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Speaker 1: When I was a kid, I was absolutely obsessed with

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Speaker 1: Jurassic Park. It wasn't just because of the dreamy Ian Malcolm,

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Speaker 1: but mostly was because I desperately wanted to be a paleontologist.

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Speaker 1: The idea of bringing long extinct animals back to life

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Speaker 1: through the magic of biology was absolutely infraling to me,

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Speaker 1: and I went to the cheap theater to watch Jurassic

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Speaker 1: Park on the big screen as often as my mom

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Speaker 1: was willing to take me. The scene where the t

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Speaker 1: Rex is chasing the jeep carrying the injured Ian Malcolm

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Speaker 1: to safety is burned into my memory. But even as

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Speaker 1: a kid, I remember watching that scene and wondering to myself,

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Speaker 1: could an animal that big really go that fast? If so,

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Speaker 1: why is the huge Brontosaurus not similarly swift. This is

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Speaker 1: a difficult question to answer, After all, how do you

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Speaker 1: even go about figuring out how an extinct animal moved

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Speaker 1: around to be videotaped anymore? And the muscles that hold

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Speaker 1: keys to answering questions like these have long since decayed away. Well.

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Speaker 1: On today's show, we're talking to doctor John Hutchinson, who

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Speaker 1: studies the movement of long dead animals. While answering amazing

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Speaker 1: questions like can hippos get airborne? And how do elephants run?

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Speaker 1: This is the perfect topic for Daniel and Kelly's Extraordinary

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Speaker 1: Universe because it's the happy intersection of biology and physics.

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Speaker 1: Welcome to Daniel and Kelly's Extraordinarily fast Moving Universe.

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Speaker 2: Hi. I'm Daniel. I'm a particle physicist, and I've always

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Speaker 2: considered myself a large animal.

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Speaker 3: Hi.

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Speaker 1: I'm Kelly Wiener Smith. I'm a biologist and I sort

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Speaker 1: of fluctuate between being a large and a larger animal.

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Speaker 1: It depends on how close we are to the holidays.

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Speaker 1: But I always feel great about myself, so it's all good.

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Speaker 2: And so, Kelly, what do you think is your top

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Speaker 2: land speed or what could Kelly outrun? Let's put it

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Speaker 2: that way.

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Speaker 1: I've definitely outrun some turtles on the property.

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Speaker 2: And that's good. Let's start there.

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Speaker 1: There are some fast frogs on the properties, so maybe

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Speaker 1: somewhere in between those things.

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Speaker 2: Wow, are you telling me a swarm of frogs could

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Speaker 2: take you down?

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Speaker 3: Oh?

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Speaker 1: I mean they could catch up to me, but they're

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Speaker 1: pretty tiny, you know. I think I could give them

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Speaker 1: a couple good swift kicks. I have taken some taekwondo,

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Speaker 1: so maybe I can give them a couple of chops.

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Speaker 2: All right, so all frog listeners be warned. Kelly can

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Speaker 2: defend herself. Yeah, I'm not a very fast person. I

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Speaker 2: could not outrun a cat or a dog or even

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Speaker 2: a rat. I've chased a rat around our garage and

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Speaker 2: lost that race rather surprisingly fast. But to my credit,

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Speaker 2: I do have offspring surprisingly fast. My son is a runner,

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Speaker 2: and he runs a mile and shockingly four minutes and

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Speaker 2: twenty seconds or something, and so I think I want

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Speaker 2: to take some credit for that, even though it's probably

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Speaker 2: more likely to be cosmic ray mutation or transcription errors

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Speaker 2: or something that led to that.

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Speaker 1: You're one of those parents whose children's accomplishments are your accomplishments.

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Speaker 2: Absolutely, while I's have kids, I put his times on

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Speaker 2: my CV for sure.

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Speaker 1: Does that help? What's funding? I can't imagine it would.

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Speaker 2: It doesn't. No, it's wonderful to see your kids grow

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Speaker 2: up and just have different skills and interest than you do.

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Speaker 2: It's fantastic and also surprising sometimes.

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Speaker 1: Yes, No, my son has amazing abs, Like you can

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Speaker 1: put him in any position and he can sort of

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Speaker 1: lift himself up with his core and it's crazy. And

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Speaker 1: my daughter's starting her first math competition. Both of those

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Speaker 1: things are My kids are amazing, and I had something

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Speaker 1: to do with it, But I don't know how much

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Speaker 1: credit I get for either of those things.

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Speaker 2: Our biology is complicated, right.

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Speaker 1: They tell yep, yep, it's true. And you know another

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Speaker 1: thing that's complicated is how do you portray biology in

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Speaker 1: movies and TV shows, especially when you're really pushing the

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Speaker 1: boundaries of the biology. And we have a really great

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Speaker 1: question about that today from a listener. Let's go ahead

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Speaker 1: and hear it.

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Speaker 4: Hi, there, Daniel and Kelly. It's been from Melbourne in

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Speaker 4: Australia here, and I've got a question about large creatures,

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Speaker 4: including giant people, and how they move. So I've noticed

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Speaker 4: in a lot of movies and TV shows when something

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Speaker 4: giant is depicted, like giant ant Man in the Marvel movies,

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Speaker 4: they're often depicted as moving really slow, kind of like

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Speaker 4: in slow motion. But then in other media we've got

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Speaker 4: giant things like the Ava units in the Evangelian anime,

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Speaker 4: which move really really fast. And it got me wondering,

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Speaker 4: is there any physics reason or any biol raisin why

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Speaker 4: one of those depictions is accurate as opposed to the

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Speaker 4: other or does it depend on the particular case. Really

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Speaker 4: enjoy the podcast and really looking forward to what you

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Speaker 4: might have to say.

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Speaker 1: So this is an amazing question. And I was so

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Speaker 1: excited when I got this question because I had somewhat

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Speaker 1: recently met a professor who studies very large animals, and

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Speaker 1: we were in a meeting with a bunch of other

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Speaker 1: people and there were things going on, and I didn't

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Speaker 1: get a chance to ask him all the questions that

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Speaker 1: I wanted to ask him about his research. So I

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Speaker 1: was so excited to have an excuse to invite him

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Speaker 1: on the show. And so today we have doctor John

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Speaker 1: Hutchinson on the show to tell us all about how

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Speaker 1: very large animals move and.

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Speaker 2: What a giraffe burger taste like hmmm.

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Speaker 1: Doctor John Hutchinson is a professor of evolutionary biomechanics and

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Speaker 1: a Fellow of the Royal Society. His research straddles the

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Speaker 1: fields of evolutionary biology and biomechanics, with an emphasis on

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Speaker 1: how very large animals stand and move, and how locomotion

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Speaker 1: evolved in different groups of land vertebrates. Welcome to the show, John,

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Speaker 1: Thank you very much.

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Speaker 2: Kelly, Kelly in your introduction, you neglected to mention that

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Speaker 2: John also has an incredible array of heads on the

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Speaker 2: wall behind him.

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Speaker 1: Well, I didn't know that when I wrote the intro.

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Speaker 2: What's going on there?

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Speaker 3: Yeah, that's my mask and collection. Oh cool, which got

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Speaker 3: particularly ironic early in the COVID pandemic, But it only

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Speaker 3: encouraged my collection of masks.

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Speaker 2: So for those of you just listening, we see octopus

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Speaker 2: and what else is going on with giraffe?

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Speaker 1: Thulu Giraffe? Are these all from places that you visited?

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Speaker 3: Just random places, often just gifts from people, or I

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Speaker 3: find them like at a arts sale kind of thing

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Speaker 3: or whatever.

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Speaker 2: I don't know why you don't just wear them when

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Speaker 2: you jump onto a zoom call. That'd be very dramatic.

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Speaker 3: Some of them.

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Speaker 1: All right, Well, let's pull back and talk about what

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Speaker 1: got you into in studying the movement of very large animals.

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Speaker 3: It really goes back I think to being a high

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Speaker 3: school student in a physics class, and I remember my

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Speaker 3: teacher had like a bulletin board with some news articles

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Speaker 3: or something on it. That's the way I remember it.

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Speaker 3: And one of them explained why King Kong and Godzilla

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Speaker 3: were physical impossibilities because they were just too big to

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Speaker 3: support their own weight. And I was a big, big

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Speaker 3: monster movie fan, just way too early for my years,

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Speaker 3: really into Kaiju type movies. And that was really interesting

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Speaker 3: to me because it made me grapple with my growing

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Speaker 3: interest in science and my longstanding interest in the arts

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Speaker 3: and fiction. So I had to think about, Oh, wow,

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Speaker 3: that actually really makes sense, but too bad.

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Speaker 1: And you were like, one day, I'm going to crush

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Speaker 1: dreams just like the author of that article.

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Speaker 2: Yes, walk us to the argument, why does physics say

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Speaker 2: that biology can't get too big?

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Speaker 3: The simplest explanation is what they call the square cube law. Well,

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Speaker 3: there's various terms for it. But as animals get bigger,

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Speaker 3: their wet mass or their weight goes up by a

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Speaker 3: linear dimension cubed. So you have a length, a width,

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Speaker 3: and a height. That's your mass, your volume so forth,

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Speaker 3: so that increases with your size. Overall, mass is a

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Speaker 3: metric of size more or less. But as your mass increases,

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Speaker 3: your area your linear dimensions squared, So cross sexual area

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Speaker 3: only goes up proportionately by the linear dimension squared, so

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Speaker 3: very quickly, the amount of weight you support on a

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Speaker 3: given area gets higher and higher and higher, unless you

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Speaker 3: do something to change your mechanics of movement.

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Speaker 2: So let me interpret that. Assume, for example, we have

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Speaker 2: a spherical godzilla, right, solways like to assume spherical monsters.

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Speaker 2: Then you're saying the volume of that sphere goes with

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Speaker 2: the radius cubed right, it's like four thirds pi r cube.

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Speaker 2: But the surface area of the sphere is four pi

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Speaker 2: r squared. And so when you double the radius, the

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Speaker 2: volume goes up by eight, but the surface area only

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Speaker 2: goes up by four. And as that continues, as the

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Speaker 2: radius goes up and up and up, and you get

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Speaker 2: to actual gun zilla sizes, the ratio gets larger and

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Speaker 2: larger a volume to surface area. But why is that

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Speaker 2: a problem, Like why is it a big issue to

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Speaker 2: have a lot of wet mass inside your surface area?

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Speaker 3: Because of biology? Because animals are made of the same

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Speaker 3: stuff that has intrinsically the same mechanical properties, the same strength. Fundamentally,

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Speaker 3: that's the most important thing. See the amount of forest

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Speaker 3: per unit area a bone or a muscle can support

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Speaker 3: is fairly constant. A vertebrates that move on land in particular,

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Speaker 3: because this is all operating under gravity. Is assumption if

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Speaker 3: once animals get into the water, all bets are off.

