Philosophical Transactions of the Royal Society B: Biological Sciences

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.

Aims: Antimicrobial peptide (AMP) combinations have been proposed to delay resistance evolution, but it remains unclear what properties of a peptide pair determine whether a combination reduces resistance evolution relative to its component AMPs used alone. One suggested factor is mode of action, yet this has rarely been tested experimentally. In the current study we have asked whether mode of action or physicochemical similarity between peptides better predicts which combinations delay resistance. Methods: We evolved Staphylococcus aureus with six AMPs with reported membrane-targeting and intracellular-targeting activity, individually and in all 15 pairwise combinations. We quantified resistance evolution, cross-resistance and fitness costs across the full AMP panel, and performed whole-genome sequencing on 126 evolved lineages. Results: Resistance varied across AMPs and correlated with peptide chain length, not mode of action. Cross-resistance was associated with physicochemical similarity, and similar peptides selected for overlapping mutations. Most combinations reduced resistance relative to single-AMP treatment, but those whose components shared cross-resistance were less effective, channeling evolution into convergent trajectories that resolve both selective pressures at once. Notably, mode of action did not predict combination outcome. Conclusions: Cross-resistance, not mode of action, is a key factor in determining AMP combination efficacy. Physicochemical distance between peptides may serve as a practical predictor for cross-resistance, enabling selection of AMP combinations that are more likely to constrain resistance evolution.

Transposon insertion sequencing (Tn-seq) has become a powerful tool for assigning gene fitness and essentiality in bacteria, and has recently been extended to bacteriophages. A core but rarely examined assumption of these screens is that fitness is measured in an asocial environment, where each mutant succeeds or fails on its own. Yet many genes act socially: their products can be shared among neighbors, allowing defective mutants to be complemented in trans. In phages multiple genotypes routinely coinfect the same cell. Here we show that social interactions distort gene essentiality. Using paired quorum-sensing microarray and Tn-seq data from Pseudomonas aeruginosa, we find that quorum-sensing-regulated genes are over-represented among genes scored as non-essential, confirming that social genes are under-reported as essential. We then build a stochastic, agent-based model of phage Tn-seq across an MOI gradient, assigning each gene an intrinsic fitness effect and a complementation fraction. Complementable ("social") genes rise in frequency as MOI increases, masking their true fitness cost, whereas non-complementable ("private") genes, do not. Partitioning genes by life-cycle stage and applying a two-round high-then-low-MOI design, further separates gene functions by life cycle stage. We argue that deliberate MOI manipulation turns a confound into a tool, enabling systematic classification of phage sociality.

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.

The deepest ocean is one of the most extreme environments for life on our planet, combining near-freezing temperatures, low oxygen levels, and hydrostatic pressures reaching 111 MPa (1100 atm). Extreme pressures are predicted to alter many aspects of biology, including the physical properties of biological hydrogels, protein structure, and the solubility of gases in water. How organisms have adapted to live in these conditions is poorly understood. Studying these organisms in situ is difficult and requires specialized deep-sea equipment capable of withstanding the extreme pressure; raising these organisms in captivity is also challenging due to their extreme habitat requirements. Given these difficulties in studying deep-sea organisms, we set out to identify the problems shallow-dwelling organisms face due to increased pressure. These can provide insights into how organisms tolerate life in the deepest parts of the ocean. This project aims to take embryos of the shallow-dwelling aquatic organism Xenopus laevis, determine how surface-dwelling organisms fail under high hydrostatic pressure, and identify a means to survive this deadly pressure. We have designed a system to expose different embryonic stages of X. laevis to high pressures and observe its effects. After identifying the limits of survivability, we sought to understand how these embryos can acclimate to changing pressures. Comparative RNA-seq and cross-species analyses revealed a conserved, pressure-induced transcriptional response across phyla, with the heat shock pathway among the most strongly activated. Pre-activation of this pathway via prior pressure or other stressors enhances survival under otherwise lethal hydrostatic conditions.

