Philosophical Transactions of the Royal Society B: Biological Sciences

Humans and other animals live in interconnected social communities that are essential for survival and well-being. In principle, social communities can persist despite changes in constituent members. However, gradually accumulating changes to membership could push systems past critical thresholds into alternate states. We investigated social network dynamics for 443 wild female Asian elephants over 12 years by tracking community membership and structure. Following accumulated demographic turnover, networks fractured into smaller and more isolated social communities. Connections were changed not only due to turnover of members but also rewired among remaining individuals. This provides the first empirical evidence of a social network state change in a long-lived mammal.

Social relationships are strongly linked to health and biological fitness in humans and other animals. For example, social support may buffer individuals against harsh ecological conditions. Reciprocally, better health may allow for greater investment in social relationships. We examined links between health and social behaviour in an endangered population of northern bottlenose whales (Hyperoodon ampullatus). Using photo-identifications spanning 37 years, we visually classified whether individuals had poor body condition on each day they were observed (N = 3,086 whale-days). We then used generalized linear mixed models to explore how body condition varied with sex, age, and within-individual deviations in group size or other social metrics derived from Bayesian social networks. Approximately 11% of individuals were classified as being in poor condition at any time, though the prevalence of poor condition varied across raters and years. Visually assessed condition was successfully validated with morphometric measures, though there was only weak evidence that poor condition predicted apparent survival. Contrary to expectations, whales in poor condition were found in larger groups and had more social partners than their average across the study period. These findings run counter to the expectation that health and social connectedness are positively correlated in social mammals.

Compositional syntax - the ability to combine meaningful units into structured sequences whose overall meaning depends on both the meanings of the parts and their combination - is a hallmark of human language. Recent work suggests that chimpanzees may exhibit similar capacities, raising the possibility that compositionality predates the emergence of language in humans. However, a key challenge has been to exclude simpler explanations in which call combinations are processed as independent utterances rather than integrated structures. Here, we address this issue using a source-manipulation paradigm in playback experiments with captive chimpanzees (n = 6) at the Sigean African Reserve, France. We presented sequences combining alarm and recruitment calls either from a single source (one loudspeaker) or from two spatially distinct sources (two loudspeakers). If sequences are interpreted as independent calls, responses should not differ between conditions. Instead, chimpanzees responded significantly faster when sequences originated from a single source. Bayesian survival analyses confirmed this effect. These results support a non-trivial form of compositionality, whereby the meaning of call combinations depends on their integration into a unified sequence produced by a single individual. Our findings provide experimental evidence that key features of linguistic compositionality may have evolutionary roots in the primate lineage.

Social relationships can buffer individuals against environmental challenges, reducing the physiological costs of disturbance. Assessing how social and environmental conditions jointly shape physiological stress is critical for predicting individual responses to disturbance, particularly in managed populations. We evaluated whether social and environmental stressors act additively or whether social context modifies physiological responses to environmental challenges. We combined behavioural data and faecal glucocorticoid metabolite samples from a small, intensively monitored population of African elephants (Loxodonta africana) in a fenced reserve. Using a Bayesian framework, we tested how social factors interacted with variation in the biophysical environment, including natural environmental and anthropogenic disturbances, to predict glucocorticoid concentrations. Natural environmental variables, including weather, water availability, and season, did not predict glucocorticoid concentrations. In contrast, helicopter use, a common management intervention, was associated with higher glucocorticoid concentrations. Social effects were context dependent. Following disturbance, low-ranking individuals showed higher glucocorticoid concentrations than high-ranking individuals, whereas this pattern reversed under low-disturbance conditions. Individuals with more social connections had lower glucocorticoid concentrations, but this effect was evident only under non-disturbance conditions. Measures of betweenness centrality did not predict glucocorticoid levels. These results demonstrate that social factors mediate physiological responses to anthropogenic disturbance and that management actions can impose uneven physiological costs across individuals. Quantifying interactions between social factors and the biophysical environment may improve conservation and management strategies for social species. Integrating physiological responses to interactions between social factors and the biophysical environment can guide conservation strategies and improve management interventions in social species.

