The American Naturalist

Animal mating systems are hugely diverse, ranging from species where mating is essentially random to those exhibiting complex systems of mate choice by one or both sexes. While polygyny and mate choice are known to alter adaptation and persistence in a changing environment, there has been little exploration of the ways that adaptation and evolutionary rescue are modulated by other types of mating systems. We developed an individual-based model that allows random mating, female-only choice, and mutual mate choice to be compared between monogamous and polygynous frameworks and used it to explore how mating systems influence adaptive response, loss of heterozygosity, and extinction risk under worsening environmental conditions. We find that mating systems interact with population size in determining extinction risk: mate choice under polygyny lowers effective population size, small polygynous populations with either mutual or female-only mate choice lose heterozygosity quickly and so face higher extinction risks than randomly mating populations. However, in larger populations where inbreeding and genetic drift are less important, mate-choice-based polygynous systems enhance evolutionary rescue by allowing better-adapted males to dominate reproduction, accelerating adaptation and increasing resilience to environmental change. Among polygynous systems, female-only choice leads to slower loss of heterozygosity and facilitates population resilience better than mutual mate choice. These findings demonstrate that mating systems can critically shape a populations ability to adapt to environmental change and alter extinction risks, emphasizing the need to consider mating systems in designing effective conservation strategies. Significance StatementEnvironmental change threatens species survival, and sexual selection can have profound modulating processes that determine extinction risk. Sexual selection operates in a variety of mating systems, and the role of this diversity is often overlooked. Using individual-based simulations, we show that mating systems with mate choice boost evolutionary rescue in larger populations via "good genes," while in small populations, it has the opposite effect by elevating the loss of heterozygosity. These results have critical implications for conservation biology. Conservation strategies should consider mating system characteristics when assessing species vulnerability and planning management efforts to support evolutionary resilience and long-term population persistence.

Habitat complexity (HC) in part determines the diversity, stability, and behavior of food webs and can influence predation according to a wide variety of functional relationships. Many aquatic species provide habitat complexity and are also consumed by other species (e.g., macrophytes, corals, mussels). However, food web theory does not readily account for these species that act as edible habitat complexity (EHC). Here, we combine existing theory on predator-prey interactions, HC, and prey switching to describe the role of EHC in benthic food web models. We dissect feedback loops in each model to demonstrate how self-regulation of the prey species, mediated by species densities and HC, drives that food webs behavior. HC can stabilize predator-prey interactions by coupling prey self-regulation with HC self-regulation. EHC can further stabilize predator-prey interactions across a wide variety of "HC functions" that relate HC to predation rates. Significance StatementHabitat complexity (HC) plays a critical role in trophic interactions, population dynamics, and food web stability. However, little theory exists to describe edible habitat complexity (EHC), where a species is both consumed and confers habitat complexity for other species. We provide a series of models demonstrating how HC and EHC alter the population dynamics and stability of simple aquatic food webs. HC is strongly stabilizing in food webs by providing safety in rarity for prey. EHC provides safety in rarity for both prey and the EHC species because their predators are omnivorous. Given the prevalence of EHC species in aquatic systems (e.g., macrophytes, corals, mussels), our models demonstrate the importance of maintaining EHC species in aquatic systems for stable food webs.

Species tolerating the same environmental conditions can potentially colonize and thrive in the same habitats and eco-regions. Are any pair of those species equally probable to co-occur in the same community? Can we quantify the propensity of two species to co-occur together? Here, we focus on a simple but largely overlooked community-level pattern: the co-occurrence-occupancy curve, which relates the tendency of species to co-occur with others to their total occupancy across sites. We first define this empirical curve and then derive its expected shape under a random null model that assumes site equivalence and species independence. Building on these results, we introduce the Species Association Index (SAI), an occupancy-standardized measure that quantifies the tendency of a species to associate with others independently of its overall frequency of occurrence. The SAI enables meaningful comparisons among species with contrasting occupancies and provides a transparent benchmark against which departures from neutrality can be assessed. We illustrate the approach using two contrasting systems--tropical rain forest trees on Barro Colorado Island and organisms from Mediterranean rocky shores--highlighting both the generality of the co-occurrence-occupancy framework and its limitations.

