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Speaker 1: Hey, everybody, Welcome to Creature feature, the show where we

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Speaker 1: take a little sightseeing trip inside the minds of humans

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Speaker 1: and animals, looking at some weird behaviors, taking photos of

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Speaker 1: us next to the prefrontal cortex, and riding on the

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Speaker 1: Hippocampus coaster. Today we're talking about city slickers, who do

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Speaker 1: animals cope with human cities? What are some of the

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Speaker 1: ways animals have adapted to human society? And did we

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Speaker 1: domesticate dogs or did dogs domesticate us? And we're definitely

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Speaker 1: not sick of these mother heckan dogs on this mother

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Speaker 1: heck and train. We'll discuss this and more as we

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Speaker 1: answer the age old question how much trash can you

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Speaker 1: fit inside a seagull? Spoiler A lot? And later I'll

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Speaker 1: be talking to Dr Greg Paully, a real life researcher

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Speaker 1: and curator at the Natural History Museum of Los Angeles County.

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Speaker 1: Joining me today is Katie Willard, actor, writer, producer, cat

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Speaker 1: owner and snail superhero. Hello, quickly, explain why I call

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Speaker 1: you a snail superhero. This is very cute because ever

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Speaker 1: since I was a kid um seeing snail smushed on

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Speaker 1: the sidewalk made me so sad and so ever since

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Speaker 1: I was a kid. If I see a snail on

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Speaker 1: the sidewalk, obviously going in a line, I pick them

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Speaker 1: up and take them to the other side off the

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Speaker 1: sidewalk so they don't get crushed. I like to imagine

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Speaker 1: they've just kind of created a whole religion around you,

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Speaker 1: as like this being that's like the savior. I mean,

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Speaker 1: that's the ultimate goal is made to be the head

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Speaker 1: of some of a of a religion, some kind of

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Speaker 1: snail religion. Yeah, it's great because like I don't have to.

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Speaker 1: I won't go to jail because I'm a cull latter.

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Speaker 1: One of the most defining characteristics of humans is our

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Speaker 1: ability to form society, get enough of us together and

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Speaker 1: well from entire cities bustling with connections. But what happens

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Speaker 1: when you have a phobia of cities themselves. One group

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Speaker 1: of anthropophobia patients coped with their phobia groups by forming

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Speaker 1: a club. It sounds like someone with arachnophobia jumping into

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Speaker 1: a bathtub full of spiders, but it's actually one of

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Speaker 1: the most logical ways to treat their phobia of society.

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Speaker 1: In nine seventy a group of anthropophobic men were discharged

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Speaker 1: from a private therapeutic institute in Tokyo. They started meeting

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Speaker 1: at coffee shops to discuss their fear of socializing. It

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Speaker 1: may sound oxymoronic, but it makes sense when you think

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Speaker 1: about it. They all shared a common fear, so they

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Speaker 1: could bond and discuss the fear in a way that

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Speaker 1: felt more like therapy than socializing, tricking their brains into

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Speaker 1: allowing them to form what a mounted to a social

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Speaker 1: club they wittingly are not also treated themselves with exposure therapy.

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Speaker 1: Remember how I joked about jumping in a bath with

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Speaker 1: the spiders. That's actually not a bad way to treat

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Speaker 1: arachnophobia or any other phobia. When you expose yourself to

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Speaker 1: your fear repeatedly and find you survive it, the fear

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Speaker 1: will go away. Maybe I should jump in a bathful

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Speaker 1: of the concept of death. Anyways, this club for clinical

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Speaker 1: misanthropes was actually a genius way to hack their brains

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Speaker 1: and cope with their peers. But how do animals cope

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Speaker 1: with human cities. Society is not made for them and

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Speaker 1: in fact, is often completely antithetical to their survival as well.

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Speaker 1: Discuss some animals can't hack it in the big city,

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Speaker 1: but others, like the anthropophobic men who formed a club,

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Speaker 1: have found incredible loopholes that allows them to exploit a hostile,

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Speaker 1: human dominated world and thrive. Anyways, Katie, uh, what would

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Speaker 1: be your response to robots slowly taking over society? And

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Speaker 1: they wouldn't be like the cool robots who are like

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Speaker 1: as Katie willert is to snails. Robots are not to us.

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Speaker 1: They don't like pick us up and like put us

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Speaker 1: on a little soft patch of grass. They are big

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Speaker 1: robots who just really don't give a care about us.

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Speaker 1: I guess I would probably go off into the nature

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Speaker 1: where there is no far away from where they are

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Speaker 1: and just continued to live a no matic existence. I

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Speaker 1: think it's less of a like fleeing scared thing and

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Speaker 1: more of just like, oh, it's time to move again,

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Speaker 1: It's time to go just start using rocks is toilets again.

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Speaker 1: Let's just get out of the get out of dodge,

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Speaker 1: Let's go to you know what. Bakersfield was the first

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Speaker 1: place in Pine count My mom grew up in Bakersfield.

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Speaker 1: And it's like when they rerouted the highway so it

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Speaker 1: didn't go through there, it's just like it's like, well,

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Speaker 1: it's still nineteen sixty. Yeah. I ever now I went

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Speaker 1: to the Current County Oil Museum. One. Yeah, because Rolling

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Speaker 1: Road Show, which does like screenings of movies in their locations,

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Speaker 1: did there will be blood at Current County Oil Museum

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Speaker 1: because that was where Paul Thomas Anderson did a lot

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Speaker 1: of his like research for it. Interesting. Um, but yeah,

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Speaker 1: it seems like just there's just not a lot. It's

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Speaker 1: just not a lot going on. It's going to be

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Speaker 1: the sixties forever. And you know that's that's line. That's fine,

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Speaker 1: it works. Other than the racism, that's okay, you know,

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Speaker 1: just a little bubble um. I feel like if for me,

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Speaker 1: I would feel like it's inevitable that the robots are

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Speaker 1: going to find me in the woods or in Bakersfield,

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Speaker 1: So like I would, uh, I think that I would

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Speaker 1: try to ingrace sheet myself as like a pet, like

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Speaker 1: like you can comb my hair and give me treats. Oh,

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Speaker 1: and I snuggle and I snuggle. Yeah. I will wear

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Speaker 1: ridiculous clothing at your behest. I will put on a cape.

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Speaker 1: I will poop on command. Take me outside, I'll poop anyway. Yeah,

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Speaker 1: I don't I guess isn't that the path of all animal,

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Speaker 1: you know, all eventually domesticating animals, run, run, run, and

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Speaker 1: then then oh you'll feed me, you know, Okay, I'll

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Speaker 1: hang outs and you give me enough corn and I'll

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Speaker 1: just lie down on my back. Well, like you think

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Speaker 1: of it, just a ferrel. I mean I have plenty

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Speaker 1: of friends who have ferrell who now have feral cats

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Speaker 1: that live in their house, like cats that would not

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Speaker 1: be anywhere near them, and then we eat a little food, yeah,

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Speaker 1: and then get a little kind of like squatting. I

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Speaker 1: feel like cats are squatters. Yeah, they can pretty much

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Speaker 1: just be anywhere. But so it's interesting. What I'm getting

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Speaker 1: at here with my robots thing is that there are

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Speaker 1: different ways that animals respond to urbanizations. So human cities

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Speaker 1: encroaching on their habitat. There's um avoiders, which is what

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Speaker 1: you would be if you was animals, if I was

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Speaker 1: all those animals, and so they are not able to

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Speaker 1: adapt to human environments, and so they avoid urbanized areas,

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Speaker 1: they avoid contact with humans, and they really only make

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Speaker 1: appearances in the city if they're migrating or fleeing their

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Speaker 1: shrinking habitat. And they're usually unable to adapt due to

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Speaker 1: very specialized survival reproductive or feeding strategy, or like they

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Speaker 1: come into conflict with humans. And then there's a few

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Speaker 1: other ways that animals respond to urbanization. There's adapters and exploiters,

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Speaker 1: and they respond by changing their behavior or physiology to

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Speaker 1: better fit their new human altered environments. So they try

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Speaker 1: to use human cities as best as they can. What

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Speaker 1: I see in my head is just that gift of

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Speaker 1: the raccoon going up on the porch to the cat

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Speaker 1: food and getting a hand scoop of the cat and

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Speaker 1: then running away on the tiny legs. But I love

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Speaker 1: about raccoons, and as we'll talk about in a little

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Speaker 1: bit of seagulls, is that when they do the stealing

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Speaker 1: they do a burglary, they have that little jaunty runaway

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Speaker 1: where they're like, gotta go go, gotta go out of here. Well, yeah,

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Speaker 1: raccoons are that. What I think is funny about raccoons

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Speaker 1: do is like most of the time it's like, Okay,

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Speaker 1: I gotta grab the trash, get out of here, like

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Speaker 1: we gotta go. But then there are some that are

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Speaker 1: just like I mean, my mom and I once almost

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Speaker 1: got trapped in our subterranean parking garage because there were

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Speaker 1: two raccoons on the stairs that were the under the stairs,

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Speaker 1: that were the size of golden retriever, Like they were

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Speaker 1: really big and like, I don't think I've ever been

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Speaker 1: worried about like a raccoon because most of the time

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Speaker 1: they scurry right like when you get near there, like

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Speaker 1: oh no, no, not worth it, like abort mission, let's

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Speaker 1: go away. Um. We walked up saw them and they

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Speaker 1: just stood there and she stared at us like, Um,

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Speaker 1: a raccoons stands up and is bold is just kind

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Speaker 1: of scary. But that's not that's not good news because

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Speaker 1: it doesn't go in my head. Was like, oh, the

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Speaker 1: animals are just afraid of us, Like they're more afraid

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Speaker 1: of you than you are. A bold raccoon is one

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Speaker 1: to be feared. My favorite bold raccoon story is one

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Speaker 1: of my mom's best friends, Donna Marie, was sleeping one

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Speaker 1: night and she heard noise in her backyard and she

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Speaker 1: was like, so she turned on the back of the

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Speaker 1: lights to the backyard and looked out over her balcony

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Speaker 1: to her pool and there was a family of five

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Speaker 1: raccoons swimming in her pool, just having a family, just

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Speaker 1: chilling doing swimming in the swimming pool and she just

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Speaker 1: turned off the light and went back to bed. I mean,

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Speaker 1: no one else is using it time. I know it's

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Speaker 1: offsets raccoon swim. Yeah. Uh so that would be an

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Speaker 1: urban adapter for sure. That is the most adaptive adaptation. Kids,

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Speaker 1: Let's go to the pool we're going to. It's just

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Speaker 1: like it's like a doofy Dad and like like a

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Speaker 1: Marge like mom, where it's like, well, well we'll just

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Speaker 1: use their pool them and then the kids are like

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Speaker 1: me when Kim Apple or whatever. Just the raccoon family. God,

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Speaker 1: that's going to be a cartoon, I'm sure. But let's

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Speaker 1: talk about some of the unfortunate urban avoiders. And there's

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Speaker 1: one that's uh native to Los Angeles, the mountain lion. Yeah.

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Speaker 1: And have you ever seen a mountain lion in person?

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Speaker 1: I have not. I've seen tracks. And I've also heard like,

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Speaker 1: oh they just saw what, Like if I was in

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Speaker 1: Griffith or whatever, it'd be like, oh, they saw one

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Speaker 1: like yesterday, it was like when you were out there. Yeah,

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Speaker 1: but it's I mean, I've never seen one in person either. Uh.

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Speaker 1: And it's I think it's just so rare because they'll

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Speaker 1: avoid the city. They don't want no part of it.

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Speaker 1: And like I said, it's because I mean they will

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Speaker 1: come into conflict with humans and they just they're too

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Speaker 1: specialized of an animal to really be able to adapt

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Speaker 1: like a raccoon can. So I want to tell you

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Speaker 1: the story about Griffith Park's lonely single mail metal Um.

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Speaker 1: He's seeking hot cougars in his area, but there aren't any.

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Speaker 1: He's the only one. So the National Park Service named

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Speaker 1: him P twenty two UM, which is I wish it

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Speaker 1: stood for something cool like predator twenty two, but I

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Speaker 1: think it's just like like how many ladies whose bang

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Speaker 1: Like he's really super handsome. He's like He's like it

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Speaker 1: is hottest cougar ever. Um. But now it's just like

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Speaker 1: the like sequence in which they market Yeah. UM. So

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Speaker 1: he traveled from the Santa Monica Mountains to try to

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Speaker 1: find his own territory, and in the wild they require

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Speaker 1: a really large toys. I'm Elmer Fudd all of a sudden,

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Speaker 1: um over two hundred square miles uh is for like

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Speaker 1: one male and his current range in Griffith Park is

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Speaker 1: nine square miles. It's tiny. It's like trying to live

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Speaker 1: in San Francisco. I'm all right, it's hard. It's hard

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Speaker 1: to get by these days. It's hard. It's very high expensive, expensive,

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Speaker 1: it's hard to date. Hard in this city. I feel

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Speaker 1: like twenty two is just like the millennial experience just

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Speaker 1: in Mountain Lion from Can I ask you a question?

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Speaker 1: So because there were cubs recently born, I think in

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Speaker 1: the Mounta Lion cubs because there used to be female

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Speaker 1: there was like was it right? Wasn't there? I don't

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Speaker 1: know if it was in Grip Parkrint, San would be

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Speaker 1: probably the San Monica Mountains, Yeah, okay, because yeah, something

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Speaker 1: had happened during the fires. I think where they were

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Speaker 1: like really nervous that the cups had been killed. Yeah,

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Speaker 1: I think that was the Santa Monica Mountains Griffith Park.

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Speaker 1: The issue with that why he's so isolated is he

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Speaker 1: surrounded by freeway. There's no way to get and he

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Speaker 1: actually had traveled with a few of his companions but

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Speaker 1: then they got killed by vehicles, so he was like

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Speaker 1: the only one to survive. He's got a tragic Disney

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Speaker 1: back story. Um, and so yeah, there's no mate for him,

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Speaker 1: and he's able to survive by eating the raccoon coyote. Uh.

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Speaker 1: And also dear, And it's interesting because the reason dear

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Speaker 1: can drive is that we have these big cemeteries and

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Speaker 1: golf courses, which is like, as you may know, like

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Speaker 1: the only green parts in Los Angeles is either rich

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Speaker 1: people golf courses or dead people cemeteries. Um. But it's

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Speaker 1: actually there's like a few creepy stories of people like

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Speaker 1: they'll give the flowers to their their dead loved ones

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Speaker 1: in the cemeteries, deers will come to eat them, and

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Speaker 1: then the mountains p. Twenty two will just like like

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Speaker 1: just like metal cup and there and like just just wait,

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Speaker 1: like I imagine like you're grieving. You're like, oh man,

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Speaker 1: look it's maybe it's Grandpa's spirit come in the form

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Speaker 1: of a deer and he's eating the flowers and you're like, look,

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Speaker 1: Grandpa's visiting us. And then this mountains just like guts

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Speaker 1: everywhere and it's like, I don't look, children, Grandpa's dying again.

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Speaker 1: And yeah, the spirit there's time is souls dead. Now.

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Speaker 1: My my best friend Sheet puts flowers on Mama Cass's

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Speaker 1: grave at Fort Lawn and at the flower Place, they

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Speaker 1: have like a specific they they have flowers that you

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Speaker 1: don't put in like offerings for grave sites because of

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Speaker 1: deer like flowers that if deer eight their plants of

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Speaker 1: deer eate them, it would poison the deer. Oh yeah,

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Speaker 1: that's a good differ, yeah, because there are like certain

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Speaker 1: flowers that are inedible, and like literally that would suck

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Speaker 1: even worse. Like you're visiting your grandma's grave and like

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Speaker 1: a deer comes up and it's like, oh, it's so

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Speaker 1: lovely the circle of life and just starts vomiting like

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Speaker 1: a frat bro just like before you leave the flowers,

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Speaker 1: and then you come back a week later and there's

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Speaker 1: just a dead deer you just sacrifice on your grandmother's grave.

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Speaker 1: So actually, also speaking of being poisoned. P. Twenty two

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Speaker 1: has faced some troubles because he eats you know, rodents

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Speaker 1: and stuffy. They're pretty opportunistic. They'll eat any meat they

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Speaker 1: can get their hands on. But he was found with

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Speaker 1: rodenticide in his bloodstream a few times when like the

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Speaker 1: conservationists will capture him and check up on his health

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Speaker 1: and um and like in high enough doses, like the

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Speaker 1: rodenticide can kill mountain lions. But actually, like just for him,

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Speaker 1: it caused him to have match right, right, because it

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Speaker 1: compromises their immune systems UM, and then like it makes

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Speaker 1: it harder for them to fight maange. But he is

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Speaker 1: actually I think so as of now, I think he's

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Speaker 1: made a full recovery and he's doing pretty well. Two

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Speaker 1: is scrappy. He is scrappy, and it's I feel so

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Speaker 1: bad firm because like he's doing all these things, crapping

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Speaker 1: on by but there's just like he is never going

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Speaker 1: to find I made. Is it a situation where it's

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Speaker 1: too detrimental to the ecosystem to introduce Yeah, I think

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Speaker 1: that they don't really want to miss, Like they don't

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Speaker 1: want to transport a female line who's doing well and

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Speaker 1: like the Santa Monica Mountains because Griffith Park is not

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Speaker 1: really a good zone. And it's also like I think

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Speaker 1: if they took him and put him in the Santa

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Speaker 1: Monica Mountains, he in another male mountain line might just

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Speaker 1: like kill each other. He moved for a reason, right,

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Speaker 1: So that's an avoid er. UM. So now let's talk

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Speaker 1: about adapters and exploiters because this is really interesting. Adapters

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Speaker 1: are a little less aggressively successful than UH exploiters, but

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Speaker 1: they can manage in urban areas. So an example would

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Speaker 1: be bobcats. You know, they live on the periphery of

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Speaker 1: urban areas. They are smaller. There's not really conflict with

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Speaker 1: humans as much because they're not big. Humans aren't like, oh,

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Speaker 1: you know a bobcat, gotta kill it um and like, uh,

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Speaker 1: they feed on rodents and small mammals, and rodents are exploiters.

