Royal Society Open Science

Collective movement in social organisms emerges from local interactions and can generate large-scale spatial patterns of ecological relevance. In termites, trail formation is a well-known collective phenomenon, yet reproducing and recording its emergence under controlled laboratory conditions using whole colonies remains challenging. Existing laboratory approaches often rely on confined arenas or manually assembled subgroups, which can restrict movement and limit observation of colony-level dynamics. Here, we present a semi-folded arena designed for whole-colony observation of termite movement under controlled conditions. We developed a circular semi-folded arena that remained continuously connected to an intact nest and allowed individuals to move across a central observation surface while recirculating through a folded peripheral section. Using whole colonies of the Neotropical termite Constrictotermes cyphergaster, we recorded exploratory activity under baseline conditions, in the absence of added food or water. High-resolution video recordings were analysed using automated movement extraction to recover trajectories and visualise collective trail structure. Within the first 6 min of activity, collective trail structure was observed in 15 of the 16 colonies analysed. Under these conditions, the semi-folded setup captured early collective trail structure, visible as convergence of cumulative trajectories along shared routes radiating from the arena entrance region. Automated movement extraction was compatible with dense whole-colony recordings and yielded large quantities of positional data during the initial observation interval. Descriptive trajectory-based outputs, including speed distributions for workers and soldiers, showed that the recordings were suitable for recovery of fine-scale movement information. Repeatedly used routes were also often marked by visible dark traces on the paper lining by the end of the observations, providing a qualitative record of cumulative route use. The semi-folded arena provides a practical method for recording whole-colony termite movement under laboratory conditions while maintaining continuous nest access and avoiding manual transfer of individuals during trials. Rather than replacing conventional arena designs, this approach offers an additional methodological option for studying emergent movement patterns in species for which whole-colony observation is feasible. More broadly, it expands the experimental toolkit available for investigating colony-scale spatial organisation under controlled conditions.

Risk-taking behaviour permeates daily decision-making across many taxa and has significant impact on fitness outcomes. Previous research finds that individuals display consistent tendencies in their propensity to take risks, often labelled as a "Boldness-Shyness" personality trait. In this experimental study, we investigated repeatability in risk-taking behaviour in 241 wild vervet monkeys by measuring their responses to capture threat (via human-initiated darting procedure) and predation threat (via two predator models). We further examined the influence of socio-demographic, group identity and hormonal factors on risk-taking behaviour. We found that multiple behavioural responses, including the likelihood of approaching a food source under threat, were consistent across contexts. Risk-taking behaviour was influenced by age, sex, dominance rank, and hormonal profiles: juveniles, males, and higher-ranking individuals were more likely to approach food under (perceived) predation risk. Additionally, we observed significant among-group differences, suggesting that individuals within the same social group exhibit similar risk sensitivities, potentially due to social facilitation or shared environmental effects. The findings contribute to our understanding of animal personality and the ecological and social drivers underlying variation in risk-related behaviours.

Animals often rely on social information when making movement decisions. In zebrafish, classic work showed that shoal size and shoal activity both bias shoal choice. Here we extend these effects in Goldfish (Carassius auratus) and extend them with a drift-diffusion model (DDM) account of individual evidence accumulation under dynamic social cues. Using a three-chamber linear arena, we quantified a focal fishs position for 10 minutes while manipulating (i) numerical differences between flanking shoals and (ii) their activity (swimming speed) via temperature manipulation. ANOVA on time-proportion choices confirmed robust attraction to larger shoals; when shoal sizes were equal, the more active shoal was preferred. In combined manipulations, activity effects dominated at small numbers but saturated as group size increased, indicating a threshold-like integration where activity dominates at small shoal sizes (<3 fish) but saturates at larger sizes. We formalize these processes with a bounded DDM in which a sigmoidal stimulus function maps shoal size and average speed to momentary evidence, subject to random perturbations. The model reproduces the observed psychometric relations between relative numerosity, velocity differences, and choice. Our results (i) generalize zebrafish findings to a carp species with distinct ecology and physiology, and (ii) provide a compact mechanistic link between social cues and individual decision trajectories in dynamic social contexts.

