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Ross CT, McElreath R, Redhead D. Modelling animal network data in R using STRAND. J Anim Ecol 2024; 93:254-266. [PMID: 37936514 DOI: 10.1111/1365-2656.14021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 09/27/2023] [Indexed: 11/09/2023]
Abstract
There have been recent calls for wider application of generative modelling approaches in applied social network analysis. At present, however, it remains difficult for typical end users-for example, field researchers-to implement generative network models, as there is a dearth of openly available software packages that make application of such models as simple as other, permutation-based approaches. Here, we outline the STRAND R package, which provides a suite of generative models for Bayesian analysis of animal social network data that can be implemented using simple, base R syntax. To facilitate ease of use, we provide a tutorial demonstrating how STRAND can be used to model proportion, count or binary network data using stochastic block models, social relation models or a combination of the two modelling frameworks. STRAND facilitates the application of generative network models to a broad range of data found in the animal social networks literature.
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Affiliation(s)
- Cody T Ross
- Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Richard McElreath
- Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Daniel Redhead
- Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
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2
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Toth JM, Fewell JH, Waters JS. Scaling of ant colony interaction networks. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2022.993627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
In social insect colonies, individuals are physically independent but functionally integrated by interaction networks which provide a foundation for communication and drive the emergence of collective behaviors, including nest architecture, division of labor, and potentially also the social regulation of metabolic rates. To investigate the relationship between interactions, metabolism, and colony size, we varied group size for harvester ant colonies (Pogonomyrmex californicus) and assessed their communication networks based on direct antennal contacts and compared these results with proximity networks and a random movement simulation. We found support for the hypothesis of social regulation; individuals did not interact with each other randomly but exhibited restraint. Connectivity scaled hypometrically with colony size, per-capita interaction rate was scale-invariant, and smaller colonies exhibited higher measures of closeness centrality and edge density, correlating with higher per-capita metabolic rates. Although the immediate energetic cost for two ants to interact is insignificant, the downstream effects of receiving and integrating social information can have metabolic consequences. Our results indicate that individuals in larger colonies are relatively more insulated from each other, a factor that may reduce or filter noisy stimuli and contribute to the hypometric scaling of their metabolic rates, and perhaps more generally, the evolution of larger colony sizes.
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3
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Shpurov I, Froese T. Evidence of Critical Dynamics in Movements of Bees inside a Hive. ENTROPY (BASEL, SWITZERLAND) 2022; 24:1840. [PMID: 36554245 PMCID: PMC9777906 DOI: 10.3390/e24121840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/14/2022] [Accepted: 12/15/2022] [Indexed: 06/17/2023]
Abstract
Social insects such as honey bees exhibit complex behavioral patterns, and their distributed behavioral coordination enables decision-making at the colony level. It has, therefore, been proposed that a high-level description of their collective behavior might share commonalities with the dynamics of neural processes in brains. Here, we investigated this proposal by focusing on the possibility that brains are poised at the edge of a critical phase transition and that such a state is enabling increased computational power and adaptability. We applied mathematical tools developed in computational neuroscience to a dataset of bee movement trajectories that were recorded within the hive during the course of many days. We found that certain characteristics of the activity of the bee hive system are consistent with the Ising model when it operates at a critical temperature, and that the system's behavioral dynamics share features with the human brain in the resting state.
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4
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Hasenjager MJ, Franks VR, Leadbeater E. From dyads to collectives: a review of honeybee signalling. Behav Ecol Sociobiol 2022. [DOI: 10.1007/s00265-022-03218-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
AbstractThe societies of honeybees (Apis spp.) are microcosms of divided labour where the fitness interests of individuals are so closely aligned that, in some contexts, the colony behaves as an entity in itself. Self-organization at this extraordinary level requires sophisticated communication networks, so it is not surprising that the celebrated waggle dance, by which bees share information about locations outside the hive, evolved here. Yet bees within the colony respond to several other lesser-known signalling systems, including the tremble dance, the stop signal and the shaking signal, whose roles in coordinating worker behaviour are not yet fully understood. Here, we firstly bring together the large but disparate historical body of work that has investigated the “meaning” of such signals for individual bees, before going on to discuss how network-based approaches can show how such signals function as a complex system to control the collective foraging effort of these remarkable social insect societies.
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Abstract
Networks are fundamental for our understanding of complex systems. The study of networks has uncovered common principles that underlie the behavior of vastly different fields of study, including physics, biology, sociology, and engineering. One of these common principles is the existence of network motifs-small recurrent patterns that can provide certain features that are important for the specific network. However, it remains unclear how network motifs are joined in real networks to make larger circuits and what properties emerge from interactions between network motifs. Here, we develop a framework to explore the mesoscale-level behavior of complex networks. Considering network motifs as hypernodes, we define the rules for their interaction at the network's next level of organization. We develop a method to infer the favorable arrangements of interactions between network motifs into hypermotifs from real evolved and designed network data. We mathematically explore the emergent properties of these higher-order circuits and their relations to the properties of the individual minimal circuit components they combine. We apply this framework to biological, neuronal, social, linguistic, and electronic networks and find that network motifs are not randomly distributed in real networks but are combined in a way that both maintains autonomy and generates emergent properties. This framework provides a basis for exploring the mesoscale structure and behavior of complex systems where it can be used to reveal intermediate patterns in complex networks and to identify specific nodes and links in the network that are the key drivers of the network's emergent properties.
