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Workers with three different task zones are clustered in their task SFZ as food-processing cluster, brood-care cluster and trash-maintenance cluster.
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The relationship between division of labor and individuals' spatial behavior in social insect colonies provides a useful context to study how social interactions influence the spreading of elements (which could be information, virus or food) across distributed agent systems. In social insect colonies, spatial heterogeneity associated with variation...
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... ( Tschinkel and Han- ley, 2017;Crall et al., 2018;Jandt and Dornhaus, 2009;Baracchi and Cini, 2014;Sendova-Franks and Franks, 1995;Mersch et al., 2013;Baracchi et al., 2007 ). A large subset of (although not all) tasks occur in specific locations within the nest, creating Spatial Fidelity Zones (SFZs) for the workers performing those tasks ( Fig. 1 ). This spatial structure should contribute to the regulation of local contact rates Gordon et al. (1993) , shaping the structure of colony information networks Mersch et al. (2013) , and potentially enhancing communication transmission for tasks ( Sendova- Franks and Franks, 1994;Baracchi and Cini, 2014 ). Worker task assignments and ...
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... group : Based on the laboratory observations on the social insects colonies ( P. californicus ), three major task zones that workers aggregated around are usually formulated in the colony: brood-care cluster, trash-maintenance cluster, and food-processing cluster Fig. 1 . There is P different task group that each worker takes exactly one of them at a time. For each task p ∈ { 1 , 2 , . . . , P } we allocate one central location-called SFZ-in the colony called S p ∈ X . This SFZ for each task is disjoint from other task, that is, S p = S q if p = q . The Fig. 1 shows how workers with different tasks ...
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... cluster, and food-processing cluster Fig. 1 . There is P different task group that each worker takes exactly one of them at a time. For each task p ∈ { 1 , 2 , . . . , P } we allocate one central location-called SFZ-in the colony called S p ∈ X . This SFZ for each task is disjoint from other task, that is, S p = S q if p = q . The Fig. 1 shows how workers with different tasks are clustered in locations related to their task, ...
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Citations
... Additionally, the foraging patterns observed in ant colonies show notable similarities to other biological processes, such as the aggregation of immune cells and the propagation of chemical signals (Sumpter 2010). These interdisciplinary parallels provide deeper insights into the principles of self-organization and adaptation in complex systems (Bonabeau et al. 1999;Chen et al. 2024;Dorigo et al. 1996;Guo et al. 2020;Kang et al. 2015;Kang and Theraulaz 2016;Navas-Zuloaga et al. 2023;Pratt 2009;Wang et al. 2024). ...
Understanding the collective foraging strategies of ant colonies is essential for studying
self-organization and collective behavior in biological systems. This study introduces
a simplified foraging model that classifies worker roles into two functional groups-
available workers and active foragers-providing a concise yet effective framework for
analyzing foraging dynamics. Our model effectively reproduces the foraging dynamics
observed in more complex three-dimensional models, while taking a more tractable
form that is more conducive to mathematical analysis. We examine the effects of
stochasticity in mortality rates of foragers and workers on foraging state transitions,
with a particular emphasis on the critical noise threshold, transition probability, and
transition time. While the critical noise threshold is reduced by stochasticity in either
of the two mortality rates, that of active foragers has the greatest effect. We find that
slight increases in the arrival rate of available workers and the recruitment rate of active
foragers enhance the colony’s resilience to environmental stochasticity, suggesting that
colonies can self-regulate via a feedback loop of foraging and recruitment to maintain
their foraging while their environment changes around them. In contrast, varying the
mortality rate of available workers had little effect on this resilience, analogously
to experimental observations that older or unhealthy worker ants disproportionately
transition into foraging roles. This study not only advances our understanding of ant
foraging dynamics by simplifying complex models but also provides valuable insights
into the robustness of foraging activities under varying environmental conditions.
... The potential flow of spreading elements, such as viruses, in the communication networks of social insects, has some general similarities with that in human populations. Although they have different spreading dynamics, some features that are typical of human systems (e.g., bursty interaction patterns with heavy-tailed delay distributions in models) were observed in the ants Temnothorax rugatulusants and the honeybee Apis mellifera (Blonder and Dornhaus 2011;Gernat et al. 2018;Guo et al. 2020). ...
