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Speaker 1: Welcome to the news show. On this week's episode, we're

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Speaker 1: covering new research on how Neanderthal's Neanderthals, if you want

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Speaker 1: to be more official, how Neanderthals got it on the

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Speaker 1: controversial Catalina Island. Dear Annihilation program. Is your wife or

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Speaker 1: daughter or you wearing illegally imported fake eyelashes made of

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Speaker 1: minkfurt are tattoos gonna be totally screwed in the future.

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Speaker 1: And just when you thought Colorado animal rights people couldn't

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Speaker 1: embarrass their state any more than they already have, they

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Speaker 1: do Bringing you this news, We've got me Stephen Ronella,

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Speaker 1: along with Giannis poutell Us, doctor Randall, William Spencer, Newheart

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Speaker 1: Brody Henderson. The show is broken into three segments, Our News,

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Speaker 1: your news, and the news. Starting us out with our news,

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Speaker 1: We've got Janis with no news.

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Speaker 2: Why is it known news?

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Speaker 1: Because you haven't caught a lion? How do you report

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Speaker 1: on that?

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Speaker 3: In this case, no news is not good news?

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Speaker 2: Hmm, I don't know. I'm always the optimist.

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Speaker 1: You know.

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Speaker 2: My dog and I are still getting out there on

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Speaker 2: plenty of nice hikes in the mountains, enjoining ourselves, practicing

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Speaker 2: what we're trying to do.

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Speaker 1: He's trying to put a positive spin on this.

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Speaker 3: Do you think if Mingus could talk, he'd say, yeah,

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Speaker 3: this is fun.

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Speaker 1: Oh yeah, you think the dog isn't bummed that you

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Speaker 1: guys haven't caught one yet this year.

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Speaker 2: I don't know if he knows. I have no idea

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Speaker 2: of sort of what his sense of time is.

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Speaker 1: I venture to guess if the dog doesn't think of

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Speaker 1: it as being that he's in this season and then

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Speaker 1: there'll be another season next year.

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Speaker 2: And I don't know that he can he knows that

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Speaker 2: it's been a long time he saw a lion.

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Speaker 4: But I would venture to guess that if you had

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Speaker 4: two bowls of kibble and you could metaphorically put chasing

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Speaker 4: a lion and catching it into one bowl and then

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Speaker 4: just sort of aimlessly chasing sense to the woods and

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Speaker 4: the other bowl and never catching the line, I think

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Speaker 4: you would go for that bowl first.

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Speaker 2: He would, I think.

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Speaker 1: So, I mean, you don't know what mental trip he's on.

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Speaker 2: No, he could.

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Speaker 1: Be like just a real process or anything. He could

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Speaker 1: be like when he's laying there sleep and you think like, oh,

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Speaker 1: look at him sleeping, he could be there being like

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Speaker 1: I'm a loser. I always knew, you know, I came

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Speaker 1: from the kennel. I came from the dog pound. I'll

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Speaker 1: never live it down.

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Speaker 3: Or it could be the opposite.

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Speaker 1: One's owner abandoned me.

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Speaker 3: When he's on a line, he could be like, kind

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Speaker 3: of hate this, but I know he likes.

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Speaker 4: Or he's like he's like, if we caught one two

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Speaker 4: months ago, I wouldn't be the best shape of my

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Speaker 4: life right now.

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Speaker 1: Or he's like, I don't see the point in harass

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Speaker 1: in these poor things. I'm not gonna chase it up

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Speaker 1: a tree.

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Speaker 5: Oh rebelling m Maybe he's disappointed in you, Yanni.

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Speaker 1: What do you think about this?

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Speaker 2: N That could be too uh, you know, it's been

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Speaker 2: it's been humbling, That's what I think about it. Because

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Speaker 2: he's five this year, so really we've been hard at

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Speaker 2: it for this would probably be the fourth year, right,

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Speaker 2: So we've had three years. One of those years was

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Speaker 2: cut very short by that accident that we had together

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Speaker 2: with Mangus. So really he had like two good years.

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Speaker 2: And in those two good years, he had a year

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Speaker 2: where he caught like sixteen lions, and then a thirteen year,

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Speaker 2: a thirteen lion year. So to go now to this

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Speaker 2: year to have none, it's like, oh, were those flukes?

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Speaker 1: No, I don't think sixteen and thirteen that doesn't You

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Speaker 1: don't luck, That's not like if it was like two

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Speaker 1: and one, yeah, y yeah, and zero, I'd be like, well,

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Speaker 1: maybe zero is normal, but sixteen thirteen zero something happened.

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Speaker 3: Yeah, the weather happens.

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Speaker 5: Are you blaming the snow? Is that the problem?

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Speaker 2: For sure? But I've also just had a string of

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Speaker 2: bad luck where on the good snow days, we've found

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Speaker 2: tracks and one day the tracks literally filled in with

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Speaker 2: snow in front of our eyes, like it's just snowing

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Speaker 2: so hard. Multiple days, I've had tracks that just took

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Speaker 2: a left when they should have kept going right, and

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Speaker 2: they went on to private land. So I just called

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Speaker 2: mangus back. One day, I felt like we were within

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Speaker 2: hundreds of yards less than a thousand yards of pair

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Speaker 2: of lions, and it literally was getting dark on us.

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Speaker 2: I'm like, ah, you just gotta at some point, you

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Speaker 2: just got to call it because it's getting you know,

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Speaker 2: it gets dangerous when he gets dark, right, I don't

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Speaker 2: want to leave him out all night long. So there's

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Speaker 2: been a string of that kind of stuff also, But

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Speaker 2: the fact that Yeah, we've had like the worst snow

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Speaker 2: winter in a long time. It's definitely played into it.

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Speaker 1: Understood, Thank you, honest, you're welcome.

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Speaker 4: How many numbers of days in the field to it?

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Speaker 2: You know, I wish I had.

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Speaker 1: I just had a burning question.

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Speaker 2: No, that's a good question, because I feel like I've

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Speaker 2: been hunting roughly the same amount.

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Speaker 4: Oh it's even more between the you know.

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Speaker 2: Over the last four or five years.

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Speaker 6: Uh.

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Speaker 2: But yeah, I don't have a number for you, but

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Speaker 2: if I had to guess, we've been out maybe twenty days.

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Speaker 2: But you know, I've talked about this before. I think

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Speaker 2: I talked about this on a previous podcast. The one

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Speaker 2: silver lining of this year is not catching anything. We

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Speaker 2: caught a bobcat oh yeah, which I know you're real

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Speaker 2: frustrated about that, but catching release, catch and released about

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Speaker 2: half I know. But that's huge for me as a

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Speaker 2: as a hound owner.

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Speaker 1: Oh that's a triumph.

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Speaker 2: Yeah, for him be able to do that all by himself,

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Speaker 2: it was. It was a big day. So all all

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Speaker 2: is not lost. Like, if that's the only thing that

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Speaker 2: happens this this hound season, it'll be a pretty good

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Speaker 2: season because we accomplished that one thing.

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Speaker 1: Yeah, I would just say you caught one and leave

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Speaker 1: it at that.

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Speaker 2: One cat, one cat, one cat.

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Speaker 1: Did you get your cats? Yep?

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Speaker 2: Yeah. But I mean if you talk to like our

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Speaker 2: good buddy Jake Gribb, he'll tell you that that one

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Speaker 2: Bobcat is worth ten to twenty lines.

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Speaker 1: So then you say that, say ten to twenty.

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Speaker 4: Then you're right on You're right on average here.

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Speaker 2: Yeah, it's not over for you yet.

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Speaker 3: Anyway, you got one good time another.

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Speaker 2: Yeah, I got a big I got a big.

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Speaker 1: Month, big hot. You get big hot, snowless month, seventy

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Speaker 1: degrees next week, they're saying it's coming.

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Speaker 5: I can't believe the conversion rate is ten to twenty

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Speaker 5: mountain lions for one bombcat.

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Speaker 1: I don't believe that. I think it's an exaggerate.

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Speaker 2: It is so hard. Many people, many people literally will

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Speaker 2: not cut loose on a Bobcat track because they're like,

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Speaker 2: it's not worth my time. We're not gonna catch it.

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Speaker 2: We're just gonna end up on this long chase and

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Speaker 2: end up in a pile of rocks, and I won't

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Speaker 2: get to see a Bobcat. Maybe it's even.

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Speaker 1: Hot ground mountain.

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Speaker 2: Yeah, I mean, it's so special that maybe what.

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Speaker 3: I think it's gonna happen with this Steve.

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Speaker 2: It's so special. I would consider by getting a tattoo

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Speaker 2: to debt, to honor believe the word I'm looking for memorialized.

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Speaker 1: Yeah, memorialized. I would have it to be a tattoo,

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Speaker 1: no tattoo, and be like, this blank spot on my

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Speaker 1: skin is the year nothing happened.

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Speaker 3: No, he should get a lion tattoo to be like,

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Speaker 3: oh that's what they look didn't you just do.

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Speaker 7: An indefensible loss, Steve where people should memorialize places where

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Speaker 7: things didn't happen.

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Speaker 1: Well, yeah, I did one where where you would put

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Speaker 1: signs where people almost got killed.

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Speaker 2: Yeah, that's good.

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Speaker 1: Uh. On the subject tattoos, the radio Live finale, a

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Speaker 1: tattoo artist came in and did he in the office.

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Speaker 1: He did thirteen tattoos that day. Oh wow, Rody got

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Speaker 1: his first tattoo ever, which my wife thought was cool.

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Speaker 1: When he gets all done, when he gets all done,

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Speaker 1: this is my news here. He gets all done, and

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Speaker 1: me and him get the bs and and I'm like, hey,

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Speaker 1: act like you're giving me one. Get it all set up,

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Speaker 1: act like you're giving me one. And I'm gonna send

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Speaker 1: it to. We have a family group text chat called

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Speaker 1: the Free Trappers. So I'm like, act like you're giving

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Speaker 1: me one, and I'm gonna send it to my family

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Speaker 1: and be like. I finally broke down. I can't believe

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Speaker 1: I did it. I got a tattoo. I send it

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Speaker 1: no reply. My little ones later told me they knew

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Speaker 1: it wasn't true. My wife had already talked to Brody,

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Speaker 1: so she knew it wasn't true. My fifteen year old

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Speaker 1: going on sixteen, this is why I know that tattoos

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Speaker 1: are in trouble. The tattoo industry is in trouble. Okay,

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Speaker 1: fifteen year old, He says, that is so blank, I

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Speaker 1: can't say what. He says he'd get in trouble to

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Speaker 1: his mom. Later, he so he thinks it's true. Later

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Speaker 1: he says to me, dude, don't ever comment on my

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Speaker 1: hair cut again, Like coming from a guy with a

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Speaker 1: tattoo and their mind like and him and his buddy's minds.

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Speaker 1: I gather it is the dorkiest thing a person could do.

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Speaker 1: Not rebellious, not rebellious.

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Speaker 8: It's like, oh my god, times have changed, Oh my god,

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Speaker 8: I don't think so tattoos have been.

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Speaker 1: I thought, here's why I think that his social circle

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Speaker 1: is interesting. They have a foot in two worlds. He's

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Speaker 1: been brought up around all kinds of redneck stuff, knows

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Speaker 1: all kinds of rednecks, right, he just went and pulled

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Speaker 1: calves at his buddy's ranch. But he also knows all

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Speaker 1: about rich people. He knows about like rich urban people

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Speaker 1: and ski people. So here's this kind of interesting mix

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Speaker 1: of redneck stuff and rich people stuff. And from either

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Speaker 1: side of that, he's not getting tattoo cool factor from

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Speaker 1: either side. So I just am worried about the tattoo market.

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Speaker 3: I'm not because my kid said I want to get

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Speaker 3: the same one as you. I was wondering if you

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Speaker 3: had your argument.

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Speaker 2: I'm looking at data right now.

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Speaker 1: Spencer went got his.

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Speaker 2: Trump the America the Beautiful Past, and Phil has data

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Speaker 2: on this right now here.

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Speaker 7: I am looking at a percentage of Americans with tattoos

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Speaker 7: over time, and the year nineteen thirty six, it looks

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Speaker 7: like ten percent of the American population had tattoos. If

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Speaker 7: we jump and then two thousand and three, that's a

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Speaker 7: long jump. It was sixteen percent. But then we have

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Speaker 7: from two thousand and three to twenty twelve, twenty one

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Speaker 7: percent of Americans had tattoos. From twenty twelve to twenty fifteen,

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Speaker 7: that number jump from twenty one to twenty nine, and

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Speaker 7: from twenty fifteen to twenty twenty three that number jumped

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Speaker 7: to thirty two percent.

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Speaker 2: Boo, it's been a steady increase.

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Speaker 6: He's looking over the clever.

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Speaker 1: Okay, that's why Phil should do a better job of listening.

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Speaker 7: So you're so your argument is like, right now, sure

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Speaker 7: the future Okay, I'm just saying the trends disagree.

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Speaker 1: We're in the tattoo. Our trend doesn't show the future

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Speaker 1: because it's not no much I got. I run the future.

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Speaker 4: That's why I'm telling you he's forecasting a sharp decline

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Speaker 4: based on I.

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Speaker 1: Have detected an attitudinal shift. I have detected an attitudinal shift,

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Speaker 1: and I looked at data, and so if I'm going

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Speaker 1: to go on to a prediction market, I want to

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Speaker 1: make a bet that in twenty years there has been

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Speaker 1: a cataclysmic drop off in tattoo rates. Because I've had

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Speaker 1: a glimpse into the future by talking to my kids' buddies.

