The American Naturalist

Despite the ecological importance of ungulate migrations, we lack a complete understanding of why some ungulates migrate and others do not. Though progress has been made towards understanding differences across species and between populations, migratory behavior varies even within populations: in many populations, some individuals remain behind as residents (partial migration). Theoretical population-level work has suggested that these different migratory tactics can coexist, but such approaches stop short of providing insights into how individuals make the decision to stay or go each year. Using long-term data from three ungulate populations, we find that individuals probabilities of migrating are highly variable across years, which points to a non-trivial context-dependent decision-making process, whose underlying mechanisms must be probed via individual-level modeling. Drawing on existing knowledge, we propose a decision-making model of ungulate migration onset wherein individuals probabilistically decide to start migrating based on the local intensity of environmental and/or social cues. Residents arise as a robust collective organization phenomenon in our model. At sufficiently large population sizes, the number of residents is invariant with total population size, consistent with empirical patterns. Instead, resident numbers are influenced by the severity of the bad season, by relevant character differences among individuals, and by how individuals contribute and respond to environmental and/or social cues; for instance, when social cues contribute to decision-making in addition to environmental ones, fewer residents result, and migration is more likely to be complete. Overall, our model provides a potential mechanistic explanation for how residents might emerge within migratory ungulate populations.

Hosts defend themselves against parasites through resistance (reducing parasite burden) and tolerance (reducing the fitness cost of infection without affecting parasites). This distinction has important evolutionary implications: resistance is predicted to maintain polymorphism while tolerance tends to fix, and only resistance is expected to provoke parasite counter-adaptation. The reaction-norm framework, which infers tolerance from the slope of host fitness regressed on parasite burden, assumes that a shallow slope reflects parasite-independent host protection. We test this assumption using a within-host model in two variants: microparasites (Model 1, with within-host replication) and macroparasites (Model 2, without). Sublethal immunity impairs the host-exploitation rate of the parasite, reducing both growth and per-parasite virulence without killing them. We show that this generates systematic slope differences among host genotypes that the framework interprets as variation in tolerance. Furthermore, the ranking of slopes across genotypes reverses between linear and sigmoidal damage functions: under linear damage, the strongest immune responder appears most tolerant; under sigmoidal damage, the weakest responder does. Decomposition of the damage reduction shows that virulence reduction accounts for the majority of the effect across both model variants. Thus, the reaction-norm slope cannot determine whether host fitness is maintained by parasite-independent tissue protection or by sublethal impairment of parasites.

Reproductive success requires allocating effort across lifespan in a manner that balances the risk of early mortality against the benefit of higher fecundity or parental expertise that increase with body size or age. Here we report a cross-taxonomic analysis of reproductive schedules in plants, animals, and humans, showing that peak reproductive effort consistently occurs at approximately 1/e (~37%) of species-specific maximum lifespan. The pattern is robust across major phylogenetic groups and independent of absolute lifespan. This convergence is both logically and numerically consistent with the optimal stopping fraction (1/e), which maximizes the probability of selecting a superior option under uncertainty by delaying commitment until 1/e of the available options have been examined. By integrating population dynamics and empirical data with a formal decision-theoretic model, our results suggest a striking previously unrecognized quantitative regularity linking lifespan and reproductive timing. These findings provide a unifying perspective on life-history evolution and suggest that complex biological scheduling strategies are governed by probabilistic principles.

Empirical studies have demonstrated that mutation rates may change with individual condition, such as in the case of stress-induced mutagenesis. This has led to the hypothesis that condition-dependent (or "plastic") mutation rates could be selectively favoured, as the increased production of new mutants in times of maladaptation enhances evolvability, the ability to undergo adaptive evolution. However, while empirical evidence for condition-dependent mutation rates is accumulating, theoretical models studying their evolution are lacking. Here, we employ an individual-based simulation approach to examine the evolution of condition-dependent mutation rates in a changing environment. We find that condition-dependent mutation rates consistently evolve when the environment changes at an intermediate pace. Furthermore, populations with condition-dependent mutation rates are substantially better adapted to their (changing) environment. Finally, the evolutionary dynamics of condition-dependent mutation rates are both accelerated and destabilised when the mutation rate is self-referential (i.e., when mutator loci affect their own mutation rate). We conclude that condition-dependent mutation rates (and thus evolvability) can readily evolve in changing environments. Significance statementMutation provides the raw material for evolution. Mutation rates thus tune evolvability, the ability to undergo adaptive evolution: if mutation rates are too low, evolution is impeded; if mutation rates are too high, adaptive traits cannot be maintained. Using a theoretical model, we explore the evolution of plastic mutation rates that systematically depend on the condition of the organism and its environment. An example is stress-induced mutagenesis in bacteria, which is implicated in the evolution of antibiotic resistance. We show that plastic mutation rates readily evolve, providing "well-timed" variation specifically when organisms are poorly adapted. Such plastic mutation rates thus facilitate better adaptation to changing environments, and their evolution provides an example of evolvability itself evolving.