Viruses of soil-dwelling invertebrates remain poorly studied. Viruses of eusocial insects are of special interest as they can serve as a model for studying the spread of viruses via social interactions. In this review, we aim to compile and actualize the available information on the diversity of viruses associated with soil-dwelling social insects, termites and ants. Both groups are among the most functionally important soil invertebrates and include numerous pests and invasive species. We analyzed 93 articles dedicated to viral findings in these groups. Viruses were found in 54 species of ants and 28 species of termites. In sum, 270 viruses and viral genetic variants from over 16 viral orders were found to date in soil-dwelling social insects. Complete information on viruses detected in termites and ants, including insect species, viral name, species, replication status, and GenBank accession number is provided. For most of the novel viruses, replication in the insect was not yet confirmed. We encourage more studies of the virome of ants and termites, which should pay more attention to viral replication and infection symptoms.
... For example, reproductive individuals tend to be confined to the colony and are exempt from potentially costly activities such as foraging, defense, and activities associated with colony hygiene such as the disposal of corpses (Sah et al., 2018;Stroeymeyt et al., 2018;Sun & Zhou, 2013). Typically, sterile castes responsible for such tasks have limited or no contact with the queen (and king in termites) and the larval brood (Guo et al., 2020;Stroeymeyt et al., 2018), even to the point of pathogen-infected individuals self-isolating from the colony (Geffre et al., 2020;Heinze & Walter, 2010). However, some pathogen-infected nonreproductive termites do not self-isolate and may still move in and out of all parts of the colony, where they can potentially benefit from being groomed by other nestmates (Moran et al., 2022). ...
Social insects are prone to pathogen infection because of high exposure rates from social interactions. However, it remains unclear whether queens have enhanced pathogen resistance, because reproduction is largely confined to queens. Here, we used a natural host–pathogen system, the subterranean termite Reticulitermes chinensis and the entomopathogenic fungus Metarhizium anisopliae, to investigate the differences in allogrooming, locomotion, and immune gene expression between queens and workers against pathogen infection. We found that fungal infection significantly reduced survival in both queens and workers. Infected queens received significantly more grooming time from sanitary nestmates than infected workers, but they returned much less grooming time to sanitary nestmates than infected workers. Infection resulted in a reduction in the average locomotion speed and distance of queens but had no effect on worker locomotion. Infection resulted in upregulated expression of two immune genes (termicin and transferrin), two antioxidant genes (CAT and SOD), and phosphate genes CYP450 in queens but not in workers. Our results indicated that eusocial termites evolved strategies that prioritize the reproductive castes' welfare in defending against the pathogen infection to ensure continued reproduction and colony persistence.
... 97 Pathogens are introduced to the colony by foragers, but they rarely interact within the nest, thus limiting the spread of disease. [98][99][100] Pathogens are analogous to individual faults or errors. ...
Increasing the resilience of modern infrastructure systems is recognized as a priority by both the International Council on Systems Engineering and the National Academy of Engineering. Resilience answers the key stakeholder need for a stable and predictable system by withstanding, adapting to, and recovering from unexpected faults. Increasing resilience in multi‐agent systems is especially challenging because resilience is an emergent system‐level property rather than the sum of individual agent functions. This paper uses biological systems as a source of inspiration for resilient functions, examining the central question How can biologically inspired design be used to increase the emergent property of resilience in multi‐agent systems? The paper uses functional decomposition to break down the individual functions that result in resilience and transfer the properties to generalized systems. Accordingly, the central hypothesis examined in this article is If functional decomposition is performed on eusocial insect colonies, then generalizable approaches to increase the emergent property of multi‐agent system resilience can be identified . The results provide two contributions. The first contribution is the identification of six general functions based on eusocial insect behavior that influence resilience. The second contribution is a description of the process of identifying and transferring insect behaviors into generalized design‐for‐resilience guidance. To support these contributions, a case study applies biologically inspired functions to an emergency power service system and proposes tactics for the power system to improve its resilience. Thus, this article provides a key step towards our goal of using biologically inspired design to influence the emergent property of resilience in multi‐agent systems.