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Speaker 3: It's effectively zero gravity more or less. So then this

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Speaker 3: square cube law is not such a concern. On land,

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Speaker 3: the strength of tissue becomes fundamental.

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Speaker 1: Is the limiting factor there mostly bone or mostly muscle,

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Speaker 1: or it has to be both. What limits what an

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Speaker 1: animal can hold?

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Speaker 3: I think this is still a big question in science

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Speaker 3: that you would think it might be bone because bones

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Speaker 3: are there to support body weight against gravity. But bones

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Speaker 3: form joints that muscles act around to support animals. So

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Speaker 3: there's the living component, the contractile component of support, which

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Speaker 3: is muscle, But then there's all the other passive stuff bone,

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Speaker 3: ligaments and cartilage and so forth. It also provides support.

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Speaker 3: And what we don't really understand yet is how much

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Speaker 3: of a role each of those things plays and how

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Speaker 3: that balance changes as animals get bigger. One thing we

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Speaker 3: do know is that as animals get bigger land animals,

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Speaker 3: I should specify land vertebrates, As they get bigger, they

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Speaker 3: tend to straighten their legs, so that shifts their mechanics

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Speaker 3: of support to using their legs more and more and

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Speaker 3: more like pillars, which transmits more of the force down

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Speaker 3: the long axis of the bone. So like when we stand,

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Speaker 3: we're using our legs like pillars. More or less. We're

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Speaker 3: quite unusual actually for animals of our size, and the

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Speaker 3: way we do that, it's very efficient, providing a lot

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Speaker 3: of passive support. So mostly the bones are providing allow

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Speaker 3: of support once you get to a very very pillar

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Speaker 3: like posture, whereas intermediate postures with more bending of the

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Speaker 3: limbs would involve presumably more muscle activity. But you know,

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Speaker 3: this is hard to figure out because there are so

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Speaker 3: many components acting around each joint in any real organism.

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Speaker 3: It's a really difficult mathematical problem.

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Speaker 2: So my takeaway is that it's not necessarily impossible to

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Speaker 2: have any given size of animal, but that the task

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Speaker 2: of the animal, the sort of biological engineering needed changes

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Speaker 2: as the animal gets bigger or smaller. Because of these

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Speaker 2: different ratios and the strategies that we have, are vertebrates

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Speaker 2: on Earth might not scale to like really big godzillas.

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Speaker 2: But does that mean, for example, you couldn't have a

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Speaker 2: fundamentally different biology, you know, some crazy hollow thing or

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Speaker 2: different kind of biological engineering or no joints or I

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Speaker 2: don't know, something you know really out of this world

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Speaker 2: that could allow for much much larger animals.

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Speaker 3: That is a great question, like in terms of like

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Speaker 3: other worlds or such. Certainly we don't know what tissue

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Speaker 3: could achieve. We only know what's there.

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Speaker 1: So Daniel was asking, are there different ways to get bigger?

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Speaker 1: Like can you hollow out your inside or something you

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Speaker 1: mentioned in water is effectively zero gravity. Does that mean

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Speaker 1: that blue whales, like we could have something a hundred

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Speaker 1: times bigger than that, or does something else limit size

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Speaker 1: in the ocean?

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Speaker 3: This is another big question. We don't understand. We don't

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Speaker 3: understand what the upper limit of size is on land

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Speaker 3: or in water or anything. We only know what we see.

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Speaker 3: And the largest animal ever so far is the blue whale.

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Speaker 3: There are some fossils that kind of seem to maybe

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Speaker 3: come close to that in size, but blue whales are

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Speaker 3: the biggest. But it doesn't mean that animals can't get

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Speaker 3: any bigger than that. It's just that that's what evolution

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Speaker 3: has produced. And certainly there are other mitigating factors like physiology,

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Speaker 3: cardiovascular issues, breathing, ecology. So food is a huge constraint

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Speaker 3: on body size. If you don't have enough food around,

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Speaker 3: if you're in an unstable environment where food resources are crashing,

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Speaker 3: all the time, like in the face of environmental change.

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Speaker 3: Then being big is a very terrible biological strategy, so

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Speaker 3: to speak. So large body size has many limits, not

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Speaker 3: only the only the physical. There is a whole different

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Speaker 3: body plan out there that we can look to in

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Speaker 3: nature to ask questions about mechanics of size and support,

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Speaker 3: and that's arthropods. What's really interesting is that even in

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Speaker 3: the most extreme cases in the fossil record, we see

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Speaker 3: no gigantic arthropods.

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Speaker 2: Remind me, what's an arthropod.

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Speaker 3: Animals with exoskeletons, So insects, crabs, crustaceans, spiders, and so forth,

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Speaker 3: things with their skeleton on their outside.

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Speaker 2: So no lobsters the size of blue whale so far.

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Speaker 3: Yeah. Yeah. So they keep their muscles on the inside,

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Speaker 3: which constrains how big their muscles can be because they've

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Speaker 3: got to have not only all their muscle on the inside,

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Speaker 3: but all the other stuff. They're a circulatory system, so

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Speaker 3: on and so forth, so that constrains them to a

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Speaker 3: certain degree. But also other factors like their circulatory system,

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Speaker 3: constrain their size. So they are weirdos. But also arthropods

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Speaker 3: are weirdos because their muscles break all the rule of

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Speaker 3: what muscles can do. I talked about vertebrate muscle having

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Speaker 3: pretty much the same properties across any size of vertebrate,

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Speaker 3: but insect muscles have tremendous variation in what kind of

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Speaker 3: properties they can have, but they still could not enable

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Speaker 3: like a fifty ton ant.

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Speaker 1: Oh there was a movie when I was a kid

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Speaker 1: that had a giant ant after a new bar more

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Speaker 1: and yeah them, Oh, oh, you've crushed my dreams. I

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Speaker 1: was really hoping that that would be a silver lining.

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Speaker 3: I think I specifically chose that to crush your dash man.

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Speaker 1: Well, good job, good job.

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Speaker 2: Spot on a little taste of your own medicine there, Kelly.

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Speaker 1: Oh ouch, could you tell us a little bit more

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Speaker 1: about the different kinds of insect muscles how do they

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Speaker 1: break the rules? Or arthropod muscles?

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Speaker 3: Okay, this is getting outside of my expertise a bit,

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Speaker 3: but they have really different sizes and proportions of proteins

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Speaker 3: that make up muscle. There are three major proteins that

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Speaker 3: make up muscle actin myosin and and those three molecules

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Speaker 3: interact to produce these sliding filaments that lengthen and shorten

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Speaker 3: the muscle unit called the sarkamre. Invertebrates, they're all kind

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Speaker 3: of made the same, but in insects, they're built in

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Speaker 3: different ways. They can contract at different rates, they can

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Speaker 3: do all kinds of crazy stuff, and I can't explain

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Speaker 3: that to you. I'm not an insect muscle physiologist. I

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Speaker 3: have huge respect for them because they studied things that

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Speaker 3: are really weird to me.

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Speaker 2: Can I admit something that may be embarrassing? Yeah, I

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Speaker 2: didn't know until this conversation that insects had muscles. My

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Speaker 2: mental image was that they just basically had some sort

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Speaker 2: of hydraulic goo inside their exoskeletons, and I had no

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Speaker 2: idea how they moved. So that's fascinating. Are you saying

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Speaker 2: it's like differentiated inside there? Like if I cut into

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Speaker 2: a fifty ton ant, It's not just like a fire

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Speaker 2: hose of goo that's going to spread out.

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Speaker 3: No, no, No, they have plenty of internal structure. Spiders

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Speaker 3: do move using a largely hydraulic limb structure, so they

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Speaker 3: have muscles, but they're mostly powering their leg movements through

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Speaker 3: a hydraulic movement that's coupled to their circulatory system, so

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Speaker 3: they're pumping fluid around their bodies. And using that fluid

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Speaker 3: to move their legs.

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Speaker 2: So are muscles conserved across all animals? Like everything that's

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Speaker 2: mobile on Earth uses some kind of muscle.

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Speaker 3: Yeah, every animal. There are other things that do weird stuff.

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Speaker 3: I guess once you get down to a single cell,

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Speaker 3: it becomes a question of what really is a muscle.

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Speaker 3: H becomes a little weird. I mean, you're using proteins

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Speaker 3: to spin a flagella, a little whip like structure in

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Speaker 3: bacteria and other small small organisms. So I think if

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Speaker 3: we're talking about muscle in the way that we're familiar

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Speaker 3: with it, with the three major components acting miosin Titan,

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Speaker 3: then that's an animal thing more or less.

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Speaker 2: And so on that topic, why don't we have like

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Speaker 2: macroscopic sized bacteria. Why don't we see the ocean filled

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Speaker 2: with like blue whales and then like bacteria the size

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Speaker 2: blue whale with a massive flagella behind it. Oh boy,

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Speaker 2: and hack, nobody's made that monster movie yet. That's the

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Speaker 2: real question.

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Speaker 3: Yeah, Well, I mean the blob was kind of in

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Speaker 3: that direction of the I don't know how you classify

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Speaker 3: that blob, although if you know your HP lovecraft lore,

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Speaker 3: it was probably a shagoth anyway. Yeah, bacteria, I don't

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Speaker 3: know if I could give you an easy answer there.

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Speaker 3: I think diffusion would be a big problem for them.

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Speaker 3: They've got this big, tough cell wall, and they're one

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Speaker 3: cell that relies on stuff to get in and out

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Speaker 3: of that cell wall and move around the organism. They

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Speaker 3: have no respiratory circulatory systems anything like that. They just

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Speaker 3: rely purely on diffusion. So I think that's going to

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Speaker 3: be a big constraint on any single celled organism is diffusion.

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Speaker 3: And maybe the support of their cell wall itself might

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Speaker 3: just crumple under its own weight and they can't really move.

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Speaker 3: I mean, take a huge flagellum to move a big

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Speaker 3: bacterium through the water. I can't even imagine how the

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Speaker 3: mechanics of that would work.

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Speaker 2: I'm sure you can imagine it. Mister monster movie over there,

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Speaker 2: for sure has the mental image.

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Speaker 3: Give me a few million in VFX budget and I

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Speaker 3: can imagine it.

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Speaker 2: Yeah, done and done.

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Speaker 1: Yes, oh yeah, because we've got loads of money.

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Speaker 3: James Cameron, There you go.

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Speaker 2: Welcome to Daniel and Kelly's production studio.

