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Speaker 1: Hello the Internet, and welcome to season three oh nine,

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Speaker 1: Episode two of Dally's Guys production of iHeartRadio. This is

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Speaker 1: a podcast where we take a deep dive into America's

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Speaker 1: shared consciousness. And it's Tuesday, October seventeenth, twenty twenty three.

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Speaker 1: I don't know, Come on, Jack, guess guess one of them? Yeah,

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Speaker 1: I guess. Yes.

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Speaker 2: One is something that's like where two full weeks out

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Speaker 2: from Halloween.

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Speaker 1: Yeah, but there's one. There's one. There's one food.

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Speaker 2: That gets a day to day that is just like

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Speaker 2: a It's just like a food that everyone eats.

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Speaker 1: It's a food and it was stolen.

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Speaker 2: In by the Italians from pasta. Yes, okay, National Pasta Day,

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Speaker 2: National Mulligan Day, let's see. Oh no, pro life Day

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Speaker 2: of Silence are no, sir, I'm going to do that one.

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Speaker 2: But we will do this Black Poetry Day, National Pharmacy

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Speaker 2: Technician Day, shout out to the homie at the pharmacy

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Speaker 2: that cooks up their homebrew WAYGOVI for the people in

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Speaker 2: the community.

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Speaker 1: Uh.

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Speaker 2: And also National Edge Day, which I believe is for

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Speaker 2: the straight edge.

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Speaker 1: People out there, okay, for people who are edging sexually? No, no, no,

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Speaker 1: this is frustrated. Although you guys can always do your thing.

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Speaker 1: You know we're not getting you don't need a day

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Speaker 1: to do to do whatever you need to do. I

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Speaker 1: feel good whatever it is you do. Anyways, my name

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Speaker 1: is Jack O'Brien aka he got legs that it seems

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Speaker 1: to me reminds me of childhood memories. Lyon my mom,

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Speaker 1: that's my piss. It's Italian ice. Wow, sweet Jack O'Brian.

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Speaker 1: That is courtesy of Laccaroni on the discord. How did

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Speaker 1: you find out? Are you talking to my mom about melted? Yeah?

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Speaker 1: I went on that roller coaster and came off and

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Speaker 1: it's just water's almost water ice call over my dang it. Anyways,

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Speaker 1: I'm throwed to be joined as always by my co host,

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Speaker 1: mister Miles Gray.

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Speaker 2: Miles Gray aka you gotta van mow me.

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Speaker 1: You gotta van mow me when eggs ain't that cheap?

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Speaker 3: Just remember that I got you Next week twenty bones

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Speaker 3: would be sweet because you gotta I thought I knew

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Speaker 3: the militia, but it's just enough to get you started.

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Speaker 1: That you gotta van moon me doom.

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Speaker 2: Shout out to Randa Dixon Art because yeah, eggs are pretty.

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Speaker 1: They're kind of going up and down.

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Speaker 2: Gas though, Yeah, shout out to Shout out to plug

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Speaker 2: in hybrid vehicles.

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Speaker 1: Yeah, save you that sweet sweet dough. Shout out to

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Speaker 1: Randy Newman for being able to stay on It's meat Live.

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Speaker 1: You know.

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Speaker 2: That's one where I'm like, it could be a mulligan, Yeah,

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Speaker 2: or it could go not a mulligan, but it could

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Speaker 2: be a push.

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Speaker 1: It could go either way with me, truly could. He's alive,

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Speaker 1: great alive on seventy nine. Good shout out to him.

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Speaker 1: I did not like when Susanne Summers passed r P.

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Speaker 1: I was like, oh, oh damn, I thought never mind. Okay, Miles.

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Speaker 1: We are thrilled to be joined by an acclaimed wildlife

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Speaker 1: ecologist and conservationist who specializes in researching how human activity

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Speaker 1: influences the behavior of wild animals. She's a TV host

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Speaker 1: and the host of the PBS Nature podcast Going Wild

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Speaker 1: with Doctor ray Wing Grant, which makes sense because she

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Speaker 1: is doctor ray Win Grant.

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Speaker 4: I'm here here, welcome back.

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Speaker 1: Oh.

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Speaker 4: I really love having so many memories, you know.

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Speaker 1: Yeah.

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Speaker 2: Yeah, we loved having you last time, and we're like,

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Speaker 2: now that we're talking to experts, let's talk to it

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Speaker 2: let's really digging to a real expert.

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Speaker 1: Yeah, I spent some time doing some research and like

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Speaker 1: just you know, really square up make ourselves seem extremely smart.

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Speaker 1: And that's what we're doing. We put put our brains

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Speaker 1: together and have put together a list of some of

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Speaker 1: the hardest hitting science based, deeply researched, science based questions

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Speaker 1: in your area of expertise.

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Speaker 4: This is like my all over again.

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Speaker 1: Yeah, yeah it is, and this is on and it's

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Speaker 1: going to be on the.

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Speaker 4: Record, right right.

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Speaker 5: Stakes are highs, incredibly high.

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Speaker 1: So we're going to get to that in a moment.

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Speaker 1: But before we do, we still like to ask our guests,

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Speaker 1: what is something from your search history that's revealing about

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Speaker 1: who you are or what you're up to.

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Speaker 4: Oh, well, I have something. I hope this can kind

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Speaker 4: of be the great equalizer. Perhaps because I'm a scientist, right,

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Speaker 4: I'm an environmental scientist, a wildlife ecologist. I have all

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Speaker 4: this expertise, and yet ever so often I have to

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Speaker 4: google like the simpler things just to make sure that

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Speaker 4: I'm explaining it correctly. So two weeks ago, I was

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Speaker 4: with a film crew and filming a television show. It's

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Speaker 4: called Wild Kingdom. It's great. You can watch it. It's

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Speaker 4: on NBC streaming on Peacock. And I was with the

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Speaker 4: crew and we were in a place I meant, gotta

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Speaker 4: gotta sneak it in. We were in Texas, or in

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Speaker 4: Central Texas, in a place that has dinosaur footprints, right,

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Speaker 4: Like this part of Central Texas used to be an

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Speaker 4: ocean and then at the point that there were these dinosaurs,

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Speaker 4: it was like more of a swamp and they sunk

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Speaker 4: their giant feet into the mud and then it just

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Speaker 4: like there was a drought and they just solidified and

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Speaker 4: they're still there. It's amazing. So I'm talking to the

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Speaker 4: crew about dinosaurs. This is just like rural central Texas too.

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Speaker 4: And somehow we got into the topic of fossil fuels,

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Speaker 4: and one of the producers on the show didn't know

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Speaker 4: where fossil fuels came from, Like she didn't understand the

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Speaker 4: word fossil that's part of fossil frut. So fossil fuels

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Speaker 4: are like you know, the gas you put in your

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Speaker 4: car is a type of fossil fuel, right right, It's

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Speaker 4: what's contributing to climate change. And so I was explained

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Speaker 4: to her, like, girl, yeah, it's when dinosaurs lived and

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Speaker 4: then they died, their bodies decomposed and sunk into the earth.

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Speaker 4: But because it's been millions of years, those decomposed dinosaur

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Speaker 4: bodies have liquefied because it's so hot down there and

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Speaker 4: turned into essentially like oil that we drill up and

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Speaker 4: used to put in our cars and used to you know,

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Speaker 4: power stuff, and we've you know, contaminated the whole atmosphere

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Speaker 4: because of it. And her mind was blown to the

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Speaker 4: point that I started getting like a little bit concerned.

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Speaker 4: I was like, that is that right?

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Speaker 2: So that what we would sometimes call fossils, those slowly,

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Speaker 2: over a course of long decomposition became fuel.

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Speaker 4: So just say I was right. I mean I had

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Speaker 4: to google it because I was like, I mean, I

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Speaker 4: study living animals, not dead runs. But I mean, but

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Speaker 4: that is accurate, right, So fossil fuels like scientists throw

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Speaker 4: that turn around, politicians thrown around, but it's literally fossils.

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Speaker 4: We have them because it's decomposed dinosaurs from under the earth.

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Speaker 4: So like the gas you put in your car is

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Speaker 4: dinosaur body gas, right that we drive and it combusts

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Speaker 4: and you know, makes a dinosaur.

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Speaker 1: It's not It's not like plant body or something.

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Speaker 4: It's not plants. It's like decomposed animal matter. So it's

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Speaker 4: like dinosaurs. It's like all those old crustaceans. And I

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Speaker 4: mean it's it's a bunch of stuff that used to live.

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Speaker 4: One day humans will be that same liquefied substance and

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Speaker 4: people could use.

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Speaker 1: Us al Wikipedia, Why does Wikipedia says, are they?

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Speaker 4: I think it's like they might be or I might

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Speaker 4: be wrong, but I believe it's like if it's plants,

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Speaker 4: it's from those like ancient oceans, right.

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Speaker 1: That like like not like not like you know, the

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Speaker 1: grad Yeah.

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Speaker 4: It's all prehistoric from before there were people to take

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Speaker 4: down the data of like how it all started and

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Speaker 4: what decomposed. It's just like organic matter, but it's a

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Speaker 4: lot of it is like really big animals like dinosaurs

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Speaker 4: using their bodies.

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Speaker 1: I have to apologize to the listeners. I've been calling

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Speaker 1: fossil fuels dinosaur farts that were just cooking dinosaur farts

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Speaker 1: for our guess, so I'm looking them. I always said,

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Speaker 1: I said, yeah, what is that cooking farts? Yeah, yeah,

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Speaker 1: we're cooking them to get our cars started. But yes,

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Speaker 1: it's the bodies, not the fart.

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Speaker 4: I mean I feel like that's like click baity enough.

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Speaker 4: Like a lot of people, you know, you just hear

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Speaker 4: this word over and over and you're just like, I

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Speaker 4: get I guess that just means like dirty gases that

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Speaker 4: go into the atmosphere. But it's like, really, I mean,

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Speaker 4: it was interesting to make the connection while looking at

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Speaker 4: a dinosaur footprint and like marveling at it to be like, oh,

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Speaker 4: I interacted dinosaurs all the time.

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Speaker 1: Right, And you're also likely you will have your come

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Speaker 1: up in dinosaurs. You will help destroy.

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Speaker 4: Our they remain relevant.

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Speaker 1: Dinosaur fart to dinosaur fart, as the Bible says, Yeah,

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Speaker 1: my my, how I would have searched that. What you

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Speaker 1: were just talking about is how dinosaurs footprints Texas? Because

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Speaker 1: I only talked to Google in the dumbest phrases.

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Speaker 4: But we were in Glen Rose, Texas. If you ever

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Speaker 4: go there, you'll be astonished because there are legit huge

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Speaker 4: dinosaur footprints, like and it's just there's just out in

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Speaker 4: the in the community. It's just it's this rural, rural

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Speaker 4: part of central Texas that is like you know kind.

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Speaker 2: Of oh, do they have like like dinosaur statues there too?

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Speaker 4: They have the other big statues like off the highway

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Speaker 4: kind of statues. But it is the country like it

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Speaker 4: is like it is not urban, it is a wild place,

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Speaker 4: but it's just very accessible. So let me just say,

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Speaker 4: dinosaur footprints are super accessibly, just like I got a

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Speaker 4: walk upon them.

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Speaker 1: Really, I'm looking at a picture from the Smithsonian magazine

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Speaker 1: and it has the dinosaur footprints. And then to make

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Speaker 1: sure you know that it's Texas, somebody just dropped a

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Speaker 1: cowboy hat on top of them. For scale. Yeah yeah,

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Speaker 1: scale scale, Yeah, how many cowboy hats tall? Are you? Jack?

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Speaker 1: If we're doing the Texas measurement? That's right? Uh? What

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Speaker 1: is something you think is overrated?

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Speaker 4: Oh? So this is an unpopular opinion I think, maybe

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Speaker 4: not in this group, but overrated, especially right now, like

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Speaker 4: all the pumpkin flavorings that we see going on. I think, Okay,

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Speaker 4: I know this. When I was a kid, I ate

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Speaker 4: an entire pumpkin pie one Thanksgiving and I barfed everywhere.

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Speaker 4: And now I can't even think about a pumpkin flavor

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Speaker 4: without like getting nauseous. So I can't. I can't handle it.

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Speaker 4: So all the you know, like no offfense install the

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Speaker 4: pumpkins don't worry about it. And I love me some

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Speaker 4: you know, apple cider or whatnot, but I just can't

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Speaker 4: do the pumpkin flavor. I can't. I can't. I can't overrated.

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Speaker 1: That's wild. How like one bad experience can totally mess

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Speaker 1: you up.

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Speaker 4: Like some folks have that with candy corn, right, Like,

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Speaker 4: eat too much candy corn, you can never eat it again.

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Speaker 2: I didn't even eat too much. I just had one

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Speaker 2: and I was like, this is disgusting and a joke, like.

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Speaker 4: No need to eat wax.

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Speaker 1: Yeah, the hatefulness, the anti candy corn. And I personally

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Speaker 1: like candy corn and the little freeds because I like

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Speaker 1: as much sugar. I like a sugar de treat and

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Speaker 1: that that's just giving you pure sugar, like sometimes you

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Speaker 1: bite into it and it just like dissolves into a

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Speaker 1: pile of sugar in your mouth. But the hatefulness with

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Speaker 1: which the candy corn people describe divisive.

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Speaker 2: Yeah, I just have a very strong opinion about what

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Speaker 2: I want for Halloween, and I'm only looking at through

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Speaker 2: that prism and I'm like, well, I hate this, so

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Speaker 2: your back, you know, give me chocolate.

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Speaker 4: It's like the people who hand out fruit or something.

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Speaker 4: You're like just don't open the door like mad.

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Speaker 1: You just fight me instead. Yeah, if you're gonna do that,

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Speaker 1: oh a fucking apple. Okay, why just why don't just

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Speaker 1: smack my mother? That's with me, and then we can

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Speaker 1: just get we can just get there a lot sooner, sir. No,

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Speaker 1: I do loose handfuls of loose candy corn in the

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Speaker 1: kids bags every year. That's just yeah, just scattered and

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Speaker 1: sweaty with your sweaty palms and all some stick. My

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Speaker 1: hands are bright yellow and orange by the time, by

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Speaker 1: the after by the evening. No that, yeah, I never

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Speaker 1: got candy corn in like that was not a problem

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Speaker 1: for me, like that people were giving out a significant

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Speaker 1: amount of candy corn. I always associate candy corn with,

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Speaker 1: you know, just being places where candy wouldn't normally be. Yeah,

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Speaker 1: I don't think it's an appropriate replacement for like Reese's

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Speaker 1: peanut butter cups prinstance.

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Speaker 2: No, candy candy corn is the oh I hit the

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Speaker 2: CVS right before I came to your birthday.

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Speaker 1: Yeah, candy like it has that energy, like it's like.

