Royal Society Open Science

Purpose: Impaired balance and fall risk in individuals with respiratory conditions highlight the importance of respiratory-postural integration during upright activity. However, breathing and postural control are often studied separately, limiting understanding of their interaction. Singing imposes concurrent ventilatory and trunk control demands, yet respiratory-postural responses during standing singing remain unclear. We examined the effects of vocalisation and tempo on respiratory-postural responses during standing, and whether age and singing experience moderated these responses. Methods: Eighty healthy younger (18-35yr; n=35) and older ([&ge;]60yr; n= 45) adults completed rhythmically paced speaking and singing tasks at slow, normal, and fast tempos while standing on a force platform. Respiratory rate (RR), mediolateral and anteroposterior sway, peripheral oxygen saturation, and perceived breathlessness were measured. Generalised estimating equations assessed vocalisation, tempo, and their interaction, with moderation by age and singing experience. Results: RR showed a vocalisation x tempo interaction (p<.001), with higher RR during slow speaking and greatest increases during fast singing. Singing increased postural sway relative to speaking, particularly mediolaterally (p<.001), with tempo-related increases in anteroposterior sway (p<.001). Older adults exhibited greater postural sway overall (p values[&le;].040) but similar task-dependent modulation to younger adults. Singing experience attenuated RR increases during fast singing (p=.033) and was associated with greater mediolateral sway (p=.004). Perceived breathlessness increased with tempo but was not associated with vocalisation; SpO2 was unchanged. Conclusions: Standing singing was associated with tempo-dependent respiratory and postural responses. Age and singing experience showed distinct associations with these responses. Task-dependent respiratory-postural coordination appeared preserved among participants.

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.

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.

Diurnal ectotherms in hot and dry ecosystems face an acquisition trade-off between maximizing collective energy intake and minimizing individual exposure time. We employed optimal foraging and thermoregulation models to examine the surface foraging and thermoregulatory strategies of Pogonomyrmex barbatus foragers in response to habitat warming in a tropical deciduous forest. Foraging activity was evaluated using field-based thermal performance curves (fTPCs) for individual foraging speed and collective foraging success. Thermoregulation was assessed through indices of thermal unsuitability, as well as thermoregulatory effectiveness and exploitation. Our results show that afternoon conditions were significantly hotter and drier than those in the morning. Furthermore, the decoupling of fTPCs was dynamic; while the optimal temperature (Topt) for individual foraging speed remained stable at 44 degrees C, the Topt for collective foraging success shifted from 35 degrees C in the morning to 41 degrees C in the afternoon. This shift in foraging strategy, driven by stressful afternoon conditions, was reflected in a transition of the thermoregulatory strategy. Specifically, the probability of foraging activity decreased as thermal unsuitability increased, with a lower baseline in the afternoon. The thermoregulatory exploitation dropped from 94% in the morning to 63% in the afternoon. Based on thermoregulatory effectiveness, foragers transitioned from an active thermoregulatory strategy in the morning to a thermoconformist strategy in the afternoon while foraging on the surface. So, the observed colonies optimized the balance between individual foraging speed and collective foraging success through a thermoregulatory strategy that was primarily spatial in the morning and strictly temporal in the afternoon. A comparison with historical data from the same site reveals a 40% contraction in the total daily foraging window since 2013.