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Speaker 1: They do super well in cities. Yeah, pizza at Pizza

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Speaker 1: for that little what was it a chinchilla? It was

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Speaker 1: some rodent in Australia that got into the bakery and

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Speaker 1: made all the pastries until it couldn't mean yes, that

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Speaker 1: was actually an Australian opossum. Yeah, yeah, and it was

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Speaker 1: in like a box of jelly doughnuts. And Australian opossums

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Speaker 1: are way cuter than American possums, Like American possums are

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Speaker 1: just such like their nightmare the grunge versions of like

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Speaker 1: the cute, fluffy Australian opossums. I just think there's so misunderstanding.

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Speaker 1: People are so mean. They just they're trying their best.

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Speaker 1: They do. They are really scary though, the way they

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Speaker 1: just come back to life and just like yeah, but

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Speaker 1: they are they are great there. I do like them too,

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Speaker 1: so you know the bugcats do. Okay, they still face

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Speaker 1: some threats from urbanization. Like we talked about the highway

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Speaker 1: system and freeways and roads really screw up with animals

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Speaker 1: because like what happens is it's called habitat fragmentations. So

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Speaker 1: you know, they try to cross the highway, they could

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Speaker 1: get killed, and so it creates these genetic islands basically

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Speaker 1: where they have these kind of this genetic bottleneck where

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Speaker 1: they can't really cross the freeways, so they just have

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Speaker 1: this smaller community where it's not as much genetic diversity

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Speaker 1: and they can be taken out more quickly essentially by

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Speaker 1: genetic or whatever, right right, and or just come out weird,

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Speaker 1: you know, with like six fingers off like a lazy eye.

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Speaker 1: I well, I think as in Norway or the Netherlands

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Speaker 1: or somewhere I can't remember where, but they have those

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Speaker 1: animal crossing high like overpasses that go from one side

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Speaker 1: of a territory to another so that animals are able

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Speaker 1: to cross over without risk of being hit by cars. Yeah,

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Speaker 1: that's pretty cool. That's also sort of like in Japan

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Speaker 1: they're the snow monkeys who um, they use telephone wires

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Speaker 1: to cross like when it's snowy because they just don

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Speaker 1: won't get there. It's too cold. You're going to telephone wires.

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Speaker 1: I mean, there's a really funny video you could just

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Speaker 1: if you look like snow monkeys Japan, Like, you'll find

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Speaker 1: a video of them hours of joy. Well, and and

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Speaker 1: they're they like, I'll go in a little a neat,

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Speaker 1: little line on these telephone wires. It's just like you

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Speaker 1: can just hear that. It's really cute. So here's an

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Speaker 1: urban exploiter that everyone knows and loves. The seagull. It

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Speaker 1: is just a trash compactor of an animal. It is

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Speaker 1: so opportunistic. It'll eat fish, human food, garbage, cat food

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Speaker 1: in small rodents, eggs, doritos, small reptiles, smaller birds, sandwiches,

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Speaker 1: vats of tiki masala, hotdogs, pigeons, potato chips, tinfoil coins, socks,

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Speaker 1: human fingers, small babies, cookies, and Claire's house keys, their

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Speaker 1: own babies, flying rats. I'm from San Diego, so like

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Speaker 1: I grew up in a beach community and seagulls are

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Speaker 1: just yeah, they are. They're so aggressive too. If you

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Speaker 1: go to the beach and you have any food, they

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Speaker 1: will swarm you and they're they're very so it's interesting

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Speaker 1: because they're highly social animals, and this is what kind

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Speaker 1: of is distinctive about them versus like a mountain lion.

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Speaker 1: They're small, highly mobile, very socially intelligent, and they have

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Speaker 1: this mobbing behavior where you know, like they just like

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Speaker 1: in the hitchcock birds, they'll surround you, they'll bully other

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Speaker 1: birds out of their territory, and so it like really

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Speaker 1: helps them in a city because they can just kind

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Speaker 1: of bully their way into these niche feeding areas. And

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Speaker 1: they also will eat literally anything. The tiki masala thing mentioned,

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Speaker 1: that's not a joke. There was there's a picture of

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Speaker 1: the seagull who landed in a vat of tiki masala

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Speaker 1: and he's like bright orange. It's a pretty cute. Probably

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Speaker 1: put that on Twitter or something. What a piece of garbage?

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Speaker 1: Can you imagine if you like got some tika masala

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Speaker 1: and you're like, tastes a little tastes like bird, tastes

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Speaker 1: like birds. This tastes like bird. So they're very inquisitive.

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Speaker 1: They'll boldly investigate their environment and they'll go to landfills

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Speaker 1: and just cram themselves full of garbage and trash like

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Speaker 1: they've opened up seagulls that have been eating at landfills

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Speaker 1: and there's just like tinfoil plastic like pieces of metals POGs. Probably, Yeah,

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Speaker 1: I think about with seagulls. Like I grew up in

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Speaker 1: La Joya and San Diego, and my high school is

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Speaker 1: primarily outdoors. There's a lot of southern California schools are

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Speaker 1: because the weather is nice, so you can want for

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Speaker 1: building a building. It's not a huge deal. And we

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Speaker 1: a huge odd where you'd eat lunch, and I think

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Speaker 1: lunch was like at noon, and so around one they

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Speaker 1: would start to circle because they knew that lunch would

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Speaker 1: be over and then they could descend. And then once

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Speaker 1: that bell rang, they started to descend, and so we'd

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Speaker 1: all you'd have to like run go with your your

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Speaker 1: binder on your head because they start shitting. Yeah, that's

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Speaker 1: the funny part about him is the uncontrollable crap just everywhere,

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Speaker 1: just raining down seagulls. They don't have the cute little

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Speaker 1: tin like bird duke. You know, it's like big water

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Speaker 1: with it's like toothpasted, like brown, big glob of stinky toothpaste.

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Speaker 1: But then on days where we had um, like half

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Speaker 1: days for whatever reason. Uh, and we'd get out, they'd

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Speaker 1: still on the dot at one start to circle even

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Speaker 1: though no one was at school anymore. We should break legs. Yeah,

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Speaker 1: they are. They are mobs. They will form literal mobs

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Speaker 1: and they will attack other birds. And they're actually really intelligent.

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Speaker 1: So like, you got to respect the seagull because they um,

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Speaker 1: they can understand each other's warning vocalizations, and they even

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Speaker 1: learn each other's personalities. So if you have like a

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Speaker 1: kind of twitchy seagull who's like always doing false alarms,

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Speaker 1: they learned to ignore them, like like the seagull who

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Speaker 1: cried um, and they'll listen more to the ones that

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Speaker 1: are like the trustworthy seagulls. Like we were like, m hmm,

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Speaker 1: this is a situation in which I should go. I

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Speaker 1: think about being on um. There's a bad Liberating did

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Speaker 1: a series of Star Wars songs, and one of them

385
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Speaker 1: is called Seagulls. But now that I just listened to

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Speaker 1: because it's a good song about the yodo one like

387
00:22:50,520 --> 00:22:57,000
Speaker 1: where everyone listened to it. It's fabulous. But my mom

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00:22:57,280 --> 00:22:59,760
Speaker 1: really got into the song, and so we were listening

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Speaker 1: to in the car and we were driving south on

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Speaker 1: Fairfax almost to will Shure, and then there's just a

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Speaker 1: seagull above our car, and I'm like, what are you

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Speaker 1: doing here? Why are you at Fairfax and Wilsher. You

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00:23:10,800 --> 00:23:14,040
Speaker 1: are far away from God seagle and he sent you

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00:23:14,160 --> 00:23:16,919
Speaker 1: his profit sign. I was like almost looked at like

395
00:23:16,960 --> 00:23:20,320
Speaker 1: the animal meaning of seagull. It's like, you are garbage.

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Speaker 1: We're listening to seagulls and there's a seagull. I feel

397
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Speaker 1: like there's a meaning just some ass backwards done seagull.

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Speaker 1: This fucking type. Dude, bro bro bro this It was

399
00:23:35,800 --> 00:23:39,359
Speaker 1: so great. Sick. You just gotta pay attention to the

400
00:23:39,359 --> 00:23:44,880
Speaker 1: world around good tune in, dude. So also a cute thing.

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Speaker 1: Here's one cute thing about seagulls. The only cute thing

402
00:23:47,680 --> 00:23:51,400
Speaker 1: about them. Mated pears will utter soft murmurs to each

403
00:23:51,440 --> 00:23:54,119
Speaker 1: other as they seek out a nesting area for their eggs.

404
00:23:54,440 --> 00:23:59,399
Speaker 1: They're very particular about where they nest their good parents,

405
00:23:59,440 --> 00:24:03,040
Speaker 1: but other wise they're good parents. And their murmurs are

406
00:24:03,240 --> 00:24:06,160
Speaker 1: vocalizations indicating where they think the nest should be put,

407
00:24:06,160 --> 00:24:08,880
Speaker 1: and they kind of work together to reach a consensus,

408
00:24:09,040 --> 00:24:12,439
Speaker 1: like here's where little leg nursery will be. It's like

409
00:24:12,840 --> 00:24:15,280
Speaker 1: what about here? What do you think about this? It's

410
00:24:15,359 --> 00:24:21,160
Speaker 1: like like it's like the husband seagulls like, what about

411
00:24:21,200 --> 00:24:23,040
Speaker 1: over here? And then the wife is like, that's like

412
00:24:23,280 --> 00:24:26,000
Speaker 1: literally on the edge of a rock. You like, at

413
00:24:26,080 --> 00:24:31,919
Speaker 1: least try so. Some of the less intuitive effects of

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00:24:32,000 --> 00:24:35,440
Speaker 1: urbanization is seen in birds, who are not exploiters, they're

415
00:24:35,480 --> 00:24:42,000
Speaker 1: actually avoiders. Um. And that is bird divorce. Bird divorced

416
00:24:42,760 --> 00:24:46,200
Speaker 1: divorce legally binding in the state of Californias, the saddest

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Speaker 1: thing out into American society today. Bird divorce. Come on,

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00:24:50,840 --> 00:24:54,119
Speaker 1: you know, yeah, it's just the degradation of society of

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00:24:54,240 --> 00:25:00,000
Speaker 1: morals and the bird family and the bird family. Um.

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00:25:00,200 --> 00:25:03,040
Speaker 1: So in humans, people are more likely to divorce in

421
00:25:03,200 --> 00:25:06,840
Speaker 1: cities versus suburbs. Um. And you know, there's like a

422
00:25:06,920 --> 00:25:11,080
Speaker 1: variety of causes, but one potential causes like difference and income.

423
00:25:11,160 --> 00:25:14,600
Speaker 1: So people in suburbs are typically more financially stable. So

424
00:25:14,640 --> 00:25:17,439
Speaker 1: it turns out, you know, having money and resources to

425
00:25:17,560 --> 00:25:23,800
Speaker 1: like go to couples therapy or like money makes quality

426
00:25:23,840 --> 00:25:28,159
Speaker 1: of life better. It turns out, um, but you know,

427
00:25:28,200 --> 00:25:31,760
Speaker 1: we don't know what the exact causes. But in birds,

428
00:25:32,040 --> 00:25:35,920
Speaker 1: the contrast is uh, in suburbs are real bad news

429
00:25:35,960 --> 00:25:38,919
Speaker 1: for birds. They will get divorced a lot due to

430
00:25:39,200 --> 00:25:42,959
Speaker 1: suburban crawl into their territory because suburbs usually it's like

431
00:25:43,040 --> 00:25:46,199
Speaker 1: around you know the nice leaf line streets. Well, the

432
00:25:46,200 --> 00:25:48,320
Speaker 1: reason it's lined with leaves is you're like kind of

433
00:25:48,359 --> 00:25:53,360
Speaker 1: near like wooded areas. Um. So uh, there's a study

434
00:25:53,760 --> 00:26:00,679
Speaker 1: um done in Seattle, Washington of these urban avoiders songbirds. Um.

435
00:26:00,720 --> 00:26:05,360
Speaker 1: They looked at the Swainson's thrush and Pacific Rends, who

436
00:26:05,359 --> 00:26:09,680
Speaker 1: are both urban avoiders, and they will divorce each other

437
00:26:09,760 --> 00:26:13,520
Speaker 1: in response to the trauma of the suburbs invading their habitat.

438
00:26:14,359 --> 00:26:16,960
Speaker 1: So they abandon their nests and then they just like

439
00:26:17,440 --> 00:26:20,359
Speaker 1: stop seeing each other and they get with new new mates.

440
00:26:20,960 --> 00:26:23,880
Speaker 1: And this is like similar to the human patterns of divorce,

441
00:26:23,920 --> 00:26:28,760
Speaker 1: where like environmental and economic stress may factor into splitting up.

442
00:26:29,200 --> 00:26:32,280
Speaker 1: That's like when you move you have your college boyfriend

443
00:26:32,280 --> 00:26:36,000
Speaker 1: and then you decide to like after you out of college,

444
00:26:36,040 --> 00:26:39,520
Speaker 1: like go moving together, but then everything is different. I

445
00:26:39,560 --> 00:26:42,920
Speaker 1: don't know. This was a terrible idea only worked in college.

446
00:26:43,320 --> 00:26:47,439
Speaker 1: Must It must have been the chicken nuggets and the

447
00:26:47,480 --> 00:26:50,760
Speaker 1: tater taught the chicken nugget hates These tater tots held

448
00:26:50,760 --> 00:26:57,480
Speaker 1: a relationship together. Dude, bro, it's a glue that kept

449
00:26:57,520 --> 00:27:01,000
Speaker 1: us together. Is literally like some kind of industrial glue,

450
00:27:01,320 --> 00:27:05,439
Speaker 1: some starchy cement, some starchy cement that held their love together.

451
00:27:05,800 --> 00:27:10,000
Speaker 1: That's really upsetting, I know, because songbirds are so lovely. Yeah,

452
00:27:10,000 --> 00:27:12,320
Speaker 1: they're supposed to be sort of like the doves that

453
00:27:12,359 --> 00:27:15,879
Speaker 1: you release on your way, which you shouldn't. Don't do that,

454
00:27:16,640 --> 00:27:20,320
Speaker 1: murdering doves monsters really seriously, like if you have like

455
00:27:20,400 --> 00:27:24,720
Speaker 1: captive doves and you release them, they're like, uh yeah, okay,

456
00:27:24,760 --> 00:27:27,440
Speaker 1: Like what now, dude, Yeah, where do I go? You've

457
00:27:27,440 --> 00:27:30,600
Speaker 1: remin me from everything? I know? What? What? What? What

458
00:27:30,760 --> 00:27:34,520
Speaker 1: is this open sky? I mean, like congratulations and everything.

459
00:27:34,520 --> 00:27:37,639
Speaker 1: But also I'm woefully underprepared for this. Yeah, it's just

460
00:27:37,720 --> 00:27:40,480
Speaker 1: like they will they will die, but also they will

461
00:27:40,520 --> 00:27:43,600
Speaker 1: may be divorced too, because birds are just you know,

462
00:27:43,920 --> 00:27:46,800
Speaker 1: there's nothing sacred. Birds are as messed up as we are.