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Speaker 1: There you go. So the conversation we've been having has

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Speaker 1: gone between physics and biology a lot. So you clearly

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Speaker 1: know a lot about both. And so after the break,

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Speaker 1: I'm going to ask you to explain why biology is

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Speaker 1: better than physics.

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Speaker 5: Oh, if possible, the gauntlet has been thrown down.

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Speaker 1: And we're back, all right. So, John, you know a

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Speaker 1: bunch about physics a bunch about biology. Do you have

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Speaker 1: a favorite or what do you love about the intersection

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Speaker 1: of these fields.

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Speaker 3: I do love the intersection. I love intersections of fields

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Speaker 3: in general. I like to defy boundaries. I like to

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Speaker 3: think about how a lot of boundaries we erect with

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Speaker 3: our minds are false and they're just there as conveniences. So, however,

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Speaker 3: in physics is physics, it's very easily circumscribable, much like

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Speaker 3: mathematics is, whereas biology is fuzzier. I like that aspect

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Speaker 3: of biology, maybe because I like fuzziness, although physics can

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Speaker 3: get pretty fuzzy. I guess down at the weird end

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Speaker 3: of scales. Maybe Daniel you can agree that or not.

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Speaker 1: That's where Daniel lives. Yeah, at the weird end.

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Speaker 2: Yeah, I'm at the weird end of everything.

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Speaker 1: That's right.

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Speaker 2: But you ended up a biologist, I mean by name,

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Speaker 2: you're in the evolutionary biomechanics department, do you not like

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Speaker 2: in a physics department doing biophysics? And I completely agree

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Speaker 2: with you that these are artificial dotted lines that we

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Speaker 2: draw on a smooth spectrum of natural curiosity. But I

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Speaker 2: am curious why you ended up on one side of

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Speaker 2: that then the other, like, why are biologists more likely

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Speaker 2: to hire you than physicists?

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Speaker 3: Oh, my training very much is in biology. Into my PhD.

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Speaker 3: I am a biologist. Fundamentally. I can't claim to be

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Speaker 3: a physicist. It's just not my training. I'm not an

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Speaker 3: engineer or anything like that. I did do a postdoc

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Speaker 3: in an engineering laboratory, which gave me a bit of

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Speaker 3: street cred with that crowd and did teach me a

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Speaker 3: lot about that kind of perspective with Newtonian mechanics. But yeah,

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Speaker 3: I couldn't go work in a physics department. They could

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Speaker 3: tell that I was an impostor.

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Speaker 2: Now you'd just be like, Hey, what happens if we

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Speaker 2: have a really high energy collisions of very large animals,

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Speaker 2: two elephants running at each other at high speeds. Let's

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Speaker 2: do that experiment, right, It's easy to be in the

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Speaker 2: physics department.

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Speaker 1: Well, can we get into the details of your day

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Speaker 1: to day life studying this stuff. So like, when I

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Speaker 1: think about studying movement in small mammals, I can imagine,

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Speaker 1: for example, putting them in a CT scanner or an

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Speaker 1: X ray machine. But you study animals that are just

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Speaker 1: absolutely massive, and so presumably they don't stay still in

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Speaker 1: those machines or there's no machines big enough. So how

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Speaker 1: do you get your data?

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Speaker 3: Well, I'm interested in the size spectrum of animals in general,

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Speaker 3: because I don't think you can understand big animals without

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Speaker 3: also understanding smaller ones. It's just that we do have

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Speaker 3: a lot of knowledge of how smaller animals work, and

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Speaker 3: just up until my work, there haven't been that much

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Speaker 3: research on how the biggest land animals worked. So I

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Speaker 3: do work on living animals using like X ray machines.

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Speaker 3: We have multiple X ray video cameras as you can

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Speaker 3: loosely call them, where you can have an animal moving

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Speaker 3: through two planar X ray systems with high speed video

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Speaker 3: cameras attached to them and use those in animation software

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Speaker 3: to reconstruct how the skeleton moved in the living animal.

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Speaker 3: That's really cutting edge stuff in our field. That allows

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Speaker 3: us to see inside the animal and see it's skeleton

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Speaker 3: moving in life. It's been a big game changer over

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Speaker 3: the last twenty years. But yeah, we can't do that

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Speaker 3: with big animals. The biggest size you can image is

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Speaker 3: about soccer or football sized for Americans, soccer ball sized roughly,

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Speaker 3: And the technology, for reasons I don't understand, or maybe

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Speaker 3: just demand, has not created any machine that can do

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Speaker 3: a volume bigger than that, So doing even small parts

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Speaker 3: of big animals is impossible with that kind of stuff.

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Speaker 3: We do more conventional kinds of study of larger animals

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Speaker 3: with motion capture or just high speed video or whatever.

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Speaker 3: We use other devices to measure how hard they exert

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Speaker 3: force against their environments, so what we call force platforms

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Speaker 3: and pressure pads that measure the force per unit area

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Speaker 3: they apply to the grounds. We have lots of cool

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Speaker 3: toys to measure what we would call the kinetics, so

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Speaker 3: the forces and related things and the kinematics the motions

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Speaker 3: of organisms.

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Speaker 2: I'm confused when you say that you can only image

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Speaker 2: something the size of a soccer ball, because like, you

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Speaker 2: can put a whole human inside a CT machine, and

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Speaker 2: there are some pretty big humans out there, why can't

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Speaker 2: we do that with animals?

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Speaker 3: Also, you can't have them moving around with like a

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Speaker 3: video camera going on capturing data the a CT scan,

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Speaker 3: you have to have individual remaining still because you're taking

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Speaker 3: cereal slices cerial X rays of the individual to them

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Speaker 3: piece together the whole three D person. So if they move,

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Speaker 3: actually your image gets screwed up.

439
00:24:33,720 --> 00:24:36,040
Speaker 2: I see. You can't convince an elephant to stay still.

440
00:24:36,920 --> 00:24:37,320
Speaker 3: Yeah.

441
00:24:37,480 --> 00:24:40,240
Speaker 1: Yeah, what's the biggest animal that you've studied.

442
00:24:40,520 --> 00:24:43,200
Speaker 3: I've worked a bit on the big stopod dinosaurs. I'm

443
00:24:43,200 --> 00:24:46,040
Speaker 3: not so well known for doing that, but I have

444
00:24:46,240 --> 00:24:49,320
Speaker 3: published a bit on them with some colleagues. I'm more

445
00:24:49,359 --> 00:24:52,879
Speaker 3: well known for studying the big carnivorous dinosaurs like t Rex.

446
00:24:52,920 --> 00:24:55,159
Speaker 3: I really made my name with an early study I

447
00:24:55,160 --> 00:24:58,919
Speaker 3: did showing that t Rex couldn't run quickly, again smashing dreams,

448
00:24:59,280 --> 00:25:02,480
Speaker 3: making some pal petology fans rather upset, but it was

449
00:25:02,520 --> 00:25:06,240
Speaker 3: well received scientifically, so I'm very pleased about that. I've

450
00:25:06,240 --> 00:25:08,360
Speaker 3: worked with elephants a lot, about as much as I've

451
00:25:08,400 --> 00:25:10,919
Speaker 3: worked on t Rex, and it's ken. I've worked on

452
00:25:11,000 --> 00:25:15,399
Speaker 3: living elephants from zoos around the US and UK to

453
00:25:15,840 --> 00:25:20,399
Speaker 3: more wild type elephants in Thailand, working with elephants that

454
00:25:20,440 --> 00:25:24,760
Speaker 3: were either previously used in logging or tourism, or even

455
00:25:24,920 --> 00:25:28,679
Speaker 3: used in racing. So I got to measure how the

456
00:25:28,760 --> 00:25:31,359
Speaker 3: fastest elephants could move, which was really really cool.

457
00:25:31,640 --> 00:25:33,240
Speaker 2: How fast can the elephant move?

458
00:25:33,600 --> 00:25:37,040
Speaker 3: They can go up to almost fifteen miles an hour,

459
00:25:37,240 --> 00:25:40,720
Speaker 3: which might not sound that fast, but that's a challenge

460
00:25:40,720 --> 00:25:44,240
Speaker 3: for me to keep up with that pace. It's still

461
00:25:44,280 --> 00:25:47,359
Speaker 3: pretty impressive to see like a four thousand kilogram animal

462
00:25:47,480 --> 00:25:49,800
Speaker 3: traveling at fifteen miles an hour.

463
00:25:50,280 --> 00:25:51,639
Speaker 2: That's a lot of kinetic energy.

464
00:25:51,840 --> 00:25:53,800
Speaker 1: I bet it feels really fast if it's chasing you.

465
00:25:54,119 --> 00:25:58,600
Speaker 3: Oh yeah. What we found with that work was that

466
00:25:58,680 --> 00:26:01,320
Speaker 3: even though elephants don't go born at any time, when

467
00:26:01,320 --> 00:26:03,280
Speaker 3: they go quickly, which is kind of what we thought,

468
00:26:04,359 --> 00:26:09,320
Speaker 3: they do, sometimes only have support on one limb while

469
00:26:09,359 --> 00:26:12,199
Speaker 3: the other three limbs are airborne, kind of doing the

470
00:26:12,240 --> 00:26:15,359
Speaker 3: splits in mid air. So that was really cool to

471
00:26:15,440 --> 00:26:18,920
Speaker 3: see how extreme the gate of elephants could be. They

472
00:26:18,960 --> 00:26:21,639
Speaker 3: really do move in rather extreme ways even though they

473
00:26:21,640 --> 00:26:22,840
Speaker 3: don't go fully airborne.

474
00:26:22,880 --> 00:26:25,119
Speaker 2: That's fascinating. You talk about the gate of elephants like

475
00:26:25,160 --> 00:26:28,520
Speaker 2: whether they're ever have all four legs off the ground. Yeah,

476
00:26:28,640 --> 00:26:31,080
Speaker 2: animals do ever have all four legs off the.

477
00:26:31,000 --> 00:26:35,520
Speaker 3: Ground pretty much everything except like tortoises and other really

478
00:26:35,560 --> 00:26:38,879
Speaker 3: slow animals. And just this past summer we showed with

479
00:26:38,920 --> 00:26:42,160
Speaker 3: another paper that when hippos go really quickly, they leave

480
00:26:42,200 --> 00:26:44,679
Speaker 3: the ground with all four feet, which elephants don't. So

481
00:26:44,720 --> 00:26:47,000
Speaker 3: that was a nice thing to find which had never

482
00:26:47,080 --> 00:26:50,800
Speaker 3: been reported scientifically. We know that rhinos, which get very

483
00:26:50,880 --> 00:26:53,800
Speaker 3: very big, up to three thousand kilograms or so, so

484
00:26:54,000 --> 00:26:58,960
Speaker 3: rivaling the size of some like Asian elephants, they can gallop,

485
00:26:59,119 --> 00:27:01,640
Speaker 3: they can leave the grind with all four feet, so

486
00:27:01,720 --> 00:27:05,080
Speaker 3: they are kind of in that zone of being big

487
00:27:05,160 --> 00:27:08,560
Speaker 3: and being athletic that is apparently hard to achieve.