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Social information-mediated population dynamics in non-grouping prey. Behav Ecol Sociobiol 2022. [DOI: 10.1007/s00265-022-03215-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Abstract
Inadvertent social information (ISI) use, i.e., the exploitation of social cues including the presence and behaviour of others, has been predicted to mediate population-level processes even in the absence of cohesive grouping. However, we know little about how such effects may arise when the prey population lacks social structure beyond the spatiotemporal autocorrelation originating from the random movement of individuals. In this study, we built an individual-based model where predator avoidance behaviour could spread among randomly moving prey through the network of nearby observers. We qualitatively assessed how ISI use may affect prey population size when cue detection was associated with different probabilities and fitness costs, and characterised the structural properties of the emerging detection networks that would provide pathways for information spread in prey. We found that ISI use was among the most influential model parameters affecting prey abundance and increased equilibrium population sizes in most examined scenarios. Moreover, it could substantially contribute to population survival under high predation pressure, but this effect strongly depended on the level of predator detection ability. When prey exploited social cues in the presence of high predation risk, the observed detection networks consisted of a large number of connected components with small sizes and small ego networks; this resulted in efficient information spread among connected individuals in the detection networks. Our study provides hypothetical mechanisms about how temporary local densities may allow information diffusion about predation threats among conspecifics and facilitate population stability and persistence in non-grouping animals.
Significance statement
The exploitation of inadvertently produced social cues may not only modify individual behaviour but also fundamentally influence population dynamics and species interactions. Using an individual-based model, we investigated how the detection and spread of adaptive antipredator behaviour may cascade to changes in the demographic performance of randomly moving (i.e., non-grouping) prey. We found that social information use contributed to population stability and persistence by reducing predation-related per capita mortality and raising equilibrium population sizes when predator detection ability reached a sufficient level. We also showed that temporary detection networks had structural properties that allowed efficient information spread among prey under high predation pressure. Our work represents a general modelling approach that could be adapted to specific predator-prey systems and scrutinise how temporary local densities allow dynamic information diffusion about predation threats and facilitate population stability in non-grouping animals.
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Triad Analysis of Global Energy Trade Networks and Implications for Energy Trade Stability. ENERGIES 2022. [DOI: 10.3390/en15103673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
An international push to decarbonize economies has initiated a major transition in the global energy system and has begun to disrupt the intricate network of energy trade. As trade patterns begin to reconfigure, it is important that policy makers understand how vulnerabilities of the existing network may present obstacles to a smooth energy transition. We analyze the topology of the global energy trade network in aggregate, for various energy commodities, and for individual countries. Using the network science technique of triad analysis, which examines the prevalence of 3-node subnetworks in a target network, we calculate triad significance profiles for each network. We then analyze whether various triads are under- or over-represented in our networks and find that triads associated with stability appear more frequently than expected, whereas triads associated with conflict appear less frequently than expected. We further find that the global energy trade network is quite robust against disruptions, maintaining its topological characteristics even after random removal of 80% of the network’s nodes. However, when analyzing individual countries, we find that some exhibit a high prevalence of unstable triads or a low prevalence of stabilizing triads, suggesting that vulnerabilities in global energy trade are more pronounced in some countries than others.
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Easter C, Leadbeater E, Hasenjager MJ. Behavioural variation among workers promotes feed-forward loops in a simulated insect colony. ROYAL SOCIETY OPEN SCIENCE 2022; 9:220120. [PMID: 35316950 PMCID: PMC8889185 DOI: 10.1098/rsos.220120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 02/04/2022] [Indexed: 05/03/2023]
Abstract
Coordinated responses in eusocial insect colonies arise from worker interaction networks that enable collective processing of ecologically relevant information. Previous studies have detected a structural motif in these networks known as the feed-forward loop, which functions to process information in other biological regulatory networks (e.g. transcriptional networks). However, the processes that generate feed-forward loops among workers and the consequences for information flow within the colony remain largely unexplored. We constructed an agent-based model to investigate how individual variation in activity and movement shaped the production of feed-forward loops in a simulated insect colony. We hypothesized that individual variation along these axes would generate feed-forward loops by driving variation in interaction frequency among workers. We found that among-individual variation in activity drove over-representation of feed-forward loops in the interaction networks by determining the directionality of interactions. However, despite previous work linking feed-forward loops with efficient information transfer, activity variation did not promote faster or more efficient information flow, thus providing no support for the hypothesis that feed-forward loops reflect selection for enhanced collective functioning. Conversely, individual variation in movement trajectory, despite playing no role in generating feed-forward loops, promoted fast and efficient information flow by linking together otherwise unconnected regions of the nest.
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Affiliation(s)
- Carrie Easter
- School of Biology, University of Leeds, Leeds LS2 9JT, UK
| | - Ellouise Leadbeater
- Department of Biological Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - Matthew J. Hasenjager
- Department of Biological Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
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Shimoji H, Dobata S. The build-up of dominance hierarchies in eusocial insects. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200437. [PMID: 35000446 PMCID: PMC8743887 DOI: 10.1098/rstb.2020.0437] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 11/08/2021] [Indexed: 12/11/2022] Open
Abstract
Reproductive division of labour is a hallmark of eusocial insects. However, its stability can often be hampered by the potential for reproduction by otherwise sterile nest-mates. Dominance hierarchy has a crucial role in some species in regulating which individuals reproduce. Compared with those in vertebrates, the dominance hierarchies in eusocial insects tend to involve many more individuals, and should require additional selective forces unique to them. Here, we provide an overview of a series of studies on dominance hierarchies in eusocial insects. Although reported from diverse eusocial taxa, dominance hierarchies have been extensively studied in paper wasps and ponerine ants. Starting from molecular physiological attributes of individuals, we describe how the emergence of dominance hierarchies can be understood as a kind of self-organizing process through individual memory and local behavioural interactions. The resulting global structures can be captured by using network analyses. Lastly, we argue the adaptive significance of dominance hierarchies from the standpoint of sterile subordinates. Kin selection, underpinned by relatedness between nest-mates, is key to the subordinates' acceptance of their positions in the hierarchies. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.