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Speaker 7: Yeah, you could be very very right based on what

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Speaker 7: they're doing in the alcohol industry and how they don't

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Speaker 7: like sex and movies.

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Speaker 1: Yeah, yeah, a bunch of breeds. Yeah, Spencer got a

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Speaker 1: new pass from explain this. This is very interesting. This

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Speaker 1: is legit news.

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Speaker 5: I went to Yellowstone a couple of weekends ago, and

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Speaker 5: my winter trip there is usually when we get our

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Speaker 5: new past for the year. It's called the America the

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Speaker 5: Beautiful Pass.

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Speaker 1: How long has that existed?

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Speaker 5: Since two thousand and four, I believe some version of

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Speaker 5: it has existed. Phil's got them pulled up the America

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Speaker 5: the Beautiful Pass. It's eighty dollars. It grants you entry

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Speaker 5: to national parks, national wildlife refugees. Also covers your day

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Speaker 5: use fees if you're in National forest Grasslands blm Army

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Speaker 5: corps Land a place where you're required to pay a

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Speaker 5: day use fee. You typically don't need to you if.

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Speaker 3: You have, it's like a good deal if you do

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Speaker 3: these things a lot.

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Speaker 1: Right, certainly, Yeah, yep.

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Speaker 5: But I think although there's like so many places it

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Speaker 5: gives you access to, these are primarily just using national parks.

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Speaker 5: That's what people buy them for us to get in

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Speaker 5: and out of national parks for a year, and and

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Speaker 5: you and the missus buy one every year every year

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Speaker 5: since we moved to Montana. So this is our seventh

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Speaker 5: pass that we've had. I've got three of them here.

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Speaker 1: Now, why didn't you buy it in South Dakota?

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Speaker 5: Just didn't attend national parks the same way we do now,

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Speaker 5: didn't live as close to the Rushmore.

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Speaker 1: Yeah, but that'd get you into Rushmore.

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Speaker 5: It would get you into Rushmore.

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Speaker 3: Yeah, actually rush.

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Speaker 5: So the America the Beautiful Pass. It's like the size

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Speaker 5: of your credit card or driver's license. It's a laminated card.

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Speaker 5: Traditionally these have a photo on them of wildlife for landscape,

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Speaker 5: and I've got past examples here that you can see.

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Speaker 1: And you go back to that that shot you had.

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Speaker 5: Up and that's that's showing you like the last decade

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Speaker 5: of that's a roseated spoon bill. That is a yes

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Speaker 5: correct from the Everglades.

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Speaker 1: So what year is that? That is last year national

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Speaker 1: park roseated spoon bilt.

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Speaker 5: And then what year is this twenty twenty four? That's

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Speaker 5: an Eastern collared.

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Speaker 1: Lizard, Okay lizard twenty twenty four past.

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Speaker 5: Twenty twenty three. It was a landscape picture from King's

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Speaker 5: Canyon National Park.

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Speaker 1: So that's you get an idea of what they look

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Speaker 1: like what park would that be from?

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Speaker 5: I don't know, Denali, the Arctic. I also don't think

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Speaker 5: it has to be in a national it's just like

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Speaker 5: federal land. And so you did say it's gotta be

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Speaker 5: a it's it's like by law since two thousand and four,

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Speaker 5: it's been a federal law that the way these are

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Speaker 5: chosen is there is a picture contest done by what

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Speaker 5: is it the National Parks Foundation, and the winning photo

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Speaker 5: from that is on the pass for the following year.

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Speaker 5: So this year you can see what it was supposed

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Speaker 5: to be. It was supposed to be Glacier National Park

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Speaker 5: in Montana. That was what the winning photo was from

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Speaker 5: last year. But the the Trump administration has changed this.

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Speaker 5: They they are breaking this two thousand and four federal

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Speaker 5: law and instead it is a picture of George Washington

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Speaker 5: and Donald Trump on the pass.

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Speaker 1: And and this this has made some folks very mad.

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Speaker 1: It's made folks very mad. He doesn't look like he's

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Speaker 1: at the park.

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Speaker 5: No, it has.

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Speaker 1: You wouldn't look at that and think, you know why,

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Speaker 1: you know, it looks like it looks like he got

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Speaker 1: to the outhouse at the park. He got to the

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Speaker 1: and it was and it's and and there's and it's overflowed.

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Speaker 1: And he opened the door and he's like someone's gonna pay.

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Speaker 5: Yes, And you can see these these photos on our

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Speaker 5: YouTube channel.

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Speaker 1: And I mean, in all fair and this is two

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Speaker 1: hundred and fiftieth first president, current president, two hundred fift

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Speaker 1: years of presidents. I think that's what this is going

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Speaker 1: for here.

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Speaker 5: Yes, I mean he made a lot of changes with

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Speaker 5: National park related stuff this year that is supposed to

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Speaker 5: be more patriotic. For example, he got rid of Juneteenth

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Speaker 5: and MLK Day as free days, and he's made Flag Day,

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Speaker 5: which is his birthday, and then President's Days as free

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Speaker 5: days instead. And this is all patriotic. Team He's also

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Speaker 5: this is a good one. He bumped up the fee

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Speaker 5: for non residents if you're from Canada, if you're from Italy.

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Speaker 1: I support that, and I agree that's I think that's

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Speaker 1: the other stuff I don't get.

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Speaker 5: That's a North American thing that we're like, if you

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Speaker 5: want to go recreate in Colorado as a non resident,

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Speaker 5: you pay a higher fee.

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Speaker 1: It's like part of it.

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Speaker 4: They've also removed like indigenous perspectives from that's.

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Speaker 5: Yeah, totally different.

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Speaker 3: Happens if you put a piece of tape over Trump's Yeah.

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Speaker 5: So within within days of the new year, when these

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Speaker 5: went into effect, the National Park Service had to release

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Speaker 5: a statement saying that your pass will be voided if

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Speaker 5: you alter it by putting a sticker over it, by drawing.

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Speaker 1: On it, by Has that always been true?

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Speaker 5: Yes, but I don't think anyone's ever tested. It hasn't

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Speaker 5: been a problem. But it's always been It's always been true, yes.

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Speaker 5: And and like for example of how how much drama

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Speaker 5: this is made, there's an Etsy shop seller who has

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Speaker 5: started making stickers for these, and she said that she

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Speaker 5: would like give that money to public lands. For what

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Speaker 5: she would sell, it's a sticker that would go over

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Speaker 5: Trump's face. She made sixteen thousand dollars in the first month.

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Speaker 1: M just just doing this. I don't remember. I think

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Speaker 1: it's it's like a yeah, maybe Pika.

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Speaker 5: We've looked this up on trivia. You can say a

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Speaker 5: Pica or Pika who can anyway can go eat?

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Speaker 1: I can't. I We did this on we addressed that

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Speaker 1: on trivia. Okay, what what what's next year's Are they

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Speaker 1: going to revert next year's pass to the winner? If

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Speaker 1: the duck stamp you like the whole duck stamp competition. Yeah,

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Speaker 1: if all sudden the ut was like a duck with

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Speaker 1: like Trump's face on it. Yeah, and he's like, no, no, no,

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Speaker 1: that's the that's the duck stands. Yeah.

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Speaker 5: So the Trump administration has not been great to the

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Speaker 5: National Parks. You know, Doge cut a thousand employees last year.

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Speaker 5: They tried to slash the budget by thirty eight percent

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Speaker 5: this year. The Senate rejected that. So Trump not exactly

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Speaker 5: a mascot for the National Parks. I was trying to

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Speaker 5: think of an analogy. It would be like if we

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Speaker 5: had a meat eater radio Live listening pass and then

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Speaker 5: Steve put his face on it.

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Speaker 1: Yeah, I totally understand. That's what it would be like.

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Speaker 3: Or if you let Elon Musk take an axe.

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Speaker 1: To radio Live. Yeah.

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Speaker 3: And this this drama is gonna get bigger now.

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Speaker 5: The National Parks get forty percent of their visitation between

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Speaker 5: June and August. So there's a lot of folks who

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Speaker 5: are going to be buying their pass in a few months.

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Speaker 5: And it's already it's already been a big deal, but

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Speaker 5: it's it's going to become probably a bigger deal.

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Speaker 1: On a related note, someone just shared with me this

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Speaker 1: is this article is a little bit older, and I've

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Speaker 1: been kind of hanging on to it. Someone shared with

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Speaker 1: me an article, an op ed that came out and

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Speaker 1: there was a guest essay called maga Elites who live

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Speaker 1: on their phones are ruining the outdoors and at points

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Speaker 1: that's a hyperbolic headline, but what it points out is

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Speaker 1: we've kind of like we've moved away. We're currently moved

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Speaker 1: away from the old style of like outdoor republican. And

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Speaker 1: you know, like you think about the bushes. Were anglers right,

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Speaker 1: they would vacation at like Kenny Bumpport and go fishing. Anyways,

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Speaker 1: this article lays out this idea that that rather than

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Speaker 1: rather than trips to Wyoming to fly fish and stuff,

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Speaker 1: what we see out of the administration is golfing in Florida.

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Speaker 1: And this individual argues that there's been this like perspective

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Speaker 1: shift away from this like tradition of outdoor Republicans into

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Speaker 1: like indoor Republicans. The guy is a research so the

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Speaker 1: guy that wrote it. You should go go check it out.

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Speaker 1: Listener should check it out. It'll like it'll it'll do

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Speaker 1: one of two things. It'll either make you so mad

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Speaker 1: because you're disagreeing. You'll be like so mad, you'd be

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Speaker 1: mad that we mentioned it, or you'll be so happy

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Speaker 1: we mentioned it because it already aligns with what you think.

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Speaker 1: So you can go, no matter who you are, just

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Speaker 1: think about this. No matter who you are, you can

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Speaker 1: go read this and reinforce your opinions and be happi

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Speaker 1: or sad.

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Speaker 4: If you ever read something that everybody agrees on everybody,

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Speaker 4: it's probably not worth reading.

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Speaker 1: It'd be like reading the Park Pass. Yeah, that's a joke.

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Speaker 1: The guy that wrote it. You get a little suspicious

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Speaker 1: when you read what he does. So he Doctor Lezak

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Speaker 1: is a researcher at the University of Oxford and the

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Speaker 1: University of California, Berkeley who studies the politics of climate change.

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Speaker 1: So guess what his biases might be. Another piece of

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Speaker 1: news we got, we're doing this. We're doing a new

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Speaker 1: series called the time Machine. So every month we're taking

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Speaker 1: artwork like see this one here, this goes back to

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Speaker 1: the farthest. This is a time machine artwork of Clovis points,

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Speaker 1: archaeological drawings of Clovis points. That's this month, We're gonna

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Speaker 1: hit the Custer Battle, the Battle of the Greasy Grass

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Speaker 1: or the Battle of the Little Big Horn, depending on

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Speaker 1: what side you're on. Pittman Robertson Act. Every month you

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Speaker 1: can come check it out. T shirts, hoodies, time capsule,

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Speaker 1: we go back in time. That's the Clovis shirt right there.

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Speaker 1: They're all limited to run. Teas and hoodies. Find them

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Speaker 1: at the Meat Eater store website. Okay, moving on to corrections.

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Speaker 2: Corrections, Corrections.

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Speaker 1: That's from Fiddler around Them. This is our inaugural segment.

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Speaker 1: Inaugural segment of corrections where we have a correction of

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Speaker 1: the Weak contest sponsored by Takova's. So corrections are like this,

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Speaker 1: if you're sitting around like normally in today's political climate,

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Speaker 1: and I mean this is when I'm sticking it to

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Speaker 1: both sides on this, people just say stuff that's just

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Speaker 1: wrong and they don't and they know it's wrong. It's

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Speaker 1: like a flex to say stuff that's just wrong because

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Speaker 1: it's kind of like it's like I know it's wrong,

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Speaker 1: you know it's wrong, and now you're going to have

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Speaker 1: to live with it. But we try to invite corrections.

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Speaker 1: So if we say something that's screwed up, or or

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Speaker 1: we make a mistake or omit the truth or whatever.

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Speaker 1: We invite your corrections. We want your corrections so bad

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Speaker 1: about things we're wrong about that If you get the

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Speaker 1: correction of the week, you win a pair of Takova's boots.

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Speaker 1: You send yours to the meat Eater podcast at the

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Speaker 1: meeater dot com. We got three to choose from to

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Speaker 1: who wins the Dakova's Boots. Okay, Going in the future,

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Speaker 1: we'll only be accepting corrections from the news show. But

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Speaker 1: we're we're accepting corrections otherwise. Right now, episode eight thirty eight,

437
00:23:23,160 --> 00:23:27,160
Speaker 1: someone writes and this is his correction. Episode eight thirty eight,

438
00:23:27,200 --> 00:23:30,280
Speaker 1: Steve is talking about a Hen Turkey making bad calls

439
00:23:31,080 --> 00:23:38,560
Speaker 1: and uses the term on accident. The corrector goes on

440
00:23:38,680 --> 00:23:41,520
Speaker 1: to say, as a writer and someone who makes a

441
00:23:41,640 --> 00:23:43,960
Speaker 1: living speaking, he should know it.

442
00:23:44,119 --> 00:23:45,120
Speaker 2: Is by.

443
00:23:46,560 --> 00:23:51,720
Speaker 1: Accident. He goes on to say, fewer things annoy me

444
00:23:52,160 --> 00:23:57,359
Speaker 1: more than this. If he could please correct this going forward,

445
00:23:58,440 --> 00:24:02,560
Speaker 1: it would make my listening experience. It's much better you

446
00:24:02,600 --> 00:24:04,120
Speaker 1: don't do something on accident.

