Philosophical Transactions of the Royal Society B

Objective: To develop and demonstrate an agent-based modeling framework for healthcare AI adoption, using ambient clinical documentation as the calibration case. Materials and Methods: We built an agent-based model with 50,000 clinician agents, 500 organization agents, and 4 vendor agents over 104 weeks. Modeled clinicians differed by psychotype, specialty, and friction/benefit thresholds; modeled organizations progressed through deployment phases with governance delays anchored to 8-28 weeks. All cited deployment values were independently re-verified against primary sources, and the model was validated against published data from seven health systems and three benchmarks using formal goodness-of-fit metrics (RMSE, 90% predictive-interval coverage) grouped by reference class. After correcting an organization-initialization artifact, we performed a formal six-parameter re-calibration to align both the early-time trajectory and the steady-state plateau with published data. Six intervention scenarios were compared in paired simulations (n=30 realizations per scenario) using effect sizes with bootstrap intervals, and both the full intervention comparison and the Sobol sensitivity screen were re-run natively under the re-calibrated model. Global sensitivity analysis used Sobol indices (64 base samples; 1,152 parameter sets) across eight parameters. Results: Baseline simulations produced S-curve adoption trajectories with wide variability. The re-calibrated model reproduced both early-time single-site trajectories and the cross-sectional adoption plateau, covering 86% of reference-class-matched anchors at the nominal 90% level, versus 29% for the original configuration. Most intervention scenarios increased adoption; in the original configuration the combined intervention outperformed individual levers, with significant interactions confirmed by 23 factorial analysis. Re-running the analyses natively under the calibrated model both confirmed and revised these conclusions: governance remained the largest single structural lever and non-success absorbing states remained prominent, but intervention effects attenuated sharply, the combined intervention no longer reliably exceeded the best single lever at operating scale, and the leading sensitivity driver shifted from governance delay to clinician friction/edit-rate tolerance. That calibration changes which levers appear influential is itself the central methodological finding. Organizational outcomes clustered into non-success absorbing states (pilot stagnation and failure) alongside success and scaling. Conclusions: Governance delay is an explicit upstream gate in the model, so its influence reflects model architecture and should not be interpreted as a universal real-world priority. The modeled pilot stagnation state is hypothesis-generating rather than an empirical category. Agent-based modeling provides a structured framework for understanding healthcare AI adoption dynamics. The approach supports hypothesis generation and comparative scenario exploration rather than point prediction.

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.

As the worlds oceans change in response to climate change, phytoplankton communities will adapt to warmer, more stratified surface waters via plasticity, evolution, and range shifts. Current global ocean models assume that size structured phytoplankton communities have fixed trait relationships, and as a result generally predict that smaller size classes will become more dominant globally. However, this general expectation fails to consider how intra-species trait tradeoffs may operate orthogonally from large-scale inter-species tradeoffs--allowing for alternative evolutionary pathways given the limits and/or possibilities available to ancestral populations. To identify evolutionary pathways phytoplankton populations might take, we develop a novel modeling framework that combines a trait-based phytoplankton quota model with stochastic evolution (ecoTRACE). EcoTRACE explicitly decouples key phytoplankton traits from interspecific allometric relationships, allowing for novel phenotypes to emerge. We validated ecoTRACE against a long-term artificial size selection experiment on Dunaliella tertiolecta. We show that ecoTRACE captures multi-dimensional evolved phenotypes that quota models based on interspecific relationships fail to reproduce. Under fluctuating multi-stressor growth, model populations evolve phenotypic plasticity that deviates from predicted interspecific allometric relationships. EcoTRACE provides a framework for generating hypotheses as to the evolutionary trajectories that phytoplankton will experience in a warmer, more variable ocean.

Introgression following hybridization is increasingly recognized as a major driver of evolution. However, its importance depends on its frequency in nature, which remains to be quantified. To address this, we provide a snapshot of ongoing introgression in a whole species assemblage (4126 ant colonies). 23% of all 82 local species show signs of introgression, which is more than twice previous estimates. Introgression is typically subtle, yet we find that it contributes measurably to genetic diversity. Species divergence, rather than classical prezygotic reproductive barriers (mating phenology, ecological niche, fine-scale habitat use) constrains introgression, suggesting that the main reproductive barriers are postzygotic at this stage of divergence. Our results indicate that introgression may be a common but often overlooked feature of natural communities.