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Affiliation(s)
- Hiroyuki Shimoji
- School of Biological and Environmental Sciences, Kwansei Gakuin University, Sanda, Hyogo 669-1337, Japan
| | - Shigeto Dobata
- Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Komaba, Meguro, Tokyo 153-8902, Japan
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10
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Lemanski N, Silk M, Fefferman N, Udiani O. How territoriality reduces disease transmission among social insect colonies. Behav Ecol Sociobiol 2021; 75:164. [PMID: 34866761 PMCID: PMC8630993 DOI: 10.1007/s00265-021-03095-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 10/03/2021] [Accepted: 10/11/2021] [Indexed: 12/22/2022]
Abstract
Abstract
Social behavior can have a major impact on the dynamics of infectious disease outbreaks. For animals that live in dense social groups, such as the eusocial insects, pathogens pose an especially large risk because frequent contacts among individuals can allow rapid spread within colonies. While there has been a large body of work examining adaptations to mitigate the spread of infectious disease within social insect colonies, there has been less work on strategies to prevent the introduction of pathogens into colonies in the first place. We develop an agent-based model to examine the effect of territorial behavior on the transmission of infectious diseases between social insect colonies. We find that by preventing the introduction of infected foreign workers into a colony, territoriality can flatten the curve of an epidemic, delaying the introduction of an infectious disease and reducing its maximum prevalence, but only for diseases with moderate to low transmissibility. Our results have implications for understanding how pathogen risk influences the evolution of territorial behavior in social insects and other highly social animals. Significance statement Infectious disease outbreaks can impose a large fitness cost to animals that live in social groups. The frequency and pattern of contacts both within and among groups can have a large impact on the speed and extent of an epidemic. Using an individual-based model, we examined how the exclusion of foreign workers from a territory around the nest influences disease transmission between social insect colonies. We find that territoriality can protect colonies from outbreaks of low to moderately contagious pathogens by delaying the spillover from other colonies and reducing the maximum number of workers who are infected. These results suggest that the relative threat posed by infectious diseases may have played an important role in shaping the diversity of territorial behaviors seen in different social insect species. Supplementary Information The online version contains supplementary material available at 10.1007/s00265-021-03095-0.
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Affiliation(s)
- Natalie Lemanski
- Department of Ecology, Evolution, & Natural Resources, Rutgers University, New Brunswick, NJ USA
| | - Matthew Silk
- Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville, TN USA
| | - Nina Fefferman
- Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville, TN USA
| | - Oyita Udiani
- Department of Mathematics and Applied Mathematics, Virginia Commonwealth University, Richmond, VA USA
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11
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Gareta García M, Farine DR, Brachotte C, Borgeaud C, Bshary R. Wild female vervet monkeys change grooming patterns and partners when freed from feeding constraints. Anim Behav 2021. [DOI: 10.1016/j.anbehav.2021.08.027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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12
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Quque M, Bles O, Bénard A, Héraud A, Meunier B, Criscuolo F, Deneubourg JL, Sueur C. Hierarchical networks of food exchange in the black garden ant Lasius niger. INSECT SCIENCE 2021; 28:825-838. [PMID: 32306510 DOI: 10.1111/1744-7917.12792] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 04/05/2020] [Accepted: 04/07/2020] [Indexed: 06/11/2023]
Abstract
In most eusocial insects, the division of labor results in relatively few individuals foraging for the entire colony. Thus, the survival of the colony depends on its efficiency in meeting the nutritional needs of all its members. Here, we characterize the network topology of a eusocial insect to understand the role and centrality of each caste in this network during the process of food dissemination. We constructed trophallaxis networks from 34 food-exchange experiments in black garden ants (Lasius niger). We tested the influence of brood and colony size on (i) global indices at the network level (i.e., efficiency, resilience, centralization, and modularity) and (ii) individual values (i.e., degree, strength, betweenness, and the clustering coefficient). Network resilience, the ratio between global efficiency and centralization, was stable with colony size but increased in the presence of broods, presumably in response to the nutritional needs of larvae. Individual metrics highlighted the major role of foragers in food dissemination. In addition, a hierarchical clustering analysis suggested that some domestics acted as intermediaries between foragers and other domestics. Networks appeared to be hierarchical rather than random or centralized exclusively around foragers. Finally, our results suggested that networks emerging from social insect interactions can improve group performance and thus colony fitness.
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Affiliation(s)
- Martin Quque
- CNRS, IPHC, Université de Strasbourg, Strasbourg, UMR718, France
| | - Olivier Bles
- Centre for Nonlinear Phenomena and Complex Systems (Cenoli)-CP 231, Université libre de Bruxelles (ULB), Bruxelles, Belgium
| | | | - Amélie Héraud
- CNRS, IPHC, Université de Strasbourg, Strasbourg, UMR718, France
| | | | | | - Jean-Louis Deneubourg
- Centre for Nonlinear Phenomena and Complex Systems (Cenoli)-CP 231, Université libre de Bruxelles (ULB), Bruxelles, Belgium
| | - Cédric Sueur
- CNRS, IPHC, Université de Strasbourg, Strasbourg, UMR718, France
- Institut Universitaire de France, Paris, France
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Fadul-Pacheco L, Liou M, Reinemann DJ, Cabrera VE. A Preliminary Investigation of Social Network Analysis Applied to Dairy Cow Behavior in Automatic Milking System Environments. Animals (Basel) 2021; 11:ani11051229. [PMID: 33923167 PMCID: PMC8146444 DOI: 10.3390/ani11051229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 04/20/2021] [Accepted: 04/23/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Cows are social animals, therefore understanding the ways that they interact can help improve their management and welfare. We used social network analysis (SNA) to data on voluntary cow movement through a sort gate in an automatic milking system to identify pairs of cows that repeatedly passed through a sort gate in close succession (affinity pairs). Results from this exploratory study showed that when cows were separated from their affinity-pair cow the day-day variability in milk production increased by a factor of 3, a possible indicator of stress. The results of this exploratory study suggest that SNA could be used as a tool to better understand the social dynamics of dairy cows and inform group and regrouping process to produce positive outcomes. Abstract We have applied social network analysis (SNA) to data on voluntary cow movement through a sort gate in an automatic milking system to identify pairs of cows that repeatedly passed through a sort gate in close succession (affinity pairs). The SNA was applied to social groups defined by four pens on a dairy farm, each served by an automatic milking system (AMS). Each pen was equipped with an automatic sorting gate that identified when cows voluntarily moved from the resting area to either milking or feeding areas. The aim of this study was two-fold: to determine if SNA could identify affinity pairs and to determine if milk production was affected when affinity pairs where broken. Cow traffic and milking performance data from a commercial guided-flow AMS dairy farm were used. Average number of milked cows was 214 ± 34, distributed in four AMS over 1 year. The SNA was able to identify clear affinity pairs and showed when these pairings were formed and broken as cows entered and left the social group (pen). The trend in all four pens was toward higher-than-expected milk production during periods of affinity. Moreover, we found that when affinities were broken (separation of cow pairs) the day-to-day variability in milk production was three times higher than for cows in an affinity pair. The results of this exploratory study suggest that SNA could be potentially used as a tool to reduce milk yield variation and better understand the social dynamics of dairy cows supporting management and welfare decisions.