The mechanisms by which organisms extract relevant information from complex sensory signals and use it for decision-making constitute a fundamental issue in biological and cognitive sciences. In social animal societies, individual decision-making is profoundly shaped by information provided by conspecifics. Collective patch-foraging experiments in the laboratory provide a controlled setting in which social information use can be quantified. Here, we consider a go/no-go task in which groups choose between two patches differing in food reward probability. We use agent-based simulations, underpinned by an augmented collective drift-diffusion model, to investigate alternative mechanisms for representing and integrating social information. We consider two representations, continuous (counting representation) and discrete (pulsatile representation), and two integration mechanisms, biasing the decision threshold (threshold modulation) and modifying the accumulated belief (belief modulation), yielding four distinct social models, in addition to a non-interacting model. We first characterize the collective dynamics generated by these models across cognitive parameters and experimental conditions. The temporal dynamics of group accuracy provide informative signatures of the underlying mechanisms. We then assess model selection and parameter identifiability using Bayesian inference and Wasserstein distance minimization, applied to group-accuracy and departure-time distributions. Bayesian inference using distributions of group accuracy provides the most reliable identification across the conditions considered. Importantly, model selection and parameter identifiability are associated with different aspects of collective behavior: model selection is closely linked to the presence of oscillations in the temporal dynamics, whereas parameter identifiability is more closely related to the global accuracy value. Thus, the information available for distinguishing the underlying cognitive mechanisms is not necessarily the same as that required to recover their parameters. Our results further show that identification depends not only on model structure but also on the experimental conditions. Overall, this study provides practical guidelines for identifying socio-cognitive mechanisms in collective foraging experiments.

In camouflage research, field studies provide ecological validity but lack experimental control, and computer-based experimental studies have the opposite issue. Virtual reality (VR) systems could potentially allow researchers to have both experimental control and ecological validity. Here we develop a VR environment using Unreal Engine and present it via a head-mounted display (HMD). The HMD affords binocular depth and therefore a more ecologically valid, three-dimensional environment, whilst still maintaining experimental control. Disruptive camouflage interferes with depth-based cues, making it a good candidate for testing within a VR environment. Disruptively camouflaged moth-like targets were presented to human surrogate predators, and their survivability was measured. We show that VR can be used to measure camouflage effectiveness by replicating existing findings showing that edge-enhanced disruptive camouflage (EE-DC) is more effective than disruptive camouflage (DC) alone. Furthermore, we extend these findings to show that the effectiveness of EE-DC is modulated by the relative contrast of the disruptive patches. Specifically, it is more effective when the contrast difference between the patches is low. Additionally, we considered edge-enhancement in isolation and found that it still provided a camouflage benefit even without a DC component. Search paradigms within an immersive VR experimental framework offer a unique opportunity to evaluate camouflage theory in a rigorous, yet ecologically grounded manner.

Estimating the postmortem submersion interval (PMSI) remains challenging due to complex biological and environmental interactions during aquatic decomposition. This study proposes a reduced mechanistic ordinary differential equation (ODE) model linking tissue degradation, microbial activity, and dissolved oxygen dynamics. Calibrated against the total aquatic decomposition score (TADS) trajectory for Northern Adriatic Sea cases, the model preserves a strictly monotone TADS--time relationship, ensuring unique numerical inversion from observed TADS to PMSI. Synthetic observation experiments evaluated how data selection influences parameter recovery, practical identifiability, and robustness under measurement uncertainty. Microbial measurements improved parameter recovery for microbial dynamics, whereas dissolved oxygen measurements constrained oxygen-consumption and renewal processes. Combining both types of observation optimized the recovery of coupled parameters. Trajectory reconstruction, profile likelihood analysis, boundary-hit frequencies, and Monte Carlo simulations confirmed these findings. Importantly, while all observation strategies reproduced TADS with comparable accuracy, they differed substantially in recovering underlying biological parameters and latent-state dynamics. Thus, accurately reproducing decomposition scores alone is insufficient for reliable parameter inference. This framework provides a transparent and biologically interpretable foundation for the mechanistic estimation of PMSI. Future applications to case-level and multi-site datasets may enable site-specific recalibration and improved predictive evaluation across diverse aquatic environments.

