This AI just figured out geometry — is this a step towards artificial reasoning?

Shamini Bundell

Welcome back to the Nature Podcast, this week: an AI that’s figured out geometry…

Benjamin Thompson

…and how mass predator die-offs might affect ecosystems. I’m Benjamin Thompson.

Shamini Bundell

And I’m Shamini Bundell.

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Shamini Bundell

First up on the show, reporter Nick Petrić Howe has been learning about an AI that can logically deduce solutions to complex mathematical problems. Here’s Nick.

Nick Petrić Howe

You might think that computers are pretty good at maths. When I have a mathematical conundrum for instance I will often reach for a calculator or a trusty spreadsheet. But fundamentally a lot of maths is about logic — deducing what makes sense from the information you have. Meaning that a lot of mathematical problems are really just complicated puzzles. In fact, there is a competition known as the Mathematical Olympiad where high school students are given challenges, where they need to figure out solutions to such puzzles. They’ll be given a series of statements like “x + y = this” and also “5 to the power y equals that” etc and then they’ll have to use these to figure out the solution to a puzzle, like “what could x be?” Challenges like this are difficult though for computers and AIs, as Thang Luong, deep learning researcher and former Mathematical Olympiad competitor, explains.

Thang Luong

Let's say if I give you two basket, each have like 10 balls, how many balls do I have in total. So these actually machine can solve pretty well. But for problem by Mathematical Olympiad, it will involve very deep reasoning. So the model have to think for many, many, many steps before it can arrive at a solution. That's actually what makes it so interesting.

Nick Petrić Howe

In fact, tackling these Mathematical Olympiad problems has been of interest to AI researchers for decades and it’s been a tough nut to crack. The best AIs still fare worse than the average International Mathematical Olympiad competitor. The thing that makes these lympiad challenges so well… challenging is that there is essentially an infinitely large number of ways you could try and tackle a problem. Where do you even start? Arguably, you have to reason — logically draw conclusions from what is given to you. In other words, if this is true, then this should also be true. This is something that we normally input into our machines, they don’t normally work it out for themselves from scratch.

Thang Luong

So that would require, you know, a lot of thinking ahead, and sometimes creativity as well. So the machine needs to be creative. It needs to think for a long time.

Nick Petrić Howe

Now the way that many Ais solve challenging problems is by scouring through a lot of data and ‘learning’ from it certain rules about how one thing applies to another. This is how Large Language Models, like ChatGPT, are built for example. But for would-be Mathematical Olympiad Ais there’s a snag here.

Thang Luong

Large language models, like ChatGPT can read the entire internet, you know, it understand all kinds of knowledge from Wikipedia, from Reddit. But then for Mathematical Olympiad problems, these kinds of data to teach machine is so limited. There’s not many material on the Internet, there are a few forums, but that’s not enough data to really teach the machine.

Nick Petrić Howe

But despite this lack of training data, Thang and a team of researchers are demonstrating an AI, known as AlphaGeometry in Nature this week. And unlike previous attempts their system can reach the top levels of human performance on geometry problems from the Maths Olympiad. But for the AI to solve these problems, the team had to solve their own — what to do about the lack of data? Well, they made it themselves.

Thang Luong

We leveraged a large amount of computation at Google to synthesise a large amount of training data for the machine to learn from scratch. So, in total, we was able to generate 100 millions of theorem and proof so that the machine can learn all of these by itself. And then it can learn to generalise the new problems.

Nick Petrić Howe

This huge volume of random mathematical theorems and proofs — statements and the relevant logical argument that back them up — were given to AlphaGeometry, which used them to work out general rules of geometry. With that in place, it was ready to take on the Mathematical Olympiad. AlphaGeometry was fed the olympiad problems, which it worked on using a two-part system, a neural network and a symbolic system, two different kinds of AIs that each operate at a different pace. They worked together, to solve the problems

Thang Luong

So the neural network you can think of it like system one, because neural network can think very fast. It can be creative, it can suggest interesting lines and points to help unlock a solution. And then we have a symbolic system, which is system two, it’s reliable, but it's slow.