Principles of collective motion are now well established, though research has largely focused on homogeneous groups. Heterogeneity is widespread in animal groups, e.g. arising from sex, size or even species, raising a central question: can collective behaviour emerge when individuals have distinct behaviours? Here, we combine experiments and modelling to investigate mixed-species collective motion using two closely related fish species, rosy barbs and tiger barbs. In conspecific groups, both species exhibit collective motion, but they differ strikingly in their intrinsic movement: tiger barbs exhibit slowand fast-swimming, whereas rosy barbs display fast swimming only. Despite this difference, these species readily form mixed-species schools where the slow swimming speed of tiger barbs disappears, and the collective motion is dominated by a single fast-swimming mode. We develop an individual-based model incorporating local interactions involving speed matching. Our model demonstrates that bimodal speed in conspecific schools of tiger barbs is an emergent property that is lost in mixed-species groups. Additionally, despite high cohesion, we observe spatial sorting of the two species within the mixed-species groups, which our model explains through differences in inter- and intra-specific interactions. Our results provide experimental evidence that canonical principles of collective motion extend to heterogeneous mixed-species groups.

Super-Recognisers show exceptional ability in face recognition, providing a natural model of how perceptual systems optimise for individuating visually similar stimuli in variable viewing conditions. However, the neural representations supporting this extreme perceptual expertise are unknown. Here, we tested whether Super-Recognisers (n = 23) differed from typical recognisers (n = 21) in the dimensional organisation of neural face identity coding. We recorded 64-channel electroencephalography while participants viewed random and rapidly-presented sequences containing 10 naturally varying images of 40 unfamiliar identities. Using time-resolved representational similarity analysis we measured the geometry of identity representations, their consistency across observers, and how clearly they specified face identity. Although neural expression of identity information was robust in both groups, we found three key differences between Super-Recognisers and typical recognisers. First, the geometry of face identity representations differed between groups. Second, Super-Recognisers showed greater inter-individual consistency in representational geometry. Third, Super-Recognisers' neural signals discriminated between face identities more strongly than those of typical recognisers. Differences in the coding of broader face categories (sex, age, ethnicity) were notably weaker, suggesting that the observed group differences reflected fine-scale differences in identity coding rather than global reshaping of representational geometry. Strikingly, all three differences emerged within a common mid-latency interval (~300-500ms), implicating higher-stages of face processing associated with representations that are sensitive to face familiarity and link between perceptual and semantic domains. Together, these findings indicate that individual differences in face recognition ability reflect higher-level differences in neural identity coding, rather than enhanced early sensory processing.

Phage therapy offers a promising solution to the antimicrobial resistance crisis. However, a major concern preventing the adoption of phage therapy is the potential for unintended consequences of phage release; both in regard to preventing the spread of phage resistance, and the proliferation of a non-endemic virus into the microbial ecosystem. Conditional replication (biocontainment) of phages through bioengineering may address these concerns, but the impact on bactericidal efficacy is unknown. Here, we created a biocontained T7 phage (T7{Delta}capsid) lacking the major structural capsid gene, gp10AB, that can only replicate on Escherichia coli strains expressing gp10AB in trans, and assessed its bactericidal efficacy compared with wild-type T7. Congruent with model predictions, T7{Delta}capsid was only able to clear a well-mixed culture of E. coli at a multiplicity of infection (MOI) of 10 or higher, whereas wild-type T7 prohibited growth at an MOI of 0.1. The reduction in efficacy was more evident in a complex structured environment within a microfluidic device, where phage success depends on its ability to penetrate a microbial niche via propagation. In this environment, T7{Delta}capsid was unable to propagate into the bacterial population and unlike wild-type T7, had no impact on the population's growth. This study shows that whilst biocontainment of phages may improve the biosafety of phage therapy, it comes at the cost of its propagation efficacy and niche penetration in relevant environments.

