Listener Questions #22

24:56So it's basically laid the egg along with some food. It's sort of like a chicken egg is the embryo with the food, but the chicken provides it instead of stealing it from a cockroach. All right. Yeah, that's exactly right. And a lot of parasitoids do this. There are parasitoids. Just the other day, I saw a parasitoid dragging a giant spider. It had paralyzed and it was dragging it to its nest so that it could then lay eggs on it and keep its meal fresh. And so what's special about this system, not from the perspective of the cockroach, of course, but is that a lot of parasitoids will paralyze food and then lay their eggs in or on it as a meal for when they hatch.

25:34But you've got this extra layer where the parasitoid is also able to direct the cockroach to go to a particular location rather than needing to physically drag it there, which a bunch of others have to do. Wow, amazing. Yes, amazing. So the cockroach participates in its own demise. It does. It does. It's complicit. That's gross. Complicit. I don't know. That word has too much human baggage. It unwillingly, unwittingly does the wasp's bidding. Okay, so Marco was interested in the fact that when that second sting happens, and the sting is happening in the brain, the wasp that is stinging the brain, its mom isn't there to teach it how to do that.

26:16So how does it just know where to sting in a brain? And at the end of the day, the answer is going to be, we don't really know. But I'm going to give you a little bit more detail about what is actually happening when it stings the brain. So we talked about how it puts its little like hypodermic needle-esque butt into the neck of the wasp and it starts going up to the brain. And there have been some experiments trying to figure out what happens inside the cockroach's brain. So one thing they did was they injected carbon-14 radiolabeled amino acids into the stinger, and then they looked to see where it ended up in the cockroach.

26:53And it does end up in this area called the subesophageal ganglion, so it's like kind of the bottom part of a cockroach's brain. So injecting carbon-14 labeled amino acids, this is just a way of tracing like where something goes. It's like add like a little dye so you can see where something goes. But in this case, it's not a visual dye. It's like you're measuring the radioactive decays or how does that work? Yeah, that's exactly right. Fascinating. Yeah, yeah. Pretty cool experiment. Okay. And then they did some other experiments to try to figure out what it is that the WASP is cueing in on to figure out where it's supposed to deposit what we call it.

27:29the stuff that gets deposited during the sting, venom, which is awesome. Anyway, so they've done things like humanely euthanize a cockroach and then remove its brain and then give it back to the wasp. And when you do that, the wasp spends a bunch of time, like, searching and not delivering its venom. It's like, what? Something is missing in here. And so it's like, it's definitely... It's looking for the brain. It's looking for the brain, and it gets kind of confused when it's not there. And so then the scientists looked a little bit closer at the ovipositor and they found sensors on there. And some of the sensors are mechanical receptors so they like can touch things.

28:05And some are chemical receptors. And so first they wanted to dive into what happens with the mechanical receptors. And so they took all the mechanical receptors off of the wasp and the wasp just kind of like searched around for a really long time. It was super confused because it couldn't feel anything. Then they humanely euthanized the cockroaches and they put a very soft substance that wasn't very brain-like into the head of the cockroach. And the wasp also searched around for a really long time and was like, what is going on? But then they put a hard substance, harder substance, that's more like the brain.

28:39And the wasp responded more quickly. So it doesn't have to be a brain, but it's got to feel right. So they're testing what the wasp wants to sting. And they're like, how about a squishy brain? How about an actual brain? How about something that feels like a brain? They're like exploring the space of what the wasp is willing to engage with. That's fascinating. Yeah, yeah. And if you like kind of mix up the brain and kind of change its consistency by like mixing it up with like scissors or something, they also are confused and are like, what the heck is going on here? So it looks like the mechanical stuff really matters.

29:14And so that suggests to me that there's some genetic coding that gets passed from generation to generation, doesn't need to be learned, where they know, like, it goes in the neck and then you look for something that feels a certain way. And I don't think we've looked close enough in this system to understand exactly how that happens. But we have looked at other behaviors that are, you know, what we would say is innate. They just happen without learning. So it's so important that it touches the brain that the system has evolved requirements to ensure that it only happens when there's like an actual brain there to be delivered on, not just like randomly spraying this stuff in the head of the cockroach.

29:51Yeah. So presumably the chemical cocktail that gets delivered into the brain is expensive to make in some way, like requires a lot of energy or certain nutrients or something. so you don't want to go stinging things and wasting it and so if this cockroach seems like it's totally off for some reason then you you abandon it well go go find a cockroach with a bigger tastier brain that's right what well there are other parasitoids that can test and see like are there already parasitoid wasps living inside of this insect because i don't want my babies to have to compete with babies that had a head start and so there's all sorts of like crazy stuff that happens when the wasp is like evaluating its host for quality.