463
00:27:47,119 --> 00:27:50,240
Speaker 1: I just mentioned little bird feet signing a little piece

464
00:27:50,280 --> 00:27:53,760
Speaker 1: of paper bird attorneys, Like, I guess, I guess this

465
00:27:53,920 --> 00:27:56,400
Speaker 1: is it just going like and you will get half

466
00:27:56,400 --> 00:28:00,200
Speaker 1: of the millet and some sticks. That's my favorite stick,

467
00:28:00,280 --> 00:28:05,720
Speaker 1: you know, that's my favorite stick. Oh upsetting, so sad,

468
00:28:05,880 --> 00:28:07,360
Speaker 1: But I mean if they're happier in the long run,

469
00:28:07,400 --> 00:28:10,159
Speaker 1: I guess it's better. Yeah, I mean until all of

470
00:28:10,200 --> 00:28:20,120
Speaker 1: their territories by suburbs and stuff. The world sucks. Not

471
00:28:20,200 --> 00:28:24,160
Speaker 1: all birds are as shy as our divorcee songbirds. There's

472
00:28:24,200 --> 00:28:26,800
Speaker 1: a type of bird who looks innocent enough but is

473
00:28:26,840 --> 00:28:31,639
Speaker 1: actually a vicious invader, and it's all Shakespeare's fault. Starlings

474
00:28:31,640 --> 00:28:35,080
Speaker 1: are small blackbirds with white dots, named such because they

475
00:28:35,119 --> 00:28:39,000
Speaker 1: look like a star speckled sky. They're highly intelligent, able

476
00:28:39,040 --> 00:28:42,680
Speaker 1: to open the tops off of milk jugs, and like parrots,

477
00:28:42,760 --> 00:28:46,320
Speaker 1: they're able to learn and mimic human words. So what's

478
00:28:46,320 --> 00:28:50,360
Speaker 1: the problem, Well, there are over two hundred million European

479
00:28:50,480 --> 00:28:54,320
Speaker 1: starlings in North America, with flocks big enough to sometimes

480
00:28:54,400 --> 00:28:58,240
Speaker 1: darken the sky, looking like a large cloud, strobing in

481
00:28:58,320 --> 00:29:01,920
Speaker 1: what is known as murmurations as they change directions. But

482
00:29:02,080 --> 00:29:05,360
Speaker 1: they're non native, in a big problem for North American birds,

483
00:29:05,400 --> 00:29:09,720
Speaker 1: including bluebirds, flickers, and woodpeckers only two of which sounds

484
00:29:09,760 --> 00:29:13,120
Speaker 1: like a slang for wieners. Starlings will kick them out

485
00:29:13,120 --> 00:29:16,440
Speaker 1: of their nests, making it difficult for these indigenous species

486
00:29:16,440 --> 00:29:19,600
Speaker 1: to breathe successfully, they can be a nuisance for humans

487
00:29:19,640 --> 00:29:23,400
Speaker 1: as well. Large flocks can demolish entire crops of wheat

488
00:29:23,680 --> 00:29:26,720
Speaker 1: their vectors for disease, and their nests are even known

489
00:29:26,760 --> 00:29:31,880
Speaker 1: to cultivate a spooky fungus called Pistoplasma capsulatum, whose fungal

490
00:29:31,920 --> 00:29:37,000
Speaker 1: spores can cause pistoplasmosis and humans, which can cause fever, chills,

491
00:29:37,080 --> 00:29:40,120
Speaker 1: coughing up blood, and if left untreated, will attack your

492
00:29:40,160 --> 00:29:44,360
Speaker 1: whole body, including the central nervous system, adrenal glands, and liver,

493
00:29:44,560 --> 00:29:48,280
Speaker 1: causing blindness and a vicilly death. So how did these

494
00:29:48,320 --> 00:29:52,280
Speaker 1: little harbingers of doom get to North America the cause

495
00:29:52,320 --> 00:29:57,480
Speaker 1: of most of our problems? An overenthusiastic fanboy in Night,

496
00:29:57,880 --> 00:30:02,920
Speaker 1: Eugene Chfel in New York pharmaceutical manufacturer, had an evil

497
00:30:03,080 --> 00:30:07,000
Speaker 1: nerdy plan. He wanted to introduce every bird mentioned in

498
00:30:07,120 --> 00:30:11,600
Speaker 1: Shakespeare's plays and poems to North America. Other birds he

499
00:30:11,640 --> 00:30:14,600
Speaker 1: had tried, such as nightingales and skylarks, had failed to

500
00:30:14,680 --> 00:30:19,280
Speaker 1: thrive and died off. Unfortunately, Shakespeare had faithfully made mention

501
00:30:19,360 --> 00:30:23,280
Speaker 1: of one other bird in Henry the Fourth, the Starling. Remember,

502
00:30:23,400 --> 00:30:27,960
Speaker 1: starlings can be taught human words so Shakespeare wrote this line, Nay,

503
00:30:28,000 --> 00:30:31,080
Speaker 1: I'll have a starling shall be brought to speak nothing

504
00:30:31,120 --> 00:30:33,960
Speaker 1: but Mortimer, and give it to him to keep his

505
00:30:34,040 --> 00:30:38,080
Speaker 1: anger still in motion. So basically, as Starling was taught

506
00:30:38,120 --> 00:30:39,920
Speaker 1: to say, a name that annoyed the king is a

507
00:30:40,040 --> 00:30:44,760
Speaker 1: sort of old timey prank. Uh. So Shakespeare dork Sheffilin

508
00:30:44,960 --> 00:30:49,440
Speaker 1: imported sixties starlings from Europe and released these winged demons

509
00:30:49,440 --> 00:30:53,080
Speaker 1: into New York Central Park. Today there are hundreds of

510
00:30:53,120 --> 00:30:56,680
Speaker 1: millions of these feathered bullets, as the U. S. Department

511
00:30:56,720 --> 00:31:00,280
Speaker 1: of Agriculture likes to call them. So there's a bunch

512
00:31:00,360 --> 00:31:05,320
Speaker 1: of birds outside our window staring a menacingly. We're gonna

513
00:31:05,360 --> 00:31:12,160
Speaker 1: take a quick break to adjust the situation. So our

514
00:31:12,320 --> 00:31:16,320
Speaker 1: dogs parasites? A newspaper column once answered this with a

515
00:31:16,440 --> 00:31:21,440
Speaker 1: controversial yes. The San Diego Union Tribune, my hometown, by

516
00:31:21,440 --> 00:31:24,880
Speaker 1: the way, ran a column titled, let's be honest, America,

517
00:31:25,160 --> 00:31:31,120
Speaker 1: dogs are parasites, not Man's best friend. Twitter responded, let's say, tepidly,

518
00:31:31,640 --> 00:31:35,360
Speaker 1: telling the newspaper to go funk itself, amongst other strongly

519
00:31:35,440 --> 00:31:39,000
Speaker 1: worded complaints. But is there any truth to the claim

520
00:31:39,080 --> 00:31:43,200
Speaker 1: that dogs are parasites? The article's main assertion is that

521
00:31:43,320 --> 00:31:48,120
Speaker 1: dogs are master manipulators. All the pampering, stroller rides, grooming,

522
00:31:48,200 --> 00:31:51,640
Speaker 1: expensive care, these are all signs that dogs have gained

523
00:31:51,680 --> 00:31:55,920
Speaker 1: the system and asserted themselves as our furry overlords. The

524
00:31:55,960 --> 00:32:01,000
Speaker 1: author sites in article called the Truth about Dogs, which

525
00:32:01,040 --> 00:32:05,520
Speaker 1: explains that rather than us humans domesticating dogs, dogs may

526
00:32:05,520 --> 00:32:08,640
Speaker 1: have exploited human empathy in order to live with us,

527
00:32:08,920 --> 00:32:13,560
Speaker 1: in a way domesticating themselves so the less aggressive, more

528
00:32:13,680 --> 00:32:18,080
Speaker 1: human friendly proto dogs would be favored by our human ancestors,

529
00:32:18,120 --> 00:32:22,240
Speaker 1: and they'd earn the enviable position of man's best friend. This,

530
00:32:22,400 --> 00:32:25,440
Speaker 1: I think is a pretty strong and compelling theory. But

531
00:32:25,680 --> 00:32:29,240
Speaker 1: to then call dogs parasites is not only cynical but

532
00:32:29,440 --> 00:32:34,400
Speaker 1: scientifically inaccurate. The definition of parasites are organisms that benefit

533
00:32:34,520 --> 00:32:38,080
Speaker 1: at the cost to a host. Dogs are at worst

534
00:32:38,200 --> 00:32:41,880
Speaker 1: commence alistic symbiots of fancy way of saying, an animal

535
00:32:41,920 --> 00:32:44,480
Speaker 1: who benefits from a host at no cost or harm

536
00:32:44,520 --> 00:32:47,800
Speaker 1: to the host. But in my opinion, they are mutualistic,

537
00:32:47,880 --> 00:32:50,200
Speaker 1: meaning we gain as much from them as they gain

538
00:32:50,280 --> 00:32:52,960
Speaker 1: from us, be it in the work they do for us,

539
00:32:53,040 --> 00:32:56,920
Speaker 1: hurting sheep and eating rats. The emotional benefits we receive

540
00:32:57,080 --> 00:32:59,400
Speaker 1: and all the Instagram likes we'd get when we post

541
00:32:59,400 --> 00:33:02,480
Speaker 1: pictures of them in cute shirts. Seriously, look me in

542
00:33:02,520 --> 00:33:04,720
Speaker 1: the eye and tell me that a dog who tolerates

543
00:33:04,760 --> 00:33:08,480
Speaker 1: being costooned with bows, hats, and booties isn't paying for

544
00:33:08,560 --> 00:33:12,200
Speaker 1: his meals. Some dogs, however, have figured out a way

545
00:33:12,240 --> 00:33:15,440
Speaker 1: to leach off of human society without having to pay

546
00:33:15,480 --> 00:33:17,840
Speaker 1: with their dignity, and we have to go to Russia

547
00:33:17,960 --> 00:33:21,800
Speaker 1: to find them. Katie, Yes, you like dogs? I do

548
00:33:21,800 --> 00:33:25,120
Speaker 1: you like dogs? I love dogs. They are good papas.

549
00:33:25,480 --> 00:33:28,640
Speaker 1: They're good papa. They are heck and sweet, and I

550
00:33:28,720 --> 00:33:31,840
Speaker 1: want us motionales. Would you want dogs to be able

551
00:33:31,880 --> 00:33:36,840
Speaker 1: to talk? No? I know right, I feel like it

552
00:33:36,880 --> 00:33:39,600
Speaker 1: would just make things weird. Like it's fine the way

553
00:33:39,640 --> 00:33:43,200
Speaker 1: it is. You know, they express through their behavior how

554
00:33:43,240 --> 00:33:46,560
Speaker 1: they're feeling. That's all I need, DoD. You'd imagine like

555
00:33:46,560 --> 00:33:50,160
Speaker 1: like an updog, like like you know, the dog from

556
00:33:50,280 --> 00:33:54,640
Speaker 1: up going like you know, I'm sweet and lovable because

557
00:33:54,680 --> 00:33:58,720
Speaker 1: I love you. Yeah, But in reality they'd be like Mia, Mia, Yeah,

558
00:33:58,960 --> 00:34:03,760
Speaker 1: I mean I'm gonna poop everywhere? What is that? What

559
00:34:04,000 --> 00:34:06,200
Speaker 1: is that? I feel like it'd be a lot of yelling,

560
00:34:06,600 --> 00:34:11,080
Speaker 1: just like, oh my god, someone needs a block away

561
00:34:11,400 --> 00:34:14,240
Speaker 1: and you'd just be like I can't, like you already

562
00:34:14,239 --> 00:34:16,920
Speaker 1: bark like I know what you are saying. Someone is away,

563
00:34:17,040 --> 00:34:20,640
Speaker 1: like close to our door. The Maleman is here. Yeah,

564
00:34:20,760 --> 00:34:22,520
Speaker 1: I do, I have a I mean, I love cats

565
00:34:22,560 --> 00:34:24,359
Speaker 1: and I love dogs, and I have a cat. Just

566
00:34:25,320 --> 00:34:27,719
Speaker 1: well I love cats, but also it's just easier for

567
00:34:27,760 --> 00:34:29,120
Speaker 1: me right now, and I can't live in a place

568
00:34:29,160 --> 00:34:31,600
Speaker 1: where I have a dog, but like I do just

569
00:34:31,719 --> 00:34:35,560
Speaker 1: want like just like a sweet boy. It's like a

570
00:34:35,640 --> 00:34:40,120
Speaker 1: swoo boy dog, just as like a dope, big doofy dog.

571
00:34:40,200 --> 00:34:44,080
Speaker 1: But they're I mean, like I got a dog. And

572
00:34:44,120 --> 00:34:47,440
Speaker 1: my impression as a former cat owner is like dogs

573
00:34:47,440 --> 00:34:50,120
Speaker 1: are all these sort of doofy lovable dogs, but a

574
00:34:50,160 --> 00:34:54,200
Speaker 1: lot of them just are extremely emotionally needy, like neurotically neurotic.

575
00:34:54,400 --> 00:34:56,960
Speaker 1: Like just like my dog who every time the printer

576
00:34:57,080 --> 00:34:59,840
Speaker 1: goes off or something beeps or my phone gets a

577
00:35:00,000 --> 00:35:02,839
Speaker 1: HEXT message, she like gets on my shoulders and like

578
00:35:03,160 --> 00:35:05,359
Speaker 1: it's like her face is in my face and she's like,

579
00:35:05,640 --> 00:35:07,400
Speaker 1: what is that? What is that? What is that? What

580
00:35:07,440 --> 00:35:10,600
Speaker 1: does that sound? At least my cat, my cat is neurotic,

581
00:35:10,640 --> 00:35:12,719
Speaker 1: but my cat is also a loof right, so it's

582
00:35:12,800 --> 00:35:14,520
Speaker 1: kind of just like I'm gonna just deal with my

583
00:35:14,520 --> 00:35:17,359
Speaker 1: my stuff like over here, whereas dogs are like, I'm

584
00:35:17,400 --> 00:35:20,080
Speaker 1: having problems and you need to dress them here, you

585
00:35:20,120 --> 00:35:22,160
Speaker 1: need to fix it. Yeah, you need to fix this

586
00:35:22,280 --> 00:35:25,200
Speaker 1: or right now. And so there's a good reason that

587
00:35:25,280 --> 00:35:29,520
Speaker 1: they're like that. Dogs have been domesticated for around fifteen

588
00:35:29,560 --> 00:35:34,120
Speaker 1: thousand years. Um, so they've basically co evolved with us

589
00:35:34,200 --> 00:35:37,719
Speaker 1: over a really long period of time, which, um, you know,

590
00:35:37,880 --> 00:35:40,880
Speaker 1: it's created this situation where we can kind of communicate

591
00:35:40,920 --> 00:35:43,359
Speaker 1: with them in a way, we can train them, and

592
00:35:43,719 --> 00:35:47,120
Speaker 1: they also are sort of like they're very good at

593
00:35:47,120 --> 00:35:50,920
Speaker 1: getting us to pay attention to them, those big puppy dogs,

594
00:35:50,960 --> 00:35:53,960
Speaker 1: and like just like the wines they make, we we

595
00:35:54,160 --> 00:35:57,280
Speaker 1: feel the need to to help them, and they also

596
00:35:57,520 --> 00:36:01,839
Speaker 1: help us. So um. But what it's crazy is so

597
00:36:02,360 --> 00:36:04,359
Speaker 1: you would think that most dogs in the world are

598
00:36:04,640 --> 00:36:09,760
Speaker 1: pet dogs, but of dogs are unrestrained, so that means

599
00:36:09,800 --> 00:36:14,120
Speaker 1: they're either feral, they're stray, or their village free range dogs.

600
00:36:14,640 --> 00:36:17,200
Speaker 1: There's nine hundred million dogs in the world, two hundred

601
00:36:17,239 --> 00:36:20,800
Speaker 1: million are strays, and in Moscow alone there are thirty

602
00:36:20,840 --> 00:36:24,320
Speaker 1: five thousand stray dogs. That's a lot. Yeah, that's a

603
00:36:24,400 --> 00:36:29,120
Speaker 1: lot of that's a lot. But I can't I apologize.

604
00:36:29,160 --> 00:36:31,719
Speaker 1: I cannot help it when I talk about dog kind

605
00:36:31,719 --> 00:36:33,920
Speaker 1: of to to put that in perspective, the number of

606
00:36:33,960 --> 00:36:37,600
Speaker 1: wolves in all of Russia is around fifty thou Yeah,

607
00:36:38,280 --> 00:36:41,520
Speaker 1: um so there's a small group of intrepid stray dogs

608
00:36:41,520 --> 00:36:48,880
Speaker 1: in Moscow who have learned to navigate the subway system. Yes, yeah,

609
00:36:49,040 --> 00:36:51,520
Speaker 1: they're they're great videos online of these dogs where they

610
00:36:51,640 --> 00:36:54,560
Speaker 1: just like they're like in the subway. Uh, They're they're

611
00:36:54,600 --> 00:36:57,480
Speaker 1: at like the subway station. They're just like waiting around

612
00:36:57,480 --> 00:36:59,400
Speaker 1: with all the other commuters, and they're like kind of

613
00:36:59,440 --> 00:37:01,319
Speaker 1: go to work, kind of go to work than the

614
00:37:01,440 --> 00:37:05,480
Speaker 1: trade doors. And they're like they're like excuse me, pardon me, ma'am.

615
00:37:05,560 --> 00:37:09,640
Speaker 1: Just me and dog going to work. Um so. They

616
00:37:09,640 --> 00:37:15,480
Speaker 1: were studied by Russian biologists Andre Poyarkov and animal expert

617
00:37:15,719 --> 00:37:21,600
Speaker 1: Andre neronov Um. So poiarkov Um observed stray dogs becoming

618
00:37:21,600 --> 00:37:26,200
Speaker 1: more wolf like with greater intelligence, pack structure, and they

619
00:37:26,239 --> 00:37:30,120
Speaker 1: were losing domesticated dog behaviors such as tail wagging and

620
00:37:30,239 --> 00:37:33,320
Speaker 1: physical traits such as spotted coats. So the more feral,

621
00:37:33,360 --> 00:37:36,640
Speaker 1: they became the more wolf like um. And then these

622
00:37:36,719 --> 00:37:42,440
Speaker 1: more feral wolf like dogs were also exploiting the subway system. Um.