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Speaker 4: At the like like at the secretary's desk right like

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Speaker 4: like in the main office at school.

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Speaker 1: Like, Yeah, I think My family just got like a

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Speaker 1: bunch of candy corn and pumpkins one year, and I

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Speaker 1: was just feasting on them and just have the pumpkins

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Speaker 1: in particular.

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Speaker 4: They're filling. They're actually they're filling.

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Speaker 1: It is like the most sugar that you can get

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Speaker 1: in like a single piece of.

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Speaker 4: Can wax, Like I keep saying, I'm like, it is

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Speaker 4: made of wax.

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Speaker 1: I think, is it?

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Speaker 5: I think it's like a dinosaur. IX. Tell your kids, Jack,

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Speaker 5: tell your kids. Yeah, that's like the thing.

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Speaker 2: I mean, yeah, the whenever you have a bad experience

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Speaker 2: and then you end up, you know, having to vomit after,

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Speaker 2: it does put you off. Like and I'm not trying

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Speaker 2: to cast dispersions, but one time I had like a

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Speaker 2: somebody from Firehouse Subs.

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Speaker 1: I can't even fire House Subs anymore, and now we

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Speaker 1: can't have them as a sponsor. Sorry.

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Speaker 2: Here's another one, Jack, I'm about to completely fuck us

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Speaker 2: over with ninety nine bananas. I drank a whole bottle

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Speaker 2: in ninety nine bananas, brain liqueur and vomited. Ever, I

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Speaker 2: can't even eat bananas anymore, Oh my god.

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Speaker 4: But a bottle though, yeah.

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Speaker 2: Yeah, somebody some people said there was a mistake starting

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Speaker 2: with ninety nine bananas.

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Speaker 4: But I had to just the quantity also.

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Speaker 1: And I misunderstood what you were describing when you said

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Speaker 1: you ate ninety nine bananas, that it made you sick.

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Speaker 1: And I tried it myself and just ate ninety nine

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Speaker 1: bana and it made me very sad. Yeah, not sick

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Speaker 1: enough to not love bananas. I love them always and forever.

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Speaker 1: Good for you, doctor Grant. What is something you think

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Speaker 1: is underrated?

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Speaker 4: Okay? This is like, this is a little eye rolly,

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Speaker 4: but this morning. Okay. So I have a girlfriend who

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Speaker 4: has four kids. Shout out to Dana if she's listening

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Speaker 4: to us, Wow, And she knows how to run a

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Speaker 4: house like she is. She's also an attorney, Like she's

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Speaker 4: so skilled, but she knows how to run a house.

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Speaker 4: And I have two kids and I am constantly like,

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Speaker 4: feel like I'm a hot mess. So I reached out

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Speaker 4: to my friend and I was like, how do I

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Speaker 4: not like lose control by the beginning of the day

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Speaker 4: every day? And she's like, you have to wake up

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Speaker 4: at five am, Like you have to. That's the only

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Speaker 4: way you If you wake up at five am, you'll

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Speaker 4: have enough time for yourself imagine that, like you can

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Speaker 4: take a shower and get dressed and be a person.

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Speaker 4: You can like get a head start on the day.

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Speaker 4: You can finish up any work you didn't finish the

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Speaker 4: night before, and then you can be ready for the

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Speaker 4: kid chaos, and then you can jump into your work day.

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Speaker 4: And I was like girl five though like that, like

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Speaker 4: like we're old now. I don't know if I could

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Speaker 4: do that anyway. So I've been putting this off. I've

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Speaker 4: been procrastinating for weeks and this morning I set my alarm,

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Speaker 4: I woke up at five. I only hit this news

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Speaker 4: button one time. Yeah, and I got up. And So

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Speaker 4: what I'm saying is underrated is sunrise? Right, like walking

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Speaker 4: the sunrise. I'm kind of like this is underrated. This

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Speaker 4: is so peaceful, you know, like I'm like real groggy

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Speaker 4: and not real happy. But as soon as like I

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Speaker 4: get to experience sunrise and don and I like, wow,

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Speaker 4: what a gift, what a blessing? You know. So I'm

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Speaker 4: a new person. We'll see what happens tomorrow. But essentially,

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Speaker 4: I did that once, and I did it once, and

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Speaker 4: I'm here on your show to say, yeah, I.

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Speaker 1: Did sunrise once. Yeah that sounds nice. Yeah, it's just

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Speaker 1: I will get on a kick of like I gotta

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Speaker 1: wake up before these kids because otherwise, like they're just

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Speaker 1: all over me. And I also have this thing I

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Speaker 1: tell myself that they like have a sixth sense that

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Speaker 1: when I'm awake, they will also wake up right right.

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Speaker 1: That is a that is a rough couple hours to

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Speaker 1: spend with a wide awake five year old. And what's

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Speaker 1: going on? What's going on when you're doing out here? Dad?

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Speaker 1: What's going exactly? Just sitting there? Well, I'm trying to

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Speaker 1: catch up on emails and I'm mad because the sun's

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Speaker 1: not up. But yeah, it's it's just so it's so hard.

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Speaker 1: Little kids are so hard.

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Speaker 4: Little kids are so hard because I mean, but there's

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Speaker 4: something so stressful about like the moment you open your eyes,

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Speaker 4: you have to be actively parenting. And so this is

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Speaker 4: like getting ahead of that. I'm like, even if I

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Speaker 4: have ten minutes before, I'm like actively parenting. Like, my

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Speaker 4: little list is three and she is a complete maniac. Like, yes,

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Speaker 4: she's the wildest kid. I never thought I'd have a

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Speaker 4: kid so wilder than.

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Speaker 1: Some of the beasts, wilder than the beasts.

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Speaker 4: Okay, do you that? Yeah? Before like, how do you like,

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Speaker 4: you know, are you ever afraid? I'm like, I can't

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Speaker 4: wait to get into the wilderness.

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Speaker 2: I would rather face a den of bears, oh my god,

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Speaker 2: and I'm holding one of their cubs.

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Speaker 1: Yeah, at least I know what to do. I've just

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Speaker 1: come around to the idea of like, okay, so I

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Speaker 1: am going to be more tired at the end of

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Speaker 1: the weekend than at the end of the word. Yeah,

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Speaker 1: and that's okay, That's how it was meant to be

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Speaker 1: for for a time.

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Speaker 4: There's no t g I f that's not no.

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Speaker 1: And I think it took me a while, Like I

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Speaker 1: was like, why are my week Why am I not

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Speaker 1: like loving these weekends? And it's like and I do

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Speaker 1: in spots, but I am very tired. I'm so exhausted. Yeah,

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Speaker 1: so sweet. Have you tried the Vietnamese coffee yet? This

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Speaker 1: is not going to help me in the long run.

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Speaker 1: I wired.

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Speaker 2: I've been waiting to hear your report of how you

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Speaker 2: had to chain yourself to a radiator in the basement

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Speaker 2: because the caffeine is just hitting too hard.

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Speaker 1: From the view. Should do it on the Halloween night?

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Speaker 4: You can like sip it over the course of the day.

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Speaker 2: You.

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Speaker 4: I mean that is a good point, Like with one

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Speaker 4: of those the Vietnamese coffee with the condensed mell sweet and.

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Speaker 1: Drink sip it.

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Speaker 4: You sip it over the whole day. Yeah, like a

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Speaker 4: sustained fake Wow.

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Speaker 2: Okay, I do it in one go and then have

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Speaker 2: an existential crisis for the next eight hours.

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Speaker 1: So sweat through your chair and then god like it's

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Speaker 1: a damp in here. Oh my sweat. Yeah, amazing. All right,

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Speaker 1: Well we're going to take a quick break and when

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Speaker 1: we come back, we're going to get into the hard

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Speaker 1: hitting science. Yeah, and so we'll be right back. And

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Speaker 1: we're back. We are, And so we want to take

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Speaker 1: this opportunity to check in with you, doctor Grenn, about

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Speaker 1: how you, as a scientist, perceive some of the news

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Speaker 1: that we cover on a regular basis, and that is

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Speaker 1: entering the zeitgeist on a regular basis. As the sign

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Speaker 1: in my front yard will attest in this house, we

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Speaker 1: believe in science. Okay, no, but we we do believe.

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Speaker 1: We don't think COVID was caused by five gen Okay,

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Speaker 1: speak for yourself, speak for yourself. We don't think vaccines

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Speaker 1: killed every celebrity who has died since twenty nineteen, since

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Speaker 1: before the pandemic.

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Speaker 4: Yeah for the pandemic.

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Speaker 1: Yeah, okay, that's good. That's good, but good solid take.

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Speaker 1: So I guess you'll be shocked to know Miles is

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Speaker 1: not a scientist. But I am also not a scientist.

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Speaker 1: How do you think about communicating as a scientist to

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Speaker 1: non scientists? Like how strategic are you when communicating with

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Speaker 1: with those of us who may not I'm not going

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Speaker 1: to confirm that I don't have a PhD in the science.

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Speaker 2: Well, look, I think getting I'm on Reddit are slash science,

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Speaker 2: so I think I have a good.

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Speaker 1: Grasp on things.

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Speaker 2: But yes, how how would you in a world of

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Speaker 2: contentious information? What's what's it like?

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Speaker 1: What do you do? How do you know? You know?

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Speaker 4: I gotta say I got to say that I work

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Speaker 4: really hard at it and I am also gifted with

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Speaker 4: a type of science that I do that is highly

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Speaker 4: vis right, Like there are like chemists out there, people

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Speaker 4: who study like micro organisms, that it's harder for them

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Speaker 4: to show the science as they're doing it right or

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Speaker 4: might not aways interesting to look at. But I study

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Speaker 4: large animals. I study large carnivores, bears and lions and

400
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Speaker 4: mountain lions and wolves and the science behind setting them

401
00:21:20,680 --> 00:21:24,480
Speaker 4: might be very technical or like you know, very mathy

402
00:21:25,000 --> 00:21:28,760
Speaker 4: or very analytical, but kind of the basics of it

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Speaker 4: are fun to look at and highly engaging. So I

404
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Speaker 4: just I get that benefit just automatically that like people

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Speaker 4: might tune in if I show like a hibernating bear,

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Speaker 4: there's a huge science behind that. But the visual also

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Speaker 4: speaks volumes, so there's that. And then I also want

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Speaker 4: to just shout out how identity plays a huge role

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Speaker 4: into how I approach science communication. And I even think

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Speaker 4: how I got into it because as a you know,

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Speaker 4: almost at a young black woman, but I should create

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Speaker 4: that as a as a millennial.

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Speaker 1: No, no, we're young, we're were you?

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Speaker 4: That used to mean young? As a millennial black woman,

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Speaker 4: I always was a part of my community, right, Like

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Speaker 4: my professional community was always so different from my personal,

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Speaker 4: my my you know, social community. And because of that,

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Speaker 4: I was always telling stories about what I was doing

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Speaker 4: to my community, which is predominantly Black women my own age,

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Speaker 4: right or maybe their brothers and their husbands or their

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Speaker 4: boyfriends or you know, my family. And so because there

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Speaker 4: was such a disconnect between like ecologists and the people

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Speaker 4: I spend my free time with without really trying, without

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Speaker 4: being purposeful, I would talk a lot about what I

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Speaker 4: do or where I had been, or why I was

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Speaker 4: going these places, or the cool stuff that I found.

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Speaker 4: And so I found that just naturally, storytelling or just

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Speaker 4: science communication became a thing. And then of course I

429
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Speaker 4: was also like growing up, I was such a nerd.

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Speaker 4: So imagine me in college. I went to college in Atlanta,

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Speaker 4: and there's this wonderful black community, and I was the

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Speaker 4: girl who was like obsessed with recycling, right, like environmental health,

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Speaker 4: like picking up litter. I was the recycling coordinator from

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Speaker 4: my dorm, right, And so I was also that person

435
00:23:18,000 --> 00:23:21,560
Speaker 4: no matter what my identity was that was like knocking

436
00:23:21,600 --> 00:23:24,800
Speaker 4: on people's dorm rooms and being like it's recycling day,

437
00:23:24,920 --> 00:23:27,600
Speaker 4: Like bring me out of your bottles of ninety nine

438
00:23:27,600 --> 00:23:28,719
Speaker 4: bananas or whatever.

439
00:23:29,040 --> 00:23:32,080
Speaker 1: No, I'm collecting them. I put them up on a

440
00:23:32,160 --> 00:23:34,880
Speaker 1: pyramid out of them next to my gray Goose bottles,

441
00:23:36,040 --> 00:23:39,120
Speaker 1: so they know I at one point could afford great.

442
00:23:39,000 --> 00:23:43,800
Speaker 4: I have class. So so I think that in so

443
00:23:43,960 --> 00:23:47,560
Speaker 4: many of the ways that I've been involved in science,

444
00:23:47,680 --> 00:23:50,320
Speaker 4: there's been also a practice to it that you can see, right,

445
00:23:50,400 --> 00:23:53,439
Speaker 4: you can see someone collecting recycling, right, But there's like

446
00:23:53,480 --> 00:23:57,240
Speaker 4: a science behind why that's important and how it works.

447
00:23:57,280 --> 00:24:00,000
Speaker 4: And you can see someone like hiking in the wildernes

448
00:24:00,200 --> 00:24:03,800
Speaker 4: looking for a bear, and there's a science behind that. So,

449
00:24:04,640 --> 00:24:06,520
Speaker 4: you know, I think that I might have been super

450
00:24:06,600 --> 00:24:09,520
Speaker 4: challenged in other ways, but I've just had this amazing

451
00:24:09,560 --> 00:24:11,480
Speaker 4: benefit of what I do or what I care about,

452
00:24:11,480 --> 00:24:15,200
Speaker 4: and how visual it is and how a person can

453
00:24:15,240 --> 00:24:18,959
Speaker 4: kind of symbolize a lot of that, and so I

454
00:24:19,000 --> 00:24:21,439
Speaker 4: haven't struggled too much. You know, I get like I

455
00:24:21,440 --> 00:24:24,520
Speaker 4: do get the like comments on Facebook I got. I

456
00:24:24,560 --> 00:24:27,280
Speaker 4: recently got an email through my website about someone like

457
00:24:27,880 --> 00:24:31,920
Speaker 4: kind of threatening me to tell a story the right way, right.

458
00:24:32,000 --> 00:24:35,280
Speaker 4: It was really interesting. There's a bird called the Atwater

459
00:24:35,400 --> 00:24:38,960
Speaker 4: prairie chicken in central Texas. It's a highly endangered bird

460
00:24:39,200 --> 00:24:41,919
Speaker 4: that has this terrible name because the word chicken is

461
00:24:41,920 --> 00:24:44,840
Speaker 4: in it. But it's actually one of these like remarkable

462
00:24:44,880 --> 00:24:47,080
Speaker 4: birds in the sage grouse family. So it has these

463
00:24:47,119 --> 00:24:50,719
Speaker 4: like yellow cheeks that puff up really big, and they

464
00:24:50,760 --> 00:24:53,120
Speaker 4: do like one of those mating dances that you'd see

465
00:24:53,119 --> 00:24:55,520
Speaker 4: in all the natural history shows. It's like an incredible bird.

