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Resilience in ant societies

Periodic Reporting for period 3 - resiliANT (Resilience in ant societies)

Reporting period: 2020-09-01 to 2022-02-28

The aim of this project is to study the mechanisms regulating social organisation in ants. Ants are an ideal system to identify behavioural responses allowing homeostatic processes conferring resilience against external perturbations. The overall aim of this proposal is to identify the collective mechanisms responsible for resilience to both abiotic and biotic perturbations. Abiotic perturbations such as flooding or famine can eliminate entire sectors of the workforce (e.g. nurses or foragers). We are performing controlled knockout experiments, designed to induce compensatory changes in the behaviour of the survivors. This will allow us to test whether ants can deviate from their baseline behavioural trajectory to buffer the effect of external perturbations. We also study how ants react to epidemics. The rapid, unchecked infection 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 are investigating whether the colony-level interaction network that emerges from the individual-level behaviours, constitutes a preventative barrier against disease spread. We are also performing controlled inoculations with a generalist fungal pathogen to identify potential 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.
There were four aims to this project:
For Aim 1a, we successfully constructed a model that describes and predicts the ontogeny of two important components of individual behaviour, namely the topological position of each ant within the colony-wide social interaction network, and the types of labour that each individual performs. We have been able to show 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 submitted to Current Biology.

For Aim 1b, we conducted targeted manipulations as suggested in the proposal. 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. We also proposed to manipulate colony size with the aim to investigate the role of group size on resilience. We had planned to do these experiments this year. Unfortunately, we will have to postpone these experiments given that there is a shutdown of our University because of the covid-19. Similarly, we were planning to conduct experiments with several other species to investigate how social structure varies phylogenetically. Unfortunately, these experiments will need to be delayed because of the covid-19.

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 (Stroeymeyt et al. 2018 Science). However, if time permits we will try to develop them because it would allow us to conduct some new experiments to track in real time the spread of spores.

For aim 2b, we also completed several of the objectives. We have quantified the impact of the entomopathogenic fungus Metarhizium brunneum on ant colonies over the course of infection nd compared the network properties of colonies before and after exposure to the pathogen and show 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 a high-impact journal article: Stroeymeyt et al. 2018 Science. We also have done good progress in the development of the robotic ant. We have improved the trajectory-control algorithms. We have achieved both the software and hardware integration of the robotic ant into the tracking system setup. We are currently investigating other stimulation techniques, as well as transport mechanisms.
Guiding a robotic dummy in an ant colony has revealed to be a state of the art problem in robotic navigation and path planning. Moving comparably slow in a dynamic environment for safety, causes oscillatory motion without significant progress 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. We have made significant progress towards establishing a closed loop manipulation experiment that completely eliminates the human bias.

Because task preference has been shown to be associated with fat content we have developed a technique using Nuclear Magnetic Resonance (NMR) to measure the lipid content of individual ants without harming them. This provides the unique opportunity to acquire multiple repeat physiological measurements for every individual ant within a colony. We will utilize this technique in tandem with automated behavioural tracking for a period of four months to investigate whether fat-content is an important predictor of DoL. Unfortunately, this part of the project has been temporarily postponed with the outbreak of covid-19.
Tagged queens and workers of the ant Lasius nigher