One way that animals can cope with the challenge of locating ephemeral food in time and space is by tracking elapsed time and planning revisits to these resources. These abilities likely evolved under constraints of memory capacity. We expect that during evolution a trade-off emerged between a large memory size (quantity) and high accuracy (quality) of information. We used computer simulations of a forager moving through space and time to investigate how timing accuracy, memory size, and forgetting affect foraging efficiency across environmental conditions, and how foragers should trade off the quantity against quality of memorised information. Memory in general paid off, as it improved foraging efficiency. However, surprisingly, the largest accuracy and size were not always most beneficial. In resource-poor, heterogeneous, and highly dynamic environments, extensive memory was even detrimental, as individuals likely became trapped in overexploited familiar areas. This suggests that under certain environmental conditions, a hidden, non-energetic cost of memory can arise. Furthermore, environmental structure shaped a quantity-quality trade-off such that a minimal memory size and higher timing accuracy were favoured in resource-poor, temporally stable and homogenous environments. Finally, forgetting was beneficial when memory was constrained, and environments were poor, heterogenous and dynamic. Forgetting limited the benefits of increased memory size, highlighting that memory costs can emerge from how it shapes movement patterns and foraging decisions. Overall, our results highlight that larger and more accurate memory is not necessarily better and that forgetting can be adaptive. This study takes a first step toward the theoretical consideration of memory trade-offs in order to research how they shape, and are shaped, by foraging pressures. Author summaryHow can we explain foraging memory abilities differences in animals? In this study, we make an attempt to elucidate the current patterns of temporal memory using a computational model that was inspired by realistic environmental and cognitive mechanisms. Building on our previous theoretical and empirical investigations of the causes and consequences of spatiotemporal memory, we provide new insights into the ecological drivers of temporal memory, how they shape an accuracy-size trade off, and its consequences for movement behaviour. We show that a larger memory is favoured, at the cost of accuracy, in resource-rich and dynamic environments. Our results highlight that while memory is generally beneficial, a larger and more accurate memory is not necessarily better. Moreover, our model suggests that such constraints of memory stem from a hidden cost of how memory restricts movement and instigates local overexploitation. Our findings contribute to a broader understanding of how cognition evolves in response to ecological conditions.

Cancer prevalence varies across species, with traits such as litter/clutch size, gestation duration, carnivory, and adult mass, partly explaining this variation. Yet no coherent explanation exists for why shorter gestation and carnivory both correlate with cancer prevalence or risk. Given that carnivores sleep more than herbivores, sleep reportedly being a compensation for brain immaturity after gestation, longer sleep appearing in species with shorter gestation, and shorter gestation in species with higher cancer prevalence, we hypothesize that sleep may mediate the gestation-cancer association. We obtained neoplasia prevalence, cancer prevalence, cancer mortality risk (n [&ge;] 20 individuals/species), gestation duration, and sleep duration data across vertebrates. We tested whether sleep duration mediates the known gestation-cancer prevalence association, whether sleep duration is directly correlated with neoplasia/cancer prevalence or risk, and tested the known gestation-sleep duration association using more vertebrate species and phylogenetic generalized least squares analyses. Gestation and sleep duration were not correlated with neoplasia prevalence, cancer prevalence, or cancer mortality risk. Gestation and sleep duration were negatively correlated. These results highlight the complexity of understanding how multiple physiology variables explain the variation in cancer prevalence or risk across vertebrates, and the need to verify previously known associations with more powerful and robust statistical tools.

Despite their currently scarce taxonomic diversity, rhinocerotoids were among the most evolutionarily successful clades of large herbivorous mammals throughout the Caenozoic. Within an array of morphological adaptations, the cranial horn represents the clades most remarkable and name-giving feature, imposing significant morpho-functional demands on the skull. In this paper, patterns and drivers of the rhinos cranial evolution were investigated for the first time by compiling a three-dimensional geometric morphometric dataset of living and extinct species. Multiple aspects of morphological evolution were explored using phylogenetic comparative methods, including craniofacial evolutionary allometry (CREA - tendency of larger species to have longer faces), phylogenetic constraints, and tempo of evolution. Cranial shape variation linked to horn presence and size evolved under a phylogenetically constrained framework, with a notable transition from hornless to horned species. Rhinos significantly deviated from CREA, likely due to diversity of cranial forms and proportions that evolved independently across the clade in response to varying horn morphologies and dietary habits. Hornless and horned rhinos exhibited similar rates of cranial evolution, and shape variation was obtained through multiple episodes of accelerated evolution. This highlights the role of morphological innovations and Caenozoic global cooling events in the emergence of phenotypic diversity.