466
00:24:56,160 --> 00:24:58,239
Speaker 4: And this guy sent an email and he was like

467
00:24:58,600 --> 00:25:01,439
Speaker 4: you better like if your shit h does a story

468
00:25:01,440 --> 00:25:03,600
Speaker 4: on the atwater prairie chick, and you better do it

469
00:25:03,680 --> 00:25:06,200
Speaker 4: right because so many other people have done it wrong.

470
00:25:06,280 --> 00:25:07,679
Speaker 4: You know, that's what those things are. I was like,

471
00:25:07,920 --> 00:25:10,639
Speaker 4: you don't even know what we're doing, you know, you know,

472
00:25:10,720 --> 00:25:12,879
Speaker 4: like like there's no context here. But he was like

473
00:25:12,960 --> 00:25:16,679
Speaker 4: threatening me, like little old me about this prairie chicken,

474
00:25:17,240 --> 00:25:19,560
Speaker 4: you know. And so it's just very interesting that I

475
00:25:19,600 --> 00:25:23,359
Speaker 4: do get people who don't like my communication, you know.

476
00:25:23,440 --> 00:25:27,080
Speaker 4: I do get people who find problems in it, usually

477
00:25:27,320 --> 00:25:29,840
Speaker 4: for no good reason, sure, but I don't get a

478
00:25:29,840 --> 00:25:33,440
Speaker 4: lot of deniers when it comes to what I'm communicating.

479
00:25:33,640 --> 00:25:35,840
Speaker 4: And and that is special.

480
00:25:36,800 --> 00:25:39,800
Speaker 2: To continue down this because I think this is it's

481
00:25:39,840 --> 00:25:42,440
Speaker 2: relevant right because we're it's such an era to where

482
00:25:42,440 --> 00:25:44,600
Speaker 2: it's people like I got to see it to believe it.

483
00:25:44,720 --> 00:25:46,879
Speaker 2: For a lot of scientific stuff, like they're like I

484
00:25:46,880 --> 00:25:50,000
Speaker 2: don't know how a vaccine works, and like and I

485
00:25:50,000 --> 00:25:52,920
Speaker 2: remember like the like like was it the CDC's like

486
00:25:52,960 --> 00:25:56,440
Speaker 2: here's a fucking video, man, Yeah, I'm not gonna watch that.

487
00:25:56,440 --> 00:25:59,840
Speaker 2: It's fucking nonsense. But like for things that are measurable, right,

488
00:26:00,040 --> 00:26:02,480
Speaker 2: and like for people like if seeing is believing a

489
00:26:02,480 --> 00:26:06,000
Speaker 2: lot of times, how I guess in that sense, how

490
00:26:06,040 --> 00:26:08,880
Speaker 2: are you seeing climate change? Because this is another thing

491
00:26:08,960 --> 00:26:14,000
Speaker 2: that people are like it's cold today, therefore, like fine,

492
00:26:14,080 --> 00:26:17,320
Speaker 2: shut up, but how are you seeing that sort of

493
00:26:17,480 --> 00:26:21,040
Speaker 2: manifest in the physical world that of like these environments

494
00:26:21,040 --> 00:26:23,320
Speaker 2: of the species that you study, because that's one thing,

495
00:26:23,760 --> 00:26:27,479
Speaker 2: like obviously you're not like an atmospheric scientist, but you

496
00:26:27,640 --> 00:26:31,960
Speaker 2: very much do understand how climate is impacting animals. So

497
00:26:32,000 --> 00:26:35,000
Speaker 2: in that sense, how are you seeing this play out

498
00:26:35,119 --> 00:26:37,199
Speaker 2: like at that scale, because I'm sure that's indicative to

499
00:26:37,400 --> 00:26:40,040
Speaker 2: like the sort of chain reaction that could happen with

500
00:26:40,080 --> 00:26:42,000
Speaker 2: our environmental systems.

501
00:26:42,400 --> 00:26:44,560
Speaker 4: Right. And you know, it's really interesting that you bring

502
00:26:44,600 --> 00:26:46,479
Speaker 4: that up because I kind of want to put this

503
00:26:46,480 --> 00:26:52,280
Speaker 4: disclaimer out that climate change impacts wild animals tremendously in

504
00:26:52,320 --> 00:26:56,159
Speaker 4: a way that's not okay, But I think that we

505
00:26:56,280 --> 00:27:02,160
Speaker 4: need to solve the issues of climate change to help people. First.

506
00:27:02,400 --> 00:27:03,760
Speaker 4: You know, there's a lot of people who like kind

507
00:27:03,760 --> 00:27:05,879
Speaker 4: of care more about animals than people, or they might

508
00:27:05,920 --> 00:27:09,359
Speaker 4: be more convinced to care if there's an animal story

509
00:27:09,480 --> 00:27:13,520
Speaker 4: rather than like, oh, people in this developing nation are

510
00:27:13,600 --> 00:27:15,240
Speaker 4: suffering kind of story.

511
00:27:15,280 --> 00:27:17,960
Speaker 1: But to see how they're how emaciated their dogs are.

512
00:27:18,400 --> 00:27:22,000
Speaker 4: Exactly, no, exactly exactly. So I always want to point out,

513
00:27:22,040 --> 00:27:24,840
Speaker 4: like I like I live and breathe wild animals every day.

514
00:27:24,880 --> 00:27:26,800
Speaker 4: I've dedicated my life to saving them and keeping them

515
00:27:26,840 --> 00:27:29,159
Speaker 4: on this planet. And I think people are more important

516
00:27:29,840 --> 00:27:33,560
Speaker 4: and more urgently need saving, right because climate change is

517
00:27:33,760 --> 00:27:39,400
Speaker 4: devastating entire communities of people right now. With that said, bears, right,

518
00:27:39,440 --> 00:27:41,640
Speaker 4: bears are a perfect example of in studying bears for

519
00:27:41,680 --> 00:27:46,760
Speaker 4: thirteen years and we're seeing how climate change is impacting

520
00:27:46,880 --> 00:27:49,240
Speaker 4: all different kinds of bears. So one of the things

521
00:27:49,280 --> 00:27:52,119
Speaker 4: that we love about bears, as like Americans, is that

522
00:27:52,160 --> 00:27:55,320
Speaker 4: they hibernate in the winter. It gets cold, and they

523
00:27:55,359 --> 00:27:58,080
Speaker 4: go into their den and they hibernate and they sleep

524
00:27:58,200 --> 00:28:01,960
Speaker 4: for you know, two, four or six months at a time. Well,

525
00:28:01,960 --> 00:28:07,000
Speaker 4: they actually need all kinds of environmental cues to enter hibernation, right.

526
00:28:07,080 --> 00:28:09,639
Speaker 4: So it's not like they just like look at a

527
00:28:09,640 --> 00:28:13,240
Speaker 4: calendar and say like, oh my gosh, it's November fifteenth,

528
00:28:13,359 --> 00:28:18,000
Speaker 4: like yeah, time to go, right, It's like their ecosystem

529
00:28:18,080 --> 00:28:22,280
Speaker 4: has to signal to them winter is coming, the temperature drops,

530
00:28:22,359 --> 00:28:26,400
Speaker 4: maybe precipitation, increases, maybe because some snow right the trees

531
00:28:26,440 --> 00:28:30,520
Speaker 4: stop producing food. The other animal species they eat, whether

532
00:28:30,560 --> 00:28:34,760
Speaker 4: it's fish or deer, go away. Everyone is locking down

533
00:28:34,760 --> 00:28:38,400
Speaker 4: and there's nothing to eat. That's when bears chemical balance

534
00:28:38,560 --> 00:28:43,160
Speaker 4: changes and hibernation starts. The actually their metabolism slows down, right,

535
00:28:43,200 --> 00:28:46,760
Speaker 4: that's like body chemistry within them. But that's not going

536
00:28:46,800 --> 00:28:49,520
Speaker 4: to work if it stays warm, right, if the trees

537
00:28:49,640 --> 00:28:52,440
Speaker 4: keep producing, if the bunny rabbits keep hopping around, that

538
00:28:52,440 --> 00:28:54,640
Speaker 4: that doesn't happen. So in some of the places that

539
00:28:54,680 --> 00:28:58,160
Speaker 4: I've studied black bears in the western United States, there

540
00:28:58,200 --> 00:29:03,360
Speaker 4: have been these winters recently where the temperature hasn't dropped

541
00:29:03,360 --> 00:29:08,040
Speaker 4: and the snow hasn't fallen until like February, and so

542
00:29:08,080 --> 00:29:11,959
Speaker 4: the bears have remained active. But then when February comes

543
00:29:12,120 --> 00:29:15,720
Speaker 4: and in one week it's you know, three months of snow,

544
00:29:15,840 --> 00:29:19,720
Speaker 4: and everything shuts down. They're not hibernating already. Their bodies

545
00:29:19,760 --> 00:29:22,880
Speaker 4: haven't gotten into that hibernation state. They might not be

546
00:29:22,920 --> 00:29:25,520
Speaker 4: able to get there in time, and they may starve,

547
00:29:26,080 --> 00:29:29,080
Speaker 4: or they may freeze to death, or they may die,

548
00:29:29,400 --> 00:29:33,360
Speaker 4: or they may come into your garage and look for

549
00:29:33,400 --> 00:29:36,360
Speaker 4: a warm place and some food. So we're finding that

550
00:29:36,440 --> 00:29:41,479
Speaker 4: climate change not only impacts like the bear's perception of

551
00:29:41,520 --> 00:29:43,720
Speaker 4: what season it is and whether or not it's time

552
00:29:43,720 --> 00:29:47,120
Speaker 4: to hibernate, but it could also increase conflicts with people,

553
00:29:47,320 --> 00:29:49,200
Speaker 4: right because they kind of freak out. They're like, all

554
00:29:49,200 --> 00:29:51,720
Speaker 4: I need is some food. It was available last week,

555
00:29:51,760 --> 00:29:54,080
Speaker 4: it's not this week, So where can I find it?

556
00:29:54,120 --> 00:29:57,640
Speaker 4: In your trash can? And that is also a problem.

557
00:29:57,760 --> 00:29:59,560
Speaker 1: It's got to be a heart just like on their

558
00:29:59,640 --> 00:30:02,680
Speaker 1: natural like if they're not getting the rest that they

559
00:30:02,720 --> 00:30:05,400
Speaker 1: had in the past, right like that, that doesn't that

560
00:30:05,480 --> 00:30:06,120
Speaker 1: affect them?

561
00:30:06,680 --> 00:30:06,920
Speaker 2: You know?

562
00:30:07,880 --> 00:30:12,160
Speaker 4: Are they cranky? They are cranky. Bears are a lot

563
00:30:12,200 --> 00:30:15,520
Speaker 4: like us. They just aren't. They're hungry. They have they're angry.

564
00:30:15,800 --> 00:30:18,120
Speaker 1: I just need three months of sleep in the water.

565
00:30:18,440 --> 00:30:22,640
Speaker 4: They're hangry, like as do I. There are bears in

566
00:30:23,040 --> 00:30:26,520
Speaker 4: warm places where they never hibernate. So there are bears

567
00:30:26,520 --> 00:30:30,400
Speaker 4: in Florida right like in the Everglades. It's swampy, it's warm,

568
00:30:30,400 --> 00:30:32,520
Speaker 4: and they don't hibernate in the winter. But let me

569
00:30:32,600 --> 00:30:38,240
Speaker 4: clarify that setting up a hibernation den is the most

570
00:30:38,360 --> 00:30:42,040
Speaker 4: important and the most critical for surviving periods where there's

571
00:30:42,080 --> 00:30:44,680
Speaker 4: no food, right, So like classic winter when there's no

572
00:30:44,760 --> 00:30:50,320
Speaker 4: food and female bears give birth in hibernation, they need

573
00:30:50,360 --> 00:30:52,720
Speaker 4: to set up a hibernation den. They need to slow

574
00:30:52,800 --> 00:30:55,520
Speaker 4: down their metabolism, they need to go into a hibernation

575
00:30:55,600 --> 00:30:58,080
Speaker 4: state in order to give birth, because when they do,

576
00:30:58,120 --> 00:31:01,440
Speaker 4: they give birth. Every January. Every bear that's ever lived

577
00:31:01,440 --> 00:31:05,400
Speaker 4: in the history of no North American bears has given

578
00:31:05,440 --> 00:31:08,360
Speaker 4: birth in January, every single one. It's the most. It's

579
00:31:08,400 --> 00:31:08,680
Speaker 4: like my.

580
00:31:08,680 --> 00:31:11,560
Speaker 1: Favorite doctor, I'm gonna have to fact check that, check

581
00:31:11,640 --> 00:31:12,280
Speaker 1: it now.

582
00:31:12,520 --> 00:31:15,320
Speaker 4: Like you have my you have my permission. They're born

583
00:31:15,360 --> 00:31:16,200
Speaker 4: in January.

584
00:31:16,560 --> 00:31:19,240
Speaker 1: Let me call it Tim Ferris. Really quick, they realize

585
00:31:19,280 --> 00:31:21,400
Speaker 1: how much better they'd get it, Hockey if they were

586
00:31:21,480 --> 00:31:22,560
Speaker 1: born a little bit later.

587
00:31:22,800 --> 00:31:24,040
Speaker 4: Oh just slightly later.

588
00:31:24,240 --> 00:31:26,360
Speaker 1: Oh wow, you're really going to Malcolm Black, aren't you.

589
00:31:26,600 --> 00:31:30,480
Speaker 4: YEA. When I was doing my PhD research in the

590
00:31:30,560 --> 00:31:33,000
Speaker 4: Lake Tahoe area on black bears, we would just give

591
00:31:33,120 --> 00:31:37,320
Speaker 4: every bear a January first birthday. It was more about

592
00:31:37,320 --> 00:31:39,200
Speaker 4: it was less about when they were born and more

593
00:31:39,240 --> 00:31:41,520
Speaker 4: about what year right, as opposed to like what day

594
00:31:41,560 --> 00:31:46,040
Speaker 4: or what just January, And so the moms and mama

595
00:31:46,080 --> 00:31:50,080
Speaker 4: bears like have to stay in their den for you know,

596
00:31:50,280 --> 00:31:54,080
Speaker 4: sixteen twenty weeks, because they give birth to these one

597
00:31:54,240 --> 00:31:58,400
Speaker 4: pound like hairless, kind of blind little cubs, right like

598
00:31:58,440 --> 00:32:02,080
Speaker 4: they're they're they're little, are huge, right, Bears are bigger

599
00:32:02,080 --> 00:32:05,000
Speaker 4: than people and they give birth to these tiny, little,

600
00:32:05,120 --> 00:32:07,640
Speaker 4: like fist sized cups.

