About ten years ago I was working in Cambridge as a research assistant with Dr Alex Thornton, studying a population of wild jackdaws. During the winter months we started observing the huge numbers of jackdaws roosting together, and got fascinated about the incredible timing of the birds all arriving and leaving the roosts at once. We started with some pilot studies of the roost at dawn and dusk, which showed the jackdaws were very vocal in the early morning and seemed to increasingly call more the closer to the moment they were to leave.
Many years later, Alex, who had now started a professorship at the University of Exeter, started looking at our questions again and decided to start a proper project to investigate the mechanisms underlying the massive departures of jackdaw roosts. Together with his master student Alex Dibnah, he was able to collect detailed observational data from a number of roosts across two winters. They also now ran a full-on playback experiment in the field to test our hypothesis that the jackdaws use vocalisations as a means to reach consensus decisions.
We observed the departures of roosts ranging from a couple hundred to a couple thousands of birds. While on some mornings jackdaws departed in a stream of small groups of individuals, on most mornings a majority or even the entire roost departed together and this happened almost at an instance, within a few seconds. By using audio recorders in the roost, we were able to record the calling of the birds and observed that the exact timing of departure of the roost was strongly linked to the calling of the jackdaws: the steeper the increase in calling intensity, the earlier the mass departure.
By a playback experiment in which we played calls of jackdaws in the roost, we were able to make the whole roost leave many minutes earlier than the predicted time of departure. Control playbacks of noise or wind did not induce any earlier departure. Hence, our playback experiments provides further evidence that it is the calling that mediates the timing of the jackdaws’ mass departures. Through their calls, jackdaws appear to effectively signal their willingness to leave, providing large groups with a means of achieving consensus to perform cohesive, collective departures from their roost.
Our study is published in Current Biology: Dibnah, A. J., Herbert-read, J. E., Boogert, N. J., Mcivor, G. E., Jolles, J. W., & Thornton, A. (2022). Vocally mediated consensus decisions govern mass departures from jackdaw roosts. Current Biology, 32(10), R455–R456. https://doi.org/10.1016/j.cub.2022.04.032
I thought it would be nice to have my Google Scholar profile integrated in my academic website. After some thought and trial and error, I came up with an automated method using R and dropbox to have an up-to-date graph of my citations in the sidebar and on my publications page every day! I gave it a simple look just like you can see on Google Scholar profile pages. If others are interested I may write a blog post some day to help explain how to create one yourself!
Predation is one of the main drivers of social grouping in animals. Hence, understanding when, where, and how predators attack animal groups, and the types of anti-predator benefits grouping animals may experience, has been of long-standing interest. Although it is well appreciated that there is differential predation risk within animal groups, our understanding has nonetheless remained largely focused on marginal predation and selfish herd effects.
In a new preprint (link) I just released with colleagues from the Max Planck Institute of Animal Behaviour and Princeton University, we try to overcome this gap. Specifically, we ran detailed experiments with live predators attacking live schools of prey to gain a detailed mechanistic understanding of when, where, and who predators attack in schooling prey.
By tracking the attacks in high spatial and temporal detail, we not only provide novel insights into predator decision-making, but show which key features related to both prey and predator predict individual’s risk to be targeted and survive attacks. Consideration of these multi-faceted factors underlying predation risk, in combination with predators’ attack strategy and decision-making, will have important consequences for understanding the costs and benefits of animal grouping and thereby the evolution of social and collective behaviour.
Reference Jolles, J. W., Sosna, M. M. G., Mazué, G. P. F., Twomey, C. R., Rubenstein, D. I., and Couzin, I. D. (2021). Both Prey and Predator Features Determine Predation Risk and Survival of Schooling Prey. biorxiv, 1–20. doi:10.1101/2021.12.13.472101.
I am happy to say that an exciting paper that I worked on with Shaun Killen, Christos Ioannou, and others is now available online in Frontiers in Physiology. In the paper we line out physiological performance curves, the nonlinear changes in the physiological traits and performance of animals across environmental gradients, and discuss their potential to change social behaviour and group functioning, and the ecological consequences
The paper leans heavily on my 2020 TREE paper with Shaun and Andrew King, but goes further by focusing on individual heterogeneity in variability between individuals. The work is mostly theoretical because there is still very little empirical work done, so looking forward to test some of the ideas myself with Shaun and colleagues next year in terms of how fish differ in how they respond to severe droughts. You can download the paper open access here!
Reference Killen, S. S., Cortese, D., Cotgrove, L., Jolles, J. W., Munson, A., and Christos, C. (2021). The potential for physiological performance curves to shape environmental effects on social behaviour. Front. Physiol. 12, 754719. doi:10.32942/osf.io/bh968.