Recent evidence of extensive call sequence use in non-human primates has led to the theory that syntax evolved to mitigate the constraints of their genetically fixed repertoires, before vocal production learning later emerged in humans. However, evidence of similarly extensive sequence repertoires in an open-ended vocal production learner--the Western Australian magpie (Gymnorhina tibicen dorsalis)--offers a unique opportunity to explore potential alternative pathways to syntactic communication. Our previous work revealed fledgling magpies learn group-specific repertoires of structured call sequences from their social contacts, with more sociable individuals acquiring larger repertoires earlier in development. Notably however, the individual vocal segments that combine to form their calls and call sequences were shared across groups and emerged as early as the first week post-fledging--suggesting the underlying vocal elements may not be learned. Here we utilised acoustic neighbourhood-based dimensionality reduction to compare clustering patterns of vocal segments across magpie fledgling developmental stages, and between fledglings and adults. We found no evidence of acoustic development over time, and no significant distinction between fledgling and adult productions of the same vocal segments. The same coarticulatory effects--where a vocal element is produced differently when combined with another--and geographic variation established previously in adults were supported in fledglings too. These findings support that the vocal building blocks underpinning magpie call sequences are innate, suggesting usage learning better explains how fledglings learn to combine calls. In a species capable of open-ended production learning, this suggests learning to combine existing signals may be more adaptive than productively learning new ones. Rather than evolving solely to compensate for genetically fixed repertoires, syntax may have evolved as a flexible, convergent solution to the various challenges of expanding communicative capacity--whether due to genetic constraints, cognitive limitations or the cost of establishing new meaning in novel signals.

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.

Growing evidence of animals combining discrete, meaningful calls into sequences--a feature once thought unique to linguistic syntax--has presented the opportunity to investigate the evolutionary origins of syntactic communication. The arbitrary assignment of meaning to words marks an important step in human language evolution, and a necessary precursor to generating further meaning through sentences. Studying how other animals that produce call sequences learn the meaning of these signals could help shed light on how referentiality and semantic combinatoriality evolved. Given the presence of meaningful call sequences has only recently been revealed in several non-human animals, ontogenetic studies of the comprehension of these vocalisations are, to date, non-existent. Western Australian magpies (Gymnorhina tibicen dorsalis) combine discrete calls into a diverse array of call sequences. Recent evidence shows these sequences are socially learned, but the developmental stage at which fledglings respond correctly to them remains unstudied. We performed playbacks of a discrete alarm call and call sequence to fledglings over the course of their first 18 weeks out of the nest, identifying when they differentiate between the low-level disturbance associated with the discrete call and the high-grade aerial threat associated with the sequence. Fledglings showed immediate vigilance to both vocalisations but exhibited significantly greater vigilance and upward scanning following the sequence. Critically, fledglings showed this response to the sequence from the first week of testing, with no effect of age on the response to either vocalisation. These findings suggest that comprehension precedes production of sequences in magpies and that sequence meanings are either learned rapidly or have an innate basis. While further investigation is essential, this study offers the first empirical insight into the ontogenetic emergence of combinatorial comprehension in a non-human animal.

Conjugative plasmids drive the dissemination of antimicrobial resistance genes and other conditionally beneficial accessory genes, but otherwise inflict fitness costs on their hosts that limit their spread. These costs can be ameliorated by compensatory mutations on the chromosome, the plasmid, or both combined (combined compensation). Mutants with plasmid-borne or chromosomal compensation differ in how they spread and compete, making the location of compensation an important determinant of plasmid and antimicrobial resistance (AMR) dynamics. We collate experimental data on plasmid-host co-evolution which, albeit limited, suggest compensatory benefits differ by location and are highest for combined compensation. We develop and analyse a mathematical model of compensatory evolution, finding that the long-term location of compensation is mainly determined by the highest cost reduction. Short term, however, succession dynamics arise from differences between locations: for instance, plasmid-borne compensation spreads horizontally, initially dominates, and can even facilitate the establishment of chromosomal or combined compensation. Strong trade-offs between compensation and either resistance or conjugation render compensation non-viable, but only conjugation trade-offs are location-dependent, disadvantaging plasmid-borne compensation and generating oscillatory dynamics. Our findings suggest plasmid-borne compensation may initially accelerate AMR-plasmid spread, whereas long-term chromosomal or combined compensation may enable hosts to accumulate multiple AMR-plasmids, promoting multidrug resistance.

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.