601
00:32:08,000 --> 00:32:08,160
Speaker 1: Right.

602
00:32:08,680 --> 00:32:11,760
Speaker 4: I mean, I personally am jealous, like human beings should

603
00:32:11,760 --> 00:32:14,000
Speaker 4: be able to do that, right, Like, we are smaller

604
00:32:14,120 --> 00:32:16,120
Speaker 4: and we give birth to these enormous babies and it

605
00:32:16,160 --> 00:32:18,640
Speaker 4: turns us apart. So bears they have these like nice

606
00:32:18,640 --> 00:32:21,400
Speaker 4: little bursts. The babies just slip out right, and then

607
00:32:21,560 --> 00:32:24,120
Speaker 4: they just nurse from their moms and the protection of

608
00:32:24,160 --> 00:32:28,080
Speaker 4: this hibernation den for a couple of months, like two

609
00:32:28,160 --> 00:32:30,680
Speaker 4: or three months, and then they emerge from the den altogether.

610
00:32:30,720 --> 00:32:33,080
Speaker 4: So the mama bear needs to prepare for hibernation by

611
00:32:33,160 --> 00:32:36,480
Speaker 4: packing on the pounds, getting as fat as she possibly

612
00:32:36,520 --> 00:32:41,320
Speaker 4: can in order to not eat, not drink, not urinate,

613
00:32:41,440 --> 00:32:45,200
Speaker 4: not defecate, and justurt birth and nurse some babies for

614
00:32:45,240 --> 00:32:49,120
Speaker 4: several months. And if the climate is not giving her

615
00:32:49,160 --> 00:32:51,080
Speaker 4: that signal that it is time to do that, then

616
00:32:51,120 --> 00:32:52,320
Speaker 4: she won't be ready.

617
00:32:52,920 --> 00:32:55,160
Speaker 1: And the like. If you play it out to the

618
00:32:55,200 --> 00:32:56,280
Speaker 1: worst possible outcome.

619
00:32:56,320 --> 00:32:59,360
Speaker 2: It's that like the cycle gets disrupted, disrupted to the

620
00:32:59,360 --> 00:33:01,760
Speaker 2: point that the the population just begin dwindling.

621
00:33:02,000 --> 00:33:05,560
Speaker 4: That's right, we just stop having births like successful berths.

622
00:33:05,760 --> 00:33:05,960
Speaker 1: Right.

623
00:33:06,000 --> 00:33:08,040
Speaker 4: So it's less about sometimes people are worried about like

624
00:33:08,160 --> 00:33:11,000
Speaker 4: hunting them, right, like outright killing of them, and it's

625
00:33:11,040 --> 00:33:15,200
Speaker 4: more about like females of reproductive age, like having successful

626
00:33:15,200 --> 00:33:17,520
Speaker 4: berths over and over, and that's if we don't have that,

627
00:33:17,560 --> 00:33:19,320
Speaker 4: then we don't have a future of the species.

628
00:33:19,720 --> 00:33:22,360
Speaker 2: You said something really interesting earlier that I wanted to

629
00:33:22,360 --> 00:33:25,120
Speaker 2: touch back on. They don't And I was always curious

630
00:33:25,120 --> 00:33:27,240
Speaker 2: about this. They don't pooper pee that whole time.

631
00:33:27,560 --> 00:33:28,680
Speaker 4: Yeah, isn't that crazy.

632
00:33:29,360 --> 00:33:32,480
Speaker 1: I always wondered how that. I don't know.

633
00:33:32,480 --> 00:33:34,280
Speaker 2: I remember as a kid hearing that. I'm like, they

634
00:33:34,320 --> 00:33:36,960
Speaker 2: got to poop a little bit, probably.

635
00:33:36,640 --> 00:33:40,080
Speaker 4: They Okay, okay, So let me just say because scientists

636
00:33:40,080 --> 00:33:42,840
Speaker 4: are always going to give a good like, it depends, right,

637
00:33:42,880 --> 00:33:47,200
Speaker 4: So here's my scientist. It depends for accuracy. There haven't

638
00:33:47,240 --> 00:33:50,080
Speaker 4: been a lot of studies done on hibernating bears. You

639
00:33:50,120 --> 00:33:53,200
Speaker 4: can imagine why, right, Like it is very hard to

640
00:33:53,280 --> 00:33:54,600
Speaker 4: study these animals.

641
00:33:54,280 --> 00:33:56,560
Speaker 1: Right, Yeah, it seems so cozy in there. I would

642
00:33:56,600 --> 00:33:58,600
Speaker 1: be all about that. If you need somebody to go

643
00:33:58,680 --> 00:34:02,280
Speaker 1: in there, you can all right, cool, I'll be back

644
00:34:02,280 --> 00:34:03,000
Speaker 1: in a couple hours.

645
00:34:03,680 --> 00:34:05,680
Speaker 4: Like it says, it's like pretty dangerous and like they

646
00:34:05,680 --> 00:34:08,560
Speaker 4: don't want to be bothered, and a lot of these

647
00:34:08,560 --> 00:34:10,640
Speaker 4: things out very important. And then it's hard to study

648
00:34:10,840 --> 00:34:14,439
Speaker 4: hibernation and captive bears like at the zoo because again,

649
00:34:14,480 --> 00:34:17,160
Speaker 4: their food source doesn't go away in the wintertime, and

650
00:34:17,239 --> 00:34:20,120
Speaker 4: so they often don't hibernate because they're like, I'm I'm cool,

651
00:34:20,160 --> 00:34:23,680
Speaker 4: I'm chilling. I have like a heater and a you know,

652
00:34:23,760 --> 00:34:25,920
Speaker 4: person who brings me food. So there aren't a lot

653
00:34:25,960 --> 00:34:27,799
Speaker 4: of studies on this. But what we found is that

654
00:34:28,880 --> 00:34:32,359
Speaker 4: in this metabolic state that they enter, they recycle all

655
00:34:32,400 --> 00:34:34,919
Speaker 4: of their waste and urine, so that's why they don't

656
00:34:35,000 --> 00:34:39,080
Speaker 4: drink anything, and the liquid in their body is being

657
00:34:39,120 --> 00:34:42,400
Speaker 4: recycled like over and over. It's fascinating and there's a

658
00:34:42,400 --> 00:34:46,560
Speaker 4: lot that we can learn about human health and you know,

659
00:34:46,640 --> 00:34:51,839
Speaker 4: biomedicine from studying hibernating bears. In fact, there are some

660
00:34:52,160 --> 00:34:56,200
Speaker 4: hypotheses that they're plasma changes, so we can detect the

661
00:34:56,239 --> 00:34:59,160
Speaker 4: chemical changes down to the blood and the plasma level

662
00:34:59,680 --> 00:35:04,600
Speaker 4: and their organs are actually preserved because the like just

663
00:35:04,600 --> 00:35:10,320
Speaker 4: from recycling molecular components of their plasma changes. I've had

664
00:35:10,600 --> 00:35:14,040
Speaker 4: a researcher come to the field with me in Minnesota

665
00:35:14,600 --> 00:35:19,280
Speaker 4: who was a cardiologist and was studying, you know, human hearts,

666
00:35:20,200 --> 00:35:21,640
Speaker 4: and the idea was that they wanted to take a

667
00:35:21,640 --> 00:35:24,800
Speaker 4: blood sample from a hibernating bear, which we were able

668
00:35:24,840 --> 00:35:27,000
Speaker 4: to do, not without drama, but we were able to

669
00:35:27,040 --> 00:35:31,560
Speaker 4: do it. And they wanted to see if the blood

670
00:35:31,960 --> 00:35:36,279
Speaker 4: of a hibernating bear could preserve human organs because we

671
00:35:36,400 --> 00:35:42,000
Speaker 4: need a way to make organ donors. Organs oh last longer.

672
00:35:43,120 --> 00:35:46,440
Speaker 4: When there's an organ donor and there's a recipient somewhere

673
00:35:46,440 --> 00:35:48,840
Speaker 4: in a hospital waiting for a lung or a heart

674
00:35:49,000 --> 00:35:53,560
Speaker 4: or a kidney, often the organ will die in transport

675
00:35:53,719 --> 00:35:55,960
Speaker 4: because we don't have a good way to keep them alive.

676
00:35:56,000 --> 00:36:00,239
Speaker 4: But apparently bear blood, hibernating bear blood might be the

677
00:36:00,239 --> 00:36:03,120
Speaker 4: thing we need to like if we can replicate it

678
00:36:03,760 --> 00:36:06,239
Speaker 4: to figure out how to preserve organs for double the

679
00:36:06,280 --> 00:36:08,640
Speaker 4: amount of time so that more lives can be saved

680
00:36:08,680 --> 00:36:09,800
Speaker 4: by organ donors.

681
00:36:10,880 --> 00:36:11,600
Speaker 1: That's incredible.

682
00:36:11,840 --> 00:36:14,080
Speaker 2: See this is in learning new stuff too. I'm gonna

683
00:36:14,080 --> 00:36:15,839
Speaker 2: start going poop and pee in the recycling can.

684
00:36:16,160 --> 00:36:19,040
Speaker 4: Yeah right, I mean that's what I'm saying.

685
00:36:19,160 --> 00:36:21,279
Speaker 1: That is, I think we got what you recycle your

686
00:36:21,280 --> 00:36:23,920
Speaker 1: way to live. I mean, you know, talking about the

687
00:36:23,960 --> 00:36:26,640
Speaker 1: vaccine and you know the like, there is a lot

688
00:36:26,640 --> 00:36:28,600
Speaker 1: of people who had some ideas about how you could

689
00:36:28,640 --> 00:36:33,759
Speaker 1: recycle your own You're protect you from Jack. I think

690
00:36:33,800 --> 00:36:36,399
Speaker 1: you just endorsed that, right, so we can just move along.

691
00:36:36,400 --> 00:36:39,480
Speaker 2: That's the joke stuff, Jack. Why don't you want to

692
00:36:39,480 --> 00:36:40,440
Speaker 2: ask a serious question?

693
00:36:40,680 --> 00:36:44,160
Speaker 1: Yeah? Okay, so you wake up and you're a bear.

694
00:36:45,920 --> 00:36:47,840
Speaker 1: I have an answer to this that I'll get first.

695
00:36:47,840 --> 00:36:51,200
Speaker 1: But like, what's the first thing you're doing? Like, I

696
00:36:51,239 --> 00:36:57,000
Speaker 1: personally feel like showing the other bears water slides would

697
00:36:57,000 --> 00:37:01,040
Speaker 1: be high on. I feel like bears would love water slides.

698
00:37:01,239 --> 00:37:03,399
Speaker 1: And I don't think i've seen a bear like I've

699
00:37:03,400 --> 00:37:07,000
Speaker 1: seen them enjoy a pool. I've seen them enjoy hammocks,

700
00:37:07,880 --> 00:37:11,440
Speaker 1: love a hammock, but like a water slide park, like

701
00:37:11,600 --> 00:37:15,560
Speaker 1: me and my bear friends go ride on water slide park. Yeah,

702
00:37:15,640 --> 00:37:18,040
Speaker 1: that sounds pretty fun. What would what would your be

703
00:37:18,200 --> 00:37:18,759
Speaker 1: other than that?

704
00:37:19,120 --> 00:37:22,080
Speaker 4: What would be the first I guess realistically? Yeah, sure,

705
00:37:22,120 --> 00:37:24,719
Speaker 4: that I do as a bear. I mean, you know,

706
00:37:24,800 --> 00:37:29,839
Speaker 4: they're just so motivated by hunger as am I. So

707
00:37:30,120 --> 00:37:32,120
Speaker 4: I think the first thing I might do is like

708
00:37:32,800 --> 00:37:36,759
Speaker 4: hit up like a buffet, you know, like like a

709
00:37:36,800 --> 00:37:39,880
Speaker 4: good Like what's a good buffet? I mean, Sizzler is classic.

710
00:37:40,280 --> 00:37:43,800
Speaker 1: Yeah, just in my family pizza hut salad bar oh.

711
00:37:43,640 --> 00:37:47,640
Speaker 4: From the nineties. Yeah, pizza hut salad bar I thinks

712
00:37:47,760 --> 00:37:51,000
Speaker 4: used to have one. Yeah, okay, yeah, you know, like

713
00:37:51,040 --> 00:37:54,680
Speaker 4: a solid buffet I think would be what I do.

714
00:37:55,320 --> 00:37:58,239
Speaker 4: But I might also, like, you know what's funny is

715
00:37:58,239 --> 00:38:00,759
Speaker 4: that what people talk to me about bears all the time, right,

716
00:38:00,800 --> 00:38:03,879
Speaker 4: And so often they'll bring up like Yogi Bear, right,

717
00:38:03,920 --> 00:38:07,719
Speaker 4: the cartoon, and they'll talk about like picnic baskets and

718
00:38:07,880 --> 00:38:10,160
Speaker 4: like going for a picnic and all that kind of stuff,

719
00:38:10,160 --> 00:38:11,640
Speaker 4: And I'm like, maybe that would be cute. Maybe if

720
00:38:11,640 --> 00:38:13,200
Speaker 4: I woke up as a bear, I might be like, Hey,

721
00:38:13,280 --> 00:38:16,440
Speaker 4: let's let's like let's actualize this. Let's like go for

722
00:38:16,520 --> 00:38:19,440
Speaker 4: a picnic at a picnic table in a public park

723
00:38:19,520 --> 00:38:22,320
Speaker 4: and blow people's minds. You know, let's just like screw

724
00:38:22,440 --> 00:38:26,080
Speaker 4: with people and make this whole Yogi Bear story real. Yeah,

725
00:38:26,080 --> 00:38:28,000
Speaker 4: and you know, do that play the part.

726
00:38:28,440 --> 00:38:31,319
Speaker 1: I like that. Sorry, we're just furiously crossing off the

727
00:38:31,360 --> 00:38:34,919
Speaker 1: five Yogi bear questions. Yeah, might not that one. Those

728
00:38:34,960 --> 00:38:38,560
Speaker 1: might come off as hack. Now that's another one.

729
00:38:38,920 --> 00:38:42,319
Speaker 2: Oh okay, So to that point right about you know,

730
00:38:43,080 --> 00:38:45,800
Speaker 2: bears taking a pie off a window sill and things

731
00:38:45,880 --> 00:38:49,280
Speaker 2: like this. So we constantly read stories or I'm constant

732
00:38:49,320 --> 00:38:52,000
Speaker 2: seeing stories of like, you know, black bear shows up

733
00:38:52,040 --> 00:38:55,719
Speaker 2: in a backyard, and you know, the species are increasing.