30:32All right. So this is really fascinating and very complex behavior. And I feel like Marco's question is essentially, how does the wasp evolve this kind of behavior? The mom is not there to teach it, which means it must be somehow innate, which suggests it's like in the code of the DNA, which means it comes from evolution, not from like the wasp culture. How is such a complex process ever evolved? It feels impossible to imagine that you develop such an intricate system because it needs many parts to work all at once. Well, maybe your imagination is limited, Daniel. No, I'm just kidding. Yes, it is very complicated.

31:07So one of the ways that we look at the evolution of complex behaviors is that we'll look at things that closely related species are doing. And sometimes you can see the steps that build in a more complicated behavior. So, for example, this system has two stings, and one of them is a little bit more complicated. But a lot of other parasitoids, as we've already talked about, do one sting to paralyze their prey. So you can see that as like a beneficial early step. We have not, in this system, been able to work out the order in which all of these complicated things evolved and sort of built up. And so let me just make it explicit.

31:44You're suggesting that it's a complex series of behaviors, but there probably are simpler versions of it that are also beneficial. You don't need all the complex pieces in order to gain some benefit. And that would allow you to tell the evolutionary story. Is that the argument? Yep, that's exactly right. And every intermediate step needs to be beneficial in order for it to keep passing through the population, unless you've got drift going on. But anyway, okay, so there are beneficial steps. And you can imagine something like initially the jewel wasps only stung the cockroach once and paralyzed it, and then you had to drag it.

32:18But then there was one wasp that had some mutation that made it extra stabby, and it stabbed once in the thorax and once in the brain. And that did something that made the cockroach a little bit easier to handle, which meant the mom could lay more eggs and could do this more times. And maybe that got passed on genetically. And you can imagine generation after generation that gets honed and more and more beneficial. And maybe my imagination is limited, but does the phrase extra stabby appear in the biological literature anywhere? No, that's just because I'm super creative. You know, that was my creativity.

32:54I'm just kidding. You're very creative. But yeah, so we don't know exactly the path that this took, but you can imagine how it would have built up. And then, you know, it's possible somebody could test this by looking at closely related wasp species. And maybe if you understood more mechanistically about how this was all happening, you could understand how one step could happen after another. But for this system, I would say we don't have a really good evolutionary answer. I think that all makes sense, that complex behaviors evolve from simpler behaviors that are also beneficial. And it sometimes takes a while to figure out what path you can take from simpler to more complex.

33:27I think the thing that blows my mind is that these complex behaviors feel kind of fragile. Like everything has to work for this to happen. And it feels like there's so many ways for it to go wrong. It's incredible that it relies on such a complex system. And then it mostly works. And then I look at, you know, like humans. I've raised a child. It's complicated. It feels like there's so many ways it can go wrong. And then I walk around, I'm like, wow, all of these humans, they were raised by people. It seems to mostly work. It's incredible. Yeah. You know, biology seems so fragile, but it is pretty robust.

34:01Yeah. I mean, it is incredible. But, you know, there's plenty of times when jewel wasps go after cockroaches in nature and the cockroach wins and the jewel wasp doesn't get to sting. Yay, cockroach. Yay, cockroach. Or, you know, the jewel wasp dies for one reason or another. It just doesn't. Like, there's plenty of times in nature where these things do fail. and those individuals usually just get wiped out of the population. And just so it doesn't sound like I'm saying, well, whenever we're talking about complex behaviors, we always just imagine a picture. There are systems where step by step, we've sort of figured this stuff out and I'm working on finding a behavioral geneticist to come on the show to talk to us about those answers.

34:38So stay tuned. All right. Well, I think that's a pretty good answer for Marco. Let's inject that into his head and see how his brain responds. Did we lead you to the answer, Marco? I promise we won't lay any eggs on you. After hearing your answer, I admit I'm no less terrified of jewel wasps. I can only hope I don't have another fever dream frantically trying to keep one from stinging the back of my head by jumping into water I can't find. I'm forever in awe of evolution coming down to random events and mind-boggling numbers until some advantage emerges and gets successfully encoded. I keep going back to a couple points you made.

35:15One is that without passing down knowledge, genetic coding instructs an organism's behavior. The wasps are compelled to behave as they do, and evolution handles the rest. As with most of the podcast episodes, we end up with more questions like, how did Kelly end up on Team Jewel Wasp? I can't side with that freak show. I fully support Wally's cute sidekick, not the Jewel Wasps. That feels like siding with monstrous killers, or the 17 % of people that prefer white chocolate. not tolerate it, but like it better. It truly is an extraordinary universe. Thanks, Daniel and Kelly.