I am excited to say that a new paper that I have been involved in came out today in Frontiers in Physics about the role of speed variability in collective animal behaviour.
A number of agent-based models have been developed to help understand how coordinated collective behaviour can emerge from simple interaction rules. Thereby, a common, simplifying assumption is that individual agents move with a constant speed. In this paper together with the team of Pawel Romenczuk and colleagues in Berlin, we critically re-asses this assumption and provide new theoretical evidence that shows variability in the speed of individuals can have profound effects on the emergent collective patterns.
I have long been working on the role of individual heterogeneity in collective behaviour and was therefore excited to collaborate with Pawel and his team to run in-depth computer simulations to start better consider behavioural variability as a source of heterogeneity in animal groups. You can find the paper (open access) here.
Reference: Klamser, P. P., Gómez-Nava, L., Landgraf, T., Jolles, J. W., Bierbach, D., and Romanczuk, P. (2021). Impact of Variable Speed on Collective Movement of Animal Groups. Front. Phys. 9, 1–11. doi:10.3389/fphy.2021.715996.
Today my latest paper came out in Trends in Ecology and Evolution. Co-led by Valerio Sbragaglia at ICM in Barcelona (joint first-authorship) and with Marta Coll and Robert Arlinghaus, we provide a new perspective about the role that fisheries may have on the shoaling tendency and collective behaviour of exploited fish species. Besides discussing the different potential mechanisms (see also figure below), we highlight potential consequences for fish populations and food webs, and discuss possible repercussions for fisheries and conservation strategies.
It has been nice to work on the ideas of this paper and focusing a bit more on the important practical implications of my main research topic of individual heterogeneity and collective animal behaviour. I am looking forward to further work I will be doing with Valerio and our colleagues to start test some of the ideas we put forward in our paper and co-supervise students on the topic.
Reference Sbragaglia, V., Jolles, J. W., Coll, M., and Arlinghaus, R. (2021). Fisheries-induced changes of shoaling behaviour: mechanisms and potential consequences. Trends Ecol. Evol. 36, 885–888. doi:10.1016/j.tree.2021.06.015.
Single-board computers like the Raspberry Pi have taken the world by storm and are being used in almost any situation imaginable. In a new open-access paper I published in the journal Methods in Ecology and Evolution, I now show these low-cost open-source computers are also increasingly being used in science and highlight how the Raspberry Pi can play a fundamental role to further revolutionise biological research.
By reviewing the biological literature, I found over a hundred empirical studies across the biological domain that implemented the Raspberry Pi in some way, both in the lab, the field, and in the classroom. The list of applications is almost endless, and ranges from weather stations, and automated bird feeders, to closed-loop learning devices, deep-sea recording systems, environmental monitoring tools, and wild-life camera traps.
The broad capabilities of the Raspberry Pi, combined with its low cost, ease of use and large user community make it a great research tool for almost any project. But despite its increasing uptake by the scientific community, the Raspberry Pi is not the common research tool that it actually could be.
To stimulate its uptake and help researchers integrate the Raspberry Pi in their work, I provide detailed recommendations, guidelines, and considerations, and developed a dedicated website (raspberrypi-guide.github.io) with over 30 easy-to-use tutorials.
I believe low-cost micro-computers like the Raspberry Pi are a powerful tool that can help transform and democratize scientific research, and will ultimately help push the boundaries of science. I therefore hope my paper will help generate more awareness about the Raspberry Pi among scientists and help advance our understanding of biology, from the micro- to the macro-scale.
Source Jolles, J. W. (2021). Broad‐scale applications of the Raspberry Pi: A review and guide for biologists. Methods Ecol. Evol. 12, 1562–1579. doi:10.1111/2041-210X.13652
Update: My paper has been picked up by the Raspberry Pi Blog (link), scidev.net (link), and Niche magazine of the British Ecological Society (link, p12), among others!
I just heard the news that our grant application entitled Cognitive buffer and population persistence under environmental change for a Research project grant was awarded by the Spanish Ministry (I+D+i, MICINN)!
Using a population of jackdaws that has been monitored for two decades, we will combine molecular analyses, field observations, field experiments, and remote sensing to analyse how individuals gather and share information to exploit food resource that vary in time and space, and assess how their individual and collective decisions affect population dynamics.
The €160k grant is led by Dr Dani Sol, also from CREAF, and is for until the end of 2023. I am excited to be part of the interdisciplinary team and to be working with Jackdaws again, pushing novel technologies to study their individual and collective behaviour in the wild!
Together with my CREAF colleague Professor Dani Sol I am happy to say I recently started co-supervising my first PhD Student. Marçal Pou Rossell will be studying the role of behavioural plasticity and individual differences related to (social) cognition in wild jackdaws. He will be working on the large monitored Jackdaw population dat Dani has been managing near Lleida, Spain, and his PhD work will likely combine GPS data with behavioural observations and automated nest-box monitoring to better understand how individuals deal with their changing environment, make foraging decisions, and how that is affected by their social context. You can find him on instagram here.