Social animals must identify, evaluate, and appropriately respond to other individuals, often relying on multiple sources of information to guide context-dependent behavior. While individual recognition is thought to be widespread and critical for many social interactions (e.g. territoriality, dominance hierarchies), convincing demonstrations across animals beyond class-level recognition remain rare. Further, the cues animals use to recognize individuals remains poorly understood, especially in natural environments where they are exposed to numerous cues which may require cue integration. Here, we examine how socially dominant males of the African cichlid fish, Astatotilapia burtoni, use individual recognition to modulate aggression and whether this process depends on the spatial context. Using naturalistic experimental setups, we exposed males to familiar and unfamiliar neighbors while systematically manipulating spatial location and presenting a neighbor either singly or simultaneously to simulate competing social cues. Additionally, we measured circulating testosterone to assess endocrine correlates of recognition and aggression. We found that focal males habituated to familiar neighbors only when they remained in a consistent territorial location, demonstrating that spatial context is important for recognition. Further, when familiar and unfamiliar neighbors were presented simultaneously, males preferentially aggressed toward unfamiliar rival and adjust their aggressive response to the perceived threat of their neighbors, indicating that identity-based threat assessment is maintained under competing social demands. Together, our results show that recognition is a flexible, multi-faceted process that depends on the integration of identity and contextual information to guide territorial decision-making under dynamic social conditions.

Resource handling time is an important cost to foraging animals and this is especially true for low-ranking individuals who may be displaced before they acquire rewards. Handling may also require visual attention that can lead to a trade-off between scanning the environment and focusing on food acquisition. We ran a foraging experiment on wild vervet monkeys where we simultaneously offered them three puzzle boxes in a straight-line array that increased sequentially in handling difficulty and reward value. We found that differences in competitive ability had a large impact on access to long-handling time resources and willingness to invest time in costly problem-solving when social interference was possible. Resources with lower handling time and smaller rewards were accessed by individuals of all dominance ranks but only dominant monkeys that did not fear displacement attempted the high handling time puzzle box. Handling time improved with experience at each puzzle box and contrary to predictions, when vigilance rates were higher, monkeys were also faster at solving puzzle boxes. Thus, there is not necessarily a trade-off between attention to foraging tasks that require handling and vigilance, if a high scanning frequency to both can be balanced with limited scanning duration. These results have important implications for understanding the decision-making of foraging animals that live in competitive groups and the diets of individuals, which may vary with dominance when important resources require long handling times.

Crickets are gaining attention as sustainable protein sources because of their high nutritional value and low environmental impact. Growth models are essential tools for optimising production by predicting growth characteristics. However, previous studies have not compared multiple non-linear growth models for crickets or explicitly considered environmental factors. We analysed the growth patterns of the two-spotted cricket (Gryllus bimaculatus) and the Asian cricket (Teleogryllus occipitalis) at multiple temperatures (25.0, 27.5, 30.0, 32.5 and 35.0 {degrees}C) using three non-linear models (Gompertz model, logistic model, and von Bertalanffy model) and combined the predicted body mass with observed survival rates to predict the optimal harvest time and temperature. All three models fitted the data well (R2 [&ge;] 0.97 in both species). The asymptotic body mass was highest at 30.0 {degrees}C, and the growth rate constant increased with temperature, reaching its maximum at 35.0 {degrees}C except for the logistic model in G. bimaculatus (32.5 {degrees}C). In addition, the predicted value of harvest, calculated by combining predicted body mass and observed survival probability, was highest at 30.0 {degrees}C in both species, reaching 13.82 kg/m3 at 38 days in G. bimaculatus and 7.12 kg/m3 at 62 days in T. occipitalis. These results suggest that 30.0 {degrees}C is the most suitable constant-temperature condition for maximising predicted productivity, although the optimal harvest timing differs between species.

The Siamese fighting fish (Betta splendens) is well-known for its high levels of aggression and complex, stereotyped displays, making it an ideal model for testing deep learning-based tools for high-throughput, unbiased quantification of aggressive behaviour. A deep-learning object recognition model (BettaAI) was developed to detect the species' aggressive displays, including threat (opercula opening and fin distension), attack (bites) behaviours, as well as surface air breathing, a behaviour correlated with the frequency and intensity of aggression. Videos of males confronting their mirror image were acquired simultaneously with synchronised top and side cameras. Two separate models were trained, with some behaviours identified from top-view frames and others from side-view frames; outputs from both models were combined and post-processed for final quantification. BettaAI performed with high accuracy: F1 scores were 0.99 for the top-view model and 0.93 for the side-view model. Average Precision (AP) at 0.5 IoU exceeded 0.98 for all categories except bites, a rare behaviour in the dataset, which reached 0.865. Comparisons with a manually curated "ground-truth" dataset from videos of 10 males showed strong concordance between automated quantification and manual annotations by expert observers across all behaviours. A case study on 461 males reacting either to a mirror or to a video playback of a conspecific demonstrated the high-throughput and unbiased advantages of BettaAI, with threat displays being more frequent toward the mirror image and attack rates not differing between treatments. This work underscores the potential of BettaAI for automated, bias-free quantification of aggressive displays in B. splendens.