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Affiliation(s)
- Liliana Fadul-Pacheco
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA;
- Correspondence:
| | - Michael Liou
- Department of Statistical Science, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Douglas J. Reinemann
- Biological and Systems Engineering Department, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Victor E. Cabrera
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA;
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Fujioka H, Okada Y, Abe MS. Bipartite network analysis of ant-task associations reveals task groups and absence of colonial daily activity. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201637. [PMID: 33614094 PMCID: PMC7890512 DOI: 10.1098/rsos.201637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 12/11/2020] [Indexed: 06/12/2023]
Abstract
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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Affiliation(s)
- Haruna Fujioka
- Graduate School of Arts and Sciences, the University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo, Japan
- Graduate School of Science, Osaka City University, 3-3-138 Sugimoto-cho, Sumiyoshi-ku, Osaka 558-8585, Japan
| | - Yasukazu Okada
- Department of Biological Sciences, Tokyo Metropolitan University, 1-1 Minamiosawa, Hachioji, Tokyo, Japan
| | - Masato S. Abe
- Center for Advanced Intelligence Project, RIKEN, Nihonbashi 1-chome Mitsui Building, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
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15
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Valentini G, Masuda N, Shaffer Z, Hanson JR, Sasaki T, Walker SI, Pavlic TP, Pratt SC. Division of labour promotes the spread of information in colony emigrations by the ant Temnothorax rugatulus. Proc Biol Sci 2020; 287:20192950. [PMID: 32228408 PMCID: PMC7209055 DOI: 10.1098/rspb.2019.2950] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 03/06/2020] [Indexed: 01/23/2023] Open
Abstract
The fitness of group-living animals often depends on how well members share information needed for collective decision-making. Theoretical studies have shown that collective choices can emerge in a homogeneous group of individuals following identical rules, but real animals show much evidence for heterogeneity in the degree and nature of their contribution to group decisions. In social insects, for example, the transmission and processing of information is influenced by a well-organized division of labour. Studies that accurately quantify how this behavioural heterogeneity affects the spread of information among group members are still lacking. In this paper, we look at nest choices during colony emigrations of the ant Temnothorax rugatulus and quantify the degree of behavioural heterogeneity of workers. Using clustering methods and network analysis, we identify and characterize four behavioural castes of workers-primary, secondary, passive and wandering-covering distinct roles in the spread of information during an emigration. This detailed characterization of the contribution of each worker can improve models of collective decision-making in this species and promises a deeper understanding of behavioural variation at the colony level.
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Affiliation(s)
- Gabriele Valentini
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Naoki Masuda
- Department of Mathematics, State University of New York, Buffalo, NY 14260, USA
- Computational and Data-Enabled Science and Engineering Program, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
| | - Zachary Shaffer
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Jake R. Hanson
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85287, USA
| | - Takao Sasaki
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
| | - Sara Imari Walker
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85287, USA
- ASU–SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85287, USA
| | - Theodore P. Pavlic
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85287, USA
- ASU–SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85287, USA
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
- School of Sustainability, Arizona State University, Tempe, AZ 85287, USA
| | - Stephen C. Pratt
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
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16
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Sosa S, Sueur C, Puga‐Gonzalez I. Network measures in animal social network analysis: Their strengths, limits, interpretations and uses. Methods Ecol Evol 2020. [DOI: 10.1111/2041-210x.13366] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Sebastian Sosa
- Université de StrasbourgCNRSIPHC UMR 7178 Strasbourg France
| | - Cédric Sueur
- Université de StrasbourgCNRSIPHC UMR 7178 Strasbourg France
- Institut Universitaire de France Paris France
| | - Ivan Puga‐Gonzalez
- Institute for Global Development and Planning University of Agder Kristiansand Norway
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17
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George EA, Brockmann A. Social modulation of individual differences in dance communication in honey bees. Behav Ecol Sociobiol 2019. [DOI: 10.1007/s00265-019-2649-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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18
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Abstract
Nest choice in Temnothorax spp.; task allocation and the regulation of activity in Pheidole dentata, Pogonomyrmex barbatus, and Atta spp.; and trail networks in Monomorium pharaonis and Cephalotes goniodontus all provide examples of correspondences between the dynamics of the environment and the dynamics of collective behavior. Some important aspects of the dynamics of the environment include stability, the threat of rupture or disturbance, the ratio of inflow and outflow of resources or energy, and the distribution of resources. These correspond to the dynamics of collective behavior, including the extent of amplification, how feedback instigates and inhibits activity, and the extent to which the interactions that provide the information to regulate behavior are local or spatially centralized.