447
00:24:04,200 --> 00:24:05,840
Speaker 3: Are we voting at the ending?

448
00:24:06,520 --> 00:24:10,239
Speaker 2: I'm not voting for this guy, can I I mean,

449
00:24:10,320 --> 00:24:13,960
Speaker 2: maybe my grammar is off, but shouldn't those quotes be

450
00:24:15,200 --> 00:24:21,560
Speaker 2: outside of that? Was at his face, in.

451
00:24:21,640 --> 00:24:30,600
Speaker 1: His face, in your face, I got, Steve, I got

452
00:24:30,640 --> 00:24:33,000
Speaker 1: a little suggestion for you, learn how to put your

453
00:24:33,040 --> 00:24:34,439
Speaker 1: quotes in the right place. Buddy.

454
00:24:35,280 --> 00:24:38,320
Speaker 3: I think this guy's already lost a pair of boots.

455
00:24:39,520 --> 00:24:40,119
Speaker 2: He's out.

456
00:24:41,520 --> 00:24:42,200
Speaker 1: Close call.

457
00:24:42,560 --> 00:24:46,399
Speaker 2: But no, no, no, no, I'm sure that he placed

458
00:24:46,440 --> 00:24:48,560
Speaker 2: those periods there by accident.

459
00:24:51,720 --> 00:24:55,640
Speaker 6: So on accident. I'm looking this up and I see

460
00:24:55,680 --> 00:24:58,240
Speaker 6: that it's like colloquial, But I don't know. Is it

461
00:24:58,320 --> 00:24:59,879
Speaker 6: a grammar thing I've heard you.

462
00:25:00,040 --> 00:25:05,399
Speaker 1: Glocal off of me is wrong? Yeah? Yeah, But I

463
00:25:05,480 --> 00:25:07,840
Speaker 1: don't think he's gonna win because because he got it,

464
00:25:08,000 --> 00:25:11,680
Speaker 1: he got like back at them, back at them. Okay,

465
00:25:12,119 --> 00:25:15,760
Speaker 1: on mink coals and bad smells, here's a contender, here's

466
00:25:15,800 --> 00:25:22,359
Speaker 1: a real contender. He's referencing back to episode eight thirty eight. Okay,

467
00:25:23,440 --> 00:25:26,080
Speaker 1: around the thirty one minute mark. In the episode, Steve

468
00:25:26,280 --> 00:25:31,240
Speaker 1: referenced the two thy twenty coal of mink and Denmark

469
00:25:31,280 --> 00:25:35,040
Speaker 1: we were talking about. During the COVID pandemic, they found

470
00:25:35,080 --> 00:25:40,159
Speaker 1: out that mink were harbingers of COVID and they started

471
00:25:40,280 --> 00:25:44,159
Speaker 1: killing all ranch mink in Denver, in Denmark, and I

472
00:25:44,400 --> 00:25:47,960
Speaker 1: said that the mink all went to market. My understanding

473
00:25:48,200 --> 00:25:51,080
Speaker 1: was when I first heard about the cold, I thought

474
00:25:51,080 --> 00:25:54,119
Speaker 1: it would cause mink prices to skyrocket because there's no

475
00:25:54,240 --> 00:25:58,040
Speaker 1: more mink. But someone said the inverse was true. It

476
00:25:58,200 --> 00:26:01,320
Speaker 1: was a massive influx of mink pelts because they had

477
00:26:01,359 --> 00:26:04,280
Speaker 1: to go pelt all the mink, and so it flooded

478
00:26:04,320 --> 00:26:06,760
Speaker 1: the market with mink and tanked it. So I said

479
00:26:06,800 --> 00:26:11,040
Speaker 1: they were all pelted out. This guy says the coal

480
00:26:11,359 --> 00:26:15,280
Speaker 1: was so hasty and disorganized that it didn't give the

481
00:26:15,400 --> 00:26:22,080
Speaker 1: opportunity for many of the affected mink farmers to pelt out,

482
00:26:22,359 --> 00:26:25,480
Speaker 1: meaning to skin them all. Given that just before the

483
00:26:25,560 --> 00:26:28,560
Speaker 1: discussion of the mink coal there was a discussion of

484
00:26:28,640 --> 00:26:31,760
Speaker 1: various bad smells, you may also be interested in the

485
00:26:31,840 --> 00:26:35,520
Speaker 1: fact that the coal resulted in millions of mink being

486
00:26:35,720 --> 00:26:39,439
Speaker 1: buried in mass burial sites, and the fact that they

487
00:26:39,520 --> 00:26:42,800
Speaker 1: hadn't been skinned meant that some of them started to

488
00:26:42,960 --> 00:26:47,480
Speaker 1: decompose and bloat and push their way out of the ground,

489
00:26:48,520 --> 00:26:55,440
Speaker 1: which media dubbed zombie mink. I like that that was

490
00:26:55,480 --> 00:26:55,880
Speaker 1: from Doug.

491
00:26:56,040 --> 00:26:59,440
Speaker 4: That's a correction of a correction you received, right, because

492
00:26:59,480 --> 00:27:02,879
Speaker 4: your initial impression was that they wouldn't be skinned. Your

493
00:27:02,920 --> 00:27:06,399
Speaker 4: initial assumption, Yeah, but that was an internal Yeah, this

494
00:27:06,560 --> 00:27:07,920
Speaker 4: is that was a leg still action.

495
00:27:08,560 --> 00:27:11,399
Speaker 1: Now here is like a great correction that's going to

496
00:27:11,440 --> 00:27:17,720
Speaker 1: compete with the mink correction. Episode eight twenty nine, at

497
00:27:17,760 --> 00:27:23,160
Speaker 1: the fourteen minute mark, we're talking about this, okay, we're

498
00:27:23,160 --> 00:27:27,240
Speaker 1: talking about salmon leaving their natal spawning streams and going

499
00:27:27,359 --> 00:27:30,160
Speaker 1: back out to the ocean. Or were we talking about

500
00:27:30,200 --> 00:27:36,119
Speaker 1: one's coming up, coming up? Oh? Okay, pretty sure either way.

501
00:27:36,160 --> 00:27:40,000
Speaker 1: We're talking about fish loss at dams in the Columbia system.

502
00:27:40,520 --> 00:27:42,760
Speaker 3: Oh no, were we talking about smoke going out?

503
00:27:42,880 --> 00:27:46,520
Speaker 1: I think it's I think it's smoke going out. Yeah, okay,

504
00:27:46,760 --> 00:27:50,440
Speaker 1: And we're saying that they're losing that at every dam

505
00:27:51,240 --> 00:27:55,280
Speaker 1: these fish encounter. They're losing seven to fifteen percent of

506
00:27:55,400 --> 00:28:01,360
Speaker 1: the population at every dam. And all of his ignorance,

507
00:28:03,400 --> 00:28:08,160
Speaker 1: I say, I can't even do that math Brody does,

508
00:28:08,400 --> 00:28:13,080
Speaker 1: and he says that's over one hundred percent, him being dumb.

509
00:28:15,520 --> 00:28:19,200
Speaker 4: Jeez, Yeah, that's not how the math works.

510
00:28:19,280 --> 00:28:23,320
Speaker 1: Now the MathWorks. This guy writes in It's actually like this,

511
00:28:23,840 --> 00:28:27,359
Speaker 1: if two hundred thousand salmon attempt to make it past

512
00:28:27,440 --> 00:28:33,400
Speaker 1: the first dam with a fifteen percent mortality rate, there

513
00:28:33,440 --> 00:28:36,440
Speaker 1: will be one hundred and seventy thousand that make it

514
00:28:36,600 --> 00:28:41,600
Speaker 1: through to attempt the next dam. After damn number two,

515
00:28:42,120 --> 00:28:47,120
Speaker 1: at fifteen percent mortality rate, there are one hundred and

516
00:28:47,320 --> 00:28:52,160
Speaker 1: forty four thousand, five hundred smelt left. If you continue

517
00:28:52,280 --> 00:28:57,520
Speaker 1: this trend through all eight dams, you are left with

518
00:28:57,800 --> 00:29:02,960
Speaker 1: fifty four thousand, five hundred salmon. This is a total

519
00:29:03,080 --> 00:29:06,560
Speaker 1: loss of about seventy three percent at the high end.

520
00:29:07,440 --> 00:29:10,800
Speaker 1: If you use the seven percent mortality rate with this method,

521
00:29:11,920 --> 00:29:15,720
Speaker 1: you end up with one hundred and eleven thousand, nine

522
00:29:15,880 --> 00:29:24,200
Speaker 1: hundred fish after the eighth dam. So the total mortality

523
00:29:24,360 --> 00:29:29,720
Speaker 1: rate range is from forty four to seventy three percent,

524
00:29:30,080 --> 00:29:32,800
Speaker 1: not as what I did in my head, more than

525
00:29:32,920 --> 00:29:33,480
Speaker 1: all of them.

526
00:29:34,040 --> 00:29:37,200
Speaker 4: Yeah, this is this is probably going to get a

527
00:29:37,240 --> 00:29:39,760
Speaker 4: correction too. But it's like it's like the reverse of

528
00:29:39,880 --> 00:29:45,880
Speaker 4: compound interest, whereas if you have money invested, as it grows,

529
00:29:46,000 --> 00:29:49,480
Speaker 4: it grows more. As it shrinks, it shrinks less in

530
00:29:49,560 --> 00:29:54,680
Speaker 4: each iteration understood the way, Well that does.

531
00:29:54,840 --> 00:29:57,720
Speaker 3: Okay, you got a minor and math, you got a doctor.

532
00:29:57,800 --> 00:29:59,920
Speaker 4: I was actually just thinking we should, we should. It's

533
00:30:00,040 --> 00:30:03,920
Speaker 4: some point just have a podcast episode with a statistician

534
00:30:04,480 --> 00:30:08,240
Speaker 4: about draws and just probabilities. Probabilities for the for the

535
00:30:08,640 --> 00:30:11,240
Speaker 4: Joe Blow Outdoorsman. We can explain things like this, We

536
00:30:11,320 --> 00:30:12,120
Speaker 4: can explain.

537
00:30:11,880 --> 00:30:16,160
Speaker 1: Draws, you know, because that's another thing is there's a

538
00:30:16,200 --> 00:30:19,400
Speaker 1: lot of confusion about draw odds. That'd be a good

539
00:30:19,400 --> 00:30:20,760
Speaker 1: idea a hunter.

540
00:30:21,800 --> 00:30:23,800
Speaker 4: It might not be, it might it might not be

541
00:30:23,840 --> 00:30:26,400
Speaker 4: a two hour podcast, but it could be a fwop.

542
00:30:28,120 --> 00:30:31,520
Speaker 6: Please write in the media podcast at the mediator dot com.

543
00:30:31,680 --> 00:30:35,080
Speaker 1: I also need someone from the did you know that

544
00:30:35,200 --> 00:30:39,280
Speaker 1: there's a did you know that there's a discipline that

545
00:30:39,560 --> 00:30:48,360
Speaker 1: zoos have zoo swat teams? Okay, and there's like a

546
00:30:48,480 --> 00:30:52,360
Speaker 1: leading figure in the zoo swat team area, and she

547
00:30:52,560 --> 00:30:55,800
Speaker 1: made a YouTube video one time about her industry and

548
00:30:55,880 --> 00:31:01,360
Speaker 1: her training, tactical zoo keeper training. And in this video

549
00:31:01,440 --> 00:31:05,880
Speaker 1: they're like shooting shot shooting slug guns through woven wire fences.

550
00:31:06,600 --> 00:31:08,840
Speaker 1: She does her interview in front of a bear with

551
00:31:08,960 --> 00:31:11,040
Speaker 1: a bullet with a bulls eye on his brain.

552
00:31:11,800 --> 00:31:14,680
Speaker 3: Yeah, would you need to clarify what these swat teams do?

553
00:31:14,840 --> 00:31:19,040
Speaker 1: It's after people. It's for if monkeys get loose, the

554
00:31:19,200 --> 00:31:19,840
Speaker 1: lions get.

555
00:31:21,520 --> 00:31:21,920
Speaker 2: Or someone.

556
00:31:22,040 --> 00:31:24,520
Speaker 1: They had they had a kid fall into us into

557
00:31:24,680 --> 00:31:28,720
Speaker 1: a gorilla container and they killed the Gorilla was.

558
00:31:28,720 --> 00:31:30,520
Speaker 4: Who was that at Cincinnati and Natty.

559
00:31:30,760 --> 00:31:33,840
Speaker 1: So we reached out to people within this zoo swat

560
00:31:33,920 --> 00:31:37,080
Speaker 1: team community and they're like, no one will talk to you.

561
00:31:37,400 --> 00:31:41,320
Speaker 1: This is a very tight knit community. No one will speak.

562
00:31:41,800 --> 00:31:46,080
Speaker 1: If if X person won't speak, no one will speak.

563
00:31:47,440 --> 00:31:54,520
Speaker 1: But X person has spoken weirdly, but won't if you

564
00:31:54,640 --> 00:31:57,240
Speaker 1: are in the zoo keeper swap team business, we would

565
00:31:57,280 --> 00:31:59,000
Speaker 1: love to talk to you on the podcast.

566
00:32:00,680 --> 00:32:01,840
Speaker 2: That does sound like a good one.

567
00:32:02,000 --> 00:32:04,440
Speaker 1: Oh, it'd be a great one. Yeah, But they're like,

568
00:32:04,720 --> 00:32:07,520
Speaker 1: they don't want zoos have to have a zoo keeper

569
00:32:07,600 --> 00:32:11,440
Speaker 1: swat team. I do know someone, well, I know, but

570
00:32:11,520 --> 00:32:15,240
Speaker 1: I didn't pan out like no or they call people no.