Many proposed mechanisms for the evolution of cooperation among unrelated individuals rely on relatively demanding cognitive abilities that are not widespread across taxa. In contrast, individual heterogeneity is a pervasive feature of animal groups, encompassing differences in personality as well as physical and cognitive traits. Such heterogeneity can promote the evolution of cooperation, yet its role has received comparatively little attention, particularly as a source of variation giving rise to social organization such as leadership. A specific form of leadership can emerge under unstable environmental conditions, when some individuals become better suited than others to initiate action and influence the behavior of their peers. Unlike fixed dominance hierarchies, emergent leadership can rapidly adjust to changing environmental conditions, thereby reshaping group organization. Because it does not require the maintenance of stable hierarchies, this form of leadership can arise even in species that do not have the cognitive capabilities to sustain complex social structures. In this work, we investigate the combined effects of individual heterogeneity and emergent leadership on the evolution of cooperation using an evolutionary game-theoretic model in which individuals may assume the roles of leaders or followers according to their strength, representing individual differences in suitability to prevailing environmental conditions. We examine different levels of population heterogeneity together with increasingly complex strategy sets requiring progressively greater informational requirements, allowing individuals to condition cooperation on their own strength, leadership role, or both. Our results show that the interplay between leadership and heterogeneity promotes the evolution of cooperation, particularly when only a small fraction of individuals act as leaders. Under these circumstances, cooperation evolves even when individuals employ the simplest possible strategies. Under harsher ecological conditions, cooperation can be sustained by more sophisticated strategies, specifically by conditional strategies that prescribe cooperation when individuals are strong or leading and defect when acting independently. Author summaryIn this study, we propose that emergent leadership mediated by individual diversity can boost the evolution of cooperation in animal groups. Building on growing evidence on the heterogeneity of animal capabilities and personalities, we focus on the fleeting leadership that emerges in animal groups when facing rapidly changing environmental conditions. We suggest that this type of leadership that emerges from individual differences in strength--a generic quality encompassing those characteristics that make an individual more fit to lead in a given situation--does not require complex cognitive capabilities from the animals and represents a valid alternative to more demanding strategies proposed in the past to explain the evolution of cooperation. Using an evolutionary game theory model, we show that if a population includes a few strong players, these can become influential leaders and guide the actions of their peers to achieve cooperation. Although the naive strategy of always cooperating is sufficient for cooperation to evolve, the introduction of more complex strategies leads players to cooperate only when they are more likely to be recognized as influential leaders. These strategies are more effective in promoting cooperation under unfavorable ecological conditions and are also more robust against exploitation by defectors.

Observed group sizes rarely match the size that would maximize what each member gets from belonging. We propose a two-part theory in which group size is regulated by two related conflicts: insider-outsider conflict over admission, and within-group conflict as crowding, competition, and social tensions intensify with size. Three strategies are available: admission, exclusion, and fission. The first part shows that even when exclusion is unavailable, fission dynamics alone drive group size away from the optimum in both directions, with the pattern set by how prospective joiners encounter groups and by the geometry of fission. When joiners compare groups across a shared landscape and fission is asymmetric, the standing distribution is bimodal: supra-optimal large groups coexisting with a sub-optimal mode of small groups, the pattern characteristic of fission-fusion societies. The second part promotes exclusion and fission to active decisions: incumbents weigh the per-capita cost of accommodating entry ({beta}) against the costs of coordinated exclusion (c +{gamma} N*) and fissioning (F). A single inequality, {beta} > c +{gamma} N*, partitions populations into two regimes: where it holds, exclusion is viable and groups lock at the optimum size; where it fails, groups grow past the optimum and cycle through recurrent fission. Modal group size, fission frequency, and exclusion behavior together identify which regime governs a population -- a set of predictions applicable across fishes, social insects, birds, and mammals including primates and human foragers.