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Affiliation(s)
- Deborah M Gordon
- Department of Biology, Stanford University, Stanford, California 94305-5020, USA;
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19
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Wang H, Lu Y, Shutters ST, Steptoe M, Wang F, Landis S, Maciejewski R. A Visual Analytics Framework for Spatiotemporal Trade Network Analysis. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2018; 25:331-341. [PMID: 30130225 DOI: 10.1109/tvcg.2018.2864844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Economic globalization is increasing connectedness among regions of the world, creating complex interdependencies within various supply chains. Recent studies have indicated that changes and disruptions within such networks can serve as indicators for increased risks of violence and armed conflicts. This is especially true of countries that may not be able to compete for scarce commodities during supply shocks. Thus, network-induced vulnerability to supply disruption is typically exported from wealthier populations to disadvantaged populations. As such, researchers and stakeholders concerned with supply chains, political science, environmental studies, etc. need tools to explore the complex dynamics within global trade networks and how the structure of these networks relates to regional instability. However, the multivariate, spatiotemporal nature of the network structure creates a bottleneck in the extraction and analysis of correlations and anomalies for exploratory data analysis and hypothesis generation. Working closely with experts in political science and sustainability, we have developed a highly coordinated, multi-view framework that utilizes anomaly detection, network analytics, and spatiotemporal visualization methods for exploring the relationship between global trade networks and regional instability. Requirements for analysis and initial research questions to be investigated are elicited from domain experts, and a variety of visual encoding techniques for rapid assessment of analysis and correlations between trade goods, network patterns, and time series signatures are explored. We demonstrate the application of our framework through case studies focusing on armed conflicts in Africa, regional instability measures, and their relationship to international global trade.
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20
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Waters JS, Ochs A, Fewell JH, Harrison JF. Differentiating causality and correlation in allometric scaling: ant colony size drives metabolic hypometry. Proc Biol Sci 2018; 284:rspb.2016.2582. [PMID: 28228514 DOI: 10.1098/rspb.2016.2582] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 02/01/2017] [Indexed: 11/12/2022] Open
Abstract
Metabolic rates of individual animals and social insect colonies generally scale hypometrically, with mass-specific metabolic rates decreasing with increasing size. Although this allometry has wide ranging effects on social behaviour, ecology and evolution, its causes remain controversial. Because it is difficult to experimentally manipulate body size of organisms, most studies of metabolic scaling depend on correlative data, limiting their ability to determine causation. To overcome this limitation, we experimentally reduced the size of harvester ant colonies (Pogonomyrmex californicus) and quantified the consequent increase in mass-specific metabolic rates. Our results clearly demonstrate a causal relationship between colony size and hypometric changes in metabolic rate that could not be explained by changes in physical density. These findings provide evidence against prominent models arguing that the hypometric scaling of metabolic rate is primarily driven by constraints on resource delivery or surface area/volume ratios, because colonies were provided with excess food and colony size does not affect individual oxygen or nutrient transport. We found that larger colonies had lower median walking speeds and relatively more stationary ants and including walking speed as a variable in the mass-scaling allometry greatly reduced the amount of residual variation in the model, reinforcing the role of behaviour in metabolic allometry. Following the experimental size reduction, however, the proportion of stationary ants increased, demonstrating that variation in locomotory activity cannot solely explain hypometric scaling of metabolic rates in these colonies. Based on prior studies of this species, the increase in metabolic rate in size-reduced colonies could be due to increased anabolic processes associated with brood care and colony growth.
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Affiliation(s)
- James S Waters
- Department of Biology, Providence College, Providence, RI 02918, USA
| | - Alison Ochs
- Mount Holyoke College, South Hadley, MA 01075, USA
| | - Jennifer H Fewell
- School of Life Sciences, Arizona State University, Tempe, AZ 85287-4601, USA
| | - Jon F Harrison
- School of Life Sciences, Arizona State University, Tempe, AZ 85287-4601, USA
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21
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O'Connor MP, O'Donnell S. Implications of iterative communication for biological system performance. J Theor Biol 2018; 436:93-104. [PMID: 28987465 DOI: 10.1016/j.jtbi.2017.09.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 09/23/2017] [Accepted: 09/26/2017] [Indexed: 11/16/2022]
Abstract
The performance of integrated biological systems can often be described by the behavior of component subunits: the proportion of subunits performing an activity, and the rate of recruitment to the activity, can be relevant to system performance. We develop a model for activation of subunits (receivers) to a task when activation requires repeated signals (iterative communication). The model predicts how system performance will be affected by the parameters of iterative communication. Receiver activation is influenced by the frequency of stimulation, by forgetting about past interactions, and by the number of stimuli needed to activate the receivers. These parameters, along with the probability of activated receivers returning to a de-activated state, modulate the system-wide time course of activation and the steady-state proportion of activated receivers. Parameters can interact to affect system-wide activation, and multiple parameter combinations can yield similar patterns of activation. Group performance is less variable at higher stimulation frequencies and in systems with greater numbers of receivers. Biological constraints on iterative communication, such as time and energy costs, may limit the parameter values that are feasible for a given system. Iterative communication parameters may be subject to natural selection at the system (group) level because they affect system performance.
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Affiliation(s)
- Michael P O'Connor
- Departments of Biodiversity Earth and Environmental Science and Biology, Drexel University, Philadelphia, PA 19104, USA
| | - Sean O'Donnell
- Departments of Biodiversity Earth and Environmental Science and Biology, Drexel University, Philadelphia, PA 19104, USA.
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22
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Gräwer J, Ronellenfitsch H, Mazza MG, Katifori E. Trophallaxis-inspired model for distributed transport between randomly interacting agents. Phys Rev E 2017; 96:022111. [PMID: 28950481 DOI: 10.1103/physreve.96.022111] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Indexed: 11/07/2022]
Abstract
Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.
