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Chen J, Guo X, Charbonneau D, Azizi A, Fewell J, Kang Y. Dynamics of Information Flow and Task Allocation of Social Insect Colonies: Impacts of Spatial Interactions and Task Switching. Bull Math Biol 2024; 86:50. [PMID: 38581473 DOI: 10.1007/s11538-024-01280-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/03/2024] [Indexed: 04/08/2024]
Abstract
Models of social interaction dynamics have been powerful tools for understanding the efficiency of information spread and the robustness of task allocation in social insect colonies. How workers spatially distribute within the colony, or spatial heterogeneity degree (SHD), plays a vital role in contact dynamics, influencing information spread and task allocation. We used agent-based models to explore factors affecting spatial heterogeneity and information flow, including the number of task groups, variation in spatial arrangements, and levels of task switching, to study: (1) the impact of multiple task groups on SHD, contact dynamics, and information spread, and (2) the impact of task switching on SHD and contact dynamics. Both models show a strong linear relationship between the dynamics of SHD and contact dynamics, which exists for different initial conditions. The multiple-task-group model without task switching reveals the impacts of the number and spatial arrangements of task locations on information transmission. The task-switching model allows task-switching with a probability through contact between individuals. The model indicates that the task-switching mechanism enables a dynamical state of task-related spatial fidelity at the individual level. This spatial fidelity can assist the colony in redistributing their workforce, with consequent effects on the dynamics of spatial heterogeneity degree. The spatial fidelity of a task group is the proportion of workers who perform that task and have preferential walking styles toward their task location. Our analysis shows that the task switching rate between two tasks is an exponentially decreasing function of the spatial fidelity and contact rate. Higher spatial fidelity leads to more agents aggregating to task location, reducing contact between groups, thus making task switching more difficult. Our results provide important insights into the mechanisms that generate spatial heterogeneity and deepen our understanding of how spatial heterogeneity impacts task allocation, social interaction, and information spread.
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Affiliation(s)
- Jun Chen
- Simon A. Levin Mathematical and Computational Modeling Sciences Center, Arizona State University, 1031 Palm Walk, Tempe, AZ, 85281, USA
| | - Xiaohui Guo
- School of Life Sciences, Arizona State University, Tempe, AZ, 85281, USA
| | | | - Asma Azizi
- Department of Mathematics, Kennesaw State University, Marrieta, GA, 30060, USA
| | - Jennifer Fewell
- School of Life Sciences, Arizona State University, Tempe, AZ, 85281, USA
| | - Yun Kang
- Sciences and Mathematics Faculty, College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ, 85212, USA.
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2
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Bhaumik J, Masuda N. Fixation probability in evolutionary dynamics on switching temporal networks. J Math Biol 2023; 87:64. [PMID: 37768362 PMCID: PMC10539469 DOI: 10.1007/s00285-023-01987-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 08/03/2023] [Accepted: 08/13/2023] [Indexed: 09/29/2023]
Abstract
Population structure has been known to substantially affect evolutionary dynamics. Networks that promote the spreading of fitter mutants are called amplifiers of selection, and those that suppress the spreading of fitter mutants are called suppressors of selection. Research in the past two decades has found various families of amplifiers while suppressors still remain somewhat elusive. It has also been discovered that most networks are amplifiers of selection under the birth-death updating combined with uniform initialization, which is a standard condition assumed widely in the literature. In the present study, we extend the birth-death processes to temporal (i.e., time-varying) networks. For the sake of tractability, we restrict ourselves to switching temporal networks, in which the network structure deterministically alternates between two static networks at constant time intervals or stochastically in a Markovian manner. We show that, in a majority of cases, switching networks are less amplifying than both of the two static networks constituting the switching networks. Furthermore, most small switching networks, i.e., networks on six nodes or less, are suppressors, which contrasts to the case of static networks.
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Affiliation(s)
- Jnanajyoti Bhaumik
- Department of Mathematics, State University of New York at Buffalo, Buffalo, NY, 14260-2900, USA
| | - Naoki Masuda
- Department of Mathematics, State University of New York at Buffalo, Buffalo, NY, 14260-2900, USA.
- Computational and Data-Enabled Science and Engineering Program, State University of New York at Buffalo, Buffalo, NY, 14260-5030, USA.
- Center for Computational Social Science, Kobe University, Kobe, 657-8501, Japan.