If an individuals niche is determined by its genotype, then competition for limiting resources should be most intense among individuals of the same genotype. Theory predicts this will act to maintain genetic variation, but whether this mechanism operates under natural conditions is unclear. Using long-term observations of a population of free-living Trinidadian guppies, we asked (i) whether competition was strongest between kin, and (ii) whether this process maintained genetic variation. Competition between kin was 1.5-1.8 times stronger than that between non-kin. This contributed to balancing selection: after [~]10 generations, variation was 29% higher than expected under drift. Our results show that relatedness can play a major role in structuring ecological competition, with broader consequences for theories of inclusive fitness. One-sentence summaryHeritable variation is maintained due to resource competition being more intense among kin.

Under complex perturbation regimes, biodiversity dynamics show temporal variability in species and community abundance around long-term population trends. Many species indeed show long-term declines while other species increase, putting natural communities far from stationary regimes, while variability is often studied near equilibrium. We contribute to bridging this gap by investigating population and community variability during long-term trends caused by press perturbations in stochastic models of population dynamics. By estimating the deterministic changes in mean and variance during the transient regime, we show that population variability deviates from stationary expectations. Moreover, the deviation strongly depends on the sign of the population trends: increases generate excesses of variability while declines generate deficits. Scaling up to community variability, we propose a decomposition of community variability deviation, allowing to highlight that community variability in the transient regime depends on how the press perturbation is distributed within species relative abundances and growth rates. These results challenge the equilibrium assumption and open new perspectives for the study of the variability of ecological systems under multiple perturbation types.

The number of chromosome sets per nucleus is a fundamental trait, but why this number is nearly always two for multicellular eukaryotes remains unclear. Chromosomes are made of nucleic acids, which possess abundant phosphorus (P). Therefore, producing new chromosomes, as well as generating new cells and organismal growth, demands substantial phosphorus. Yet, because P is often limiting in nature, P availability could influence the prevalence of diploidy versus polyploidy. Here, we compare growth rates of diploid and triploid Potamopyrgus antipodarum, a freshwater snail, relative to P availability. Because diploid P. antipodarum are obligately sexual while obligately asexual individuals are polyploid, costs associated with sensitivity to P limitation in polyploids could also help explain the maintenance of sexual P. antipodarum. We raised juvenile diploid and triploid snails on either P-adequate or P-deficient diets and found that independent of P availability, juvenile triploid asexual snails grew faster and harbored higher P content as adults than sexual diploid conspecifics. Together, these results suggest life-history advantages of polyploidy or asexual reproduction that exacerbate rather than ameliorate the cost of sex. These outcomes suggest that P availability is unlikely to be a main driver of ploidy polymorphism or the maintenance of sex in P. antipodarum.

Evolutionary game theory and ecological coexistence theory both seek to predict the outcome of competition between biological entities, be they strategies or species, but the two fields have relied on largely separate approaches. Replicator equations provide a foundation for analyzing strategy competition, yet they do not explicitly separate the mechanisms that stabilize competition from those that equalize fitness differences between strategies. Here, we extend modern coexistence theory from community ecology to develop strategic coexistence theory (SCT), a framework for quantifying strategic niche and fitness differences between competing strategies. SCT recovers the classic classification of two-strategy games, distinguishing competitive exclusion, coexistence, and priority effects within a shared niche-fitness difference space. Applying SCT to five mechanisms for the evolution of cooperation further reveals that these mechanisms promote cooperation through distinct dynamical routes: kin selection, network reciprocity, and group selection primarily reduce fitness differences, whereas direct and indirect reciprocity destabilize competition and generate priority effects. Finally, applying SCT to microbial public-goods game shows that nonlinear microbial growth can both stabilize and equalize competition between cooperators and defectors, allowing coexistence. Together, these results show that SCT provides a complementary framework for comparing evolutionary games and teasing apart the coexistence mechanisms underlying strategy competition.

