Plasticity can take the lead in adaptive evolution

Plasticity-led evolution would be likely if the trait combinations induced by novel environments harbour more than their fair share of genetic variation. Our new paper in PNAS shows that this is in fact quite common. For a nice overview, see this post by Luis-Miguel Chevin on F1000.

Dan Noble and Reinder Radersma collected data from studies that quantified traits and their additive genetic covariance in animals and plants exposed to novel environments. On the whole, the multivariate phenotypic change caused by environmental change were well aligned with the maximum genetic variation – and better than expected by chance.

There are several ways to interpret these results. Perhaps the most interesting from the perspective of evolvability is that developmental systems respond to environmental novelty as they do to genetic mutation. Such developmental bias means that populations that evolve plasticity will tend to continue to evolve in some ways rather than others. The present paper is the first in a series of empirical and theoretical papers that address this problem as part of our group’s involvement in an international research effort. So please keep an eye out for more.

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It is time to say goodbye…

… to Reinder and Alfredo.

As the EES grant comes to a close, we are sad to see some of our friends move on, but excited about the opportunities they have created for themselves.

Reinder is now a researcher in statistical genetics at Wageningen University & Research Institute, which is THE place to be for agriculture, environmental and food science. His work on maternal effects, plasticity and evolvability will undoubtedly prove useful also to domesticated plants and animals.

Alfredo also leaves us, in this case for a postdoc in Copenhagen. After a couple of years with theory, he is now ready to get his hands dirty with data again. The aim is to reveal the molecular complexities of maternal-fetal communication, a perfect opportunity to transfer skills between evolutionary and developmental biology!

Although it is sad for all of us to see them leave, it is particularly sad for Tobias – they have known each other since the Oxford years, when Reinder did a postdoc with Ben Sheldon and Alfredo his MSc with Tobias. They have been fantastic friends and colleagues – always positive, helpful, and engaged. Hats off for everything you have taught us over the years.

See you soon!!




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Summer cottage getaway

All visitors to Sweden should experience that summer cottage feeling! Accordingly, the group packed their thermal underwear, swim trunks, shorts and rain coats and headed to Tobias’ family’s cottage in Värmland. All outfits came to good use since we had typical Swedish summer weather – blue sky followed by rain, and then glorious weather when we had to leave. Just like every year.

View from the veranda on day 1…. and day 2…

Germs, lizards and field work cut our numbers this time. But the rest of us had a great time – relaxing, birding, fishing, swimming, and beaver watching, enjoying local art exhibitions, cultural history, snaps, and grillkvällar… or, to quote Yang: “we managed to do and see everything we were promised – and in addition we watched the Champion’s League final!”

What can we catch here – pike? perch? pikeperch?… hang on, what did you just say!?  
Yang and Roman are off for an adventure! They did come back eventually.


A beaver with unfinished business, perhaps the one that swam past this morning?


Summer lunch with traditional food, snaps and songs. The students are getting younger every year…


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Geoff While visiting

We are very happy to have Geoff While from the University of Tasmania visiting us for three months. Geoff is a fantastic friend and collaborator whose scientific drive, passion for biology, and lizard catching skills are nearly impossible to beat. In addition to the usual wall lizard field season, we have a few old projects to finish off, some that are in full swing, and perhaps one or two new ones to launch. Not to mention all the other things you could get done over a beer or two. Welcome Geoff!



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Ullergroup at Evolution Evolving

The Evolution Evolving at Cambridge was packed with three days of exciting talks – from culture in whales to control theory and the philosophy of explanation. The crew from Lund felt like lizards in the sun – pretty comfy and happy! So much in fact that Alfredo won the prize for best talk, and Illiam the prize for best poster. Congratulations to both!

We are very grateful to our fellow organisers and all the participants for making this such a great event. A full conference report will be posted in due time at the EES webpage, together with recordings of plenaries and key notes. They were brilliant! Until then, you can see what you missed at #evoevolving and #EES_Update

Alfredo on “How does evolution work with strong attractors?”


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How adaptive plasticity evolves when selected against

Yes, that is the surprise title of Alfredo’s new paper in PLoS Computation Biology! When we discover examples of adaptive plasticity we usually think that it evolved because selection favoured it. But can adaptive plasticity evolve when selection favours non-plastic individuals?

Think of a population of insects that hatches, reproduces and dies twice every year: once in spring and once in autumn. Spring and autumn conditions may be very different, but plasticity could allow the insects to cope with both seasons. Yet, insects born in spring never experience autumn, and vice versa, so natural selection cannot directly favour plasticity. In fact, plastic individuals may do worse than individuals that are not plastic, which means plasticity could consistently be selected against.

This problem is similar to tuning the learning rate in Machine Learning. To teach a machine how to solve a problem, we give it a set of example questions we already know the answer to. Each time the machine gives us the wrong answer, we change its parameters to produce a new answer that is closer to the right one. If the examples share a consistent logic, the machine will eventually find this logic. But if we change the model’s parameters too much with every example shown, the machine will just repeat the solution for the last example, which prevents it from finding the underlying logic that connects the examples.

Just like in machine learning, organisms receive a set of questions in the form of environmental cues and need to provide the right answer in terms of a fit phenotype. Adaptive plasticity is the solution that produces the right phenotype for every environment. Organisms that see only one environment per lifetime could easily “forget” that plasticity is adaptive and instead only produce the right phenotype for their last environment. The offspring of insects that live in spring would be better matched to spring, even though they will have to deal with autumn conditions.

So when does learning theory predict that a machine will learn the logic of plasticity rather than the last solution? And do those predictions hold for a simple representation of evolution by natural selection? To find out, have a look at the paper!

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