571
00:32:15,360 --> 00:32:19,080
Speaker 1: I think they got they got tactical trained people who

572
00:32:19,160 --> 00:32:20,680
Speaker 1: are ready for a lion to get out.

573
00:32:20,800 --> 00:32:23,239
Speaker 5: I mean also guess that they're wearing multiple hats at

574
00:32:23,240 --> 00:32:23,560
Speaker 5: the zoo.

575
00:32:23,960 --> 00:32:27,200
Speaker 1: Yeah, it's like it's like the but they in their

576
00:32:27,280 --> 00:32:28,880
Speaker 1: mind it's a dirty secret.

577
00:32:30,600 --> 00:32:34,440
Speaker 6: I think it's more that nobody wants to see animals

578
00:32:34,520 --> 00:32:37,760
Speaker 6: harmed at the zoo, but if something happens where it's

579
00:32:37,880 --> 00:32:40,480
Speaker 6: between an animal and a human being, then they'll do

580
00:32:40,600 --> 00:32:42,320
Speaker 6: what they need to do. So I think that there

581
00:32:42,400 --> 00:32:46,120
Speaker 6: are people at zoos who are trained lest something get

582
00:32:46,200 --> 00:32:46,960
Speaker 6: out of control.

583
00:32:47,080 --> 00:32:50,560
Speaker 1: Yeah, but I don't think that's a dirty secret. Someone

584
00:32:50,600 --> 00:32:53,200
Speaker 1: out there works in this field. I would like to

585
00:32:53,280 --> 00:32:57,920
Speaker 1: have a serious conversation on the podcast about that field,

586
00:32:58,040 --> 00:33:01,880
Speaker 1: like like, what is the training, what is the probability,

587
00:33:02,680 --> 00:33:05,360
Speaker 1: what are some examples where this has occurred? Why does

588
00:33:05,400 --> 00:33:07,160
Speaker 1: this go on? I don't feel like it's a thing

589
00:33:07,200 --> 00:33:10,160
Speaker 1: that they're like, hush, hush, can't talk about that. It

590
00:33:10,280 --> 00:33:14,800
Speaker 1: just seems weird to me. Some more audience emails.

591
00:33:16,640 --> 00:33:20,760
Speaker 5: Between we're voting between millions of mink and thousands of salmon.

592
00:33:20,960 --> 00:33:23,520
Speaker 6: Gosh, it's tough, Like okay, number three did a lot

593
00:33:23,560 --> 00:33:23,880
Speaker 6: of metal.

594
00:33:24,120 --> 00:33:26,600
Speaker 1: Number one, the guy that can't use his quotes right

595
00:33:26,720 --> 00:33:28,120
Speaker 1: any votes Here's.

596
00:33:28,080 --> 00:33:30,920
Speaker 4: Well, here's one one way that I'm thinking about this.

597
00:33:32,160 --> 00:33:34,320
Speaker 4: If a good correction, I would think is one that

598
00:33:34,400 --> 00:33:37,200
Speaker 4: you would deliver to someone to their face if they're

599
00:33:37,240 --> 00:33:39,400
Speaker 4: a stranger at a bar and they'd walk away going.

600
00:33:41,720 --> 00:33:43,360
Speaker 4: If you were at a bar with a stranger and

601
00:33:43,440 --> 00:33:48,960
Speaker 4: they said it's not on accident, it's by accident, then.

602
00:33:48,880 --> 00:33:52,240
Speaker 1: I would like that guy. You would, yeah, just from

603
00:33:52,320 --> 00:33:54,800
Speaker 1: the real like Nate Mason would hit me with that

604
00:33:55,120 --> 00:33:55,560
Speaker 1: that's true.

605
00:33:55,600 --> 00:33:58,400
Speaker 2: It sounds like Nate, but he's kind.

606
00:33:58,280 --> 00:34:02,720
Speaker 4: Of I like, but it's not really opening your he'd

607
00:34:02,760 --> 00:34:04,600
Speaker 4: tell you that it's not really opening your eyes.

608
00:34:05,320 --> 00:34:06,680
Speaker 1: You know. You wouldn't go home and be like, you

609
00:34:06,760 --> 00:34:08,800
Speaker 1: know what I learned today? No, I would tell my

610
00:34:08,880 --> 00:34:12,880
Speaker 1: wife that I'd wait hert in the middle night. I

611
00:34:14,000 --> 00:34:15,440
Speaker 1: stand corrected. I can't sleep.

612
00:34:15,760 --> 00:34:17,560
Speaker 5: I don't think guy number one would even vote for

613
00:34:17,640 --> 00:34:19,120
Speaker 5: guy number one in this one.

614
00:34:19,239 --> 00:34:21,920
Speaker 1: Okay, So and he votes. We got seven voters in

615
00:34:21,960 --> 00:34:26,200
Speaker 1: the room, guy number one, okay, Guy number two. Not

616
00:34:26,440 --> 00:34:29,080
Speaker 1: all mink were discard, not all mink werepelled. It out.

617
00:34:29,920 --> 00:34:32,080
Speaker 1: That's I'm voting for that guy. You know what, You're

618
00:34:32,160 --> 00:34:34,440
Speaker 1: voting for him because the other guy's goofing on you.

619
00:34:36,560 --> 00:34:40,000
Speaker 8: I'm voting for him because it's like he's he's bringing

620
00:34:40,080 --> 00:34:41,280
Speaker 8: the like receipts.

621
00:34:41,320 --> 00:34:42,440
Speaker 3: He's got an article.

622
00:34:42,640 --> 00:34:45,600
Speaker 6: It's like her information articles.

623
00:34:46,000 --> 00:34:49,200
Speaker 4: I will say, typically when in the news, when somebody

624
00:34:49,280 --> 00:34:52,440
Speaker 4: calls something a zombie, something like a zombie, dear, I

625
00:34:52,520 --> 00:34:52,960
Speaker 4: don't like it.

626
00:34:53,040 --> 00:34:55,120
Speaker 1: I like this use of zombie. Okay, I'm voting for him.

627
00:34:55,840 --> 00:34:59,520
Speaker 6: So the mink guy, we all need to be like

628
00:34:59,640 --> 00:35:00,479
Speaker 6: closing your eyes.

629
00:35:01,360 --> 00:35:05,520
Speaker 1: Okay. The math the math guy. Goof not Brody, he

630
00:35:05,680 --> 00:35:09,239
Speaker 1: went some taka boats. We have some people to abstained.

631
00:35:09,680 --> 00:35:13,359
Speaker 3: Didn't even vote, say in the thing that he's making

632
00:35:13,440 --> 00:35:13,640
Speaker 3: fun of.

633
00:35:13,719 --> 00:35:14,960
Speaker 2: Well, you voted for the mint guy.

634
00:35:15,960 --> 00:35:17,120
Speaker 1: We got a miscount.

635
00:35:20,719 --> 00:35:29,400
Speaker 2: Here, Okay, to hanging Chats guy. No sorry, okay, the mink.

636
00:35:29,320 --> 00:35:38,680
Speaker 1: Guy, change your vote this lection. This is some hanging

637
00:35:38,800 --> 00:35:43,359
Speaker 1: chats final final vote, final vote. This is serious this time. Okay,

638
00:35:43,840 --> 00:35:48,080
Speaker 1: the mink guy. Two votes for the Mint Guy, the

639
00:35:48,200 --> 00:35:48,759
Speaker 1: math guy.

640
00:35:50,000 --> 00:35:51,400
Speaker 3: Steve convinced himself to.

641
00:35:54,120 --> 00:35:56,120
Speaker 2: Steve's undefeated.

642
00:35:57,840 --> 00:36:00,959
Speaker 1: Because not Brody. That's why you got my vot. Max

643
00:36:01,040 --> 00:36:02,440
Speaker 1: al you got a free pair of boots. You can

644
00:36:02,480 --> 00:36:04,080
Speaker 1: tell us what size and style and all that.

645
00:36:05,440 --> 00:36:05,720
Speaker 2: Max.

646
00:36:07,280 --> 00:36:10,360
Speaker 1: Okay, quick audience email. We're running behind time. We got

647
00:36:10,440 --> 00:36:14,800
Speaker 1: a hustle. No one even comment on this.

648
00:36:15,800 --> 00:36:16,920
Speaker 2: H I think we're actually doing pretty good.

649
00:36:17,000 --> 00:36:20,719
Speaker 1: No one even comment on this, guy writes in and

650
00:36:20,840 --> 00:36:24,200
Speaker 1: the Screwworm episode eight thirty five. You guys relate a

651
00:36:24,239 --> 00:36:28,800
Speaker 1: story from Kevin Murphy's childhood about about putting an altered

652
00:36:29,239 --> 00:36:33,919
Speaker 1: bull to work for breeding purposes. What I was talking

653
00:36:33,920 --> 00:36:36,680
Speaker 1: about is Kevin Murphy. I was driving along with Kevin Murphy.

654
00:36:36,719 --> 00:36:38,360
Speaker 1: He's talking about working at a ranch. I said, what

655
00:36:38,440 --> 00:36:39,640
Speaker 1: kind of work are you doing at the ranch? And

656
00:36:39,680 --> 00:36:41,960
Speaker 1: he just related to me a story that they would

657
00:36:42,000 --> 00:36:45,319
Speaker 1: be able to in the old days. They would surgically

658
00:36:45,840 --> 00:36:50,840
Speaker 1: redirect a bull's penis so that it was coming out backward.

659
00:36:53,560 --> 00:36:56,400
Speaker 1: You would make this bull wear a big ink blodder

660
00:36:56,600 --> 00:36:59,800
Speaker 1: on his neck, and you turn him out with your cows.

661
00:37:00,760 --> 00:37:03,960
Speaker 1: He would detect that a cow was in heat and

662
00:37:04,080 --> 00:37:07,920
Speaker 1: he would mount the cow, but his pecker, being misoriented,

663
00:37:08,440 --> 00:37:15,200
Speaker 1: would not result in fertilization, but the ink blot would

664
00:37:15,320 --> 00:37:21,000
Speaker 1: mark the cow as being receptive, at which point a

665
00:37:21,160 --> 00:37:25,279
Speaker 1: farm boy or whoever would like Kevin you would then

666
00:37:25,480 --> 00:37:30,279
Speaker 1: rush out and artificially inseminate that cow. I thought that

667
00:37:30,480 --> 00:37:38,200
Speaker 1: was very, very very interesting. That's great, and just writer

668
00:37:38,360 --> 00:37:40,799
Speaker 1: writes in, and this listener writes in, in my time

669
00:37:40,920 --> 00:37:43,839
Speaker 1: spent cowboying out west, we have come to call these

670
00:37:44,040 --> 00:37:47,440
Speaker 1: heat seeking missiles. He's being metaphoric, he's being poetic. There

671
00:37:48,640 --> 00:37:52,560
Speaker 1: Gomer bulls g O. M. E. R. Golmer, perhaps from

672
00:37:52,560 --> 00:37:56,360
Speaker 1: Gomer Pyle, I don't know, Gomer bulls or teaser bowls.

673
00:37:57,920 --> 00:38:00,360
Speaker 1: And he says that phrase is commonly used in the

674
00:38:00,480 --> 00:38:05,080
Speaker 1: equine industry as well. Goomer bulls are often selected because

675
00:38:05,080 --> 00:38:08,400
Speaker 1: they won't cut it as a good breeder bul genetically,

676
00:38:09,320 --> 00:38:14,480
Speaker 1: but are generally easy to work and be around. Advances

677
00:38:14,520 --> 00:38:19,600
Speaker 1: an animal husbandry have made vast sectomy the primary method

678
00:38:19,760 --> 00:38:28,640
Speaker 1: for sterilizing these bulls. I could relate. And for the cows,

679
00:38:29,000 --> 00:38:32,200
Speaker 1: we often use paint patches that work like a scratch

680
00:38:32,280 --> 00:38:38,200
Speaker 1: off huh, rather than lots of ink and paint. The

681
00:38:38,360 --> 00:38:42,040
Speaker 1: patches can rip off and do a good job showing

682
00:38:42,080 --> 00:38:47,680
Speaker 1: who's been getting ridden by the gomer bull. If he

683
00:38:47,800 --> 00:38:50,800
Speaker 1: sees someone with a cowboy hat on backwards at the airport,

684
00:38:50,880 --> 00:38:55,840
Speaker 1: he points out, he calls them a gomer. He wonders,

685
00:38:56,239 --> 00:39:00,400
Speaker 1: does Kevin Murphy consider himself livestock adjacent e enough to

686
00:39:00,560 --> 00:39:05,560
Speaker 1: wear a cowboy hat. His hat's not quite a cowboy hat,

687
00:39:05,640 --> 00:39:11,440
Speaker 1: But Kevin Murphy entered cowboy hat validity through an entirely

688
00:39:11,520 --> 00:39:16,759
Speaker 1: different path. In my view, he could have never looked

689
00:39:16,760 --> 00:39:20,239
Speaker 1: at an equine or bovine animal and wear a cowboy hat.

690
00:39:24,120 --> 00:39:27,799
Speaker 1: Switching to the news with the news, doctor Randall.

