Division of Labour in Ants

As part of my post-doc I have been working on several projects related to understanding Division of Labour in ants. All of them involve using the fantastic FORT tracking system at the Department of Ecology and Evolution, University of Lausanne. The system allows me to combine high resolution tracking data of individual ants with behavioural observations to explore how individual and social factors interact to regulate the division of labour in ant colonies.

Check out details of the individual projects through the tabs below.

Camponotus fellah working cleaning wound of another worker

Wound Caregivers Brood Effects Response Parameters

Wound Care in Ants

One of the most fascinating behaviours recently discovered in ants is the wound care behaviour in which injured ants are cared for by their nestmates, and this behaviour has been shown to increase the survival of injured ants. While the behaviour has been described in several species of ants, the factors that regulate an individual’s decision to provide wound care are still unknown. Using the FORT system, we looked at how individual and social factors interact to regulate the wound care behaviour in Camponotus fellah. We combined detailed behavioural observations with high resolution spatial data to show that caregivers are ants transitioning between the nurse and forager roles in the colony. Intriguingly, their decision to provide care is dependent on their social and spatial affinity with the injured ants before the injury occurs.

The manuscript detailing these findings is currently available as a preprint on bioRxiv.

Collaborators: Alba Motes-Rodrigo, Laurent Keller and Erik Frank

Effects of Brood on Ant Colonies

In this project we looked at how the amount of brood affects the behaviour and social network structure of workers in an ant colony. We performed experiments with Camponotus floridanus and compared colonies with different amounts of brood.

We are still working on analysing the data that we collected so check back later for updates.

Collaborators: Juan José Lagos Oviedo, Tomas Kay and Laurent Keller

Hierarchical Response Parameters

Classical models of division of labour in social insects assume that workers differ in their response thresholds to task-related stimuli and that these differences in response thresholds are sufficient to generate division of labour in the colony. Recent empirical work shows response thresholds alone are not sufficient to explain the observed patterns of division of labour in social insect colonies and that other response parameters, like response probability and response intensity, also play an important role. I have been developing a framework that formalises these three response parameters and their hierarchical relationship and have been using this to explore how these parameters interact to regulate the division of labour in social insect colonies.

I have submitted a manuscript describing this framework and am now working on simulations to explore how these parameters can interact to generate different patterns of division of labour.

Computational Ethology

During my post-doc I have also become interested in developing computational tools to quantify animal behaviour in an automated manner. This involves using recent advances in deep learning and applying these newer techniques to different data modalities (e.g. video, accelerometer) to extract behavioural information from them. I have also become interested in using more advanced tools in the analysis of social networks, like multi-layer networks and Stochastic Block models.

Check out details of the individual projects implementing some of these tools through the tabs below.

Vervet adult with an accelerometer collar

Accelerometer Inference Fly Courtship Primate Social Ontogeny

Behavioural Inference from Accelerometer Data

Biologging is rapidly growing as a viable technology for studying animal behaviour in the wild, but the analysis of the data collected from these devices is still a bottleneck in many studies. Most biological studies rely on using standard machine learning mdoels, like random Forests, to infer behaviour from accelerometer data, but these models are not designed to take into account the temporal structure of the data and thus require a lot of manual feature engineering. In this project, we are using deep learning models to infer behaviour from accelerometer data in a more automated manner and are comparing the performance of these models to standard machine learning models. We are particulary focused on using foundational tabular models (TabPFN) as well as state of the art time series models (ROCKETs) and are looking at how key decisions during the pre-processing of these large datasets influence model performance on a per-behaviour basis.

The manuscript detailing these findings is currently currently available as a preprint on bioRxiv.

Collaborators: Loïc Brun and Erica van de Waal

Quantifying Male Courtship in Drosophila

In this project we are looking at how male courtship in Drosophila melanogaster changes with infection status. We are using SLEAP for pose estimation of several individual flies from video data, followed by manually extracting features from the pose and then training a hierarchical deep learning tabular classifier to quantify behaviour from these videos.

We have developed an end to end pipeline that quantifies male courtship with high accuracy and are now analysing the data that we collected. Check back later for updates.

Collaborators: Aijuan Liao and Tadeusz Kawecki

Ontogeny of Sociality in Primates

Vervet monkeys are strongly matrilineal and the social relationships that individuals form early in life have a strong influence on their fitness as adults, but we still don't know how these relationships form in the first place. In this project we used multi-layer analysis to compare the ontogeny of social relationships across different behavioural contexts (e.g. grooming, proximity) in a population of wild vervet monkeys in South Africa. We find that as juveniles age, the overlap between their social interactions and proximity networks increases, whereas both networks decrease in similarity to their kinship networks. This change is driven by increasing independence of juveniles from their mothers.

The manuscript detailing these findings is currently available as a preprint on bioRxiv.

Collaborators: Mawa Defraville, Charlotte Canteloup and Erica van de Waal

Inclusivity in Scientific platforms

I am part of several initiatives to make scientific platforms, particularly conferences, more inclusive and accessible.

I helped organise the second edition of the Animal Behavior Society/ Association for the Study of Animal Behaviour Twitter conference in 2023. We detailed our findings on how the conference was received and reflected on how online conferences can be organised moving forward in a manuscript published in Animal Behaviour.

For the past few years, I have also been involved in the Animal Behaviour Live platform. Our flagship event is the annual online conference which is now in it's sixth edition. As part of the conference we have collected valuable demographic data on participants and presenters over the years and are currently preparing a manuscript detailing findings on how to run a low cost virtual conference based on this data.