Nick Petrić Howe

The symbolic system was the one that was trying to use logic to solve the puzzle — it did the heavy lifting, using the geometry rules it ‘learned’ from the synthetic data to solve the problem. And you might think that system would be enough, but actually you need the creative system one as well. As often the slow symbolic system gets stuck and so it needs a bit of creative juice to get its cogs turning. For example, if the symbolic system is working on a problem involving triangles and gets stuck, the creative system one neural network can suggest maybe splitting the triangle in two and thinking about those two ‘new’ triangles instead. The problem would be the same, but, if you'll pardon the phrase, it would be able to think about it in a different way. The systems then go back and forward like this until the problem is solved. Together they would create a proof, essentially showing how it solved the problem, which humans could then check. And this is exactly what happened. The system was given a series of Maths Olympiad problems, and it figured out ways to solve them and wrote out its solutions. Thang and the team then sent the AI’s solutions to pupils of the Maths Olympiad and the US coach who were then able to verify them. Overall, Thang was pleased with how their AlphaGeometry theoretically would have performed, if it was in an International Mathematical Olympiad.

Thang Luong

We were very happy that for the year 2000, 2015 AlphaGeometry was able to solve all the geometry problem in that year. So, you can think of it like an AI for the first time achieved the bronze medal.

Nick Petrić Howe

The AI would win bronze as it only focused on geometry, whereas the actual competition involves other kinds of maths as well. But, if you did just look at geometry problems then AlphaGeometry was almost at the gold-medallist level — solving 25 out of 30 problems where gold medallists solve on average 25.9. However, in years other than 2000 and 2015 the AI wasn’t able to solve all the geometry problems, which could perhaps be down to certain geometry theories not being part of the synthetic data that the AI was using. Another issue was that the solutions that AlphaGeometry came up with were very long, which may be down to much the same reason. Effectively, the AI only knew the very basic rules of geometry, whereas humans are able to use other theorems and even other mathematical notations to shorten their explanations. So in the future Thang would like to make the solutions a bit more… elegant.

Thang Luong

The solution from AlphaGeometry for the year 2015, it’s a long list of steps, it’s 109 steps in the solution. This is something that we're not optimised for actually, so far we only optimised to get the solution, but it can also be in the future, we might want to optimise for some beauty, you know, because with 109 steps, it will be a lot of work for people to actually read the proof.

Nick Petrić Howe

Beautiful or not though, Thang believes that AlphaGeometry shows that it’s possible to build AIs which can ‘learn’ basic principles from large amounts of data and apply them to other situations. For some researchers, this could be a step towards building AIs that could ‘reason’ and potentially come up with solutions even in fields outside mathematics.

Thang Luong

It really tells that we can actually build AI to learn from scratch. And then in the future, hopefully AI can discover new knowledge from other domains.

Shamini Bundell

That was Thang Luong, from Google DeepMind. He’s based in the US. For more on that story, check out the show notes for a link to the paper.

Benjamin Thompson

Coming up, how researchers built their own ecosystem to find out what happens when a large number of predators die off in a short period. Right now though, it’s time for the Research Highlights, with Dan Fox.

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Dan Fox

A new material dubbed a ‘hydrospongel’ could find uses in soft robotics by mimicking living tissue. Tissue, like cartilage, can withstand heavy loads and hold large quantities of water, which is helpful in biological systems. But this combination is a challenge for synthetic materials. Hydrogels, for instance, are good at holding lots of water, but they tend to irreversibly deform when squashed. Sponges are resilient to heavy loads springing back after being deformed, but this lack of stiffness means they are too soft for many uses, and drain their liquid contents too readily. Now, researchers have designed a new material made from a network of Kevlar polymer fibres enriched with nitrogen atoms. The interwoven polymers — similar to those used in bulletproof vests — made the gel-like substance stiff, while creating nanoscale pores that trapped water and allowed it to diffuse. Under high compression, the spaghetti like network released water and got squashed before springing back. The material held more than 5,000 times its own weight in water and was 22 times stiffer than comparable water-rich gels. The authors say it could be used in drug delivery, or to build scaffolds for tissue engineering. You can soak up the rest of that research in Nature Materials.

The level of methane in the atmosphere is rising, and scientists have attributed much of that rise to emissions from tropical Africa. And new research puts a large percentage of the continent’s increased emissions down to rice production. Like cattle and natural wetlands, flooded rice paddies can host micro-organisms that emit methane. Between 2008 and 2018, rice production in sub-Saharan Africa doubled. And so a team of researchers recalculated emissions to take this into account. The new number suggests that rice growing in Africa accounted for nearly a third of the increase in the continent’s methane emissions between 2006 and 2017, and for 7% of the global increase in the same period. With aims for rice production in the region to double again between 2019 and 2030, multinational goals of reducing methane emissions by 30% will require deep reductions elsewhere to compensate. You could read that research in full in Nature Climate Change.

