The American Naturalist

A prominent developmental plasticity theory proposes that early life adversity accelerates life history trajectories so organisms can maximize fitness in challenging environments. Standard tests of this hypothesis rely on empirical predictions about observable life history variables (e.g., age at first birth), because the proposed internal processes cannot be directly measured. However, the observable proxies are themselves mechanically linked, and regressions that ignore this may conflate causal effects with mechanical relationships among proxies. Here, we develop theory that explicitly justifies some existing empirical tests but rejects others. We integrate an accounting model that incorporates age at first birth, interbirth intervals, and lifespan with an optimization model, to derive the mathematical form that tests of the hypothesis should take. We apply these tests to data from wild female baboons, using early life rainfall as an exogenous proxy for early adversity so that estimates can plausibly be interpreted causally. The accounting model explains >98% of the variation in lifetime reproductive success among females that reproduced. However, our theory-derived tests find no evidence for the reproductive acceleration hypothesis. Our study illustrates the value of formal theory for causal inference in developmental plasticity research, where intertwined measurable variables may be obscured by strictly verbal hypotheses.

Successional communities often recover slowly because progression stalls at persistent stages that resist replacement. Here, we show that resilience in such systems is frequently governed by a single bottleneck stage with the lowest effective exit rate. Using empirical transition ma-trices from intertidal and plant communities, we demonstrate that altering the bottleneck has a much larger effect on resilience than modifying any other stage. We then show that this bottle-neck principle emerges naturally from both Markov and continuous-time models of succession. Specifically that the slowest return to equilibrium is controlled primarily by the stage with the smallest effective exit rate, which also dominates the mean first-passage time to late succession. These results provide a simple biological interpretation of resilience in successional communities and suggest that management efforts are most effective when they target the stage that limits the pace of succession.

Understanding how populations persist in gradually deteriorating environments through evolution is a central question in ecology and evolutionary biology. Previous studies have primarily focused on identifying the critical rate of environmental change beyond which extinction is certain. However, the existence of a viable equilibrium when the rate is below the threshold does not guarantee that a population can survive the transient dynamics to reach it. Using a quantitative genetic model that explicitly incorporates feedback among population size, genetic variance, and mean trait evolution, we show that population persistence can exhibit bistability when the rate of environmental change is below the extinction threshold. Specifically, extinction still occurs if the initial population size and genetic variance fall below a critical level. The initial state also influences the eco-evolutionary dynamics, such that a temporary increase or decline in population size and/or genetic variance does not necessarily predict the ultimate fate of the population. Therefore, in addition to estimating the critical rate of environmental change for extinction, characterizing current population size, genetic variation, and the degree of maladaptation may improve predictions of extinction risk in deteriorating environments.

Floral plantings can either concentrate bees or export them to adjacent crops, yet the ecological conditions influencing these outcomes remain unclear. Here, we develop a mathematical model as proof of concept for our previous integrative hypothesis: concentrator and exporter outcomes can arise as alternative, context-dependent outcomes of the same underlying resource-selection process. Using bees as a model and focusing specifically on spillover from floral plantings to crops, we identified resource-specific thresholds separating concentration- and export-favoring conditions. Our model translates differences in relative patch attractiveness into context-dependent concentration and export outcomes and generates resource-specific, testable predictions about the conditions favoring pollinator movement into crops. In our simulations, the concentrator-exporter transition occurred at a lower flowering-intensity contrast than at pollen or nectar contrasts, which suggests that flowering intensity may provide an initial cue for bee movement, whereas nectar and pollen rewards refine or sustain bee responses once crops are perceived as attractive. Spillover thresholds differed among resource contrasts, whereas response steepness varied across bee-trait and community scenarios. Under the model's trait-sensitivity formulation, predicted spillover probability responded more strongly to flowering contrast for specialists than for generalists; colony size amplified this response, whereas bee richness dampened it. Together, these patterns show how flowering and resource contrasts interact with bee traits and community context to shape predicted spillover. Our results confirm that the concentrator and exporter hypotheses can be understood as context-dependent outcomes of the same ecological process rather than as mutually exclusive alternatives. Experimental tests of the predicted thresholds conducted in the field could reveal when and where floral plantings are most likely to promote bee spillover to crops, potentially supporting crop pollination.