Climate-driven disease forecasts typically assess whether environmental conditions favor pathogen growth, yet epidemic spread depends critically on how physiological processes within infected hosts shape transmission over time. This distinction is particularly consequential for vector-borne plant diseases, where vectors acquire infection from hosts whose pathogen load, symptom severity, and recovery are themselves temperature-dependent. Here, we develop a mechanistic epidemic framework that couples temperature-driven within-host pathogen dynamics to vector-mediated transmission. Infected hosts progress through ordered infection stages with stage-specific infectiousness, while transitions among stages-both progression and regression-are governed by thermal effects on pathogen accumulation and decay. We parameterize the model using experimental data for Pierce's disease of grapevine, caused by Xylella fastidiosa, and analyze epidemic invasion under constant, seasonal, stochastic, and empirical temperature regimes. We show that temperature affects invasion not only by altering pathogen growth rates but also by reshaping the time hosts spend in transmissible infection stages. This generates a slow-growth paradox: temperatures that maximize within-host pathogen growth need not maximize epidemic spread, because rapid progression shortens the effective transmission window, whereas mildly suboptimal temperatures can prolong infectiousness and sustain larger epidemics. Conversely, cold conditions can suppress invasion by either halting progression or inducing regression and recovery. Analytical expressions for the basic reproduction number under constant and seasonal forcing capture these mechanisms and predict final epidemic size across diverse climatic regimes. Short-term temperature variability has its strongest effects near thermal thresholds, and empirical temperature series from invaded regions generate markedly different epidemic trajectories despite similar invasion suitability. These results show that ignoring the coupling between within-host physiology and transmission can qualitatively mislead predictions of plant disease dynamics under climate change, misidentifying the thermal regimes that pose the greatest epidemic risk.

Understanding how social complexity responds to environmental variation remains a longstanding challenge in evolutionary biology. Here, we investigated the drivers of social complexity using intraspecific social variation across seven locations of the obligatory shell-brooding cichlid Neolamprologus meeli in Lake Tanganyika. We quantified the number of subordinate individuals per female territory and examined the effects of predation risk, shell availability, and their interaction. Social complexity increased with shell availability under high predation risk but showed little association under low predation risk. A field manipulative-experiment further demonstrated that increasing shell availability led to higher juvenile retention, indicating a causal effect of territory quality. In addition, removal of subordinates reduced shell availability, suggesting the feedback between group size and territory maintenance. We also assessed genetic population structure based on nuclear SNPs obtained by MIG-seq and found only weak genetic differentiation among localities, suggesting that the observed social variation is unlikely to simply reflect strong genetic subdivision. Together, these results show that predation risk promotes group living, whereas nesting resource availability constrains its extent. Our study highlights that social complexity emerges from the interaction between macro- and micro-ecological factors, providing a mechanistic understanding of the evolution of social complexity and philopatry.

Sexual conflict has been hypothesized as a driver of speciation, though its effects are likely heterogeneous across phylogenies and between sexes. The semi-aquatic bug, which inhabits water surfaces across diverse aquatic environments, has long served as a model for studying sexual conflict. While previous studies have focused on rapid antagonistic coevolution and the genetic basis of sexually antagonistic traits, the macroevolutionary consequences of asymmetrical sexual conflict--particularly male-dominated grasping traits versus female resistance--remain largely unexplored. Within the subgenus Pseudovelia, males exhibit pronounced phenotypic diversification in grasping structures, whereas females show modest, clade-specific resistance traits, suggesting male-biased asymmetric conflict. This system presents a valuable opportunity to examine how sexual conflict influences diversification and asymmetrical trait evolution across lineages. Using 204 individuals, representing over half of the subgenus's species diversity, we reconstructed a time-calibrated phylogeny, quantified diversification rates, assessed sexual conflict intensity across clades, and analyzed correlations between sexual trait evolution and diversification. Our results reveal extensive phylogenetic conflict, particularly within the East Asian clade, driven by introgression and incomplete lineage sorting (ILS). Furthermore, we observe significant phylogenetic heterogeneity in both phenotypic evolution and diversification rates. Notably, a male "trait package" enhancing grasping ability likely drives rapid diversification in the recently radiated "South China" lineage. In contrast, grasping traits involving abdominal segment VIII are associated with lower conflict intensity, facilitating greater evolutionary flexibility in female resistance and resulting in lineage-specific counter-adaptations. These findings highlight the heterogeneous dynamics of asymmetrical sexual conflict in shaping diversification and speciation.