True crabs (Brachyura) are among the most iconic marine arthropods, representing noteworthy examples of morphological and ecological disparity. A striking feature of brachyurans are their anterior pincer-like appendages: chelipeds. These structures showcase a large diversity of morphologies that reflect ecology and overall multifunctionality. Yet, a comprehensive assessment of appendage functional morphology within phylogenetic and ecological trait contexts has never been attempted. By combining 3D geometric morphometrics, finite element analyses, multilocus molecular phylogeny, and ecological trait data for 80 crab species, including three fossil forms, we unveil a complex evolutionary history for crab chelipeds. Despite extreme shape diversity amongst chelipeds, stress distributions are very similar across taxa and hint a many-to-one pattern. High concentrations of chelipeds within constrained morphospace regions associated with peak pinch forces illustrates that brachyuran morphologies optimised for shell crushing may have arisen in the Cretaceous. Deviations from this morphospace highlight the diversification of non-shell-crushing life modes and the influence of sexual selection on appendages. Neither cheliped shape nor pinch force show phylogenetic signal. Together these results indicate that the evolution of cheliped shape is closely associated with, and inferred to have been strongly influenced by, crab ecology, biomechanical needs and sexual selection. SIGNIFICANCE STATEMENTChelipeds, the pincer-like claws of crabs, are among the most morphologically diverse appendages within Arthropoda, yet the evolutionary forces driving this diversity remain poorly understood. By integrating 3D geometric morphometrics, biomechanical modelling, molecular phylogeny, and ecological data across 80 crab species including fossil forms, we demonstrate that cheliped morphology is driven by ecology, biomechanical demands, and sexual selection rather than phylogenetic relatedness. The multifunctionality of these structures produces strong evidence for many-to-one mapping of form to function. Morphologies optimised for durophagy appear to have originated in the Cretaceous, with subsequent diversification into manipulative and sexually selected forms from a morphologically flexible foundation. These findings demonstrate that cheliped diversity reflects a complex interplay between ecological specialisation, biomechanical optimisation, and sexual selection across Brachyura.

Speech and music consistently differ in their acoustic rhythms, despite the cross-cultural diversity in their surface forms. Here, we investigate whether speech and music rhythms are rooted in distinct intrinsic timescales of the sensorimotor system, which are separately recruited to support individual communication and group synchronization, respectively. Corpus analysis revealed that the timescales dominating speech (4-8 Hz) and music rhythms (< 2 Hz) separately emerge in infant laughter, babbling and cries, and that both speech and song rhythms mature at about age three. The functional division between the two timescales is further probed through sensorimotor synchronization experiments, in which participants vocalize or tap to sound sequences presented at different rates. The rhythm produced by individuals is strongest between 4 and 8 Hz. In contrast, the produced rhythm is best synchronized among participants below 2 Hz. Collectively, these findings reveal two characteristic timescales in the human sensorimotor system, i.e., a faster (4-8 Hz) timescale reflecting resonance in individual production and a slower (<2 Hz) timescale that fosters interpersonal synchronization. The two timescales provide plausible biological basis for the rhythms of speech and music.

Collective animal behavior occurs in high-stakes contexts where failing to coordinate effectively with group-mates can spell disaster for individuals. Yet, identifying instances of coordination failure is challenging, meaning their evolutionary effects remain mysterious. Synchronous calls in alternating frog choruses (i.e., inadvertent signal collisions) are unambiguous failure events that impose steep attractiveness costs. We modeled tungara frog chorusing dynamics to reveal the sensorimotor and social mechanisms underpinning synchrony. Ultimately, inter-male variation in two key sensorimotor attributes, the periods of male calling rhythms and call latencies, generated divergent synchrony engagement patterns. Modeling female preferences revealed that these varied behavioral outcomes then yielded disparate attractiveness consequences. By mechanistically linking the causes and consequences of coordination failure, we demonstrate that non-random failure patterns in collectives generate selection gradients that refine sensorimotor tuning.