Masting, characterized by highly variable, synchronized, and intermittent seed or fruit production, represents a common reproductive strategy among perennial plants and has profound ecological consequences. Resource provisioning and pollen limitation have long been viewed as central physiological mechanisms underlying this strategy, recent empirical evidence also highlights the role of weather cues in initiating and synchronizing reproductive effort. Drawing on mechanisms that drive periodicity in disease dynamics, this study proposes an alternative proximate mechanism for masting. We develop and analyze a stage-structured population growth model in which developmental delays create population-level cycles, and demographic stochasticity adds individual-level variation; together, yielding masting-like patterns. We compare the behaviour of this novel model with that of the widely used resource budget model and empirically observed patterns of masting in perennial plants. To quantify and compare model outputs and empirical observations, we employ three continuous metrics of masting that capture volatility, synchrony, and periodicity. Our study provides an alternative proximate mechanism for masting. Comparison of this novel mechanism and the established resource-budget model to empirical time-series reveals that both represent realistic yet distinct forms of masting reproduction. Together, these models provide a foundation for further exploration of the conditions under which this reproductive strategy can evolve. Beyond masting, our results highlight the general importance of life-history timing and demographic stochasticity in shaping population ecology.

Male and female animals often differ remarkably in their reproductive behaviours, typified by competing males and caring females. One influential explanation traces sex-role divergence to anisogamy: sex differences in gamete size. This explanation remains controversial, because existing models have not fully resolved how anisogamy leads to secondary sex-role divergence, and exceptions to typical patterns are empirically well-documented. Here, we develop mathematical models linking anisogamy to secondary sex-role evolution, showing that anisogamy drives sex-role divergence along contrasting evolutionary trajectories depending on ecological context. When the sexes differ only in gamete size, male-biased mating competition and offspring care evolve under scramble competition, whereas uncertain paternity shifts the population towards typical patterns. By contrast, anisogamy generally drives typical sex roles under contest competition, although sex-role reversal can emerge as an alternative stable state when care must be apportioned among offspring. Anisogamy can thus explain the striking diversity of sex differences across taxa.

The performance of any natural population in variable environments depends on contemporaneous changes in its vital rates (e.g., survival, reproduction) as well as legacies carried by its population structure. Yet whether the relative contribution of these two pathways can be predicted from life history remains unknown. Here, we use stochastic simulations of 1,986 matrix population models from 137 species to quantify the contribution of transient dynamics to variation in population growth rate, and test its associations with key life history traits. Longer generation times were associated with reductions in transient contributions, contrary to theoretical expectations. Greater stage-specific survival heterogeneities were associated with increases in transient contributions, whereas greater iteroparity was associated with decreases in plants but increases in animals. These associations were robust to body size, phylogenetic relationships, and vital-rate variability. Life history traits therefore provide a strong predictor for when population structure shapes population responses to environmental variability.

When ecological communities experience environmental change, continued coexistence may require rapid adaptation to avoid extinction, i.e., evolutionary rescue. This rescue can be inhibited by competition. Combining Lotka-Volterra and population genetic models, we investigate how both within- and between-species competition impact the probability of rescue. With a single species we derive closed-form approximations that quantify the negative impact of competition. We then use a two-species model to examine how the sweep of a rescue mutant in one species inhibits establishment of rescue mutants in another, a process we term survival interference. This interference is strongest when the stronger competitor begins recovering first, creating eco-evolutionary priority effects despite conditions permitting deterministic coexistence. Finally, considering larger competitive communities, we document how survival interference reduces the number of rescued species but weakens with species richness and unevenness. These results move us closer to predicting evolutionary rescue in ecological communities.