Rising temperatures linked to global climate change can disrupt the chemical communication that animals rely on for reproduction. Arthropods are particularly vulnerable due to their limited ability for thermoregulation and their reliance on cuticular hydrocarbons (CHCs), which have a dual role in social communication and heat protection. Heat-induced changes in cuticular composition may therefore lead to mate recognition errors. We tested this in the burying beetle Nicrophorus vespilloides, by exposing males to either benign temperatures (20{degrees}C) or a simulated 3-day heatwave (26{degrees}C). We recorded the frequency of same-sex sexual behaviour under these contrasting thermal conditions and examined associated changes in the males' cuticular profiles. Our results show a higher rate of same-sex mounting under heat stress, with the CHCs of heat-stressed males shifting toward more saturated, longer-chained compounds and more female-like compounds. We also found a positive association between chain length and the frequency of same-sex mounting, suggesting a trade-off between the social communication and waterproofing functions of CHCs. Overall, our findings provide evidence for a causal effect of heat on same-sex sexual behaviour, which may be partly explained by changes in cuticular lipids. Such disruption of chemical communication could have major consequences for animal reproduction in a warming world.

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.

The most studied symbiosis between land vertebrates and algae, is the one between Ambystoma maculatum and Oophila amblystomatis, where the latter colonizes the amphibian''s eggs. Although clear benefit given by algal growth for the salamander embryo has been observed, mutualism is not widely accepted. Mutualistic hypotheses posit benefits from the host to the algae which include protection, N- and C-sources, but no experimental evidence has been obtained. In fact, recent studies suggest that the algae are stressed during this relationship and propose fermentation rather than photosynthesis as main driver for algal growth. In this work, we analyzed embryonic host developmental rate, algal and embryo growth and photosynthetic function of eggs housed at different light intensities. We provide evidence that photosynthetic growth is the main driver for Oophila and that higher algal growth yields faster developmental rate and embryo size. Also, we provide strong evidence that rates of photosynthetic electron transport (and the concomitant O2 evolution) must be higher than those of consumption by the embryo for this symbiosis to be mutualistic. Since photosynthetic rate is dependent on light, this work illustrates the importance of light intensity in this symbiotic relationship.

Animal behaviour is both innately constrained and shaped by learning. This mosaic organization has evolved in response to species-specific ecological demands and may differ between sensory modalities. Flower-visiting animals are a particularly useful system for investigating the relationship between sensory ecology and learning because they rely on multiple floral cues, particularly odour and colour, to locate food sources. However, it remains largely unexplored whether specialization on floral resources entails divergence in learning abilities across sensory modalities. Drosophila elegans is a flower-feeding species that depends heavily on floral resources throughout its life; adults spend much of their time on flowers and larvae develop on fallen flower leaves. Here, we compared odour-reward and colour-reward associative learning between the flower-feeding D. elegans and the fruit-feeding D. melanogaster. We found that, under conditions of equilibrated motivation, odour- and colour-preference, and using the same sugar reward, D. elegans exhibited poorer odour-reward learning performance but better colour-reward learning performance than D. melanogaster. These results suggest that the modality-specific eligibility of sensory information to enter into associations, known as the 'Garcia-effect' in experimental psychology, can evolve oppositely between species. This highlights the relationship between ecological specialization and mnemonic processing, and shows that biological 'intelligence' is not general.

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.