488
00:27:08,800 --> 00:27:11,840
Speaker 2: You discovered flying rhinoceurces. That's amazing.

489
00:27:12,080 --> 00:27:14,680
Speaker 3: The rhino thing was known, but the fine hippo thing

490
00:27:14,760 --> 00:27:18,320
Speaker 3: that was a small new contraction that I'm still proud

491
00:27:18,320 --> 00:27:20,600
Speaker 3: of and got a lot of news attention. I was

492
00:27:20,640 --> 00:27:22,840
Speaker 3: really kind of pleasantly surprised by that.

493
00:27:23,280 --> 00:27:24,920
Speaker 2: I want to come back to the dinosaurs in a minute,

494
00:27:24,920 --> 00:27:26,920
Speaker 2: but first I have a question about elephants, because I've

495
00:27:26,960 --> 00:27:30,520
Speaker 2: always heard this story about elephants that the reason elephants

496
00:27:30,560 --> 00:27:33,439
Speaker 2: have really big ears is because of this volume surface

497
00:27:33,480 --> 00:27:36,040
Speaker 2: area of question. And you know you've scaled up the

498
00:27:36,040 --> 00:27:38,360
Speaker 2: elephants to be so big, it's got so much meat

499
00:27:38,400 --> 00:27:40,640
Speaker 2: it's hard for it to stay cool, and so having

500
00:27:40,720 --> 00:27:42,879
Speaker 2: really big, flappy ears is like a cheap way to

501
00:27:42,880 --> 00:27:46,399
Speaker 2: increase your service area without increasing your volume. Is that

502
00:27:46,520 --> 00:27:48,680
Speaker 2: pop science nonsense or is that real science?

503
00:27:48,960 --> 00:27:51,480
Speaker 3: There is some truth to that. So there's big differences

504
00:27:51,520 --> 00:27:56,119
Speaker 3: in ear size in Asian versus African bush elephants. The

505
00:27:56,160 --> 00:28:00,439
Speaker 3: bush elephants in Africa have much bigger ears that it

506
00:28:00,480 --> 00:28:04,520
Speaker 3: corresponds to being out there in hotter temperatures in the open,

507
00:28:04,760 --> 00:28:07,560
Speaker 3: exposed to sunlight and so forth. I think it's pretty

508
00:28:07,560 --> 00:28:10,679
Speaker 3: well accepted that that difference in ear size and just

509
00:28:10,800 --> 00:28:14,320
Speaker 3: the overall large ear size and elephants overall relates to

510
00:28:14,359 --> 00:28:17,159
Speaker 3: them using the ears as the cooling mechanism, and they

511
00:28:17,200 --> 00:28:20,840
Speaker 3: do wave their ears so they get convective cooling, moving

512
00:28:20,880 --> 00:28:24,960
Speaker 3: the air quickly passed to ensure that there's always more

513
00:28:25,160 --> 00:28:29,399
Speaker 3: air to unload the heat onto as they keep airflow going.

514
00:28:29,920 --> 00:28:31,720
Speaker 1: And mammoths had little ears, right.

515
00:28:32,080 --> 00:28:35,439
Speaker 3: Some wooly mammoths did, so. There are quite a few

516
00:28:35,480 --> 00:28:38,200
Speaker 3: different species of mammliths. The wooly moth is the one

517
00:28:38,200 --> 00:28:42,440
Speaker 3: we know best from animals preserved in frost, and Siberia

518
00:28:42,640 --> 00:28:45,400
Speaker 3: had a lot of body parts reduced to avoid frostbite.

519
00:28:45,480 --> 00:28:49,000
Speaker 2: Probably you know, I noticed that in Farside Far Side

520
00:28:49,000 --> 00:28:51,560
Speaker 2: the mammoths always have kind of little cute ears, and

521
00:28:51,600 --> 00:28:53,400
Speaker 2: I remember as a kid being like, is that right?

522
00:28:53,960 --> 00:28:56,280
Speaker 2: So it's amazing Gary Larson ahead of his time.

523
00:28:56,680 --> 00:28:58,840
Speaker 3: Oh he needs science. Yeah, he paid attention.

524
00:29:00,240 --> 00:29:01,680
Speaker 1: Can I dig in a little bit more to your

525
00:29:01,680 --> 00:29:04,320
Speaker 1: elephant study before we go to dinosaurs? So how did

526
00:29:04,360 --> 00:29:07,120
Speaker 1: you figure out that the elephants had one foot on

527
00:29:07,120 --> 00:29:08,600
Speaker 1: the ground at all time? Was it just a really

528
00:29:08,600 --> 00:29:11,000
Speaker 1: good camera? And how do you make an elephant run

529
00:29:11,000 --> 00:29:12,480
Speaker 1: on command? That sounds scary?

530
00:29:12,960 --> 00:29:16,680
Speaker 3: It was just using pretty conventional cameras or not very

531
00:29:16,760 --> 00:29:19,040
Speaker 3: high speed cameras. We did eventually get hold of some

532
00:29:19,080 --> 00:29:22,800
Speaker 3: good cameras that helped confirm it even better. But when

533
00:29:22,840 --> 00:29:25,480
Speaker 3: I was just a post doc or even a grad student, yeah,

534
00:29:25,520 --> 00:29:28,880
Speaker 3: I was just like in my mid twenties, I started

535
00:29:28,880 --> 00:29:31,080
Speaker 3: working on elephants trying to answer the question, well, do

536
00:29:31,120 --> 00:29:33,120
Speaker 3: they leave the ground with all four feet or not?

537
00:29:33,520 --> 00:29:37,240
Speaker 3: We didn't think so, but I wanted to test that empirically,

538
00:29:37,600 --> 00:29:39,520
Speaker 3: and so I just took a video camera out to

539
00:29:39,600 --> 00:29:43,000
Speaker 3: some zoos couldn't get them going quickly, and then got

540
00:29:43,040 --> 00:29:45,360
Speaker 3: in touch with the guy in Thailand. He was interested

541
00:29:45,360 --> 00:29:47,520
Speaker 3: in this kind of question, and I went out there

542
00:29:47,520 --> 00:29:50,479
Speaker 3: with just a conventional video camera, and he knew all

543
00:29:50,480 --> 00:29:53,560
Speaker 3: of the elephant keepers and just got them together and

544
00:29:53,760 --> 00:29:55,520
Speaker 3: made it into kind of a game for them or

545
00:29:55,520 --> 00:29:58,960
Speaker 3: a contest. So each elephant has its own companion, a

546
00:29:59,080 --> 00:30:02,280
Speaker 3: mahout or a rider who pretty much grows up with

547
00:30:02,320 --> 00:30:05,920
Speaker 3: the elephant, and they have a very strong bond in Thailand.

548
00:30:06,600 --> 00:30:10,280
Speaker 3: And so the mahout would encourage the elephant by whatever

549
00:30:10,400 --> 00:30:14,600
Speaker 3: means he thought was reasonable, like calling to it usually

550
00:30:14,720 --> 00:30:16,719
Speaker 3: or having someone run in front of it, or have

551
00:30:16,720 --> 00:30:20,400
Speaker 3: it go toward a friendly elephant, and that would motivate

552
00:30:20,440 --> 00:30:24,080
Speaker 3: it to go quickly. It certainly did work in Thailand.

553
00:30:24,120 --> 00:30:27,480
Speaker 3: We got much faster elephants than we ever did elsewhere.

554
00:30:27,720 --> 00:30:29,920
Speaker 1: I love the idea of explaining to your thesis advisor.

555
00:30:30,160 --> 00:30:32,360
Speaker 1: I couldn't answer the question. I couldn't get the elephants

556
00:30:32,400 --> 00:30:35,800
Speaker 1: to go fast enough. It's a very unique problem.

557
00:30:36,240 --> 00:30:39,920
Speaker 3: This is animal research. Yeahm Motivating animals very challenging.

558
00:30:40,880 --> 00:30:41,360
Speaker 1: It's true.

559
00:30:41,600 --> 00:30:44,040
Speaker 2: Do you have to get an IRB there, like do

560
00:30:44,120 --> 00:30:46,480
Speaker 2: elephants get grumpy if you make them run, or can

561
00:30:46,480 --> 00:30:48,080
Speaker 2: you probably hurt them or something.

562
00:30:48,240 --> 00:30:52,280
Speaker 3: Yeah, there's always stringent ethical approval involved because even just

563
00:30:52,320 --> 00:30:56,040
Speaker 3: stress is a concern. So you have to explain how

564
00:30:56,040 --> 00:30:58,120
Speaker 3: are you going to mitigate stress? What are you going

565
00:30:58,160 --> 00:31:00,440
Speaker 3: to do if an animal seems stressed? Will you terminate

566
00:31:00,440 --> 00:31:04,280
Speaker 3: the experiment? What does stress look like? There are important questions,

567
00:31:04,360 --> 00:31:07,360
Speaker 3: and avoiding fatigue also is really important. So we give

568
00:31:07,400 --> 00:31:09,920
Speaker 3: animals lots of risk because we don't want to study fatigue.

569
00:31:09,960 --> 00:31:11,400
Speaker 3: We want animals that are fresh.

570
00:31:11,800 --> 00:31:14,680
Speaker 1: Let's go back to dinosaurs. You mentioned t rex right

571
00:31:14,720 --> 00:31:17,760
Speaker 1: after we have finished talking about methods for looking at

572
00:31:17,800 --> 00:31:21,040
Speaker 1: animal movement. But when you're studying dinosaurs, of course, you

573
00:31:21,080 --> 00:31:23,800
Speaker 1: can't see them move at all. So how do you

574
00:31:23,840 --> 00:31:26,240
Speaker 1: study animal movement in long dead animals?