Demographic stochasticity is generally expected to contribute little to population variability when census abundance is large, because random demographic events are increasingly averaged across many individuals. This expectation, however, depends on how evenly individuals contribute to reproduction. In many natural populations, reproductive success is highly skewed, so that a large census population can coexist with a much smaller effective number of breeders (Nb). Although Nb is commonly used as a genetic measure of contemporary effective size, it also summarizes variation in reproductive contribution and may therefore contain information about demographic variability. Here, we develop a female-based age-structured theoretical framework linking Nb to temporal variability in mature population abundance, with N denoting the census number of mature females and Nb the effective number of female breeders. Recruitment variability arises from non-Poisson reproductive variation and environmental stochasticity, and its transmission to mature abundance is described by a life-history coefficient, {gamma}, determined by survival, maturation, and the contribution of overlapping cohorts. When the Poisson component of recruitment variance is negligible and Nb/N is sufficiently small, the coefficient of variation in mature abundance, CV[N], can be approximated from Nb, environmental variability, and {gamma}, with little additional information from census abundance. This approximation does not require specification of the functional form of the relationship between adult abundance and recruitment. Stochastic age-structured simulations closely reproduced the analytical prediction, even when additional demographic stochasticity in survival was included. Substantial fluctuations in mature abundance occurred at census sizes on the order of 105 when Nb was small, whereas overlapping cohorts buffered recruitment fluctuations. Because Nb can be estimated genetically from samples of a single cohort, the framework provides a direct link between genetic monitoring and population dynamics. More broadly, these results show that large census abundance alone does not guarantee weak demographic variability and highlight the potential of genetic data to inform expected population fluctuations when detailed demographic information is limited.

Understanding how species interactions, ecological drift, and immigration jointly shape community composition is a central goal of community ecology. These processes determine not only average community composition, but also how often different community states occur. Here, we ask how competition reshapes the neutral distribution of community composition generated by drift and immigration. We analyze a stochastic two-species competition model with immigration and derive the stationary distribution of relative species composition near neutrality. The stationary distribution shows when communities are usually balanced and when they are instead dominated by one species. Species dominance can become common even when the corresponding deterministic model predicts stable coexistence, particularly in smaller communities. Balanced and dominance states can also occur together, producing a trimodal distribution. Competitive asymmetry further biases the distribution toward the competitively favored species. Thus, the interplay between competition, ecological drift, and immigration determines not only how much community composition varies, but also which community states are most likely to be observed. Our results provide an analytical bridge between neutral and competition theory and a framework for interpreting variation in community composition.

Delayed germination is classically explained as a bet-hedging strategy against environmental variability: by withholding a fraction of seeds from germination, plants spread establishment risk across years that vary in temperature, precipitation, and other conditions governing seedling survival. Whether biotic interactions can generate analogous selective pressure has received comparatively little theoretical attention. Here we examine the evolution of germination timing in a host-pathogen model in which a saturating (Holling Type II) transmission function couples seed bank dynamics to epidemic cycles. The model produces three qualitatively distinct ecological regimes: a pathogen-free equilibrium, a stable endemic equilibrium, and an oscillatory endemic regime arising through a bifurcation, a transition from stable to oscillatory endemic dynamics. Using adaptive dynamics, namely invasion analysis, we show that the evolutionarily stable germination rate depends critically on which regime the resident population occupies. When pathogen dynamics settle to an equilibrium, selection favours ever-faster germination with no finite optimum, regardless of pathogen presence. When dynamics are limit cycles, periodic epidemic peaks create recurrent windows of high establishment mortality that function as biotic analogues of abiotic interactions (environmental), and selection drives the germination rate toward the bifurcation boundary. The evolutionary attractor thus coincides with an ecological bifurcation point. Trait substitution sequence simulations confirm convergence to this attractor, and multi-trait eco-evolutionary simulations provide evidence that the attractor is evolutionarily stable, consistent with a continuously stable strategy (CSS).These results extend classical bet-hedging theory to biotic drivers and suggest that pathogens capable of sustaining population cycles may be an underappreciated selective force on germination timing and, more broadly, on the pace of life-history evolution.

Haldane's principle relates equilibrium mutation load to deleterious mutational input rather than to selection strength. We study this balance in a homeostatically regulated, damage-structured population where mutation occurs during reproduction, repair restores individuals toward lower-damage states, and nonlinear demographic feedback maintains constant population size. An exact demographic identity shows that load at every time equals excess reproductive effort weighted by mean relative fecundity. Without repair, the equilibrium branch with positive pristine-class frequency is exactly solvable, and along it the load is exactly the mutation probability times the realized per-capita reproductive turnover rate; when the terminal cap is removed, this is precisely the realized deleterious input, for every mutation probability below one. For rare mutation it reduces to the mutation probability times the pristine turnover rate, with the local fitness contrast canceling at leading order. With a finite terminal class the branch instead reaches a closure-dependent boundary collision. Repair modifies the rare-mutation balance by partitioning first-order removal from the first damaged class between selection and restoration, multiplying the leading load by the selective share of that removal. An exact binary solution extends these results to finite mutation pressure: the unrepaired interior equilibrium collides nonhyperbolically with the fully damaged boundary and converges algebraically at the threshold, whereas any positive repair rate restores a unique interior equilibrium for positive mutation; at the no-repair threshold, its displacement from the boundary scales as the square root of the repair rate as repair vanishes. These results separate the familiar competing-transition structure of mutation--selection balance from the specifically homeostatic effects of turnover-dependent mutation input and nonlinear demographic feedback.