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Affiliation(s)
- Johannes Gräwer
- Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen, Germany
| | - Henrik Ronellenfitsch
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Marco G Mazza
- Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen, Germany
| | - Eleni Katifori
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
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23
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Sueur C, Mery F. Editorial: Social Interaction in Animals: Linking Experimental Approach and Social Network Analysis. Front Psychol 2017; 8:35. [PMID: 28154548 PMCID: PMC5244467 DOI: 10.3389/fpsyg.2017.00035] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 01/06/2017] [Indexed: 11/13/2022] Open
Affiliation(s)
- Cédric Sueur
- Centre National de la Recherche Scientifique (CNRS), Institut Pluridisciplinaire Hubert Curien UMR 7178, Université de Strasbourg Strasbourg, France
| | - Frédéric Mery
- Evolution, Génomes, Comportement and Ecologie, Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD), Université Paris-Sud, Université Paris-Saclay Gif-sur-Yvette, France
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24
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Davidson JD, Arauco-Aliaga RP, Crow S, Gordon DM, Goldman MS. Effect of Interactions between Harvester Ants on Forager Decisions. Front Ecol Evol 2016; 4:115. [PMID: 28758093 PMCID: PMC5531068 DOI: 10.3389/fevo.2016.00115] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Harvester ant colonies adjust their foraging activity to day-to-day changes in food availability and hour-to-hour changes in environmental conditions. This collective behavior is regulated through interactions, in the form of brief antennal contacts, between outgoing foragers and returning foragers with food. Here we consider how an ant, waiting in the entrance chamber just inside the nest entrance, uses its accumulated experience of interactions to decide whether to leave the nest to forage. Using videos of field observations, we tracked the interactions and foraging decisions of ants in the entrance chamber. Outgoing foragers tended to interact with returning foragers at higher rates than ants that returned to the deeper nest and did not forage. To provide a mechanistic framework for interpreting these results, we develop a decision model in which ants make decisions based upon a noisy accumulation of individual contacts with returning foragers. The model can reproduce core trends and realistic distributions for individual ant interaction statistics, and suggests possible mechanisms by which foraging activity may be regulated at an individual ant level.
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Affiliation(s)
- Jacob D. Davidson
- Center for Neuroscience, University of California, Davis, Davis, CA, USA
| | | | - Sam Crow
- Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | | | - Mark S. Goldman
- Center for Neuroscience, University of California, Davis, Davis, CA, USA
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA, USA
- Department of Ophthalmology and Vision Science, University of California, Davis, Davis, CA, USA
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25
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Sasaki T, Janssen MA, Shaffer Z, Pratt SC. Exploration of unpredictable environments by networked groups. Curr Zool 2016; 62:207-214. [PMID: 29491907 PMCID: PMC5804274 DOI: 10.1093/cz/zow052] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 06/30/2015] [Indexed: 11/25/2022] Open
Abstract
Information sharing is a critical task for group-living animals. The pattern of sharing can be modeled as a network whose structure can affect the decision-making performance of individual members as well as that of the group as a whole. A fully connected network, in which each member can directly transfer information to all other members, ensures rapid sharing of important information, such as a promising foraging location. However, it can also impose costs by amplifying the spread of inaccurate information (if, for example the foraging location is actually not profitable). Thus, an optimal network structure should balance effective sharing of current knowledge with opportunities to discover new information. We used a computer simulation to measure how well groups characterized by different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment. We found that a fully connected network outperformed other structures when resource quality was predictable. When resource quality showed random variation, however, the small world network was better than the fully connected one at avoiding extremely poor outcomes. These results suggest that animal groups may benefit by adjusting their information-sharing network structures depending on the noisiness of their environment.
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Affiliation(s)
- Takao Sasaki
- School of Life Sciences and Center for Social Dynamics and Complexity, Arizona State University, Tempe AZ 85287-4501, USA.,Department of Zoology, University of Oxford, OX1 3PS, UK, and
| | - Marco A Janssen
- School of Sustainability and Center for Behavior, Institutions and the Environment, Arizona State University, Tempe, AZ 85287-5502, USA
| | - Zachary Shaffer
- School of Life Sciences and Center for Social Dynamics and Complexity, Arizona State University, Tempe AZ 85287-4501, USA
| | - Stephen C Pratt
- School of Life Sciences and Center for Social Dynamics and Complexity, Arizona State University, Tempe AZ 85287-4501, USA
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26
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Mersch DP. The social mirror for division of labor: what network topology and dynamics can teach us about organization of work in insect societies. Behav Ecol Sociobiol 2016. [DOI: 10.1007/s00265-016-2104-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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27
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Kim H, Davies P, Walker SI. New scaling relation for information transfer in biological networks. J R Soc Interface 2015; 12:20150944. [PMID: 26701883 PMCID: PMC4707865 DOI: 10.1098/rsif.2015.0944] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Accepted: 11/24/2015] [Indexed: 12/19/2022] Open
Abstract
We quantify characteristics of the informational architecture of two representative biological networks: the Boolean network model for the cell-cycle regulatory network of the fission yeast Schizosaccharomyces pombe (Davidich et al. 2008 PLoS ONE 3, e1672 (doi:10.1371/journal.pone.0001672)) and that of the budding yeast Saccharomyces cerevisiae (Li et al. 2004 Proc. Natl Acad. Sci. USA 101, 4781-4786 (doi:10.1073/pnas.0305937101)). We compare our results for these biological networks with the same analysis performed on ensembles of two different types of random networks: Erdös-Rényi and scale-free. We show that both biological networks share features in common that are not shared by either random network ensemble. In particular, the biological networks in our study process more information than the random networks on average. Both biological networks also exhibit a scaling relation in information transferred between nodes that distinguishes them from random, where the biological networks stand out as distinct even when compared with random networks that share important topological properties, such as degree distribution, with the biological network. We show that the most biologically distinct regime of this scaling relation is associated with a subset of control nodes that regulate the dynamics and function of each respective biological network. Information processing in biological networks is therefore interpreted as an emergent property of topology (causal structure) and dynamics (function). Our results demonstrate quantitatively how the informational architecture of biologically evolved networks can distinguish them from other classes of network architecture that do not share the same informational properties.