575
00:31:26,520 --> 00:31:30,040
Speaker 3: So we have kind of two things. We have the

576
00:31:30,040 --> 00:31:34,120
Speaker 3: fundamental principles of animal movement that we know from living animals,

577
00:31:34,680 --> 00:31:38,920
Speaker 3: which tell us some pretty good, reliable general rules that

578
00:31:38,960 --> 00:31:43,760
Speaker 3: we can use as expectations to apply to extinct animals,

579
00:31:43,840 --> 00:31:47,080
Speaker 3: or at least give boundaries for here's what this could

580
00:31:47,120 --> 00:31:49,600
Speaker 3: be like. Here's how big the muscles might be relative

581
00:31:49,640 --> 00:31:53,760
Speaker 3: to the limbs. That kind of thing and then we

582
00:31:53,800 --> 00:31:56,600
Speaker 3: have physics, so we can and this is what I

583
00:31:56,600 --> 00:31:59,520
Speaker 3: did in my PhD thesis, we can build either very

584
00:31:59,520 --> 00:32:03,000
Speaker 3: simple or very complicated mechanical model of a dinosaur for

585
00:32:03,040 --> 00:32:06,560
Speaker 3: its own sake. So actually try to reconstruct, like in

586
00:32:06,600 --> 00:32:10,120
Speaker 3: a computer usually what the animal looked like, it's dimensions,

587
00:32:10,680 --> 00:32:16,280
Speaker 3: and give those dimensions physical properties, mass, center of mass, inertia,

588
00:32:16,640 --> 00:32:19,880
Speaker 3: so forth, stuff that physicists would care about, and then

589
00:32:19,920 --> 00:32:23,480
Speaker 3: ask questions of that model, basically, what can you do

590
00:32:24,040 --> 00:32:29,240
Speaker 3: what is possible with this representation of a dinosaur. And

591
00:32:29,280 --> 00:32:32,080
Speaker 3: then you can test hypotheses like, well, given this set

592
00:32:32,080 --> 00:32:34,280
Speaker 3: of assumptions about a t rex, could it run quickly

593
00:32:34,360 --> 00:32:36,960
Speaker 3: or not? How much muscle mass would it have needed

594
00:32:36,960 --> 00:32:39,720
Speaker 3: to run quickly? And is that reasonable given how much

595
00:32:39,720 --> 00:32:42,000
Speaker 3: we could fit on the skeleton or not? And I

596
00:32:42,120 --> 00:32:45,600
Speaker 3: tested that and found that no, it couldn't run very quickly,

597
00:32:45,640 --> 00:32:48,080
Speaker 3: not like a racehorse, like twenty five miles an hour,

598
00:32:48,160 --> 00:32:53,160
Speaker 3: but still possible to do more like kind of elephant speeds,

599
00:32:53,240 --> 00:32:55,640
Speaker 3: maybe fifteen miles an hour, which for an animal that

600
00:32:55,640 --> 00:32:58,600
Speaker 3: could get bigger than an elephant, it's still pretty darn good.

601
00:32:58,800 --> 00:33:01,479
Speaker 2: So what you're doing here is like imagining how you

602
00:33:01,600 --> 00:33:04,920
Speaker 2: might build a dinosaur saying like, well, how do reptiles

603
00:33:04,960 --> 00:33:06,840
Speaker 2: move and how do current animals move? And you know

604
00:33:06,880 --> 00:33:08,720
Speaker 2: the sort of shape of a dinosaur, so you're sort

605
00:33:08,720 --> 00:33:12,440
Speaker 2: of imagining a biological model of a dinosaur then studying that.

606
00:33:12,760 --> 00:33:16,560
Speaker 3: It's setting up a set of constraints. So here's what

607
00:33:16,640 --> 00:33:19,600
Speaker 3: it's possible given what we know from living animals, the

608
00:33:19,680 --> 00:33:22,480
Speaker 3: range of variation we see in living animals, which sometimes

609
00:33:22,520 --> 00:33:26,920
Speaker 3: can be pretty conservative, and using that as inspiration to

610
00:33:27,000 --> 00:33:31,040
Speaker 3: make assumptions about extinct animals. So we have the bones,

611
00:33:31,320 --> 00:33:34,800
Speaker 3: that's direct information. Sometimes we have fossil footprints that we

612
00:33:34,800 --> 00:33:36,920
Speaker 3: can use to kind of give an idea. Okay, this

613
00:33:37,000 --> 00:33:40,040
Speaker 3: animal stood on two feet with the feet very close together,

614
00:33:40,560 --> 00:33:45,640
Speaker 3: not sprawled out to either side. And yeah, so ultimately

615
00:33:45,680 --> 00:33:50,760
Speaker 3: then we can, for example, reconstruct muscles attaching from bone

616
00:33:50,800 --> 00:33:54,960
Speaker 3: to bone to guide their lines of action. And that

617
00:33:55,040 --> 00:33:57,520
Speaker 3: can be done by looking at living animals and seeing, okay,

618
00:33:57,560 --> 00:34:01,000
Speaker 3: where are the muscles of living animals attach? And I

619
00:34:01,040 --> 00:34:03,360
Speaker 3: did a lot of that in my PhD work and

620
00:34:03,480 --> 00:34:07,040
Speaker 3: found that if you look at living animals, especially the

621
00:34:07,080 --> 00:34:11,680
Speaker 3: closest relatives to dinosaurs, like living birds and crocodiles and

622
00:34:11,800 --> 00:34:17,239
Speaker 3: other reptiles. The leg muscles are really conservative, so you

623
00:34:17,280 --> 00:34:21,719
Speaker 3: can pretty well predict where the muscles attach from the

624
00:34:21,760 --> 00:34:24,040
Speaker 3: shape of the bones, from marks on the bones which

625
00:34:24,160 --> 00:34:28,680
Speaker 3: reveal the actual interface between the muscler tendon and the

626
00:34:28,719 --> 00:34:29,480
Speaker 3: bone itself.

627
00:34:29,680 --> 00:34:33,279
Speaker 2: When you say conservative, you mean similar across species. Yeah,

628
00:34:33,480 --> 00:34:34,680
Speaker 2: in small government.

629
00:34:35,360 --> 00:34:40,920
Speaker 3: Yes, yeah, similar across species. So yeah, consistent and probably

630
00:34:41,000 --> 00:34:44,279
Speaker 3: predictable that we can make assumptions about the anatomy of

631
00:34:44,320 --> 00:34:47,040
Speaker 3: extinct animals that are reasonable. They're not going to be perfect,

632
00:34:47,440 --> 00:34:51,120
Speaker 3: but they're pretty well grounded in actual evidence, and we

633
00:34:51,200 --> 00:34:53,480
Speaker 3: can be very explicit. Well, I think it was this

634
00:34:53,560 --> 00:34:56,560
Speaker 3: way because of these data that we have from living

635
00:34:56,600 --> 00:34:59,640
Speaker 3: animals and this information that we have directly from the skeleton.

636
00:35:00,280 --> 00:35:02,560
Speaker 2: The physicists in me likes that you're like building a

637
00:35:02,600 --> 00:35:06,160
Speaker 2: model and exploring the speed and motion of that model,

638
00:35:06,520 --> 00:35:08,760
Speaker 2: but then also wonders like what do we know about

639
00:35:08,800 --> 00:35:11,680
Speaker 2: how that model might differ from real blinosaurs? Right, you

640
00:35:11,719 --> 00:35:15,120
Speaker 2: are making assumptions and extrapolations. Then along with that you

641
00:35:15,480 --> 00:35:18,960
Speaker 2: might develop like some uncertainty window or some band of

642
00:35:19,040 --> 00:35:22,520
Speaker 2: your knowledge and confidence to say like, well, we're pretty sure,

643
00:35:22,640 --> 00:35:25,040
Speaker 2: or is that something you can quantify, or is the

644
00:35:25,080 --> 00:35:27,319
Speaker 2: information so sketchy that we can just sort of like

645
00:35:27,640 --> 00:35:30,480
Speaker 2: make qualitative arguments about how well we know this stuff.

646
00:35:30,880 --> 00:35:35,080
Speaker 3: It is difficult to make very specific predictions, and I

647
00:35:35,080 --> 00:35:38,600
Speaker 3: mean quantitative arguments are always in some very rough bounds

648
00:35:39,040 --> 00:35:42,200
Speaker 3: of possibilities. So like trying to predict the speed doesn't

649
00:35:42,239 --> 00:35:45,080
Speaker 3: extinct on us, or we don't even know for sure

650
00:35:45,080 --> 00:35:46,880
Speaker 3: what the bounds can be. But we can do what

651
00:35:46,920 --> 00:35:49,879
Speaker 3: we'd call sensitivity analysis, or the different inputs we put

652
00:35:49,880 --> 00:35:53,200
Speaker 3: into the model, So how big are the leg muscles,

653
00:35:53,200 --> 00:35:55,720
Speaker 3: where are they attached to, so on and so forth,

654
00:35:56,800 --> 00:36:00,319
Speaker 3: and then see what the output of the modeling analysis is, Well,

655
00:36:00,320 --> 00:36:03,680
Speaker 3: how does that change running speed if we change these assumptions.

656
00:36:03,080 --> 00:36:03,680
Speaker 5: In the model.

657
00:36:04,040 --> 00:36:06,319
Speaker 3: Another thing we do that's really important, and this is

658
00:36:06,520 --> 00:36:09,640
Speaker 3: where my training in biology really comes to bear and

659
00:36:09,719 --> 00:36:12,560
Speaker 3: my work with living animals is we can apply the

660
00:36:12,680 --> 00:36:16,759
Speaker 3: same methods to a model of living animals and see

661
00:36:16,800 --> 00:36:19,360
Speaker 3: can we predict how a living animal works based on

662
00:36:19,920 --> 00:36:23,040
Speaker 3: the same kind of modeling approach as we apply to

663
00:36:23,080 --> 00:36:27,040
Speaker 3: an extinct animal. And comfortingly, when we do those kinds

664
00:36:27,040 --> 00:36:29,560
Speaker 3: of tests, they usually do pretty darn well. So we

665
00:36:29,640 --> 00:36:32,480
Speaker 3: can predict that a bird can run by ped lee,

666
00:36:32,560 --> 00:36:35,799
Speaker 3: whereas a crocodile that doesn't run by p Lee cannot.

667
00:36:35,840 --> 00:36:38,320
Speaker 2: That's very cool that you apply your mechanism to animals

668
00:36:38,360 --> 00:36:39,480
Speaker 2: where you can check yourself.

669
00:36:39,520 --> 00:36:41,280
Speaker 3: That's very cool, very important.

670
00:36:41,480 --> 00:36:44,640
Speaker 2: But also, as a complete non expert in biology or

671
00:36:44,640 --> 00:36:48,480
Speaker 2: in dinosaurs, I have the sense that our mental imagery

672
00:36:48,520 --> 00:36:52,000
Speaker 2: of how dinosaurs stood and moved and looked has changed

673
00:36:52,040 --> 00:36:54,320
Speaker 2: over the last fifteen hundred years. You know, like t

674
00:36:54,480 --> 00:36:56,440
Speaker 2: Rex used to look more like standing up, and now

675
00:36:56,440 --> 00:36:59,200
Speaker 2: we think dinosaurs might have all had feathers or something

676
00:37:00,040 --> 00:37:02,520
Speaker 2: to tell us that a lot of what we're assuming,

677
00:37:02,640 --> 00:37:05,279
Speaker 2: that the assumptions we're making might be changing with time

678
00:37:05,400 --> 00:37:07,400
Speaker 2: and might have uncertainties we haven't accounted for.

