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This study investigates the prevalence and implications of nestedness within primate social networks, examining its relationship with cognitive and structural factors. We analysed data from 51 primate groups across 21 species, employing network analysis to evaluate nestedness and its correlation with modularity, neocortex ratio, and group size. We used Bayesian mixed effects modelling to investigate nestedness in primate social networks, controlling for phylogenetic dependencies and exploring various factors like neocortex ratio and group size. Our findings reveal a significant occurrence of nestedness in 66% of the species studied, exceeding chance expectations. This nestedness was more pronounced in groups with less steep dominance hierarchies, contrary to traditional assumptions linking it to hierarchical social structures. A notable inverse relationship between nestedness and modularity was observed, suggesting a structural trade-off in network formation. This pattern persisted even after controlling for species-specific social behaviours, indicating a general structural feature of primate networks. Surprisingly, our analysis showed no significant correlation between nestedness and neocortex ratio or group size, challenging the social brain hypothesis and suggesting a greater role for ecological factors in cognitive evolution. This study emphasises the importance of weak links in maintaining network resilience. Overall, our research provides new insights into primate social network structures, highlighting complex interplays between network characteristics and challenging existing paradigms in cognitive and evolutionary biology.

Individual identification plays a pivotal role in ecology and ethology, notably as a tool for complex social structures understanding. However, traditional identification methods often involve invasive physical tags and can prove both disruptive for animals and time-intensive for researchers. In recent years, the integration of deep learning in research offered new methodological perspectives through automatization of complex tasks. Harnessing object detection and recognition technologies is increasingly used by researchers to achieve identification on video footage. This study represents a preliminary exploration into the development of a non-invasive tool for face detection and individual identification of Japanese macaques (Macaca fuscata) through deep learning. The ultimate goal of this research is, using identifications done on the dataset, to automatically generate a social network representation of the studied population. The current main results are promising: (i) the creation of a Japanese macaques' face detector (Faster-RCNN model), reaching a 82.2% accuracy and (ii) the creation of an individual recognizer for K{\=o}jima island macaques population (YOLOv8n model), reaching a 83% accuracy. We also created a K{\=o}jima population social network by traditional methods, based on co-occurrences on videos. Thus, we provide a benchmark against which the automatically generated network will be assessed for reliability. These preliminary results are a testament to the potential of this innovative approach to provide the scientific community with a tool for tracking individuals and social network studies in Japanese macaques.

The latest advancements in artificial intelligence technology have opened doors to the analysis of intricate behaviours. In light of this, ethologists are actively exploring the potential of these innovations to streamline the time-intensive process of behavioural analysis using video data. In the realm of primatology, several tools have been developed for this purpose. Nonetheless, each of these tools grapples with technical constraints that we aim to surmount. To address these limitations, we have established a comprehensive protocol designed to harness the capabilities of a cutting-edge tool, LabGym. Our primary objective was to evaluate LabGym's suitability for the analysis of primate behaviour, with a focus on Japanese macaques as our model subjects. We have successfully developed a model that demonstrates a high degree of accuracy in detecting Japanese macaques stone-handling behaviour. Our behavioural analysis model was completed as per our initial expectations and LabGym succeed to recognise stone-handling behaviour on videos. However, it is important to note that our study's ability to draw definitive conclusions regarding the quality of the behavioural analysis is hampered by the absence of quantitative data within the specified timeframe. Nevertheless, our model represents the pioneering endeavour, as far as our knowledge extends, in leveraging LabGym for the analysis of primate behaviours. It lays the groundwork for potential future research in this promising field.

