraints where a single reproductive female is fully specialised in reproduction (as with eusocial insects). We end with some testable hypotheses.

The U.S. Department of Energy's Office of Scientific and Technical Information