I am happy to say that today I start my new job as an independent postdoctoral researcher at the Center for Ecological Research and Forestry Applications (CREAF)! CREAF is a research institute in Barcelona, Spain, focused on biodiversity and global change and has been accredited as an Severo Ochoa Center of Excellence. I am excited to continue my work on individual heterogeneity here in Catalunya to understand how animal groups and communities deal with environmental change. Watch this space!
I was invited to give a talk today as part of the yearly workshop of the White Sea Stickleback Research Group. Virtual because of covid of course, so unfortunately no trip to the White Sea yet. But some great questions, nice to see the research being conducted by Dmitry Lajus and his group, and meeting some fellow stickleback researchers. They also have a very active instagram account: three little spines.
Today I gave a seminar at CEAB, a CSIC research institute in Blanes, Spain focused on understanding aquatic ecosystems. Excited about the potential to collaborate on experimental and observational work on freshwater and marine fish populations in the region.
My latest paper has just been published in the Journal of Open Source Software! It is the paper that accompanies my Python package pirecorder, which facilitates controlled and automated image and video recordings with optimal settings for the raspberry pi, specifically developed for biological research.
So far, researchers have often relied on writing their own recordings scripts to take still photographs and videos from the command line.
Although some specific software solutions exist, what was missing is a complete solution that helps researchers, especially those with limited coding skills, to easily set up and configure their raspberry pi to run large numbers of controlled and automated image and video recordings.
pirecorder was developed to overcome this need. You can get a quick overview of the package and what it is capable of in the video below:
Today my latest paper came out in Biology Letters! You can find it here.
The spectacular and complex visual patterns created by animal groups moving together have fascinated humans since the beginning of time. Think of the highly synchronized movements of a flock of starlings, or the circular motion of a school of barracudas. Using state-of-the-art robotics, a research team from the University of Konstanz, Science of Intelligence, and the Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB) shows that animals’ speed is fundamental for collective behavioral patterns, and that ultimately it is the faster individuals that have the strongest influence on group-level behavior. The study, published in Biology Letters of the Royal Society, gives new insights on complex collective behavioral patterns in nature, and provides knowledge that could help develop robotic systems that move collectively, such as robot swarms, driverless cars, and drones.
Researchers have long focused on identifying the emergence of collective patterns. Thanks to a combination of behavioral experiments, computer simulations, and field observations, it is clear that many seemingly complex patterns can actually be explained by relatively simple rules: move away from others if they get too near, speed up towards others if they get too far away, and otherwise move at the same speed and align with your group mates.
“Besides understanding the rules that individuals follow when interacting with others, we need to consider the behaviors and characteristics of those individuals that make up the group and determine their influence for collective outcomes” says Dr. Jolle Jolles, a scientist at the Zukunftskolleg, University of Konstanz, and lead author of the study. “Across the animal kingdom, it has been found again and again that animals tend to differ considerably from one another in their behavior such as in terms of their activity, risk-taking, and social behavior“. What are the consequences of this behavioral heterogeneity when it comes to collective behavior? And how can one test for its social consequences?
To disentangle the role of individual differences in collective behavior and the mechanisms underlying this type of behavior, the research team built “Robofish”, a robotic fish that not only realistically looks and behaves like a guppy – a small tropical freshwater fish – , but also interacts with the live fish in a natural way. The experimenters paired the robotic fish with a guppy and programmed it to always follow its partner and copy its movements, lacking however any movement preferences of its own. The team then used high-definition video tracking and a closed-loop feedback system to let the robotic fish respond to the live fish’s actions in real-time.
“One of Robofish’s simple interaction rules was to keep a constant distance to its shoal mate” explains Dr. David Bierbach, who works within the Berlin-based Excellence Cluster ‘Science of Intelligence’ at the HU Berlin and the IGB, and is senior author on the paper. “Using this rule, our Robofish tried to keep the same distance to the live fish by accelerating and decelerating whenever the live fish did. Also, programming the robotic fish without any own movement preferences gave us the unique opportunity to investigate how individual differences in the behavior of the live fish led to group-level differences. In short, with our unique approach, we could isolate the effect of the fish’s movement speed on the pair’s collective behavior“.
The researchers first quantified the guppies’ natural movement speed by observing their movements when alone in an open environment, and found that there were large individual differences in how fast guppies tended to move. When the fish were subsequently tested with Robofish, the fish and Robofish tended to swim naturally together as a pair. However, the researchers observed that there were large differences in the social behaviors between the pairs: pairs in which the guppy had a faster movement speed tended to be much more aligned, more coordinated, and less cohesive, and the guppy emerged as a clearer leader. As Robofish behaved according to the same identical rules with each and every guppy, it is the individual speed of the guppies that must have led to these differences in group-level properties.