Understanding the effects of built environment on physical activity is important for promoting healthy lifestyles in cities. Yet, very few studies have used objective continuous location data and measures of physical activity while addressing biases to causal inference. In addition, the effect of the environment on body postures during trips, albeit of physiological importance, is rarely addressed. Using mixed models for compositional data on sensor-derived physical activity information, we estimated the effects of greenery, destination density, public transport time e ciency, and average area education among 692 homework journeys made by 121 healthy adults (80 men, 41 women). Higher levels of greenery, public transport time e ciency, and average area education along the shortest network path between home and workplaces were found to reduce contemporaneous sedentary postures and increase physical activity. These relationships suggest that decision makers should consider greening cities and improving public transport e ciency as an effective way to reduce the prevalence of sedentary behaviors in our societies.

Recently discovered, the oldest human abstract drawing is around 73,000 years. Although the origins of drawing behaviour have remained an enigma to this day, light may be shone on the subject through its study among our closest neighbours, the great apes. This study analyses 749 drawings of five female Bornean orang-utans (Pongo pygmaeus) at Tama Zoological Park in Japan. We searched for differences between individuals but also tried to identify possible temporal changes among the drawings of one individual, Molly, who drew almost 1,300 drawings from 2006 to 2016. A classical analysis of the drawings was carried out after collecting quantitative and qualitative variables. Our findings reveal evidence of differences in the drawing style of the five individuals as well as creative changes in Molly's drawing style throughout her lifetime. Individuals differed in terms of the colours used, the space they filled but also the shapes (fan patterns, circles or loops) they drew. Molly drew less and less as she grew older, and we found a significant difference between drawings produced in winter, when orang-utans were kept inside and had less activity, and those produced during other seasons. Our results suggest that the drawing behaviour of these five orangutans is not random and that differences among individuals might reflect differences of styles, states of mind but also motivation to draw. These novel results are a significant contribution to our understanding of how drawing behaviour evolved in hominids.

Figurative drawing is a skill that takes time to learn, and evolves during different childhood phases that begin with scribbling and end with representational drawing. Between these phases, it is difficult to assess when and how children demonstrate intentions and representativeness in their drawings. The marks produced are increasingly goal-oriented and efficient as the child's skills progress from scribbles to figurative drawings. Pre-figurative activities provide an opportunity to focus on drawing processes. We applied fourteen metrics to two different datasets (N=65 and N=345) to better understand the intentional and representational processes behind drawing, and combined these metrics using principal component analysis (PCA) in different biologically significant dimensions. Three dimensions were identified: efficiency based on spatial metrics, diversity with colour metrics, and temporal sequentiality. The metrics at play in each dimension are similar for both datasets, and PCA explains 77% of the variance in both datasets. These analyses differentiate scribbles by children from those drawn by adults. The three dimensions highlighted by this study provide a better understanding of the emergence of intentions and representativeness in drawings. We have already discussed the perspectives of such findings in Comparative Psychology and Evolutionary Anthropology.

Road accidents involving pedestrians are still too numerous in cities, particularly at crosswalks. Many pedestrians crossed at the red light at zebras increasing the risk of accidents, for them and for people following mimetically them. Several studies tried to understand the causes of these illegal road-crossing behaviours, showing an effect of age, gender but also culture. This current study aims to understand causes of the uncertainty behaviour in two different countries: France and Japan. Uncertainty behaviour during road-crossing is here defined as a walking stop or a slowing down during a road-crossing behaviour at the red light. Uncertainty happens when there is a conflict between different information a pedestrians get, specifically between private and social information. This uncertainty behaviour is followed either by a speeding up to finish to cross the road or a giving-up. Our study showed an uncertainty time longer in Japan compared to France. Japanese pedestrians hesitated on a longer time when someone accompanied them. Being on the phone did not have an effect on the uncertainty time. There are many more give-ups than speed-ups, and this rate increases with the number of lanes. Moreover, there is a tendency to speed up with the number of pedestrians already crossing the road. This study confirms that pedestrians followed social information at road-crossings and hesitate when they realised their errors, increasing their risk of accidents. Understanding this, different solutions might be proposed to avoid these unintentional illegal road-crossing behaviours., Comment: arXiv admin note: text overlap with arXiv:1805.11834" Changes in authorship and strong modifications of the paper (errors in some frequencies)