O_LISeasonal patterns of species appearances constitute a major component of diversity variation. Theory attributes this phenological structuring of communities to the alignment of life cycles to suitable moments and to constraints of seasonality on development, yet the specific mechanisms operating across taxa remain largely unresolved. In insects, body size and colour are key functional traits that contribute to driving spatial community assembly through their link to thermoregulatory performance and development. C_LIO_LIHere we analyse variation in mean body size and colour lightness of 483 butterfly assemblages across Great Britain and throughout the season to test whether trait alignment with seasonal environment and developmental constraints may shape the phenological structuring of communities. C_LIO_LIBoth body size and body colour varied more along season than across space, emphasizing the importance of phenology on diversity variation. Body size was larger early and late in the season, i.e. under conditions of low temperature and solar radiation. This pattern contrasted with the spatial trends found and was driven by species overwintering as adults, which we interpret as being likely due to energetic constraints. Body colour, conversely, was darker early and late in the season, mirroring the spatial pattern found, and suggesting a thermoregulatory alignment with seasonal conditions. Furthermore, covariation between body size and colour suggests a thermoregulatory interaction between both traits. C_LIO_LIOur findings suggest that life-cycle constraints and seasonal thermoregulatory alignment contribute to shaping the phenological structure of insect communities. C_LI

Article summaryGene interactions are common, yet additive genetic models often predict short-term evolution and breeding response. This study argues that additivity can arise because populations sample only a small neighbourhood of a curved fitness landscape. In additive channels, genetic variation is small enough that local curvature contributes little to heritable fitness differences. The study defines an additivity index ([A]g) that compares variance from the local slope of log-fitness with variance from curvature, and links this ratio to expected prediction accuracy under Gaussian assumptions. A selection-inheritance framework shows when additive channels persist and when populations leave them. It yields testable predictions.

The Allee effect is a phenomenon where individual fitness is reduced in small populations, for example because of mate-finding difficulties or increased predation. Allee effects matter in conservation biology because they can drive small populations to extinction. The severity of Allee effects can depend on traits such as mate-search rate and defense against predators. Many natural populations exhibit considerable intraspecific trait variation (ITV) in such traits, but most studies so far assume these traits to be constant. Thus the impact of ITV on populations with Allee effect is largely unknown. Here we create two individual-based stochastic models that simulate a small population experiencing either a mate-finding Allee effect or a predator-driven Allee effect. We analyze how ITV, trait inheritance, and mutation affect the proportion of surviving populations. Under the mate-finding Allee effect, higher ITV hindered population survival and increased Allee thresholds. This can be explained by Jensens inequality and the negative curvature of the mate-finding function. Under the predator-driven Allee effect, ITV effects were weak, but higher mutation standard deviations were beneficial, likely because they provided more substrate for selection to act on. We thus recommend to take into account ITV when dealing with threatened populations with an Allee effect.

Repeated divergence across contrasting habitats is widely used to infer natural selection and local adaptation. However, such inferences remain inherently correlative and capture only adaptation shared within habitat types, thereby missing site-specific adaptation among populations from the same habitat type. Field transplant experiments test adaptation more directly by measuring fitness in nature, but they are typically limited to pairwise reciprocal exchanges between populations and therefore cannot separate the contributions of shared habitat-level and site-specific adaptation to fitness. Here, we overcome these limitations by extending the typical transplant framework to include multiple populations transplanted both within and across habitat types. We apply this framework to lake-stream stickleback, a classic system for studying local adaptation via repeated divergence. Specifically, we transplanted laboratory-reared fish from a panmictic lake population and four independently evolving stream populations into one lake and two stream sites. Stream fish outperformed lake fish in streams and vice versa, providing evidence for adaptive lake-stream divergence. Strikingly, local stream fish also outperformed foreign stream fish at both stream sites. This site-specific advantage was twice as large as the advantage of foreign stream fish over lake fish, which reflects the fitness benefit of shared stream adaptation. These results show that in this system, the majority of fitness-relevant evolutionary variation is site-specific and therefore missed by approaches that rely on repeated divergence to infer adaptation. More broadly, this underscores the importance of ecological scale for understanding adaptation and evolutionary predictability.