36:11Next up, we have a question from Southern Scotland, and I am so excited because I got to go to Scotland for the first time last month. I was in Edinburgh, which is probably not where Ben is from. But Ben, your country is beautiful. I loved it. And vegetarian haggis, A+. And I'm going to Scotland next week for a wedding in Inverness. Yeah, and you're going to wear a kilt. I'm going to wear a kilt, exactly. All right. But today, the question is not about Daniel's wardrobe at Scottish weddings. It's about what these terms and tines mean. So let's hear Ben's question. Hello, Daniel and Kelly. It's Ben here from Kukubri in Southern Scotland.

36:47I'd really like to know what you think is the difference, if any, between a theory, a law, a hypothesis and a model. I'm especially curious about Darwin's theory of the origin of species. Is this a typical scientific theory? Does it have predictive power? Can it be refuted by experiment? I feel I really need the combined advice of a particle physicist and a parasitologist to help to settle these questions. I really enjoy your podcast. Oh, this is a really great question. This is a really fun question. I'm really glad that Ben asked it because it's one of these questions where if you ask philosophers or if you ask scientists, you'll get a different answer.

37:29And if you ask different philosophers and different scientists, you'll get lots of different answers. It's something a lot of people are not very precise about, frankly. Yeah, I think when I was an undergrad, I remember in my biology class, there were definitions of all of these terms. And then I was very confused later on when they were used in ways that were not at all consistent with what was in that textbook. And anyway, now I know we're all sloppy. well you know scientists are practitioners we're not experts in the philosophy of science we go out there and we do science and we say theory we say law we say model we haven't all taken philosophy classes where like the distinctions between these things are argued by nerds who are super excited about it you know we're excited about the biology or the chemistry or the physics or that kind of stuff and so when you hear scientists talk about it they're not often being very precise because they're not experts in the definitions of these terms.

38:21Philosophers of science are the folks who really narrow down on this. But again, also philosophers of science disagree reasonably with each other about how to describe this stuff. So I'll break it down for you in a way that makes sense to me, but definitely other people will have different definitions of this. This is not definitive in any sense. And if I could just mention that, I also think another thing that makes it complicated isn't just that most of us don't actually know what these terms mean. is that even if we did, when you understand something, it's not usually like there's a clear switch that gets flipped where you're like, oh, now we've entered law lands.

38:54Before we were in hypothesis land. It's like you need to slowly accumulate and it's not always clear when it's time to update to a new term. And so anyway, that probably complicates things too. Yeah, yeah, absolutely. So let's start with laws. I think of a law as something the universe actually does. There's some truth out there. And one of the basic assumptions in science is that the universe follows laws and we don't know them, but we can do experiments and think about it and all those sorts of stuff to try to figure them out. So we think the universe follows some sort of concise, simple, fundamental rules.

39:30And those are the laws of the universe. All right. Still with me. Yep. Cool. Now, we don't know what those things are, but we can have theories about it. So we went from law to theory. Theories are like our explanations for how the universe works. So general relativity, for example, is a theory about how matter bends space and how space tells matter to move. Quantum mechanics is a theory that tells us that space is filled with oscillating fields. These are theories. They're like our explanatory frameworks to describe the things that we see in the universe. And we hope that those theories line up with the truth, the laws that are actually out there in the universe.

40:11And so theories, it's kind of a fuzzy term, right? Theories are sort of like our ideas. They include a bunch of evidence and they come together to give like some sort of coherent explanation for how something is working in the universe. A theory is not just like a random guess, not just like, hmm, maybe it's this, right? Like a fan theory to explain the ending of some movie you just saw, right? It's something that's really based in evidence and has been tested and it's sort of part of our explanation of the universe. Yeah. Lots of different labs have looked at it. It's been looked at from lots of different angles.

40:46Predictions have been tested. Yeah. Agreed. Yeah. So the whole like, you know, gravity is just a theory, man, doesn't mean that like we don't know anything about gravity or it's just like one of 10 options to explain why we stick to the surface of the Earth. Right. A theory can be something that's very well developed and understood. I don't know. Was gravity really the best pick there? Seems like there's a lot we don't know about gravity. There is a lot we don't know about gravity. That's the other thing about a theory is that they're never complete, right? They're evolving. They're changing. Gravity is a wonderful, amazing theory, but there's definitely a lot we don't know about what's going on at the center of black holes or the early universe or fundamentally how gravity works for particles, right?