691
00:39:28,880 --> 00:39:32,879
Speaker 4: Well, there's some exciting developments in the world of Neanderthal

692
00:39:33,400 --> 00:39:38,960
Speaker 4: or Neanderthal romance. There is a report paper that came

693
00:39:39,000 --> 00:39:47,000
Speaker 4: out last month in the journal Science that concluded that, like,

694
00:39:47,480 --> 00:39:50,040
Speaker 4: for a while, we've known that humans and Neanderthals shared

695
00:39:50,120 --> 00:39:52,960
Speaker 4: DNA and cross bread at some point, but they've now

696
00:39:53,080 --> 00:39:59,400
Speaker 4: determined that the preponderance of those interactions and couplings had

697
00:39:59,440 --> 00:40:03,880
Speaker 4: to do with a male Neanderthal and a female Homo sapien.

698
00:40:04,560 --> 00:40:07,480
Speaker 1: This is showing because they can track like mitochondrial DNA

699
00:40:07,680 --> 00:40:09,640
Speaker 1: and yeah, bunch stuff I don't.

700
00:40:10,280 --> 00:40:15,240
Speaker 4: I found a term called the Neanderthal desert, which refers

701
00:40:15,320 --> 00:40:20,319
Speaker 4: to the fact that in human X chromosomes they show

702
00:40:20,680 --> 00:40:26,040
Speaker 4: much less Neanderthal DNA than the rest of the genome. Okay,

703
00:40:26,320 --> 00:40:28,800
Speaker 4: and if you're a specialist in this area, I'm gonna

704
00:40:28,920 --> 00:40:30,680
Speaker 4: misuse a lot of these terms.

705
00:40:30,920 --> 00:40:32,640
Speaker 1: Oh so get your corrections ready.

706
00:40:33,000 --> 00:40:36,000
Speaker 4: But if I use, say sixty to seventy percent of

707
00:40:36,040 --> 00:40:37,960
Speaker 4: them correctly, right in and say you did a good job,

708
00:40:38,000 --> 00:40:39,040
Speaker 4: because that's what I'm meaning before.

709
00:40:39,600 --> 00:40:42,560
Speaker 1: So there there was there were a bunch of theories

710
00:40:42,600 --> 00:40:43,600
Speaker 1: about why this might be.

711
00:40:43,920 --> 00:40:47,840
Speaker 4: It could have been like the Neanderthal DNA could have

712
00:40:47,880 --> 00:40:50,680
Speaker 4: been missing from the X chromosomes because there's some sort

713
00:40:50,719 --> 00:40:54,640
Speaker 4: of like health risk or something that would just sort

714
00:40:54,640 --> 00:40:57,640
Speaker 4: of be weeded out through natural selection like it whatever,

715
00:40:57,800 --> 00:41:03,320
Speaker 4: that that Neanderthal DNA made humans more made the offspring

716
00:41:03,440 --> 00:41:05,000
Speaker 4: more susceptible to certain diseases.

717
00:41:05,080 --> 00:41:05,200
Speaker 1: Right.

718
00:41:05,760 --> 00:41:07,360
Speaker 4: But what they did is they went and looked at

719
00:41:07,440 --> 00:41:12,359
Speaker 4: Neanderthal DNA and they found that Neanderthal DNA on their

720
00:41:12,560 --> 00:41:15,480
Speaker 4: X chromosomes they actually have like a much higher percentage

721
00:41:15,760 --> 00:41:20,320
Speaker 4: of human DNA in them, right, because there's there's DNA

722
00:41:20,440 --> 00:41:24,200
Speaker 4: from both sides. So they kind of reverse engineering at that.

723
00:41:24,560 --> 00:41:28,480
Speaker 1: Yeah, so you take an old Neanderthal dead guy bones

724
00:41:28,800 --> 00:41:31,160
Speaker 1: and be like, well, he's got some Homo sapien lurking

725
00:41:31,239 --> 00:41:32,279
Speaker 1: in them. Yeah. Uh.

726
00:41:32,360 --> 00:41:36,080
Speaker 4: And so that's so that essentially that's the explanation now,

727
00:41:36,239 --> 00:41:39,879
Speaker 4: and there are some there are other reasons that could

728
00:41:40,239 --> 00:41:43,000
Speaker 4: sort of account for it other than just like sexual preference.

729
00:41:44,080 --> 00:41:45,879
Speaker 1: If this has nothing to do with sexual they're trying

730
00:41:45,920 --> 00:41:46,560
Speaker 1: to make it like that.

731
00:41:47,080 --> 00:41:49,480
Speaker 4: Oh no, no, I'm I don't like there's there are

732
00:41:49,640 --> 00:41:54,600
Speaker 4: some theories. There are some theories about like like you

733
00:41:54,719 --> 00:41:58,800
Speaker 4: can have whatever sex bias in breeding because of like,

734
00:41:59,680 --> 00:42:06,840
Speaker 4: uh distribution like whatever, Neanderthal males travel more, something like that.

735
00:42:07,680 --> 00:42:10,800
Speaker 4: But they've so but basically they've ruled it down to

736
00:42:11,280 --> 00:42:15,719
Speaker 4: the fact that for whatever reason, Neanderthal males and nandertal

737
00:42:15,840 --> 00:42:21,120
Speaker 4: female and human females were the most likely, uh like

738
00:42:21,280 --> 00:42:24,200
Speaker 4: overwhelmingly more likely to couple than say, human male and

739
00:42:24,239 --> 00:42:25,280
Speaker 4: a Neanderthal female.

740
00:42:26,440 --> 00:42:29,439
Speaker 1: And the pieces that I read about this, I can't

741
00:42:29,440 --> 00:42:31,680
Speaker 1: remember where I read about the pieces I read. It

742
00:42:31,840 --> 00:42:33,960
Speaker 1: was like they were sort of getting into the suggestion

743
00:42:34,120 --> 00:42:41,160
Speaker 1: of like attraction, Yeah, was there an attraction component? I don't.

744
00:42:42,320 --> 00:42:44,600
Speaker 1: I don't know. Earlier I told you what would happen

745
00:42:44,680 --> 00:42:47,719
Speaker 1: in the future, Yeah, I can, and here I could

746
00:42:47,719 --> 00:42:49,360
Speaker 1: tell you what happened in the past if you'd like.

747
00:42:50,840 --> 00:42:54,240
Speaker 4: Yeah, I mean I read another I read another article

748
00:42:54,360 --> 00:42:58,640
Speaker 4: that was very much leaning in the opposite direction of

749
00:42:58,800 --> 00:43:02,279
Speaker 4: the attraction to be proved. It was just like, you know,

750
00:43:02,400 --> 00:43:07,279
Speaker 4: for most of human history, mating resembled what we see

751
00:43:07,280 --> 00:43:10,200
Speaker 4: in animals, and that there's no consent, right, and it's

752
00:43:10,600 --> 00:43:12,120
Speaker 4: you know, it's like when you watch a duck with

753
00:43:12,200 --> 00:43:16,960
Speaker 4: a duck. It's sometimes ugly, but in any event, they

754
00:43:17,080 --> 00:43:20,960
Speaker 4: they went the opposite direction to be more provocative.

755
00:43:20,440 --> 00:43:23,360
Speaker 1: Okay, right, But that there was a there was a

756
00:43:23,440 --> 00:43:27,719
Speaker 1: coercion element. Yeah, That's where I'm going. Yeah, in understanding this,

757
00:43:27,840 --> 00:43:31,279
Speaker 1: and I don't know that maybe you guys know this, Uh,

758
00:43:32,320 --> 00:43:38,560
Speaker 1: meal deer and white tail deer will not infrequently interbreed,

759
00:43:39,560 --> 00:43:41,919
Speaker 1: and I believe that when they do that, like they'll

760
00:43:42,000 --> 00:43:45,080
Speaker 1: they'll have a their offspring don't do well. But I've

761
00:43:45,160 --> 00:43:47,160
Speaker 1: read that, and I don't know why this is true.

762
00:43:47,360 --> 00:43:51,120
Speaker 1: I've read that it is typically a white tail buck

763
00:43:53,200 --> 00:43:58,239
Speaker 1: breeding a mule deer dough but I've never read why

764
00:43:58,960 --> 00:44:00,799
Speaker 1: is it because the other I don't know if it's

765
00:44:01,080 --> 00:44:07,239
Speaker 1: that the other couplings don't produce offspring, or is it

766
00:44:07,440 --> 00:44:10,560
Speaker 1: that that's just how it goes and that's just how

767
00:44:10,600 --> 00:44:10,919
Speaker 1: it goes.

768
00:44:11,120 --> 00:44:14,440
Speaker 4: Yeah, yeah, I mean. The other really interesting thing that

769
00:44:14,520 --> 00:44:17,560
Speaker 4: I pulled up when I was doing my deep dive

770
00:44:17,640 --> 00:44:24,120
Speaker 4: on Neanderthals was like the there's another human species, the

771
00:44:24,200 --> 00:44:28,640
Speaker 4: denise Evans or Denisovans, who were more they're sort of

772
00:44:28,719 --> 00:44:32,200
Speaker 4: like the Asiatic version of a Neanderthal, and they split

773
00:44:32,280 --> 00:44:34,680
Speaker 4: off like around the same time as the Anertales. The

774
00:44:34,760 --> 00:44:37,440
Speaker 4: Andertales sort of went north and west and the denis

775
00:44:37,520 --> 00:44:41,000
Speaker 4: Ovans went east. And this is one case where they

776
00:44:41,160 --> 00:44:43,720
Speaker 4: just found I think, like a fingerbone in a cave

777
00:44:45,160 --> 00:44:47,680
Speaker 4: in Russia and they discovered that, hey, this is a

778
00:44:47,719 --> 00:44:50,520
Speaker 4: different type of human and they've sort of done what

779
00:44:50,640 --> 00:44:54,879
Speaker 4: Heffelfinger's doing with the the Merriam's elk. So they're going

780
00:44:55,000 --> 00:44:59,319
Speaker 4: back to older fossils that they assumed were just either

781
00:45:00,120 --> 00:45:03,640
Speaker 4: there's just normal Homo sapiens, and they're identifying them retroactively

782
00:45:03,800 --> 00:45:06,080
Speaker 4: as denise of ins ordentisil.

783
00:45:05,719 --> 00:45:08,920
Speaker 1: They had been miscategorized. Yeah, yeah, I was reading a

784
00:45:09,400 --> 00:45:14,440
Speaker 1: book on human genetics. I want to say, like, if

785
00:45:14,520 --> 00:45:17,239
Speaker 1: I'm wrong, it's still an interesting book. I want to

786
00:45:17,239 --> 00:45:18,879
Speaker 1: say that it was in this book. Now I wasn't

787
00:45:18,880 --> 00:45:20,440
Speaker 1: in that book. I was going to say it was

788
00:45:20,480 --> 00:45:23,960
Speaker 1: in The Seven Daughters of Eve. I can't remember what

789
00:45:23,960 --> 00:45:25,720
Speaker 1: the hell book. I was reading a book about human genetics.

790
00:45:28,680 --> 00:45:33,000
Speaker 1: In the book, they were talking about that, you know,

791
00:45:33,160 --> 00:45:35,919
Speaker 1: as the human diaster. As humans spread around the world,

792
00:45:36,080 --> 00:45:39,280
Speaker 1: there are pockets of the world that have much higher

793
00:45:40,320 --> 00:45:45,000
Speaker 1: Neanderthal DNA concentrations. There are pockets of the world that

794
00:45:45,160 --> 00:45:48,960
Speaker 1: have no Yeah, like in.

795
00:45:49,080 --> 00:45:57,719
Speaker 4: Africa, like like sub Saharan Africa and Africa, like down

796
00:45:57,800 --> 00:45:58,920
Speaker 4: into the African continent.

797
00:45:59,040 --> 00:46:03,200
Speaker 1: Neanderthals weren't down there. They were a European predominant European

798
00:46:03,400 --> 00:46:07,640
Speaker 1: Asian Middle Eastern species. So people that remained and that

799
00:46:07,960 --> 00:46:12,719
Speaker 1: remained in Africa, they don't have introgression from Neanderthals. He

800
00:46:12,920 --> 00:46:16,759
Speaker 1: points out that this is a very this is a

801
00:46:16,880 --> 00:46:20,799
Speaker 1: very hot loaded subject. And he said that there's even

802
00:46:20,880 --> 00:46:23,239
Speaker 1: been a reluctance, he claims in this book and I

803
00:46:23,239 --> 00:46:25,759
Speaker 1: can't remember the guy's damn name, he claims that there's

804
00:46:25,800 --> 00:46:29,600
Speaker 1: been a reluctance to talk about what populations around the

805
00:46:29,640 --> 00:46:32,680
Speaker 1: world have a lot of neanderthal because it would be

806
00:46:32,840 --> 00:46:36,600
Speaker 1: viewed as disparaging these people. Yeah, and so he said,

807
00:46:36,640 --> 00:46:39,000
Speaker 1: it's like it's become like a sort of hush hush

808
00:46:39,080 --> 00:46:43,160
Speaker 1: subject because because it's it's uh, people would review it,

809
00:46:43,360 --> 00:46:44,759
Speaker 1: view it as derogatory.

