Social influence and interaction bias can drive emergent behavioural specialization and modular social networks across systems

Tokita, Christopher K.; Tarnita, Corina E.

doi:10.1098/rsif.2019.0564

Cited by 14 publications

(12 citation statements)

References 80 publications

(121 reference statements)

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“…While we focused on the simplest model that could recapitulate our empirical results, we recognize that DOL can be influenced by an even broader set of parameters, whose roles deserve further empirical and theoretical work. For example, experience and social interactions [28,[80][81][82] might dynamically change individual thresholds [36] and/or task efficiency [34,83] over time, potentially modulating the effects observed here. It will be important to consider such effects in future theoretical extensions.…”

Section: Discussionmentioning

confidence: 96%

Response thresholds alone cannot explain empirical patterns of division of labor in social insects

et al. 2021

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The effects of heterogeneity in group composition remain a major hurdle to our understanding of collective behavior across disciplines. In social insects, division of labor (DOL) is an emergent, colony-level trait thought to depend on colony composition. Theoretically, behavioral response threshold models have most commonly been employed to investigate the impact of heterogeneity on DOL. However, empirical studies that systematically test their predictions are lacking because they require control over colony composition and the ability to monitor individual behavior in groups, both of which are challenging. Here, we employ automated behavioral tracking in 120 colonies of the clonal raider ant with unparalleled control over genetic, morphological, and demographic composition. We find that each of these sources of variation in colony composition generates a distinct pattern of behavioral organization, ranging from the amplification to the dampening of inherent behavioral differences in heterogeneous colonies. Furthermore, larvae modulate interactions between adults, exacerbating the apparent complexity. Models based on threshold variation alone only partially recapitulate these empirical patterns. However, by incorporating the potential for variability in task efficiency among adults and task demand among larvae, we account for all the observed phenomena. Our findings highlight the significance of previously overlooked parameters pertaining to both larvae and workers, allow the formulation of theoretical predictions for increasing colony complexity, and suggest new avenues of empirical study.

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Section: Discussionmentioning

confidence: 96%

Response thresholds alone cannot explain empirical patterns of division of labor in social insects

et al. 2021

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“…Assessing how the quantified patterns emerged based on decision making in individuals is our next question for understanding task allocation. Previous studies have shown that the interactions between individuals and division of labour can have substantial interplay [63]. Thus, it is imperative to integrate individual-behaviour networks revealed here into the interaction networks between individuals.…”

Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Bipartite network analysis of ant-task associations reveals task groups and absence of colonial daily activity

Fujioka

Okada

Abe

2020

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Division of labour is the key factor leading to higher-order systems such as cooperative animal groups. How division of labour is achieved without a central control is one of the most fascinating questions in behavioural ecology and complex systems science. Social insects are one of the best examples of complex self-organised systems through local interactions. However, it is difficult to comprehensively understand division of labour due to the chronological and individual variation in behaviours, and the differences between social environments. Thus, it is imperative to quantify individual behaviours and integrate them into colony levels. Here, we demonstrate that network analyses on individual-behaviour relationships can be valid for characterising the task allocation patterns. We recorded the behaviours of all individuals with verified age in colonies of monomorphic ant and analysed the individual-behaviour relationship at individual, sub-network, and network-levels. We detected the "task groups" including subsets of individuals and behaviour, and the patterns of task groups were consistent throughout the day. We also found a relationship between the age and the characteristics of individuals within the network. These findings suggest that bipartite network analyses can untangle the complex task allocation patterns and provide novel insights into understanding how division of labour is achieved.How the simple elements at a lower level, for example, a single cell and an individual, can evolve to higher-level systems, for instance, multicellular organisms and animal groups, through natural selection has been a central question in evolutionary biology [1]. Such systems often exhibit division of labour through efficient task allocation, in which different elements perform different tasks [2]. It has been considered that division of labour can be a primary advantage for social evolution [3,4]. Therefore, it is crucial to understand how they achieve division of labour.Social insects are one of the most sophisticated examples of division of labour because individuals exhibit a reproductive division of labour between queen(s) and workers; and among workers various tasks are allocated. For example, task allocation for nursing, foraging, nest defence, or cleaning is accomplished without central controls in a colony [5][6][7]. To elucidate how such colonies achieve task allocation through interactions among individuals, we need to reveal the behavioural rules underlying it. However, it is difficult not only to determine the behavioural rules but also to describe and quantify the individual behavioural patterns. The difficulty in measuring these parameters arises from the fact that a large number of individuals comprise a colony, and that the behavioural differences depend on internal states, experience, colony size, demands from the nestmates, or environment, that can change across time [8][9][10][11][12][13][14]. Moreover, colonies generally consist of individuals with different characteristics such as morphology, age, ...

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“…Assessing how the quantified patterns emerged based on decision making in individuals is our next question for understanding task allocation. Previous studies have shown that the interactions between individuals and division of labour can have substantial interplay [ 14 , 75 ]. Thus, it is imperative to integrate individual-behaviour networks revealed here into the interaction networks between individuals.…”

Section: Discussionmentioning

confidence: 99%

“…Further studies are needed to examine how interactions affect individual decision making and subsequent task allocation patterns. One possible way is to analyse mathematical models to construct the patterns of the networks from rules at individual levels [ 3 , 75 , 76 ]. The network perspective can capture complex phenomena composed of many elements and extract important information at multiple levels.…”

Section: Discussionmentioning

confidence: 99%

Bipartite network analysis of ant-task associations reveals task groups and absence of colonial daily activity

2021

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Social insects are one of the best examples of complex self-organized systems exhibiting task allocation. How task allocation is achieved is the most fascinating question in behavioural ecology and complex systems science. However, it is difficult to comprehensively characterize task allocation patterns due to behavioural complexity, such as the individual variation, context dependency and chronological variation. Thus, it is imperative to quantify individual behaviours and integrate them into colony levels. Here, we applied bipartite network analyses to characterize individual-behaviour relationships. We recorded the behaviours of all individuals with verified age in ant colonies and analysed the individual-behaviour relationship at the individual, module and network levels. Bipartite network analysis successfully detected the module structures, illustrating that certain individuals performed a subset of behaviours (i.e. task groups). We confirmed age polyethism by comparing age between modules. Additionally, to test the daily rhythm of the executed tasks, the data were partitioned between daytime and nighttime, and a bipartite network was re-constructed. This analysis supported that there was no daily rhythm in the tasks performed. These findings suggested that bipartite network analyses could untangle complex task allocation patterns and provide insights into understanding the division of labour.

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Social influence and interaction bias can drive emergent behavioural specialization and modular social networks across systems

Cited by 14 publications

References 80 publications

Response thresholds alone cannot explain empirical patterns of division of labor in social insects

Response thresholds alone cannot explain empirical patterns of division of labor in social insects

Bipartite network analysis of ant-task associations reveals task groups and absence of colonial daily activity

Bipartite network analysis of ant-task associations reveals task groups and absence of colonial daily activity

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