Spacer efficacy generally declines with distance from the leader sequence, but the scarcity of fine-scale studies hampers comparisons across taxa. Here, we investigated positional effects across an exceptionally long 121-spacer CRISPR array associated with the type I-C cas operon of a Myxococcus xanthus natural isolate. In plasmid-interference assays, we found that interference rapidly declined with distance from the leader sequence, with only the proximal ~4% of spacers conferring measurable interference. This contrasts strikingly with a study in Vibrio cholerae, in which it was shown that ~95% of spacers in a shorter (39-spacer) array were effective. Our results suggest that there is great variation in the effective proportion of spacers across species, highlighting the need for fine-scale studies of CRISPR-array activity across diverse bacterial lineages.

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.

Pitch control models quantify spatial dominance in football by estimating which player can arrive first at each pitch location, but they treat all players as equivalently capable regardless of preceding effort. We introduce physiology-aware pitch control (Phys-PC), a model-agnostic time-to-arrive correction that imposes two physiological capacity channels calibrated from tracking data: a transient recoverable burden capturing incomplete recovery from recent high-intensity efforts, and a cumulative non-recoverable drain accumulating across match play. Both channels reduce a bounded access scale that modulates kinematic TTA before any downstream pitch-control computation. All parameters are anchored to exercise-physiology benchmarks; no laboratory measurements are assumed. Applied to a 64-match international tournament, Phys-PC reveals structure that kinematic models cannot detect. In head-to-head races, the dominant burden channel shifts from transient to cumulative over the course of a match, with a transient resurgence in the final 15 minutes. These physiological asymmetries predict match outcomes: relative reserve advantage is associated with higher odds of winning ground challenges (OR = 1.20, p = 0.006; +4.2 pp), completing over-the-top passes past recovering defenders (OR = 1.45, p = 0.034; +8.3 pp), and progressing possession sequences into the final third (OR = 1.31, p = 0.013; +5.1 pp). At the player-profile level, an acute-cumulative decomposition of contested space access separates roles and individuals whose territorial reach is maintained through sustained positioning from those whose access is rebuilt through repeated high-intensity actions, providing a physiological lens on team tactical structure.

The impacts of a changing abiotic environment on fitness and performance arise not only from low tolerance to new environmental conditions, but also from changes in the abundance and interaction intensity with other species. The strength of the interaction may itself depend on how well each species performs across environments, but there is a dearth of studies investigating how intrinsic fitness and interaction intensity covary across an abiotic environmental gradient. We addressed this question in a hypersaline consumer-resource system: the microalga Dunaliella spp. grazed by the brine shrimp Artemia franciscana. We exposed four Dunaliella strains to a range of salinities above seawater, with or without brine shrimps, and tracked their population sizes over time and the survival of their predators, to estimate basic parameters of a Lotka-Volterra model. We found that the intrinsic growth rate of algae, the survival rate of predators, and the per-capita predation rate, all varied with salinity and algal strain. Significant interactions between strain and salinity further revealed that these ecological responses to salinity are evolvable. Together with correlations between demographic parameters across salinity, this suggests that predation may influence the evolution of salinity tolerance curves, blurring the line between the fundamental and realized niches.

Song evolves rapidly in songbirds, as has been proven for a substantial number of songbird species by demonstrating acoustic differences between current songs and "historical" songs recorded 20 or 30 years previously. In two species of songbirds, white-crowned sparrows and savannah sparrows, it has been further shown that evolutionary changes over such time spans are sufficient to affect the response of receivers, with territorial males responding more aggressively to current songs than to historical ones. These two species, however, have especially low population variability in song, with most males in any population singing the same, single song type; this background of song uniformity makes it especially easy to discern temporal changes. Here we examine response to temporal change in song in a third sparrow species, the song sparrow, in which population variation in song is much higher: males sing 5-13 song types each, with low song-sharing between males, so that hundreds of distinct song types occur in a local population. We find evidence that temporal change has occurred in the songs of our study population, in that 24 song current song types share more introductory phrases with other current song types than do 24 historical song types recorded 27-29 years earlier. Nevertheless, in a song playback experiment, current males showed no difference in response to current and historical songs. The results are in accord with the hypothesis that high levels of population variability in song make temporal changes in song difficult to discern.

