Persistent species relationships characterize migrating bird communities across stopover sites and seasons.

Global migrations of diverse animal species often converge along the same routes, bringing together seasonal assemblages of animals that may compete, prey on each other, and share information or pathogens. These interspecific interactions, when energetic demands are high and the time to complete journeys is short, may influence survival, migratory success, stopover ecology, and migratory routes. Numerous accounts suggest that interspecific co-migrations are globally distributed in aerial, aquatic, and terrestrial systems, although the study of migration to date has rarely investigated species interactions among migrating animals. Here, we test the hypothesis that migrating animals are communities engaged in networks of ecological interactions. We leverage over half a million records of 50 bird species from five bird banding sites collected over 8 to 23 y to test for species associations using social network analyses. We find strong support for persistent species relationships across sites and between spring and fall migration. These relationships may be ecologically meaningful: They are often stronger among phylogenetically related species with similar foraging behaviors and nonbreeding ranges even after accounting for the nonsocial contributions to associations, including overlap in migration timing and habitat use. While interspecific interactions could result in costly competition or beneficial information exchange, we find that relationships are largely positive, suggesting limited competitive exclusion at the scale of a banding station during migratory stopovers. Our findings support an understanding of animal migrations that consist of networked communities rather than random assemblages of independently migrating species, encouraging future studies of the nature and consequences of co-migrant interactions.

Collective mitochondrial dynamics resolve conflicting cellular tensions: From plants to general principles.

Mitochondria play diverse and essential roles in eukaryotic cells, and plants are no exception. Plant mitochondria have several differences from their metazoan and fungal cousins: they often exist in a fragmented state, move rapidly on actin rather than microtubules, have many plant-specific metabolic features and roles, and usually contain only a subset of the complete mtDNA genome, which itself undergoes frequent recombination. This arrangement means that exchange and complementation is essential for plant mitochondria, and recent work has begun to reveal how their collective dynamics and resultant "social networks" of encounters support this exchange, connecting plant mitochondria in time rather than in space. This review will argue that this social network perspective can be extended to a "societal network", where mitochondrial dynamics are an essential part of the interacting cellular society of organelles and biomolecules. Evidence is emerging that mitochondrial dynamics allow optimal resolutions to competing cellular priorities; we will survey this evidence and review potential future research directions, highlighting that plant mitochondria can help reveal and test principles that apply across other kingdoms of life. In parallel with this fundamental cell biology, we also highlight the translational "One Health" importance of plant mitochondrial behaviour - which is exploited in the production of a vast amount of crops consumed worldwide - and the potential for multi-objective optimisation to understand and rationally re-engineer the evolved resolutions to these tensions.

Neural Mechanisms of Social Cognition in Primates.

Activity in a network of areas spanning the superior temporal sulcus, dorsomedial frontal cortex, and anterior cingulate cortex is concerned with how nonhuman primates negotiate the social worlds in which they live. Central aspects of these circuits are retained in humans. Activity in these areas codes for primates' interactions with one another, their attempts to find out about one another, and their attempts to prevent others from finding out too much about themselves. Moreover, important features of the social world, such as dominance status, cooperation, and competition, modulate activity in these areas. We consider the degree to which activity in these regions is simply encoding an individual's own actions and choices or whether this activity is especially and specifically concerned with social cognition. Recent advances in comparative anatomy and computational modeling may help us to gain deeper insights into the nature and boundaries of primate social cognition.

Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools.

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society's responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak.

Indirect influence in social networks as an induced percolation phenomenon.

Percolation theory has been widely used to study phase transitions in network systems. It has also successfully explained various macroscopic spreading phenomena across different fields. Yet, the theoretical frameworks have been focusing on direct interactions among nodes, while recent empirical observations have shown that indirect interactions are common in many network systems like social and ecological networks, among others. By investigating the detailed mechanism of both direct and indirect influence on scientific collaboration networks, here we show that indirect influence can play the dominant role in behavioral influence. To address the lack of theoretical understanding of such indirect influence on the macroscopic behavior of the system, we propose a percolation mechanism of indirect interactions called induced percolation. Surprisingly, our model exhibits a unique anisotropy property. Specifically, directed networks show first-order abrupt transitions as opposed to the second-order continuous transition in the same network structure but with undirected links. A mix of directed and undirected links leads to rich hybrid phase transitions. Furthermore, a unique feature of the nonmonotonic pattern is observed in network connectivities near the critical point. We also present an analytical framework to characterize the proposed induced percolation, paving the way to further understanding network dynamics with indirect interactions.

Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting.

BACKGROUND: Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2. METHODS: We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs. RESULTS: Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001). CONCLUSIONS: IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Natal legacies cause social and spatial marginalization during dispersal.

Early-life experiences can drive subsequent variation in social behaviours, but how differences among individuals emerge remains unknown. We combined experimental manipulations with GPS-tracking to investigate the pathways through which developmental conditions affect social network position during the early dispersal of wild red kites (Milvus milvus). Across 211 juveniles from 140 broods, last-hatched chicks-the least competitive-had the fewest number of peer encounters after fledging. However, when food supplemented, they had more encounters than all others. Using 4425 bird-days of GPS data, we revealed that this was driven by differential responses to competition, with less competitive individuals naturally spreading out into marginal areas, and clustering in central foraging areas when food supplemented. Our results suggest that early-life adversities can cause significant natal legacies on individual behaviour beyond independence, with potentially far-reaching consequences on the social and spatial structure of animal populations.

Challenges in replication: Does amygdala gray matter volume relate to social network size?

In this work, we tried to replicate and extend prior research on the relationship between social network size and the volume of the amygdala. We focused on the earliest evidence for this relationship (Bickart et al., Nature Neuroscience 14(2), 163-164, 2011) and another methodologically unique study that often is cited as a replication (Kanai et al., Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012). Despite their tight link in the literature, we argue that Kanai et al. (Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012) is not a replication of Bickart et al. Nature Neuroscience 14(2), 163-164 (2011), because it uses different morphometric measurements. We collected data from 128 participants on a 7-Tesla MRI and examined variations in gray matter volume (GMV) in the amygdala and its nuclei. We found inconclusive support for a correlation between measures of real-world social network and amygdala GMV, with small effect sizes and only anecdotal evidence for a positive relationship. We found support for the absence of a correlation between measures of online social network and amygdala GMV. We discuss different challenges faced in replication attempts for small effects, as initially reported in these two studies, and suggest that the results would be most helpful in the context of estimation and future meta-analytical efforts. Our findings underscore the value of a narrow approach in replication of brain-behavior relationships, one that is focused enough to investigate the specifics of what is measured. This approach can provide a complementary perspective to the more popular "thematic" alternative, in which conclusions are often broader but where conclusions may become disconnected from the evidence.

Social network size, empathy, and white matter: A diffusion tensor imaging (DTI) study.

Social networks are fundamental for social interactions, with the social brain hypothesis positing that the size of the neocortex evolved to meet social demands. However, the role of fractional anisotropy (FA) in white matter (WM) tracts relevant to mentalizing, empathy, and social networks remains unclear. In this study, we investigated the relationships between FA in brain regions associated with social cognition (superior longitudinal fasciculus (SLF), cingulum (CING), uncinate fasciculus, inferior fronto-occipital fasciculus), social network characteristics (diversity, size, complexity), and empathy (cognitive, affective). We employed diffusion tensor imaging, tract-based spatial statistics, and mediation analyses to examine these associations. Our findings revealed that increased social network size was positively correlated with FA in the left SLF. Further, our mediation analysis showed that lower FA in left CING was associated with increased social network size, mediated by cognitive empathy. In summary, our findings suggest that WM tracts involved in social cognition play distinct roles in social network size and empathy, potentially implicating affective brain regions. In conclusion, our findings offer new perspectives on the cognitive mechanisms involved in understanding others' mental states and experiencing empathy within supportive social networks, with potential implications for understanding individual differences in social behavior and mental health.

Aggressive interactions influence cognitive performance in Western Australian magpies.

Extensive research has investigated the relationship between the social environment and cognition, suggesting that social complexity may drive cognitive evolution and development. However, evidence for this relationship remains equivocal. Group size is often used as a measure of social complexity, but this may not capture intraspecific variation in social interactions. Social network analysis can provide insight into the cognitively demanding challenges associated with group living at the individual level. Here, we use social networks to investigate whether the cognitive performance of wild Western Australian magpies (Gymnorhina tibicen dorsalis) is related to group size and individual social connectedness. We quantified social connectedness using four interaction types: proximity, affiliative, agonistic and vocal. Consistent with previous research on this species, individuals in larger groups performed better on an associative learning task. However, social network position was also related to cognitive performance. Individuals receiving aggressive interactions performed better, while those involved in aggressive interactions with more group members performed worse. Overall, this suggests that cognitive performance is related to specific types of social interaction. The findings from this study highlight the value of considering fine-grained metrics of sociality that capture the challenges associated with social life when testing the relationship between the social environment and cognition.