Game theory in biology started as an attempt to model animal contests by making assumptions about the fitness costs individuals pay in aggressive interactions. Among the different approaches, a notable one is to construct mechanistic models, using assumptions about behaviours and cognitive processes. Reinforcement learning is an important cognitive process, and we use it here to model pairwise and coalitional contests. We study situations where territorial neighbours become so-called dear enemies. A defending individual can get help from a neighbour through a defender-neighbour coalition against a challenger attempting territory takeover. In our model, coalition members have an advantage in contests in terms of costs of aggression, with the challenger being exposed to aggression from both members and each member only receiving part of the aggression from the challenger. We find that notable costs of border conflicts between neighbours, together with substantial advantages for coalitions, favour intervention. Neighbours intervene when they can help weaker defenders, in this way avoiding costs of border renegotiation with a new and potentially stronger territory owner. We also introduce different forms of perceived costs into the model, which we show correspond to the range from pure mutual assessment to partial self-assessment.

Global biodiversity recovery demands restoration at landscape scales, where ecological outcomes are shaped not only by habitat amount but also spatial arrangement. Alternative landscape restoration strategies can increase habitat amount, improve quality, and alter configuration in fundamentally different ways and may therefore vary in their efficiency. Here, we conceptualise five landscape restoration strategies and use a spatially explicit metapopulation framework to compare their ability to increase predicted species persistence across heterogeneous landscapes and trait space defined by dispersal ability and specialisation. We find that restoration outcomes are strongly trait-dependent, with restoration of existing degraded habitats yielding the highest benefits - particularly for specialists. Improvement of the landscape matrix to create low-quality habitat primarily benefits generalists, while strategies creating new habitat patches or enlarging patches provide more consistent but modest gains. These results reveal fundamental trade-offs among restoration strategies and highlight the utility of trait-explicit approaches to inform their implementation and evaluation.

Primates maintain cooperative relationships largely through grooming reciprocity, yet studies disagree on the timescales over which grooming is returned. Part of this disagreement stems from statistical issues: inconsistent definitions of a reciprocation window, combined with the exclusion of unreciprocated grooming, leave the debate unresolved. We still do not know if primates exchange grooming within the short windows predicted by biological market theory or over much longer timescales. Whilst survival analysis can identify reciprocation windows objectively by retaining unreciprocated grooming as censored data, previous studies have applied it inconsistently. This inconsistency leaves the true time frames over which primates reciprocate grooming somewhat blurred. Here, we use a statistical approach that addresses these problems to examine grooming reciprocity in crested macaques (Macaca nigra), a socially tolerant macaque species. We applied survival analysis to identify each group's short-term reciprocation window without imposing arbitrary cut offs, and Bayesian survival models to test whether social bond strength and eigenvector centrality predicted reciprocation latency. Short-term reciprocation occurred rarely (29% of events in one group and 5% in the other); most reciprocation occurred over longer timescales than previous research commonly assumes. Stronger bonds predicted faster reciprocation; this finding suggests that crested macaques express social investment in valued partners through how promptly they return grooming, meaning that the timing of exchange carries information about relationship value. Eigenvector centrality showed no credible effect, though our small sample size and dense groups prevent us from interpreting this outcome more robustly. Substantial variation between dyads remained unexplained, pointing to partnerspecific properties we have yet to identify. These findings caution against assuming that reciprocity operates over short windows. They show that social predictors, such as bond strength, remain essential to understanding when primates return grooming. This work provides a baseline for testing whether grooming is exchanged for other social commodities, and for comparing reciprocation timescales across macaque species that differ in social tolerance.

A central question in ecology and evolution is determining when environmental challenges translate into stress and biological harm. Human-derived pollutants are often assumed to be inherently damaging; however, their effects may depend strongly on ecological and physiological context. Microplastics exemplify this complexity, eliciting heterogeneous responses across taxa rather than uniform toxicity. Here, we synthesise evidence from 14 meta-analyses encompassing 9,101 effect sizes to identify the conditions under which microplastic exposure leads to damage, neutrality, compensation, or stimulation. These syntheses reveal clear negative effects alongside frequent neutral outcomes and occasional stimulatory responses. Microplastic effects vary with particle characteristics and exposure conditions and are strongly moderated by species-specific traits and life stage. We further argue that plasticity in the gut and in behavioural and physiological traits may buffer microplastic effects. Emerging evidence also indicates that biofilm colonisation alters the physicochemical and biological properties of microplastics, potentially modifying their ecological interactions and toxicity profiles. By reframing microplastics as context-dependent challenges rather than universally toxic agents, we provide a conceptual framework for understanding animal responses under realistic ecological conditions and identifying the biological and environmental contexts in which microplastic exposure is most likely to result in harm.