Rapid evolution allows populations to persist in environments where they would otherwise go extinct. This phenomenon, known as evolutionary rescue, is typically studied in the framework of biological evolution, yet adaptive traits can also arise and spread through cultural evolution. The present study developed a stochastic eco-evolutionary model to compare rescue probabilities through biological and cultural evolution. Transmission bias governed the rescue probability under cultural evolution by setting how readily a rare adaptive trait was copied. Conformity bias suppressed population persistence because a rare trait was the least likely to be copied. Content bias toward the adaptive trait enabled evolutionary rescue when social learning was rapid, but it typically yielded a lower rescue probability than biological evolution. Only anticonformity bias, together with a high social learning rate, exceeded the rescue probability of biological evolution by enabling the adaptive trait to be established more rapidly. These results demonstrate that transmission bias alters the demographic consequences of cultural evolution and highlight the importance of transmission processes in evolutionary rescue theory. Understanding how adaptive behaviours are socially transmitted may also improve predictions of animal population persistence and inform conservation efforts in rapidly changing environments.

Early-life phenotypes frequently predict adult phenotypes through developmental 'silver-spoon' carry-over effects, but how strongly and under what circumstances? Using 40 years of individual-based data from a great tit (Parus major) population, we used covariance reaction norms to understand how the natal-to-adult body mass association shifts across temperature, rainfall, and population density gradients during both life stages. We show that the natal-adult mass correlation is substantial (r {approx} 0.7) but strongly environment-dependent. Reaction norm shapes across climatic and density axes point to distinct mechanisms, including compensatory growth under benign adult conditions and density-dependent modulation of early-life differences. We further show that the conditions experienced in adulthood largely drive these patterns and determine whether early-life advantages are retained, even when explicitly tested within an environmental-matching paradigm. Decomposing the correlation using 38 generations of pedigree data revealed no evidence of gene-by-environment interactions. Instead, the observed phenotypic correlation reaction norms could be attributed almost entirely to environmentally-sensitive non-genetic individual differences. Overall, our findings show that climatic and demographic shifts can substantially reshape developmental carry-over without altering the genetic architecture tying body mass across life stages, with implications for how reliably early-life mass can predict individual quality and adult traits in wild animal populations.

Assortative mating for a trait under selection can increase the rate of adaptive evolution and limit introgression of detrimental alleles. We therefore hypothesized that assortative mating facilitated the rapid evolution of flowering phenology observed in the self-incompatible perennial Lythrum salicaria (purple loosestrife) as it invaded eastern North America. We characterized flowering schedules of 600 individuals representing 20 populations sampled along a latitudinal gradient of 10 degrees and grown in a common garden at mid-latitude. Consistent with our hypothesis, we found that flowering schedules were less synchronous in the mixed population of the common garden (s = 0.50) relative to the 20 locally adapted populations comprising it (s = 0.56 to 0.86), and flowering synchrony decreased towards higher latitudes of origin. Despite high synchrony, assortment potential ({rho}) by growth and phenology varied by population ({rho} = 0.03 to 0.61), but the predicted negative correlation between s and {rho} was masked by among-individual fitness variation in the common garden. We show how fitness variation and asynchrony associated with locally adapted phenology can reduce the fitness impacts of maladaptive gene flow and accelerate the rate of adaptive evolution during invasion.

Ecological stability and function emerge from the many and diverse types of interactions among species. Ecological networks represent the structure and strength of species interactions, but their study is often restricted to single interaction-types, likely due to an absence of models for plausibly (i.e., nonrandomly) structured 'multiplex networks' of multiple interaction types. Here, we present a general but mechanistic model that simulates multiplex networks using the different, but correlated, traits that determine different species interactions. We show that ecological stability varies systematically with these trait correlations by controlling the emergent complexity and positioning of strong interactions in the community. Our model provides a flexible but power tool to study multiplex networks under alternative trait-based hypotheses, offering new insights into the structure and stability of complex natural systems.

