Group-level differences in social network structure remain repeatable after accounting for environmental drivers

Individuals show consistent between-individual behavioural variation when they interact with conspecifics or heterospecifics. Such patterns might underlie emergent group-specific behavioural patterns and between-group behavioural differences. However, little is known about (i) how social and non-social drivers (external drivers) shape group-level social structures and (ii) whether animal groups show consistent between-group differences in social structure after accounting for external drivers. We used automated tracking to quantify daily social interactions and association networks in 12 colonies of zebra finches (Taeniopygia guttata). We quantified the effects of five external drivers (group size, group composition, ecological factors, physical environments and methodological differences) on daily interaction and association networks and tested whether colonies expressed consistent differences in day-to-day network structure after controlling for these drivers. Overall, we found that external drivers contribute significantly to network structure. However, even after accounting for the contribution of external drivers, there remained significant support for consistent between-group differences in both interaction (repeatability R: up to 0.493) and association (repeatability R : up to 0.736) network structures. Our study demonstrates how group-level differences in social behaviour can be partitioned into different drivers of variation, with consistent contributions from both social and non-social factors

Superchargeを付加した腹直筋皮弁を用いた乳房再建

2013年以降、乳がん全摘後に保険適応となった人工ゲル充填乳房を用いた乳房再建術のまれな合併症として、T細胞型非ホジキンリンパ腫が報告され、同タイプの人工ゲル充填乳房は使用できなくなった。これを受けて、当院では自家組織を用いた乳房再建の症例が増加している。ボリュームのある乳房の場合、腹部を用いた有茎腹直筋皮弁、遊離皮弁が選択されることが多い。有茎皮弁では上腹壁動静脈を血管茎とするが、腹直筋の血行は深下腹壁動静脈優位のため血行が不十分と考えられる硬結が術後に生じることがある。これを改善するため、当科では可能な限り深下腹壁動静脈を胸部のレシピエント血管に吻合してsuperchargeを行い、血行の増強に努めている。遊離皮弁と異なり、皮弁の自由度が制限されるため血管吻合がやや困難であるが、術後は柔らかい乳房が再現されることが期待できる。With the onset of insurance coverage in 2013, implant-based techniques had been popular for breast reconstruction in Japan until fairly recently. However, possible complications of non-Hodgkin’s lymphoma caused by implant materials led a recall of textured-typed implants for breast reconstruction. Such situation led patients head for breast reconstruction using autologous tissue. In case of well-developed breasts, either rectus abdominal musculocutaneous flap or deep inferior epigastric perforator flap is frequently selected for breast reconstruction. The former flap is well-vascularized but rectus abdominal muscle is used to transpose the flap, which could cause the herniation of the abdominal wall as a complication at late-stage. In the latter flap, since abdominal fat tissue is used, reconstructed breasts are similar to original breasts, while operation periods are relatively long in order to anastomose vessels under microscopy. Besides, thrombosis in anastomosed vessels could cause the total necrosis of reconstructed breasts.To overcome the disadvantages of the both methods, rectus abdominal musculocutaneous flaps anastomosed with vessels in the recipient region (i.e., Supercharged flap) have been developed. Here, we will describe seven cases with supercharged flaps to reconstruct breasts performed in our hospital

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Challenges of mismatching timescales in longitudinal studies of collective behaviour

How individuals’ prior experience and population evolutionary history shape emergent patterns in animal collectives remains a major gap in the study of collective behaviour. One reason for this is that the processes that can shape individual contributions to collective actions can happen over very different timescales from each other and from the collective actions themselves, resulting in mismatched timescales. For example, a preference to move towards a specific patch might arise from phenotype, memory or physiological state. Although providing critical context to collective actions, bridging different timescales remains conceptually and methodologically challenging. Here, we briefly outline some of these challenges, and discuss existing approaches that have already generated insights into the factors shaping individual contributions in animal collectives. We then explore a case study of mismatching timescales—defining relevant group membership—by combining fine-scaled GPS tracking data and daily field census data from a wild population of vulturine guineafowl ( Acryllium vulturinum ). We show that applying different temporal definitions can produce different assignments of individuals into groups. These assignments can then have consequences when determining individuals' social history, and thus the conclusions we might draw on the impacts of the social environment on collective actions. This article is part of a discussion meeting issue ‘Collective behaviour through time’

Data from: Challenges of mismatching timescales in longitudinal studies of collective behaviour

Datasets and R scripts for the analysis in Ogino M, Strauss E, Farine D. 2022. Challenges of mismatching timescales in longitudinal studies of collective behaviour (doi.org/10.1098/rstb.2022.0064). 20201001_20201031, 20201101_20201130, 10101201_20211231, 20210101_20210131, 20210201_20210228, 20210301_20210331: files containing daily averaged GPS pairwise distance between males for each month Seasons_Monthly.csv: dataset containing the metadata for each sampling periods Census.Rdata: dataset (list) with dataframes for individual metadata (data$Birds) and census observation data (data$ind_obs, data$grp_obs). The grp_obs dataframe contains the metadata for the ind_obs dataset. Script1_GroupDetection.r: code to detect group memberships over time, using different approaches Script2_GPSpairwisedistance.R: code to produce the boxplot showing averaged GPS pairwise distances within detected communities and GLM to quantify how methodological processes applied in different approaches drive differences in cohesiveness of detected groups. This code requires the outputs of Script1. Script3_GroupSize.R: code to produce the boxplots showing the distribution of detected social unit sizes and Jaccard similarity between social units in consecutive sampling periods, and GLM to quantidy how methodological processes drive differences in group size and Jaccard similarity.  This code requires the outputs of Script1 and Script2.</p