Background: Public services are increasingly delivered through digital platforms. Although digital health may improve access and scalability, they may also widen inequalities for people who lack reliable access, confidence, skills, affordability or trust. Objective: This study examined the prevalence of self-reported digital exclusion among UK veterans and assessed its association with depression, anxiety and loneliness. Methods: A cross-sectional online survey was conducted between July 2025 and March 2026. Participants were UK Armed Forces veterans and resident in the UK. The survey collected sociodemographic, military service, digital access and health data. Self-reported digital exclusion was defined as reporting feeling excluded or disadvantaged due to lack of digital access or skills. Probable depression, anxiety and loneliness were assessed using the PHQ-2, GAD-2 and three-item UCLA Loneliness Scale, respectively. Associations between digital exclusion and each outcome were examined using adjusted multivariable logistic regression. Results: Of 1,911 responses received, 1,607 were included after data quality exclusions. Among participants with valid responses to the primary digital exclusion item, 553 (41.7%) reported digital exclusion. Digital exclusion was more common among females, younger veterans and those with lower household income. Probable depression, anxiety and loneliness were more prevalent among digitally excluded participants than among non-excluded participants. In adjusted models, self-reported digital exclusion was associated with higher odds of probable depression (AOR 1.38; 95% CI 1.04 to 1.83; p=0.028), probable anxiety (AOR 1.63, 95% CI 1.23 to 2.16; p<0.001), and probable loneliness (AOR 1.85; 95% CI 1.43 to 2.40; p<0.001). Conclusion: More than two-fifths of veterans with valid exposure data reported digital exclusion, despite high reported device access and confidence. Self-reported digital exclusion was associated with poorer mental health and loneliness, although causality cannot be inferred from these cross-sectional data. Digital-first services for veterans should include routine digital needs screening, targeted support and clear non-digital routes to care.

Tactile sensing enables humans and animals to detect and discriminate features during exploration and guide context appropriate actions. Compared to conventional touch sensors, sensing of tactile features in animals is fundamentally event-based through spikes. Yet how sensor mechanics shape spike activity for tactile perception is not well understood. Inspired by the American cockroach--an insect touch specialist--we developed a neuromechanical framework that linked antenna passive mechanics, mechanosensory encoding, and spike-based computation. A physics-based model of antenna bending simulated spatiotemporal strain patterns during contact, which were encoded into spike trains through a strain-to-firing mapping calibrated against electrophysiological recordings. The model captured antennal nerve activity observed in vivo by reproducing key features of population-level neural responses across multiple contact locations and speeds. Compared with conventional threshold-based encoding, the insect-inspired spike encoder preserved the spatiotemporal structure of tactile signals while achieving sparser activity. To establish a link between spiking activity and perception, we trained a spiking neural network to classify contact location and speed directly from the predicted spike trains. The network achieved >95% accuracy with reduced computational demands and enabled rapid discrimination within the first 170 ms of contact, indicating that sparse, event-based codes support fast and reliable tactile perception. Together, these results establish a mechanistic bridge between sensor mechanics and neural computation, revealing how physical interactions shape efficient sensory coding. This integrative framework advances our understanding of tactile perception and provides design principles for energy-efficient, neuromorphic tactile systems. Author SummaryAnimals use touch to explore their surroundings, identify objects, and make rapid decisions. Unlike most engineered touch sensors, which continuously transmit data, biological touch systems communicate through brief electrical signals called spikes. However, how the physical properties of a touch sensor influence these signals remains poorly understood. In this study, we used the antenna of the American cockroach as a model system to investigate how mechanics and neural activity work together during touch. We developed a computational framework that links the way an antenna bends during contact to the neural signals generated by touch-sensitive sensors. By comparing our model with neural recordings from living insects, we showed that it can reproduce key patterns of neural activity observed during tactile interactions. We found that the insect-inspired encoding strategy produces sparse signals that retain important information about where and how contact occurs. These signals enabled a neural network to rapidly and accurately identify contact location and speed while using fewer computational resources. Our results suggest that tactile perception emerges from a close interaction between sensor mechanics and neural processing. Beyond advancing our understanding of animal sensation, this work provides principles for designing energy-efficient touch sensors and neuromorphic robotic systems.