Shifts in predation and human harvest often coincide with changes in life history trait distributions in prey populations. These changes may arise via evolution or plasticity, and extrinsic environmental effects may affect such traits. This complexity prompts questions about how trait distributions are shaped by multiple factors' interactions. We hypothesized that food availability and climate affect both the magnitude, and mechanism (evolution vs. plasticity), by which traits change in response to harvest's intensity and size selectivity. We tested these hypotheses using individual-based bioenergetic population models allowing both plasticity and evolution. We exposed genetically diverse fish populations to gradients of productivity and stochasticity in food availability, crossed with gradients of selective or nonselective fishing mortality. Food availability shaped traits both plastically and evolutionarily, and modulated how harvesting influenced those responses. Food effects can suppress harvest impacts altogether, or obscure evolution's effects on phenotypes. However, when climatic factors shape food-driven changes by affecting both fish and their prey, either synergistic or antagonistic interactions can emerge between food variation and harvest in determining phenotype distributions. Our research suggests that understanding consumer-resource dynamics, and climatic processes shaping them, is essential to interpreting how harvest can shape traits relevant to population viability and fisheries sustainability.

Defended prey are often thought to rely on conspicuous warning signals to distinguish themselves from undefended prey, facilitating predator learning and avoidance. Yet many chemically defended organisms are inconspicuous and difficult to distinguish from palatable prey, raising a fundamental question: how do predators avoid defended prey when prey themselves provide little or no reliable signals of defense? We tested whether host plants can function as indirect indicators of prey defense using Carolina wrens (Thryothorus ludovicianus), chemically defended Eumaeus atala larvae, undefended Galleria mellonella larvae, and two distinct plant species. Defended and undefended prey were experimentally made to appear visually identical, forcing predators to rely on host-plant associations as the only available source of information. Wrens rapidly altered both search behavior and attack decisions according to plant identity. Mechanistic attack models incorporating predator discrimination between defended and undefended prey were strongly favored when plants were present, with defended prey experiencing substantially lower attack risk than undefended prey. When plants were removed, support for discrimination weakened and attacks on both prey types increased. Spatial autocorrelation of host plants further shaped predator behavior, with strongly clustered plants hosting defended prey receiving disproportionately fewer visits. Together, these results suggest host plants can function as ecologically meaningful cues of prey defense, influencing both predator search patterns and attack decisions. More broadly, our findings suggest warning systems may extend beyond prey phenotype alone, and that ecological context (including host-plant identity and spatial structure) may contribute to the evolution and maintenance of aposematism.

Understanding the limits of species distributions is a central objective of biogeography and macroecology and has become increasingly important as climate change drives rapid shifts in geographic ranges. Species range sizes follow a highly skewed frequency distribution, with most species occupying ranges orders of magnitude smaller than those of the most widespread species. Range sizes also exhibit pronounced geographic patterns, with small-ranged species concentrated near continental margins and other geographic boundaries. No universally accepted explanation has been proposed for these patterns. Here we present a simple geometric model showing that species range size patterns emerge from the random placement of dispersal barriers within continental domains. The model predicts both the observed frequency distribution and the spatial distribution of range sizes across amphibians, birds, and mammals. It therefore provides a first-order explanation for global patterns of species rarity and can be refined by incorporating elevational barriers and spatial variation in species richness. Our findings suggest that species range size is constrained by the geometry of dispersal barriers and the geographic domain, with proximity to domain boundaries acting as a primary determinant of species rarity. These results have important implications for understanding species' evolutionary potential and vulnerability to extinction.

Environmental variability influences the evolution of phenotypic plasticity and the ecological interactions among species in communities, but it is unclear how these processes interact to affect ecological systems across scales. We investigate models describing how plasticity evolves in competitive communities exposed to seasonal variation in abiotic conditions. We conducted eco-evolutionary analyses to identify communities of coexisting species with evolutionarily stable plasticity traits. These analyses revealed that the presence of interspecific competitors constrained the evolution of plasticity in some species, which instead evolved to be specialists. Plasticity often impaired species coexistence by allowing individual species to control more niche space. Communities containing plastic species were usually less species-rich but more productive and less variable. Similar results were obtained when plasticity rate was evolutionarily labile, but plasticity rate altered the patterning of temporal niche partitioning. This work shows how plasticity and competition combine to shape ecological and trait responses to environmental variability.