2The genotype-to-phenotype architecture (GPA), defined by complex interactions such as pleiotropy, epistasis, and regulatory control, is a fundamental yet often overlooked driver of biodiversity dynamics. While empirical evidence suggests that traits mediating species interactions (biotic) and environmental responses (abiotic) are frequently correlated, most eco-evolutionary theories treat these traits as independent, leaving a gap in our understanding of how genomic architecture influences community-level outcomes. In this study, we contrast two distinct GPAs, modular (independent trait evolution) and correlated (integrated trait evolution), within a spatially explicit multilayer network framework. We evaluate their impact on biodiversity across varying regimes of selection, migration, and biotic and environmental filtering. Our results reveal a hierarchy of drivers: selection strength dictates the absolute magnitude of the architectural effect, while migration and context-dependent biotic and abiotic effects determine which architecture yields a diversity advantage. Correlated GPAs enhance species coexistence and diversity in low-migration landscapes characterized by strong selection and moderate, balanced biotic and abiotic pressures. In these contexts, trait integration serves as a buffer against selective noise. Conversely, modular GPAs support higher diversity under high migration and strong biotic interactions, where the decoupling of trait modules provides the adaptive flexibility necessary to navigate spatially conflicting selective pressures. Our findings demonstrate that genomic architecture acts as a critical filter for environmental perturbations. Integrating complex GPAs into multispecies models is essential for quantifying the co-evolutionary feedbacks among traits, population adaptation, and species persistence. Our framework provides a path for predicting how biodiversity emerges and persists across biological scales, from genomics to communities and food webs, under the accelerating pressures of global change. 1 ConclusionsO_LIWe integrate trait architecture to spatial biodiversity to show biodiversity patterns are not merely products of ecological interactions, but are fundamentally constrained by Genotype-to-Phenotype Architecture (GPA). By linking GPA to biodiversity we show the interplay between the complexity of an organism and community structure in determining diversity patterns. C_LIO_LIThe hierarchy of Eco-Evolutionary Drivers: We establish a new conceptual hierarchy where selection strength acts as the fundamental governor of architectural impact, while the specific architecture predicting higher diversity (Correlational vs. Modular) is dictated by the interplay of migration scales and context-dependent biotic and abiotic dynamics. C_LIO_LISelection-Migration contingency for coexistence: We provide a new hypothesis for species coexistence: Correlational selection serves as a stabilizing force under dispersal limitation, whereas Modular trait architecture provides the adaptive flexibility to maintain diversity in high-migration, spatially heterogeneous landscapes. C_LIO_LIAdaptive decoupling as a diversity engine: We propose that trait modularity functions as a "buffer" against extinction by decoupling phenotypic responses. This allows populations to navigate conflicting selective pressures, effectively facilitating evolutionary rescue in complex biotic environments. C_LIO_LIMethodological framework for empirical inference: To bridge the gap between theory and data, we provide a novel likelihood-based framework. This enables researchers to infer latent trait architectures from population genomic samplings, turning GPA from a theoretical construct into a measurable sampling variable in natural populations. C_LIO_LIWe define a new roadmap for the next generation of eco-evolutionary modeling. By identifying the gaps between existing simulation engines, we provide a conceptual "blueprint" for a digital ecosystem that fully integrates complex genetic architecture with global bio-diversity dynamics. C_LI