Many sea anemones reproduce asexually by pedal laceration, shedding fragments of the pedal disk that regenerate into polyps. How feeding affects the amount of this reproduction differs among species, but whether feeding also sets its timing has rarely been examined. We fed the sea anemone Cylista elegans (formerly Sagartia elegans) daily, every second day, every fourth day, or not at all, measured growth, laceration, and survival over 35 days, then reassigned anemones to new schedules to test whether laceration follows the current or previous schedule. Growth rose with feeding but saturated, animals fed daily and every second day growing at similar rates. Total laceration depended on whether an anemone was fed rather than how often. Every fed schedule produced more lacerates than starvation. The timing, by contrast, tracked the schedule closely. Laceration was suppressed for about a day after each meal and recovered before the next, so anemones fed every second or every fourth day lacerated on matching two- and four-day rhythms, while daily-fed animals were arrhythmic. When moved to a new schedule, the period shifted to match it, not the old one. Only starvation caused death. Asexual reproduction in C. elegans is therefore bound closely to feeding, which fuels laceration yet suppresses it during digestion, confining it between meals. This coupling distinguishes C. elegans from anemones with symbiotic microalgae, where starvation rather than feeding drives reproduction, and links it to the feeding-driven clonal proliferation of the invasive sea anemone Diadumene lineata.

AO_SCPLOWBSTRACTC_SCPLOWO_LICommunity assembly graphs (CAGs) summarize which species combinations can coexist and how single-species invasions drive transitions between them, encoding the pathways, alternative endpoints, and cycles that make up a communitys assembly history. Constructing CAGs from dynamical models requires methods that are both computationally tractable and faithful to the underlying ecological dynamics. However, existing methods rely on restrictive assumptions, such as global stability, that exclude alternative stable states and non-equilibrium dynamics known to occur in empirical systems. C_LIO_LIWe develop a computational pipeline that constructs CAGs from any generalized Lotka-Volterra model. Building on the invasion graph framework and its connection to permanence, the pipeline verifies that community dynamics are bounded, identifies which subsets of species coexist in the sense of permanence, determines which single-species invasions are dynamically realized, and assigns each community a topographic height equal to the length of the longest assembly path leading to it. We also provide a numerical algorithm to simulate the dynamics of community assembly. C_LIO_LIWe prove several general properties of the resulting graphs, including that a successful invader is never subsequently excluded and that, in the absence of assembly cycles, permanent communities can be reassembled by introducing their species one at a time in the right order. We prove that the CAG faithfully reproduces the compositional shifts seen in the numerically simulated dynamics of assembly. Applying the pipeline to three empirically based models (a New Zealand grassland, a European pasture, and a Puerto Rican ant community), we show how competition strength and mutualistic feedbacks reshape the assembly landscape and how intransitive competition generates assembly cycles. C_LIO_LIOur approach accommodates alternative stable states and non-equilibrium dynamics without requiring global stability, and it turns the long-standing landscape metaphor into a quantitative, mechanistically grounded object by resolving what "height" means. More broadly, it makes the topography of the assembly pathways measurable, providing a way to compare the historical contingency and predictability of the assembly in ecological systems. C_LI

Ecosystems are rarely at steady state, yet most theory predicting universal biodiversity patterns assumes they are. Here, we test whether and how eco-evolutionary dynamics drive departures from steady state by combining arthropod community data from the geologic chronosequence of the Hawaiian Archipelago with the Maximum Entropy Theory of Ecology (METE), a minimalist steady-state framework that simultaneously predicts species abundance distributions (SADs) and individual metabolic rate distributions (IPDs). The chronosequence of the Hawaiian Archipelago has yielded insights into eco-evolutionary processes because ecosystems growing on different aged substrates offer snapshots of community assembly with different histories. We find that deviations from METE peak at geologically middle-aged sites (150 Kya-1.4 Mya), consistent with active adaptive radiation pushing communities away from statistical steady state. Within-site {beta}-diversity, which also peaks at middle-aged sites, robustly predicts deviations from METE across all sites, while the proportion of non-native species predicts deviations only after excluding the geologically youngest site. Partitioning {beta}-diversity between native and non-native species resolves this discrepancy: at the youngest site, non-native species are distributed homogeneously and do not elevate {beta}-diversity despite their high proportional representation. Together, these results are consistent with a trajectory from young, dispersal-assembled communities near statistical steady state, through an eco-evolutionary non-steady-state transition driven by diversification, to a new stable steady state at the oldest sites. Our findings suggest that periods of active diversification create windows of ecological instability that may facilitate biological invasion, with implications for understanding invasion dynamics in biodiversity hotspots.