623
00:37:42,480 --> 00:37:45,879
Speaker 1: So there are three types of dog commuters. There are

624
00:37:46,000 --> 00:37:48,520
Speaker 1: dogs who live in the subway, but they don't travel.

625
00:37:48,640 --> 00:37:51,040
Speaker 1: They just lived there because it's warm. Lots of people

626
00:37:51,360 --> 00:37:53,960
Speaker 1: in Russia it's snow it's snowy. And it's also just

627
00:37:54,000 --> 00:37:57,280
Speaker 1: like you know, commuters bumping up, dropping their pretzels and stuff.

628
00:37:57,280 --> 00:38:01,200
Speaker 1: They're borsh, that's not really right. It's trash and polish.

629
00:38:01,640 --> 00:38:04,319
Speaker 1: Maybe it's polish, but also like who's walk around with

630
00:38:04,360 --> 00:38:07,960
Speaker 1: a big old bottom? I don't know. I'm like a

631
00:38:08,000 --> 00:38:12,600
Speaker 1: couple of generations removed Russians, so I don't actually knowsh

632
00:38:12,640 --> 00:38:19,239
Speaker 1: it around. I just don't actually um so uh. And

633
00:38:19,280 --> 00:38:22,399
Speaker 1: then the second type of subway dogs are those who

634
00:38:22,520 --> 00:38:25,799
Speaker 1: use the subway to travel instead of walking there. They're

635
00:38:25,840 --> 00:38:27,359
Speaker 1: just like, you know, I need to get from point

636
00:38:27,360 --> 00:38:29,919
Speaker 1: A to point B. I know the subway will take

637
00:38:29,920 --> 00:38:32,080
Speaker 1: me there, and so I just hop right on there,

638
00:38:32,640 --> 00:38:35,160
Speaker 1: you know, open up a good newspaper and eat that

639
00:38:35,200 --> 00:38:39,919
Speaker 1: newspaper because on top of it, um and it's really

640
00:38:39,920 --> 00:38:42,440
Speaker 1: cute too, because like sometimes they travel and like pairs

641
00:38:42,840 --> 00:38:45,319
Speaker 1: or groups, and like when one dog is like, it's

642
00:38:45,320 --> 00:38:49,600
Speaker 1: our stop now, they'll like inform the other dog like, hey, hey, barfie,

643
00:38:49,719 --> 00:38:55,840
Speaker 1: just our stop. Oh my god, we gotta go. Um.

644
00:38:55,960 --> 00:38:58,719
Speaker 1: The third type is my favorite. It's dogs who use

645
00:38:58,800 --> 00:39:03,040
Speaker 1: the subway to commute to location for busking purposes. So

646
00:39:03,120 --> 00:39:06,760
Speaker 1: they will uh live in areas that are good for sleeping,

647
00:39:06,800 --> 00:39:10,000
Speaker 1: so like suburban areas. Um. And then like they will

648
00:39:10,360 --> 00:39:12,840
Speaker 1: go into the urban areas, like into the city to

649
00:39:12,920 --> 00:39:15,360
Speaker 1: go beg for food. It's like people who work in

650
00:39:15,360 --> 00:39:18,880
Speaker 1: in Manhattan but commune from there, Like it's easier to

651
00:39:18,920 --> 00:39:22,000
Speaker 1: buy a house out there, and you know, we like

652
00:39:22,120 --> 00:39:26,560
Speaker 1: the wide open space. Dog, I can't afford rent. I

653
00:39:26,600 --> 00:39:29,960
Speaker 1: shouldn't rent. No, I'd rather just live in Jersey, live

654
00:39:30,000 --> 00:39:33,400
Speaker 1: in a drain pipe, and I gotta commute to work.

655
00:39:34,360 --> 00:39:38,480
Speaker 1: I mean, it's just like my workout a talk start up. Yeah,

656
00:39:38,560 --> 00:39:43,799
Speaker 1: you live in like out in in uh in my

657
00:39:43,840 --> 00:39:48,919
Speaker 1: own dookey. I just like. But my favorite thing about

658
00:39:48,920 --> 00:39:51,640
Speaker 1: that is there's the first dog, Like the first dog

659
00:39:51,680 --> 00:39:55,239
Speaker 1: who accidentally like got on the subway and realize what

660
00:39:55,360 --> 00:39:58,280
Speaker 1: happened and then was like he's like, oh, we gotta

661
00:39:58,400 --> 00:40:01,960
Speaker 1: I gotta tell every about it a good portal. Rich

662
00:40:02,040 --> 00:40:05,600
Speaker 1: wizards were like, oh man, I've been here before, but

663
00:40:05,640 --> 00:40:07,600
Speaker 1: it took me way longer to get here before, like

664
00:40:07,640 --> 00:40:11,000
Speaker 1: the thought process that had to go, yeah, like, oh,

665
00:40:11,080 --> 00:40:13,279
Speaker 1: this is something we gotta keep doing because my legs

666
00:40:13,280 --> 00:40:16,759
Speaker 1: are small. Have you heard of train It's the hot

667
00:40:16,800 --> 00:40:20,960
Speaker 1: new trend. They're like Ted's drunk again, someone taken away

668
00:40:21,000 --> 00:40:25,240
Speaker 1: from him? Take the borched away from the dog. Another

669
00:40:25,440 --> 00:40:29,000
Speaker 1: fun thing that straight dogs will do that's really like intelligent,

670
00:40:29,200 --> 00:40:32,600
Speaker 1: the big limpse. Oh my god, I love it. Yeah. Yeah,

671
00:40:32,640 --> 00:40:34,560
Speaker 1: they'll like they'll like drag one leg on the ground

672
00:40:34,600 --> 00:40:38,239
Speaker 1: and be like, oh no, whoe is me. I'm just

673
00:40:38,360 --> 00:40:41,520
Speaker 1: a poor dog and it's our board. I am just

674
00:40:41,600 --> 00:40:44,919
Speaker 1: a good boy. And then as soon as they get

675
00:40:44,920 --> 00:40:49,920
Speaker 1: that sausage there, like got you suck it, and then

676
00:40:49,920 --> 00:40:54,080
Speaker 1: they hop away giving you they run away giving you

677
00:40:54,120 --> 00:40:58,759
Speaker 1: the middle finger. Um. Pet dogs also do this. So

678
00:40:58,840 --> 00:41:01,560
Speaker 1: sometimes my dog will shiver as if she's scared, and

679
00:41:01,600 --> 00:41:04,480
Speaker 1: it's like usually after so like there will be a

680
00:41:04,520 --> 00:41:08,480
Speaker 1: thunderstorm and she's shivering out of true fear and she

681
00:41:08,560 --> 00:41:11,120
Speaker 1: gets a lot of attention, and then the next day

682
00:41:11,280 --> 00:41:15,560
Speaker 1: there's freaking nothing going on. She starts shivering. I'm like,

683
00:41:16,320 --> 00:41:20,120
Speaker 1: you want hugs and treats, and she's like yuh huh,

684
00:41:20,120 --> 00:41:22,160
Speaker 1: And then I also give it to her, though I

685
00:41:22,200 --> 00:41:27,000
Speaker 1: do give in. She played like a fit. You're technically

686
00:41:27,000 --> 00:41:29,200
Speaker 1: not supposed to You're not like supposed to coddle them

687
00:41:29,200 --> 00:41:32,040
Speaker 1: because they learned that to do the fear response in

688
00:41:32,120 --> 00:41:35,359
Speaker 1: order to get the coddling. But I just I caught

689
00:41:35,440 --> 00:41:37,719
Speaker 1: I'm a coddler. Why can I say? Yeah, it's like

690
00:41:37,760 --> 00:41:41,319
Speaker 1: with kids when they learned that if they freak out,

691
00:41:42,040 --> 00:41:44,000
Speaker 1: like at Walmart or I don't know why that was

692
00:41:44,080 --> 00:41:46,680
Speaker 1: like a target, they have a melting to take the

693
00:41:46,719 --> 00:41:50,920
Speaker 1: kids to Walmart and they throw a tantrum, then you

694
00:41:51,000 --> 00:41:52,520
Speaker 1: buy him a fit if you buy the thing to

695
00:41:52,600 --> 00:41:54,640
Speaker 1: make them quiet, And then anytime you go anywhere, they

696
00:41:54,640 --> 00:41:58,640
Speaker 1: started tying. I hope if and when I become a parent,

697
00:41:58,760 --> 00:42:02,880
Speaker 1: I don't treat my children like a treatment we would have.

698
00:42:03,080 --> 00:42:07,759
Speaker 1: It's like, I hope I would have better better boundaries.

699
00:42:07,920 --> 00:42:14,960
Speaker 1: I think so um so, just me with a thousand

700
00:42:15,040 --> 00:42:21,400
Speaker 1: miles stare of like, damn it, dog raising is hard, parenting,

701
00:42:21,400 --> 00:42:24,520
Speaker 1: oh geez. So the idea that they can kind of

702
00:42:24,520 --> 00:42:27,680
Speaker 1: like tap into our human empathy and exploit. It does

703
00:42:27,800 --> 00:42:31,319
Speaker 1: tie into that theory of dog evolution that wolves with

704
00:42:31,400 --> 00:42:35,520
Speaker 1: certain affable temperaments could exploit human kindness, and so they

705
00:42:35,520 --> 00:42:39,520
Speaker 1: were kind of responsible for domesticating themselves. Maybe. Well, I

706
00:42:39,520 --> 00:42:42,719
Speaker 1: think it's interesting that it's like domesticated going up in

707
00:42:42,760 --> 00:42:44,760
Speaker 1: a bell curve and then as they became feral again,

708
00:42:45,880 --> 00:42:49,759
Speaker 1: losing some of the behaviors again. But yeah, yeah, it's

709
00:42:49,760 --> 00:42:52,560
Speaker 1: like you can't unknow what you know because they're I

710
00:42:52,560 --> 00:42:58,799
Speaker 1: don't think they're vicious. They're not necessarily friendly dogs, but yeah,

711
00:42:58,880 --> 00:43:01,800
Speaker 1: they and they are more or they have that pack structure.

712
00:43:01,840 --> 00:43:04,440
Speaker 1: I think they like their ears get stiffer to they

713
00:43:04,480 --> 00:43:08,080
Speaker 1: lose the spotted coats. Because what's interesting is that all

714
00:43:08,400 --> 00:43:13,800
Speaker 1: domesticated animals share certain genetic markers, like the the weak

715
00:43:13,840 --> 00:43:17,200
Speaker 1: cartilage in the ears that causes like floppiness, sloppy ears

716
00:43:17,239 --> 00:43:22,000
Speaker 1: like pigs, cows, dogs, um. Notably cats don't don't know,

717
00:43:24,320 --> 00:43:27,360
Speaker 1: cats are not really as domestic. They're very close to

718
00:43:27,400 --> 00:43:31,000
Speaker 1: their wild counterparts. They're very genetically similar to the wildcats.

719
00:43:31,280 --> 00:43:34,479
Speaker 1: And then like other things like spotted coats, you see

720
00:43:34,480 --> 00:43:41,600
Speaker 1: that in cows, dogs, pigs, rabbits, you know, um, constructors, um.

721
00:43:42,840 --> 00:43:46,000
Speaker 1: But yeah, Like I don't know if reptiles actually counting this,

722
00:43:46,120 --> 00:43:49,320
Speaker 1: but like, yeah, most domesticated mammals share these genetic markers.

723
00:43:49,640 --> 00:43:51,799
Speaker 1: As dogs become more feral, they kind of lose some

724
00:43:51,880 --> 00:43:54,720
Speaker 1: of those some of those traits. It is the ears

725
00:43:54,800 --> 00:43:57,080
Speaker 1: thing that like, Okay, when they're stiff, they're better, they're

726
00:43:57,200 --> 00:43:59,480
Speaker 1: eat they can hear, and they're more like aware. And

727
00:43:59,520 --> 00:44:03,160
Speaker 1: then as they been domesticated, it's like the chiller lazier

728
00:44:03,239 --> 00:44:06,000
Speaker 1: dogs that get bread to be like pets, and so

729
00:44:06,080 --> 00:44:08,840
Speaker 1: then they're just all their skill, they're just so relaxed,

730
00:44:08,920 --> 00:44:13,040
Speaker 1: they're like or that they're like spotted coats. I don't

731
00:44:13,040 --> 00:44:15,400
Speaker 1: I'm like, I don't think so. I think it's just

732
00:44:15,520 --> 00:44:20,960
Speaker 1: sort of arbitrarily attached to certain behavioral traits, so like

733
00:44:21,120 --> 00:44:26,160
Speaker 1: more um, you know, the chiller behavior is it's just like,

734
00:44:26,239 --> 00:44:30,520
Speaker 1: for whatever reason, be less less aggressive. Also, maybe less

735
00:44:30,600 --> 00:44:34,719
Speaker 1: of certain hormones are attached to like cartilage productions. So

736
00:44:34,880 --> 00:44:38,560
Speaker 1: these things just like that just happened to be biologically linked.

737
00:44:38,600 --> 00:44:42,400
Speaker 1: But I don't think there's any like actual structural purpose

738
00:44:42,560 --> 00:44:50,120
Speaker 1: of like the ears flopping down kept Sometimes my dog

739
00:44:50,400 --> 00:44:54,000
Speaker 1: has one ear that sticks up and the other one.

740
00:44:55,160 --> 00:45:00,120
Speaker 1: I just oh, just I'll buy, but you don't. You

741
00:45:00,160 --> 00:45:02,960
Speaker 1: love it when cats get their ear turned inside out

742
00:45:02,960 --> 00:45:05,640
Speaker 1: and they're just like going around like my always book,

743
00:45:06,080 --> 00:45:09,840
Speaker 1: I'm just like, you look like such a picking because

744
00:45:09,920 --> 00:45:12,760
Speaker 1: Lila likes to look cool and smart all the time,

745
00:45:12,800 --> 00:45:15,520
Speaker 1: and when she looks dumb, I'm like, you're an idiot.

746
00:45:15,719 --> 00:45:18,200
Speaker 1: Like they go from being like British Bond villain of

747
00:45:18,360 --> 00:45:23,200
Speaker 1: like yes, feed me la tuna, to like, oh you pokey, mommy,

748
00:45:23,440 --> 00:45:25,920
Speaker 1: mommy fixs me. You always spoke in. My favorite is

749
00:45:25,920 --> 00:45:28,200
Speaker 1: when Lola rolls off the bed accidentally and then like

750
00:45:28,560 --> 00:45:30,960
Speaker 1: hits the deck and looks around like like tries to

751
00:45:31,000 --> 00:45:33,359
Speaker 1: act like nothing just happened. I was like, you fell.

752
00:45:33,680 --> 00:45:38,640
Speaker 1: Your dog sometimes miscalculates to jump on the bed and

753
00:45:38,760 --> 00:45:41,439
Speaker 1: just like wipes out. She kind of just like looks

754
00:45:41,440 --> 00:45:46,920
Speaker 1: around like what what just happened? Who did that? Who

755
00:45:46,960 --> 00:45:50,239
Speaker 1: was responsible? The couch was responsible for this. No one

756
00:45:50,320 --> 00:45:54,480
Speaker 1: moved the couch. Nobody moved the couch. You're just stupid,

757
00:45:54,880 --> 00:46:05,719
Speaker 1: Yeah you. So we talked briefly about how dogs may

758
00:46:05,760 --> 00:46:09,480
Speaker 1: have domesticated themselves, but they may not be the only ones.

759
00:46:09,800 --> 00:46:13,160
Speaker 1: There's a theory that humans are self domesticated, that the

760
00:46:13,239 --> 00:46:17,520
Speaker 1: reason we conform societies and civilizations is our ability to

761
00:46:17,560 --> 00:46:20,880
Speaker 1: be docile and cooperative, a trait we may have self

762
00:46:20,920 --> 00:46:24,720
Speaker 1: selected for. The theory is that humans depended on group

763
00:46:24,800 --> 00:46:29,080
Speaker 1: dynamics to survive or not the strongest, fastest, or large

764
00:46:29,160 --> 00:46:31,880
Speaker 1: tooth eist of them all. But we are smart and

765
00:46:31,960 --> 00:46:35,320
Speaker 1: we can work together, so groups of our pre Homo

766
00:46:35,400 --> 00:46:39,480
Speaker 1: sapien ancestors would weed out those who were overly anti social.

767
00:46:40,280 --> 00:46:44,400
Speaker 1: So say there's that one asshole auster Lepithecus, an early

768
00:46:44,480 --> 00:46:49,040
Speaker 1: human ancestor, though we'll call Lucy. Lucy is a general

769
00:46:49,080 --> 00:46:53,879
Speaker 1: asshole to other austro Lepithecai, especially one name, let's say,

770
00:46:54,239 --> 00:46:58,879
Speaker 1: Charlie Grog. And whenever they're playing kick the oblong rock,

771
00:46:59,200 --> 00:47:02,040
Speaker 1: she pretends as if she's holding it for Charlie Grog,

772
00:47:02,080 --> 00:47:04,520
Speaker 1: but then she lifts it up at the last second,

773
00:47:04,880 --> 00:47:07,720
Speaker 1: causing his kick to send him flying onto his back.