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Affiliation(s)
- Hyunju Kim
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA
| | - Paul Davies
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA
| | - Sara Imari Walker
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA ASU-SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ, USA Blue Marble Space Institute of Science, Seattle, WA, USA
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28
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Fontanari JF, Rodrigues FA. Influence of network topology on cooperative problem-solving systems. Theory Biosci 2015; 135:101-10. [DOI: 10.1007/s12064-015-0219-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2015] [Accepted: 11/14/2015] [Indexed: 11/28/2022]
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29
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Shizuka D, McDonald DB. The network motif architecture of dominance hierarchies. J R Soc Interface 2015; 12:rsif.2015.0080. [PMID: 25762649 DOI: 10.1098/rsif.2015.0080] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The widespread existence of dominance hierarchies has been a central puzzle in social evolution, yet we lack a framework for synthesizing the vast empirical data on hierarchy structure in animal groups. We applied network motif analysis to compare the structures of dominance networks from data published over the past 80 years. Overall patterns of dominance relations, including some aspects of non-interactions, were strikingly similar across disparate group types. For example, nearly all groups exhibited high frequencies of transitive triads, whereas cycles were very rare. Moreover, pass-along triads were rare, and double-dominant triads were common in most groups. These patterns did not vary in any systematic way across taxa, study settings (captive or wild) or group size. Two factors significantly affected network motif structure: the proportion of dyads that were observed to interact and the interaction rates of the top-ranked individuals. Thus, study design (i.e. how many interactions were observed) and the behaviour of key individuals in the group could explain much of the variations we see in social hierarchies across animals. Our findings confirm the ubiquity of dominance hierarchies across all animal systems, and demonstrate that network analysis provides new avenues for comparative analyses of social hierarchies.
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Affiliation(s)
- Daizaburo Shizuka
- School of Biological Sciences, University of Nebraska-Lincoln, 348 Manter Hall, PO Box 881108, Lincoln, NE 68588, USA
| | - David B McDonald
- Department of Zoology and Physiology, University of Wyoming, Laramie, WY 82071, USA
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30
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Nandi AK, Sumana A, Bhattacharya K. Social insect colony as a biological regulatory system: modelling information flow in dominance networks. J R Soc Interface 2015; 11:20140951. [PMID: 25320069 DOI: 10.1098/rsif.2014.0951] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony.
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Affiliation(s)
- Anjan K Nandi
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, Karnataka 560012, India
| | - Annagiri Sumana
- Department of Biological Sciences, Indian Institute of Science Education and Research-Kolkata, Mohanpur, West Bengal 741252, India
| | - Kunal Bhattacharya
- Department of Physics, Birla Institute of Technology and Science, Pilani, Rajasthan 333031, India
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31
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Fewell JH. Social Biomimicry: what do ants and bees tell us about organization in the natural world? ACTA ACUST UNITED AC 2015. [DOI: 10.1007/s10818-015-9207-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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32
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Quevillon LE, Hanks EM, Bansal S, Hughes DP. Social, spatial, and temporal organization in a complex insect society. Sci Rep 2015; 5:13393. [PMID: 26300390 PMCID: PMC4547134 DOI: 10.1038/srep13393] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Accepted: 07/23/2015] [Indexed: 12/01/2022] Open
Abstract
High-density living is often associated with high disease risk due to density-dependent epidemic spread. Despite being paragons of high-density living, the social insects have largely decoupled the association with density-dependent epidemics. It is hypothesized that this is accomplished through prophylactic and inducible defenses termed 'collective immunity'. Here we characterise segregation of carpenter ants that would be most likely to encounter infectious agents (i.e. foragers) using integrated social, spatial, and temporal analyses. Importantly, we do this in the absence of disease to establish baseline colony organization. Behavioural and social network analyses show that active foragers engage in more trophallaxis interactions than their nest worker and queen counterparts and occupy greater area within the nest. When the temporal ordering of social interactions is taken into account, active foragers and inactive foragers are not observed to interact with the queen in ways that could lead to the meaningful transfer of disease. Furthermore, theoretical resource spread analyses show that such temporal segregation does not appear to impact the colony-wide flow of food. This study provides an understanding of a complex society's organization in the absence of disease that will serve as a null model for future studies in which disease is explicitly introduced.
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Affiliation(s)
- Lauren E. Quevillon
- Center for Infectious Disease Dynamics, Penn State University, University Park, Pennsylvania, USA
- Department of Biology, Penn State University, University Park, Pennsylvania, USA
| | - Ephraim M. Hanks
- Center for Infectious Disease Dynamics, Penn State University, University Park, Pennsylvania, USA
- Department of Statistics, Penn State University, University Park, Pennsylvania, USA
| | - Shweta Bansal
- Department of Biology, Georgetown University, Washington, D.C., USA
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - David P. Hughes
- Center for Infectious Disease Dynamics, Penn State University, University Park, Pennsylvania, USA
- Department of Biology, Penn State University, University Park, Pennsylvania, USA
- Department of Entomology, Penn State University, University Park, Pennsylvania, USA
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33
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When doing nothing is something. How task allocation strategies compromise between flexibility, efficiency, and inactive agents. ACTA ACUST UNITED AC 2015. [DOI: 10.1007/s10818-015-9205-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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34
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Hasenjager MJ, Dugatkin LA. Social Network Analysis in Behavioral Ecology. ADVANCES IN THE STUDY OF BEHAVIOR 2015. [DOI: 10.1016/bs.asb.2015.02.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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35
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Pasquaretta C, Levé M, Claidière N, van de Waal E, Whiten A, MacIntosh AJJ, Pelé M, Bergstrom ML, Borgeaud C, Brosnan SF, Crofoot MC, Fedigan LM, Fichtel C, Hopper LM, Mareno MC, Petit O, Schnoell AV, di Sorrentino EP, Thierry B, Tiddi B, Sueur C. Social networks in primates: smart and tolerant species have more efficient networks. Sci Rep 2014; 4:7600. [PMID: 25534964 PMCID: PMC4274513 DOI: 10.1038/srep07600] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Accepted: 12/03/2014] [Indexed: 11/13/2022] Open
Abstract
Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities.