810
00:46:45,760 --> 00:46:50,120
Speaker 4: Yeah, it is interesting. I think like our understanding neanderthalis

811
00:46:50,160 --> 00:46:53,080
Speaker 4: has changed a lot. And now he recognized that they

812
00:46:53,120 --> 00:46:56,520
Speaker 4: were they buried their dead, and they wore jewelry, and

813
00:46:56,640 --> 00:46:59,160
Speaker 4: they used tools and lit fires and things like that,

814
00:46:59,280 --> 00:47:02,840
Speaker 4: and probably had language, but dove for shellfish. Yeah, but

815
00:47:03,080 --> 00:47:07,879
Speaker 4: for a long time, obviously there was this the sort

816
00:47:07,920 --> 00:47:10,279
Speaker 4: of I mean, I think what Western science did for

817
00:47:10,360 --> 00:47:12,480
Speaker 4: a long time is like, look at something else and

818
00:47:12,600 --> 00:47:15,800
Speaker 4: assume it's lesser than right if it's not Homo sapiens,

819
00:47:15,880 --> 00:47:18,719
Speaker 4: or if it's not you know, previously like if it's

820
00:47:18,719 --> 00:47:21,840
Speaker 4: not European, it's it's sort of on this order of

821
00:47:22,760 --> 00:47:26,040
Speaker 4: being right, and there's like this progressive view of these things.

822
00:47:28,000 --> 00:47:30,520
Speaker 4: But now I think it's like the Neanderthal DNA story

823
00:47:30,640 --> 00:47:34,160
Speaker 4: is even more interesting because, like I was reading something

824
00:47:34,200 --> 00:47:36,680
Speaker 4: the other day that if you have, they found in

825
00:47:36,840 --> 00:47:40,600
Speaker 4: one study that people with more Neanderthal DNA or a

826
00:47:40,640 --> 00:47:44,560
Speaker 4: certain sequence of Neanderthal DNA were more susceptible to bad

827
00:47:44,680 --> 00:47:49,520
Speaker 4: COVID outcomes. So it shows like how you know, like

828
00:47:49,880 --> 00:47:52,759
Speaker 4: some chunks of Neanderthal DNA could go missing over time

829
00:47:52,840 --> 00:47:56,400
Speaker 4: because for whatever reason, it makes people susceptible to certain infections.

830
00:47:56,480 --> 00:47:59,600
Speaker 1: But or if they had bad COVID restrictions in their

831
00:47:59,640 --> 00:48:04,239
Speaker 1: commune authorities are like no going outside of your cave.

832
00:48:07,160 --> 00:48:11,239
Speaker 1: All their Amazon boxes are laying around unopened. I'll tell

833
00:48:11,239 --> 00:48:16,560
Speaker 1: you what happened, ready, Yes, I think that Neanderthal groups

834
00:48:16,719 --> 00:48:19,640
Speaker 1: would now and then overpower Homo sapient groups. They would

835
00:48:19,719 --> 00:48:22,279
Speaker 1: kill the they would kill the males, and they would

836
00:48:22,360 --> 00:48:26,600
Speaker 1: keep the females as concubines. That's exactly what happened.

837
00:48:28,440 --> 00:48:35,600
Speaker 4: I can't dispute that. You ready to move on, I

838
00:48:35,640 --> 00:48:38,120
Speaker 4: don't know that these guys are not Neanderthal guys.

839
00:48:38,239 --> 00:48:40,520
Speaker 1: Don't you bet? That's good news?

840
00:48:40,640 --> 00:48:41,000
Speaker 2: All right?

841
00:48:41,280 --> 00:48:44,200
Speaker 1: Can I tell you my favorite Neanderthal little thing? Sure.

842
00:48:45,120 --> 00:48:47,680
Speaker 1: I was reading a book about in the Anerthales had

843
00:48:47,680 --> 00:48:49,759
Speaker 1: a lot to do with the Neanderthals, and this guy

844
00:48:49,960 --> 00:48:55,640
Speaker 1: was talking about when they exhume all these remain Neanderthal remains,

845
00:48:56,760 --> 00:49:02,640
Speaker 1: they see a like a predict suite of injuries on

846
00:49:02,760 --> 00:49:09,080
Speaker 1: the bones. They were showing them to physicians, and there

847
00:49:09,200 --> 00:49:13,000
Speaker 1: was a physician who had treated a lot of bull

848
00:49:13,120 --> 00:49:20,040
Speaker 1: riders in his career, and he pointed out that, Wow,

849
00:49:21,680 --> 00:49:25,920
Speaker 1: the types of injuries I'm seeing are very representative of

850
00:49:26,000 --> 00:49:29,759
Speaker 1: what I see on bull riders. Out of this came

851
00:49:29,840 --> 00:49:32,080
Speaker 1: this idea and this guy wrote about it that they

852
00:49:32,200 --> 00:49:38,120
Speaker 1: practiced a confrontational style of hunting. Yeah, that they mix

853
00:49:38,200 --> 00:49:38,480
Speaker 1: it up.

854
00:49:39,440 --> 00:49:43,080
Speaker 2: You're not saying that bull riders are like Neanderthals.

855
00:49:42,800 --> 00:49:45,080
Speaker 1: No, I'm saying that he was like the kinds of

856
00:49:45,280 --> 00:49:50,759
Speaker 1: breaks and lesions he saw reminded him of what he

857
00:49:50,920 --> 00:49:55,000
Speaker 1: sees from bull riders getting trampled. Gord.

858
00:49:55,760 --> 00:49:57,840
Speaker 2: Yeah, but you have to have a little bit of

859
00:49:57,880 --> 00:50:02,200
Speaker 2: a Neanderthal mindset to get on a two thousand pounds

860
00:50:02,200 --> 00:50:06,880
Speaker 2: animal and they.

861
00:50:05,520 --> 00:50:07,080
Speaker 3: Should research the genetics there.

862
00:50:07,160 --> 00:50:09,600
Speaker 8: What I would like to know is if it went

863
00:50:09,680 --> 00:50:14,000
Speaker 8: the other way, did Homo sapiens do the same thing.

864
00:50:14,120 --> 00:50:17,320
Speaker 1: Well, that's a bunch of lady, a bunch of female

865
00:50:17,400 --> 00:50:19,279
Speaker 1: Homo sapiens rated.

866
00:50:22,920 --> 00:50:26,080
Speaker 4: Would do that to I mean, that's that is one

867
00:50:26,280 --> 00:50:30,319
Speaker 4: theory as far as because it's only like a one

868
00:50:30,400 --> 00:50:33,000
Speaker 4: way path that Randall's talking about, right Like.

869
00:50:34,960 --> 00:50:38,560
Speaker 1: Yeah, understood, I'm not that good. I can't tell you.

870
00:50:39,560 --> 00:50:42,640
Speaker 4: Yeah, I mean there there is like at some point

871
00:50:42,840 --> 00:50:48,120
Speaker 4: human behavior changed, because that that's one of the explanations

872
00:50:48,160 --> 00:50:51,719
Speaker 4: at least for the extinction of the Anderthals is there's

873
00:50:51,800 --> 00:50:54,840
Speaker 4: no like discernible physical change in humans over that period

874
00:50:54,880 --> 00:50:58,800
Speaker 4: of time. So whatever when we went from cohabitation to

875
00:50:59,560 --> 00:51:05,200
Speaker 4: once he's being left. Uh, there's a change in culture. Yep,

876
00:51:05,360 --> 00:51:09,560
Speaker 4: that explains it. Uh, we can move on from Neanderthals,

877
00:51:09,640 --> 00:51:11,320
Speaker 4: or I can offer one more factory please.

878
00:51:12,200 --> 00:51:12,319
Speaker 9: Uh.

879
00:51:12,640 --> 00:51:17,239
Speaker 4: The old man of La Chappelle famous Neanderthal remains that

880
00:51:17,560 --> 00:51:19,440
Speaker 4: was used for a long time to sort of imagine

881
00:51:19,480 --> 00:51:24,279
Speaker 4: what they looked like. Ah, for a while they thought

882
00:51:24,360 --> 00:51:26,920
Speaker 4: that this is like the best model of a Neanderthal,

883
00:51:27,000 --> 00:51:29,759
Speaker 4: and then at some point someone pointed out, this is

884
00:51:29,840 --> 00:51:32,960
Speaker 4: like an old guy with some serious back injuries and

885
00:51:33,120 --> 00:51:36,600
Speaker 4: a lot of arthritis from the propotental hunt. He probably

886
00:51:36,600 --> 00:51:39,520
Speaker 4: had a more upright posture. If you can imagine, like

887
00:51:40,239 --> 00:51:44,080
Speaker 4: if we discovered some you know, if we're aliens and

888
00:51:44,160 --> 00:51:46,000
Speaker 4: we came in. This is the way it was put

889
00:51:46,040 --> 00:51:48,320
Speaker 4: on one thing. It's like we're aliens and we arrived

890
00:51:48,400 --> 00:51:52,279
Speaker 4: on Earth and we found Joe O'Neills or yeah, or

891
00:51:52,800 --> 00:51:55,719
Speaker 4: like and we're like, my god, they're all seven feet tall.

892
00:51:57,960 --> 00:52:00,520
Speaker 4: Or if we found like some some decrep it, you know,

893
00:52:00,640 --> 00:52:04,680
Speaker 4: old person who watched walks all hunched over. It's just

894
00:52:05,080 --> 00:52:07,279
Speaker 4: you jump to some conclusions. So that's one of the

895
00:52:08,000 --> 00:52:10,200
Speaker 4: the sort of changes in our thinking as we recognize

896
00:52:10,200 --> 00:52:11,680
Speaker 4: this is probably not the guy we should go on

897
00:52:11,800 --> 00:52:13,440
Speaker 4: for a benchmark.

898
00:52:14,960 --> 00:52:16,960
Speaker 1: I don't know if there's any Melville readers out there,

899
00:52:17,000 --> 00:52:22,440
Speaker 1: Herman Melville readers, but a neander tall expert is this

900
00:52:22,800 --> 00:52:28,319
Speaker 1: podcast white whale. We just cannot find one.

901
00:52:28,400 --> 00:52:30,960
Speaker 6: We have a bunch of emails in I found some

902
00:52:31,600 --> 00:52:34,680
Speaker 6: and they are too busy or have declined. So it's

903
00:52:34,719 --> 00:52:36,160
Speaker 6: a whole we have to find the best.

904
00:52:37,160 --> 00:52:39,720
Speaker 1: If I had a zoo keeper swat team person standing

905
00:52:39,760 --> 00:52:42,880
Speaker 1: here and a Neanderthal person standing here, I would go Neanderthal.

906
00:52:44,000 --> 00:52:46,600
Speaker 6: Maybe maybe don't get like a bunch in a row

907
00:52:47,160 --> 00:52:50,480
Speaker 6: like now, like if we if we get multiple ones,

908
00:52:50,600 --> 00:52:52,320
Speaker 6: like we have one and then the next week we

909
00:52:52,440 --> 00:52:53,759
Speaker 6: have another Neanderthal guy.

910
00:52:54,040 --> 00:52:56,359
Speaker 1: When I was on Theovon's show, He's got a huge show.

911
00:52:57,040 --> 00:52:58,960
Speaker 1: On Theovon Show, I said, Hey, I'm looking for a

912
00:52:59,040 --> 00:53:02,120
Speaker 1: Neanderthal expert. So I thought I'll reach new people because

913
00:53:02,160 --> 00:53:03,839
Speaker 1: like there's like the Hosers that listened to our thing

914
00:53:03,880 --> 00:53:06,759
Speaker 1: and that wasn't working. So I thought I'll talk to

915
00:53:07,600 --> 00:53:08,319
Speaker 1: I'll talk to the.

916
00:53:10,560 --> 00:53:15,080
Speaker 4: Still nothing that was JK, Phil, can you pull up

917
00:53:15,120 --> 00:53:18,040
Speaker 4: my assets really quick? Oh yeah, sure, Sorry, I forgot this.

918
00:53:18,280 --> 00:53:20,719
Speaker 1: This is uh this does not use this the whole time.

919
00:53:21,560 --> 00:53:24,360
Speaker 4: Well, I forgot about it just until now. Uh, this

920
00:53:24,920 --> 00:53:29,840
Speaker 4: is a recreation of a Neanderthal. And then if you

921
00:53:29,960 --> 00:53:32,440
Speaker 4: go home with that guy, yeah, if you go to

922
00:53:32,719 --> 00:53:35,680
Speaker 4: the Natural History Museum in Vienna, they have a thing

923
00:53:35,760 --> 00:53:38,479
Speaker 4: that scans your face and renders you into any number

924
00:53:38,480 --> 00:53:41,320
Speaker 4: of hominid species. So, Phil, if you'll continue to my

925
00:53:41,400 --> 00:53:44,319
Speaker 4: ex side, that's what I look like as a neanderthal,

926
00:53:45,120 --> 00:53:47,480
Speaker 4: sort of spread my eyes apart and added a more

927
00:53:47,880 --> 00:53:50,800
Speaker 4: prominent brow ridge. But you can see my mustache on

928
00:53:50,840 --> 00:53:51,919
Speaker 4: the bottom is still red.

929
00:53:52,800 --> 00:53:59,920
Speaker 1: I'm yeah, yeah, I'm sure like your bug eye.

930
00:54:00,320 --> 00:54:01,680
Speaker 2: Yeah, no, I can't.

931
00:54:03,600 --> 00:54:03,960
Speaker 5: Upgrade.

932
00:54:05,760 --> 00:54:08,279
Speaker 3: Didn't you say there was a like a red hair?

933
00:54:09,120 --> 00:54:09,520
Speaker 2: I believe?

934
00:54:10,280 --> 00:54:13,680
Speaker 1: Yeah. Moving on, Yan is going to bring us now

935
00:54:13,800 --> 00:54:15,719
Speaker 1: about Yan is going to talk to us now about

936
00:54:15,760 --> 00:54:19,000
Speaker 1: Catalina Island mule deer eradication program, which we've touched on

937
00:54:19,160 --> 00:54:23,280
Speaker 1: periodically over the years, just as a as a recap,

938
00:54:23,320 --> 00:54:25,320
Speaker 1: We're gonna find out where things stand now as a recap.