774
00:47:08,360 --> 00:47:11,040
Speaker 1: Then she smashes Charlie Grog's head in with the rock

775
00:47:11,120 --> 00:47:14,360
Speaker 1: and eats the soft brain tissue. Lucy would quickly be

776
00:47:14,480 --> 00:47:18,319
Speaker 1: excommunicated from the group of Australopithecus and left to die.

777
00:47:18,680 --> 00:47:23,200
Speaker 1: Her homicidal asshole genes meaning a quick ant Recently, genetic

778
00:47:23,280 --> 00:47:26,800
Speaker 1: studies have shown this theory may have some solid scientific merit.

779
00:47:27,280 --> 00:47:31,440
Speaker 1: Researchers compared the genomes of humans with that of domesticated animals,

780
00:47:31,760 --> 00:47:36,359
Speaker 1: finding similar genetic markers that all domesticated animals share. So

781
00:47:36,520 --> 00:47:40,319
Speaker 1: there you go, we probably domesticated ourselves. I am now

782
00:47:40,400 --> 00:47:43,200
Speaker 1: going to scoop my butt across the carpet because science

783
00:47:43,200 --> 00:47:46,120
Speaker 1: says I can. So I'm about to have an interview

784
00:47:46,160 --> 00:47:49,480
Speaker 1: with Dr Greg Pauley. But first, Katie, you got anything

785
00:47:49,480 --> 00:47:52,239
Speaker 1: you want to plug? Oh? You can find me on

786
00:47:52,280 --> 00:47:56,040
Speaker 1: Twitter and Instagram at k A w I L L

787
00:47:56,200 --> 00:48:00,399
Speaker 1: e r T. That's at k A Willard. Nice. Our

788
00:48:00,520 --> 00:48:04,000
Speaker 1: names are the same, I know, and it's spelled the same,

789
00:48:04,000 --> 00:48:06,520
Speaker 1: and I'd be happy. We're doing a D and D

790
00:48:06,680 --> 00:48:10,280
Speaker 1: campaign to have it do. Yeah, yeah, it's the best.

791
00:48:10,880 --> 00:48:16,880
Speaker 1: Stay stay there, good yo. We'll be right back after

792
00:48:16,960 --> 00:48:25,680
Speaker 1: these messages and we're joining me. Is Dr Greg Paully,

793
00:48:25,920 --> 00:48:29,839
Speaker 1: researcher and herpetology curator at the Natural History Museum of

794
00:48:29,880 --> 00:48:34,400
Speaker 1: Los Angeles County. He studies things like conservation, genetics, the

795
00:48:34,480 --> 00:48:38,600
Speaker 1: effects of urbanization, and he's a herpetologist. Great, can you

796
00:48:38,680 --> 00:48:41,799
Speaker 1: explain what that means to our audience. Yeah, so herpetology

797
00:48:41,880 --> 00:48:44,680
Speaker 1: is the study of reptiles and amphibians. And then the

798
00:48:44,719 --> 00:48:47,640
Speaker 1: curator part of what I do is at the Natural

799
00:48:47,680 --> 00:48:50,520
Speaker 1: History z M, I do a combination of research. We're

800
00:48:50,600 --> 00:48:52,719
Speaker 1: working on exhibits in that region, and maybe the most

801
00:48:52,760 --> 00:48:54,799
Speaker 1: important part of my job is actually taking care of

802
00:48:54,840 --> 00:48:57,719
Speaker 1: this research collection, which is we have a hundred ninety

803
00:48:57,760 --> 00:49:01,279
Speaker 1: thousand research specimens that are opped out to researchers all

804
00:49:01,280 --> 00:49:04,200
Speaker 1: around the country, um for their own research needs. Now,

805
00:49:04,200 --> 00:49:08,600
Speaker 1: are these are these specimens alive or preserved in some way?

806
00:49:08,719 --> 00:49:12,520
Speaker 1: These are all one ninety of those are preserved animals.

807
00:49:12,520 --> 00:49:16,040
Speaker 1: So they are animals that we either received dead or

808
00:49:16,160 --> 00:49:18,719
Speaker 1: some researcher in the past used for their research and

809
00:49:18,760 --> 00:49:21,279
Speaker 1: then it's still had research you know, potential, and so

810
00:49:21,360 --> 00:49:24,280
Speaker 1: it was preserved and it's still now available for scientists

811
00:49:24,280 --> 00:49:28,239
Speaker 1: to use. And so how do you maintain preserved a

812
00:49:28,280 --> 00:49:31,480
Speaker 1: bunch of preserved reptiles? Yeah, so it'll depend on what

813
00:49:31,560 --> 00:49:33,640
Speaker 1: kind of collection you're thinking about. For a collection like

814
00:49:33,680 --> 00:49:36,680
Speaker 1: reptiles amphibians, we have what are called wet specimens, So

815
00:49:36,800 --> 00:49:40,279
Speaker 1: we preserve all of our animals first and formulae and

816
00:49:40,280 --> 00:49:42,920
Speaker 1: then transfer them over to alcohol and then they will

817
00:49:42,920 --> 00:49:47,279
Speaker 1: stay in a jar of alcohol for literally decades, you know,

818
00:49:47,320 --> 00:49:51,840
Speaker 1: really centuries to come. Yeah, I've seen like, uh, specimens

819
00:49:51,840 --> 00:49:53,640
Speaker 1: that are like hundreds of years old and they look

820
00:49:53,719 --> 00:49:57,279
Speaker 1: pretty good. Yeah, it's amazing. So we that method of

821
00:49:57,320 --> 00:49:59,800
Speaker 1: form of preserving and formulat and then switching to alcohol.

822
00:50:00,200 --> 00:50:02,880
Speaker 1: That method has only been around since about nineteen o

823
00:50:02,920 --> 00:50:05,520
Speaker 1: five six. And if you look at a specimen that

824
00:50:05,600 --> 00:50:08,640
Speaker 1: was preserved that way, say in five, and you look

825
00:50:08,680 --> 00:50:10,600
Speaker 1: at one that was preserved in nine, you can't tell

826
00:50:10,640 --> 00:50:12,680
Speaker 1: the difference. If I show you one that I preserved

827
00:50:12,840 --> 00:50:14,560
Speaker 1: last year and I show you one that was preserved

828
00:50:14,600 --> 00:50:16,640
Speaker 1: thirty years ago, yeah there's a little bit of a difference.

829
00:50:16,960 --> 00:50:21,320
Speaker 1: But we estimate that these specimens have cared for properly,

830
00:50:21,360 --> 00:50:24,399
Speaker 1: will be useful for researchers for a minimum of three years.

831
00:50:25,000 --> 00:50:27,360
Speaker 1: But there are specimens that were preserved in all sorts

832
00:50:27,360 --> 00:50:30,000
Speaker 1: of bizarre ways, usually like in some sort of alcohol

833
00:50:30,040 --> 00:50:33,200
Speaker 1: e spirit from the late sixteen hundreds, that are still

834
00:50:33,239 --> 00:50:37,080
Speaker 1: in European museums and still available for research use. That's amazing.

835
00:50:37,160 --> 00:50:40,480
Speaker 1: So like, uh, does research ever take one of those

836
00:50:40,520 --> 00:50:44,359
Speaker 1: really old specimens and do genetic testing on them or

837
00:50:44,480 --> 00:50:47,360
Speaker 1: so It's funny like, once you preserve something in formula,

838
00:50:47,400 --> 00:50:49,600
Speaker 1: it makes it really hard to get DNA out of.

839
00:50:50,680 --> 00:50:53,400
Speaker 1: So actually those older specimens that were never exposed to

840
00:50:53,440 --> 00:50:57,719
Speaker 1: formula oftentimes are better at DNA then, say something that's

841
00:50:57,719 --> 00:51:00,800
Speaker 1: from the nineteen thirties, and then what we do today

842
00:51:01,000 --> 00:51:02,680
Speaker 1: is before we expose it to formula and we take

843
00:51:02,680 --> 00:51:04,440
Speaker 1: a tissue sam. I see, so you have the d

844
00:51:04,560 --> 00:51:07,320
Speaker 1: N a kind of lot. Yeah, so I I curate

845
00:51:07,880 --> 00:51:10,920
Speaker 1: the what collection. We also have a skeletal collection, and

846
00:51:11,000 --> 00:51:12,680
Speaker 1: on top of that, we have a tissue collection which

847
00:51:12,719 --> 00:51:15,080
Speaker 1: is in a negative a d degree Celsius freezer, and

848
00:51:15,120 --> 00:51:16,799
Speaker 1: so we have all these tissue samples, and so when

849
00:51:16,880 --> 00:51:19,640
Speaker 1: researchers just want to look at a tissue, they can

850
00:51:19,640 --> 00:51:21,880
Speaker 1: request that tissue stample and we might then ship that

851
00:51:21,920 --> 00:51:26,320
Speaker 1: off to them for them. That's some Jurassic Park stuff situation.

852
00:51:26,520 --> 00:51:29,040
Speaker 1: We hope that nobody's cloning, you know, trying to bring back,

853
00:51:29,080 --> 00:51:32,560
Speaker 1: you know, something that hasn't been approved. Yeah, we're not

854
00:51:32,600 --> 00:51:35,160
Speaker 1: too worried about that. Yeah, no, that that's awesome. So

855
00:51:35,440 --> 00:51:37,200
Speaker 1: I wanted to talk to you a bit about the

856
00:51:37,239 --> 00:51:41,840
Speaker 1: Citizens Science Initiative that you and the Natural History Museum

857
00:51:42,280 --> 00:51:45,680
Speaker 1: are doing so, you're recruiting l A residents to help

858
00:51:45,760 --> 00:51:50,680
Speaker 1: with documenting animal populations and behaviors. Can you talk a

859
00:51:50,680 --> 00:51:53,719
Speaker 1: little bit about what citizen science is in how it

860
00:51:53,800 --> 00:51:56,520
Speaker 1: helps with your research. Yes, a citizen science, I mean

861
00:51:56,520 --> 00:51:59,920
Speaker 1: the basic idea of citizen sciences. It's crowdsourcing. It's basically

862
00:52:00,520 --> 00:52:04,640
Speaker 1: asking members of the public to help answer to work

863
00:52:04,680 --> 00:52:07,280
Speaker 1: with a professional scientist to help answer some research question.

864
00:52:08,000 --> 00:52:11,640
Speaker 1: And as a museum curator, I have this amazing time

865
00:52:11,680 --> 00:52:14,279
Speaker 1: machine where I can go into the collections and I

866
00:52:14,280 --> 00:52:16,480
Speaker 1: can find all these specimens that tell me for a

867
00:52:16,480 --> 00:52:19,880
Speaker 1: place like l A. You know this absolutely amazing huge cities,

868
00:52:19,880 --> 00:52:21,440
Speaker 1: one of one of the biggest cities in the world.

869
00:52:21,920 --> 00:52:23,879
Speaker 1: We have the specimens that tell us where species were

870
00:52:23,880 --> 00:52:26,640
Speaker 1: found at a particular place at a particular time. So

871
00:52:26,680 --> 00:52:29,320
Speaker 1: we know like the distributions of species in the past,

872
00:52:29,680 --> 00:52:32,240
Speaker 1: But how do you learn where some of those species

873
00:52:32,239 --> 00:52:34,839
Speaker 1: are found today? When everything is private property? Like, that's

874
00:52:34,840 --> 00:52:37,040
Speaker 1: not places that I can easily as a scientist go

875
00:52:37,160 --> 00:52:40,160
Speaker 1: do research. You can't take your team of grad students

876
00:52:40,160 --> 00:52:44,520
Speaker 1: into someone's lawn up not ly usually so in order

877
00:52:44,560 --> 00:52:47,680
Speaker 1: to avoid being shot or you know, getting getting trespassing

878
00:52:47,719 --> 00:52:50,840
Speaker 1: tickets all the time. Um, we use this crowd sourcing approach.

879
00:52:50,840 --> 00:52:52,919
Speaker 1: We use citizen science. So we basically just asked people

880
00:52:52,920 --> 00:52:54,960
Speaker 1: to pull out their smartphones and their digital cameras and

881
00:52:54,960 --> 00:52:57,560
Speaker 1: take photographs of what they see and upload it to

882
00:52:57,600 --> 00:53:01,360
Speaker 1: this amazing website, this this online community of science or

883
00:53:01,360 --> 00:53:05,239
Speaker 1: citizen science platform called by naturalists. So by doing that,

884
00:53:05,440 --> 00:53:08,239
Speaker 1: I can learn where things are found today, compare that

885
00:53:08,320 --> 00:53:10,800
Speaker 1: to the historical records in the museums, and see how

886
00:53:11,200 --> 00:53:13,759
Speaker 1: ranges are shifting over the course of urbanization. So it

887
00:53:13,760 --> 00:53:16,520
Speaker 1: has these massive conservation benefits and you can use that

888
00:53:16,560 --> 00:53:20,160
Speaker 1: information for landscape and urban planning. But these photographs that

889
00:53:20,200 --> 00:53:23,200
Speaker 1: people are taking aren't just like, oh, here's an animal

890
00:53:23,760 --> 00:53:25,600
Speaker 1: and it shows you where it is. Yes, that's all true,

891
00:53:25,920 --> 00:53:29,960
Speaker 1: But sometimes they're photographing really interesting ecological or behavioral phenomena

892
00:53:30,040 --> 00:53:33,520
Speaker 1: as well. I know this because so you had asked

893
00:53:33,560 --> 00:53:37,360
Speaker 1: for photos of alligator lizards, which is a totally normal

894
00:53:37,360 --> 00:53:41,480
Speaker 1: thing to ask for, right, Yeah, And I wass thinking like, oh,

895
00:53:41,560 --> 00:53:43,440
Speaker 1: that'd be cool if I could could find them. But

896
00:53:43,480 --> 00:53:45,200
Speaker 1: I didn't have much hope because I live in a

897
00:53:45,360 --> 00:53:49,000
Speaker 1: very sort of uh like a bunch of apartments and

898
00:53:49,080 --> 00:53:50,799
Speaker 1: streets and I thought there's no way they would want

899
00:53:50,800 --> 00:53:53,319
Speaker 1: to be here. But there's a pair of them right

900
00:53:53,440 --> 00:53:56,600
Speaker 1: in the middle of the sidewalk, um doing their weird

901
00:53:56,680 --> 00:54:00,000
Speaker 1: mating ritual where the male bites down on the female

902
00:54:00,200 --> 00:54:02,680
Speaker 1: head and they just like stay there. And so like

903
00:54:02,719 --> 00:54:05,560
Speaker 1: there's all this foot traffic and like I'm on like

904
00:54:05,920 --> 00:54:08,480
Speaker 1: kneel down onto the sidewalk with my phone and like

905
00:54:08,560 --> 00:54:11,280
Speaker 1: do close ups. And people are kind of laughing because

906
00:54:11,280 --> 00:54:14,880
Speaker 1: it's like, you know, a little different is the weirdo

907
00:54:14,960 --> 00:54:18,640
Speaker 1: and the yoga pants taking photos of of lizards getting

908
00:54:18,640 --> 00:54:21,919
Speaker 1: it on. Um, But yeah, that is it's really fun

909
00:54:22,000 --> 00:54:25,200
Speaker 1: to kind of be feel like you're contributing to science

910
00:54:25,280 --> 00:54:27,959
Speaker 1: without having to do any of the other hard work.

911
00:54:28,200 --> 00:54:29,760
Speaker 1: So this is and this is such a great example.

912
00:54:29,840 --> 00:54:32,520
Speaker 1: So what you have seen, you've now seen to southern

913
00:54:32,560 --> 00:54:35,960
Speaker 1: alligator lizards mating. I've lived within the range of the

914
00:54:35,960 --> 00:54:41,839
Speaker 1: southern alligator lizard for thirty six years of thirty four

915
00:54:41,920 --> 00:54:45,560
Speaker 1: years of my life, I've never seen this. Um, you

916
00:54:45,560 --> 00:54:48,080
Speaker 1: have now seen something that I've never seen. And yet

917
00:54:48,160 --> 00:54:50,880
Speaker 1: I study this. And the reason that we rely on

918
00:54:50,960 --> 00:54:53,840
Speaker 1: citizen science is for exactly that it's just random chance

919
00:54:53,920 --> 00:54:55,799
Speaker 1: that you're going to happen upon them. And so if

920
00:54:55,920 --> 00:54:58,440
Speaker 1: enough people know about it, they'll be able to And

921
00:54:58,480 --> 00:55:01,759
Speaker 1: everyone has smartphones now, like you have your camera on

922
00:55:01,840 --> 00:55:04,080
Speaker 1: you at all times, and so I mean here you

923
00:55:04,080 --> 00:55:07,319
Speaker 1: have the situation where an observation that's rarely observed by

924
00:55:07,360 --> 00:55:10,280
Speaker 1: any one person, but by crowdsourcing it, we can generate

925
00:55:10,320 --> 00:55:14,319
Speaker 1: this amazing data set. So as of this morning, over

926
00:55:14,400 --> 00:55:16,840
Speaker 1: five years of doing this on citizen Science, we've generated

927
00:55:16,840 --> 00:55:20,600
Speaker 1: a data set of roughly three hundred and fifty observation.