Population genetic models excel at identifying the conditions for polymorphisms based on balancing selection but typically disregard the ecological processes that yield particular values of selection coefficients. We model a system that combines antagonistic pleiotropy, dominance reversal and heterozygote advantage: the wood tiger moth Arctia plantaginis, where alternative haplotypes at a major-effect locus determine male hindwing coloration. Yellow offers better protection against predators, while white is often associated with better mating success. The effects of mortality and reproductive success overlap in time because protandrous males can mate as long as they are alive, but they need to avoid predation for several days before the bulk of females emerge. We show that protandry aids polymorphism maintenance whenever the second-fittest genotype (after the heterozygote) is the poorly surviving but mating advantaged homozygote, while increased protandry harms polymorphism when the second-best fitness is that of the survival advantaged morph. Ecologically plausible protandry times predict that dominance reversal does not have to be strong for polymorphism to be maintained. Our study highlights the importance of timing traits in maintaining polymorphisms in Lepidoptera and showcases the benefits of deriving fitness explicitly in place of abstract selection coefficients that lack temporal components within the life cycle.

Research on stochastic phenotypic variation (i.e., variation arising despite the apparent absence of genetic and environmental differences) has recently emerged as a rapidly growing area in biological research. But despite growing recognition of both its existence and fitness relevance, it remains unknown whether and to what extent such stochastically induced variation is transmitted across generations, potentially making it an unrecognized contributor to evolutionary processes and the adaptive potential of populations. In order to address this knowledge gap, we here performed a two-generation behavioral screening with a naturally clonal fish: 34 genetically identical mothers and their 232 offspring were separated directly after birth into near-identical environments and tracked continuously at high resolution, constituting a total of [~]19,000 observation hours. We find that consistent among-individual differences in behavioral profiles (i.e., activity and feeding patterns) of both mothers and offspring emerged despite the absence of apparent genetic and environmental differences. Mother feeding behavior - but not mother activity - was positively associated with offspring activity: mothers that spent more time feeding produced more active offspring, explaining [~] 33 % of the total variation in offspring activity. This link between mother and offspring behavior was not mediated by mother size or offspring size at parturition. Our study provides first evidence for the non-genetic transmission of among-individual phenotypic differences that arise despite the apparent lack of genetic or environmental variation, highlighting the potential importance of this variation for evolutionary processes and the adaptability of populations.

Natural populations exhibit complex class structures that profoundly shape evolutionary trajectories. While evolutionary demography provides a formal framework to predict adaptation using invasion fitness, the high mathematical dimensionality of these models often precludes analytical solutions, obscuring biological interpretation and hindering the analysis of long-term evolutionary outcomes. Because current reduction techniques remain fragmented, a unifying theoretical foundation is critically needed. Here, we introduce "structural evolutionary invasion analysis," a systematic framework that integrates two complementary tools to simplify complex life cycles. First, we formulate the "invasion determinant," an algebraic method that yields a direct scalar condition for mutant invasion. Second, we develop the Projected Next-Generation Matrix (PNGM), which structurally compresses life-cycle graphs by eliminating secondary classes. We demonstrate that this reduction is mathematically equivalent to separating dynamical timescales, explicitly preserving Fishers reproductive values for the retained focal classes. Crucially, under the standard assumption of weak selection, our synthesized framework guarantees that all properties of evolutionary singularities--including their location, convergence stability, and evolutionary stability--are strictly identical to those derived from the full, unreduced model. Illustrated with diverse ecological examples, this framework provides modellers with a rigorous and tractable toolkit for decoding state-dependent selection in high-dimensional populations.