939
00:54:25,640 --> 00:54:29,000
Speaker 1: There's an island off the coast of California called Catalina Island.

940
00:54:30,120 --> 00:54:35,160
Speaker 1: It has the map, It is hosted, It has hosted

941
00:54:35,200 --> 00:54:38,520
Speaker 1: a number of non native species over the years. There

942
00:54:38,640 --> 00:54:41,200
Speaker 1: was a there was a herd of American buffalo that

943
00:54:41,239 --> 00:54:44,359
Speaker 1: were brought out there for a film. They are there,

944
00:54:44,800 --> 00:54:48,520
Speaker 1: but the but there is a large population of mule

945
00:54:48,600 --> 00:54:55,520
Speaker 1: deer on Catalina Island. They were not historically on Catalina Island,

946
00:54:55,640 --> 00:55:01,040
Speaker 1: but they were historically just in shore for Catalina Island.

947
00:55:01,840 --> 00:55:06,279
Speaker 1: So brings up this question are they native? Are they not?

948
00:55:07,080 --> 00:55:09,759
Speaker 1: People want to get rid of them. They don't want

949
00:55:09,800 --> 00:55:11,680
Speaker 1: to get rid of them. So over the years, we've

950
00:55:11,760 --> 00:55:16,320
Speaker 1: often mentioned various things about they're expanding hunting opportunities for

951
00:55:16,440 --> 00:55:20,440
Speaker 1: mildeer on Catalina Island, they are retracting hunting opportunities for

952
00:55:20,600 --> 00:55:24,360
Speaker 1: milder on Catalina Island. I've never even fully understood it.

953
00:55:24,800 --> 00:55:27,040
Speaker 1: Giannis is here to tell us where it stands now,

954
00:55:27,080 --> 00:55:31,360
Speaker 1: because there's been significant buzz yes.

955
00:55:32,560 --> 00:55:35,080
Speaker 2: To cut to the chase. When we're all done here

956
00:55:35,120 --> 00:55:38,000
Speaker 2: in the next five or ten minutes, I will still

957
00:55:38,440 --> 00:55:40,680
Speaker 2: not fully understand it. No one probably else in this

958
00:55:40,840 --> 00:55:44,920
Speaker 2: room will fully understand it. Yeah. I signed up to

959
00:55:45,120 --> 00:55:48,399
Speaker 2: cover this little this little story yesterday, less than twenty

960
00:55:48,440 --> 00:55:50,799
Speaker 2: four hours ago, and I thought, oh, this will be easy. Well,

961
00:55:50,920 --> 00:55:53,239
Speaker 2: once I dove in, I see that this is one

962
00:55:53,280 --> 00:55:55,960
Speaker 2: of those that Steve likes to say makes its own gravy.

963
00:55:58,160 --> 00:56:01,040
Speaker 2: So I'll try to give like a oh overview of

964
00:56:01,160 --> 00:56:04,200
Speaker 2: what's happened and really just state facts, and then I'm

965
00:56:04,280 --> 00:56:06,480
Speaker 2: hoping that you guys can sort of start then, you know,

966
00:56:06,680 --> 00:56:09,440
Speaker 2: asking questions. We might be able to get into the

967
00:56:09,520 --> 00:56:14,560
Speaker 2: stuff that doesn't seem so factual about this story. Like

968
00:56:14,680 --> 00:56:18,280
Speaker 2: Steve said, it's Catalina Island, it's about seventy five square miles.

969
00:56:20,080 --> 00:56:22,279
Speaker 2: Some important things you need to know. It's eighty eight

970
00:56:22,400 --> 00:56:27,560
Speaker 2: percent roughly private land, and that land is managed by

971
00:56:27,840 --> 00:56:32,279
Speaker 2: the Catalina Island Conservancy, which is pretty much an organization,

972
00:56:32,480 --> 00:56:39,000
Speaker 2: a nonprofit private conservation org that is made by and

973
00:56:39,120 --> 00:56:42,839
Speaker 2: made up of the people that own the land. Does

974
00:56:42,920 --> 00:56:46,600
Speaker 2: that make sense, Yeah, the family, the regularly family. Yeah,

975
00:56:46,680 --> 00:56:50,239
Speaker 2: they definitely have a lot of influence. They basically if

976
00:56:50,280 --> 00:56:54,840
Speaker 2: you they also own like most of the businesses that

977
00:56:55,040 --> 00:56:57,880
Speaker 2: operate on that island. I think there's there's like four

978
00:56:57,920 --> 00:57:01,319
Speaker 2: to five thousand people that live on that island. If

979
00:57:01,400 --> 00:57:03,880
Speaker 2: you live there and work there, you most likely work

980
00:57:04,320 --> 00:57:07,000
Speaker 2: for them in somewhere or another and rent from them

981
00:57:07,120 --> 00:57:10,960
Speaker 2: maybe probably, you know. So that in itself gets tricky

982
00:57:11,080 --> 00:57:16,560
Speaker 2: because people want to protect their livelihoods, right, and then

983
00:57:16,840 --> 00:57:21,000
Speaker 2: talking and saying things that you know might cause problems.

984
00:57:21,240 --> 00:57:22,840
Speaker 2: You may or may not want to do that.

985
00:57:23,280 --> 00:57:26,040
Speaker 1: Yeah, you're living in a company town. You don't trash

986
00:57:26,080 --> 00:57:27,160
Speaker 1: the company. Yeah.

987
00:57:27,800 --> 00:57:33,080
Speaker 2: So we have this conservancy, this Calleyan Island Conservancy. They

988
00:57:34,400 --> 00:57:38,439
Speaker 2: want to restore the island. I think that their motto

989
00:57:38,520 --> 00:57:44,160
Speaker 2: is basically to like like keep the do the best

990
00:57:44,200 --> 00:57:48,640
Speaker 2: they can be the best stewards of that land through recreation,

991
00:57:49,680 --> 00:57:55,760
Speaker 2: habitat management one other thing. But there they want to

992
00:57:55,840 --> 00:58:00,480
Speaker 2: make it be as those it was before. Kin they're

993
00:58:00,520 --> 00:58:04,760
Speaker 2: sort of like what I would call island purists.

994
00:58:05,680 --> 00:58:08,400
Speaker 1: Like restore the native vegetation. So you're looking at it,

995
00:58:08,480 --> 00:58:10,280
Speaker 1: you're looking like what it looked like a long time.

996
00:58:10,120 --> 00:58:18,720
Speaker 2: Ago, exactly before the deer they had, Like you mentioned,

997
00:58:18,760 --> 00:58:21,520
Speaker 2: all these other animals. Ferl goats were a big one.

998
00:58:21,760 --> 00:58:25,880
Speaker 2: They were also cattle that were once run on Catalina

999
00:58:25,960 --> 00:58:28,760
Speaker 2: Island by the Wrigley family, like it was a business.

1000
00:58:28,920 --> 00:58:29,040
Speaker 1: Right.

1001
00:58:29,960 --> 00:58:32,920
Speaker 2: They've kind of gotten rid of all these other grazers

1002
00:58:32,960 --> 00:58:36,120
Speaker 2: and animals, but the thing left are these deer that

1003
00:58:36,240 --> 00:58:38,800
Speaker 2: are still and you can see there's there's pictures online

1004
00:58:38,800 --> 00:58:41,600
Speaker 2: where you can see enclosures and you can see the

1005
00:58:42,040 --> 00:58:44,919
Speaker 2: line like often we see in Mexico when we're hunting

1006
00:58:44,960 --> 00:58:47,560
Speaker 2: coups deer, right where the cattle have been on one

1007
00:58:47,600 --> 00:58:48,800
Speaker 2: side of the fence and they haven't been on the

1008
00:58:48,840 --> 00:58:51,000
Speaker 2: other side of the fence, and one side looks scorched

1009
00:58:51,080 --> 00:58:53,640
Speaker 2: earth and the other side looks pretty lush and green

1010
00:58:53,800 --> 00:58:56,560
Speaker 2: right and tall grass. You can see images like that

1011
00:58:56,760 --> 00:58:57,960
Speaker 2: online if you look for them.

1012
00:58:58,080 --> 00:59:01,080
Speaker 1: It's where they got deer fenced out or in exactly.

1013
00:59:03,560 --> 00:59:06,520
Speaker 2: So the conservancy believes is saying that at this point,

1014
00:59:07,160 --> 00:59:09,640
Speaker 2: like they've had a hunting program on the island for

1015
00:59:09,800 --> 00:59:12,959
Speaker 2: twenty some years, and again this hunting program is run

1016
00:59:13,280 --> 00:59:18,800
Speaker 2: through the Rickley family or this Catalina Island Conservancy, Right,

1017
00:59:20,360 --> 00:59:24,520
Speaker 2: they believe that it's not doing enough to suppress the

1018
00:59:24,640 --> 00:59:30,280
Speaker 2: deer numbers to make a difference in letting the habitat rebound.

1019
00:59:31,440 --> 00:59:34,960
Speaker 2: They want to see more of these sort of lush

1020
00:59:36,480 --> 00:59:41,640
Speaker 2: forbes brush living there and less of that cheat grass,

1021
00:59:42,000 --> 00:59:44,600
Speaker 2: non native landscape going there. And they believe that the

1022
00:59:45,000 --> 00:59:48,080
Speaker 2: deer browsing is causing that. Right, they're eating the stuff

1023
00:59:48,240 --> 00:59:50,520
Speaker 2: that they're preferring that stuff, and they're letting this other

1024
00:59:50,560 --> 00:59:55,240
Speaker 2: stuff grow more of They have for years been trying

1025
00:59:55,280 --> 00:59:58,840
Speaker 2: to get a permit that basically allows them to do

1026
00:59:59,440 --> 01:00:02,120
Speaker 2: massive calling efforts and take out as many as these

1027
01:00:02,160 --> 01:00:04,000
Speaker 2: deer as they want, because again they feel like the

1028
01:00:04,080 --> 01:00:06,520
Speaker 2: hunting program is not doing doing the trick.

1029
01:00:06,600 --> 01:00:08,600
Speaker 1: Can I wedge because you're trying to go just facts?

1030
01:00:08,640 --> 01:00:10,680
Speaker 1: Can I wedge it a not just fact thing? Yeah?

1031
01:00:10,920 --> 01:00:12,160
Speaker 1: Do you mind? Because I know that? Can I be

1032
01:00:12,200 --> 01:00:17,760
Speaker 1: the guy that does not pay. I want to choose

1033
01:00:17,800 --> 01:00:23,120
Speaker 1: my words carefully here. A common refrain among people who

1034
01:00:23,480 --> 01:00:28,600
Speaker 1: have attempted to do a meald Your Hunt on Catalina

1035
01:00:28,680 --> 01:00:34,360
Speaker 1: Island is that they do their best to make it impossible.

1036
01:00:36,960 --> 01:00:42,360
Speaker 1: Who's today the Conservancy likes to like this is just

1037
01:00:42,640 --> 01:00:47,640
Speaker 1: a viewpoint that is expressed to me, is that they

1038
01:00:47,720 --> 01:00:54,360
Speaker 1: pay lip service to a hunting program, but make the

1039
01:00:54,480 --> 01:00:58,480
Speaker 1: hunting program they set it up to fail. Is a

1040
01:00:58,600 --> 01:01:02,560
Speaker 1: common refrain among friends of mine who've tried to participate

1041
01:01:02,720 --> 01:01:04,920
Speaker 1: in the meald Your Hunt is they set it up

1042
01:01:04,960 --> 01:01:05,480
Speaker 1: to not work.

1043
01:01:06,080 --> 01:01:10,360
Speaker 2: Yeah, it's disingenuous, and it's been all it's been all

1044
01:01:10,440 --> 01:01:13,800
Speaker 2: over the place as far as who can hunt there,

1045
01:01:13,920 --> 01:01:16,160
Speaker 2: how much they can hunt there. They they've had years

1046
01:01:16,200 --> 01:01:18,600
Speaker 2: where it's only been a couple hundred tags. They've had

1047
01:01:18,680 --> 01:01:21,560
Speaker 2: years where it's been a thousand tags. They've had years

1048
01:01:21,560 --> 01:01:25,160
Speaker 2: where only locals can hunt, only Californians can hunt, and

1049
01:01:25,320 --> 01:01:28,360
Speaker 2: then other years where you can't have non residents coming

1050
01:01:28,400 --> 01:01:32,680
Speaker 2: in and hunting. When they had that, it wasn't very

1051
01:01:32,720 --> 01:01:35,160
Speaker 2: well publicized, so a lot of people didn't know, and

1052
01:01:35,200 --> 01:01:37,080
Speaker 2: then those that knew were sort of keeping it hush

1053
01:01:37,160 --> 01:01:38,880
Speaker 2: husts because it's like oh, we got a good thing going,

1054
01:01:39,280 --> 01:01:40,920
Speaker 2: like we're not going to tell all of our friends

1055
01:01:40,960 --> 01:01:42,840
Speaker 2: about this great hunting opportunity and it.

1056
01:01:42,920 --> 01:01:46,960
Speaker 1: Want to spot burn eradication program, which is expected.

1057
01:01:48,320 --> 01:01:52,520
Speaker 2: So kind of where we are now is that they

1058
01:01:52,840 --> 01:01:56,800
Speaker 2: have the Kellean Island Conservancy've gotten to a point where

1059
01:01:56,880 --> 01:02:02,320
Speaker 2: they they got this permit to basically do the calling

1060
01:02:02,400 --> 01:02:05,040
Speaker 2: that they want to do and it's a five year

1061
01:02:05,240 --> 01:02:07,920
Speaker 2: program and they're like they're allowed to do it. They

1062
01:02:08,560 --> 01:02:13,960
Speaker 2: to this point. I talked to Charles Whitwam Whitwam this morning.