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Benjamin Thompson

Ecosystems are all about balance. For example — take a super simplified, three-stage food web — plants, herbivores, carnivores. The nutrients in the system feed the plants, which feed herbivores which feed the carnivores. And so the quantity of nutrients impacts the rest of the system from the bottom up. At the same time, the carnivores eat the herbivores and keep their numbers in check, which reduces the number of plants eaten and so allows more plants to grow and so the system is regulated from the top down. Top down and bottom-up effects like these exist in constant, shifting, complex balance, but what happens when that balance is interrupted? Mass Mortality Events, sometimes called mass die-offs, can result in huge numbers of a single species dying off in a short period of time. Events like these have been seen in a variety of different animals: fish, birds, antelope the list goes on. And the numbers of animals that perish can be staggering, in some cases estimates range into the millions or even billions. But there’s not a huge amount known about the effects that events like these might be having on wider ecosystems. Well, that is something that Adam Siepielski from the University of Arkansas and his colleagues have been studying. I gave Adam a call.

Adam Siepielski

I mean, what we wanted to do was, in part, test some of the theory that we had been developing, and we really wanted to know, could you take these really wonderful classic ideas in community ecology, top-down effects where predators have an important role in affecting primary producers like plants, or algae and ecosystems and bottom-up effects, where nutrients are the important factor regulating primary producers and ecosystems and could we combine them. And then use those combinations to make a prediction about how a system would actually respond when predators die, decompose for these nutrients and generate that bottom-up effect.

Benjamin Thompson

So obviously, if you want to test this hypothesis and work out what's happening during a mass die-off, you have to study an ecosystem, right? But you can't go into the wild and cause a mass die-off, of course. So what you've done, then you've actually built your own freshwater ecosystem, a series of artificial ecosystems to test what a predator mass die-off might do. How do you go about making these ecosystems and what does one look like?

Adam Siepielski

So, we did take this classic approach in ecology, and generally these little, they're called mesocosms, they're sort of like a smaller version of like a complex lake-ecosystem. What do they look like? If you ever go out to like a farm or something and see a big barrel of water that cattle are drinking water from, that's what those things are, there's nothing special about them we fill them up with water and then we just sort of start seeding it. A lot of the basic things of the food web naturally kind of come in like some of the bacteria will get in there. But you know, we put some like leaf litter in there to start to decompose that releases nutrients that allows algae, phytoplankton the base of this food web to start to grow in the system. We went out to a local lake and we collected zooplankton, the things that eat all the phytoplankton, so the algae and the diatoms, that sort of thing. And then we eventually stocked it with fish, bluegill, which are really common game fish, and really one of the most important predator species of zooplankton in the part of the lake that we were looking at. So basically, we just established like, three different trophic levels that naturally occur in lakes.

Benjamin Thompson

And so you had these artificial ecosystems then, and you treated them in different ways. Some of them you just left as they were, some of them, you removed the fish manually. And some of them you used electricity, in part, to cause a mass die-off of the fish. What did you see? What was the difference between the ecosystems? How do they compare?

Adam Siepielski

Yeah, so after we, you know, induced this mass mortality event, we compared a number of different features of the remaining food levels that were present. And if you remove the fish, one of the things that happens is that the zooplankton become more abundant, because the predators that ate them are now gone. And when they become more abundant, the phytoplankton — the things that the zooplankton eat — start to go down. But one of the unique facets though, was that because in a mass mortality event, when the fish are dying and then decomposing, the zooplankton aren't able to simply consume all of the phytoplankton up and cause the system to sort of collapse. What happens is that because those fish die, and decompose and release those nutrients, that kind of causes a fertilisation effect, that allows for the primary producers, the phytoplankton to stay abundant, even though there's this increase in the zooplankton herbivores in a system. What that actually looks like is that it becomes very similar to the control system where everything is being like, nicely regulated. And so it kind of looks a little bit more just like an intact ecosystem,

Benjamin Thompson

And how does this fit then with ideas of what might happen?