Environmental variability can strongly alter coexistence among competing species and their extinction risk, particularly when population dynamics are shaped by behavioral interactions, such as fear. In this work, we develop a novel stochastic differential equation competition model that incorporates both non-consumptive fear effects and environmental variability to investigate how behavioral interactions influence species coexistence under random fluctuations. Our result reveals that environmental stochasticity can drive species to extinction even when the corresponding deterministic system admits coexistence. In particular, under an explicit stability condition on the fear and competition parameters and sufficiently strong averaged noise intensities, we prove that both competing species become extinct exponentially almost surely. Conversely, we derive a stochastic persistence criterion in terms of fear, competition, and noise-induced suppression parameters for the fearful species. We further demonstrate that environmental noise may reverse classical competition-exclusion outcomes, leading to qualitatively different long-term dynamics from those predicted deterministically. These results provide rigorous thresholds separating stochastic extinction from persistence and highlight the critical role of environmental variability in fear-mediated competitive ecosystems. From an applied perspective, these results provide insight into how behavioral interactions and environmental variability influence species survival, with potential applications in ecological management and conservation.

The timing of reproductive processes can influence how mating interactions shape reproductive strategies. We examined how female age correlates with receptivity and preference in the jumping spider Habronattus formosus, a system characterized by elaborate male courtship and strong female choice. To test how receptivity changes across the post-maturation period, we paired females of different ages with males and quantified male courtship displays and mating outcomes. Females were not receptive immediately after maturation and instead exhibited receptivity primarily 2-3 weeks after maturation. We further found that the full male courtship predicted mating success in older females, whereas only the second stage of the courtship predicted success in younger females. The delay in female receptivity is consistent with expectations for strong female choice systems, where females may have a greater opportunity to evaluate male courtship before mating. These results highlight the importance of age-dependent changes in female reproductive state and suggest that the timing of receptivity may shape how different components of male courtship influence mating success.

The general random walk model (GRW) of Hunt (2006) is used to infer directional evolution in mean trait values from sparse fossil data by modeling phenotypic change as the accumulated result of small steps with mean step sizes and step variances. Using simulations and real data cases, Ergon (2026) showed that the step variances can be estimated reasonably well only when the mean trait values have small measurement errors, while for fossil data with realistic measurement errors they appear to be extremely difficult to find, and they are often found to be negative. In the simulations Ergon (2026) assumed that the true phenotypic mean values were known. Here, I essentially repeat these simulations under the assumption that only mean trait values with large measurement errors are known, and based on weighted mean squared error (WMSE) comparisons the conclusion is that weighted least squares (WLS) is a better method than GRW. A second conclusion is that WLS is a better method also in the possibly rare cases with large measurement errors where the GRW parameters are estimated well. The GRW method is simply not flexible enough to handle such cases. A third conclusion is that Akaike Information Criterion (AIC) results for GRW models with large measurement errors relative to the step variance may be overly optimistic.

Eusocial Hymenoptera present the highest known recombination rates among metazoans, which evolved several times independently among bees, ants and wasps. Several hypotheses have been proposed to explain this observation, including stronger selection for recombination caused by coevolving parasites and pathogens, and strong sexual selection among haploid males due to male-biased sex ratios among reproductive individuals. In this article, we explore the effects of haplodiploidy and differential selection between sexes on the evolution of recombination, by analyzing a three-locus model in which selection for recombination stems from negative epistasis between selected loci. Our analytical predictions are compared with the results of individual-based simulations in which deleterious mutations occur along a linear chromosome. Our results show that, at mutation-selection balance for deleterious alleles, increasing the strength of selection against deleterious alleles (due to the effect of male haploidy and/or sexual selection) tends to reduce selection for recombination. However, an increase in the overall magnitude of negative epistasis (which may also be due to male haploidy and/or sexual selection) combined with the fact that recombination only occurs in females may increase selection for recombination substantially. Our model also shows that, in conditions favoring recombination, increasing recombination in meioses leading to parthenogenetic ovules (and male offspring) may yield stronger benefits than in meioses leading to fertilized ovules (and female offspring).