... In recent modeling work (Guo et al. 2020), we investigated the information transmission through physical contact in several realistic scenarios involving three task groups of ants. We assumed that the performance of each task group is tied to predefined spatial fidelities, which reflect the proportion of ants that prefer to drift back to the task location compared to those that move randomly. ...
... Our model extends the agent-based discrete-time Markov chain model developed in Guo et al. (2020) by including various task groups and task-switching procedures. Unlike conducting experiments in such contexts that can be very challenging, our model is an easy while effective tool that can shed some light on dynamics in real social insect colonies. ...
... The walking style of the worker is represented by w A ∈ {Random (R), Drifted (D)}. Based on previous work and literature (Charbonneau and Dornhaus 2015a;Mersch et al. 2013;Guo et al. 2020), we set two walking styles for Worker A: Some workers do not wander inside during each task; they randomly select one of the neighboring cells and moves toward that Charbonneau and Dornhaus (2015a). We set the walking style of such an ant to be w A = R. ...
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.
... The main purpose of this paper is to show that heterogeneous number of contacts may induce complex initial growth behavior for the infected nodes in each degree class, which are different from the scalar SIR model. Although considerable physical, biological and mathematical research papers have been published to investigated the effect of contact heterogeneity on disease dynamics [38][39][40] , most existing research work mainly focus on threshold conditions, and cannot adequately describe some transient and asymptotic behaviors especially when an epidemic begin invading. To the best of our knowledge, there appears rather few analytical results on this topic. ...
... This social organization allows the reproductive caste to be protected from external threats, as some tasks, such as foraging, defense or corpse disposal, increase the risk of pathogen exposure (Durrer and Schmid-Hempel, 1994;Sun and Zhou, 2013;Stroeymeyt et al., 2014;Sah et al., 2018). Typically, colony members responsible for these risky tasks have reduced contact with high-value members of the colony (i.e., reproductives and brood), thus decreasing the chance that these valuable individuals will become infected (Wang and Mofller, 1970;Naug and Camazine, 2002;Naug and Smith, 2007;Stroeymeyt et al., 2018;Guo et al., 2020). Even within the worker caste, particularly dangerous tasks are handled by more expendable individuals. ...
Social insect colonies are characterized by an efficient division of labor, allowing high-value individuals (i.e., reproductives and brood) to be sheltered from tasks associated with increased risk of pathogen exposure, such as foraging or corpse disposal. This social organization helps limit the transmission of disease throughout the colony. Further, individuals can actively respond to imminent disease threats by altering their behaviors as a means of social immunity. In subterranean termites, although workers typically avoid detected pathogens, they can be attracted to pathogen cues when a nestmate is infected. Infected termites are usually groomed, but they may instead be cannibalized if the infection has already become lethal. The mechanisms governing these changes in behavior are unclear. We set out to examine immediate changes in individual behaviors, investigating the role that the infected individual plays in communicating its infection status to nestmates. We also assessed gradual changes in social organization after the re-introduction of an infected termite to the colony. Our results reveal that infected termites likely do not signal their infection status to nestmates through shaking behaviors and reduced movements, suggesting the occurrence of other mechanisms used in communicating infection. We also found that infected termites do not self-isolate and may travel to the densest part of the colony, where they can potentially benefit from grooming by large groups of nestmates. These results provide new insights into how individual changes in immune behaviors contribute to overall colony health, highlighting that, at early stages of infection, termites favor a rescuing strategy rather than isolation and/or cannibalization.
... Infection transmission through the social contact network has become one of the most important health issues in the modern world [26], and there are clear similarities between the features of communication in humans and in social insects, though they differ in dynamics. Social insects, including termites, can be considered as a model for understanding the spread of infection via social interactions [27]. Moreover, soil invertebrates can contribute to the We also found five contigs with homology to the polymerase of the various members of Mononegavirales in the O. wallonensis pool. ...