The evolution of genome size and eukaryotic genome organisation has puzzled evolutionary biologists for decades. Are differences in DNA content and protein-coding capacity of eukaryotic genomes a result of natural selection, or neutral processes? If they were shaped by natural selection, which features might be connected with these differences: cell volume, ecological strategy, availability of nutrients, etc.? Kinetoplastids are protists with compact nuclear genomes that almost entirely lack introns, but whose mitochondrial DNA content (kDNA) can rival that of their nuclei. We hypothesised that the reduction in non-protein coding nuclear DNA content during the evolution of kinetoplastids is connected with an increase in kDNA content: species with larger fractions of total cellular DNA that is allocated to kDNA will have concomitantly smaller fractions of non-coding DNA in the nuclear genome. We developed a framework for estimation of DNA content in both the mitochondria and nuclei from quantitative fluorescence microscopy data, and inferred the fraction of non-coding DNA in nuclear genomes based on the combination of transcriptomic and fluorescence imaging data. Across 10 genetically distant isolates from diverse free-living kinetoplastid lineages, there is indeed a trend towards a lower proportion of non-protein-coding nuclear DNA when kDNA proportion is higher relative to the total DNA in the cell. This observation is consistent with the hypothesis that in free-living kinetoplastids, mitochondrial and nuclear genomes might co-evolve in terms of their DNA content. This finding raises the possibility that natural selection acts on genome size evolution in kinetoplastids, and contributes evidence and methodology to address this question more broadly in eukaryotes.

Health inequalities are often examined through single axes such as class or ethnicity, obscuring how these dimensions interlock. This study applies a longitudinal intersectional approach to examine physical and mental health trajectories across five generations in the UK. We analysed 14 waves of the UK Household Longitudinal Study (2009-2024) using longitudinal Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). We modelled SF-12 physical and mental health trajectories for 398 intersectional strata defined by gender, ethnicity, occupational class, and generation. Physical health inequalities widened with age, consistent with cumulative disadvantage, while mental health inequalities were more evident among later-born cohorts. The 'Boomer' generation exhibited a relatively flat mental health trajectory across its observed age range. In contrast, 'Generation Z' had lower predicted mental health, particularly among White British women with no work history - a group with poorer predicted trajectories than their South Asian peers. Our study shows how health inequalities are structurally differentiated by cohort and intersectional position. Policy responses should support proportionate universalism, combining broad population-level support with intensified action for groups showing poorer health.

Hunting for mobile prey is thought to have played a key role in hominin evolution, by providing high-quality nutrition that supported the development of the exceptionally large human brain. However, human-prey dynamics remain poorly understood because studies have not yet tracked human foragers and their prey simultaneously. Here, we employ high resolution tracking of groups of human foragers (ice-fishers) and their prey (fish shoals) to study human-prey dynamics. Our results show that foragers adaptively combined personal and social information in deciding where to forage and for how long, closely matching the prey distribution. Prey responded dynamically to human exploitation, showing increased attraction to fishing activity, alongside decreased biting probability. Furthermore, we found that foragers adaptively relied on memory, preferentially returning to areas with high prey presence, particularly when their current return rate was low. Our results show how human foragers overcome the challenges of extracting invisible, mobile and reactive prey by tightly tuning patch-selection, patch-leaving and patch-return decisions to the distribution and behaviour of their prey.

1. Adaptive behavioural strategies require animals to simultaneously navigate social and ecological domains across multiple spatial and temporal scales. Although drones and computer vision have recently transformed the study of wild animal societies, many nocturnal species and those occupying structurally complex habitats remain inaccessible to these approaches, limiting our understanding of behaviour in natural settings. 2. We aimed to determine how behavioural strategies are organised across nested spatial and temporal scales within a wild communication network. 3. We used three-dimensional acoustic localisation and source separation to track individual male Hyperolius sp. A, a nocturnal African reed frog, within a natural rainforest chorus and quantify patterns of site fidelity, movement, spatial organisation, and call-timing interactions. 4. Males exhibited significant site fidelity across nights, while chorus spatial structure varied with local caller density. Within nights, individuals followed a stereotyped behavioural sequence, descending from elevated arboreal refugia before settling into lower calling positions near breeding sites. At finer temporal scales, call-timing interactions varied according to both local competitor density and the proximity of neighbouring rivals. 5. These findings demonstrate that behavioural strategies emerge across nested spatial and temporal scales and that long-term spatial positioning, short-term movement decisions, and moment-to-moment signalling interactions are tightly linked within natural communication networks. More broadly, acoustic localisation provides a powerful framework for studying behaviour in species and habitats that remain difficult to observe using conventional approaches.