Predicting and understanding behaviour is a primary objective of many disciplines, especially human behaviour, as it is the cause of many of the worlds most pressing problems. Although it is a fundamental concept in multiple disciplines, there is no agreed operational definition of what it is. Neither is there a generally agreed theoretical framework for predicting it. Here we propose a data-driven approach, using the "Conductome" -- the complete set of factors that both predict and explain a behaviour -- to operationalise a discipline-neutral definition of behaviour that is based on an ensemble of stimulus/response measurements of a system, showing that it must be determined through a process of statistical inference. As the prediction of behaviour can be characterised as a classification problem, we argue that Bayesian classifiers offer a promising framework in which explainable prediction models that can approximate the Conductome can be developed. We show the efficacy of the framework using a dataset of 1075 persons, with over 3000 features, constructing a model for predicting sedentariness, a behaviour that is a known risk factor for obesity and metabolic disease. We analyse the effect size, coverage, statistical significance and potential causality of a subset of 396 features associated with 58 variables.of different types.

The osteocyte network in bone is believed to play an important role for how bone tissues sense and respond to mechanical stimulation. Yet, bone adaptation to mechanical loads is often conceptualised as a simple response to mechanical stimuli, such as Wolffs law, which is based on mechanical variables only and takes no account of the cellular basis of mechanosensation. Wolffs law presumes the existence of a reference mechanical stimulus, the mechanical setpoint, above which bone is consolidated, and under which bone is removed. In this paper, we develop a theory of bone tissue sensing and adaptation based on osteocytes to provide new understanding of the role played by osteocyte signals in mechanical adaptation. In this theory, the mechanical setpoint of Frosts mechanostat is explicitly embodied as osteocyte properties involved in mechanotransduction. The mechanical setpoint is allowed to adapt due to the replacement of osteocytes during remodelling, making the setpoint space and time dependent. We propose a mathematical model to implement this new theory of bone adapation and present numerical simulations of this model to explore how mechanobiological response curves (effective Wolffs laws) are modulated by setpoint adaptation during remodelling. By accounting for varying osteocyte populations within bone tissue, we explore bone adaptation under osteocyte disruptions, which is particularly relevant to age-related bone loss. Our model suggests that biological disruptions of remodelling balance cannot always be compensated by mechanical feedback, and that setpoint adaptation during remodelling may have significant observable consequences, such as hysteresis in bone response signatures that resemble lazy zones.

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

Total knee replacement restores mobility in patients with advanced osteoarthritis, yet many individuals still experience limited ability to perform high-flexion tasks such as squatting. Current preoperative planning relies on static imaging and cannot predict how different implant alignment choices will affect postoperative dynamic function. This study developed a predictive simulation framework that uses bi-level inverse optimal control to link preoperative implant alignment directly to expected postoperative squat kinematics. Subject-specific musculoskeletal models were constructed for six total knee replacement patients using experimental squat data. Bi-level inverse optimal control was applied to identify both individualised and group-level cost functions. The individualised setting provided subject-specific accuracy, while the group-level setting derived a single group-level cost function as an initial step toward preoperative use without requiring postoperative motion data. The individualised setting reproduced experimental trajectories with low errors across all joints (mean apex difference 1.53{degrees}, root-mean-square error 5.15{degrees}, normalised root-mean-square error 11.15%, Pearson correlation 0.96). The group-level setting yielded higher but acceptable errors (mean apex difference 5.70{degrees}, root-mean-square error 6.75{degrees}, normalised root-mean-square error 17.53%, Pearson correlation 0.95) while preserving the general pattern and phasing of the motion. Squat depth emerged naturally from the optimisation rather than being prescribed. This framework may provide a basis for future quantitative tools to evaluate how implant alignment choices influence postoperative squat performance, potentially improving functional outcomes in total knee replacement. These results suggest that the proposed IOC framework can reproduce key features of post-TKR squat kinematics, but further out-of-sample validation is required before it can be used for preoperative prediction or translated into tools aimed at improving functional outcomes in total knee replacement.