928
00:55:21,480 --> 00:55:23,560
Speaker 1: Well I shouldn't say rough actually did the math this morning,

929
00:55:23,640 --> 00:55:26,040
Speaker 1: so it's actually like three d and fifty two observations

930
00:55:26,120 --> 00:55:28,280
Speaker 1: this morning, and five years of promoting this on citizen science,

931
00:55:28,280 --> 00:55:31,240
Speaker 1: I myself has still never seen this in the entirety

932
00:55:31,320 --> 00:55:34,200
Speaker 1: of the pure view scientific literature. There are three reported

933
00:55:34,719 --> 00:55:38,600
Speaker 1: dates of when alligator lizards have been observed mating, and

934
00:55:38,640 --> 00:55:41,400
Speaker 1: so you can't do anything. You can't do anything with

935
00:55:41,400 --> 00:55:44,279
Speaker 1: three observations, like you can infer like how do how

936
00:55:44,280 --> 00:55:47,080
Speaker 1: does the timing of breeding whether from year to year?

937
00:55:47,200 --> 00:55:49,440
Speaker 1: The sample size as too small, you can't you can't

938
00:55:49,480 --> 00:55:51,680
Speaker 1: do any statistics on it. You can infer any general putnis.

939
00:55:51,719 --> 00:55:56,040
Speaker 1: But with three observations. So I'm pretty sure. I'm still

940
00:55:56,080 --> 00:55:58,080
Speaker 1: like a little hesitant to say this, but I'm pretty

941
00:55:58,080 --> 00:56:00,400
Speaker 1: sure that the data set we've generate it is the

942
00:56:00,480 --> 00:56:04,840
Speaker 1: largest data set of like of matings for any lizard

943
00:56:04,880 --> 00:56:07,960
Speaker 1: species ever, which is, I mean pretty amazing. And I

944
00:56:07,960 --> 00:56:09,640
Speaker 1: still haven't even seen this. And I know there's like

945
00:56:09,680 --> 00:56:12,680
Speaker 1: some some listeners are like, yeah, but like what can

946
00:56:12,719 --> 00:56:15,400
Speaker 1: you do with that? Like right, But the reality is

947
00:56:15,440 --> 00:56:18,560
Speaker 1: that for the entire field of animal behavior, a huge

948
00:56:18,640 --> 00:56:22,160
Speaker 1: chunk of research is all about mating behaviors because that's

949
00:56:22,160 --> 00:56:25,919
Speaker 1: sort of the necessary step to population growth. And yeah,

950
00:56:25,960 --> 00:56:28,560
Speaker 1: I mean it's kind of critical to keeping your species going.

951
00:56:28,640 --> 00:56:30,520
Speaker 1: And so it's you know, it's really common that people

952
00:56:30,520 --> 00:56:33,200
Speaker 1: and it's there's so many amazing sort of evolutionary stories

953
00:56:33,239 --> 00:56:36,000
Speaker 1: within that field of like making behaviors and behavior. So

954
00:56:36,719 --> 00:56:38,960
Speaker 1: it's this amazing thing to be able to study. But

955
00:56:39,040 --> 00:56:40,680
Speaker 1: for most species, you're never going to be able to

956
00:56:40,680 --> 00:56:43,960
Speaker 1: generate enough observations. But you can solve that problem by

957
00:56:44,000 --> 00:56:47,560
Speaker 1: crowdsourcing too. I remember, I think you guys you released

958
00:56:47,560 --> 00:56:50,560
Speaker 1: a really funny Valentine's Day called action or it is,

959
00:56:50,640 --> 00:56:53,719
Speaker 1: like do you remember that. Well, we've done this so

960
00:56:54,040 --> 00:56:55,759
Speaker 1: This was not I wish this is my good idea,

961
00:56:55,800 --> 00:56:57,960
Speaker 1: but it was not. It was somebody in our marketing

962
00:56:57,960 --> 00:57:00,239
Speaker 1: group said, if you're you know, if they ead in

963
00:57:00,239 --> 00:57:04,000
Speaker 1: the spring, why are you announcing this in early March.

964
00:57:04,280 --> 00:57:06,840
Speaker 1: Why don't you just announce it on Valentine's Yeah, And

965
00:57:06,920 --> 00:57:09,520
Speaker 1: so we absolutely just started making you know, we have this,

966
00:57:09,600 --> 00:57:11,920
Speaker 1: we have this nature and l a blog and it's

967
00:57:11,960 --> 00:57:13,640
Speaker 1: a way to reach out to a broad audience to

968
00:57:13,719 --> 00:57:16,960
Speaker 1: get people excited about you know, nature events that are

969
00:57:16,960 --> 00:57:20,560
Speaker 1: happening across across the region. And so yeah, we just

970
00:57:20,560 --> 00:57:23,200
Speaker 1: started producing it on Valentine's Day. And I forget all

971
00:57:23,200 --> 00:57:24,960
Speaker 1: the titles that we've used, because we've done we've done

972
00:57:24,960 --> 00:57:27,520
Speaker 1: a handful of these now. But it's basically, you know,

973
00:57:27,640 --> 00:57:30,200
Speaker 1: just trying to you know, get the word out. In

974
00:57:30,280 --> 00:57:32,240
Speaker 1: Valentine's Day is a great day to do that because

975
00:57:32,240 --> 00:57:35,200
Speaker 1: it's when when humans are thinking about sort of romance,

976
00:57:35,200 --> 00:57:38,200
Speaker 1: and we've got alligator litles thinking about romance and pair

977
00:57:38,280 --> 00:57:43,400
Speaker 1: those things toge and also other odors related to us alligator.

978
00:57:43,760 --> 00:57:46,960
Speaker 1: There's all sorts of great stuff going on. Um, what's

979
00:57:47,440 --> 00:57:51,000
Speaker 1: have you ever gotten a really weird or exciting submission

980
00:57:51,080 --> 00:57:53,520
Speaker 1: like a submitted photo of something that's just like blew

981
00:57:53,560 --> 00:57:56,440
Speaker 1: your mind. I mean, it's so hard for me to

982
00:57:56,440 --> 00:58:00,600
Speaker 1: whittle it down to one because we get these amazing

983
00:58:00,640 --> 00:58:03,800
Speaker 1: photographs I mean all the time, Like I feel like

984
00:58:04,000 --> 00:58:06,160
Speaker 1: I could give you a different answer to this almost

985
00:58:06,280 --> 00:58:10,280
Speaker 1: every other week. So I mean, I think some of

986
00:58:10,280 --> 00:58:13,440
Speaker 1: the neatest photos that we've received are things like I mean,

987
00:58:13,440 --> 00:58:16,320
Speaker 1: sometimes there's a single photo that literally does tell a

988
00:58:16,360 --> 00:58:19,880
Speaker 1: thousand words, and so that single photograph. UM. For some

989
00:58:19,920 --> 00:58:22,280
Speaker 1: of the cases that we've had recently have been things

990
00:58:22,280 --> 00:58:25,600
Speaker 1: like somebody took a photograph of some lizard species, for example,

991
00:58:26,040 --> 00:58:28,960
Speaker 1: that had never before been documented in California. So a

992
00:58:29,000 --> 00:58:30,680
Speaker 1: great example of this is this guy by the name

993
00:58:30,680 --> 00:58:32,720
Speaker 1: of Glenn Yoshida. I hope Glenn doesn't mind me using

994
00:58:32,720 --> 00:58:35,360
Speaker 1: his name. UM. And I never met Glenn when this

995
00:58:35,360 --> 00:58:37,840
Speaker 1: story actually happened. But Glenn was walking into his house

996
00:58:37,960 --> 00:58:41,640
Speaker 1: one day after work, and I think he even had like,

997
00:58:42,120 --> 00:58:44,200
Speaker 1: you know, groceries in one hand, and there's a gecko

998
00:58:44,440 --> 00:58:46,960
Speaker 1: hanging out right above his front door. And he took

999
00:58:46,960 --> 00:58:48,640
Speaker 1: a photo of this gecko and he emailed it to

1000
00:58:48,760 --> 00:58:51,280
Speaker 1: the to the Natural History Museum where I work, and

1001
00:58:51,360 --> 00:58:53,240
Speaker 1: so he didn't actually just upload a tin Naturalists. He

1002
00:58:53,240 --> 00:58:55,760
Speaker 1: wasn't a Ninaturalist user at the time. He just he

1003
00:58:55,920 --> 00:58:57,600
Speaker 1: just sent it right to us until I got this

1004
00:58:57,640 --> 00:58:59,360
Speaker 1: email from Glenn, and I was like, whoa, I don't

1005
00:59:00,240 --> 00:59:01,800
Speaker 1: I basically, I mean, I knew it was a house

1006
00:59:01,800 --> 00:59:03,240
Speaker 1: gecko of some kind, so I knew the genius, but

1007
00:59:03,240 --> 00:59:04,800
Speaker 1: I didn't know what species it was. And so I

1008
00:59:04,800 --> 00:59:06,560
Speaker 1: actually emailed back to Glenn and I said, oh, hey,

1009
00:59:06,560 --> 00:59:09,480
Speaker 1: this is a really interesting find. Um, would could I

1010
00:59:09,520 --> 00:59:10,920
Speaker 1: could you send me your phone number? I'd like to

1011
00:59:10,960 --> 00:59:12,560
Speaker 1: chat with you about this, And so he sent me

1012
00:59:12,920 --> 00:59:14,760
Speaker 1: send me his phone number. So I called him up.

1013
00:59:14,800 --> 00:59:16,720
Speaker 1: This is like two hours later, It's like at nine

1014
00:59:16,760 --> 00:59:19,120
Speaker 1: o'clock on a Wednesday night or something. So I called

1015
00:59:19,200 --> 00:59:21,520
Speaker 1: up Glenn and I said, hey, you know, I know

1016
00:59:21,560 --> 00:59:23,200
Speaker 1: it's one of two species. I don't know which one.

1017
00:59:23,640 --> 00:59:27,800
Speaker 1: Neither has ever been documented as established in California. UM,

1018
00:59:28,040 --> 00:59:29,680
Speaker 1: do you have have you seen multiple individuals? He goes

1019
00:59:29,680 --> 00:59:31,280
Speaker 1: like yeah, I have seen multiple individuals for a couple

1020
00:59:31,320 --> 00:59:34,320
Speaker 1: of years. And I said, okay, well, like, can I

1021
00:59:34,320 --> 00:59:37,000
Speaker 1: just come to your house tomorrow at around a p m.

1022
00:59:37,040 --> 00:59:38,840
Speaker 1: And then we'll just wander around your neighborhood and see

1023
00:59:38,840 --> 00:59:41,640
Speaker 1: if we can. Yeah, just hanging out looking for geckos.

1024
00:59:41,640 --> 00:59:44,959
Speaker 1: And he's like, yeah, you seem like a totally normal human. Sure. Um,

1025
00:59:45,040 --> 00:59:47,240
Speaker 1: so yeah. The next night I showed up at Glenn's house.

1026
00:59:47,280 --> 00:59:48,880
Speaker 1: We wandered around his house and we did find some

1027
00:59:48,880 --> 00:59:50,280
Speaker 1: more geckos, and once I had one in hand, I

1028
00:59:50,360 --> 00:59:51,760
Speaker 1: knew what it was. It's a thing called the Indo

1029
00:59:51,800 --> 00:59:55,800
Speaker 1: Pacific gecko. And it's an Yeah, it's not it's yeah,

1030
00:59:55,840 --> 00:59:58,400
Speaker 1: I mean it's from the Indo Pacific region, so in

1031
00:59:58,400 --> 01:00:01,000
Speaker 1: their native range. I mean it's thousands of miles away

1032
01:00:01,040 --> 01:00:04,760
Speaker 1: from here and so, but they are in Hawaii and

1033
01:00:04,760 --> 01:00:06,640
Speaker 1: they get moved around in the nursery plant trade. There

1034
01:00:06,720 --> 01:00:11,000
Speaker 1: also some populations on a plant exactly so, and it's

1035
01:00:11,040 --> 01:00:14,280
Speaker 1: an all female species. So one individual shows up, she

1036
01:00:14,440 --> 01:00:17,200
Speaker 1: lays eggs, her daughter's hatch out, and then they grew

1037
01:00:17,240 --> 01:00:20,440
Speaker 1: up to lay eggs as well. It's it's like parthen

1038
01:00:21,000 --> 01:00:23,800
Speaker 1: exactly so. This is an a sexual species of parthenagenetic species.

1039
01:00:23,800 --> 01:00:26,160
Speaker 1: So it just takes one individual to start a new population.

1040
01:00:26,880 --> 01:00:28,280
Speaker 1: And we see this a lot a lot of these

1041
01:00:28,320 --> 01:00:31,240
Speaker 1: non native species, particularly in reptiles. A lot of the

1042
01:00:31,280 --> 01:00:34,320
Speaker 1: non native species that show up, are these a sexual

1043
01:00:34,360 --> 01:00:38,880
Speaker 1: lineages because it only takes you don't need to individuals. Yeah,

1044
01:00:38,880 --> 01:00:40,280
Speaker 1: and you get all these crazy thing time me. So

1045
01:00:40,280 --> 01:00:42,720
Speaker 1: like literally a lot of my field work is doing

1046
01:00:42,760 --> 01:00:46,000
Speaker 1: things like wandering around neighborhoods and Torrents. Were wandering around

1047
01:00:46,040 --> 01:00:49,000
Speaker 1: neighborhoods and Orange or you know, all across southern California.

1048
01:00:49,040 --> 01:00:51,680
Speaker 1: I'm just out looking for geckos and so. But that

1049
01:00:51,760 --> 01:00:55,360
Speaker 1: one photograph and that triggered us doing this field work.

1050
01:00:55,400 --> 01:00:56,760
Speaker 1: I never would have found this on my own. It

1051
01:00:56,760 --> 01:00:59,160
Speaker 1: turns out they were only on basically Glenn's house. He

1052
01:00:59,200 --> 01:01:01,760
Speaker 1: doesn't know how about how happened. They actually died out

1053
01:01:01,800 --> 01:01:04,560
Speaker 1: after about five years, so they're not there anymore. But

1054
01:01:04,680 --> 01:01:07,440
Speaker 1: we have since then found actually two months after Glenn's discovery,

1055
01:01:07,480 --> 01:01:10,200
Speaker 1: we found them down in Um in Orange County as well,

1056
01:01:10,320 --> 01:01:14,000
Speaker 1: in the Lake Forest neighborhood. Again, a single photograph started that,

1057
01:01:14,120 --> 01:01:18,160
Speaker 1: and so Glenn and the gentleman down in Um in

1058
01:01:18,280 --> 01:01:20,240
Speaker 1: Lake Forest and Orange County he made this discovery. His

1059
01:01:20,280 --> 01:01:22,360
Speaker 1: name is Bob. Were all so Glenn and Bob and

1060
01:01:22,400 --> 01:01:24,480
Speaker 1: I actually the three of us together wrote up a

1061
01:01:24,480 --> 01:01:27,080
Speaker 1: little paper on this, published it, and so Glenn and

1062
01:01:27,120 --> 01:01:30,840
Speaker 1: Bob started out as you know, people taking photographs. He

1063
01:01:30,960 --> 01:01:33,560
Speaker 1: being these sort of citizen scientists participating in this project.

1064
01:01:33,840 --> 01:01:35,720
Speaker 1: Then they went all the way through the scientific process,

1065
01:01:35,720 --> 01:01:38,200
Speaker 1: all the way to publishing in the peer reviewed scientific literature,

1066
01:01:38,640 --> 01:01:40,920
Speaker 1: which and that all starts with one photo. That's amazing,

1067
01:01:41,000 --> 01:01:44,080
Speaker 1: so you can, like, you can become peer reviewed if

1068
01:01:44,120 --> 01:01:46,000
Speaker 1: you have your phone and you take some if you

1069
01:01:46,040 --> 01:01:49,000
Speaker 1: get if you end up happening to take a photograph,

1070
01:01:49,080 --> 01:01:51,240
Speaker 1: that is somehow you know, extra Sit and Glenn and

1071
01:01:51,280 --> 01:01:54,600
Speaker 1: Bob's case. You know, these are the first documented established

1072
01:01:54,600 --> 01:01:57,120
Speaker 1: populations of these geckos in the state of California, so

1073
01:01:57,400 --> 01:02:00,120
Speaker 1: first state record and then first county record and a

1074
01:02:00,200 --> 01:02:02,720
Speaker 1: and first county record in origin. So it was really significant.

1075
01:02:02,720 --> 01:02:06,040
Speaker 1: You know, most of the observations aren't something that's quite

1076
01:02:06,160 --> 01:02:10,560
Speaker 1: that significant, but are still really important for thinking about,

1077
01:02:10,800 --> 01:02:13,200
Speaker 1: you know, how species are responding to urbanization. And of course,

1078
01:02:13,720 --> 01:02:16,480
Speaker 1: you know this whole effort, this sort of citizen science effort,

1079
01:02:16,560 --> 01:02:19,080
Speaker 1: sort of using these photographs that are put up on naturalists.