679
00:37:07,880 --> 00:37:10,080
Speaker 3: Yeah, and I think that's the great thing about science

680
00:37:10,160 --> 00:37:14,279
Speaker 3: is these things can always be updated. Everything's provisional. They

681
00:37:14,360 --> 00:37:17,240
Speaker 3: need to be revisited. I mean, someone might come along

682
00:37:17,280 --> 00:37:19,120
Speaker 3: and show that my work that I did twenty years

683
00:37:19,120 --> 00:37:21,080
Speaker 3: ago is wrong, and that's just the way it goes.

684
00:37:21,640 --> 00:37:24,120
Speaker 3: The key thing, I think is to be explicit, to say,

685
00:37:24,280 --> 00:37:26,440
Speaker 3: here's my set of assumptions. Here are the data that

686
00:37:26,520 --> 00:37:28,719
Speaker 3: go in, here are the data that go out, here's

687
00:37:28,719 --> 00:37:32,239
Speaker 3: the methods that are used. So it's all reproducible, and

688
00:37:32,320 --> 00:37:34,879
Speaker 3: someone can go back and say, oh, no, I found

689
00:37:34,880 --> 00:37:38,760
Speaker 3: some other information that changes that inputs completely, or changes

690
00:37:38,760 --> 00:37:41,759
Speaker 3: the way we should even model the whole thing completely

691
00:37:42,040 --> 00:37:44,600
Speaker 3: the way the whole system might work, and so they

692
00:37:44,600 --> 00:37:47,960
Speaker 3: could repeat or do a completely new invention of that

693
00:37:48,080 --> 00:37:50,719
Speaker 3: kind of analysis. I think that's the key.

694
00:37:51,080 --> 00:37:52,880
Speaker 2: And sorry if I missed this earlier. But what was

695
00:37:52,920 --> 00:37:56,280
Speaker 2: the thing that limits t rexes to not going much faster?

696
00:37:56,400 --> 00:37:58,480
Speaker 2: Or what was the thing that we learned about t

697
00:37:58,640 --> 00:38:01,920
Speaker 2: rexes that change people minds about why they couldn't go quickly?

698
00:38:02,520 --> 00:38:05,880
Speaker 3: Living land animals, no matter of what their size is,

699
00:38:06,200 --> 00:38:09,120
Speaker 3: can only devote so much of their body mass to

700
00:38:10,280 --> 00:38:13,920
Speaker 3: muscle that supports the body weight. You have to have

701
00:38:14,120 --> 00:38:17,719
Speaker 3: not only muscles, but bones, skeletons, lungs, brains, so on

702
00:38:17,760 --> 00:38:22,480
Speaker 3: and so forth. And the upper limit of that muscle

703
00:38:22,560 --> 00:38:26,719
Speaker 3: mass that we can see in nature appears to be ostriches.

704
00:38:27,080 --> 00:38:30,680
Speaker 3: Large per fraction of ostriches is leg muscle that supports them.

705
00:38:30,760 --> 00:38:33,399
Speaker 3: You think about an ostrich it's got a long, skinny neck,

706
00:38:33,520 --> 00:38:36,839
Speaker 3: tiny little head, tiny little wings, no tail to speak of,

707
00:38:37,680 --> 00:38:40,960
Speaker 3: a big torso, But really most of it is these big, long,

708
00:38:41,000 --> 00:38:44,600
Speaker 3: meaty legs and no dinosaur was really built like that,

709
00:38:45,080 --> 00:38:47,640
Speaker 3: Nothing like a t rex was built to have a

710
00:38:47,719 --> 00:38:52,080
Speaker 3: body devoted to muscle like an ostrich does today. So

711
00:38:52,120 --> 00:38:54,560
Speaker 3: we could use an ostriches like an upper limit for

712
00:38:54,680 --> 00:38:57,520
Speaker 3: what we know of in terms of how much muscle

713
00:38:58,000 --> 00:39:00,960
Speaker 3: a dinosaur might have had. Even that that would be

714
00:39:00,960 --> 00:39:04,360
Speaker 3: a bit straining credulity if we did say a dinosaur

715
00:39:04,400 --> 00:39:05,320
Speaker 3: had that much muscle.

716
00:39:05,520 --> 00:39:08,200
Speaker 2: Are you saying an ostrich would beat any dinosaur in

717
00:39:08,239 --> 00:39:08,839
Speaker 2: a foot race?

718
00:39:09,840 --> 00:39:10,280
Speaker 5: Yeah?

719
00:39:10,400 --> 00:39:13,160
Speaker 3: Yeah, I think it probably would. But even ostriches have

720
00:39:13,200 --> 00:39:16,400
Speaker 3: more muscle devoted to their limbs than like past animals

721
00:39:16,440 --> 00:39:19,440
Speaker 3: like cheetahs or big animals like rhinos or elephants do.

722
00:39:20,000 --> 00:39:21,680
Speaker 3: They're super muscular animals.

723
00:39:21,960 --> 00:39:24,160
Speaker 1: All right, So let's take a break, and when we

724
00:39:24,200 --> 00:39:26,359
Speaker 1: get back, we're gonna hear about some weird stuff that's

725
00:39:26,360 --> 00:39:27,360
Speaker 1: been in John's freezer.

726
00:39:27,800 --> 00:39:47,359
Speaker 2: Oh, As someone who is married to biologist and has

727
00:39:47,360 --> 00:39:49,799
Speaker 2: weird stuff in his freezer, as a result, I am

728
00:39:49,920 --> 00:39:53,719
Speaker 2: terrified to learn what John might have in his freezer.

729
00:39:54,960 --> 00:39:57,919
Speaker 1: Yeah. So, John, you have a really great blog called

730
00:39:57,920 --> 00:40:01,000
Speaker 1: What's in John's Freezer? And I decided I shouldn't look

731
00:40:01,040 --> 00:40:03,080
Speaker 1: at it with my husband around because it might turn

732
00:40:03,120 --> 00:40:05,600
Speaker 1: his stomach too much. But you've had some cool stuff

733
00:40:05,960 --> 00:40:08,560
Speaker 1: in your freezers. Can you tell us about some of

734
00:40:08,600 --> 00:40:10,239
Speaker 1: the cool stuff that's in your freezer and what you've

735
00:40:10,239 --> 00:40:10,719
Speaker 1: done with it.

736
00:40:10,920 --> 00:40:14,120
Speaker 3: The glory days are gone you used to have cooler stuff,

737
00:40:14,120 --> 00:40:16,239
Speaker 3: although I mean there's still some cool stuff there. I've

738
00:40:16,239 --> 00:40:18,120
Speaker 3: been trying to get rid of stuff lately because it

739
00:40:18,239 --> 00:40:20,800
Speaker 3: just got too full and became kind of a hazard

740
00:40:21,280 --> 00:40:24,560
Speaker 3: with piles of frozen stuff getting up to the ceiling

741
00:40:24,640 --> 00:40:28,440
Speaker 3: of this walking freezer. But yeah, I mean, over the years,

742
00:40:28,480 --> 00:40:31,960
Speaker 3: I've had a lot of parts of elephants because elephants

743
00:40:32,040 --> 00:40:34,759
Speaker 3: die in captivity, and zoos give parts of them at

744
00:40:34,840 --> 00:40:37,279
Speaker 3: least to me to study for research. And then we

745
00:40:37,360 --> 00:40:41,520
Speaker 3: take those parts and use them to help us understand

746
00:40:41,560 --> 00:40:43,880
Speaker 3: like the anatomy of elephants and how things can go

747
00:40:43,960 --> 00:40:46,200
Speaker 3: wrong in elephant feet, which are a big cause of

748
00:40:46,239 --> 00:40:48,840
Speaker 3: mortality in elephants. They have a lot of problems with

749
00:40:48,880 --> 00:40:51,799
Speaker 3: their feet. We can use the information from cadavers to

750
00:40:51,920 --> 00:40:55,880
Speaker 3: actually contribute to taking care of animals like elephants. A

751
00:40:55,880 --> 00:41:00,720
Speaker 3: lot of elephant parts, rhinos never had a hippo of drafts,

752
00:41:01,560 --> 00:41:04,640
Speaker 3: lots of crocodiles of all kinds, of different species. I

753
00:41:04,680 --> 00:41:07,800
Speaker 3: love crocodiles. I'm crazy about them and have done a

754
00:41:07,840 --> 00:41:09,440
Speaker 3: lot of research on crocodiles.

755
00:41:09,680 --> 00:41:11,360
Speaker 2: What's to love about crocodiles?

756
00:41:11,360 --> 00:41:14,839
Speaker 3: Sorry, guys, Oh, they're so so bizarre.

757
00:41:16,960 --> 00:41:19,600
Speaker 2: I've just shocked two biologists. Everybody out there should have

758
00:41:19,600 --> 00:41:23,480
Speaker 2: seen their faces. The horror, the outrage, the surprise. Really

759
00:41:23,520 --> 00:41:27,200
Speaker 2: tell me, I'm imagining crocodiles like eating dogs and like

760
00:41:27,239 --> 00:41:30,480
Speaker 2: snatching babies. What's amazing about crocodiles. Why do we love them?

761
00:41:30,560 --> 00:41:33,280
Speaker 3: Well, just that it means that's pretty good right there.

762
00:41:35,160 --> 00:41:37,520
Speaker 2: Wow, you're coming out as anti baby on the podcast.

763
00:41:37,520 --> 00:41:38,080
Speaker 2: That's amazing.

764
00:41:38,360 --> 00:41:42,279
Speaker 3: Seriously. What's cool about them is that I think they've

765
00:41:42,280 --> 00:41:45,480
Speaker 3: gotten the short stick in terms of being just dismissed

766
00:41:45,520 --> 00:41:48,279
Speaker 3: as living fossils, which, yeah, they look a lot like

767
00:41:48,480 --> 00:41:51,879
Speaker 3: they did back in the Cretaceous when dinosaurs were around.

768
00:41:51,960 --> 00:41:55,680
Speaker 3: They've remained somewhat conservative over time, although there have been

769
00:41:55,800 --> 00:41:58,480
Speaker 3: some groups of crocodiles that have come and gone even

770
00:41:58,840 --> 00:42:01,680
Speaker 3: since the dinosaurs went that we're pretty darn weird.