The collective behavior of complex systems emerges from the actions and interactions of their individual components. But what if these individuals make mistakes, or deviate from behavior tuned to lead to collective success? Here, we explore the effects of individual errors on collective outcomes. We investigate in particular whether information flow among individuals exacerbates or mitigates such individual failures. We use an agent-based, spatially explicit model inspired by collective foraging in social insects. Social insect colonies forage for food with autonomous workers who search for and exploit resources around the central nest, as well as share information about discovered resources. We find that the errors that have the most chances of occurring had the strongest impacts: for example, false positive detections can occur at any time during search, and each such error derailed exploration activity. Similarly, forgetting errors are potentially frequent and detrimental to resource exploitation. Despite the fact that communication inherently may narrow the breadth of information used by a colony, we found, in contrast, that it enhanced spatial exploration in our model. Communication in our model also reduced the effects of individual errors, instead of permitting erroneous information to spread. Our model thus illustrates that communication plays a central role in error management in complex systems, and that the evolution of communication systems in social insects may be shaped by selection on exploration and error mitigation as well as on efficient food retrieval.

Cooperation is foundational to complex sociality, yet presents profound evolutionary dilemmas - costs and benefits are rarely distributed evenly and the decision to collaborate or defect can involve a complex contextual calculus. These challenges are compounded when cooperation scales from pairs to groups. Group-level cooperation is fundamental to many species success, but how is it sustained and regulated in nature? One promising route to addressing this question is to examine how individuals reorganise their affiliative interactions in anticipation of group-level cooperation. We examine such pre-cooperative reorganisation using long-term data (2013-2018) from three neighbouring groups of wild chimpanzees at the Tai National Park, Cote dIvoire, who routinely cooperate as a collective to defend their territory against other groups. We found that chimpanzees adjusted the distribution of their social contacts in anticipation of risky and proactive territorial defence by forming more broadly connected, yet more diffuse, affiliative networks. Specifically, adult chimpanzees groomed and played with more group members on days of proactive territorial defence, and this pattern was temporally-sensitive, with increased affiliation occurring before, rather than after, the cooperative act. Chimpanzees accessed a broader range of partners through increased interaction efficiency by switching between more partners with shorter interactions per partner. This pattern suggests a shared evolutionary basis of dynamic social readjustment in preparation for group-level social dilemmas in hominids, potentially providing the foundation for the formalized systems of affiliation found in human societies.

Dung beetles can use a variety of orientation cues to maintain a consistent bearing during ball-rolling. Where several cues are available, they appear to learn the spatial relationship between them, providing redundancy if some cues are removed. Mounting evidence indicates that such a learning process is implemented in the insect head direction circuit; specifically, in the plastic substrate between sensory input neurons and compass neurons in the central complex. This plasticity appears to be driven by rotational movements, providing a clear link with observed beetle 'dance' behaviour. Here, we extend our functional model of this circuit and use it on a robot platform, to test it in the same behavioural assay as was used for the beetles. The robot was able to replicate the beetle's ability to substitute a directional wind cue for a point source light cue in guiding straight-line movement. However, it also revealed significant biasing coupled to dance direction. This biasing appears to be caused by inherent conflict between recurrent and instantaneous inputs to the compass circuit. We predict that the real insect should experience similar issues unless it has evolved a neural mechanism to compensate.

Eponymous etymologies (i.e., organisms named after people) are prevalent in global taxonomy worldwide, across scientific and common names. The persistent usage of eponyms has been intensely debated in recent times, across various sociopolitical, applied and philosophical perspectives. However, a rigorous statistical analysis of eponyms and their enduring colonial legacies remains hitherto unexplored. Here, we use a global and spatially-explicit network analysis to examine 2416 contemporary bird eponyms (21% of all bird species on earth) and their relationships with historical European colonialism. Additionally, we develop and utilise a Colonial Exposure Index (CEI) that summarizes the geopolitical influence of various colonial empires on modern-day countries. Our results show that an overwhelming majority of bird eponyms worldwide are named after people belonging to countries where the bird species does not occur. A majority of these eponyms honor scientists, aristocrats and army officers from erstwhile colonial empires, with eponymous species descriptions peaking during colonial expansion. Importantly, our analysis highlights a positive relationship between the Colonial Exposure Index (a metric factoring the duration and area of a country colonized by a specific empire) and the number of eponymous bird species honoring persons from that specific empire. Our temporal analysis, however, shows that the use of eponyms has recently shifted towards honoring native persons and distinguished conservation champions. Overall, this study presents an important statistical examination of eponyms and their colonial legacies, thereby providing valuable context for ongoing debates on the reform or retention of eponyms worldwide.