Adam Siepielski

I mean, so we had developed some mathematical theory where we had tried to make predictions for what would happen, and some of those predictions that we had actually sort of generated a few possibilities, because one thing that we have sort of surmised could happen, and does sometimes happened during a possible like, mortality event, is that the death of those predators could sort of have almost like a toxifying-like effect, and that they could decompose and cloudy the water like so much, that the primary producers become a little bit light limited. And they couldn't even begin to proliferate. Alternatively, and what we found, though, was that, that doesn't really seem to happen, those predators do go to the bottom, they decomposed to release those nutrients, like nitrogen and phosphorus and causes those producers to increase. So it matched very well. Like I remember, when we first got the data, we were like, holy cow, that looks exactly like what we thought it was going to look like. And that was really reassuring for, you know, community ecologists to be able to say that, you know, we've got this beautiful, messy, complex ecosystem that has all these things going on, we can simplify it into this little body of a couple of differential equations, sort of make these projections for how these things should look. But then when you actually get the empirical data based on, you know, experiments from these mesocosms, it was amazing. I was like, this is so cool. It's like we were able to, you know, kind of predict these things.

Benjamin Thompson

I mean, what does this result mean, Adam? Because naively one can make the argument that a mass die-off event of predators isn't that much of an impact to an ecosystem, because as you've shown, the ecosystem will continue. But presumably, it's much more complicated than that.

Adam Siepielski

Oh, yeah. I mean, the experiment that we were able to do wasn't in a natural lake, or anything like that, which is, you know, inherently much more complicated. But I think this is important, because it should give us some reassurance about our understanding of how nature is working. Because, again, like we're able to take decades old work and combine it to make reasonably good predictions about how an ecosystem might respond to an event like a mass mortality event or some sort of ecological catastrophe.

Benjamin Thompson

And in previous work, you've suggested that mass die-offs are happening more frequently. How does this work fit into that do you think? In terms of our knowledge of what's causing these things or how they can be prevented, for example.

Adam Siepielski

These predator die-offs are happening because of extreme climatic events, disease outbreaks, human disturbances, that sort of thing. So I don't know that the paper can really tell us much about necessarily preventing those as much as it can tell us about the sort of signal of one of these events having happened. And it can also, I think, it informs us though that, you know, maybe reporting these events is an important thing to do. They are still, I think, relatively rare events. So even though you know, the data does suggest that they may be increasing in frequency, we may be observing them more often. I think that we can only continue to understand them better — what the causes of them are, and the effects of them are in ecological systems, if we can continue to get data and monitor these sorts of events from actually happening in nature. And I think citizens that are going out to lakes, and they observe, you know, a large number of animals dying, reporting that to their local authority would be really, really valuable. Just the document that hey, you know, this did happen.

Benjamin Thompson

That was Adam Siepielski from the University of Arkansas in the US. To read his paper about the research, which is out this week in Nature, head over to the show notes for a link.

Shamini Bundell

And finally on the show, it's time for the Briefing Chat, where we discuss a couple of articles that have been highlighted in the Nature Briefing. So Ben, tell us what you've been reading this week.

Benjamin Thompson

Well, actually, I've got a quick update on a story we covered last week on the podcast and listeners might remember me and Noah and Flora talking about NASA's problems opening the OSIRIS-REx’s containment canister, right. And they were trying to get to the samples of the Bennu asteroid that were inside. Now there was two screws that they couldn't figure out how to open. And we come up with some, frankly, terrible ideas of how they could have gone about that. And Noah asked Flora, like what's the timeframe for this? And she said, I don't know quite what's going to happen. And the answer is, it happened the day after the podcast came out–

Shamini Bundell

–oh, great–

Benjamin Thompson

–and NASA have released these two screws and announced that they've got them undone.

Shamini Bundell

Do you think it's a coincidence that you guys put forward some suggestions, and then the very next day, they actually managed to solve it?

Benjamin Thompson

I don't Shamini, let’s be honest. But back in the real world, of course–

Shamini Bundell

–ah–

Benjamin Thompson

–okay, so NASA had to design some special tools to fit into the sealed box that the container is currently in. This is quite a small thing. And they've made essentially a very fancy screwdriver, which is not really like any screwdriver that I've seen before.

Shamini Bundell

Yeah, what does it look like the fancy screwdriver?

Benjamin Thompson

It's got a lot of right angles, Shamini, I'll say that. But check out the show notes for a link where listeners can have a look at it. And I will say that all this info has come from NASA's OSIRIS REx blog. But we're not quite there yet. Okay, they managed to loosen these two screws, and there's a few more stages yet until they can get actually into the canister proper and look at the rocks and the dust inside. And I think what's going to happen is they're gonna open it up, then take a load of super high-res photos to see what they've got and then start kind of weighing it out and parcelling it out. And some of the previous stuff that was collected has already gone out to researchers. And presumably this will be eventually too.