734
00:38:55,760 --> 00:38:58,080
Speaker 2: The BBC over the summer was like.

735
00:38:58,480 --> 00:39:00,560
Speaker 1: Bears are returning to the Alps.

736
00:39:00,640 --> 00:39:03,520
Speaker 2: Here's what you need to do to avoid, you know,

737
00:39:03,640 --> 00:39:06,760
Speaker 2: having a horrible encounter. We're in how to stay safe

738
00:39:06,760 --> 00:39:09,759
Speaker 2: in bear territory. Some things feel and then other things

739
00:39:09,800 --> 00:39:12,000
Speaker 2: I've read about how I think Louisiana may have a

740
00:39:12,040 --> 00:39:14,600
Speaker 2: bear hunting season for the first time in a long time,

741
00:39:15,040 --> 00:39:18,760
Speaker 2: and that like populations are rising to levels where before

742
00:39:18,800 --> 00:39:21,640
Speaker 2: it seemed like it was pretty fraught with potential of like,

743
00:39:21,680 --> 00:39:24,799
Speaker 2: you know, extinction. Are these stories like are they part

744
00:39:24,800 --> 00:39:27,120
Speaker 2: of a bigger picture? Are there people who are just

745
00:39:27,160 --> 00:39:30,640
Speaker 2: looking at these bear communities being like trying to other

746
00:39:30,840 --> 00:39:33,600
Speaker 2: the bears and make them feel like a threat, and

747
00:39:33,640 --> 00:39:36,640
Speaker 2: how we have to control them or is it something

748
00:39:36,640 --> 00:39:39,520
Speaker 2: that has to be hunted. That's one thing I'm seeing constantly,

749
00:39:39,920 --> 00:39:42,319
Speaker 2: aside from also locally, especially in like La, people who

750
00:39:42,360 --> 00:39:46,239
Speaker 2: live near the Angelus National Forest, increased anecdotes and like

751
00:39:46,320 --> 00:39:48,600
Speaker 2: local news about bears like showing up.

752
00:39:49,320 --> 00:39:50,840
Speaker 1: And I'm curious, from your.

753
00:39:50,760 --> 00:39:53,319
Speaker 2: Perspective, is it like this is a good thing, like right,

754
00:39:53,400 --> 00:39:56,799
Speaker 2: like like conservations working and we're able to like help

755
00:39:56,880 --> 00:40:01,720
Speaker 2: repopulate or this is or it's fine lines?

756
00:40:02,000 --> 00:40:04,080
Speaker 1: Where are we got so.

757
00:40:04,000 --> 00:40:07,680
Speaker 4: Much to say about this? I'm gonna save the hunting stuff, okay,

758
00:40:08,000 --> 00:40:11,000
Speaker 4: because I have a personal opinion about hunting and I

759
00:40:11,000 --> 00:40:12,720
Speaker 4: have a professional opinion, and they're different.

760
00:40:13,000 --> 00:40:13,320
Speaker 1: Okay.

761
00:40:13,800 --> 00:40:15,560
Speaker 4: But to answer your first question, I just want here's

762
00:40:15,560 --> 00:40:18,560
Speaker 4: a little anecdote. When I was in grad school, my

763
00:40:18,960 --> 00:40:22,080
Speaker 4: advisor said to me he had been studying carnivores for

764
00:40:22,280 --> 00:40:24,480
Speaker 4: his whole professional career, and he said to me, when

765
00:40:24,520 --> 00:40:28,120
Speaker 4: it comes to carnivores, people think there's either too few

766
00:40:28,840 --> 00:40:32,160
Speaker 4: or too many. They never think there's the right number.

767
00:40:33,239 --> 00:40:37,359
Speaker 4: And man, oh man, does that ring true? Because when

768
00:40:37,560 --> 00:40:40,640
Speaker 4: bears are on the endangered species list, like people are

769
00:40:40,800 --> 00:40:43,040
Speaker 4: like save the bears, We love bears. We got to

770
00:40:43,080 --> 00:40:45,920
Speaker 4: get more bears, bring them back by any means necessary.

771
00:40:45,960 --> 00:40:48,760
Speaker 4: And once we get like a good number of bears

772
00:40:48,800 --> 00:40:51,680
Speaker 4: around and they're like, oh, look, my ancestors used to

773
00:40:51,680 --> 00:40:53,760
Speaker 4: live here. I'm going to come back to this space

774
00:40:54,200 --> 00:40:56,800
Speaker 4: all of a sudden, right like people are ringing the alarm,

775
00:40:56,920 --> 00:40:59,880
Speaker 4: like bears are everywhere they've returned, Like what are you

776
00:41:00,200 --> 00:41:03,840
Speaker 4: to do? They're eating your puppies. So that's like my

777
00:41:03,920 --> 00:41:07,440
Speaker 4: thing I would actually, I would I would call on

778
00:41:07,600 --> 00:41:13,400
Speaker 4: everyone listening to really think about, like, like where do

779
00:41:13,440 --> 00:41:17,080
Speaker 4: you fit in this? Like you do care about wild animals,

780
00:41:17,120 --> 00:41:19,000
Speaker 4: and you care when there's not enough of them, but

781
00:41:19,040 --> 00:41:21,600
Speaker 4: when there's like plenty or when they're doing well, and

782
00:41:21,640 --> 00:41:24,120
Speaker 4: when you see them, does that mean there's too many

783
00:41:24,239 --> 00:41:26,920
Speaker 4: or does that mean you're uncomfortable? Because I think that's

784
00:41:27,000 --> 00:41:31,080
Speaker 4: a huge, huge difference because like, on one hand, when

785
00:41:31,120 --> 00:41:33,160
Speaker 4: it comes to black bears, like we've been doing conservation

786
00:41:33,239 --> 00:41:36,240
Speaker 4: on them for several decades, it's been working pretty well,

787
00:41:36,320 --> 00:41:39,680
Speaker 4: and black bear populations are rebounding. But there's not like

788
00:41:40,400 --> 00:41:44,080
Speaker 4: so many black beers, right, I mean, considering how many

789
00:41:44,160 --> 00:41:48,080
Speaker 4: there used to be before, like you know, the colonization

790
00:41:48,280 --> 00:41:53,160
Speaker 4: of North America, there's a fraction of that number here today. Right,

791
00:41:53,239 --> 00:41:55,239
Speaker 4: there's no habitat for them. I mean, like you know,

792
00:41:55,280 --> 00:41:56,920
Speaker 4: you look at New York City. New York City used

793
00:41:56,920 --> 00:41:58,560
Speaker 4: to have bears before it was New York City, and

794
00:41:58,600 --> 00:42:00,479
Speaker 4: now you're not going to find a bear anywhere you're there.

795
00:42:01,000 --> 00:42:05,320
Speaker 4: So you know, like San Francisco, Los Angeles, grizzly bears

796
00:42:05,400 --> 00:42:07,919
Speaker 4: like walked in those spaces. You're not going to find

797
00:42:07,960 --> 00:42:12,520
Speaker 4: grizzly bears in California. So I have such a strong

798
00:42:13,560 --> 00:42:16,600
Speaker 4: like pushback on people who are like there's so many,

799
00:42:16,600 --> 00:42:18,799
Speaker 4: they're everywhere. They're in my backyard. So it's like, well,

800
00:42:18,800 --> 00:42:21,840
Speaker 4: it's their backyard. Actually, that's like they're in their backyard,

801
00:42:21,920 --> 00:42:25,520
Speaker 4: like they're at their house. It's like they came first.

802
00:42:26,000 --> 00:42:29,120
Speaker 4: Bears existed in North America from what we can tell

803
00:42:29,160 --> 00:42:32,320
Speaker 4: from like the evolutionary timeline. They were here before people,

804
00:42:32,400 --> 00:42:36,279
Speaker 4: before indigenous people, before any human beings walked on the

805
00:42:36,280 --> 00:42:39,120
Speaker 4: continent of North America. As far as we know, black

806
00:42:39,160 --> 00:42:42,960
Speaker 4: bears were here first. And so this is their land

807
00:42:43,280 --> 00:42:45,960
Speaker 4: and we need them right Like they helped to control

808
00:42:46,040 --> 00:42:50,440
Speaker 4: the herbivore population, that helps control the vegetation community, and

809
00:42:50,480 --> 00:42:53,560
Speaker 4: that gives us deeper roots in the soil that prevents erosion,

810
00:42:53,760 --> 00:42:55,640
Speaker 4: and that's a really big issue. I mean, there's a

811
00:42:55,640 --> 00:42:58,520
Speaker 4: lot of reasons we need these predators. Okay, the next

812
00:42:58,520 --> 00:43:03,000
Speaker 4: thing I'll say is that COVID, man oh Man, COVID

813
00:43:03,120 --> 00:43:07,000
Speaker 4: actually plays into this because when the world shut down

814
00:43:07,080 --> 00:43:10,640
Speaker 4: and everyone had to start working from home in twenty twenty,

815
00:43:11,080 --> 00:43:14,960
Speaker 4: we started like noticing shit, Like people started like looking

816
00:43:15,000 --> 00:43:16,799
Speaker 4: out their window and being like, oh my gosh, there's

817
00:43:16,800 --> 00:43:19,439
Speaker 4: a coyote out there. Oh my gosh, have you seen

818
00:43:19,480 --> 00:43:22,800
Speaker 4: how many raccoons are in the trash? Oh my gosh.

819
00:43:22,840 --> 00:43:26,319
Speaker 4: The combination of people being home and being able to

820
00:43:26,400 --> 00:43:29,319
Speaker 4: notice what happens in and around their home, and also

821
00:43:29,360 --> 00:43:30,960
Speaker 4: like not going out at night, right Like, we're not

822
00:43:31,000 --> 00:43:32,760
Speaker 4: going to the club, We're not like going to places.

823
00:43:32,800 --> 00:43:35,680
Speaker 4: We're just like watch. We're on bare watch. We can hear.

824
00:43:35,760 --> 00:43:39,520
Speaker 4: We can notice people spending more time in wild places,

825
00:43:39,600 --> 00:43:42,040
Speaker 4: right Like when we were able to travel getting COVID,

826
00:43:42,080 --> 00:43:45,000
Speaker 4: it was safer to be in nature than other places.

827
00:43:45,560 --> 00:43:50,160
Speaker 4: And then technology, everyone has like a ring camera, right

828
00:43:50,200 --> 00:43:51,880
Speaker 4: Like you used to have a doorbell and now you

829
00:43:51,960 --> 00:43:54,640
Speaker 4: have a camera at your door. Everyone is ape and

830
00:43:54,680 --> 00:43:55,920
Speaker 4: they have a camera at the front door, at the

831
00:43:55,960 --> 00:43:59,120
Speaker 4: back door, all around the house. Door cameras, the doorbells

832
00:43:59,120 --> 00:44:03,440
Speaker 4: have cameras, Like there's so much monitoring. There's also like

833
00:44:03,840 --> 00:44:09,560
Speaker 4: I'm flashing my iPhone at y'all because when I first

834
00:44:09,600 --> 00:44:14,160
Speaker 4: started studying bears, we didn't have cameras with phones or

835
00:44:14,320 --> 00:44:17,120
Speaker 4: phones with you know what I'm trying to say, camera phones,

836
00:44:18,000 --> 00:44:22,320
Speaker 4: and now we do. So like the amount of bears

837
00:44:22,320 --> 00:44:25,160
Speaker 4: that I can show that I'm working on today when

838
00:44:25,160 --> 00:44:28,240
Speaker 4: I do field work is an order of magnitude bigger

839
00:44:28,280 --> 00:44:32,200
Speaker 4: than before. So anyone who interacts with a bear in

840
00:44:32,239 --> 00:44:35,239
Speaker 4: twenty twenty three can prove it, can show it, can

841
00:44:35,320 --> 00:44:38,600
Speaker 4: put it on the internet, can spread this information. Whereas

842
00:44:38,640 --> 00:44:41,600
Speaker 4: ten years ago, fifteen years ago, you just had the

843
00:44:41,640 --> 00:44:43,319
Speaker 4: story to tell and it didn't get very far.

844
00:44:43,400 --> 00:44:45,560
Speaker 1: I didn't believe so existed. It was like Bigfoot.

845
00:44:45,560 --> 00:44:49,440
Speaker 4: To me, it was yoking bear and I was like, yeah, that's.

846
00:44:49,480 --> 00:44:53,279
Speaker 1: That's a cartoon, you fools. Sure enough, And then I

847
00:44:53,280 --> 00:44:57,000
Speaker 1: got a cat, sure enough, was one of those real ones.

848
00:44:58,560 --> 00:45:03,120
Speaker 4: So it's like talking to There's like this combination of things, right,

849
00:45:03,120 --> 00:45:05,480
Speaker 4: there's just a combination of things, like, yes, there are

850
00:45:05,520 --> 00:45:08,359
Speaker 4: more bears, there's not very many more bears. Like it's

851
00:45:08,400 --> 00:45:12,040
Speaker 4: going well it's going, well, there's more coyotes. There's not

852
00:45:12,160 --> 00:45:15,719
Speaker 4: that many more coyotes. There's more coyotes caught on your

853
00:45:15,840 --> 00:45:18,880
Speaker 4: nest camera. Right, That's what it is like you just

854
00:45:19,000 --> 00:45:21,239
Speaker 4: didn't know that coyotes are mining their own business on

855
00:45:21,320 --> 00:45:24,279
Speaker 4: your property, you know, five years ago, But now you know,

856
00:45:24,480 --> 00:45:26,759
Speaker 4: and now you have a feeling about it. And so

857
00:45:26,960 --> 00:45:29,800
Speaker 4: there are so many scientists, a lot of folks especially

858
00:45:29,840 --> 00:45:32,839
Speaker 4: I have to highlight like UC Berkeley has this incredible lab,

859
00:45:32,880 --> 00:45:36,400
Speaker 4: the Shell Lab sh e ll, run by a black

860
00:45:36,560 --> 00:45:41,040
Speaker 4: man who's a wonderful wildlife ecologist, and they primarily study

861
00:45:41,120 --> 00:45:45,879
Speaker 4: like urban carnivores, and they are actually using data from

862
00:45:46,239 --> 00:45:49,280
Speaker 4: next door you know that terrible like app of people

863
00:45:49,320 --> 00:45:50,120
Speaker 4: on the sist.

864
00:45:50,320 --> 00:45:54,560
Speaker 1: Yeah, yeah, kind of data are they getting? Yeah, those

865
00:45:54,600 --> 00:45:57,200
Speaker 1: people are selling stuff outside on their corner.

