Periodic Reporting for period 4 - resiliANT (Resilience in ant societies)
Periodo di rendicontazione: 2022-03-01 al 2023-08-31
The ERC project resiliANT focused on the mechanisms regulating social organisation in ants. Ants are an ideal system to identify behavioural responses that confer resilience of complex societies against external perturbations. Abiotic perturbations such as flooding or famine can eliminate entire sectors of the workforce of a society. The overall aim of the project was to identify the collective mechanisms responsible for resilience to both abiotic and biotic perturbations. We performed controlled knockout experiments, designed to induce compensatory changes in the behaviour of the survivors. This has allowed us to show how ants deviate from their baseline behavioural trajectory to buffer the effect of external perturbations. We also investigated how ants react to epidemics. The rapid, unchecked transmission of infections between densely connected conspecifics has the potential to decimate a colony. Because the kinetics of disease transmission in social groups depends upon the structure and dynamics of the interaction network, we revealed how the colony-level interaction network emerging from the individual-level behaviours constitutes a barrier against disease spread. Controlled inoculations with a generalist fungal pathogen further revealed specific pathogen-induced behavioural responses that further hinder pathogen transmission. These studies are clearly highly relevant at a time where human societies are challenged by covid-19. In combination, our research revealed how different behavioral mechanisms expressed by individual members of societies confer resilience to complex societies as a whole when these societies are challenged with abiotic and biotic stressors.
For Aim 1a, we successfully constructed a model that describes and predicts the ontogeny of two important components of individual behaviour, the topological position of each ant within the colony-wide social interaction network, and the types of labour that each individual performs. We have shown that most workers occupied one of two steady-states, namely a low-maturity nurse state and a high-maturity forager state. The remaining workers had intermediate social maturity values and were rapidly transitioning between these states. A paper reporting these data has been published in Current Biology (Richardson et al 2021).
For Aim 1b, we conducted different targeted manipulations, including the removal of workers performing specific tasks (eg. brood transport). Surprisingly, tracking of colonies revealed that workers pursued their normal task specialization independently of treatment, suggesting that the task specialization is rigidly preprogramed rather than flexibly adjusting in response to perturbations. A manuscript reporting these results is currently under preparation. We also conducted behavioural experiments testing whether it was possible to integrate a non-mimetic dummy into ant colonies and the potential of such a dummy to act as a controlled and standardized stimulus. To this end we developed a custom-made robotic platform with a magnetically tethered dummy that was integrated into our automated tracking system. We then used this platform to investigate how local density and the task being performed at a particular time influence worker responses to tactile stimulation. Our results suggest that worker behaviour is density-dependent and that worker responsiveness to stimuli is context-dependent and mediated by the task performed. A manuscript describing the robotic system and the abovementioned results is under evaluation at the journal Methods in Ecology and Evolution. We also investigated the role of group size on resilience by removing individuals based on their social network positions using the social maturity metric from Richardson et al. (2021). We performed three sets of experiments: removal of high social maturity individuals, removal of low social maturity individuals and removal of random set of individuals and quantified the changes in the social network properties of the remaining individuals as well as their task performance. A manuscript reporting on the results of these experiments is currently under preparation.
For Aim 2a, we successively achieved all the objectives listed in the proposal. We described the properties of the social interaction network in undisturbed colonies and developed a temporal, epidemiological susceptible-Infected model to predict the transmissivity of observed and randomized ant networks. We were able to show that the basal ant networks confer inherent protection against disease transmission. These findings have been published in a high-impact journal article: Stroeymeyt et al. 2018 Science. We initially proposed to develop fluorescent microbeads. However, instead of tracking microbeads, whose transmission properties may differ strongly from that of entomopathogenic fungi, we decided to focus on tracking real pathogens which we quantified at the end of the experiments by quantitative PCR. This fulfilled the same objective as the real-time tracking of fluorescent microbeads.
For Aim 2b, we also completed all the objectives. We have quantified the impact of the entomopathogenic fungus Metarhizium brunneum on ant colonies over the course of infection and compared the network properties of colonies before and after exposure to the pathogen. We showed that experimentally exposed colonies modify the properties of their networks to further reduce disease transmission (induced organizational immunity). All these findings have been published together in Stroeymeyt et al. 2018. As described above, we have also made good progress in the development of the robotic ant but prioritized its use under aim 1b as the application of external stimuli was easier to integrate in the task performance focus than the epidemiological context. We further conducted a study on the individual and collective consequences of non-fatal injuries. The behaviours and social environment of injured ants were monitored using the automated tracking system and compared to that of control ants. The results focussing on changes in behaviour and network properties associated with an injured ant in the colony are currently being written up for publication.