771
00:42:01,920 --> 00:42:03,800
Speaker 2: And just to be clear, you're not making a political

772
00:42:03,800 --> 00:42:06,320
Speaker 2: statement that conservative animals eat babies.

773
00:42:06,320 --> 00:42:13,040
Speaker 3: No, not yet. Yeah, So crocodiles are just bizarre. They're

774
00:42:13,120 --> 00:42:16,319
Speaker 3: not some sort of primitive thing everywhere you look at them.

775
00:42:16,719 --> 00:42:21,440
Speaker 3: Their body plan is incredibly specialized and modified. They're not

776
00:42:21,640 --> 00:42:28,920
Speaker 3: like some pulled over from some unspecialized, imperfect body plan.

777
00:42:29,040 --> 00:42:31,839
Speaker 3: They're really amazing at what they are able to do.

778
00:42:32,400 --> 00:42:35,520
Speaker 3: The way they breathe is really remarkable. They have this

779
00:42:35,640 --> 00:42:38,399
Speaker 3: muscle that attaches to their pelvis that pulls their liver

780
00:42:38,680 --> 00:42:42,040
Speaker 3: forwards and backwards, working like a piston to pull air

781
00:42:42,120 --> 00:42:44,440
Speaker 3: in and out of their body, kind of like we

782
00:42:44,520 --> 00:42:48,600
Speaker 3: use our diaphragm, but with a totally different mechanism, And

783
00:42:49,160 --> 00:42:52,080
Speaker 3: they can produce the largest bite forces of pretty much

784
00:42:52,080 --> 00:42:54,799
Speaker 3: any animal we know of, So they have gigantic jaw

785
00:42:54,840 --> 00:42:58,200
Speaker 3: muscles toward the back of their jaws that can produce

786
00:42:58,440 --> 00:43:01,440
Speaker 3: lost lots of force. As I showed in some of

787
00:43:01,480 --> 00:43:05,080
Speaker 3: my research, most species of crocodile can use these really

788
00:43:05,120 --> 00:43:08,200
Speaker 3: extreme bounding and galloping gates that we would normally think

789
00:43:08,239 --> 00:43:12,279
Speaker 3: of as mammalian like kinds of movement. So they bend

790
00:43:12,320 --> 00:43:15,040
Speaker 3: their backbones up and down instead of side to side

791
00:43:15,480 --> 00:43:18,680
Speaker 3: and go airborne for substantial periods of time, and can

792
00:43:18,719 --> 00:43:22,799
Speaker 3: go pretty quickly overground when they're small, at least once

793
00:43:22,800 --> 00:43:25,760
Speaker 3: they get big, they seem to lose that ability. But yeah,

794
00:43:25,800 --> 00:43:29,000
Speaker 3: they can be pretty great athletes, and so on and

795
00:43:29,000 --> 00:43:30,640
Speaker 3: so forth. Man, I could go on and on about this.

796
00:43:30,800 --> 00:43:32,799
Speaker 3: I just think they're really neat and you might look

797
00:43:32,800 --> 00:43:35,800
Speaker 3: at them and think, oh, that's just another lizard. Lizards

798
00:43:35,840 --> 00:43:37,880
Speaker 3: are great in their own right, but a crocodile is

799
00:43:37,920 --> 00:43:40,799
Speaker 3: not just an armored lizard or something like that. That's

800
00:43:40,840 --> 00:43:42,600
Speaker 3: completely different. It's its own thing.

801
00:43:42,760 --> 00:43:45,000
Speaker 1: I gotta say a little jealous. In my field, the

802
00:43:45,040 --> 00:43:47,279
Speaker 1: calls that we get are like, oh, hey, Kelly, I

803
00:43:47,320 --> 00:43:50,080
Speaker 1: saw some really fresh roadkill. Do you want to come

804
00:43:50,120 --> 00:43:52,680
Speaker 1: grab it? And like the answer is always yes, because

805
00:43:52,680 --> 00:43:56,200
Speaker 1: there's probably some really great parasites in there. This is

806
00:43:56,239 --> 00:44:00,080
Speaker 1: a bunch of tapeworms from a road killed porcupine. I

807
00:44:00,160 --> 00:44:02,040
Speaker 1: know good stuff in my office here, but I don't

808
00:44:02,080 --> 00:44:05,000
Speaker 1: have anything as cool as what you've got in my freezer.

809
00:44:05,840 --> 00:44:07,879
Speaker 3: Well, you can always come visit and have a tour.

810
00:44:07,920 --> 00:44:11,399
Speaker 3: I'd be glad to show you around. I've got ostriches EMUs,

811
00:44:11,520 --> 00:44:13,040
Speaker 3: there's a buffalo somewhere in there.

812
00:44:13,200 --> 00:44:15,760
Speaker 2: I've got a very Gary Larsen image of your freezer

813
00:44:15,800 --> 00:44:17,680
Speaker 2: going on right now with like you know, ostage head

814
00:44:17,680 --> 00:44:21,320
Speaker 2: sticking out and giraffe limbs everywhere. Is that pretty accurate?

815
00:44:21,400 --> 00:44:23,439
Speaker 3: It's kind of like a frozen Noah's arc. I guess

816
00:44:23,480 --> 00:44:24,200
Speaker 3: you could say this.

817
00:44:26,440 --> 00:44:31,359
Speaker 1: That's awesome. I'm going to see you in May. Okay, great, Yeah,

818
00:44:31,400 --> 00:44:32,759
Speaker 1: I'm coming back to town in May. I'm going to

819
00:44:32,840 --> 00:44:35,240
Speaker 1: visit your freezers. Right So, what are the big open

820
00:44:35,320 --> 00:44:36,680
Speaker 1: questions in your field right now?

821
00:44:36,960 --> 00:44:37,160
Speaker 5: Oh?

822
00:44:38,160 --> 00:44:40,680
Speaker 3: Oh boy? Some of the ones we touched on earlier

823
00:44:40,840 --> 00:44:44,720
Speaker 3: is like, what really limits size in animals? What limit

824
00:44:44,800 --> 00:44:48,680
Speaker 3: speed in animals? How flexible is that? How flexible are

825
00:44:48,680 --> 00:44:52,800
Speaker 3: those things? And how has that flexibility or the constraints

826
00:44:52,840 --> 00:44:56,600
Speaker 3: on animals evolved over time with like changes in ecosystems,

827
00:44:56,680 --> 00:45:00,359
Speaker 3: changes in animal tissues, or what have you. I think

828
00:45:00,360 --> 00:45:03,960
Speaker 3: there's still a lot that we can learn about what

829
00:45:04,080 --> 00:45:07,439
Speaker 3: the range of possibilities is in animals. And the goal

830
00:45:07,480 --> 00:45:10,520
Speaker 3: of my work that I've been really pushing on for

831
00:45:10,560 --> 00:45:13,120
Speaker 3: a long time, and I think a good general goal

832
00:45:13,160 --> 00:45:17,399
Speaker 3: for paletology is that palingtology should be able to teach

833
00:45:17,480 --> 00:45:21,640
Speaker 3: us things about biology and contribute to theories in biology

834
00:45:21,680 --> 00:45:24,120
Speaker 3: as a whole, not just be a slave to biology

835
00:45:24,160 --> 00:45:27,480
Speaker 3: where we're always looking to biology, looking to nature today

836
00:45:27,560 --> 00:45:31,719
Speaker 3: to try to solve questions about the past, but contributing

837
00:45:31,760 --> 00:45:36,799
Speaker 3: to broader theories about animals in general through looking at

838
00:45:36,800 --> 00:45:39,680
Speaker 3: the past and the present. So like my studies of

839
00:45:39,760 --> 00:45:42,960
Speaker 3: how big animals are limited by their size and how

840
00:45:43,000 --> 00:45:46,080
Speaker 3: the athletic they can be, it's all about all these

841
00:45:46,120 --> 00:45:48,319
Speaker 3: different groups living in extinct. I don't care if they're

842
00:45:48,320 --> 00:45:50,640
Speaker 3: living or extinct. I want to know what the principles

843
00:45:50,640 --> 00:45:53,319
Speaker 3: are that we can derive from them, and I want

844
00:45:53,360 --> 00:45:56,279
Speaker 3: to be able to prove to colleagues, regardless of what

845
00:45:56,360 --> 00:45:59,160
Speaker 3: field they're in, that I can answer those questions and

846
00:45:59,239 --> 00:46:01,520
Speaker 3: that we can learn something from a t rex that

847
00:46:01,600 --> 00:46:04,760
Speaker 3: isn't just you know, a variant of what we already

848
00:46:04,760 --> 00:46:08,160
Speaker 3: could learn from an elephant. That's a selfish example, just

849
00:46:08,840 --> 00:46:11,440
Speaker 3: explaining what I would say is big questions.

850
00:46:11,640 --> 00:46:14,840
Speaker 2: Do you think there are big surprises waiting for us underground?

851
00:46:14,920 --> 00:46:17,000
Speaker 2: You know? Is it possibility we could find a new

852
00:46:17,400 --> 00:46:20,800
Speaker 2: huge dinosaur that blows your mind? I mean, we found

853
00:46:20,800 --> 00:46:25,200
Speaker 2: like the Supersaurus and the Gigantosaurus and the Titanosaurus. Is

854
00:46:25,239 --> 00:46:28,120
Speaker 2: there the possibility of some like uber Megasaurus to be

855
00:46:28,160 --> 00:46:30,000
Speaker 2: discovered or do you think we've sort of maxed out

856
00:46:30,040 --> 00:46:31,760
Speaker 2: the size of dinosaurs.

857
00:46:31,320 --> 00:46:33,080
Speaker 3: Or a hollow earth like filled.

858
00:46:32,800 --> 00:46:35,440
Speaker 2: With giants exactly.

859
00:46:37,200 --> 00:46:39,520
Speaker 3: No on the latter point, A very firm no there.

860
00:46:39,520 --> 00:46:43,200
Speaker 3: But in terms of finding giant dinosaurs, yeah, I mean

861
00:46:43,280 --> 00:46:47,240
Speaker 3: over the last twenty thirty years, there have been larger

862
00:46:47,280 --> 00:46:50,279
Speaker 3: and larger sore pods that have been found, including more

863
00:46:50,280 --> 00:46:53,160
Speaker 3: and more complete ones. There's like seven skeletons of one

864
00:46:53,440 --> 00:46:56,840
Speaker 3: really giant animal called protagotitan that I've worked with a

865
00:46:56,840 --> 00:46:59,239
Speaker 3: small amount with colleagues on and that's one of the

866
00:46:59,280 --> 00:47:02,560
Speaker 3: biggest and animals ever. It's up there as a contender.

867
00:47:02,600 --> 00:47:05,719
Speaker 3: And yeah, to have sudden skeletons of that is really remarkable.

