We Happy Few: Using Structured Population Models to Identify the Decisive Events in the Lives of Exceptional Individuals

Sex-specific competitive social feedback amplifies the role of early life contingency in male mice

Contingency (or 'luck') in early life plays an important role in shaping individuals' development. When individuals live within larger societies, social experiences may cause the importance of early contingencies to be magnified or dampened. Here we test the hypothesis that competition magnifies the importance of early contingency in a sex-specific manner by comparing the developmental trajectories of genetically identical, free-living mice who either experienced high levels of territorial competition (males) or did not (females). We show that male territoriality results in a competitive feedback loop that magnifies the importance of early contingency and pushes individuals onto divergent, self-reinforcing life trajectories, while the same process appears absent in females. Our results indicate that the strength of sexual selection may be self-limiting, as within-sex competition increases the importance of early life contingency, thereby reducing the ability of selection to lead to evolution. They also demonstrate the potential for contingency to lead to dramatic differences in life outcomes, even in the absence of any underlying differences in ability ('merit').

The natural history of luck: A synthesis study of structured population models

Chance pervades life. In turn, life histories are described by probabilities (e.g. survival and breeding) and averages across individuals (e.g. mean growth rate and age at maturity). In this study, we explored patterns of luck in lifetime outcomes by analysing structured population models for a wide array of plant and animal species. We calculated four response variables: variance and skewness in both lifespan and lifetime reproductive output (LRO), and partitioned them into contributions from different forms of luck. We examined relationships among response variables and a variety of life history traits. We found that variance in lifespan and variance in LRO were positively correlated across taxa, but that variance and skewness were negatively correlated for both lifespan and LRO. The most important life history trait was longevity, which shaped variance and skew in LRO through its effects on variance in lifespan. We found that luck in survival, growth, and fecundity all contributed to variance in LRO, but skew in LRO was overwhelmingly due to survival luck. Rapidly growing populations have larger variances in LRO and lifespan than shrinking populations. Our results indicate that luck-induced genetic drift may be most severe in recovering populations of species with long mature lifespan and high iteroparity.

Adaption, neutrality and life-course diversity

Heterogeneity among individuals in fitness components is what selection acts upon. Evolutionary theories predict that selection in constant environments acts against such heterogeneity. But observations reveal substantial non-genetic and also non-environmental variability in phenotypes. Here, we examine whether there is a relationship between selection pressure and phenotypic variability by analysing structured population models based on data from a large and diverse set of species. Our findings suggest that non-genetic, non-environmental variation is in general neither truly neutral, selected for, nor selected against. We find much variations among species and populations within species, with mean patterns suggesting nearly neutral evolution of life-course variability. Populations that show greater diversity of life courses do not show, in general, increased or decreased population growth rates. Our analysis suggests we are only at the beginning of understanding the evolution and maintenance of non-genetic non-environmental variation.

When the going gets tough, the tough get going: Effect of extreme climate on an Antarctic seabird's life history

Individuals differ in many ways. Most produce few offspring; a handful produce many. Some die early; others live to old age. It is tempting to attribute these differences in outcomes to differences in individual traits, and thus in the demographic rates experienced. However, there is more to individual variation than meets the eye of the biologist. Even among individuals sharing identical traits, life history outcomes (life expectancy and lifetime reproduction) will vary due to individual stochasticity, that is to chance. Quantifying the contributions of heterogeneity and chance is essential to understand natural variability. Interindividual differences vary across environmental conditions, hence heterogeneity and stochasticity depend on environmental conditions. We show that favourable conditions increase the contributions of individual stochasticity, and reduce the contributions of heterogeneity, to variance in demographic outcomes in a seabird population. The opposite is true under poor conditions. This result has important consequence for understanding the ecology and evolution of life history strategies.

Time and Chance: Using Age Partitioning to Understand How Luck Drives Variation in Reproductive Success

AbstractOver the course of individual lifetimes, luck usually explains a large fraction of the between-individual variation in life span or lifetime reproductive output (LRO) within a population, while variation in individual traits or "quality" explains much less. To understand how, where in the life cycle, and through which demographic processes luck trumps trait variation, we show how to partition by age the contributions of luck and trait variation to LRO variance and how to quantify three distinct components of luck. We apply these tools to several empirical case studies. We find that luck swamps effects of trait variation at all ages, primarily because of randomness in individual state dynamics ("state trajectory luck"). Luck early in life is most important. Very early state trajectory luck generally determines whether an individual ever breeds, likely by ensuring that they are not dead or doomed quickly. Less early luck drives variation in success among those breeding at least once. Consequently, the importance of luck often has a sharp peak early in life or it has two peaks. We suggest that ages or stages where the importance of luck peaks are potential targets for interventions to benefit a population of concern, different from those identified by eigenvalue elasticity analysis.