Mutation is the ultimate mechanism that produces genetic novelty, and thus a central ingredient of evolution. Mutation rates are therefore thought to be tuned by natural selection, for example to optimize a delicate balance between the generation of adaptive diversity and the accumulation of deleterious mutations. As this selection occurs over very long time scales, models and simulations have been powerful tools to understand how mutation rate evolves and which factors influence it. Most simulation methods are nevertheless limited by the over-simplicity of the genotype-to-phenotype map they feature, especially regarding the encoding of mutation rate. We modified Aevol, an evolutionary simulator inspired by bacterial genomics with a realistic genome structure and a complex genotype-to-phenotype layer, to allow organisms to evolve genes coding for higher replication fidelity. This setup permits several degrees of realism absent in other models: mutation-rate modifier genes themselves experience a realistic distribution of effects of mutations and diminishing- returns epistasis, similarly to fitness modifiers. Moreover, a lower mutation rate comes with the trade-off of a larger genome to encode the genes improving replication fidelity. We use this setup to test hypotheses regarding the evolution of prokaryotic mutation rate, and its link with genome size and genetic drift. We found that evolution systematically increases replication fidelity, even when this results in lower fitness. We highlight two factors which limit the mutation rate decrease: genetic drift and the supply of gain-of-fidelity mutations.

Incomplete information on distributions for a high proportion of the world's plant species together with biases in global biodiversity data mean that current estimates of plant diversity patterns are skewed. A key issue is that current predictions rely on a subset of species that is not representative of all plant species. Here we tested the feasibility of a representative sampling approach for mapping global vascular plant diversity at the finest scale where comprehensive data is available. Using the World Checklist of Vascular Plants as a reference, we generate random samples of species with increasing sample sizes from the global species pool. We compare the diversity patterns retrieved from the samples against the patterns of the reference dataset using spatially weighted correlation coefficients and four different diversity metrics. We find that at the botanical country scale, representative global maps of species and phylogenetic diversity can be created with small numbers of species (~1% [0.2% and 0.4%, respectively]) at the botanical country scale. For effective growth form and family diversity sample sizes encompassing ~20% [19.2% and 19.5%, respectively] of all species are needed. Random samples require markedly fewer species to reach high correlations than when restricting the pool of species to single plant families or genera. We show that when representative samples are used robust inferences of plant diversity patterns can be made from only a small proportion of species.

Collective movement requires coordination between individuals, yet how this emerges during early interactions remains poorly understood. We investigated how partner familiarity influences coordination, leader-follower dynamics, and learning in homing pigeon pairs navigating from novel sites. Birds were released repeatedly with either familiar or unfamiliar partners, followed by solo releases to assess learning. By quantifying bidirectional information flow, we found familiarity influenced information-transfer dynamics during the first release: familiar pairs exhibited more asymmetric information transfer, likely reflecting established leader-follower relationships, whereas unfamiliar pairs showed more symmetric exchange. These differences disappeared after one release. Conversely, familiarity had little effect on cohesion or navigational performance. There was some evidence for an influence on learning: birds from familiar pairings had higher homing efficiency on a subsequent solo release. Finally, across partnerships, followership was more predictable than leadership with respect to individual identity and flight speed, indicating stable variation in individuals' tendency to follow rather than lead. This suggests that a shift in emphasis from leadership to followership might enhance our understanding of collective decision-making dynamics. Our results demonstrate how flight partners rapidly coordinate, producing limited downstream effects on navigation and learning, with implications for many animals that travel in fission-fusion transitory collectives.

Why male primates invest in costly behaviours producing public goods remains debated, with two leading explanations, paternal care and reputation-based partner choice (RBPC). Using long-term data from four groups of wild vervet monkeys, we tested: (1) whether males show a bias in four protective "male services" (predator alarm calling, participation in between-group conflicts, leading river crossings and sentinelling); (2) which males contribute most; and (3) whether service provision predicts mating success during the mating season. We confirmed a male bias in all services. Consistent with the paternal care hypothesis, contributions were positively associated with past mating success, independently of rank, although potential fathers did not contribute more than non-fathers. Among non-fathers, service provision varied with rank, suggesting that newly immigrated males adjust their behaviour according to competitive state. Crucially, variation in alarm calling and between-group conflicts predicted future mating success, with between-group conflict emerging as the strongest and most consistent predictor of mating success across years and within mating seasons, whereas rank, tenure and social integration added little explanatory power. In contrast, sentinelling and leading river crossings did not reliably translate into mating benefits. Our findings indicate that male services are shaped by multiple selective pressures operating across different male career stages and that some forms of public goods provision function as signals of quality and cooperativeness to females. By directly linking cooperative investment to mating outcomes in a wild primate, this study provides rare empirical support for reputation-based partner choice beyond humans and highlights female choice as a potentially important force in the evolution of cooperation.

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.