Group-level differences in social network structure remain repeatable after accounting for environmental drivers

Individuals show consistent between-individual behavioural variation when they interact with conspecifics or heterospecifics. Such patterns might underlie emergent group-specific behavioural patterns and between-group behavioural differences. However, little is known about (i) how social and non-social drivers (external drivers) shape group-level social structures and (ii) whether animal groups show consistent between-group differences in social structure after accounting for external drivers. We used automated tracking to quantify daily social interactions and association networks in 12 colonies of zebra finches (Taeniopygia guttata). We quantified the effects of five external drivers (group size, group composition, ecological factors, physical environments and methodological differences) on daily interaction and association networks and tested whether colonies expressed consistent differences in day-to-day network structure after controlling for these drivers. Overall, we found that external drivers contribute significantly to network structure. However, even after accounting for the contribution of external drivers, there remained significant support for consistent between-group differences in both interaction (repeatability R: up to 0.493) and association (repeatability R: up to 0.736) network structures. Our study demonstrates how group-level differences in social behaviour can be partitioned into different drivers of variation, with consistent contributions from both social and non-social factors.publishe

Data from: Group-level differences in social network structure remain repeatable after accounting from environmental drivers

Datasets and R scripts for the analysis in Ogino M,  Maldonado-Chaparro A, Aplin L, Farine D. 2023. Group-level differences in social network structure remain repeatable after accounting from environmental drivers. Data: AllAdults.csv: List of individuals in aviaries Aviary_metrics_daily_Pre_Socper.csv, Aviary_metrics_daily_Post_Socper.csv, Aviary_metrics_daily_Pre_Feeder.csv, Aviary_metrics_daily_Post_Feeder.csv: files containing all response variables (colony-level social network metrics), predictors (external drivers), and random effects (colony ID, day ID) Socper_CameraDetection_EachDay.csv, Feeder_CameraDetection_EachDay.csv: the number of camera detections for each day for each colony SocPerch_dailyNWs_Allday, Feeding_dailyNWs_Allday: Social networks for each day for each colony WeatherInfo: temperature and humidity data for each day R scripts: Script1__DailySocialNetworkMetrics.R: code to determine colony-level social network metrics Script2__InformedModel__PlottingGLM_FixedEffects_Post_Socper.R: code to visualise the effects of each external driver on colony-level social network metrics. This code requires outcome from Script 1 and a function (FUNCTION__PlottingFunction.R) below. Script2__InformedModel__Repeatability_informedmodels_bootstrapping.R, Script2__UninformedModel__Repeatability_uninformedmodels_bootstrapping.R: code to determine confidence intervals for the repeatability estimates of colony ID. This code requires outcome from Script 1 and functions below. Script2__InformedModel__Repeatability_Post_Socper_brms.R, Script2__UninformedModel__Repeatability_False-Positive-Model_brms.R: code to estimate repeatability estimates of colony ID. This code requires outcome from Script 1. Script2__InformedModel__Rsquare_Post_Socper.R: code to estimate R square for each model. This code requires outcome from Script 1 and a function (FUNCTION__get_variance_components) below. Script2__VIF.R: code to check collinearity. FUNCTION__get_variance_components.R: function to determine R square values. FUNCTION__PlottingFunction.R: function to visualise the effect of external drivers on social network metrics.</p

Redes sociales animales: revelando las causas e implicaciones de la estructura social en la ecología y la evolución

The social decisions that individuals make, in terms of where to move, who to interact with and how frequently, scale up to generate social structure. Such structure has profound consequences: individuals each have a unique social environment, social interactions can amplify or dampen individual differences at the population level, and population-level ecological and evolutionary processes can be governed by higher-level ‘emergent properties’ of animal societies

Redes sociales animales: revelando las causas e implicaciones de la estructura social en la ecología y la evolución

The social decisions that individuals make, in terms of where to move, who to interact with and how frequently, scale up to generate social structure. Such structure has profound consequences: individuals each have a unique social environment, social interactions can amplify or dampen individual differences at the population level, and population-level ecological and evolutionary processes can be governed by higher-level ‘emergent properties’ of animal societies

The importance of individual-to-society feedbacks in animal ecology and evolution

1. The social decisions that individuals make—who to interact with and how frequently—gives rise to social structure. The resulting social structure then determines how individuals interact with their surroundings—resources and risks, pathogens and predators, competitors and cooperators.2. However, despite intensive research on (i) how individuals make social decisions and (ii) how social structure shapes social processes (e.g. cooperation, competition and conflict), there are still few studies linking these two perspectives. These perspectives represent two halves of a feedback loop: individual behaviour scales up to define the social environment, and this environment, in turn, feeds back by shaping the selective agents that drive individual behaviour.3. We first review well-established research areas that have captured both elements of this feedback loop—host-pathogen dynamics and cultural transmission. We then highlight areas where social structure is well studied but the two perspectives remain largely disconnected. Finally, we synthesise existing research on 14 distinct research topics to identify new prospects where the interplay between social structure and social processes are likely to be important but remain largely unexplored.4. Our review shows that the inherent links between individuals’ traits, their social decisions, social structure, and social evolution, warrant more consideration. By mapping the existing and missing connections among many research areas, our review highlights where explicitly considering social structure and the individual-to-society feedbacks can reveal new dimensions to old questions in ecology and evolution.accepte