866
00:45:57,280 --> 00:46:00,200
Speaker 4: Oh, so like filter out all of the disc m

867
00:46:00,200 --> 00:46:05,040
Speaker 4: minatory like posts on racism and anti homeless rhetoric, and

868
00:46:05,160 --> 00:46:08,680
Speaker 4: you get people talking about animals and they're actually using

869
00:46:09,080 --> 00:46:13,399
Speaker 4: data from next door to kind of measure like are

870
00:46:13,440 --> 00:46:18,000
Speaker 4: people reporting seeing wildlife more often than before? And the

871
00:46:18,040 --> 00:46:20,440
Speaker 4: answer is yes, So we have like a few more animals,

872
00:46:20,480 --> 00:46:22,719
Speaker 4: but a lot more reporting, a lot more discussions, a

873
00:46:22,760 --> 00:46:25,400
Speaker 4: lot of people sharing it and seeing it, and I

874
00:46:25,400 --> 00:46:29,320
Speaker 4: think that's good. I think it normalizes wildlife being around.

875
00:46:29,600 --> 00:46:32,360
Speaker 4: But people got to like stop worrying that they're not

876
00:46:32,440 --> 00:46:34,040
Speaker 4: going to be okay, cause it's like, when was the

877
00:46:34,080 --> 00:46:37,759
Speaker 4: last time a coyote like killed somebody. We don't have that,

878
00:46:37,840 --> 00:46:41,319
Speaker 4: Like that doesn't happen a bear. Yeah, Like it's not

879
00:46:41,360 --> 00:46:44,000
Speaker 4: like you're okay, Like you're safe, you just might not

880
00:46:44,000 --> 00:46:45,440
Speaker 4: feel comfortable.

881
00:46:45,360 --> 00:46:48,680
Speaker 2: Right, Yeah, it gets to your point about awareness, Like

882
00:46:48,680 --> 00:46:50,759
Speaker 2: the more I see it, the more I'm like, I

883
00:46:50,800 --> 00:46:53,799
Speaker 2: actually see more videos of bear encounters where people like

884
00:46:53,920 --> 00:46:56,719
Speaker 2: successfully are just like who know what they're doing and

885
00:46:56,760 --> 00:46:59,360
Speaker 2: like the bear leaves, And that's actually given me a

886
00:46:59,360 --> 00:47:02,000
Speaker 2: little bit more being like, Okay, they're not out here

887
00:47:02,040 --> 00:47:03,280
Speaker 2: to fucking eat our pies.

888
00:47:03,400 --> 00:47:04,680
Speaker 1: You know, they're just doing their thing.

889
00:47:04,760 --> 00:47:07,000
Speaker 2: And if you if you happen to have an encounter,

890
00:47:07,120 --> 00:47:09,359
Speaker 2: there is a way to exit about being like, get

891
00:47:09,400 --> 00:47:10,400
Speaker 2: your fucking.

892
00:47:10,120 --> 00:47:14,480
Speaker 1: Gun tall this bear, all this bear pie fear mongering

893
00:47:14,800 --> 00:47:17,239
Speaker 1: is getting out of hand and it's unbearable.

894
00:47:17,400 --> 00:47:19,840
Speaker 4: Actually, okay, we need to wage your campaign.

895
00:47:20,200 --> 00:47:23,160
Speaker 1: Yeah, we need to take a quick break and then

896
00:47:23,200 --> 00:47:25,320
Speaker 1: we're gonna come back and I want to ask about

897
00:47:25,760 --> 00:47:29,960
Speaker 1: bear videos just generally, because I think you've mentioned it

898
00:47:29,960 --> 00:47:32,440
Speaker 1: a couple of times, but bear videos rule. They probably

899
00:47:32,440 --> 00:47:35,920
Speaker 1: make your job a little bit easier. So we're gonna talk.

900
00:47:35,960 --> 00:47:50,200
Speaker 1: We'll be right back, and we're back. And yeah, so,

901
00:47:50,280 --> 00:47:52,600
Speaker 1: I mean, cat videos is the thing. Everyone's like, the

902
00:47:52,680 --> 00:47:55,920
Speaker 1: internet full of cat videos. Bear videos for me for

903
00:47:56,040 --> 00:47:59,880
Speaker 1: my money better? They rule? So first of all, do

904
00:47:59,920 --> 00:48:03,719
Speaker 1: you like is it annoying to you as somebody with

905
00:48:03,800 --> 00:48:07,360
Speaker 1: the superior animal to cat? Yeah? Like, are you like

906
00:48:08,640 --> 00:48:11,800
Speaker 1: enough with the cat videos? Have you seen these Russian

907
00:48:11,880 --> 00:48:15,120
Speaker 1: guys whose best friends are literally a bear?

908
00:48:16,160 --> 00:48:18,200
Speaker 4: I have to say, I have to say. I don't

909
00:48:18,200 --> 00:48:22,560
Speaker 4: want to offend anybody who's listening. Oh boy, but like

910
00:48:23,080 --> 00:48:27,160
Speaker 4: I get sent so many bear videos and get me

911
00:48:27,200 --> 00:48:31,680
Speaker 4: alone so every day, like whether it's text.

912
00:48:32,440 --> 00:48:35,040
Speaker 1: Hold on, have you seen this one though? Check this

913
00:48:35,080 --> 00:48:37,400
Speaker 1: one out? This is one where the bear catches bread

914
00:48:37,920 --> 00:48:44,360
Speaker 1: yet have you seen this one? First? Sits back? Impressive

915
00:48:45,400 --> 00:48:54,640
Speaker 1: and this is probably not advisable. Bears start waving from no,

916
00:48:54,719 --> 00:48:59,239
Speaker 1: look cat. Have you seen that one? Okay? Okay, how

917
00:48:59,239 --> 00:49:00,920
Speaker 1: about this other one? Uh?

918
00:49:02,320 --> 00:49:02,920
Speaker 4: Impressive?

919
00:49:03,640 --> 00:49:04,920
Speaker 1: Okay, that was impressive.

920
00:49:05,080 --> 00:49:08,279
Speaker 4: Okay, the ketch was impressive the catch was impressive. I'm

921
00:49:08,320 --> 00:49:15,040
Speaker 4: never gonna champion like captive bears like facility, like I

922
00:49:15,160 --> 00:49:16,719
Speaker 4: studied wild bears.

923
00:49:17,040 --> 00:49:19,920
Speaker 1: Okay, but that bear was behind the smallest fence I've

924
00:49:19,960 --> 00:49:22,880
Speaker 1: ever seen. But it was like chicken wire. I was like,

925
00:49:23,000 --> 00:49:24,560
Speaker 1: I'm sorry, is okay?

926
00:49:24,920 --> 00:49:26,879
Speaker 4: It's an extremely tame bear.

927
00:49:27,080 --> 00:49:31,040
Speaker 1: Yeah right, okay, I got it. Like I love watching

928
00:49:31,040 --> 00:49:35,360
Speaker 1: bears enjoy a hammock. I particularly feel like that, like

929
00:49:35,600 --> 00:49:41,480
Speaker 1: because they they are perfectly physically expressing the weird, unstable

930
00:49:41,520 --> 00:49:43,839
Speaker 1: feeling of getting in a hammock for the first time,

931
00:49:44,560 --> 00:49:49,240
Speaker 1: like that if you like had a genius comedic actor,

932
00:49:49,840 --> 00:49:53,480
Speaker 1: like doing a routine with a hammock. This is kind

933
00:49:53,520 --> 00:49:57,440
Speaker 1: of like, so this one is too little baby cubs

934
00:49:57,480 --> 00:50:02,400
Speaker 1: doing it, says Woman Records. Rowdy Bear Cup. They're so rowdy.

935
00:50:02,840 --> 00:50:06,920
Speaker 1: They look half like, you know, they're perfectly inhabiting the

936
00:50:06,960 --> 00:50:08,920
Speaker 1: weirdness of being on a hammock, and half they just

937
00:50:08,920 --> 00:50:11,719
Speaker 1: look like if you gave my kids a little bit

938
00:50:11,760 --> 00:50:12,800
Speaker 1: of sugar and let.

939
00:50:12,680 --> 00:50:14,319
Speaker 4: Them and they flipped over.

940
00:50:14,920 --> 00:50:15,720
Speaker 1: That's so real.

941
00:50:15,800 --> 00:50:17,879
Speaker 4: Yeah, no, you're right, that's so real. Like hammocks are

942
00:50:17,960 --> 00:50:22,319
Speaker 4: super awkward and they're just having the weirdest time and

943
00:50:22,360 --> 00:50:24,480
Speaker 4: it's like who really spends that much time in a

944
00:50:24,480 --> 00:50:27,759
Speaker 4: hammock because they're like it's just so awkward and you

945
00:50:27,840 --> 00:50:32,240
Speaker 4: never feel totally like like you know, stable.

946
00:50:32,560 --> 00:50:34,480
Speaker 1: But then sometimes they get in there and they're really

947
00:50:34,760 --> 00:50:37,759
Speaker 1: they're soaking it. Yeah yeah, oh yeah.

948
00:50:37,880 --> 00:50:41,719
Speaker 4: Bears love to play, you know, especially the cubs. Like

949
00:50:41,719 --> 00:50:43,440
Speaker 4: like baby animals have to play, but the cubs are

950
00:50:43,480 --> 00:50:46,400
Speaker 4: so much like human beings, like we can just see it.

951
00:50:46,480 --> 00:50:50,120
Speaker 4: And when a bear is good and full, it has

952
00:50:50,400 --> 00:50:52,920
Speaker 4: time to play. And so we get a lot of

953
00:50:52,920 --> 00:50:55,879
Speaker 4: those videos of like bears splashing around people's swimming pools

954
00:50:56,000 --> 00:50:59,239
Speaker 4: or like like sitting you know, in their hot tubs,

955
00:50:59,520 --> 00:51:01,600
Speaker 4: or like you know, playing on the hammock or going

956
00:51:01,600 --> 00:51:03,919
Speaker 4: on the swing. Because they're curious and they like to play,

957
00:51:03,920 --> 00:51:07,040
Speaker 4: and that is one of the reasons that they show

958
00:51:07,120 --> 00:51:08,879
Speaker 4: up in the other kind of video, right, like where

959
00:51:08,880 --> 00:51:11,600
Speaker 4: they're trained. That's the reason that like we used to

960
00:51:11,600 --> 00:51:14,120
Speaker 4: see bears in the circus, yeah, right all the time.

961
00:51:14,239 --> 00:51:17,400
Speaker 4: It's like they aren't easily trained. They're really smart animals.

962
00:51:17,880 --> 00:51:21,239
Speaker 4: They are very agile, right, Like their bodies work in

963
00:51:21,280 --> 00:51:25,000
Speaker 4: weighs a lot like ours, and so they they have

964
00:51:25,040 --> 00:51:26,879
Speaker 4: fun as long as they're I'm going to say it again.

965
00:51:26,920 --> 00:51:29,600
Speaker 4: As long as their belly is full honey, like, then

966
00:51:29,760 --> 00:51:31,400
Speaker 4: they can have a good time. And I think that

967
00:51:31,520 --> 00:51:35,560
Speaker 4: is just so endearing about that, right, like relatable, relatable.

968
00:51:35,960 --> 00:51:37,480
Speaker 1: Yeah, I want to I want to show you this

969
00:51:37,520 --> 00:51:39,080
Speaker 1: other one how to. I haven't seen the.

970
00:51:39,120 --> 00:51:42,400
Speaker 2: Video, but as a really freaky title, it says, eighty

971
00:51:42,440 --> 00:51:45,239
Speaker 2: five Bears destroy Patriots.

972
00:51:45,400 --> 00:51:47,120
Speaker 1: Oh my god, it's it's.

973
00:51:47,000 --> 00:51:50,240
Speaker 2: Just apparently a group watch a group of like eighty

974
00:51:50,320 --> 00:51:52,120
Speaker 2: five bears. I don't know, have you seen?

975
00:51:52,280 --> 00:51:52,560
Speaker 1: Have you?

976
00:51:52,640 --> 00:51:56,200
Speaker 2: Do you know of these specific bears them, there's eighty

977
00:51:56,239 --> 00:51:58,120
Speaker 2: five of them. Apparently one of them is called the

978
00:51:58,239 --> 00:52:01,400
Speaker 2: Refrigerator and then one is called Walter Peyton.

979
00:52:02,520 --> 00:52:04,680
Speaker 4: Yeah a sports team, yes.

980
00:52:04,560 --> 00:52:07,080
Speaker 2: Oh ship, No, okay, this is the this is the

981
00:52:07,120 --> 00:52:12,080
Speaker 2: super Bowl? Never mind, Okay, because I don't want to

982
00:52:12,080 --> 00:52:13,239
Speaker 2: look stupid, but I just.

983
00:52:13,719 --> 00:52:15,920
Speaker 4: Want to point out I think it would be amazing

984
00:52:16,160 --> 00:52:19,880
Speaker 4: one day to like work with athletes to see what

985
00:52:20,040 --> 00:52:22,880
Speaker 4: in fact they know about the animal they're representing, because

986
00:52:22,880 --> 00:52:26,240
Speaker 4: like mascots are always animals. It's like the timber wolves

987
00:52:26,360 --> 00:52:29,120
Speaker 4: or the Eagles and the bears, right, But it's like,

988
00:52:29,400 --> 00:52:32,880
Speaker 4: do these people like have any like knowledge of the animals.

989
00:52:33,160 --> 00:52:35,680
Speaker 4: I should be a consultant. I should just go clearly,

990
00:52:35,680 --> 00:52:36,120
Speaker 4: you don't.

991
00:52:36,160 --> 00:52:39,600
Speaker 1: Yeah, you can live in Chicago. The Bears the Cubs.

992
00:52:39,280 --> 00:52:42,440
Speaker 4: Do a little science communication because everyone comes to a

993
00:52:42,480 --> 00:52:46,200
Speaker 4: football game for science, you know, perfect fit.

994
00:52:46,719 --> 00:52:49,759
Speaker 1: Yeah, absolutely. Okay, So I thought you were going to

995
00:52:49,800 --> 00:52:52,320
Speaker 1: say it would be fun to one day set eighty

996
00:52:52,320 --> 00:52:55,920
Speaker 1: five Bears loose against eighty five self described patriots, because

997
00:52:55,960 --> 00:53:04,600
Speaker 1: that would be have similar results. Yeah, eighty five faral hogs. Yeah, gosh,

998
00:53:05,280 --> 00:53:08,440
Speaker 1: do you think the Christmas episode of the Bear needed

999
00:53:08,480 --> 00:53:10,680
Speaker 1: to be a full hour? Oh?

1000
00:53:10,719 --> 00:53:12,000
Speaker 4: I haven't seen the Bear?

1001
00:53:12,080 --> 00:53:14,040
Speaker 1: Oh okay, ok wa.

