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.
Today we had the full-day PhD Workshop I co-organised with Jean-Christophe Billeter as part of the 2019 NVG (Netherlands Society for Behavioural Biology) Meeting in Groningen. The aim of the meeting was to facilitate discussion about science and academia for PhD students in the field of behavioural biology in a private setting. About 20 students participated and gave a talk about their work after which we had a general discussion about the things they were struggling with. It was really nice to be on the other side and help by sharing my own experiences and lessons I learned as a PhD student and early postdoc to manoeuvre through our world that is academia.
The past years I have been bridging the fields of behavioural ecology with mechanistic perspectives of collective behaviour research. I have recently started to use these concepts to set up some projects to understand how fish populations deal with environmental change, including field work in the Spanish Pyrenees focused specifically on the role of individual heterogeneity in the context of severe effects of floods and droughts.
I have just returned from York where I have presented some of my ideas at the BES conference Impacts of extreme climatic events on ecosystems. It was a great meeting, with many in-depth group discussions about the effects of climatic events on different ecosystems and it was nice to be able to present and discuss my research plans with the broad diversity of people attending. Good to be back in the UK for a couple days as well!
At the ASAB Summer Conference in Konstanz this year, which was focused on new frontiers in the Study of Animal Behaviour, I gave a half-day workshop about automating behavioural experiments with Raspberry Pi’s.
After a general introduction, I discussed its use in animal behaviour research, how to set up, work with, and remotely control a raspberry pi, how to work with the rpi camera system, and finally how to automate recording, including via my own pirecorder software.
I started working with these amazing machines during my PhD, which where then still quite difficult to set up and quite slow, but now with the newest model for almost the same low price, so much is possible!
It was great to see so many people (120) interested in this great open-source technology for their own work, and many told me soon afterwards they immideately started setting-up their own systems.
Due to the interest and enthusiasm I am planning to give more and more hands-on workshops in the near future. Stay tuned!
After chairing one of the sessions at the ASAB Summer Conference in Konstanz today it was time to give a talk myself. I presented an exciting project that explores the role of Schistocephalus parasite infection on individual movement and social interactions. Using experiments and individual-based modelling we show mechanistically this fascinating parasite strongly impairs mobility, with large cascading effects for animal groups.
Today my latest paper came out in Animal Behaviour, one of my favourite journals. It is titled “Personality, plasticity and predictability in sticklebacks: bold fish are less plastic and more predictable than shy fish“. In this paper, which is a result of a collaboration with Neeltje Boogert and Yimen Araj-Ayoy and a MSc project of Helen Briggs, we present an extensive experimental study focused on better understanding the sources of behavioural variation among individual animals.
In short, we tested 80 three-spined sticklebacks repeatedly on their boldness across a 10-week testing period and automatically tracked their movements. We then employed advanced statistical model techniques (GLMMs and DHGLMs) to use this large behavioural dataset to investigate the potential links between the personality (consistent differences in average behaviour), the plasticity (how individuals change their behaviour over time/contexts), and predictability (the remaining intra-individual variation after accounting for personality and plasticity differences) in behaviour.
Besides detecting large consistent individual differences in boldness and the extent to which fish changed this behaviour over time (temporal plasticity), we found that boldness personality and plasticity were negatively linked, with bold fish changing little in their behaviour over time. Interestingly, there were still large individual differences in the remaining behavioural variation, with bold fish showing much less behavioural variation and thus behaving more predictable than shy fish. Importantly, these results suggest that boldness, plasticity and predictability may be fundamentally linked and form part of the same behavioural syndrome.
Jolles, J. W., Briggs, H. D., Araya-Ajoy, Y. G., & Boogert, N. J. (2019). Personality, plasticity and predictability in sticklebacks: bold fish are less plastic and more predictable than shy fish. Animal Behaviour, 154, 193–202.
I am happy to say I have taken on the role as Head of Animal Facilities at the University of Konstanz Limnological Institute. With this new role I am the main responsible of animal ethics and holding at the institute and oversee the different facilities and projects to make sure they conform to the guidelines of the Animal Welfare Regulation Governing Experimental Animals.
From today you can stay up to date about my research and get a glimpse into the life of a Behavioral Ecologist on my new instagram account: @jollewjolles!
Not only do I think it is great to provide the outside world a glimpse into the scientific process, I also really enjoy showing all the different components of my research, from catching fish and calibrating cameras to late night grant writing and attending conferences, that all together eventually culminate into my academic papers.
Over the Christmas break I couldn’t resit playing around with some detailed stickleback photos I took for one of our experiments, and created my first full-size non-academic poster! It just arrived and I am very excited about the result:
My first non-academic poster: an array of close-up photos of 33 experimental sticklebacks.
The poster shows the 33 individual sticklebacks that we used for an experiment in which we investigated consistent individual differences. As is clear from the poster, despite the fish being size-matched for the experiments, the fish have a beautiful range of colour and shading patterns. Let’s see if I’ll continue doing this for all my future experiments..!
When you start working with Python it is great practice to create isolated Python environments to work on your specific projects.
The standard python environment is used by a large number of system scripts and therefore best to leave alone. In addition, when working on different projects, those projects may have different and conflicting dependencies and therefore should ideally be installed in their own python environments. The ability to create different python environments can also be really beneficial when developing your own python packages and thereby test its installation and performance in different versions of python.
Below I guide you through the basic steps of installing and working with python virtual environments.