41:27Definitely, it's not a complete explanation of the universe. It's an explanation of part of the universe. And we don't have a unified theory. We'd love to have one because we think there is one set of laws, but we have sort of piecemeal theories that we think are approximating those laws. Excellent. I'm glad we have a scientist slash philosopher on the show. So there are laws out there. We try to build theories about how the universe works and follow those laws. What's a model in that sense? And model is a very overloaded term. In physics, we use model to mean sort of a simplified version of a theory because theories are complicated.

42:04Like if you wanted to calculate the orbit of the Earth around the sun, you couldn't use general relativity. Nobody knows how to do that calculation. General relativity, really, really nasty. The only times we've ever been able to solve problems with general relativity are in simplified settings like an empty universe, a universe with just a black hole in it, a universe filled with uniform dust. None of those correspond to our reality. Our reality is too complicated to solve with the full theory. And so we build a model. We can simplify the universe. We can say, like, let's assume the universe is empty except for the Earth and the sun.

42:40Now let's do the calculation. And we hope that the calculation is still relevant to the real universe, right? We find a simpler version, something we actually can crank on, and hope that the answer is still relevant. or we can simplify the calculations. We can say, well, let's use an approximate version of the theory. You know, Einstein's equations for general relativity, if things are far apart and masses are not too high and they're slow moving, they reduce to Newton's theory. And so you can use Newton's theory for most stuff. You want to calculate whether your cannonball is going to fly over the castle walls.

43:15You don't need to use general relativity. You're going to get basically the right answer using a simpler model, right? a model of general relativity, which is just Newton's equations. And so, you know, spherical cows are a fun joke because that's the kind of thing physicists do. We're like, well, let's replace a complex situation with a simpler situation where the answer is basically the same. And so a model is a simplification. Either you've simplified the universe or you've simplified the theory so that you can get some answers out. Yeah. And models are great. They help you decide if, you know, your simplification, when you do a simplification, you're making assumptions that some things don't matter that much.

43:50And so then when your model gives you an answer and you test it, you can see, oh, was I right that that thing doesn't matter that much? And ideally, it's an iterative process. The model gives you a prediction you can test. You actually go out and you test it, and then you update your model as needed. That's right. And it's important to understand that every calculation anybody has ever done uses models, uses simplifications. All of physics uses approximations. If you want to calculate how the Earth goes around the sun, in principle, you need to include the gravitational tug from every single object out there in the universe, which is pulling on the earth.

44:23Most of those are negligible. And some rock out there in Andromeda is really not going to change the path of the earth in a way we can measure. But in principle, it does. So we always do approximations. It's impossible to ever do full calculations in any of our theories for any situations. So all of science is approximate to some degree. And that's where a lot of science happens is figuring out how to be clever about it. What approximations can I make so the answer is still useful and relevant, right? And I can get this done in a PhD length of time and not be here for 10 ,000 years. That can often be a very painstaking part of the process though.

44:59Like, what are my parameter estimates that are reasonable and useful? And that can be a lot of work. That's right. And so that's what a model is. And let me say that model is used very differently in different fields. Like I talk to computer scientists and machine learning people. For them, a model is like a trained network. They talk about neural networks as my model or their boosted decision tree is a model. They use model to mean something very different than physicists do. And I know biologists talk about like model systems. They're studying the brain. They're doing it in mice or they're doing it in rats or they're doing it in flies.

45:30To them, that's the meaning of model, like which model system are you using? But when someone says to you, you know, what do you do? And you say, oh, I do modeling. They know that that means that you are using equations to try to capture the dynamics of a system and are making predictions that way. So we, I think we use the word model in a couple of different ways. Um, one of which is model systems. Yeah. And I think that fits in because like you're using the mouse as a model system to understand Alzheimer's because you can't, and you shouldn't do experiments on humans. And so use the mouse brain as a stand-in as an approximation for the human brain, because you know, it's not okay to do the things to humans that you do to mice.

46:08And maybe it's not okay to do to mice either, but it's maybe more okay. I think it's the argument biologists make. Yeah. Yes. Depends on who you're talking to, but I guess I'd prefer it happened on mice. Yeah. All right. And so the last term was hypothesis. We test our model by generating hypotheses. We're saying, here's my model of the universe. I think that this interstellar comet is made of ice and CO2. Let me generate a hypothesis about what James Webb Space Telescope will see when we point it at it. And then I can compare that hypothesis to what we actually see. So the model predicts something, that's our hypothesis, and then we compare it to reality in order to learn whether the model is correct or not.