1080
01:02:19,240 --> 01:02:21,800
Speaker 1: This has been going on for ten years. Well, yeah,

1081
01:02:22,000 --> 01:02:23,960
Speaker 1: that's a good amount of time to get it's great,

1082
01:02:24,520 --> 01:02:26,800
Speaker 1: but what about the scientists that are here two hundred

1083
01:02:26,840 --> 01:02:29,680
Speaker 1: years from now, three years from now, you think about

1084
01:02:29,680 --> 01:02:32,960
Speaker 1: the digital legacy of biodiversity data that we're leaving these

1085
01:02:33,000 --> 01:02:35,720
Speaker 1: future scientists. I mean, it's amazing to think that like

1086
01:02:36,360 --> 01:02:40,920
Speaker 1: any person out there can actually create this absolutely amazing

1087
01:02:41,200 --> 01:02:45,320
Speaker 1: research potentially of conservation value for for scientists of the future.

1088
01:02:45,800 --> 01:02:48,680
Speaker 1: So we can think about leaving this like digital biodiversity data.

1089
01:02:49,600 --> 01:02:52,440
Speaker 1: It's really kind of and it plays into this whole

1090
01:02:52,440 --> 01:02:56,800
Speaker 1: idea of like now that it's everyone's responsibility what's happening

1091
01:02:56,880 --> 01:03:00,439
Speaker 1: to our planet? And um, I think you know, most

1092
01:03:00,480 --> 01:03:02,600
Speaker 1: people think about it in terms of like recycling and

1093
01:03:02,880 --> 01:03:06,520
Speaker 1: and being you know, a good conservationist, and that's all good,

1094
01:03:06,560 --> 01:03:09,479
Speaker 1: but I think that they're these un lesser known things

1095
01:03:09,480 --> 01:03:11,720
Speaker 1: that you can do and really take an active role

1096
01:03:12,240 --> 01:03:15,320
Speaker 1: in helping conservation efforts. And that's a great way to

1097
01:03:15,320 --> 01:03:17,680
Speaker 1: think about it. Yeah, and it's it truly is this

1098
01:03:17,800 --> 01:03:20,480
Speaker 1: absolutely amazing resource. And so if we just think about

1099
01:03:20,880 --> 01:03:22,880
Speaker 1: like a place like Los Angeles a hundred years ago

1100
01:03:22,960 --> 01:03:24,480
Speaker 1: or even fifty years ago, and you think about the

1101
01:03:24,520 --> 01:03:26,960
Speaker 1: species that we're common here, and in fact, one of

1102
01:03:27,000 --> 01:03:28,960
Speaker 1: the species it was really common here was the horn lizard,

1103
01:03:29,000 --> 01:03:32,400
Speaker 1: which is species that you're super excited about. So, that

1104
01:03:32,520 --> 01:03:37,120
Speaker 1: was the most common backyard lizard in UM, some of

1105
01:03:37,120 --> 01:03:39,640
Speaker 1: the foothill communities in the San Gabriel Valley up until

1106
01:03:39,640 --> 01:03:42,800
Speaker 1: the nineteen fifties, and they're now gone, completely gone. And

1107
01:03:42,840 --> 01:03:45,160
Speaker 1: so in this relatively short period of time, we've seen

1108
01:03:45,160 --> 01:03:47,880
Speaker 1: this massive change in the fauna. Well, the data that

1109
01:03:47,880 --> 01:03:49,920
Speaker 1: we're generating today, we might even it might even be

1110
01:03:49,960 --> 01:03:52,320
Speaker 1: for common species, but it's the thing that we think

1111
01:03:52,400 --> 01:03:54,600
Speaker 1: is common now. Maybe fifty years from now it won't

1112
01:03:54,600 --> 01:03:56,680
Speaker 1: be called yeah, and we'll we'll have a much more

1113
01:03:56,880 --> 01:03:59,960
Speaker 1: sort of like UM, subtle we'll see be able to

1114
01:04:00,080 --> 01:04:04,439
Speaker 1: track subtle changes much better with larger data exactly. So. UM.

1115
01:04:04,520 --> 01:04:08,720
Speaker 1: The Natural History Museum of Los Angeles County recently released

1116
01:04:08,760 --> 01:04:12,280
Speaker 1: a new book called Wild l A, exploring the amazing

1117
01:04:12,360 --> 01:04:16,040
Speaker 1: nature in and around Los Angeles. UM. So I got

1118
01:04:16,040 --> 01:04:18,440
Speaker 1: a sneak peek, and it's really beautiful. It's got these

1119
01:04:18,480 --> 01:04:22,080
Speaker 1: amazing photos, and it's also really exciting for l A

1120
01:04:22,200 --> 01:04:26,520
Speaker 1: residents in understanding native species in our own backyards and

1121
01:04:26,560 --> 01:04:29,040
Speaker 1: being able to see like, oh, here's this cool photo

1122
01:04:29,080 --> 01:04:32,800
Speaker 1: and then know exactly like where the species kind of

1123
01:04:32,920 --> 01:04:36,080
Speaker 1: is found. Um, what are some of the unique things

1124
01:04:36,120 --> 01:04:40,400
Speaker 1: that people could learn from this book. So yeah, so

1125
01:04:40,440 --> 01:04:42,200
Speaker 1: I mean this is this was a really fun project

1126
01:04:42,200 --> 01:04:43,840
Speaker 1: to be a part of UM. One of the four

1127
01:04:43,880 --> 01:04:47,800
Speaker 1: authors UM, and it's it's really written for people who

1128
01:04:47,840 --> 01:04:49,800
Speaker 1: live in Los Angeles or even or people who are

1129
01:04:49,880 --> 01:04:51,800
Speaker 1: visiting Los Angeles because it's the book is really in

1130
01:04:51,840 --> 01:04:54,560
Speaker 1: three parts. It's sort of like ten introductory chapters, and

1131
01:04:54,560 --> 01:04:56,840
Speaker 1: as you said, tons of photos, tons of factoids, like

1132
01:04:56,920 --> 01:05:00,120
Speaker 1: lots of these little call out and then they're is

1133
01:05:00,120 --> 01:05:02,240
Speaker 1: a hundred one species accounts and it's native and non

1134
01:05:02,320 --> 01:05:04,120
Speaker 1: native species and every and a lot of it are

1135
01:05:04,120 --> 01:05:05,840
Speaker 1: the common species that people are going to see on

1136
01:05:05,840 --> 01:05:09,360
Speaker 1: a daily basis, but there's also aspirational species like bighorn

1137
01:05:09,440 --> 01:05:12,120
Speaker 1: sheep and and mountain lions. You know, things that are

1138
01:05:12,200 --> 01:05:14,520
Speaker 1: unlikely to see but like you, you might see them

1139
01:05:14,520 --> 01:05:16,480
Speaker 1: if you get lucky. And then it ends with twenty

1140
01:05:16,560 --> 01:05:21,160
Speaker 1: five UM recommended excursions all across the Los Angeles region.

1141
01:05:21,360 --> 01:05:23,280
Speaker 1: And so for people who are coming in from out

1142
01:05:23,320 --> 01:05:25,480
Speaker 1: of town, it's like we sort of hope that this

1143
01:05:25,520 --> 01:05:27,840
Speaker 1: is like one stop shopping, Like grab the book. You

1144
01:05:27,840 --> 01:05:29,360
Speaker 1: can quickly plan out a couple of hikes. You can

1145
01:05:29,400 --> 01:05:31,720
Speaker 1: identify some of the stuff that you see, and you

1146
01:05:31,720 --> 01:05:33,360
Speaker 1: can learn a lot about sort of nature and Los

1147
01:05:33,400 --> 01:05:36,560
Speaker 1: Angeles and why it's interesting. Um I think that when

1148
01:05:36,560 --> 01:05:39,480
Speaker 1: people think about l A, they think like Hollywood, the

1149
01:05:39,960 --> 01:05:42,440
Speaker 1: Hollywood star Walk of Fame, but there really is some

1150
01:05:42,640 --> 01:05:46,360
Speaker 1: pretty made, amazing habitats. So that's that's the single most

1151
01:05:46,560 --> 01:05:48,479
Speaker 1: that's the single biggest message we have in this book,

1152
01:05:48,480 --> 01:05:52,160
Speaker 1: which is that l A is absolutely amazing place for nature.

1153
01:05:52,640 --> 01:05:54,520
Speaker 1: And so I have a couple of factoids that I

1154
01:05:54,520 --> 01:05:57,720
Speaker 1: always like try to share with people. Um so, and

1155
01:05:57,840 --> 01:06:00,360
Speaker 1: I think this is something that like Angelina should be

1156
01:06:00,360 --> 01:06:02,240
Speaker 1: bragging about, and it's something that people should be coming

1157
01:06:02,280 --> 01:06:07,200
Speaker 1: to l A to experience. So um quick quick, first factory.

1158
01:06:07,240 --> 01:06:09,480
Speaker 1: This is actually one of my favorite things about Los Angeles.

1159
01:06:09,560 --> 01:06:11,400
Speaker 1: So California is always bragged that you can ski and

1160
01:06:11,440 --> 01:06:14,320
Speaker 1: surf in the same day, which is true, but l

1161
01:06:14,320 --> 01:06:16,760
Speaker 1: A naturalists can also brag as well because you can

1162
01:06:16,800 --> 01:06:20,400
Speaker 1: see wild bighorn sheep and green sea turtles in the

1163
01:06:20,440 --> 01:06:23,919
Speaker 1: same day. And this is totally doable, like we could

1164
01:06:23,920 --> 01:06:26,280
Speaker 1: actually how how would you go about doing that? So

1165
01:06:26,360 --> 01:06:28,280
Speaker 1: it's actually not that hard. So first of all, the

1166
01:06:28,320 --> 01:06:32,080
Speaker 1: sea turtle part is almost guaranteed because The northernmost resident

1167
01:06:32,120 --> 01:06:34,880
Speaker 1: population of sea turtles is in the lower San Gabriel

1168
01:06:35,000 --> 01:06:37,920
Speaker 1: River in Long Beach, and as long as it isn't

1169
01:06:38,000 --> 01:06:40,080
Speaker 1: as long as it hasn't been a day with recent

1170
01:06:40,200 --> 01:06:42,080
Speaker 1: rain so that the river is up and maybe it's

1171
01:06:42,120 --> 01:06:45,120
Speaker 1: kind of murky and and it sometimes it's easy to mistake,

1172
01:06:45,280 --> 01:06:47,520
Speaker 1: you know, some chunk of trash for maybe a turtle

1173
01:06:47,520 --> 01:06:49,400
Speaker 1: that just quickly hops its head up and disappears. But

1174
01:06:49,440 --> 01:06:51,280
Speaker 1: if you go on like a regular day where it

1175
01:06:51,320 --> 01:06:53,040
Speaker 1: hasn't had it like a recent flood of it, you're

1176
01:06:53,080 --> 01:06:56,040
Speaker 1: almost guaranteed to see a green sea turtle. And the

1177
01:06:56,080 --> 01:06:58,640
Speaker 1: crazy thing is that the platform above the river that

1178
01:06:58,680 --> 01:07:00,840
Speaker 1: you can stand on to look at these green tea journals,

1179
01:07:00,960 --> 01:07:02,880
Speaker 1: at times these turtles pop up and they're like eight

1180
01:07:02,880 --> 01:07:05,000
Speaker 1: feet away from you, like a green, a wild green

1181
01:07:05,040 --> 01:07:07,760
Speaker 1: sea turtle. That's incredible. So that alone, like you don't

1182
01:07:07,760 --> 01:07:10,160
Speaker 1: have to go out like scuba diving to no, you

1183
01:07:10,280 --> 01:07:12,040
Speaker 1: just you can like be sitting there in your flip

1184
01:07:12,040 --> 01:07:14,560
Speaker 1: flops and t shirt, sunglasses and hat and you're just like,

1185
01:07:14,600 --> 01:07:17,200
Speaker 1: there's a sea turtle. My day is made. Head back,

1186
01:07:17,280 --> 01:07:19,960
Speaker 1: go grabbing margarita somewhere. And then after the Margharita, you

1187
01:07:20,000 --> 01:07:21,640
Speaker 1: go see a big horn sheep. Yeah, so the big

1188
01:07:21,640 --> 01:07:24,760
Speaker 1: horn is not quite as guaranteed, but also you have

1189
01:07:24,800 --> 01:07:26,280
Speaker 1: a good shot at And the way to go see

1190
01:07:26,320 --> 01:07:28,280
Speaker 1: a big horn sheep is you drive up into the

1191
01:07:28,280 --> 01:07:31,160
Speaker 1: sand Gabriel Mountains up towards Mount Baldy and there's a

1192
01:07:31,160 --> 01:07:32,800
Speaker 1: couple of good spots. We recommend a few of them

1193
01:07:32,840 --> 01:07:34,240
Speaker 1: in the book. There's a couple of good spots where

1194
01:07:34,240 --> 01:07:36,320
Speaker 1: you can stop and check them out. And actually, one

1195
01:07:36,320 --> 01:07:37,840
Speaker 1: of the funny things that happened us is as we

1196
01:07:37,840 --> 01:07:39,440
Speaker 1: were doing research for the book, we went up to

1197
01:07:39,440 --> 01:07:42,880
Speaker 1: Mount Baldy up to the ski area, and you know,

1198
01:07:42,880 --> 01:07:44,720
Speaker 1: it's only like an hour and twenty minute drive or

1199
01:07:44,720 --> 01:07:46,720
Speaker 1: something like that from downtown Towline. So we just zipped

1200
01:07:46,760 --> 01:07:49,960
Speaker 1: up there and got out of the car, walked like

1201
01:07:50,800 --> 01:07:53,280
Speaker 1: six steps and I look over and there's these two

1202
01:07:53,400 --> 01:07:56,080
Speaker 1: rams just on the hillside, right across from the parking lot.

1203
01:07:56,120 --> 01:07:58,120
Speaker 1: I mean, we couldn't have planned it better. And it

1204
01:07:58,200 --> 01:07:59,919
Speaker 1: was like, okay, well, like we're done, you know, let's

1205
01:08:00,000 --> 01:08:01,560
Speaker 1: at a few photos and go home. And then the

1206
01:08:01,560 --> 01:08:03,680
Speaker 1: funny thing that that happened is that in our photographer,

1207
01:08:03,800 --> 01:08:05,960
Speaker 1: who is also one of the writers Charles Hood was

1208
01:08:06,000 --> 01:08:07,440
Speaker 1: there and we were trying to get some photos of

1209
01:08:07,440 --> 01:08:09,920
Speaker 1: these of these rams. And what we didn't know at

1210
01:08:09,920 --> 01:08:12,800
Speaker 1: the time but we quickly learned, is that um, during

1211
01:08:12,840 --> 01:08:15,520
Speaker 1: certain times of the year, the rams have all of

1212
01:08:15,520 --> 01:08:18,840
Speaker 1: these dominance behaviors, and so they basically engage in lots

1213
01:08:18,840 --> 01:08:21,679
Speaker 1: of sort of homosexual behaviors and do things like mounting

1214
01:08:21,680 --> 01:08:24,720
Speaker 1: each other, you know, standard sort of dominance displays. Not

1215
01:08:24,760 --> 01:08:29,160
Speaker 1: at all female hyenas. Lots of canids do it, so like,

1216
01:08:29,240 --> 01:08:34,240
Speaker 1: not at all uncommon. But we couldn't necessarily use a

1217
01:08:34,280 --> 01:08:37,640
Speaker 1: photograph of two very you know, very clearly rams like

1218
01:08:37,680 --> 01:08:40,880
Speaker 1: you know, big curving horns. We couldn't use photos of those,

1219
01:08:40,960 --> 01:08:42,559
Speaker 1: like if we only have one photo of big horn

1220
01:08:42,640 --> 01:08:44,799
Speaker 1: sheep in the book. We didn't think that the probably

1221
01:08:44,840 --> 01:08:46,840
Speaker 1: the best photo to have sort of this photo that's

1222
01:08:46,840 --> 01:08:49,360
Speaker 1: got this complex sort of behaviors behind it, not not

1223
01:08:49,479 --> 01:08:53,040
Speaker 1: in today's society. Maybe soon, maybe soon, hopefully, so it

1224
01:08:53,040 --> 01:08:54,760
Speaker 1: would have taken a longer caption like but it is

1225
01:08:54,760 --> 01:08:56,759
Speaker 1: such a I mean, so we actually, you know, we

1226
01:08:56,760 --> 01:08:58,360
Speaker 1: we literally could have done that. If we turned around

1227
01:08:58,360 --> 01:08:59,680
Speaker 1: that day and went straight back down, we could have

1228
01:08:59,720 --> 01:09:03,200
Speaker 1: seen big horn cheap and green sea turtles, and that's

1229
01:09:03,240 --> 01:09:04,600
Speaker 1: like pretty much the only place in the world that

1230
01:09:04,640 --> 01:09:06,479
Speaker 1: you could sort of do that, and what an amazing

1231
01:09:06,520 --> 01:09:08,519
Speaker 1: thing to be able to do, you know, and you're

1232
01:09:09,000 --> 01:09:11,120
Speaker 1: in both of those cases, you're like never more than

1233
01:09:11,160 --> 01:09:14,120
Speaker 1: like probably thirty thirty five miles as the crow flies

1234
01:09:14,160 --> 01:09:19,599
Speaker 1: from downtown and almost completely opposite sort of like biomas. Yeah,

1235
01:09:19,760 --> 01:09:22,240
Speaker 1: very very different, very different, and each of them has

1236
01:09:22,280 --> 01:09:23,439
Speaker 1: their own Like this is one of the things that

1237
01:09:23,439 --> 01:09:25,360
Speaker 1: we really try to focus on in Los Angeles is

1238
01:09:25,400 --> 01:09:28,160
Speaker 1: like we've had so much change, you know, because of

1239
01:09:28,240 --> 01:09:32,000
Speaker 1: urbanization and you know, the modification of the l A

1240
01:09:32,080 --> 01:09:33,640
Speaker 1: River and the same Gabriel River and also the things

1241
01:09:33,680 --> 01:09:36,400
Speaker 1: that have happened that every single species you see has

1242
01:09:36,439 --> 01:09:39,040
Speaker 1: this absolutely amazing story. Like green sea turtles have an

1243
01:09:39,040 --> 01:09:41,800
Speaker 1: amazing story. Big horn sheep and how they're managing to

1244
01:09:41,800 --> 01:09:43,479
Speaker 1: make it in the same Gabriel's you know, is a

1245
01:09:43,520 --> 01:09:46,360
Speaker 1: really interesting story. But you know how the eastern fox

1246
01:09:46,360 --> 01:09:49,400
Speaker 1: squirrel that we can almost certainly see, you know, right

1247
01:09:49,439 --> 01:09:51,760
Speaker 1: on the block outside of the studio, they have an

1248
01:09:51,760 --> 01:09:53,559
Speaker 1: amazing story as to how they got here. You know,

1249
01:09:53,600 --> 01:09:55,599
Speaker 1: every species here has an amazing story, and we tell

1250
01:09:55,600 --> 01:09:57,120
Speaker 1: as many of those as we can in this book.