1002
00:53:13,960 --> 00:53:16,120
Speaker 4: Wait, this is what I wanted to say before, when

1003
00:53:16,160 --> 00:53:19,359
Speaker 4: I was like, I don't want to offend anybody out there,

1004
00:53:19,480 --> 00:53:21,920
Speaker 4: because people send me bear stuff all day long, like

1005
00:53:22,200 --> 00:53:25,040
Speaker 4: mostly people that I'm friends with, like people my friends

1006
00:53:25,040 --> 00:53:28,040
Speaker 4: and family send me bear stuff constantly, Like for gifts.

1007
00:53:28,120 --> 00:53:32,759
Speaker 4: I'm always getting like bears as gifts, right, Like I

1008
00:53:32,800 --> 00:53:35,120
Speaker 4: want folks to know, like I care about bears so much,

1009
00:53:35,440 --> 00:53:40,000
Speaker 4: it is my life. But like after like five PM,

1010
00:53:40,239 --> 00:53:43,359
Speaker 4: like I care way less about what bears are doing.

1011
00:53:43,560 --> 00:53:46,920
Speaker 4: Like it's like it's like a nine to five and

1012
00:53:46,960 --> 00:53:49,040
Speaker 4: like maybe a little bit on the weekends, Like I

1013
00:53:49,120 --> 00:53:54,840
Speaker 4: can't be obsessed with bears constantly, Like I like, I can't,

1014
00:53:54,960 --> 00:53:56,600
Speaker 4: It's not my identity.

1015
00:53:56,880 --> 00:53:58,560
Speaker 1: So it sounds like we only have four and a

1016
00:53:58,600 --> 00:54:00,680
Speaker 1: half hours left to keep asking these questions.

1017
00:54:00,800 --> 00:54:03,840
Speaker 2: Yeah, okay, how about how about this though, considering the

1018
00:54:03,880 --> 00:54:06,640
Speaker 2: fact that you know, bears occupy you'r nine to five,

1019
00:54:06,840 --> 00:54:10,560
Speaker 2: what's something scientifically because you do have you know, you're

1020
00:54:10,600 --> 00:54:15,200
Speaker 2: around other learned scientists, what's like a scientific breakthrough that

1021
00:54:15,280 --> 00:54:18,160
Speaker 2: has caught your attention from you know, like, what's what's

1022
00:54:18,160 --> 00:54:19,239
Speaker 2: got you excited when.

1023
00:54:19,160 --> 00:54:22,120
Speaker 1: You're around these other scientists? Science in it up? Oh?

1024
00:54:22,320 --> 00:54:25,319
Speaker 4: Oh my gosh, I have so many friends doing so

1025
00:54:25,440 --> 00:54:29,640
Speaker 4: much work. I okay, here's something. Here's something like just

1026
00:54:29,680 --> 00:54:33,560
Speaker 4: as a brief departure from bears, Like, wolves are doing

1027
00:54:33,640 --> 00:54:36,640
Speaker 4: some amazing stuff and I'm friends with some of the

1028
00:54:36,680 --> 00:54:41,160
Speaker 4: researchers who are studying the wolves that are coming into California.

1029
00:54:41,200 --> 00:54:43,960
Speaker 4: So like the state of California hasn't had wolves in

1030
00:54:44,280 --> 00:54:46,680
Speaker 4: one hundred years or something like that, or maybe over

1031
00:54:46,680 --> 00:54:49,960
Speaker 4: one hundred years, and wolf conservation has been going on

1032
00:54:50,000 --> 00:54:53,960
Speaker 4: in Oregon, and naturally, like without anyone helping or tempting them,

1033
00:54:54,080 --> 00:54:56,319
Speaker 4: they are coming into California and some of them are

1034
00:54:56,400 --> 00:54:59,480
Speaker 4: traveling down south. We had a wolf two years ago

1035
00:54:59,480 --> 00:55:03,120
Speaker 4: that made it all all the way to La County, Wow,

1036
00:55:03,200 --> 00:55:06,440
Speaker 4: from Oregon. That went on as he had a he

1037
00:55:06,480 --> 00:55:08,840
Speaker 4: had a GPS collar on, and then it died like

1038
00:55:08,880 --> 00:55:11,799
Speaker 4: around the central coast. And unfortunately, the reason we know

1039
00:55:12,040 --> 00:55:14,120
Speaker 4: he got so far was because he was hit by

1040
00:55:14,160 --> 00:55:19,600
Speaker 4: a car down at l hit by a car after

1041
00:55:19,640 --> 00:55:24,640
Speaker 4: that huge journey, But it looks like wolves are repopulating

1042
00:55:24,960 --> 00:55:27,320
Speaker 4: where they used to live in California on their own.

1043
00:55:27,520 --> 00:55:30,000
Speaker 4: Conservation has done like a little bit in Oregon, but

1044
00:55:30,160 --> 00:55:32,920
Speaker 4: not a lot in California. And it's a powerful story

1045
00:55:32,960 --> 00:55:37,960
Speaker 4: to me because it's this like triumph and perseverance and

1046
00:55:38,040 --> 00:55:41,719
Speaker 4: like you know, a reclamation of like land right that

1047
00:55:41,920 --> 00:55:44,840
Speaker 4: was once theirs that they were literally killed off of.

1048
00:55:44,880 --> 00:55:47,080
Speaker 4: It's not like people removed them and took them somewhere else.

1049
00:55:47,120 --> 00:55:51,200
Speaker 4: They were shot to death and killed and they're coming back.

1050
00:55:51,120 --> 00:55:52,760
Speaker 1: Figured the spot.

1051
00:55:52,960 --> 00:55:56,359
Speaker 4: This is coming back, Yeah, And you know they're not

1052
00:55:56,360 --> 00:55:58,279
Speaker 4: going to be again. They're not going to be like

1053
00:55:58,920 --> 00:56:02,920
Speaker 4: in your backyard, but they're gonna be in these forests

1054
00:56:03,000 --> 00:56:05,239
Speaker 4: and in these mountains and in these landscapes where they

1055
00:56:05,280 --> 00:56:08,040
Speaker 4: used to once live and to me, that's just so special.

1056
00:56:08,120 --> 00:56:10,400
Speaker 4: So I'm following that closely. And there's some colleagues of

1057
00:56:10,440 --> 00:56:14,279
Speaker 4: mine here in the California kind of academic space that

1058
00:56:14,360 --> 00:56:16,120
Speaker 4: are doing that work and I'm a big fan.

1059
00:56:16,560 --> 00:56:20,640
Speaker 1: That's cool. Do you have a favorite real bear? Like,

1060
00:56:20,760 --> 00:56:25,359
Speaker 1: is there are they to a five guy girl out

1061
00:56:25,360 --> 00:56:27,719
Speaker 1: there who you're just like every time I see their

1062
00:56:27,760 --> 00:56:31,360
Speaker 1: tracks or their leavings. Yeah, just like doing something cool

1063
00:56:31,400 --> 00:56:32,239
Speaker 1: with being a bear.

1064
00:56:32,680 --> 00:56:35,759
Speaker 4: Yeah, well, like I'm basic, Like this is how I'm

1065
00:56:35,920 --> 00:56:38,800
Speaker 4: like basic. I don't know, are we allowed to curse

1066
00:56:38,840 --> 00:56:41,000
Speaker 4: on the show? Yeah, okay, so this is where I'm

1067
00:56:41,040 --> 00:56:44,480
Speaker 4: like a basic bear bitch right. It's like there's a

1068
00:56:44,520 --> 00:56:48,080
Speaker 4: bear called three ninety nine and she's the famous bear.

1069
00:56:48,160 --> 00:56:51,600
Speaker 4: Like if you know of individual bears in America, then

1070
00:56:51,640 --> 00:56:53,560
Speaker 4: you know who three ninety nine is. If you've never

1071
00:56:53,640 --> 00:56:56,319
Speaker 4: thought of this before, I suggest you look up Bear

1072
00:56:56,440 --> 00:56:59,920
Speaker 4: three ninety nine. She lives in the Tetons in Wyoming,

1073
00:57:00,680 --> 00:57:04,640
Speaker 4: and she's super old. She's fabulous. She's super old, but

1074
00:57:04,680 --> 00:57:07,680
Speaker 4: she keeps having litters of cubs and people keep waiting

1075
00:57:07,719 --> 00:57:09,920
Speaker 4: for her to die, but she keeps showing up with

1076
00:57:10,200 --> 00:57:14,040
Speaker 4: babies and she's just like this incredible mom she's given

1077
00:57:14,080 --> 00:57:15,920
Speaker 4: birth to. She's a grizzly bear, I should say, so

1078
00:57:15,960 --> 00:57:18,920
Speaker 4: it is also extra special. Grizzly bears are an endangered species.

1079
00:57:19,200 --> 00:57:21,720
Speaker 4: So she's a grizzly bear. She's lived in Wyoming for many,

1080
00:57:21,800 --> 00:57:24,560
Speaker 4: many years. Three ninety nine. She just keeps having babies, honey, Like,

1081
00:57:24,600 --> 00:57:29,919
Speaker 4: she is fertile and fabulous and super old. So she's

1082
00:57:29,960 --> 00:57:32,560
Speaker 4: my favorite. And if anyone has a favorite bear out there,

1083
00:57:32,600 --> 00:57:34,280
Speaker 4: it's probably three ninety nine.

1084
00:57:34,720 --> 00:57:36,400
Speaker 1: That's so wild.

1085
00:57:36,840 --> 00:57:39,960
Speaker 2: There's even an there's an ig account called grizzly Bear

1086
00:57:40,040 --> 00:57:41,240
Speaker 2: three nulous.

1087
00:57:41,320 --> 00:57:44,120
Speaker 4: I am telling you, like fabulous, like get into three.

1088
00:57:44,120 --> 00:57:46,560
Speaker 2: Ninety nine, okay, because yeah, out here everybody was all

1089
00:57:46,560 --> 00:57:48,680
Speaker 2: about Pete twenty two, you know what I mean, which

1090
00:57:48,680 --> 00:57:49,760
Speaker 2: is nan.

1091
00:57:49,960 --> 00:57:52,520
Speaker 4: Like he was wonderful. May he rest in peace?

1092
00:57:53,160 --> 00:57:56,280
Speaker 2: Yeah, so now we can shift our focus to three

1093
00:57:55,800 --> 00:57:56,959
Speaker 2: ninety nine.

1094
00:57:57,320 --> 00:57:58,439
Speaker 1: Yeah, do we want.

1095
00:57:58,360 --> 00:58:01,000
Speaker 2: To probably ask one of our probably like more serious

1096
00:58:01,080 --> 00:58:02,320
Speaker 2: questions before you sign off here?

1097
00:58:02,400 --> 00:58:05,160
Speaker 1: Yeah? You do? You have one that you're trying to

1098
00:58:05,720 --> 00:58:08,000
Speaker 1: get in there? Okay, I figure while we have you here,

1099
00:58:08,560 --> 00:58:11,120
Speaker 1: doctor Ray, like, what's like the worst dump you've ever

1100
00:58:11,160 --> 00:58:14,840
Speaker 1: seen an animal? Do poop? Yeah?

1101
00:58:14,920 --> 00:58:18,200
Speaker 4: Oh, I spend so much time with animal poop right

1102
00:58:18,280 --> 00:58:22,000
Speaker 4: right through it with my hands.

1103
00:58:21,400 --> 00:58:25,400
Speaker 2: Like Doctor Grant and Jurassic Park see meant to be

1104
00:58:25,880 --> 00:58:28,120
Speaker 2: Mexically shout out for that synchronicity.

1105
00:58:28,160 --> 00:58:30,200
Speaker 1: There you go, Although it was Laura Darren who really

1106
00:58:30,280 --> 00:58:33,320
Speaker 1: dug went up to the hilt, up to the arm,

1107
00:58:33,520 --> 00:58:35,200
Speaker 1: up to the shoulder like.

1108
00:58:35,120 --> 00:58:38,360
Speaker 4: That glove on. See Laura Darren, if you're listening to this,

1109
00:58:38,520 --> 00:58:42,320
Speaker 4: I'm your neighbor. We live close to each other. Come

1110
00:58:42,440 --> 00:58:43,560
Speaker 4: find me. Let's talk.

1111
00:58:43,840 --> 00:58:46,680
Speaker 1: Oh yeah, let's talk about sticking our whole arm into

1112
00:58:46,800 --> 00:58:49,200
Speaker 1: big put talk about how I will never not be

1113
00:58:49,480 --> 00:58:53,560
Speaker 1: rich from big little eyes.

1114
00:58:55,400 --> 00:59:00,720
Speaker 4: So okay, So I just sent a whole bunch of bear, mountain, lion,

1115
00:59:01,280 --> 00:59:04,560
Speaker 4: and bobcat poop off to a laboratory to getting analyzed

1116
00:59:04,560 --> 00:59:06,840
Speaker 4: to see what these animals are eating, right, Because a

1117
00:59:06,840 --> 00:59:09,400
Speaker 4: really good way to figure out like what the bears

1118
00:59:09,400 --> 00:59:11,440
Speaker 4: and the lines I'm sending or eating is to like

1119
00:59:11,960 --> 00:59:13,760
Speaker 4: look at what's in their poop. And if I can't

1120
00:59:13,800 --> 00:59:16,040
Speaker 4: tell you, send it to a lab and they tell you,

1121
00:59:16,600 --> 00:59:19,240
Speaker 4: like what's in it. So I'm actually like hoping to

1122
00:59:19,320 --> 00:59:23,480
Speaker 4: find some interesting information that, like my bears are eating

1123
00:59:24,080 --> 00:59:28,480
Speaker 4: like a lot of wild pigs or like deer or

1124
00:59:28,520 --> 00:59:31,880
Speaker 4: you know, like the big awesome stuff. So honestly, like

1125
00:59:31,960 --> 00:59:36,760
Speaker 4: I just A'm so desensitized to giant like piles of

1126
00:59:37,320 --> 00:59:42,160
Speaker 4: poop from the large animal. I also have a toddler

1127
00:59:42,400 --> 00:59:45,200
Speaker 4: at home, right, so it's like it's at work, it's

1128
00:59:45,240 --> 00:59:47,280
Speaker 4: at home, Like poop has become.

1129
00:59:47,000 --> 00:59:52,000
Speaker 2: My life, okay, but like what's the worst I'm sorry

1130
00:59:52,080 --> 00:59:54,840
Speaker 2: to get you like.

1131
00:59:54,840 --> 00:59:56,480
Speaker 1: Send it off to the lab with just like a

1132
00:59:57,040 --> 00:59:59,720
Speaker 1: nasty written next to it. Nasty.