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3
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Baltiansky L, Frankel G, Feinerman O. Emergent regulation of ant foraging frequency through a computationally inexpensive forager movement rule. eLife 2023; 12:77659. [PMID: 37067884 PMCID: PMC10110237 DOI: 10.7554/elife.77659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 02/06/2023] [Indexed: 04/18/2023] Open
Abstract
Ant colonies regulate foraging in response to their collective hunger, yet the mechanism behind this distributed regulation remains unclear. Previously, by imaging food flow within ant colonies we showed that the frequency of foraging events declines linearly with colony satiation (Greenwald et al., 2018). Our analysis implied that as a forager distributes food in the nest, two factors affect her decision to exit for another foraging trip: her current food load and its rate of change. Sensing these variables can be attributed to the forager's individual cognitive ability. Here, new analyses of the foragers' trajectories within the nest imply a different way to achieve the observed regulation. Instead of an explicit decision to exit, foragers merely tend toward the depth of the nest when their food load is high and toward the nest exit when it is low. Thus, the colony shapes the forager's trajectory by controlling her unloading rate, while she senses only her current food load. Using an agent-based model and mathematical analysis, we show that this simple mechanism robustly yields emergent regulation of foraging frequency. These findings demonstrate how the embedding of individuals in physical space can reduce their cognitive demands without compromising their computational role in the group.
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Affiliation(s)
- Lior Baltiansky
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
| | - Guy Frankel
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
| | - Ofer Feinerman
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
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4
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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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Gordon DM. Movement, Encounter Rate, and Collective Behavior in Ant Colonies. ANNALS OF THE ENTOMOLOGICAL SOCIETY OF AMERICA 2021; 114:541-546. [PMID: 34512857 PMCID: PMC8423106 DOI: 10.1093/aesa/saaa036] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Indexed: 05/04/2023]
Abstract
Spatial patterns of movement regulate many aspects of social insect behavior, because how workers move around, and how many are there, determines how often they meet and interact. Interactions are usually olfactory; for example, in ants, by means of antennal contact in which one worker assesses the cuticular hydrocarbons of another. Encounter rates may be a simple outcome of local density: a worker experiences more encounters, the more other workers there are around it. This means that encounter rate can be used as a cue for overall density even though no individual can assess global density. Encounter rate as a cue for local density regulates many aspects of social insect behavior, including collective search, task allocation, nest choice, and traffic flow. As colonies grow older and larger, encounter rates change, which leads to changes in task allocation. Nest size affects local density and movement patterns, which influences encounter rate, so that nest size and connectivity influence colony behavior. However, encounter rate is not a simple function of local density when individuals change their movement in response to encounters, thus influencing further encounter rates. Natural selection on the regulation of collective behavior can draw on variation within and among colonies in the relation of movement patterns, encounter rate, and response to encounters.
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Baltiansky L, Sarafian‐Tamam E, Greenwald E, Feinerman O. Dual‐fluorescence imaging and automated trophallaxis detection for studying multi‐nutrient regulation in superorganisms. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Lior Baltiansky
- Department of Physics of Complex Systems Weizmann Institute of Science Rehovot Israel
| | - Einav Sarafian‐Tamam
- Department of Physics of Complex Systems Weizmann Institute of Science Rehovot Israel
| | - Efrat Greenwald
- Department of Physics of Complex Systems Weizmann Institute of Science Rehovot Israel
| | - Ofer Feinerman
- Department of Physics of Complex Systems Weizmann Institute of Science Rehovot Israel
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7
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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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8
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Pacheco PSM, Del-Claro K. Spatio-temporal variation influences the division of labour in Pseudomyrmex concolor Smith (Formicidae: Pseudomyrmecinae). J ETHOL 2021. [DOI: 10.1007/s10164-021-00695-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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9
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Wild B, Dormagen DM, Zachariae A, Smith ML, Traynor KS, Brockmann D, Couzin ID, Landgraf T. Social networks predict the life and death of honey bees. Nat Commun 2021; 12:1110. [PMID: 33597518 PMCID: PMC7889932 DOI: 10.1038/s41467-021-21212-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 01/19/2021] [Indexed: 12/22/2022] Open
Abstract
In complex societies, individuals' roles are reflected by interactions with other conspecifics. Honey bees (Apis mellifera) generally change tasks as they age, but developmental trajectories of individuals can vary drastically due to physiological and environmental factors. We introduce a succinct descriptor of an individual's social network that can be obtained without interfering with the colony. This 'network age' accurately predicts task allocation, survival, activity patterns, and future behavior. We analyze developmental trajectories of multiple cohorts of individuals in a natural setting and identify distinct developmental pathways and critical life changes. Our findings suggest a high stability in task allocation on an individual level. We show that our method is versatile and can extract different properties from social networks, opening up a broad range of future studies. Our approach highlights the relationship of social interactions and individual traits, and provides a scalable technique for understanding how complex social systems function.