46:46Yep. Cool. So we have laws, theories, models, and hypotheses. And the last bit of Ben's question was a sort of loaded question about Darwin's theory. I hear a lot of this discussion online about how evolution is just a theory, man. And because it all happened in the past, it's not really predicting anything, is just descriptive, and therefore it's unfalsifiable and not really scientifically valid. And I wonder if these critiques are really done in good faith. These are folks attacking evolution, trying to use the language of science to undermine it, but I don't think they really believe in the scientific process personally.

47:19Yeah, agreed. So let's talk about it. Darwin's theory is definitely a theory. I mean, it provides an explanation for how speciation happens, right? There's lots of evidence out there that it's pull together, it definitely qualifies as a theory. And in that sense, it's not just like some dude's random guess, right? It's a well-established explanation for a huge variety of stuff that we see out there. What do you think? Yes. So for 150 years, we've been trying to decide if evolution through natural selection is supported by the data. And, you know, there's probably evolutionary biologists in every department that does research around the world.

47:56And we have found results that make us think about evolution through natural selection in a different way. But in 150 years, none of us have come up with a result that's like, oh, definitely we dropped this theory. So we've got 150 years of researching, coming up with predictions based on this theory that are supported by future work. So yeah, I agree with you. Yeah. And Ben asks, like, is this a predictive theory? And I think the answer is absolutely. You know, it predicts lots of things about what you should find out there in the world. You should find fossils. You should find simpler behaviors leading to more complex behaviors.

48:29You should see real-time evolution, you know, when communities respond to changing circumstances. You should see a connection between the species that we observe and the genetic information that leads to them. This is, I think, a really powerful confirmation of natural selection is finding the sort of mechanism, the DNA, the biochemistry that underlies all of this and seeing confirmed the history of that evolution in the DNA. I think it's super fascinating. You know, we can learn things about like when communities diverged by seeing the differences in their DNA. Yep, yep. Yep. And, you know, Darwin is clearly like the best scientist of all time.

49:07Sorry, Daniel. And so if you could be the scientist who finds the data that refutes this theory, you could replace the name Darwin. Yeah. Right. And so there's no... Mainstream narrative the biologists are trying to protect. Yeah, that's right. That's right. No, every scientist out there wants to overthrow the mainstream narrative because that's how you become a famous scientist. And also, that's what we all want to do. We want to learn the truth about the universe. We're driven by our curiosity to reveal the truth, not to support some sort of dogma. But you raise, I think, the last, maybe the most important point is the question about whether this could be refuted.

49:46So can you, Kelly, imagine some evidence that hypothetically would undercut this theory of evolution? At this point, we have so much evidence. It's kind of hard to imagine something we could have missed. and like one piece of information that would refute everything. So I think at this point, if you had a finding that like, you know, multicellular life existed before we found unicellular life, like it just popped into existence or something, we would have to look really hard at like, have we collected all the data and all the different places? Like, because there's this mountain of evidence and you've got this one thing that maybe doesn't fit.

50:21But I do think that if there were evidence out there, scientists would be open to considering it and looking at it and trying to understand if that makes us wrong or if it's just a like shady corner in the room of evolution that we haven't explored yet. And we just need to move into that into that area instead. Yeah. And I think the question is reasonable. Like we expect theories to do more than just describe the data we've seen. We want them to generalize if they really are coming close to the truth, the laws of the actual universe, they should be able to predict things we haven't seen. And Ben's question is like, well, hasn't all this stuff happened in the past?

50:57Yeah, a lot of the stuff has happened in the past, but we haven't seen it yet. And so we can predict like, I predict what I'm going to find when I dig into the ground. Yeah, the stuff is already there and the events already occurred, but if we haven't seen it yet, then it's fair to predict it and to treat that as a test of the theory. Yep. Agreed. All right. So Ben, let us know if we answered your question about the definition of these terms and their application to Darwin's theory of the origin of the species. Well, Daniel and Kelly, even though the classification of groups of ideas is obviously a complicated topic, I just knew that you would come up with some clear insights.

51:31Thank you very much. And it's good to hear that Darwin's amazing theories are currently being used by scientists to help both explain and predict many phenomena. I wish you all the best for your trip to Inverness, Daniel, and I hope the weather matches that in Southern California so you can stay comfortable wearing that kilt. All right, well, that was a ton of fun. As always, I learned a ton. Hopefully the listeners learned a ton too. Please remember you can write us at questions at danielandkelly.org. You can join us on our Discord channel. You can find us on Twitter and Instagram and Blue Sky.

52:04Reach out to us, please. And let curiosity drive you through your day.

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