Highly pathogenic avian influenza (HPAI) is among the most significant disease threats to poultry worldwide. Modelling challenges, where independent teams address a common epidemiological scenario, can support the development of response capabilities and strengthen communication between modellers and risk managers. Despite the established benefits of these exercises, they remain uncommon in animal health, and none have previously addressed avian influenza. Here Jolly Island, an artificial landscape of 9160 poultry farms with five production types, was developed and seeded with stochastic HPAI epidemics that ran their course over a three-to-four month period. From January through April 2026, 45 registered teams across five continents investigated a selected synthetic epidemic, producing probabilistic forecasts, inferring transmission drivers, and evaluating counterfactual control policies. Here the objectives, design choices, and data generation of the HPAI Modelling Challenge are described in full, covering transmission processes, surveillance system operations, and control strategy implementation, along with the selected epidemic trajectory, the narrative situation reports supplied to the teams at each phase, and the complete phase-specific datasets released to them. As the opening paper of this special issue, here is provided the foundation upon which all subsequent contributions, where teams document their approaches and analyses, are built.

Dysfunctions in transcription cause severe human diseases. In eukaryotes, transcription initiation by RNA polymerase (Pol) II requires the formation of the pre-initiation complex (PIC) composed of general transcription factors (GTFs), Pol II, and an essential multiprotein coactivator, Mediator. In vitro experiments with GTFs and Pol II have depicted a linear sequence of PIC assembly. However, PIC assembly paths in vivo at the genomic scale and Mediator's role in these paths remain poorly understood. One strategy characterizes ChIP-seq occupancy alterations in Mediator mutants, but analysis of these data still lacks a formalized interpretation framework. In this study, we address this need by developing a quantitative framework that scores candidate assembly paths according to their ability to explain these alterations. This framework combines a model of PIC assembly based on a system of differential equations with parameter optimization based on a penalized criterion. We applied this new framework to datasets from two yeast Mediator mutants, in the Med17 and Med10 subunits. Our results show that the best-supported PIC assembly paths differ from those inferred in vitro. In particular, we show that it is important to distinguish the core TFIIH module from the TFIIK kinase module, and that similar paths starting with Mediator or TBP receive different levels of support. Furthermore, although multiple paths fit the data equally well, they differ markedly for specific gene groups. Taken together, the results show that the path can depend on the gene, and are also compatible with more than one path being operational in vivo for a single gene. This work improves our understanding of PIC assembly paths and transcription initiation, and opens perspectives for future modeling and experimental studies.

In this study, we develop a mathematical model of the hypothalamic pituitary adrenal (HPA) axis and systematically investigate the model complexity required to reproduce observed hormone dynamics. The model is fitted to ACTH and cortisol measurements from five healthy volunteers reported in the literature. We show that simultaneous reproduction of both hormone profiles requires a delay differential equation model with at least five state variables among the model architectures considered. Following fitting the volunteer data, we investigate the response of the model to sustained stress using bifurcation analysis. The coupled system exhibits bifurcations over a range of stress intensities. This analysis reveals bifurcations whose critical stress thresholds depend strongly on the modulatory state of the system. These results provide a mathematical framework for investigating transitions between physiological and dysregulated HPA axis dynamics, which may be related to states of health and disease.

Ecdysozoans is one of the most abundant and diverse groups of metazoans and grow through moulting the rigid exoskeleton that provided protection. But the moulting process is often dangerous, resulting in malformations or death. Injuries have been well documented in the calcitic exoskeleton of trilobites, some of which have been attributed to moulting complications when long spines are deformed. Injuries in trilobites are often found in the trunk rather than the cephalon, and abnormal genal spines are rarely documented. Here we examine injuries in eleven specimens of Olenoides serratus from the Burgess Shale (Cambrian, Wuluian) and demonstrate an increased frequency of genal spine malformations compared to other trilobites. The unusual pattern of malformations may be attributed to moulting injuries of the long and delicate genal spines in O. serratus. To moult, trilobites curved ventrally to press the anterior margin of their cephalon into the substrate and open the facial sutures. This process exerted force on the librigenae. To exit the exuvia, the genal spines were forced to bend as the old librigenae dipped ventrally along the anterior edge, resulting in the injured genal spines in O. serratus. A similar process of moulting resulting in injuries may be seen in other early Euarthropods.