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Affiliation(s)
- Benjamin Wild
- Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
| | - David M Dormagen
- Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany
| | | | - Michael L Smith
- Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Kirsten S Traynor
- Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany
- Global Biosocial Complexity Initiative, Arizona State University, Tempe, FL, USA
| | - Dirk Brockmann
- Robert Koch Institute, Berlin, Germany
- Institute for Theoretical Biology, Humboldt University Berlin, Berlin, Germany
| | - Iain D Couzin
- Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Tim Landgraf
- Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
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10
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Wojtusiak J, Bagchi P, Durbha SSKRTN, Mobahi H, Mogharab Nia R, Roess A. COVID-19 Symptom Monitoring and Social Distancing in a University Population. JOURNAL OF HEALTHCARE INFORMATICS RESEARCH 2021; 5:114-131. [PMID: 33437913 PMCID: PMC7790352 DOI: 10.1007/s41666-020-00089-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 11/20/2020] [Accepted: 12/03/2020] [Indexed: 12/14/2022]
Abstract
This paper reports on our efforts to collect daily COVID-19-related symptoms for a large public university population, as well as study relationship between reported symptoms and individual movements. We developed a set of tools to collect and integrate individual-level data. COVID-19-related symptoms are collected using a self-reporting tool initially implemented in Qualtrics survey system and consequently moved to .NET framework. Individual movement data are collected using off-the-shelf tracking apps available for iPhone and Android phones. Data integration and analysis are done in PostgreSQL, Python, and R. As of September 2020, we collected about 184,000 daily symptom responses for 20,000 individuals, as well as over 15,000 days of GPS movement data for 175 individuals. The analysis of the data indicates that headache is the most frequently reported symptom, present almost always when any other symptoms are reported as indicated by derived association rules. It is followed by cough, sore throat, and aches. The study participants traveled on average 223.61 km every week with a large standard deviation of 254.53 and visited on average 5.77 ± 4.75 locations each week for at least 10 min. However, there is no evidence that reported symptoms or prior COVID-19 contact affects movements (p > 0.3 in most models). The evidence suggests that although some individuals limit their movements during pandemics, the overall study population do not change their movements as suggested by guidelines.
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Affiliation(s)
- Janusz Wojtusiak
- Health Informatics Program, Department of Health Administration and Policy, George Mason University, Fairfax, VA USA
| | - Pramita Bagchi
- Department of Statistics, George Mason University, Fairfax, VA USA
| | | | - Hedyeh Mobahi
- Health Informatics Program, Department of Health Administration and Policy, George Mason University, Fairfax, VA USA
| | - Reyhaneh Mogharab Nia
- Health Informatics Program, Department of Health Administration and Policy, George Mason University, Fairfax, VA USA
| | - Amira Roess
- Department of Global and Community Health, George Mason University, Fairfax, VA USA
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11
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Wijeyakulasuriya DA, Eisenhauer EW, Shaby BA, Hanks EM. Machine learning for modeling animal movement. PLoS One 2020; 15:e0235750. [PMID: 32716917 PMCID: PMC7384613 DOI: 10.1371/journal.pone.0235750] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 06/22/2020] [Indexed: 11/20/2022] Open
Abstract
Animal movement drives important ecological processes such as migration and the spread of infectious disease. Current approaches to modeling animal tracking data focus on parametric models used to understand environmental effects on movement behavior and to fill in missing tracking data. Machine Learning and Deep learning algorithms are powerful and flexible predictive modeling tools but have rarely been applied to animal movement data. In this study we present a general framework for predicting animal movement that is a combination of two steps: first predicting movement behavioral states and second predicting the animal's velocity. We specify this framework at the individual level as well as for collective movement. We use Random Forests, Neural and Recurrent Neural Networks to compare performance predicting one step ahead as well as long range simulations. We compare results against a custom constructed Stochastic Differential Equation (SDE) model. We apply this approach to high resolution ant movement data. We found that the individual level Machine Learning and Deep Learning methods outperformed the SDE model for one step ahead prediction. The SDE model did comparatively better at simulating long range movement behaviour. Of the Machine Learning and Deep Learning models the Long Short Term Memory (LSTM) individual level model did best at long range simulations. We also applied the Random Forest and LSTM individual level models to model gull migratory movement to demonstrate the generalizability of this framework. Machine Learning and deep learning models are easier to specify compared to traditional parametric movement models which can have restrictive assumptions. However, machine learning and deep learning models are less interpretable than parametric movement models. The type of model used should be determined by the goal of the study, if the goal is prediction, our study provides evidence that machine learning and deep learning models could be useful tools.