Extremely elongate necks have convergently evolved in several amniote lineages, including both aquatic and terrestrial forms (Fig. 1). The development of such a feature brings with it advantages in obtaining food items, but also biomechanical challenges, such as flexibility, stability, lift, and inertia. In Tanystropheus, a particularly long-necked Triassic archosauromorph, the neck is composed of only 13, mostly extraordinarily elongated and slender cervical vertebrae and accompanying rod-like, overlapping ribs, making it arguably the most extreme example of neck elongation in tetrapod evolution (Fig. 1;1-6). Understanding the function of this remarkable neck provides insights into the limits of neck elongation in amniotes and the evolution of morphological novelties in Triassic reptiles. Here we present the first quantitative biomechanical analysis of the Tanystropheus neck using a digital model based on three-dimensionally preserved bones. We assessed its range of motion (ROM) and performed finite element analysis (FEA) on the individual cervical ribs and the neck model in different configurations. Our results indicate that the neck of Tanystropheus was not extremely stiff, as previously postulated, and the ribs likely did not impair its movements. They transferred tensile forces towards the base of the neck, similar to what hypothesized for sauropods7. This study elucidates the bauplan of an extremely specialized animal and brings us closer to understanding the patterns of achieving neck elongation in vertebrates.

Tessellated calcified cartilage (TCC) is a hallmark of the chondrichthyan skeleton, yet its development early in ontogeny across the four major groups (batoids, galeomorphs, squalomorphs, and holocephalans) remains poorly understood. Specialised traits of TCC, such as multi-layered TCC and internal mineralised trabeculae, typically develop in response to feeding mechanics. In this study, we evaluated TCC morphology in the jaws of 12 representative taxa to observe its structure at an early ontogenetic stage to determine whether these specialised features had yet developed. Batoids consistently exhibited well-developed, homogeneous, polygonal tesserae early in ontogeny regardless of jaw morphology or feeding habit. In contrast, galeomorphs displayed high morphological heterogeneity. Notably, we document the first report of an extensive internal trabecular network in a non-batoid elasmobranch, observed in Ginglymostoma cirratum, which may serve to resist the mechanical pressures of specialised suction feeding. Furthermore, we identified voussoir tesserae in galeomorphs for the first time, extending their documented presence across all elasmobranch groups, where they display an inverted aspect ratio (wider than tall) compared to mature forms. The durophagous Mustelus mustelus exhibited surprisingly poor TCC development despite being a durophagous feeder, pointing to a pronounced ontogenetic lag. In Squatina oculata, TCC was characterised by large and thick tesserae and extensive fused tesseral regions which may relate to its explosive ambush predation mode, whereas the holocephalan Chimaera exhibited a poorly mineralized, mesh-like structure without resolvable discrete tesserae or trabeculae-matching findings from previous studies. Across all specimens, multi-layered TCC was absent, confirming that multi-layering develops later in ontogeny. These results demonstrate that generalised models of TCC development based on one group or a few taxa fail to capture the broader diversity of TCC morphology. It also opens up many exciting avenues for further study, and forms the basis for comparisons with fossil chondrichthyans, to investigate the evolution of TCC.

The initial response of populations to the SARS-CoV-2 virus reduced the incidence of COVID-19 cases. However, this success was shorted lived once most populations relaxed most restrictions, resulting in an increase in infections. This feedback contributed to additional pandemic waves. The temporal unfolding of behavioural changes in populations present a challenge to mathematical models for disease dynamics. Coupled behaviour-disease models with varying levels of complexity accounting for several factors have been used to capture behavioural dynamics and SARS-CoV-2 transmission, with varying results. To study the impact of model complexity on the predictive power of models, here we formulate five coupled behaviour-disease models with varying structure and number of parameters. We fit the models to SARS-CoV-2 infection incidence and stringency of control interventions from five European countries in the first wave, and study how well these fitted models predict the second wave. We show that models with more parameters do not necessarily have a greater ability to explain and predict key features of a pandemic wave. Hence, our results show that a relatively simple coupled behaviour-disease model with important parameters can do an adequate job of providing information about the pandemic wave. Additionally, our findings show that complex models can be country-specific, working better for some countries and poorly for others. We conclude that modellers should not always opt for the most complicated possible models, if the data do not support their use.