Waggle dance behaviour in Asian honey bees

While in Bangalore, I have had the opportunity to work with three of the honey bee species found in this corner of the world: Apis florea, A. cerana and A. dorsata. Compared to the western honey bee, A. mellifera, very little is known about the behaviour and ecology of the Asian honey bee species. In line with my broader interest in social communication and interactions, I have been a part of projects focused on the waggle dance communication in these species.

Check out details of the individual projects through the tabs below.

Dance Dialects Dance Follower Behaviour Optic Flow and Dance Behaviour Night Dances in A. dorsata

Dance Dialects

In a project spearheaded by Patrick Kohl from the University of Würzburg, we looked at whether honey bee populations show dance dialects (differences in the slope between the waggle dance duration and distance of the food source indicated). We found that the species show differences in the slope which are inversely correlated with their foraging range (with A. cerana having the steepest slope and the shortest foraging range, and A. dorsata the shallowest slope and the largest foraging range in Bangalore). Thus, dance dialects represent an adaptive evolution to the environmental food availability in honey bees.

The manuscript detailing these findings is published in the journal Proceedings of the Royal Society B.

Collaborators: Patrick Kohl, Neethu Thulasi, Benjamin Rutschmann, Ingolf-Steffan Dewenter and Axel Brockmann

Dance Follower Behaviour

Signals produced by the foragers in the waggle dance vary amongst the extant honey bee species (A. florea produces a visual but not an acoustic signal, A. cerana does the reverse while A. dorsata produces both). However, nothing is known about how the receivers of these signals, the dance followers, respond to these differences. We found that the dance follower behaviour is conserved across all three species throughout the waggle dance and is similar to follower behaviour in A. mellifera. This indicates that the mechanism by which spatial information is transmitted in the waggle dance is likely to be conserved across the genus Apis.

The manuscript detailing these findings is published in the journal Animal Behaviour.

Collaborators: Smruti Pimplikar, Neethu Thulasi and Axel Brockmann

Optic Flow and Waggle Dance

The effect of optic flow on the waggle dance behaviour has been previously explored in A. mellifera, using foragers trained in an artificial tunnel. My collaborators and I looked at the effect of natural variation in the optic flow of foraging environments on the waggle dance activity of A. florea and A. cerana. We found that, similar to A. mellifera, higher optic flow conditions led to a more rapid increase in the waggle phase duration with distance, but only in A. florea and not A. cerana.

The manuscript detailing these findings is published in the Journal of Experimental Biology.

We also published a second manuscript in which we looked at the dance calibration curves in various A. cerana lineages and performed a common garden experiment in which we transported colonies from the Himalayas to Bangalore to look at the effect of the change in environment on the dance calibration curve. The results of these experiments also published in the Journal of Experimental Biology.

Collaborators: Neethu Thulasi, Patrick Kohl, Sachin Suresh, Benjamin Rutschmann and Axel Brockmann

Night Dances in A. dorsata

A. dorsata is unique in that it not only engages in nocturnal foraging, but also performs waggle dances at night, providing insights into how they navigate and communicate under low-light conditions. While several studies have looked at nocturnal dances in A. dorsata, they have all focused on colony level behavioural responses. My collaborators and I looked at how individual foragers adjust their dances during the night in the absence of the visual cues that are available during the day. Most foragers already adjust their dance to the expected sun's position at sunrise and we identified different strategies individual foragers use to perform this update.

The manuscript detailing these findings is currently under preparation.

Collaborators: Bharath Kumar A. K. and Axel Brockmann

Individual variation in recruitment activity

During my PhD, I was primarily interested in the interplay between individual and social factors in regulating an individual honey bee forager’s decision to recruit to a food source using the waggle dance. Through some excellent collaborations, we found that the total recruitment activity of an individual is a combination of two behavioural parameters, dance probability and dance intensity, which are in turn affected differently by individual and social factors.

Check out details of the individual projects through the tabs below.

Social Modulation Mechanisms Agent-based Simulations

Social Modulation of Individual Differences

In this project, we were interested in looking at how recruitment activity to the same food source varies within a group of foragers. We found that foragers showed strong differences, consistent over days, in their probability of dancing and intensity of dances for the same food source. When we removed some foragers from the group, only the more active individuals changed their total recruitment activity and did so by increasing their probability of dancing and not the intensity. Since the removal of foragers potentially changes social interactions in the hive, the probability of dancing is associated more with the ‘social’ perception of the food reward, as compared to the dance intensity.

The manuscript detailing these findings is published in the journal Behavioral Ecology and Sociobiology.

This project was done under the guidance of Axel Brockmann

Mechanisms underlying Individual Differences

To explore potential mechanisms underlying inter-individual variation in recruitment activity within honey bees, we looked at sucrose response thresholds and whole-brain transcript levels of specific genes in individual foragers. The sucrose responsiveness is linked to the ‘behavioural state’ that an individual is in, and while dance intensity showed a small positive correlation with sucrose responsiveness, dance probability did not. We also found that the foraging gene showed a strong negative correlation with the total recruitment activity of individual foragers, adding a new dimension to the role this gene plays in food related motor behaviours in insects.

The manuscript detailing these findings is published in the journal Genes, Brain and Behavior.

Collaborators: Ann-Kathrin Bröger, Markus Thamm, Axel Brockmann and Ricarda Scheiner

Agent Based Model Simulations of Dance Behaviour

One exciting, but largely unexplored, area of research is the role that consistent individual variation plays within social insect groups. Building on an excellent agent-based model by Shürch and Grüter, we first introduced variation in the probability and intensity of dancing amongst the agents that captures the individual variation in total recruitment seen in our empirical data. We then compared the food influx of colonies with and without inter-agent variation to determine how this variation affects the colonies fitness under different environmental conditions.

The manuscript detailing these findings is currently available as a pre-print on bioRxiv.

Collaborators: Supraja Rajagopal and Axel Brockmann