1251
01:09:57,320 --> 01:10:01,840
Speaker 1: That's fantastic, I think as I mean, even if you're

1252
01:10:01,880 --> 01:10:04,519
Speaker 1: just coming to visit as a tourist, I feel like

1253
01:10:04,520 --> 01:10:07,000
Speaker 1: the Hollywood Walk of Fame is a little bit overrated,

1254
01:10:07,120 --> 01:10:12,080
Speaker 1: super crowded, kind of annoying. It's it's basically a sidewalk

1255
01:10:12,160 --> 01:10:16,760
Speaker 1: and people dressed as avatar blue avatars screaming at you,

1256
01:10:17,400 --> 01:10:21,400
Speaker 1: um and like seventy jack sparrows. It's not that cool.

1257
01:10:22,160 --> 01:10:25,880
Speaker 1: I think going and visiting some of the really incredible

1258
01:10:26,280 --> 01:10:30,000
Speaker 1: natural habitats around l A is a lot cooler. I mean,

1259
01:10:30,080 --> 01:10:32,040
Speaker 1: I think you know, when people say, oh, there's not

1260
01:10:32,080 --> 01:10:35,040
Speaker 1: much nature in l A, my my response is always,

1261
01:10:35,840 --> 01:10:38,000
Speaker 1: there are twelve million people who can get onto public

1262
01:10:38,040 --> 01:10:41,080
Speaker 1: transit and can be guaranteed to see a midsized carnivore

1263
01:10:41,160 --> 01:10:42,800
Speaker 1: by the end of the day. And it's easy to

1264
01:10:42,800 --> 01:10:44,360
Speaker 1: do that. All you have to do is show up

1265
01:10:44,360 --> 01:10:48,120
Speaker 1: at Griffith Park right around sunset and hang out around

1266
01:10:48,120 --> 01:10:51,120
Speaker 1: the picnic tables. Right with the picnic table grounds, meet

1267
01:10:51,320 --> 01:10:53,760
Speaker 1: the edges of the of the sort of coastal stage

1268
01:10:53,760 --> 01:10:57,840
Speaker 1: group there, the Chaparale there, and at dusk every single night,

1269
01:10:57,960 --> 01:11:00,960
Speaker 1: coyotes wander through this Like, what do you mean there's

1270
01:11:00,960 --> 01:11:04,000
Speaker 1: no nature? I guarantee you I can. I can twelve

1271
01:11:04,040 --> 01:11:06,080
Speaker 1: million people and go see a coyote on any given night.

1272
01:11:06,160 --> 01:11:08,800
Speaker 1: Like that's incredible. Yeah, and it should be celebrated, like

1273
01:11:08,840 --> 01:11:11,240
Speaker 1: this is an amazing place to see nature. It really is.

1274
01:11:11,720 --> 01:11:15,960
Speaker 1: Uh So, we've been talking today about urban avoids, exploiters

1275
01:11:16,080 --> 01:11:20,479
Speaker 1: and adapters. Do you have a favorite story of urban

1276
01:11:20,560 --> 01:11:24,599
Speaker 1: exploitation or adaptation? I mean, I think that the Eastern

1277
01:11:24,600 --> 01:11:27,240
Speaker 1: fox squirrel is a pretty amazing I mean there's so

1278
01:11:27,280 --> 01:11:29,920
Speaker 1: many stories of like amazing stories, but here in Los Angeles,

1279
01:11:30,000 --> 01:11:32,840
Speaker 1: I think especially the Eastern fox world. And this has

1280
01:11:32,840 --> 01:11:35,120
Speaker 1: actually played out over many cities. The Eastern fox squirrel

1281
01:11:35,160 --> 01:11:37,400
Speaker 1: has been introduced to a huge numbers of cities in

1282
01:11:37,439 --> 01:11:39,880
Speaker 1: the western YUS. The closest that s PCs should get

1283
01:11:39,920 --> 01:11:43,439
Speaker 1: to hear is like central Texas. But um, here in

1284
01:11:43,479 --> 01:11:45,519
Speaker 1: the Los Angeles region, what happened is that we have

1285
01:11:45,560 --> 01:11:47,360
Speaker 1: the Sautel Veterans However, what used to be called the

1286
01:11:47,360 --> 01:11:50,040
Speaker 1: Sautel Veterans zone. It's actually quite close to U C

1287
01:11:50,160 --> 01:11:51,760
Speaker 1: l A. It's just it's just west of the four

1288
01:11:51,800 --> 01:11:54,519
Speaker 1: oh five um in sort of the west all A

1289
01:11:54,680 --> 01:11:58,080
Speaker 1: region and so in the in the late eighteen hundreds

1290
01:11:58,080 --> 01:12:00,160
Speaker 1: early nineteen hundreds, the people who are living that the

1291
01:12:00,200 --> 01:12:03,280
Speaker 1: Sawtel veterans homes were mostly Civil War soldiers. And so

1292
01:12:03,360 --> 01:12:05,680
Speaker 1: we had people there who might have grown up in

1293
01:12:05,800 --> 01:12:08,880
Speaker 1: Kentucky or Tennessee or elsewhere in the Eastern US. And

1294
01:12:09,000 --> 01:12:12,320
Speaker 1: it's not totally clear whether they were pets or whether

1295
01:12:12,520 --> 01:12:14,280
Speaker 1: they were being raised for food, but they had a

1296
01:12:14,280 --> 01:12:17,640
Speaker 1: bunch of Eastern fox squirrels like in pins. And what

1297
01:12:17,680 --> 01:12:20,200
Speaker 1: they would do is they would take scraps from the

1298
01:12:20,600 --> 01:12:22,800
Speaker 1: commissaria or from the cafeteria there, and they would give

1299
01:12:22,840 --> 01:12:25,720
Speaker 1: the scraps to the squirrels. And eventually some you know,

1300
01:12:25,720 --> 01:12:29,000
Speaker 1: administrators said, hey, that's a waste of government funded you

1301
01:12:29,040 --> 01:12:31,479
Speaker 1: know food, and so you have to get rid of

1302
01:12:31,520 --> 01:12:34,120
Speaker 1: those squirrels. And so the story is that the squirrels

1303
01:12:34,160 --> 01:12:37,000
Speaker 1: were then released. But at that point you have, you know,

1304
01:12:37,280 --> 01:12:39,360
Speaker 1: l a sort of building up. You've got you know,

1305
01:12:39,439 --> 01:12:41,719
Speaker 1: telephone lines and power lines running all across the place,

1306
01:12:42,120 --> 01:12:45,080
Speaker 1: and so instead of having to run around down low

1307
01:12:45,240 --> 01:12:47,400
Speaker 1: where all these cars are, these squirrels are just running

1308
01:12:47,400 --> 01:12:51,840
Speaker 1: around on all these powers. So, yeah, exactly, and so

1309
01:12:52,120 --> 01:12:55,000
Speaker 1: um in fact, we actually you're asking about interesting naturalist observations.

1310
01:12:55,040 --> 01:12:56,920
Speaker 1: I just saw a photo two weeks ago of an

1311
01:12:56,920 --> 01:13:00,559
Speaker 1: Eastern fox squirrel that had been electrocuted, you know, and

1312
01:13:00,600 --> 01:13:02,439
Speaker 1: it's like, well, that's horrible, But it's also like an

1313
01:13:02,479 --> 01:13:05,439
Speaker 1: it's an interesting aspect of sort of urban nation. Like

1314
01:13:05,520 --> 01:13:10,400
Speaker 1: there are these unusual sort of aspects of the urban environment.

1315
01:13:10,600 --> 01:13:14,599
Speaker 1: The burning squirrel. If yeah, it smells good just for

1316
01:13:14,640 --> 01:13:16,280
Speaker 1: like the first few minutes, and then once it once

1317
01:13:16,320 --> 01:13:22,240
Speaker 1: it hits well done, smells good, it's too well done. Um,

1318
01:13:22,280 --> 01:13:24,599
Speaker 1: you gotta take it off distant time and so um,

1319
01:13:24,640 --> 01:13:26,280
Speaker 1: you know, they have this amazing story of how this

1320
01:13:26,360 --> 01:13:28,760
Speaker 1: is this non native squirrel that is now spread all

1321
01:13:28,800 --> 01:13:31,960
Speaker 1: across the landscape and it's totally doing well here because

1322
01:13:32,240 --> 01:13:34,360
Speaker 1: it just happens to do really well in urban places.

1323
01:13:34,400 --> 01:13:37,080
Speaker 1: It doesn't need a high density of trees. Are native

1324
01:13:37,080 --> 01:13:40,120
Speaker 1: Western gray squirrel needs high densities of trees. Just squirrel.

1325
01:13:40,160 --> 01:13:41,559
Speaker 1: It's like, yeah, I've got some you know, I've got

1326
01:13:41,560 --> 01:13:43,639
Speaker 1: some lawn, I've got occasional tree, I've got some cat

1327
01:13:43,680 --> 01:13:46,320
Speaker 1: food to eat, I've got some fruit. So they just

1328
01:13:46,360 --> 01:13:48,280
Speaker 1: do really well in urban places. So it's a species

1329
01:13:48,320 --> 01:13:52,240
Speaker 1: is doing incredibly well as an urban exploitter. That's amazing. Um,

1330
01:13:52,320 --> 01:13:54,640
Speaker 1: So do you have any calls to action that you

1331
01:13:54,680 --> 01:13:57,760
Speaker 1: can give people or anything else to plug? So I

1332
01:13:57,800 --> 01:14:00,160
Speaker 1: think I mean the biggest called action I would suggest

1333
01:14:00,160 --> 01:14:04,200
Speaker 1: to folks is, um, get involved in a citizen science project.

1334
01:14:04,479 --> 01:14:06,160
Speaker 1: How do you How would you do that? So? I

1335
01:14:06,160 --> 01:14:08,519
Speaker 1: think it's really easy. Um. Most people are already walking

1336
01:14:08,520 --> 01:14:11,720
Speaker 1: around with smartphones, and that smartphone for reasons that are

1337
01:14:11,760 --> 01:14:15,120
Speaker 1: not clear, mostly historical artifact, we still call it a phone. No,

1338
01:14:15,240 --> 01:14:17,800
Speaker 1: we use it for dozens of other things. You know

1339
01:14:17,880 --> 01:14:21,720
Speaker 1: that that smartphone has a GPS and camera. It's a

1340
01:14:21,720 --> 01:14:23,559
Speaker 1: lizard sex can You can take all sorts of great

1341
01:14:23,560 --> 01:14:26,479
Speaker 1: lizard sex shots and so yeah, people can just pull

1342
01:14:26,520 --> 01:14:29,840
Speaker 1: out their cameras and start taking photos. And the best

1343
01:14:29,880 --> 01:14:33,120
Speaker 1: thing to do is to download this app called I Naturalist. Um,

1344
01:14:33,160 --> 01:14:35,519
Speaker 1: there's a web platform for I naturalists and there's an app.

1345
01:14:35,560 --> 01:14:37,800
Speaker 1: You can download this app. You take the photos through

1346
01:14:37,840 --> 01:14:40,880
Speaker 1: the Naturalist app, it uploads them to our naturalists. You

1347
01:14:40,880 --> 01:14:43,960
Speaker 1: can see your photos online. You can participate in literally

1348
01:14:44,000 --> 01:14:47,320
Speaker 1: one of hundreds of projects on a naturalists on that platform.

1349
01:14:47,320 --> 01:14:50,479
Speaker 1: Here in southern California, I always promote our projects at

1350
01:14:50,479 --> 01:14:52,960
Speaker 1: the natural History Museum. So my my research is on

1351
01:14:53,320 --> 01:14:55,320
Speaker 1: is this project called rough Tiles and Amphibians, and Southern

1352
01:14:55,320 --> 01:14:58,920
Speaker 1: California we have another and the acronym for that as rascals,

1353
01:14:58,920 --> 01:15:02,200
Speaker 1: we haven't really like acronyms. UM. We have a snail

1354
01:15:02,240 --> 01:15:05,080
Speaker 1: and Slug project, which is snails and slugs living in

1355
01:15:05,120 --> 01:15:09,920
Speaker 1: metropolitan environments. That's called slime again because UM. And then

1356
01:15:09,960 --> 01:15:12,160
Speaker 1: we also have the Southern California Squirrel Survey, which which

1357
01:15:12,160 --> 01:15:14,120
Speaker 1: sadly we did not come up with a great acronym

1358
01:15:14,200 --> 01:15:16,760
Speaker 1: for UM. But those are all projects that people here

1359
01:15:16,760 --> 01:15:19,240
Speaker 1: in Southern California can participate in. But no matter where

1360
01:15:19,240 --> 01:15:22,040
Speaker 1: people are, there are there are observations up on our

1361
01:15:22,120 --> 01:15:25,719
Speaker 1: naturalists from every continent, you know, from all around the world.

1362
01:15:25,840 --> 01:15:28,200
Speaker 1: And so no matter where people are, they can start

1363
01:15:28,240 --> 01:15:31,040
Speaker 1: doing this and making observations that you know, researchers today

1364
01:15:31,080 --> 01:15:33,719
Speaker 1: and researchers into the future might might be then using

1365
01:15:33,960 --> 01:15:36,640
Speaker 1: that's great. So like like whenever people take photos of

1366
01:15:36,640 --> 01:15:38,240
Speaker 1: a squirrel and try to send it to all their

1367
01:15:38,280 --> 01:15:41,240
Speaker 1: friends and your friends not necessarily going to care, but

1368
01:15:41,360 --> 01:15:46,320
Speaker 1: I naturalist is that's exactly somebody actually does care about

1369
01:15:46,360 --> 01:15:48,439
Speaker 1: that squirrel photo. Yeah. Yeah, It's like I've found a

1370
01:15:48,479 --> 01:15:53,679
Speaker 1: really fat squirrel. Friends don't care, naturalists, scientists to the rescue. Well,

1371
01:15:53,720 --> 01:15:56,920
Speaker 1: thank you so much for sitting down and letting me

1372
01:15:56,960 --> 01:16:00,479
Speaker 1: grillly over these these reptile stories and aways happy to

1373
01:16:00,520 --> 01:16:05,640
Speaker 1: chat about citizen science. Um. You can find us on

1374
01:16:05,680 --> 01:16:08,880
Speaker 1: Twitter at Creature Feet Pod. That's not feat as in

1375
01:16:08,960 --> 01:16:12,040
Speaker 1: stinky beat, it's fat as in f E A T.

1376
01:16:12,840 --> 01:16:16,040
Speaker 1: And you can find me at Katie Golden. Golden is

1377
01:16:16,040 --> 01:16:18,280
Speaker 1: spelled wrong, by the way, It's g O L d

1378
01:16:18,560 --> 01:16:22,240
Speaker 1: I N. And you can also, you know, follow me

1379
01:16:22,600 --> 01:16:26,000
Speaker 1: on my bird Twitter at pro bird Writes, where I'm

1380
01:16:26,040 --> 01:16:30,160
Speaker 1: a bird and you know that's what I am on Twitter,

1381
01:16:30,600 --> 01:16:34,120
Speaker 1: little bird. And thanks to the Space Colssics for their

1382
01:16:34,200 --> 01:16:38,120
Speaker 1: awesome song ex Alumina