Trade-offs are central to biodiversity because they prevent the emergence of dominant phenotypes by limiting the simultaneous optimization of multiple fitness components. Yet trade-offs are often difficult to detect empirically when variation in overall performance produces positive correlations that mask underlying constraints. Here we use Pareto fronts--boundaries that capture optimal trade-off solutions--to test for evolutionary constraints on niche-determining traits in phytoplankton, including minimum nutrient requirements, thermal breadth, salt tolerance, and population growth rates. Using experimentally evolved Chlamydomonas reinhardtii populations subjected to nutrient and salt stress, we detected widespread Pareto fronts limiting the joint optimization of growth rate and niche-determining traits, thereby restricting the emergence of multivariate stress tolerance. Importantly, Pareto fronts revealed trade-offs even when underlying trait correlations were positive. We found that the structure of trait covariation behind Pareto fronts strongly predicted evolutionary outcomes: populations moved toward Pareto-optimal phenotypes primarily when trait correlations were neutral or positive, whereas negative trait correlations were associated with limited evolutionary optimization. Extending this framework across phytoplankton diversity, we compiled niche-determining traits for 299 phytoplankton taxa. At a macroevolutionary scale, we detected significant Pareto fronts constraining the evolution of niche-determining traits in phytoplankton. These fronts, however, did not always recapitulate the structure of trade-offs evident among C. reinhardtii populations, suggesting that forces that dictate microevolutionary outcomes, such as genetic correlations, can be resolved across macroevolutionary time. Together, our results highlight that evolutionary trajectories may differ across scales, but that fundamental limits on multivariate trait optimization persist across phytoplankton. Significance StatementTrade-offs among biological traits are central to evolutionary theory but often prove difficult to detect empirically. Here, we apply Pareto fronts--a framework borrowed from economics and engineering--to detect and reveal trade-offs among key niche-determining traits in phytoplankton. By combining experimental evolution in the laboratory with a synthesis of ecological traits across 299 taxa, we demonstrate widespread limits on the simultaneous optimization of growth rate, nutrient competition, salt tolerance, and thermal breadth. Importantly, Pareto fronts reveal trade-offs even when conventional correlation-based approaches fail, uncovering evolutionary constraints that remain hidden in trait correlations. These results show that trade-offs shape phenotypic variation across both micro- and macroevolutionary scales and impose fundamental limits on phytoplankton responses to multiple environmental stressors.

Resource availability is a central driver of ecological and evolutionary processes, yet its effects on infectious disease and virulence are not fully understood. A key limitation is that many studies consider only a narrow range of resource conditions or a limited subset of host and pathogen traits, potentially obscuring non-linear relationships. Here, we quantify how a gradient of six food levels simultaneously shapes host fitness and pathogen performance in the Daphnia magna- Ordospora colligata system. Across two laboratory experiments, we measured infection rates, pathogen burden, host fecundity, survival, and filtration rates. Increased food availability enhanced pathogen fitness, with both infection rates and spore burden increasing with provisioning. In contrast, host responses were trait-specific: while fecundity increased with food availability, pathogen-induced reductions in fecundity (i.e., virulence) peaked at intermediate resource levels, despite continued increases in pathogen load. This pattern indicates that resource availability alters host tolerance as well as pathogen growth, generating non-linear disease outcomes. Host survival was unaffected by either food provisioning or infection, further demonstrating that resource availability can simultaneously influence host and pathogen traits in different directions. Our results highlight the importance of integrating multiple fitness components across provisioning levels to understand disease dynamics and suggest that ongoing anthropogenic changes in resource availability may alter host-pathogen interactions.

Genetic evidence for fluctuating selection has begun to accumulate for different species over the past few decades, especially for the Drosophila genus where studies have reported hundreds of loci undergoing putatively adaptive oscillations across successive seasons. However, most theoretical and simulation studies of fluctuating selection have relied on abstract or weakly parameterized models, making it difficult to assess their relevance for natural populations. In this study, we simulate multilocus seasonally fluctuating selection under a recently developed model and examine its effect on the variance effective population size (Ne) at a genome-wide scale. By recapitulating genomic, demographic, and evolutionary parameters from natural Drosophila populations in our simulations, we were able to reproduce allele frequency oscillations reported in recent studies and show that these lead to [~]50% genome-wide reductions in Ne. We also demonstrate that Ne reductions are well predicted by the maximum frequency amplitude among all adaptively fluctuating loci, and that the frequency amplitudes are largely determined by the number of adaptively fluctuating loci and the strength of their epistatic interactions. Our results demonstrate that fluctuating selection can substantially reduce effective population size and underscore the importance of temporally variable selection in shaping genome-wide patterns of variation beyond classical models. Article SummaryGenetic studies of fluctuating selection in natural populations have grown steadily over the past decade, with reports suggesting that hundreds of loci undergo adaptive oscillations over seasonal timescales in cosmopolitan Drosophila populations. By simulating seasonally fluctuating selection under a recently developed model and ecological scenarios informed by published studies, the authors show that this mode of selection can reduce effective population size by [~]50%, with the magnitude of the reduction correlated with the locus exhibiting the largest allele frequency fluctuations. These findings highlight fluctuating selection as an important factor shaping genome-wide patterns of genetic variation and effective population size.