... Infection transmission through the social contact network has become one of the most important health issues in the modern world [26], and there are clear similarities between the features of communication in humans and in social insects, though they differ in dynamics. Social insects, including termites, can be considered as a model for understanding the spread of infection via social interactions [27]. Moreover, soil invertebrates can contribute to the preservation and distribution of viruses [28]. ...
Modern metagenomic approaches enable the effective discovery of novel viruses in previously unexplored organisms. Termites are significant ecosystem converters and influencers. As with the majority of tropical forest insects, termites are studied insufficiently, and termite virome remains especially understudied. Here, we studied the virome of lichenophagous and mycophagous termites (Hospitalitermes bicolor, Macrotermes carbonarius and Odontotermes wallonensis) collected in the Cat Tien National Park (Vietnam). We assembled four full genomes of novel viruses related to Solemoviridae, Lispiviridae, Polycipiviridae and Kolmioviridae. We also found several contigs with relation to Chuviridae and Deltaflexiviridae that did not correspond to complete virus genomes. All the novel viruses clustered phylogenetically with previously identified viruses of the termites. Deltaflexi-like contigs were identified in the fungi-cultivating M. carbonarius and showed homology with viruses recently discovered in the edible basidiomycete mushrooms.
... These tracking methodologies do not, by themselves, provide a reliable assessment of individual behavioural state during social interactions, nor do they assess the reliability of information exchange during encounters between individuals. Researchers have also developed more sophisticated statistical and mathematical modelling tools to develop theory about how social insects spread information across their communication networks [18,19]. Nevertheless, a gap between empirical and theoretical studies on information movement across the network constrains understanding of how a social-insect colony is organized as a complex adaptive system. ...
Alarm signal propagation through ant colonies provides an empirically tractable context for analysing information flow through a natural system, with useful insights for network dynamics in other social animals. Here, we develop a methodological approach to track alarm spread within a group of harvester ants, Pogonomyrmex californicus. We initially alarmed three ants and tracked subsequent signal transmission through the colony. Because there was no actual standing threat, the false alarm allowed us to assess amplification and adaptive damping of the collective alarm response. We trained a random forest regression model to quantify alarm behaviour of individual workers from multiple movement features. Our approach translates subjective categorical alarm scores into a reliable, continuous variable. We combined these assessments with automatically tracked proximity data to construct an alarm propagation network. This method enables analyses of spatio-temporal patterns in alarm signal propagation in a group of ants and provides an opportunity to integrate individual and collective alarm response. Using this system, alarm propagation can be manipulated and assessed to ask and answer a wide range of questions related to information and misinformation flow in social networks.
... Besides, another method of calculating R 0 in one-dimensional space was also presented in [9]. In a recent work [14], the authors studied the dual-functionality of physical contacts driven via variations of individual spatial behavior and provided insights on mechanisms that generate spatial heterogeneity. By using an epidemic model with nonlocal delay and logistic growth, the authors in [15] studied the dynamics of model and investigated how nonlocal delay and logistic growth affect the disease transmission. ...
... We arrange the rest of this paper as follows. Section 2 is devoted to the well-posedness of system (14). We follow the standard procedures in [25] to define R 0 for (14) by the next generation operator approach in Section 3. ...
... 4 Complexity ∀x ∈ Ω, ϕ � (ϕ 1 , ϕ 2 , ϕ 3 ) T ∈ C + . It allows us to rewrite (14) as ...
In this paper, we aim to establish the threshold-type dynamics of a diffusive herpes model that assumes a fixed relapse period and nonlinear recovery rate. It turns out that when considering diseases with a fixed relapse period, the diffusion of recovered individuals will lead to nonlocal recovery term. We characterize the basic reproduction number, ℜ0, for the model through the next generation operator approach. Moreover, in a homogeneous case, we calculate the ℜ0 explicitly. By utilizing the principal eigenvalue of the associated eigenvalue problem or equivalently by ℜ0, we establish the threshold-type dynamics of the model in the sense that the herpes is either extinct or close to the epidemic value. Numerical simulations are performed to verify the theoretical results and the effects of the spatial heterogeneity on disease transmission.