Categorical rhythmic patterns are fundamental features found in language and music across cultures. In humans, these rhythmic patterns occur in both vocal production and perceptual preference, highlighting a link between rhythmic production and preference. Categorical rhythmic patterns have recently been identified in animal vocalisations too, but whether rhythm production is linked with rhythmic preferences in non-human animals remains unclear. Within this context, zebra finches (Taeniopygia castanotis) are of particular interest, as both sexes develop a song preference, and their song has been suggested to exhibit an isochronous temporal structure. Here, we tested for the first time whether zebra finches prefer songs containing discrete rhythmic patterns, using operant preference tests with either two or four rhythmic patterns. Our results show that no categorical rhythmic pattern was consistently preferred across the population, although responses varied among individuals. These findings indicate that categorical rhythmic patterns are unlikely to be a primary driver of song preference in zebra finches. Together with previous work in other vocal-learning birds, our results suggest that preferences for categorical rhythmic patterns may not be universal and could instead reflect species-specific features of vocal displays rather than the rhythmic categories characteristic of human music.

Artificial intelligence (AI) assistants can improve individual performance but may weaken unaided performance and limit interest diversity, raising questions about their long-term effects on collective intelligence (CI). Here, we consider an evolutionary model in which individuals predict, consult AI, and imitate better-performing peers. Classic reward structures that promote CI without AI can fail under Chatbot AI, whose predictions depend on users' interests, by reducing interest diversity or propagating bias. Directly rewarding or penalizing AI use does not reliably mitigate these effects. Instead, a balanced incentive that preserves minority expertise and rewards collective contributions can promote CI, but an additional incentive is needed to restore unaided collective accuracy. Our framework offers an explanation for emerging evidence of AI's societal impact and clarifies its long-term implications.

Schooling is a widespread behaviour among pelagic fish that reduces locomotion costs of migration and predation risk. It is characterised by coordinated movements, speed and orientation of group members. Although schooling can vary both between populations and among individuals of the same population, these levels of variation are seldom considered together. Here, we investigated whether schooling tendencies in three-spined sticklebacks (Gasterosteus aculeatus) vary between populations and among individuals within-populations depending on their phenotype. We first compared the schooling behaviour of anadromous (migrants) and recently landlocked (residents) populations and tested whether individual sociability explained within-population variation in schooling. We then studied whether schooling behaviour is modulated when migrants and residents are in mixed groups. Migrant groups displayed better schooling performance than residents with higher alignment. Within migrant groups, less social individuals displayed more leadership, were better aligned, swam closer to others and fatigued less than more social fish. These patterns were absent in residents. When the two populations were mixed, overall schooling performance declined, particularly in migrants, with schools exhibiting reduced compaction and alignment, resembling resident groups. Thus, individuals did not modulate their schooling behaviour to the group social composition and phenotype-dependent schooling patterns were disrupted in migrants when mixed. These findings suggest that migration-related behaviours can disappear quickly post-isolation. They also highlight the importance of individual sociability in self-organisation and shaping collective behaviour, especially in populations that retain migratory behaviour. Considering behavioural variation across multiple hierarchical levels is thus key to understanding complex social systems.

Ecological responses to environmental stressors are increasingly shaped by interactions among anthropogenic and climatic drivers, yet the influence of prior exposure history on subsequent stress responses remains poorly integrated into multiple stressor ecology. Using the blue mussel (Mytilus edulis) as a model system, we experimentally tested whether prior exposure to environmental nanoplastics modifies responses to subsequent stressors, including copper contamination, nutrient enrichment, and salinity fluctuations, individually and in combination. Nanoplastic pre-exposure reduced survival across subsequent treatments and altered stressor interaction outcomes at the community level, shifting responses toward synergistic effects that amplified metabolic costs. These results demonstrate that exposure history can modify both the magnitude and direction of multi-stressor effects, with consequences extending beyond individual performance to ecosystem functioning. By incorporating temporal exposure dynamics into multiple stressor research, our study highlights how ecological responses to global change depend not only on the identity and intensity of stressors, but also on prior environmental conditions shaping subsequent organismal and ecosystem health status and responses.