Phenotypic diversity is often thought to arise from the evolutionary modification of developmental processes. However, developmental processes are tightly coupled in space and time, with each process beginning from conditions set by the one before it. While we know from dynamical systems theory that initial conditions can significantly affect a systems out-come, their importance as a source of phenotypic evolvability has been largely overlooked. Here we show for the first time, that phenotypic evolution can proceed through changes in developmental initial conditions while the underlying developmental process remains conserved. Somitogenesis is the process by which vertebral precursors, known as somites, are periodically patterned in the pre-somitic mesoderm (PSM). Somitic count (total number of somites) is thought to diversify through the evolution of components of somitogenesis such as the tempo of the segmentation clock or the mechanisms driving axial morphogenesis. Using two closely related species of Lake Malawi cichlid fishes that differ in vertebral counts, we show that somite count evolution has happened without changes to somitogenesis itself, but instead, by altering the size of the PSM at the onset of this process. This work will expand what we consider developmental drivers of phenotypic evolution and highlight the importance of comparative studies to understand the diversification of phenotypes.

Theory suggests that different components of environmental fluctuations, from daily and seasonal cycles to multidecadal trends, can have distinct and even opposing effects on species abundances and community dynamics, depending on their specific adaptations. But empirical research that deconstructs the influence of these different cycles on communities is lacking. Here, we used long-term biological monitoring data together with flow records of rivers across New Zealand to (i) investigate the role of fast, slow, and seasonal river-flow fluctuations in structuring macroinvertebrate communities; and (ii) to assess whether life-history and mobility traits mediate the response. Using joint species distribution models, we found striking differences in taxon and community responses to the different components of river flow variation. Responses to slow fluctuations were generally stronger and better predicted by traits, while responses to seasonal fluctuations were highly heterogeneous. Fast increases in flow, typical of flooding events, had pervasive negative effects on species abundances, but the severity of impact partly depended on mobility traits. Our results suggest that different ecological mechanisms underpin the response to distinct environmental fluctuations, highlighting the value of jointly considering multiple temporal scales of variation and species functional traits to understand and predict how communities reorganise under fluctuating environmental regimes.

The phenotypic effects of mutations often depend on the genetic background, yet general patterns remain poorly resolved. Here, we tested whether genotypes drawn from the same natural population, but differing in their breeding values for a polygenic trait, differed in their contribution of new mutational variation to that trait. We established >200 mutation-accumulation (MA) lines from four Drosophila serrata genotypes. Analysing >44,000 wing-size measurements, collected over 30 generations, we quantified mutational variance and mutational bias for size. Genotypes with the smallest and largest breeding values for size contributed similar (statistically indistinguishable) amounts of mutational variance. In contrast, the genotype with an intermediate breeding value exhibited remarkably low (statistically undetectable) mutational variance, low micro-environmental variance, and high line survival over time, consistent with limited mutational decay in fitness. The three genotypes with detectable mutational input showed declines in mean size over time, indicating a consistent mutational bias toward smaller size, as reported in other taxa. The magnitude of this bias appeared genotype dependent, with the MA populations founded from the larger ancestors declining nearly twice as fast as that founded from the smallest ancestor. Together, these results demonstrate substantial heterogeneity in mutational properties among genotypes within a single natural population where the trait value spans a relatively narrow range. Such genotype-specific mutational input is expected to shape both the standing genetic variance and the evolutionary trajectory of polygenic traits.