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Affiliation(s)
- Dhanushi A. Wijeyakulasuriya
- Department of Statistics, Pennsylvania State University, University Park, State College, PA, United States of America
| | - Elizabeth W. Eisenhauer
- Department of Statistics, Pennsylvania State University, University Park, State College, PA, United States of America
| | - Benjamin A. Shaby
- Department of Statistics, Colorado State University, Fort Collins, CO, United States of America
| | - Ephraim M. Hanks
- Department of Statistics, Pennsylvania State University, University Park, State College, PA, United States of America
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12
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Pull CD, McMahon DP. Superorganism Immunity: A Major Transition in Immune System Evolution. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.00186] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
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13
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Goes AC, Barcoto MO, Kooij PW, Bueno OC, Rodrigues A. How Do Leaf-Cutting Ants Recognize Antagonistic Microbes in Their Fungal Crops? Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.00095] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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14
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Guo X, Chen J, Azizi A, Fewell J, Kang Y. Dynamics of social interactions, in the flow of information and disease spreading in social insects colonies: Effects of environmental events and spatial heterogeneity. J Theor Biol 2020; 492:110191. [DOI: 10.1016/j.jtbi.2020.110191] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 12/08/2019] [Accepted: 02/05/2020] [Indexed: 11/17/2022]
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15
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A spatiotemporal analysis of the food dissemination process and the trophallactic network in the ant Lasius niger. Sci Rep 2019; 9:15620. [PMID: 31666541 PMCID: PMC6821819 DOI: 10.1038/s41598-019-52019-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 10/12/2019] [Indexed: 01/25/2023] Open
Abstract
Intranidal food dissemination through trophallactic exchanges is a fundamental issue in social insect colonies but its underlying mechanisms are far from being clear. In light of the division of work, network theory and collective food management we develop a framework to investigate the spatiotemporal dynamics of the trophallactic network in starved Lasius niger ant colonies. Thanks to tracking methods we are able to record spatial locations of the trophallactic interactions in the nest. We highlight quantitative differences between the foragers and non-foragers concerning their contributions, their roles (donor/recipient) and their spatial distributions. Moreover, at the intracaste level, we show interindividual differences in all activities and we characterise their nature. In particular, within each caste, all the individuals have the same probability to start their food exchange activity but their probability to exchange differs after their first trophallactic event. Interestingly, despite the highlighted interindividual differences, the trophallactic network does not differ from a random network.
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16
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Malagocka J, Eilenberg J, Jensen AB. Social immunity behaviour among ants infected by specialist and generalist fungi. CURRENT OPINION IN INSECT SCIENCE 2019; 33:99-104. [PMID: 31358203 DOI: 10.1016/j.cois.2019.05.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 04/26/2019] [Accepted: 05/01/2019] [Indexed: 06/10/2023]
Abstract
Social insects are distinguished by their lifestyle of living in groups with division of labour, cooperative brood care, and reproduction limited to a few colony members. Social insects often build large colonies with remarkable densities of highly related individuals and this can lead to an increased pathogen pressure. Our review focuses on interactions of ants with two important taxonomic groups of fungi infecting ants: Hypocreales (Ascomycota) and Entomophthorales (Entomophthoromycotina), and their different infection strategies, including host manipulation for optimal spore dispersal in the specialised ant pathogens. In social insects such as ants, resistance to pathogens is present at the colony level, with social immunity in addition to the individual resistance. We describe how ants use both organizational and behavioural defence strategies to combat fungal pathogens, with emphasis on highly specialised fungi from the genera Ophiocordyceps and Pandora.