Followership is generally defined as a strategy that evolved to solve social coordination problems, and particularly those involved in group movement. Followership behaviour is particularly interesting in the context of road-crossing behaviour because it involves other principles such as risk-taking and evaluating the value of social information. This study sought to identify the cognitive mechanisms underlying decision-making by pedestrians who follow another person across the road at the green or at the red light in two different countries (France and Japan). We used agent-based modelling to simulate the road-crossing behaviours of pedestrians. This study showed that modelling is a reliable means to test different hypotheses and find the exact processes underlying decision-making when crossing the road. We found that two processes suffice to simulate pedestrian behaviours. Importantly, the study revealed differences between the two nationalities and between sexes in the decision to follow and cross at the green and at the red light. Japanese pedestrians are particularly attentive to the number of already departed pedestrians and the number of waiting pedestrians at the red light, whilst their French counterparts only consider the number of pedestrians that have already stepped off the kerb, thus showing the strong conformism of Japanese people. Finally, the simulations are revealed to be similar to observations, not only for the departure latencies but also for the number of crossing pedestrians and the rates of illegal crossings. The conclusion suggests new solutions for safety in transportation research.

Human beings have to make numerous decisions every day, and these decisions might be biased and influenced by different personal, social and/or environmental variables. Pedestrians are ideal subjects for the study of decision-making, due to the inter-individual variation in risk taking. Many studies have attempted to understand which environmental factors (light colour, waiting times, etc.) influence the number of times pedestrians broke the rules at road-crossings, very few focused on the decision-making process of pedestrians according to the different conditions of these variables, that is to say their perception and interpretation of the information they receive. This study used survival analyses to highlight the decision-making process of pedestrians crossing the road at signalized crossings in France and in Japan. For both light colours, we decided to carry out separate analyses for the first pedestrian to step off the kerb and other individuals following him/her, as the decisions underlying the departure of a first individual and those of the followers are different, and the departure of the first pedestrians strongly influences the decisions of other individuals. We showed that the probability to cross the road follows three different processes: one at the red light, one just before the pedestrian light turns green, and one after the light has turned green. Globally, the decision of the first pedestrian to cross, whether he or she does so at the green or at the red light, is influenced by their country of residence. We observed a lower threshold for Japanese pedestrians because they tend to follow their private or personal information. We identify the use of cognitive processes such as risk sensitivity and temporal discounting, and propose new concepts based on the results of this study to decrease the incidence of rule-breaking by pedestrians.

The sociality of cattle facilitates the maintenance of herd cohesion and synchronisation, making these species the ideal choice for domestication as livestock for humans. However, livestock populations are not self-regulated, and farmers transfer individuals across different groups throughout their lives for reasons such as genetic mixing, reproduction and pastureland management. Individuals consequently have to adapt to different group compositions during their lives rather than choose their own herd mates, as they would do in the wild. These changes may lead to social instability and stress, entailing potentially negative effects on animal welfare. In this study, we assess how the transfer of Highland cattle (Bos taurus) impacts individual and group social network measures. Four groups with nine different compositions and 18 individual transfers were studied to evaluate 1) the effect of group composition on individual social centralities and 2) the effect of group composition changes on these centralities. As shown in previous works, dyadic associations are stronger between individuals with similar age and dominance rank. This study reveals that the relative stability of dyadic spatial relationships between changes in group composition or enclosure is due to the identities of transferred individuals more than the quantity of individuals that are transferred. Older cattle had higher network centralities than other individuals. The centrality of individuals was also affected by their sex and the number of familiar individuals in the group. This study reveals the necessity of understanding the social structure of a group to predict social instability following the transfer of individuals between groups. The developing of guidelines for the modification of group composition could improve livestock management and reduce stress for the animals concerned., Comment: This preprint has been peer-reviewed and recommended by Peer Community In Ecology (https://dx.doi.org/10.24072/pci.ecology.100003)