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opencc-zeroMar 2022View details →

Datasets and R code for: Brood as booty: The effect of colony size and resource value in social insect contests

From the Manuscript: Animals engage in contests for access to resources like food, mates, and space. Intergroup contests between groups of organisms have received little attention, and it remains unresolved what information groups might use collectively to make contest decisions. We staged whole-colony contests using ant colonies (Temnothorax rugatulus), which perceive conspecific colonies as both a threat and resource from which to steal brood. We recorded individual behaviors and used demographic characteristics as proxies for resource value (number of brood items) and fighting ability (number of workers). We found that ants altered their fighting effort depending on the relative number of workers of their opponent. While the proximate mechanism for this ability remains uncertain, we found that colonies increased fighting when their opponent had relatively more brood, but not if opposing colonies had relatively many more workers. This suggests that ant colonies can use information about opposing colonies that shapes contest strategies. Further, the behavior of opposing colonies were strongly correlated with each other despite colony size differences ranging from 4-51%, consistent with the hypothesis that colonies can use opponent information. The behavior of a distributed, collective system of many individuals, like a eusocial insect colony, thus fits several predictions of contest models designed for individuals if we consider the gain and loss of worker ants analogous to energetic costs accrued during typical dyadic contests.

(c) simulation on Repast: after queen adaptive development-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS

On figures (b) and (c), simulations on RePast [11, 16, 18] are provided at successive times. The last figure shows the adaptive mechanism of the queen which grows with time according to the material density around it, like in natural observations.

Figure 7: Cultural equipment dynamics modeling-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS

The multi-template modelling can be used to model cultural equipment dynamics as described in figure 7. On this figure, we associate a queen to each cultural center (cinema, theatre, ...). Each queen will emit many pheromon templates, each template is associated to a specific criterium (according to age, sex, ...). Initially, we put the material in the residential place. Each material has some characteristics, corresponding to the people living in this residential area. The simulation shows the self-organization processus as the result of the set of the attractive effect of all the centers and all the templates.

Figure 4: Complexity of geographical space with respect of emergent organizations-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS

The applications we focus on in the models that we will propose in the following, concerns specifically the multi-center (or multi-organizational) phenomona inside urban development. As an artificial ecosystem, the city development has to deal with many challenges, specifically for sustainable development, mixing economical, social and environmental aspects. The decentralized methodology proposed in the following allows to deal with multi-criteria problems, leading to propose a decision making assistance, based on simulation analysis.

Figure 1: Complex spatial organizational model-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS

On Figure 1, we describe a two-level model of spatial self-organizations with interactions in both directions between these two levels: the emergence of organizations from entities interactions but also the feed-back process describing how organizations are regulating their own entities.

Figure 2: Optimization in natural ants collective behavior: foraging and clustering (from [8])-Self-organization and social insects algorithms

On figure 2, two examples of self-organization in natural ants are presented. On the left side, the well-known Deneubourg experiment consists to highlight with a very simple device the ant foraging problem. The ant objectives is to find the optimal way from nest to food source, using pheromone trail deposition. On the right side, cemetery clustering formation are shown at 4 successive times: ants form piles of corpses to clean their nests. Each of them has elementary actions, unknowing the whole situation, but dealing only with local information. There is no supervisor to lead the piles formation which emerges from ant interactions.

opencc-zeroNov 2022View details →

Data for: Intergenerational genotypic interactions drive collective behavioural cycles in a social insect

Many social animals display collective activity cycles based on synchronous behavioural oscillations across group members. A classic example is the colony cycle of army ants, where thousands of individuals undergo stereotypical biphasic behavioural cycles of about one month. Cycle phases coincide with brood developmental stages, but the regulation of this cycle is otherwise poorly understood. Here, we probe the regulation of cycle duration through interactions between brood and workers in an experimentally amenable army ant relative, the clonal raider ant. We first establish that cycle length varies across clonal lineages using long-term monitoring data. We then investigate the putative sources and impacts of this variation in a cross-fostering experiment with four lineages combining developmental, morphological, and automated behavioural tracking analyses. We show that cycle length variation stems from variation in the duration of the larval developmental stage, and that this stage can be prolonged not only by the clonal lineage of brood (direct genetic effects), but also of the workers (indirect genetic effects). We find similar indirect effects of worker line on brood adult size and, conversely but more surprisingly, indirect genetic effects of the brood on worker behaviour (walking speed and time spent in the nest).

opencc-zeroNov 2022View details →

Two simple movement mechanisms for spatial division of labour in social insects

Many animal species divide space into a patchwork of home ranges, yet there is little consensus on the mechanisms individuals use to maintain fidelity to particular locations. Theory suggests that animal movement could be based upon simple behavioural rules that use local information such as olfactory deposits, or global strategies, such as long-range biases toward landmarks. However, empirical studies have rarely attempted to distinguish between these mechanisms. Here, we perform individual tracking experiments on four species of social insects, and find that colonies consist of different groups of workers that inhabit separate but partially-overlapping spatial zones. Our trajectory analysis and simulations suggest that worker movement is consistent with two local mechanisms: one in which workers increase movement diffusivity outside their primary zone, and another in which workers modulate turning behaviour when approaching zone boundaries. Parallels with other organisms suggest that local mechanisms might represent a universal method for spatial partitioning in animal populations.

opencc-by-4.0Dec 2022View details →

Social signal learning of referential communication in a social insect

This is the dataset for a paper showing that honey bees can use social learning to improve their waggle dancing.

opencc-zeroMar 2023View details →

Supplementary data for: Transcriptomics of mosaic brain differentiation underlying complex division of labor in a social insect

Concerted developmental programming may constrain changes in component structures of the brain, thus limiting the ability of selection acting on individual brain compartments to form an adaptive mosaic independent of total brain size or body size. Measuring patterns of gene expression underpinning brain scaling in conjunction with anatomical brain atlases can aid in identifying influences of concerted and/or mosaic evolution. Species exhibiting exceptional size and behavioral polyphenisms provide excellent systems to test predictions of brain evolution models by quantifying brain gene expression. We examined patterns of brain gene expression in a remarkably polymorphic and behaviorally complex social insect, the leafcutter ant Atta cephalotes. Approximately ~50% of differential gene expression observed among three morphologically, behaviorally, and neuroanatomically differentiated worker size groups was attributable to body size, but we also found strong evidence of differential brain gene expression unexplained by worker morphological variation. Transcriptomic analysis identified patterns of gene expression not linearly correlated with worker size but rather, in some cases, mirroring neuropil scaling. Additionally, we observed enriched gene ontology terms associated with nucleic acid regulation, metabolism, neurotransmission, and sensory perception, further supporting a relationship between brain gene expression and worker social role. These findings demonstrate that differential brain gene expression among polymorphic workers is linked to behavioral and neuroanatomical differentiation underpinning complex agrarian division of labor in A. cephalotes.

publicMar 2023View details →

Supplementary data for: Transcriptomics of mosaic brain differentiation underlying complex division of labor in a social insect

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publicMar 2022View details →

Datasets and R code for: Brood as booty: The effect of colony size and resource value in social insect contests

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publicNov 2022View details →

Two simple movement mechanisms for spatial division of labour in social insects

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