Does the distribution of fitness effects of new mutations vary across the genome? Under the classical Fisher Geometric Model (FGM) we might not expect it to. In FGM, phenotypic traits are envisioned as dimensions of a landscape, with fitness determined by position in the landscape, i.e., the particular combination of traits of an individual. New mutations are represented by vectors that move from an ancestral to a new phenotype. In classical FGM these vectors affect all trait dimensions simultaneously (universal pleiotropy). However, introducing partial and modular pleiotropy into an FGM framework leads to an expectation that parameters of the DFE will vary with mutational pleiotropy-the number of traits affected by individual mutations. Here we address this prediction by investigating whether traits related to mutational pleiotropy, expression level and network connectivity, affect the parameters of the DFE using whole genome data from A. thaliana and C. grandiflora, two closely related Brassica species that vary significantly in their demography and mating system, and therefore, in effective population size and the effects of linked selection. Results were similar across both species. We found that expression level and network connectivity were predictive of the parameters of the deleterious DFE, even once co-correlations among genome biology traits were accounted for. Our results suggest that, across the genome, molecular evolutio(high mutational pleiotropy). nary patterns agree with the predictions of FGM, albeit relaxing the assumption of universal pleiotropy, and that variation in mutational pleiotropy among genes is sufficient to have detectible effects on the DFE. Significance statementHow do the effects of new mutations vary across the genome? If mutations in some genes affect many traits (high mutational pleiotropy), we hypothesise they will be more strongly deleterious, with lower variance in their selective effects. We test this by investigating the distribution of effects of new mutations across genes that vary in features that are related to mutational pleiotropy: expression level, gene network connectivity, and number of associated GO terms. The mean strength and coefficient of variation of selection of new mutations varied across genes with different features in the manner expected by our hypothesis. This demonstrates that important parameters of molecular evolution can vary across the genome with genome architecture.

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.

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.

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.

Transcriptome analyses are widely used for biomarker discovery and to gain insights into normal processes and diseases. Age-related changes in gene expression inferred from RNA-seq are typically reported relative to the transcriptome composition using library-size normalisation. As such, absolute changes in transcript abundance with age remain poorly characterised. Here, using external spike-in normalisation in the Tabula Muris Senis dataset, we quantify age-related variation in total mRNA content and gene expression across mouse cell types. We observe widespread changes in total mRNA abundance, with decreases predominantly in non-immune cell types and increases predominantly in immune cell types. In parallel, the number of genes expressed declines across most cell types, including immune populations. Differential expression analysis based on spike-in-normalised counts identifies genes consistently downregulated across cell types, enriched for functions in RNA metabolism and protein processing. Furthermore, genes downregulated during ageing and during proliferation arrest show partial overlap, suggesting that these transcriptional changes may share regulatory processes. Together, these results are consistent with a general repression of transcriptional and metabolic activity with age, modulated by immune-specific responses. More broadly, our results demonstrate that conclusions drawn from transcriptomic ageing studies can depend strongly on whether gene expression is interpreted in relative or absolute terms, highlighting the importance of absolute normalisation approaches for the analysis of age-related transcriptomic change

In order to feed a growing global population without silencing nature, conceiving agricultural management strategies reconciling yield and conservation goals is key. Using numerical simulations of a metacommunity model, we explore the possibilities for compromise offered by spatial management strategies of farmed areas. Each strategy is characterized by its farming intensity, the proportion of farmed lands and their spatial aggregation. We show that achieving equitable yield-biodiversity compromise is difficult. While conciliatory strategies offering top yield and biodiversity are typically not possible, accepting slightly lower yields (ie, "Pretty Good Yield strategies") allows to recover substantial biodiversity. Such reconciliation possibilities are limited for species with small dispersal. Yield increases mainly through farmland expansion, whereas farming intensity strongly influences biodiversity, increasing it at low intensity before decreasing with further intensification. Finally, we demonstrate that reconciliation is easier if agricultural production relies on biodiversity through ecosystem services.

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.