Fat accumulation and use is critical for sustaining life. Most insects show a typical response to feeding where fat is accumulated when sufficient sugars and other carbohydrates are consumed. Parasitoid insects are an exception, because most species do not accumulate fat when feeding on a sugar-rich diet. Studies on fat metabolism generally measure fat content early in life without considering lipid metabolism as a dynamic process that is expected to change as life progresses. In this paper, we compared fat accumulation and use throughout the lives of adult female Drosophila melanogaster and females of 5 inbred lines of the parasitoid wasp Leptopilina heterotoma. We expected that fat accumulation would take place irrespective of teneral fat content in D. melanogaster. We found that fat D. melanogaster initially used fat reserves, while lean flies economized on fat stores. Both lean and fat flies started accumulating fat after 7 days of life, indeed showing a typical response for insects. Unlike other parasitoids, L. heterotoma populations differs in fat accumulation patterns that we expected to observe also between inbred lines. In none of the inbred lines, however, did fat accumulation take place. Our results did reveal that inbred lines differed in the rate at which fat was used mainly later during life. We further confirmed that D. melanogaster pupal size was highly correlated with adult female size for both D. melanogaster and L. heterotoma. Overall, our findings for L. heterotoma provide strong evidence that genetic background has a major impact on the rate at which fat is used over a lifetime.

Task allocation in eusocial insects has long been studied under the framework of division of labor, implying a relatively rigid association between individuals and tasks. However, most eusocial species lack morphological specialization, and workers regularly switch tasks as colony demands change. This raises a fundamental question: do tasks shape the behavioral profiles of workers, or does individual behavioral variation cut across task boundaries? We addressed this in a controlled laboratory study of Aphaenogaster senilis ants, comparing the behavioral profiles of four task groups (scouts, recruits, nurses, and necrophores) spatially segregated by their location within the colony setup and subsequently tested individually in four ecologically relevant contexts. This multivariate profiling, still rarely applied in ants, revealed that some tasks impose clear behavioral specialization (scouting, brood care), whereas others do not (recruitment, necrophoresis). Critically, this specialization appears in foraging-related tasks, whereas sociality does not: it varies considerably among workers, even within a single task group. Behavioral specialization, therefore, exists, but not across every dimension of behavior, and it is not a fixed property of the task. These results suggest that workers may differ in their readiness to shift roles depending on the task at hand, and this variation may in turn shape how colonies adapt to environmental change. More broadly, our results speak to a question central to collective behavior research well beyond ants: how individual variability translates into functional structure at the group level.

To estimate the life expectancy gains that could be realised from increases in Queenslanders physical activity (PA) levels. Design Lifetable analysis Setting, Participants We modelled the 2025 Queensland population aged [&ge;]40 years. Modelled scenarios We applied two approaches. In the first, we estimated life expectancy differences between device-measured PA quartiles, with quartile1 representing the least active and quartile 4 the most active. In the second, we compared observed device-measured PA levels in Queensland with scenarios in which all individuals moved to either [&ge;]12,000 steps/day or [&le;]2,000 steps/day. We converted the steps per day by age group and PA quartile into equivalent daily minutes of moderate-intensity walking at 4.8 km/h. Additional scenarios were explored in sensitivity analyses. Main outcomes Changes in life expectancy, and total life-years gained over the lifetime of the modelled population. Benefits were also translated into minutes of life gained per additional hour walked. Results If all Queenslanders aged [&ge;]40 years were as active as the most active quartile, life expectancy at birth could be 88.3 years, an increase of 4.8 years above the life expectancy at observed activity levels. The life expectancy differences between individuals in the least active quartile and the most active quartile was 9.7 years. Achieving the activity level of the most active quartile would require individuals in the lowest activity quartile to undertake an additional 85.9 minutes/day of moderate-intensity walking, with each extra hour of PA associated with an average gain of approximately 3 hours (177 minutes) of life. In step-based modelling, life expectancy in the most active scenario (all achieving [&ge;]12,000 steps/day) was higher by {approx}7.1 years compared with the least active scenario (all at [&le;]2,000 steps/day). Conclusions Increasing PA could yield meaningful gains in life expectancy for Queenslanders, with the largest gains seen in least active individuals. Our findings strengthen the case for prioritising investment in PA -promoting programs and environments.