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Affiliation(s)
- Joanna Malagocka
- Centre for Social Evolution, Department of Plant and Environmental Science, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark.
| | - Jørgen Eilenberg
- Centre for Social Evolution, Department of Plant and Environmental Science, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark
| | - Annette Bruun Jensen
- Centre for Social Evolution, Department of Plant and Environmental Science, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark
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17
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Ireland T, Garnier S. Architecture, space and information in constructions built by humans and social insects: a conceptual review. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170244. [PMID: 29967305 PMCID: PMC6030583 DOI: 10.1098/rstb.2017.0244] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/29/2018] [Indexed: 01/23/2023] Open
Abstract
The similarities between the structures built by social insects and by humans have led to a convergence of interests between biologists and architects. This new, de facto interdisciplinary community of scholars needs a common terminology and theoretical framework in which to ground its work. In this conceptually oriented review paper, we review the terms 'information', 'space' and 'architecture' to provide definitions that span biology and architecture. A framework is proposed on which interdisciplinary exchange may be better served, with the view that this will aid better cross-fertilization between disciplines, working in the areas of collective behaviour and analysis of the structures and edifices constructed by non-humans; and to facilitate how this area of study may better contribute to the field of architecture. We then use these definitions to discuss the informational content of constructions built by organisms and the influence these have on behaviour, and vice versa. We review how spatial constraints inform and influence interaction between an organism and its environment, and examine the reciprocity of space and information on construction and the behaviour of humans and social insects.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'.
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Affiliation(s)
- Tim Ireland
- Kent School of Architecture, University of Kent, Canterbury, CT2 7NR, UK
| | - Simon Garnier
- Department of Biological Sciences, New Jersey Institute of Technology, Newark, NJ07102, USA
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18
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Varoudis T, Swenson AG, Kirkton SD, Waters JS. Exploring nest structures of acorn dwelling ants with X-ray microtomography and surface-based three-dimensional visibility graph analysis. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170237. [PMID: 29967301 PMCID: PMC6030587 DOI: 10.1098/rstb.2017.0237] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/04/2018] [Indexed: 12/16/2022] Open
Abstract
The physical spaces within which organisms live affect their biology and in many cases can be considered part of their extended phenotype. The nests of social insect societies have a fundamental impact on their ability to function as complex superorganisms. Ants in many species excavate elaborate subterranean nests, but others inhabit relatively small pre-formed cavities within rock crevices and hollow seeds. Temnothorax ants, which often nest within acorns, have become a model system for studying collective decision making. While these ants have demonstrated remarkable degrees of rationality and consistent precision with regard to their nest choices, never before has the fine scale internal architecture and spatial organization of their nests been investigated. We used X-ray microtomography to record high-resolution three-dimensional (3D) scans of Temnothorax colonies within their acorns. These data were then quantified using image segmentation and surface-based 3D visibility graph analysis, a new computational methodology for analysing spatial structures. The visibility graph analysis method integrates knowledge from the field of architecture with the empirical study of animal-built structures, thus providing the first methodological cross-disciplinary synergy of these two research areas. We found a surprisingly high surface area and degree of spatial heterogeneity within the acorn nests. Specific regions, such as those associated with the locations of queens and brood, were significantly more conducive to connectivity than others. From an architect's point of view, spatial analysis research has never focused on all-surface 3D movement, as we describe within ant nests. Therefore, we believe our approach will provide new methods for understanding both human design and the comparative biology of habitat spaces.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'.