Migration is widely recognized as a strategy for animals to track seasonally shifting resources. Yet, seasonal and spatial dynamics of migration are challenging to study, particularly for difficult-to-track insects. Among insects, monarch butterflies (Danaus plexippus) have a well-documented fall migration, but spring breeding recolonization remains poorly understood, particularly for the western population. We conducted multi-year surveys across six regions in the western United States to characterize monarch breeding phenology and evaluate three related hypotheses: (i) the successive broods model, with discrete generations shifting activity across the breeding range, (ii) a diffusion-like expansion model with overlapping breeding periods, and (iii) a mid-summer lull model with temporary summer declines in breeding for areas near the overwintering habitat. Monarch immature presence served as an indicator of local breeding activity. Our results do not support the successive broods or mid-summer lull hypotheses. Breeding onset occurred earlier near overwintering areas and gradually expanded north-and eastward, with sustained activity in many regions throughout the season. Termination of breeding also occurred earlier at more distant sites, resulting in longer breeding activity nearer to overwintering habitat. Immature monarch density declined with distance from overwintering areas at onset and termination, suggesting delayed colonization of peripheral regions. Together, these results support a diffusion-like expansion of breeding rather than sequential generational replacement. Western monarchs also do not initiate or terminate breeding in close synchrony with host plant availability, contrary to predictions from resource-tracking theory. These findings highlight fundamental differences between western monarch breeding dynamics and paradigms for eastern monarchs, demonstrating that a single species can employ fundamentally different spatial strategies for recolonizing its breeding range in different regions. More generally, these results distinguish insect migration from systems with direct movements between wintering and breeding habitats, and underscore the value of long-term, landscape-scale monitoring for resolving habitat use across heterogeneous environments.

Predator-prey interactions are key drivers of behavioural and life-history evolution, yet their mechanisms remain difficult to study in natural contexts. The nematode Pristionchus pacificus is a model predator, but most studies exploring its behaviours use Caenorhabditis elegans as prey, a species that it likely only rarely encountered in nature. Here, we examine predation within nematode communities associated with beetle carcasses, the native necromenic habitat of P. pacificus. We identify Oscheius myriophilus as a cohabiting species, likely representing natural prey. Using predatory assays, automated tracking, and machine-learning-based behavioural analysis, we show that P. pacificus actively kills and consumes O. myriophilus. Strikingly, predation rates are lower than those observed for C. elegans, suggesting partial resistance or reciprocal adaptation in O. myriophilus. Consistent with this, O. myriophilus exhibits a mixed reproductive strategy, with early oviposition followed by ovoviviparity and matricide. As later developmental stages are more resistant to predation, internal hatching may protect offspring while providing maternal resources for development. These findings establish these nematodes as a tractable model for investigating predator-prey interactions and their evolutionary consequences, highlighting how behavioural strategies and life-history traits can co-evolve in natural communities.

Conspicuous coloration in animals is generally thought to evolve and be maintained through inter- or intraspecific interactions such as mate choice, but this might not always be the case. The sight-line hypothesis proposes that conspicuous light-dark contrast in front of the eyes (hereafter, eyeline) evolves and is maintained due to viability selection, enhancing an individual visual acuity and thus evolutionarily associated with a particular foraging behavior that requires accurate aiming. However, empirical evidence that supports the sight-line hypothesis is virtually absent, with no studies demonstrating the key prediction that the direction of eyelines matters. Here, I tested the sight-line hypothesis using macroevolutionary analyses in terns and allies, which are a suitable study system, because they have variation in facial color patterns, including presence/absence and, if any, various angles of eyelines. They also have a large variation in foraging behavior, including picking, plunge diving, and skimming. As predicted by the sight-line hypothesis, tern lineages that require accurate aiming at foraging (e.g., plunge diving) are more likely to have eyelines. In addition, the evolutionary transition to the state with eyelines and these foraging behaviors was more likely to occur than the reverse transition. Furthermore, as expected by the fact that the direction of travel is upwardly deviated from the direction of the bills during skimming, the eyeline angle from bills was evolutionarily positively associated with the occurrence of skimming behavior. To my knowledge, the current study is the first to demonstrate that the direction of the eyeline matters, thereby strongly supporting the sight-line hypothesis.