Warming and shifting phenology accelerate an invasive plant life cycle

Numerous studies have documented changes in the seasonal timing of organisms' growth and reproduction in response to climate warming. These changes correlate with documented changes in species' abundance, but mechanisms linking these trends remain elusive. We investigated the joint demographic effects of advanced reproductive phenology and warming on a globally invasive plant (Carduus nutans) in a field experiment, documenting a substantial shift toward completion of the life cycle at younger ages. Demographic modeling projected 71% of warmed individuals flower as annuals, compared to 61% under current conditions. As this species only reproduces once, this represents a major acceleration of the life cycle. We project a 15% increase in this invader's population growth rate. We show that rising temperatures accelerate this invasive species' population growth by increasing the average size of reproducing individuals; increasing the proportion of individuals that survive to reproduce; and increasing the fraction that reproduce as annuals. Major increases in population growth in this, and potentially many other, invasive species will threaten food security and require careful planning to avoid significant environmental and economic impacts.

Inferring forest fate from demographic data: from vital rates to population dynamic models

As population-level patterns of interest in forests emerge from individual vital rates, modelling forest dynamics requires making the link between the scales at which data are collected (individual stems) and the scales at which questions are asked (e.g. populations and communities). Structured population models (e.g. integral projection models (IPMs)) are useful tools for linking vital rates to population dynamics. However, the application of such models to forest trees remains challenging owing to features of tree life cycles, such as slow growth, long lifespan and lack of data on crucial ontogenic stages. We developed a survival model that accounts for size-dependent mortality and a growth model that characterizes individual heterogeneity. We integrated vital rate models into two types of population model; an analytically tractable form of IPM and an individual-based model (IBM) that is applied with stochastic simulations. We calculated longevities, passage times to, and occupancy time in, different life cycle stages, important metrics for understanding how demographic rates translate into patterns of forest turnover and carbon residence times. Here, we illustrate the methods for three tropical forest species with varying life-forms. Population dynamics from IPMs and IBMs matched a 34 year time series of data (albeit a snapshot of the life cycle for canopy trees) and highlight differences in life-history strategies between species. Specifically, the greater variation in growth rates within the two canopy species suggests an ability to respond to available resources, which in turn manifests as faster passage times and greater occupancy times in larger size classes. The framework presented here offers a novel and accessible approach to modelling the population dynamics of forest trees.

The Snail's Charm

In 2017, The American Naturalist celebrated its 150th anniversary. It was founded as a journal of natural history, yet it developed into an important vehicle of the evolutionary synthesis. During the early years of the journal and through much of the twentieth century, evolutionary theory was developed to explain the history of nature before humankind existed to alter it-when time was expansive and uncommon events, though rare, were frequent enough to effect evolutionary change. Today, with the influence of human activity, dispersal patterns are fundamentally altered, genetic variation is locally limiting in small and fragmented populations, and environments are changing so rapidly that time itself seems limited. How can we use this theory, which was built to explain the past and which depends on an excess of chances and time, to address the challenges of the present and the future when chances are fewer and time seems so short? And does the habit of naturalists to observe, describe, and cultivate a fascination with nature have a place in contemporary science?

Explaining long-term inter-individual growth variation in plant populations: persistence of abiotic factors matters

An unanswered question in ecology is whether the environmental factors driving short-term performance also determine the often observed long-term performance differences among individuals. Here, we analyze the extent to which temporal persistence of spatial heterogeneity in environmental factors can contribute to long-term inter-individual variation in stem length growth. For a natural population of a long-lived understorey palm, we first quantified the effect of several environmental factors on stem length growth and survival. We then performed individual-based simulations of growth trajectories, in which we varied, for two environmental factors: (1) the strength of the effect on stem length growth and (2) the temporal persistence. Short-term variation in stem length growth was strongly driven by light availability. Auto-correlation in light availability and soil pH increased simulated variation in stem length growth among 20-year-old palms to levels similar to the observed variation. Analyses in which we varied both the strength of the effect on stem length growth and the temporal persistence of the environmental factors revealed that a large fraction of observed long-term growth differences can be explained, as long as one of these effects is strong. This implies that environmental factors that are relatively unimportant for short-term performance can still drive long-term performance differences when the environmental variation is sufficiently persistent over time.