For Aim 1b, we conducted different targeted manipulations, including the removal of workers performing specific tasks (eg. brood transport). Surprisingly, tracking of colonies revealed that workers pursued their normal task specialization independently of treatment, suggesting that the task specialization is rigidly preprogramed rather than flexibly adjusting in response to perturbations. A manuscript reporting these results is currently under preparation. We also conducted behavioural experiments testing whether it was possible to integrate a non-mimetic dummy into ant colonies and the potential of such a dummy to act as a controlled and standardized stimulus. To this end we developed a custom-made robotic platform with a magnetically tethered dummy that was integrated into our automated tracking system. We then used this platform to investigate how local density and the task being performed at a particular time influence worker responses to tactile stimulation. Our results suggest that worker behaviour is density-dependent and that worker responsiveness to stimuli is context-dependent and mediated by the task performed. A manuscript describing the robotic system and the abovementioned results is under evaluation at the journal Methods in Ecology and Evolution. We also investigated the role of group size on resilience by removing individuals based on their social network positions using the social maturity metric from Richardson et al. (2021). We performed three sets of experiments: removal of high social maturity individuals, removal of low social maturity individuals and removal of random set of individuals and quantified the changes in the social network properties of the remaining individuals as well as their task performance. A manuscript reporting on the results of these experiments is currently under preparation.
For Aim 2a, we successively achieved all the objectives listed in the proposal. We described the properties of the social interaction network in undisturbed colonies and developed a temporal, epidemiological susceptible-Infected model to predict the transmissivity of observed and randomized ant networks. We were able to show that the basal ant networks confer inherent protection against disease transmission. These findings have been published in a high-impact journal article: Stroeymeyt et al. 2018 Science. We initially proposed to develop fluorescent microbeads. However, instead of tracking microbeads, whose transmission properties may differ strongly from that of entomopathogenic fungi, we decided to focus on tracking real pathogens which we quantified at the end of the experiments by quantitative PCR. This fulfilled the same objective as the real-time tracking of fluorescent microbeads.
For Aim 2b, we also completed all the objectives. We have quantified the impact of the entomopathogenic fungus Metarhizium brunneum on ant colonies over the course of infection and compared the network properties of colonies before and after exposure to the pathogen. We showed that experimentally exposed colonies modify the properties of their networks to further reduce disease transmission (induced organizational immunity). All these findings have been published together in Stroeymeyt et al. 2018. As described above, we have also made good progress in the development of the robotic ant but prioritized its use under aim 1b as the application of external stimuli was easier to integrate in the task performance focus than the epidemiological context. We further conducted a study on the individual and collective consequences of non-fatal injuries. The behaviours and social environment of injured ants were monitored using the automated tracking system and compared to that of control ants. The results focussing on changes in behaviour and network properties associated with an injured ant in the colony are currently being written up for publication.
Guiding a robotic dummy in an ant colony turned out to be a state-of-the-art problem in robotic navigation and path planning. Slow movement of the robot in a dynamic environment (a safety requirement) causes oscillatory motions which have thus far not been solved satisfyingly with state-of-the-art algorithms. We therefore designed a new technique for temporally persistent motion planning and are preparing a publication with an abstract formulation of the problem and the algorithm to generalize the concept for the robotics community.
Because task preference of ant workers has been shown to be associated with fat content, we have developed a technique using Nuclear Magnetic Resonance to measure the lipid content of individual ants without harming them. This provided the unique opportunity to acquire multiple repeat physiological measurements for every ant within a colony. We then used this development, in combination with starvation of targeted workers, to establish a causal relationship between fat content and division of labour. A manuscript reporting the technique and the results of the described experiments is currently under preparation.
Because task preference of ant workers has been shown to be associated with fat content, we have developed a technique using Nuclear Magnetic Resonance to measure the lipid content of individual ants without harming them. This provided the unique opportunity to acquire multiple repeat physiological measurements for every ant within a colony. We then used this development, in combination with starvation of targeted workers, to establish a causal relationship between fat content and division of labour. A manuscript reporting the technique and the results of the described experiments is currently under preparation.