1133
01:00:00,040 --> 01:00:02,160
Speaker 4: So the thing about bears again, there are like a

1134
01:00:02,160 --> 01:00:05,720
Speaker 4: lot like people. Maybe this is TMI, but like depending

1135
01:00:05,720 --> 01:00:08,360
Speaker 4: on what bears eat, it just shows up in their poop, right,

1136
01:00:08,400 --> 01:00:10,960
Speaker 4: So like bear poop can look super different. It could

1137
01:00:10,960 --> 01:00:15,680
Speaker 4: be like it could be full of like berry seeds, right,

1138
01:00:15,760 --> 01:00:17,520
Speaker 4: like just like totally full of seeds. You could get

1139
01:00:17,560 --> 01:00:19,800
Speaker 4: a big pile and it's like red in color because

1140
01:00:19,800 --> 01:00:21,320
Speaker 4: it's like they ate all these berries and there's all

1141
01:00:21,320 --> 01:00:24,240
Speaker 4: these seeds in it big pile. Or maybe a bear

1142
01:00:24,360 --> 01:00:26,520
Speaker 4: like went into a bee hive, right and like ate

1143
01:00:26,520 --> 01:00:28,400
Speaker 4: a whole bunch of honey and honeycomb, and then you're

1144
01:00:28,440 --> 01:00:30,040
Speaker 4: gonna get a big pile of poop that's like a

1145
01:00:30,160 --> 01:00:32,680
Speaker 4: darker color, and it has bees in it, like the

1146
01:00:32,800 --> 01:00:36,240
Speaker 4: actual insects are like dead in that they eat the

1147
01:00:36,240 --> 01:00:38,600
Speaker 4: bees and it like goes through their system and you'll

1148
01:00:38,600 --> 01:00:41,200
Speaker 4: get like little bee butts in the pile of poop.

1149
01:00:41,800 --> 01:00:45,000
Speaker 4: And then sometimes bears eat a lot of fish, right,

1150
01:00:45,040 --> 01:00:48,400
Speaker 4: Like let's say there's like a river or stream and

1151
01:00:48,440 --> 01:00:51,160
Speaker 4: it's fall and the salmon are spawning, and that's when

1152
01:00:51,200 --> 01:00:54,600
Speaker 4: it's super gross because it's just like this black, tarry

1153
01:00:54,880 --> 01:00:57,400
Speaker 4: poop and it has this like fishy smell and it's

1154
01:00:57,440 --> 01:01:00,360
Speaker 4: more liquidy, right, Like you'd think because it was protein,

1155
01:01:00,400 --> 01:01:02,720
Speaker 4: it would be firmer, but it's yeah, because I eat

1156
01:01:02,760 --> 01:01:04,800
Speaker 4: like the fat, like they eat like the brains of

1157
01:01:04,840 --> 01:01:06,520
Speaker 4: the fish and like the cakes. So it's all like

1158
01:01:06,680 --> 01:01:10,560
Speaker 4: lucy black. Like yeah, like gross, super gross.

1159
01:01:10,640 --> 01:01:12,600
Speaker 1: Okay, so the worst kind of poop is a bear

1160
01:01:12,640 --> 01:01:13,800
Speaker 1: that's been eating a bunch of fish.

1161
01:01:13,960 --> 01:01:18,040
Speaker 2: Yeah, all right, all right, yeah you're right, Jack. I

1162
01:01:18,520 --> 01:01:20,120
Speaker 2: was gonna say it was if they've been eating candy.

1163
01:01:20,200 --> 01:01:22,840
Speaker 2: Oh yeah, yeah, because that's kind of like me.

1164
01:01:23,040 --> 01:01:27,160
Speaker 1: Yeah, and the poops you find that in woods, Like

1165
01:01:27,200 --> 01:01:29,960
Speaker 1: people sometimes are like, does a bear poop in the woods?

1166
01:01:30,040 --> 01:01:33,400
Speaker 1: And I know the answer to that, And I don't

1167
01:01:33,480 --> 01:01:35,680
Speaker 1: quietly have a panic attack because I don't know the

1168
01:01:35,720 --> 01:01:38,200
Speaker 1: answer to that, and everybody else seems to. But just

1169
01:01:38,240 --> 01:01:42,920
Speaker 1: like in your profession, if you had to get bear bears,

1170
01:01:42,920 --> 01:01:43,680
Speaker 1: do pooping them with.

1171
01:01:43,880 --> 01:01:45,920
Speaker 4: Bears, poop wherever they are.

1172
01:01:47,120 --> 01:01:51,160
Speaker 1: Okay, good, that's so good. Have confirmed. I mean, I've

1173
01:01:51,200 --> 01:01:53,200
Speaker 1: always known that. I've always known that, and I was

1174
01:01:53,280 --> 01:01:55,520
Speaker 1: not just being falsely confident. Now you can say that

1175
01:01:55,520 --> 01:01:59,360
Speaker 1: to your kids with confidence. Jack. Finally, uh, doctor ray

1176
01:01:59,400 --> 01:02:02,280
Speaker 1: Win Grant, thank you so much for joining us, for

1177
01:02:02,320 --> 01:02:05,640
Speaker 1: putting up with us. My pleasure, What a pleasure? Where

1178
01:02:05,640 --> 01:02:08,360
Speaker 1: where can people find you? Follow you here? You see

1179
01:02:08,360 --> 01:02:09,480
Speaker 1: you all that good stuff?

1180
01:02:09,520 --> 01:02:12,600
Speaker 4: Oh follow me. I'll talk about bears amongst other things.

1181
01:02:13,280 --> 01:02:16,080
Speaker 4: I love a good social follow. So all my handles

1182
01:02:16,120 --> 01:02:18,880
Speaker 4: are the same at ray Win Grant. That's R A

1183
01:02:19,040 --> 01:02:21,680
Speaker 4: E W Y and N G R A n T.

1184
01:02:22,360 --> 01:02:25,240
Speaker 4: Check out my website. It's new or it will be

1185
01:02:25,320 --> 01:02:27,200
Speaker 4: new in like a week or two, so that's a

1186
01:02:27,280 --> 01:02:31,600
Speaker 4: raywind Grant dot com. And check out my podcast, Going

1187
01:02:31,680 --> 01:02:34,520
Speaker 4: Wild with Doctor ray Wind Grant. It's on PEP it's

1188
01:02:34,560 --> 01:02:37,360
Speaker 4: for PBS Nature. You can get it wherever you listen

1189
01:02:37,360 --> 01:02:39,680
Speaker 4: to podcasts, wherever, whatever app you use, that's where you

1190
01:02:39,680 --> 01:02:42,320
Speaker 4: can find it. And check out my new television show

1191
01:02:42,480 --> 01:02:47,480
Speaker 4: Wild Kingdom, which is on NBC every Saturday and streaming

1192
01:02:47,480 --> 01:02:49,320
Speaker 4: on Peacock every single Sunday.

1193
01:02:49,680 --> 01:02:53,080
Speaker 1: And I see I've heard of them. They're Yeah, they're

1194
01:02:53,080 --> 01:02:54,920
Speaker 1: one of the channel you know notable.

1195
01:02:55,120 --> 01:02:58,160
Speaker 4: Yeah, they have SNL and they have my show.

1196
01:02:58,280 --> 01:03:01,160
Speaker 1: So yeah, that's all you need. Yeah, And is there

1197
01:03:01,160 --> 01:03:03,880
Speaker 1: a work of media that you've been enjoying?

1198
01:03:04,520 --> 01:03:09,240
Speaker 4: Oh, really love my podcast at my TV show. But

1199
01:03:09,960 --> 01:03:11,600
Speaker 4: I will just say, I mean, like if you want

1200
01:03:11,600 --> 01:03:14,440
Speaker 4: to know, like who I am after hours, I have

1201
01:03:14,600 --> 01:03:17,840
Speaker 4: been loving this show on Netflix. My husband and I

1202
01:03:17,880 --> 01:03:21,640
Speaker 4: watch it like together, and maybe this is how I'm

1203
01:03:21,800 --> 01:03:24,600
Speaker 4: just like a bear that I'm constantly hungry. But it's

1204
01:03:24,600 --> 01:03:29,880
Speaker 4: called American Barbecue Showdown, And like, you never knew a

1205
01:03:29,920 --> 01:03:34,800
Speaker 4: show about meat like could be so entertaining. So like,

1206
01:03:34,960 --> 01:03:37,120
Speaker 4: my husband and I stay up late and we watch

1207
01:03:37,160 --> 01:03:39,720
Speaker 4: American Barbecue Showdown on Netflix, and that is a piece

1208
01:03:39,720 --> 01:03:42,120
Speaker 4: of media that I'm enjoying. So I guess I'm just

1209
01:03:42,120 --> 01:03:44,000
Speaker 4: just like a bear. I just can't get enough.

1210
01:03:44,320 --> 01:03:46,480
Speaker 1: There you go, amazing, Well, thank you so much for

1211
01:03:46,560 --> 01:03:49,120
Speaker 1: joining us. Miles. Where can people find you? Follow you?

1212
01:03:49,440 --> 01:03:51,240
Speaker 1: Work a media you've been enjoying.

1213
01:03:51,000 --> 01:03:53,600
Speaker 2: At Miles of Gray all over the place where you

1214
01:03:53,680 --> 01:03:57,320
Speaker 2: got them in the Angelist National Forest, looking for the

1215
01:03:57,360 --> 01:04:02,320
Speaker 2: grossest animal poops imaginable for my other Instagram at worst

1216
01:04:02,440 --> 01:04:05,720
Speaker 2: nature Poops. And then you can find us on our

1217
01:04:05,760 --> 01:04:10,000
Speaker 2: basketball podcast Miles and Jack got Mad Boosties, where just

1218
01:04:10,080 --> 01:04:12,640
Speaker 2: the preseason delivers. I don't know why people are getting

1219
01:04:12,720 --> 01:04:15,800
Speaker 2: mad that people look this great in preseason. We're seeing

1220
01:04:15,840 --> 01:04:20,680
Speaker 2: something really cool. There are people being like, calm down,

1221
01:04:20,680 --> 01:04:24,040
Speaker 2: it's preseason. It's like, I don't care. This is so fun.

1222
01:04:24,160 --> 01:04:27,520
Speaker 2: Freaking giants out here wind milling on us all and

1223
01:04:27,560 --> 01:04:29,280
Speaker 2: then you can find me on our night on My

1224
01:04:30,080 --> 01:04:32,959
Speaker 2: ninety Day Fiance podcast for twenty Day Fiance and also

1225
01:04:33,080 --> 01:04:34,840
Speaker 2: The Good Thief that's a true crime one, but it

1226
01:04:34,840 --> 01:04:37,760
Speaker 2: doesn't have any killing. It's only about kidnapping millionaires and.

1227
01:04:37,680 --> 01:04:39,640
Speaker 1: Giving them money to port people. Pretty cool.

1228
01:04:40,320 --> 01:04:44,280
Speaker 2: Let's see tweet I like is from ronyverir at ron

1229
01:04:44,480 --> 01:04:47,920
Speaker 2: ue r O n n u. I underscore tweeted Twitter

1230
01:04:47,960 --> 01:04:51,400
Speaker 2: ads in twenty twenty one. Try drinking a refreshing pepsi

1231
01:04:51,440 --> 01:04:54,360
Speaker 2: when you see a movie. Smiley face Twitter ads in

1232
01:04:54,400 --> 01:04:57,400
Speaker 2: twenty twenty three. My name is Mike the Ratman, and

1233
01:04:57,440 --> 01:04:58,720
Speaker 2: I discovered.

1234
01:04:58,200 --> 01:05:02,520
Speaker 1: The real pizza hut. It's so fucking true, so I

1235
01:05:02,680 --> 01:05:07,920
Speaker 1: just love to tone it out. Amazing tweet. I've been

1236
01:05:08,000 --> 01:05:10,880
Speaker 1: enjoying mert at Mert Century tweeted hitting a vape that's

1237
01:05:10,920 --> 01:05:13,200
Speaker 1: attached to a desk by one of those chains they

1238
01:05:13,200 --> 01:05:17,680
Speaker 1: have on the pens at the bank. You can find

1239
01:05:18,080 --> 01:05:20,400
Speaker 1: me on Twitter at Jack Underscore O'Brien. You can find

1240
01:05:20,440 --> 01:05:22,640
Speaker 1: us on Twitter at daily Zeikeist. We're at d daily

1241
01:05:22,680 --> 01:05:24,840
Speaker 1: Zeikeist on Instagram. We have a Facebook fan page on

1242
01:05:24,880 --> 01:05:28,360
Speaker 1: a website daily zeikeist dot com. We'll post our episodes

1243
01:05:28,360 --> 01:05:30,760
Speaker 1: and our footnotes. We're going link off to the information

1244
01:05:30,800 --> 01:05:33,080
Speaker 1: that we talked about in today's episode, as well as

1245
01:05:33,080 --> 01:05:35,000
Speaker 1: a song that we think you might enjoy. Miles, is

1246
01:05:35,000 --> 01:05:37,960
Speaker 1: there a song that you think the people might enjoy?

1247
01:05:38,360 --> 01:05:39,840
Speaker 1: I think you're gonna like this one.

1248
01:05:39,960 --> 01:05:43,920
Speaker 2: This is from a UK rapper in it names bliss

1249
01:05:44,000 --> 01:05:46,600
Speaker 2: N A M E, S B L I S s

1250
01:05:46,760 --> 01:05:48,920
Speaker 2: uh and a really cool I just first of all,

1251
01:05:48,920 --> 01:05:52,040
Speaker 2: I got attracted to. The track is called Iniesta Flow,

1252
01:05:52,120 --> 01:05:55,960
Speaker 2: obviously a reference to the great Spanish footballer on DRIs Iniesta,

1253
01:05:56,640 --> 01:05:57,560
Speaker 2: but the lyrics.

1254
01:05:57,280 --> 01:06:01,840
Speaker 1: Are great and sometimes hearing rap in that beautiful UK accent.

1255
01:06:02,240 --> 01:06:05,480
Speaker 2: This is like it's like an entirely new genre, but

1256
01:06:05,760 --> 01:06:08,680
Speaker 2: the beat on it is really dope too. So for

1257
01:06:08,720 --> 01:06:11,120
Speaker 2: you know, geriatric millennials of a certain age, you're gonna.

1258
01:06:10,920 --> 01:06:13,960
Speaker 1: Like this one. It's called any Stuff Through Amazing. Well,

1259
01:06:13,960 --> 01:06:15,760
Speaker 1: we will link off to that in the footnotes. The

1260
01:06:15,840 --> 01:06:18,440
Speaker 1: Daily is the production of iHeartRadio. For more podcasts from

1261
01:06:18,480 --> 01:06:21,680
Speaker 1: my Heart Radio, the iHeartRadio app, Apple podcast. Wherever you

1262
01:06:21,680 --> 01:06:23,280
Speaker 1: listen to your favorite shows, that's gonna do it for

1263
01:06:23,440 --> 01:06:26,240
Speaker 1: us this morning. We're back this afternoon to tell you

1264
01:06:26,280 --> 01:06:28,360
Speaker 1: what's trending and we will talk to you all then

1265
01:06:28,480 --> 01:06:29,800
Speaker 1: bit by bit