Shamini Bundell

I presume it's gonna take more than a week, this time for us to have another update on this story while they all analyse the samples.

Benjamin Thompson

I'm hoping that tomorrow–

Shamini Bundell

–tomorrow, yes!–

Benjamin Thompson

–yeah, and then next week, we can talk about that too. But it is kind of exciting, and hats off to them for doing it. And it's hoped, of course, that these samples will tell us a huge amount about the origins of the solar system and how you know, the things we see around us came to be because some of these samples will have dated back maybe four and a half billion years, estimates suggest. But I've got another story today as well and I'm gonna keep going, which is also pretty old. Not quite that old I have to say, only 289 million years old.

Shamini Bundell

Is that all? Yeah, pretty recent, yeah.

Benjamin Thompson

I mean a snip really, let's be honest. And it's a story that I read about in Nature, and it's about a few shreds of fossilised skin that had been discovered and described in a paper in Current Biology.

Shamini Bundell

Ooh, so whose skin is it from 200 and whatever it was million years ago?

Benjamin Thompson

Well, that's a great question. And it seems to have come from a lizard-like animal known as Captorhinus aguti. But these skin fragments are only a few millimetres across, but they are the oldest skin ever found from a group of animals collectively known as amniotes. Okay, this includes reptiles and birds and mammals like me and you, basically all terrestrial vertebrates, except amphibians. And so yeah, quite a big find. And this one is the oldest by quite some distance.

Shamini Bundell

And we've definitely talked about dinosaur skin before, which is always exciting thinking about sort of what dinosaurs looked like and stuff, but this is even older than that?

Benjamin Thompson

Oh, millions of years older than that, before the rise of dinosaurs at all. And what's interesting is, in many cases, I think what researchers look at is the imprint of skin on rock, right? So we have the kind of pressing, but this is something different, this is actual skin, 3D, fossilised skin, and and it's very rare to find soft tissues, okay, because usually they decompose which is why we only ever find bones. But this is kind of one of those culmination of a bunch of different factors which has led to this discovery. So this skin was found in a cave in Oklahoma, and this cave has kind of got lots of conditions suitable for preserving soft tissues, right. And one of them in particular is that during the fossilisation process, there was oil seeping in from the walls of this cave, right? And this is brilliant line in the article over at nature.com and it's essentially that this skin was pickled in petroleum, like it's almost jet black. But it's completely infused with hydrocarbons and that's one of the reasons that it's in such good nick. And I will say it kind of looks a bit like crocodile skin, right, it's got those bumps on it as well. But because it's so well preserved, the researchers could actually look at the layers within it, which is kind of amazing right, you can see the dermis, and you can see the epidermis and these different kind of bits that are making it up.

Shamini Bundell

And is this being so ancient tell us something about the evolution of these kinds of soft tissues that we don't usually get to see.

Benjamin Thompson

Interesting one, I don't know if it gives any definitive answers. But as I said, like finding soft tissue is so rare. And the development of skin was kind of a big evolutionary step for animals moving from living in water to living on land, because of course, the skin is an amazing barrier that keeps the outside out and the inside, in. And so knowing more about when this happened, I think it's such an interesting one is such a key step in evolution of amniotes. And hopefully, they'll be more findings like this. So we can maybe get things even further back in the evolutionary timeline, because much of what we know about how the Tree of Life exists is from studying bones, because that's all that ever is preserved.

Shamini Bundell

Yeah, it sounds like it was quite a sort of unique situation with a very oily cave. So we're going to take a lot more searching to find even more of this rarely preserved, soft tissue. So that's very cool. I do like these fossil stories. I'm going to bring us back to the modern day about the future. It's a climate-change related story, I've got an it's quite an unusual one. So it's an article in Nature but it's not based on a paper, it's based on a presentation that a researcher gave at the Society for Integrative and Comparative Biology annual meeting at the beginning of January. And he's basically got quite a sort of radical proposal to deal with the massive problem of corals in the Caribbean, dying off and really, really suffering and struggling with climate change and other issues.

Benjamin Thompson

Of course, a serious problem with the oceans warming up. And I think we've covered on the show before, there's a bunch of different ways that people have been looking to maybe overcome or reverse this issue, you know, growing coral in a lab and transplanting it, dropping big blocks of concrete down for coral to grow on that sort of thing, right? I mean, presumably, if this is a radical solution, this is maybe not those.