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Affiliation(s)
- Tasos Varoudis
- Bartlett School of Architecture, University College London (UCL), 22 Gordon Street, London, WC1H 0QB, UK
| | - Abigail G Swenson
- Department of Biology, Providence College Providence, 1 Cunningham Square, Providence, RI 02918, USA
| | - Scott D Kirkton
- Department of Biological Sciences, Union College, 807 Union St, Schenectady, NY 12308, USA
| | - James S Waters
- Department of Biology, Providence College Providence, 1 Cunningham Square, Providence, RI 02918, USA
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19
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Russell JC, Hanks EM, Haran M, Hughes D. A spatially varying stochastic differential equation model for animal movement. Ann Appl Stat 2018. [DOI: 10.1214/17-aoas1113] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Solá Gracia E, de Bekker C, Hanks EM, Hughes DP. Within the fortress: A specialized parasite is not discriminated against in a social insect society. PLoS One 2018; 13:e0193536. [PMID: 29474472 PMCID: PMC5825133 DOI: 10.1371/journal.pone.0193536] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Accepted: 02/13/2018] [Indexed: 12/03/2022] Open
Abstract
Social insect colonies function cohesively due, in part, to altruistic behaviors performed towards related individuals. These colonies can be affected by parasites in two distinct ways, either at the level of the individual or the entire colony. As such, colonies of social insects can experience conflict with infected individuals reducing the cohesiveness that typifies them. Parasites of social insects therefore offer us a framework to study conflicts within social insect colonies in addition to the traditionally viewed conflicts afforded by groups of low genetic relatedness due to multiple mating for example. In our study, we use the behavior manipulating fungal pathogen, Ophiocordyceps kimflemingiae (= unilateralis) and its host, Camponotus castaneus, to ask if colony members are able to detect infected individuals. Such detection would be optimal for the colony since infected workers die near foraging trails where the fungus develops its external structures and releases spores that infect other colony members. To determine if C. castaneus workers can detect these future threats, we used continuous-time point observations coupled with longer continuous observations to discern any discrimination towards infected individuals. After observing 1,240 hours of video footage we found that infected individuals are not removed from the colony and continuously received food during the course of fungal infection. We also calculated the distances between workers and the nest entrance in a total of 35,691 data points to find infected workers spent more time near the entrance of the nest. Taken together, these results suggest healthy individuals do not detect the parasite inside their nestmates. The colony's inability to detect infected individuals allows O. kimflemingiae to develop within the colony, while receiving food and protection from natural enemies, which could damage or kill its ant host before the parasite has completed its development.
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Affiliation(s)
- Emilia Solá Gracia
- Ecology Program, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Centre for Infectious Disease Dynamics, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Department of Entomology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Department of Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Charissa de Bekker
- Department of Biology, University of Central Florida, Orlando, Florida, United States of America
| | - Ephraim M. Hanks
- Centre for Infectious Disease Dynamics, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - David P. Hughes
- Centre for Infectious Disease Dynamics, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Department of Entomology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Department of Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
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21
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White LA, Forester JD, Craft ME. Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges. J Anim Ecol 2017; 87:559-580. [PMID: 28944450 DOI: 10.1111/1365-2656.12761] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2017] [Accepted: 09/07/2017] [Indexed: 01/26/2023]
Abstract
Individual differences in contact rate can arise from host, group and landscape heterogeneity and can result in different patterns of spatial spread for diseases in wildlife populations with concomitant implications for disease control in wildlife of conservation concern, livestock and humans. While dynamic disease models can provide a better understanding of the drivers of spatial spread, the effects of landscape heterogeneity have only been modelled in a few well-studied wildlife systems such as rabies and bovine tuberculosis. Such spatial models tend to be either purely theoretical with intrinsic limiting assumptions or individual-based models that are often highly species- and system-specific, limiting the breadth of their utility. Our goal was to review studies that have utilized dynamic, spatial models to answer questions about pathogen transmission in wildlife and identify key gaps in the literature. We begin by providing an overview of the main types of dynamic, spatial models (e.g., metapopulation, network, lattice, cellular automata, individual-based and continuous-space) and their relation to each other. We investigate different types of ecological questions that these models have been used to explore: pathogen invasion dynamics and range expansion, spatial heterogeneity and pathogen persistence, the implications of management and intervention strategies and the role of evolution in host-pathogen dynamics. We reviewed 168 studies that consider pathogen transmission in free-ranging wildlife and classify them by the model type employed, the focal host-pathogen system, and their overall research themes and motivation. We observed a significant focus on mammalian hosts, a few well-studied or purely theoretical pathogen systems, and a lack of studies occurring at the wildlife-public health or wildlife-livestock interfaces. Finally, we discuss challenges and future directions in the context of unprecedented human-mediated environmental change. Spatial models may provide new insights into understanding, for example, how global warming and habitat disturbance contribute to disease maintenance and emergence. Moving forward, better integration of dynamic, spatial disease models with approaches from movement ecology, landscape genetics/genomics and ecoimmunology may provide new avenues for investigation and aid in the control of zoonotic and emerging infectious diseases.