868
00:47:06,280 --> 00:47:12,520
Speaker 3: But discoveries are pushing the boundaries continually. And we suspected

869
00:47:12,560 --> 00:47:17,000
Speaker 3: that dinosaurs were feathered, but it wasn't until almost thirty

870
00:47:17,080 --> 00:47:20,120
Speaker 3: years ago that we actually found out that many dinosaurs

871
00:47:20,160 --> 00:47:24,640
Speaker 3: were from some pretty startling discoveries in China. So we

872
00:47:24,760 --> 00:47:27,239
Speaker 3: know from the history of paleontology that there can be

873
00:47:27,280 --> 00:47:32,959
Speaker 3: shocks there in terms of revolutions that can happen. Going

874
00:47:33,000 --> 00:47:37,720
Speaker 3: up and digging fossils is always the primary lifeblood of paleontology.

875
00:47:37,760 --> 00:47:40,279
Speaker 3: That's where discoveries ultimately come from. I don't do that

876
00:47:40,360 --> 00:47:42,840
Speaker 3: kind of work. It's just not my skill set. I

877
00:47:42,920 --> 00:47:45,319
Speaker 3: do the more lab or computer based work where I'm

878
00:47:45,320 --> 00:47:48,520
Speaker 3: trying to unravel what it all means. But yeah, I'm

879
00:47:48,520 --> 00:47:50,080
Speaker 3: sure there's more surprises to come.

880
00:47:50,360 --> 00:47:52,040
Speaker 1: It's time for the alien question. Daniel.

881
00:47:53,480 --> 00:47:55,799
Speaker 2: Well, it's always inspiring. I think for listeners to hear

882
00:47:55,880 --> 00:47:59,759
Speaker 2: that there are lots of mysteries left to unravel. And

883
00:48:00,120 --> 00:48:02,839
Speaker 2: mystery I think about a lot is what life might

884
00:48:02,920 --> 00:48:05,440
Speaker 2: look like on another planet. And I wonder if you

885
00:48:05,520 --> 00:48:09,040
Speaker 2: might speculate with us, because everything you've learned about comes

886
00:48:09,080 --> 00:48:11,440
Speaker 2: from the experience here on Earth, and we don't know,

887
00:48:11,520 --> 00:48:14,879
Speaker 2: of course, if this is typical, if we've explored all

888
00:48:14,920 --> 00:48:18,840
Speaker 2: the effective possibilities that biology allows, or if life on

889
00:48:18,880 --> 00:48:21,880
Speaker 2: Earth went down some weird little nook and most of

890
00:48:21,880 --> 00:48:24,279
Speaker 2: life in the university is different. It's all weird and

891
00:48:24,320 --> 00:48:27,360
Speaker 2: hollow bubbles or something. So, if we are about to

892
00:48:27,440 --> 00:48:30,720
Speaker 2: land on an alien planet and you're a biologist on board,

893
00:48:30,800 --> 00:48:34,000
Speaker 2: what are you expecting to see in terms of large

894
00:48:34,040 --> 00:48:37,120
Speaker 2: animals on an alien planet? And you know, as an

895
00:48:37,120 --> 00:48:40,960
Speaker 2: efficionado of monster movies, feel free to go weird and

896
00:48:41,080 --> 00:48:42,480
Speaker 2: crazy in science fiction.

897
00:48:42,600 --> 00:48:44,680
Speaker 3: What would I expect to see? I'd be surprised if

898
00:48:44,680 --> 00:48:46,880
Speaker 3: there are large animals, Well, it depends on what we

899
00:48:46,920 --> 00:48:49,239
Speaker 3: would know about the planet if it had been a

900
00:48:49,320 --> 00:48:53,360
Speaker 3: place where the environment had been fairly stable for some time,

901
00:48:53,640 --> 00:48:56,600
Speaker 3: given a long enough time for large animals to have

902
00:48:56,719 --> 00:49:00,400
Speaker 3: evolved at all and not having mass extinctions screw it

903
00:49:00,440 --> 00:49:05,120
Speaker 3: all up, then I might be more inclined to expect that.

904
00:49:05,320 --> 00:49:09,080
Speaker 3: But anyway, all right, if I was expecting a big animal,

905
00:49:10,000 --> 00:49:13,360
Speaker 3: well I'd be wondering what's supporting itself with? Are we

906
00:49:13,400 --> 00:49:16,719
Speaker 3: going to learn something entirely new about supportive tissue, like

907
00:49:16,840 --> 00:49:19,680
Speaker 3: is it gonna just not have anything remotely like muscle

908
00:49:20,360 --> 00:49:23,560
Speaker 3: some other thing? Is it even a protein that's it's

909
00:49:23,640 --> 00:49:27,719
Speaker 3: using to provide an active support or is it I

910
00:49:27,760 --> 00:49:32,399
Speaker 3: don't know this boy. The boundaries that the possibilities there

911
00:49:32,440 --> 00:49:36,080
Speaker 3: get so interesting, and certainly depends on whether you are

912
00:49:36,239 --> 00:49:41,000
Speaker 3: a carbon based life form ultimately or silicon or whatever

913
00:49:41,080 --> 00:49:44,560
Speaker 3: else they're using as their building box. And if they

914
00:49:44,560 --> 00:49:47,440
Speaker 3: have DNA, what kind of DNA? Is it? Double banded,

915
00:49:47,520 --> 00:49:51,640
Speaker 3: triple banded? Is it to following the same curvature as

916
00:49:51,800 --> 00:49:56,000
Speaker 3: our DNA or the opposite handedness? Does that even matter?

917
00:49:56,040 --> 00:49:59,240
Speaker 3: I don't know? Or are they using something totally different

918
00:49:59,280 --> 00:50:02,920
Speaker 3: as heret material that would be a game changer for

919
00:50:03,760 --> 00:50:07,560
Speaker 3: what evolution can even do. But I'm not sure I

920
00:50:07,560 --> 00:50:10,239
Speaker 3: can give you a very satisfying answer for what I

921
00:50:10,239 --> 00:50:15,680
Speaker 3: would expect in terms of animal life. It's so wide

922
00:50:15,760 --> 00:50:17,560
Speaker 3: open for possibilities.

923
00:50:17,960 --> 00:50:20,719
Speaker 2: That's a pretty satisfying answer, honestly, to think that it's

924
00:50:20,960 --> 00:50:22,800
Speaker 2: very wide open and we could be very surprised.

925
00:50:22,960 --> 00:50:26,160
Speaker 3: I'd still expect the fundamental principle of the square cube

926
00:50:26,239 --> 00:50:29,200
Speaker 3: LA probably would hold if you've got a wide enough

927
00:50:29,239 --> 00:50:32,760
Speaker 3: size range of animals that ultimately, if you push size

928
00:50:32,760 --> 00:50:36,440
Speaker 3: to it large enough extreme on land where gravity is

929
00:50:36,520 --> 00:50:39,839
Speaker 3: affecting organisms, then they're going to hit a limit and

930
00:50:39,840 --> 00:50:41,440
Speaker 3: something's going to have to change. They're going to have

931
00:50:41,520 --> 00:50:45,120
Speaker 3: to slow down or really change their shape or something

932
00:50:45,239 --> 00:50:48,320
Speaker 3: like that. That would be a prediction that's really rooted

933
00:50:48,360 --> 00:50:53,120
Speaker 3: in physics and fundamental theory of animal size and shape change.

934
00:50:53,560 --> 00:50:57,000
Speaker 3: I'd feel pretty confident in that, but I don't know.

935
00:50:57,080 --> 00:51:00,279
Speaker 3: Biology can screw things up, and maybe they change. There

936
00:51:00,320 --> 00:51:02,399
Speaker 3: are molecules that they're made of as they go from

937
00:51:02,400 --> 00:51:04,719
Speaker 3: small to big and just break the rules of what

938
00:51:04,719 --> 00:51:05,560
Speaker 3: we think is normal.

939
00:51:06,160 --> 00:51:08,000
Speaker 1: Leave it on a high note here for Daniel, we

940
00:51:08,040 --> 00:51:10,120
Speaker 1: can be sure about the physics, but the biology can.

941
00:51:10,040 --> 00:51:14,440
Speaker 2: Screw things up all right, As usual with biology, it.

942
00:51:14,480 --> 00:51:19,239
Speaker 1: Depends its Yeah, so that's the rule in ecology at least.

943
00:51:19,520 --> 00:51:19,839
Speaker 5: All right.

944
00:51:19,880 --> 00:51:21,919
Speaker 1: Well, John, thank you so much for being on the show.

945
00:51:22,000 --> 00:51:24,399
Speaker 1: That was a ton of fun and I really hope

946
00:51:24,400 --> 00:51:26,120
Speaker 1: I get to check out your freezer one day.

947
00:51:26,200 --> 00:51:28,480
Speaker 3: Please do a comment. Yes, it's an open invitation for

948
00:51:28,640 --> 00:51:28,959
Speaker 3: you both.

949
00:51:29,680 --> 00:51:32,480
Speaker 2: John ever serves you dinner, you should ask what's innsburger?

950
00:51:36,760 --> 00:51:37,439
Speaker 2: Or don't ask?

951
00:51:38,160 --> 00:51:39,640
Speaker 1: Yeah, I think don't ask is the way to go.

952
00:51:39,920 --> 00:51:41,240
Speaker 3: You can ask, I won't be offunded.

953
00:51:49,280 --> 00:51:52,760
Speaker 1: Daniel and Kelly's Extraordinary Universe is produced by iHeart Reading.

954
00:51:53,040 --> 00:51:55,560
Speaker 1: We would love to hear from them, We really would.

955
00:51:55,760 --> 00:52:00,600
Speaker 2: We want to know what questions you have about this extraordinary.

956
00:52:00,560 --> 00:52:03,520
Speaker 1: Want to know your thoughts on recent shows, suggestions for

957
00:52:03,600 --> 00:52:06,680
Speaker 1: future shows. If you contact us, we will get back

958
00:52:06,719 --> 00:52:06,880
Speaker 1: to you.

959
00:52:07,120 --> 00:52:10,640
Speaker 2: We really mean it. We answer every message. Email us

960
00:52:10,680 --> 00:52:13,520
Speaker 2: at Questions at Danielankelly dot org.

961
00:52:13,719 --> 00:52:15,840
Speaker 1: You can find us on social media. We have accounts

962
00:52:15,960 --> 00:52:19,920
Speaker 1: on x, Instagram, Blue Sky and on all of those platforms.

963
00:52:19,920 --> 00:52:22,840
Speaker 1: You can find us at D and K Universe.

964
00:52:23,000 --> 00:52:24,520
Speaker 2: Ophye right to us