Shamini Bundell

Yeah, in a way more radical than those. But yeah, exactly as you've said, like there's all these things that people have been trying, and people are suggesting, because it's a really urgent problem. The corals in this area have been dying off for decades, loads of them are bleached. The coral reefs themselves are really important because they protect against coastal erosion. There's obviously all the sort of young fish and the ecosystem around them. And once you've got the sort of bleaching effects, like for example, there was a massive heatwave last summer, so that had a really, really bad impact. And each time these kinds of things happen, you've got the sort of remaining bleached bit of the reefs that are more likely to erode or collapse. And then it's harder to do things like as you said, transplant new baby corals from the lab and try and plant them there. Which, by the way, it was sort of noted in this article that planting all these young native corals hasn't really worked. It's not great, hence, more radical solution being proposed or being at least introduced into the discussion. The question is, what if instead of growing these native coral species and trying to transplant them, and help them grow, what if we just give up on the native species and get in species from other reefs that are inherently hardier, tougher and might thrive in the Caribbean? So, for example, corals from the Indo Pacific.

Benjamin Thompson

I mean, that’s an interesting one, because we had a long read podcast a few weeks ago, about assisted migration, which was moving endangered species away from habitats that are under threat because of climate change, to new habitats, and kind of controversial, right? Kind of considered to be a last resort–

Shamini Bundell

–absolutely–

Benjamin Thompson

–and there were concerns about, you know, the threats that the introduced species might bring diseases or upset an ecosystem. And as we heard earlier in the podcast, these things are very finely balanced. I mean, this is kind of the opposite of that, right is taking a healthy species to an endangered habitat.

Shamini Bundell

Yeah, and you’re absolutely right, this both controversial and last resort. So one environmentalist quoted in this article describes it as “unpopular and painful”. Basically, this goes against all of the sort of principles that environmentalists, conservationists usually try and maintain, which is to protect native species and not just bring in other species from outside and the guy who proposed this, his name is Mikhail Matz, I hope I'm pronouncing that right. And there's a quote from him that says “it's an 11^th-hour solution. And it's now 11.45”. He wouldn't be suggesting this — I think is the implication there — unless, you know, we weren't in such a dire situation. And predicting dire situations into the future as well like, there are predictions that this coming summer the heatwaves in the Caribbean could be too just as bad or worse as they were last year.

Benjamin Thompson

And so as you say this was described in a talk, this isn't in a peer-reviewed journal. Is this purely theoretical? Or is this based on some experiments? What are we talking about?

Shamini Bundell

Yeah this is theoretical at this stage. And it's also, at this point, it's so against all the principles that you'd have a really hard time even trying to push anything like this through. And the sort of intention here, I think, is to actually start this conversation and say, like, look, we're not in a good state, we have to talk about this. And there are suggestions for experiments that could be done. You know you’ve mentioned some of the obvious downsides earlier, like, there could be diseases that you've introduced from one reef halfway across the world into another one. So would growing the little transplanted corals in a lab helped to reduce the disease risk. Are there sort of areas where you could do a trial of this kind of thing of introducing these hardier corals from elsewhere, in places where if they were to sort of take over and spread, they wouldn't be able to spread out to then other regions, and you know, absolutely might not work. So, the Caribbean corals are struggling with the heat and with the pollution there. And also, there are obviously diseases specific to Caribbean corals. So who knows what happens when you bring in these other corals. Will they even survive? But the tone from a lot of people quoted in this article is just one of we have to try something. So one biologist sort of talking about the things that have been tried so far, and that haven't worked, says we either do something else, or we lose the corals.

Benjamin Thompson

Hmm an interesting one, and I'm sure a lot of people have got a lot of opinions on it. So we will follow that one closely I'm sure over the next months, and potentially years. But let's leave it there for this week's Briefing Chat, Shamini. And listeners, if you want to know more about the stories we discussed, or how to get more like them delivered direct to your inbox by signing up to the Nature Briefing, look out for links in the show notes.

Shamini Bundell

And that's all for this episode then. If you want to get in touch with us, then you can. We’re on X, @NaturePodcast, or you can send us an email to podcast@nature.com.I'm Shamini Bundell.

Benjamin Thompson

And I'm Benjamin Thompson. See you next time.