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Affiliation(s)
- Lauren A White
- Department of Ecology, Evolution & Behavior, University of Minnesota, St. Paul, MN, USA
| | - James D Forester
- Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, MN, USA
| | - Meggan E Craft
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
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22
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Russell JC, Hanks EM, Modlmeier AP, Hughes DP. Modeling Collective Animal Movement Through Interactions in Behavioral States. JOURNAL OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2017. [DOI: 10.1007/s13253-017-0296-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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23
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Reflected Stochastic Differential Equation Models for Constrained Animal Movement. JOURNAL OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2017. [DOI: 10.1007/s13253-017-0291-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Manlove KR, Cassirer EF, Plowright RK, Cross PC, Hudson PJ. Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep. J Anim Ecol 2017; 86:908-920. [PMID: 28317104 DOI: 10.1111/1365-2656.12664] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 02/08/2017] [Indexed: 11/27/2022]
Abstract
Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife. We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia. We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections. Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs. Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit. This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology.
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Affiliation(s)
- Kezia R Manlove
- Department of Biology, Center for Infectious Disease Dynamics, Pennsylvania State University, 208 Mueller Labs, University Park, PA, 16802, USA
| | - E Frances Cassirer
- Idaho Department of Fish and Game, 3316 16th St., Lewiston, ID, 83501, USA
| | - Raina K Plowright
- Department of Microbiology and Immunology, Montana State University, PO Box 173520, Bozeman, MT, 59717, USA
| | - Paul C Cross
- U.S. Geological Survey, Northern Rocky Mountain Research Center, 2327 University Way Ste. 2, Bozeman, MT, 59715, USA
| | - Peter J Hudson
- Department of Biology, Center for Infectious Disease Dynamics, Pennsylvania State University, 208 Mueller Labs, University Park, PA, 16802, USA
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Colman ER, Charlton N. Separating temporal and topological effects in walk-based network centrality. Phys Rev E 2016; 94:012313. [PMID: 27575154 DOI: 10.1103/physreve.94.012313] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Indexed: 12/26/2022]
Abstract
The recently introduced concept of dynamic communicability is a valuable tool for ranking the importance of nodes in a temporal network. Two metrics, broadcast score and receive score, were introduced to measure the centrality of a node with respect to a model of contagion based on time-respecting walks. This article examines the temporal and structural factors influencing these metrics by considering a versatile stochastic temporal network model. We analytically derive formulas to accurately predict the expectation of the broadcast and receive scores when one or more columns in a temporal edge-list are shuffled. These methods are then applied to two publicly available data sets and we quantify how much the centrality of each individual depends on structural or temporal influences. From our analysis, we highlight two practical contributions: a way to control for temporal variation when computing dynamic communicability and the conclusion that the broadcast and receive scores can, under a range of circumstances, be replaced by the row and column sums of the matrix exponential of a weighted adjacency matrix given by the data.
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Affiliation(s)
- Ewan R Colman
- Department of Biology, Georgetown University, Washington, DC 20057, USA
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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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Disease Dynamics in Ants: A Critical Review of the Ecological Relevance of Using Generalist Fungi to Study Infections in Insect Societies. ADVANCES IN GENETICS 2016; 94:287-306. [PMID: 27131328 DOI: 10.1016/bs.adgen.2015.12.005] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
It is assumed that social life can lead to the rapid spread of infectious diseases and outbreaks. In ants, disease outbreaks are rare and the expression of collective behaviors is invoked to explain the absence of epidemics in natural populations. Here, we address the ecological approach employed by many studies that have notably focused (89% of the studies) on two genera of generalist fungal parasites (Beauveria and Metarhizium). We ask whether these are the most representative models to study the evolutionary ecology of ant-fungal parasite interactions. To assess this, we critically examine the literature on ants and their interactions with fungal parasites from the past 114years (1900-2014). We discuss how current evolutionary ecology approaches emerged from studies focused on the biological control of pest ants. We also analyzed the ecological relevance of the laboratory protocols used in evolutionary ecology studies employing generalist parasites, as well as the rare natural occurrence of these parasites on ants. After a detailed consideration of all the publications, we suggest that using generalist pathogens such as Beauveria and Metarhizium is not an optimal approach if the goal is to study the evolutionary ecology of disease in ants. We conclude by advocating for approaches that incorporate greater realism.
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