By involving state-of-the-art robotics, this research shows that individual speed is a fundamental factor in the emergence of collective behavioral patterns. As individual differences in speed are associated with a broad range of phenotypic traits among grouping animals, such as their size, age, and hunger level, the results of this study may help understand the role of such heterogeneity in animal groups.
Future studies using the interactive Robofish will focus on other aspects of collective behavior: For example, how can animals act in synchrony if they just respond to the actions of their neighbors? “We want to improve Robofish’s software so that it can predict and anticipate the live fish’s next steps, which is assumed to be how animals do it.” says David Bierbach.
Understanding these mechanisms is not only fundamentally important as it reveals information about the mechanisms that underlie collective behavior and decisions, but also because this knowledge can be applied to artificial systems and used to develop machines that move collectively, such as robot swarms, driverless cars, and drones.
I have been awarded a €3.900 grant from the Young Scholar Fund for a pilot project in the Spanish Pyrenees to assess the effects of severe drought on fish persistence. Specifically, I want to understand how individuals and groups of fish deal with severe droughts and how phenotypic variation may impact population structure and persistence. This project will hopefully provide the basis for a long-term project whereby I will use an individual-based approach to understand how individuals and groups of fish cope with environmental change.
Today my latest paper Schistocephalus parasite infection alters sticklebacks’ movement ability and thereby shapes social interactionshas been published in Scientific Reports! Although many fundamental aspects of host-parasite relationships have been unravelled, few studies have systematically investigated how parasites affect organismal movement. In this study we combine behavioural experiments of Schistocephalus solidus infected sticklebacks with individual-based simulations to understand how parasitism affects individual movement ability and how this in turn influences social interaction patterns.
By detailed tracking of the movements of the fish, we found that infected fish swam slower, accelerated slower, turned more slowly, and tended to be more predictable in their movements than did non-infected fish. Importantly, the strength of these effects increased with increasing parasite load (% of body weight), with the behaviour of more heavily infected fish being more impaired.
When grouped, pairs of infected fish moved more slowly, were less cohesive, less aligned, and less coordinated than healthy pairs. Mixed pairs exhibited intermediate behaviours and were primarily led by the non-infected fish. These social patterns emerged naturally in model simulations of self-organised groups composed of individuals with different speeds and turning tendency, consistent with changes in mobility and manoeuvrability due to infection.
Together, our results demonstrate how infection with a complex life cycle parasite affects the movement ability of individuals and how this in turn shapes social interactions, providing important mechanistic insights into the effects of parasites on host movement dynamics. Download our open access paper here!
Today I gave a talk at the 2020 ASAB Summer meeting about my recent work about the effects of Schistocephalus parasite infection on individual and social behaviour (paper here). It was my first talk at a virtual meeting, which took a bit more time to prepare, but despite being completely virtual due to the covid-19 pandemic, the conference turned out really well. Many people “attended” my talk, which was followed by a live Q&A with the other speakers in my session. All other conferences I was planning to attend this year (at least 4) have been cancelled this year, so it was great to that this conference was made possible in the virtual realm at least!
I am excited to hereby release this 3 min short about my work. With support from the Zukunftskolleg, I teamed up with Berlin filmmaker Nicolas Buenaventura to create this video to provide a visual overview of my research. It also gives some nice insights about the various aspects of my work, from catching fish, setting-up experimental systems, writing my own recording and tracking software, to analysing data.
Today I released a new preprint on bioRxiv, Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish, which is the result of a great collaboration with David Bierbach and colleagues at the Humboldt Universität zu Berlin.
In this paper we present results of an experiment to investigate how the speed of individual group members leads to group-level patterns. We paired guppies with a biomimetic robot that was programmed to always follow and lack any individual preferences of its own. We used a state-of-the art closed-loop tracking and feedback system to be able to properly control for the influence of individual heterogeneity of the individual’s group members.
We show that individual differences in guppies’ movement speed were highly repeatable and shaped key collective patterns: higher individual speeds resulted in stronger leadership, lower cohesion, higher alignment, and better temporal coordination in the pairs. By combining the strengths of individual-based models and observational work with state-of-the-art robotics, we provide novel evidence that individual speed is a key, fundamental process in the emergence of collective behaviour.
I am excited to say that our review in Trends in Ecology and Evolution, after already being available online, is out now in print and is shining on the front cover! I took this photo of this stunning stickleback school while snorkelling in the Bodensee to study their collective behaviour. Read our open access paper here.