Short-term population dynamics are shaped by both external environmental stochasticity and endogenous ecological dynamics. The extent to which population trajectories maintain predictable temporal structure reflects underlying determinism and sets limits on inherent forecastability. Permutation entropy quantifies this intrinsic predictability using the relative frequency of short fluctuation motifs. However, requirements for long timeseries have restricted ecological applications. Here, I introduce a Bayesian hierarchical regression framework, incorporating entropy-neutral priors, that estimates expected permutation entropy from shorter, spatially-distributed ecological datasets. I validate the approach's capacity to detect the impact of increasing environmental variance through simulations. Applied to four decades of UK butterfly data, the approach identified increasing permutation entropy across 35 species, consistent with an increasing role of stochastic weather events. Outlier weather events did not have a consistent relationship with permutation entropy, highlighting the potential for environmental forcing to both disrupt and constrain trajectories. With this flexible approach, permutation entropy offers complementary perspectives on longstanding questions around forecasting and population dynamics.

Complex biological behaviours often emerge when a system is faced with mutually incompatible priorities. In such situations, the field of multi-objective optimisation can provide an informative and predictive theoretical foundation for biology. Here we adopt this paradigm in exploring the rich dynamic behaviour of mitochondria inside cells. Using plant cells as a model system, we use physical modelling to characterise the "morphospace" of possible mitochondrial behaviours, and single-cell microscopy with video analysis and network modelling to characterise collective mitochondrial dynamics. We show that wildtype Arabidopsis mitochondrial dynamics near-optimally resolve a tradeoff between maintaining physical spacing and supporting biomolecular exchange. With existing and new experimental data, we show that these dynamics adapt under mutational and chemical challenges to support a rebalanced, but still near-optimal, resolution to this tradeoff under different densities of the mitochondrial population. We also show how an assumption of multi-objective optimisation supports inference of biological mechanisms before any data are observed, and discuss the potential of this multi-objective optimisation paradigm to form a broader theoretical framework of spatial cell biology.

Phage therapy is providing a benefit to a limited number of people. To date those who have received phage therapy typically have done so via an IND expanded access mechanism, colloquially referred to as compassionate release, new clinical trials are underway, and the advent of phage therapy seems to be at hand. However, a recurring question remains, which phages to use for which bacteria. By understanding how a phage interacts with its bacterial host we will move closer to being able to provide an answer to this pressing question. By using bacterial single cell RNA sequencing (scRNAseq) during phage infection we can look at the most fundamental interaction between the phage and its host. We have observed phage gene expression consistent with well described expression profiles seen in bulk expression data. Phage genes in our scRNAseq data followed the early, mid, and late gene expression profile. Using a machine learning algorithm (Support Vector Machine) we were able to distinguish time of infection from phage genes. We also observed that phage infection is likely not random. When infected with two genetically distinct phages the likelihood of finding both inside a single cell was not consistent with Poisson distribution.

Spiders arrest their fall by abseiling on dragline silk, varying silk release rate to avoid excessive strains that could break the thread. To understand how this is achieved, we develop a minimal dynamical model of abseiling and formulate a time-optimal control problem subject to physical limits on silk strain and dragline spinning rate. We find that the optimal trajectory includes an interval over which the strain is constant, resulting in uniform deceleration consistent with published experiments. To test the generality of this strategy, we then turn to a distinct extreme motor behavior seen in jumping spiders: using a dragline anchored at the takeoff site to correct their orientation while jumping at speeds exceeding 100 body lengths per second. We show that the same constant-strain strategy suffices to counteract the initial body rotation and ensure an upright landing without significant loss of range. Together, our theoretical framework suggests how strain regulation may serve as a strategy for controlling extreme movements such as abseiling seen in many spiders and may be specialized to tasks such as aerial braking and reorientation in jumping spiders.