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Affiliation(s)
- Cristian Pasquaretta
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France
| | - Marine Levé
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France [3] Ecole Normale Supérieure, Paris, France
| | - Nicolas Claidière
- University of St Andrews, Centre for Social Learning and Cognitive Evolution, School of Psychology &Neuroscience, St Andrews, United Kingdom
| | - Erica van de Waal
- 1] University of St Andrews, Centre for Social Learning and Cognitive Evolution, School of Psychology &Neuroscience, St Andrews, United Kingdom [2] Inkawu Vervet Project, Mawana Game Reserve, Swart Mfolozi, KwaZulu Natal, South Africa
| | - Andrew Whiten
- 1] University of St Andrews, Centre for Social Learning and Cognitive Evolution, School of Psychology &Neuroscience, St Andrews, United Kingdom [2] Inkawu Vervet Project, Mawana Game Reserve, Swart Mfolozi, KwaZulu Natal, South Africa
| | - Andrew J J MacIntosh
- 1] Kyoto University, Primate Research Institute, Center for International Collaboration and Advanced Studies in Primatology Kanrin 41-2, Inuyama, Aichi, Japan 484-8506 [2] Kyoto University Wildlife Research Center, 2-24 Tanaka-Sekiden-cho, Sakyo, Kyoto, Japan 606-8203
| | - Marie Pelé
- Ethobiosciences, Research and Consultancy Agency in Animal Wellbeing and Behaviour, Strasbourg, France
| | | | - Christèle Borgeaud
- 1] Inkawu Vervet Project, Mawana Game Reserve, Swart Mfolozi, KwaZulu Natal, South Africa [2] University of Neuchâtel, Institute of Biology, Neuchâtel, Switzerland
| | - Sarah F Brosnan
- Department of Psychology &Language Research Center, Georgia State University, Atlanta, GA, 30302, USA
| | - Margaret C Crofoot
- 1] Department of Anthropology, University of California, Davis, 1 Shields Ave., Davis, CA 95616, U.S.A. [2] Smithsonian Tropical Research Institute, Ancon, Panama City, Panama
| | | | - Claudia Fichtel
- 1] Behavioral Ecology and Sociobiology Unit, German Primate Center, Göttingen, Germany [2] Courant Research Centre "Evolution of Social Behaviour", University of Göttingen, Germany
| | - Lydia M Hopper
- 1] Department of Psychology &Language Research Center, Georgia State University, Atlanta, GA, 30302, USA [2] Lester E. Fisher Center for the Study and Conservation of Apes, Lincoln Park Zoo, Chicago, IL, 60614, USA [3] Michale E. Keeling Center for Comparative Medicine and Research, UT MD Anderson Cancer Center, Bastrop, TX, 78602, USA
| | - Mary Catherine Mareno
- Michale E. Keeling Center for Comparative Medicine and Research, UT MD Anderson Cancer Center, Bastrop, TX, 78602, USA
| | - Odile Petit
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France [3] Unit of Social Ecology, CP231, Université libre de Bruxelles, Campus Plaine, Bd du triomphe, 1050 Brussels, Belgium
| | - Anna Viktoria Schnoell
- Courant Research Centre "Evolution of Social Behaviour", University of Göttingen, Germany
| | | | - Bernard Thierry
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France
| | - Barbara Tiddi
- 1] Cognitive Ethology Laboratory, German Primate Center, Goettingen, Germany [2] Courant Research Centre "Evolution of Social Behaviour", University of Göttingen, Germany
| | - Cédric Sueur
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France [3] Unit of Social Ecology, CP231, Université libre de Bruxelles, Campus Plaine, Bd du triomphe, 1050 Brussels, Belgium
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36
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Baracchi D, Cini A. A Socio-Spatial Combined Approach Confirms a Highly Compartmentalised Structure in Honeybees. Ethology 2014. [DOI: 10.1111/eth.12290] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- David Baracchi
- Research Centre for Psychology; School of Biological and Chemical Sciences; Queen Mary University of London; London UK
| | - Alessandro Cini
- Laboratoire Écologie & Évolution UMR 7625; Université Pierre et Marie Curie; Paris France
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37
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Abstract
As function units, network motifs have been detected to reveal evolutionary mechanisms of complex systems, such as biological networks, food webs, engineering networks and social networks. However, emergence of motifs in growing networks may be problematic due to large fluctuation of subgraph frequency in the initial stage. This paper contributes to present a method which can identify the emergence of motif in growing networks. Based on the Erdös-Rényi(E-R) random null model, the variation rate of expected frequency of subgraph at adjacent time points was used to define the suitable detection range for motif identification. Upper and lower boundaries of the range were obtained in analytical form according to a chosen risk level. Then, the statistical metric Z-score was extended to a new one,, which effectively reveals the statistical significance of subgraph in a continuous period of time. In this paper, a novel research framework of motif identification was proposed, defining critical boundaries for the evolutionary process of networks and a significance metric of time scale. Finally, an industrial ecosystem at Kalundborg was adopted as a case study to illustrate the effectiveness and convenience of the proposed methodology.
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Affiliation(s)
- Haijia Shi
- State Key Joint-Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Lei Shi
- State Key Joint-Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
- * E-mail:
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38
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Kleinhappel TK, Burman OHP, John EA, Wilkinson A, Pike TW. Diet-mediated social networks in shoaling fish. Behav Ecol 2014. [DOI: 10.1093/beheco/aru006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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39
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Pinter-Wollman N, Hobson EA, Smith JE, Edelman AJ, Shizuka D, de Silva S, Waters JS, Prager SD, Sasaki T, Wittemyer G, Fewell J, McDonald DB. The dynamics of animal social networks: analytical, conceptual, and theoretical advances. Behav Ecol 2013. [DOI: 10.1093/beheco/art047] [Citation(s) in RCA: 278] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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40
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Charbonneau D, Blonder B, Dornhaus A. Social Insects: A Model System for Network Dynamics. UNDERSTANDING COMPLEX SYSTEMS 2013. [DOI: 10.1007/978-3-642-36461-7_11] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
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41
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Kovanen L, Karsai M, Kaski K, Kertész J, Saramäki J. Temporal Motifs. UNDERSTANDING COMPLEX SYSTEMS 2013. [DOI: 10.1007/978-3-642-36461-7_6] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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