1063
01:02:14,160 --> 01:02:17,919
Speaker 2: He does he's the howl for wildlife guy. He's sort

1064
01:02:17,960 --> 01:02:21,680
Speaker 2: of in a accidental wake, ended up making a documentary

1065
01:02:21,840 --> 01:02:25,480
Speaker 2: called Killing Catalina that's about this subject and if you

1066
01:02:25,520 --> 01:02:30,200
Speaker 2: want to know why, go and watch it. It's very educational.

1067
01:02:30,240 --> 01:02:32,640
Speaker 2: You'll learn a lot about what's going on there. But

1068
01:02:32,760 --> 01:02:35,800
Speaker 2: he's the guy I figured that Conan would know without

1069
01:02:35,880 --> 01:02:38,400
Speaker 2: talking to somebody that works for the Catalina Island Conservancy.

1070
01:02:38,520 --> 01:02:41,920
Speaker 2: He's the guy that's probably dove into this the deepest.

1071
01:02:42,120 --> 01:02:48,120
Speaker 2: Right at this point, they haven't killed any deer that

1072
01:02:48,240 --> 01:02:51,400
Speaker 2: he knows of, but they're like they're supposed to start sometime.

1073
01:02:51,160 --> 01:02:55,560
Speaker 1: Soon, like a helicopter program, not a helicopter program.

1074
01:02:55,680 --> 01:02:58,800
Speaker 2: That was the first thing that was put out there.

1075
01:02:58,960 --> 01:03:02,000
Speaker 2: That's how they got rid of the goats in the past,

1076
01:03:02,200 --> 01:03:05,080
Speaker 2: and there was a lot of public outcry against doing

1077
01:03:05,200 --> 01:03:09,000
Speaker 2: that because they had supposedly, you know, three legged goats,

1078
01:03:09,240 --> 01:03:11,880
Speaker 2: wounded goats walking around and it didn't.

1079
01:03:11,680 --> 01:03:13,760
Speaker 1: Look so they couldn't sharpshoot them as well.

1080
01:03:14,120 --> 01:03:17,080
Speaker 2: Exactly. So now the ideas that you would have been

1081
01:03:17,240 --> 01:03:23,040
Speaker 2: bringing government sharp sharpshooters and and do the killing the locals,

1082
01:03:23,800 --> 01:03:31,560
Speaker 2: and a lot of hunters, conservation orgs and interestingly people

1083
01:03:31,720 --> 01:03:36,520
Speaker 2: like the Humane Society of the of California have bonded.

1084
01:03:36,160 --> 01:03:40,520
Speaker 1: Together strange bedfellows, yes, yes, to oppose this.

1085
01:03:41,080 --> 01:03:43,720
Speaker 2: And actually, as of I think yesterday, there's a press

1086
01:03:43,840 --> 01:03:48,360
Speaker 2: release release today that I can just give you the

1087
01:03:50,280 --> 01:03:54,320
Speaker 2: the real high look at it. Here is that a

1088
01:03:54,400 --> 01:03:57,840
Speaker 2: coalition of hunting, conservation, SPORTSMS advacy organizations follow the lawsuit

1089
01:03:57,960 --> 01:04:00,760
Speaker 2: challenging the California Department official while let approval of a

1090
01:04:00,840 --> 01:04:04,160
Speaker 2: plan to exterminate the up to two thousand mule deer

1091
01:04:04,200 --> 01:04:07,200
Speaker 2: on Catalina Island. So like Spari Club International is a

1092
01:04:07,240 --> 01:04:10,320
Speaker 2: part of that, A bunch of California's you know smaller

1093
01:04:11,440 --> 01:04:15,400
Speaker 2: orgs are there? How for wildlife? Can I ask it?

1094
01:04:15,520 --> 01:04:19,800
Speaker 8: Like, Yeah, what it's obvious why someone like group like

1095
01:04:20,080 --> 01:04:23,520
Speaker 8: the Humane Society would be against it? What are are

1096
01:04:23,640 --> 01:04:27,520
Speaker 8: these hunting groups against it because they're about to lose

1097
01:04:27,680 --> 01:04:28,640
Speaker 8: hunting opportunity?

1098
01:04:28,800 --> 01:04:29,640
Speaker 2: Like what are they?

1099
01:04:31,680 --> 01:04:31,720
Speaker 5: Like?

1100
01:04:31,840 --> 01:04:35,080
Speaker 2: What it I think that they're against it because and

1101
01:04:35,160 --> 01:04:40,040
Speaker 2: from what I gather is because it's a it's a

1102
01:04:40,280 --> 01:04:42,640
Speaker 2: in their minds, it's a bad way to manage wildlife.

1103
01:04:43,520 --> 01:04:48,440
Speaker 2: And mostly because they didn't go through the proper channels

1104
01:04:48,600 --> 01:04:52,560
Speaker 2: process these steps to get this permit. Some stuff was

1105
01:04:52,680 --> 01:04:55,760
Speaker 2: fast tracked. There was like a bill introduced last year

1106
01:04:56,360 --> 01:05:00,440
Speaker 2: that got through and Lo and Behold, sponsor of this

1107
01:05:00,640 --> 01:05:06,280
Speaker 2: bill are related and interconnected with this Calalian Island Conservancy,

1108
01:05:06,920 --> 01:05:10,600
Speaker 2: and so some things happened to help make this permit

1109
01:05:10,760 --> 01:05:16,520
Speaker 2: kind of smooth right through, which from what I research

1110
01:05:16,640 --> 01:05:18,480
Speaker 2: is that they've been trying to get this permit for

1111
01:05:18,640 --> 01:05:22,320
Speaker 2: fifteen years in California Department Fishing Wildlife has been like, no,

1112
01:05:22,920 --> 01:05:25,760
Speaker 2: you guys don't have the science to prove that you

1113
01:05:25,800 --> 01:05:27,560
Speaker 2: guys need to be doing this, because that's where it

1114
01:05:27,600 --> 01:05:30,240
Speaker 2: gets tricky is that they basically have a private island

1115
01:05:30,920 --> 01:05:33,919
Speaker 2: they control it, but they don't control the animals, sure,

1116
01:05:34,120 --> 01:05:37,320
Speaker 2: because the animals are owned by the staple California.

1117
01:05:39,080 --> 01:05:40,800
Speaker 3: How do the locals feel about the deer?

1118
01:05:41,720 --> 01:05:44,560
Speaker 1: They and what by locals, what do you mean though, Well,

1119
01:05:44,600 --> 01:05:46,840
Speaker 1: there's people that live on the island, right, Yeah, but

1120
01:05:46,920 --> 01:05:49,520
Speaker 1: they live on the property of the people that want

1121
01:05:49,520 --> 01:05:50,120
Speaker 1: to kill the deer.

1122
01:05:50,840 --> 01:05:56,040
Speaker 2: Sure, but interestingly, yeah, they're opposed to the killing of the.

1123
01:05:56,120 --> 01:05:58,640
Speaker 1: People that are renting from the family that owns the thing.

1124
01:05:58,880 --> 01:06:01,600
Speaker 2: Yeah, it's so it is.

1125
01:06:03,400 --> 01:06:04,640
Speaker 6: Of about four thousand.

1126
01:06:04,800 --> 01:06:08,200
Speaker 1: Yeah, so there's there's two of them for each dear.

1127
01:06:08,360 --> 01:06:12,800
Speaker 2: They actually passed in the last year. I don't know

1128
01:06:12,840 --> 01:06:16,360
Speaker 2: if you'd call it legislation or a zoning thing that,

1129
01:06:16,520 --> 01:06:19,840
Speaker 2: but basically within the town of Avalon, which must be

1130
01:06:19,960 --> 01:06:24,560
Speaker 2: like incorporated and so that it's been there, Yeah, it's

1131
01:06:25,600 --> 01:06:28,760
Speaker 2: it's the other twenty percent of the island that isn't

1132
01:06:28,760 --> 01:06:31,840
Speaker 2: controlled by Callian Isron Conservancy. They basically passed a law

1133
01:06:31,920 --> 01:06:37,000
Speaker 2: where you cannot shoot or discharge firearms any within those limits.

1134
01:06:37,040 --> 01:06:39,360
Speaker 2: And of course that is where most of these deer

1135
01:06:39,480 --> 01:06:40,840
Speaker 2: live or that's where all the people are.

1136
01:06:40,880 --> 01:06:42,440
Speaker 1: Though, Like when you come in there, it's like a

1137
01:06:42,520 --> 01:06:46,480
Speaker 1: beautiful little bay and a port. Yeah, it's beautiful, real

1138
01:06:46,600 --> 01:06:49,800
Speaker 1: like real like walk around, get an ice cream cone

1139
01:06:49,840 --> 01:06:50,400
Speaker 1: kind of vibe.

1140
01:06:50,560 --> 01:06:53,440
Speaker 2: Yeah, but they they made it so that they're not

1141
01:06:53,720 --> 01:06:56,160
Speaker 2: going to be able to kill every single deer off

1142
01:06:56,240 --> 01:06:59,080
Speaker 2: the island because it's basically the ones now that are

1143
01:06:59,120 --> 01:07:01,600
Speaker 2: in town cannot be eradicated.

1144
01:07:01,680 --> 01:07:03,960
Speaker 1: Has anyone Are there any real studs? I'm not talking

1145
01:07:03,960 --> 01:07:06,919
Speaker 1: about the townspeople. Are there any studs on this island

1146
01:07:07,000 --> 01:07:07,520
Speaker 1: or the danks?

1147
01:07:07,840 --> 01:07:10,600
Speaker 2: You know, just a few images that I saw, nothing

1148
01:07:10,680 --> 01:07:13,600
Speaker 2: that would fall fall into like nice Colorado mule.

1149
01:07:13,840 --> 01:07:16,480
Speaker 3: I looked in, but it's not like a destination mule.

1150
01:07:16,640 --> 01:07:18,840
Speaker 1: Dudes aren't like it's not like Anelope Island.

1151
01:07:19,040 --> 01:07:20,720
Speaker 2: Yeah, nothing like that.

1152
01:07:21,200 --> 01:07:24,800
Speaker 1: No, no, here, I mean, I'm gonna stay real obvious

1153
01:07:24,880 --> 01:07:30,080
Speaker 1: on this one. It brings up an interesting question of

1154
01:07:30,560 --> 01:07:34,920
Speaker 1: how far from the native source do you need to

1155
01:07:35,000 --> 01:07:40,680
Speaker 1: be where it becomes like irrefutably an exotic mm hmm.

1156
01:07:41,600 --> 01:07:46,880
Speaker 1: So like take something like nil Ghai in South Texas,

1157
01:07:47,440 --> 01:07:52,160
Speaker 1: right the Indian Like I think I think they're predominantly

1158
01:07:52,160 --> 01:07:57,080
Speaker 1: from like the Indian subcontinent. Am I right about that? Yeah? No, no, no, yeah,

1159
01:07:57,200 --> 01:08:00,840
Speaker 1: I think so to Texas when I look at it,

1160
01:08:01,080 --> 01:08:06,760
Speaker 1: when I spin the old Globe. I'm like, that is

1161
01:08:06,880 --> 01:08:11,720
Speaker 1: a non native from way far away, Like that has nothing. Yeah,

1162
01:08:12,080 --> 01:08:16,640
Speaker 1: that has nothing to do with that, do you know

1163
01:08:16,680 --> 01:08:19,000
Speaker 1: what I mean? Nothing to do with that. That's its

1164
01:08:19,040 --> 01:08:22,519
Speaker 1: own little thing. Their fate, the fate of the nil

1165
01:08:22,600 --> 01:08:25,080
Speaker 1: guy in South Texas is not related to sort of

1166
01:08:25,120 --> 01:08:28,200
Speaker 1: like the fate of Nilghai as a wild species in general.

1167
01:08:28,840 --> 01:08:33,120
Speaker 1: When you get to a situation like this where you

1168
01:08:33,240 --> 01:08:37,439
Speaker 1: can look and see, you can look and see where

1169
01:08:37,439 --> 01:08:37,880
Speaker 1: they're from.

1170
01:08:38,000 --> 01:08:41,120
Speaker 5: It's twenty two miles from Los Angeles, it's the Catalina Island.

1171
01:08:41,200 --> 01:08:43,200
Speaker 1: You can look and see where they're native.

1172
01:08:43,800 --> 01:08:48,360
Speaker 2: Yeah, it wouldn't be impossible for a deer to make

1173
01:08:48,439 --> 01:08:48,880
Speaker 2: that swim.

1174
01:08:49,160 --> 01:08:52,400
Speaker 8: Oh look at Southeast Alaska. You see those blacktails swimming around.

1175
01:08:53,280 --> 01:08:56,439
Speaker 1: Yeah, So it's like it does bring up interesting question.

1176
01:08:56,520 --> 01:09:00,439
Speaker 1: I'd be like, Okay, they came in with people by dude,

1177
01:09:00,520 --> 01:09:04,160
Speaker 1: it's just right. Their native grange is like right there.

1178
01:09:05,360 --> 01:09:07,479
Speaker 1: You can't rule out that one hasn't made the swim.

1179
01:09:08,280 --> 01:09:13,320
Speaker 8: But it is an island, which, like island ecosystems, operate

1180
01:09:13,479 --> 01:09:15,879
Speaker 8: differently than a mainland.

1181
01:09:16,000 --> 01:09:18,920
Speaker 1: I'd like to refer I'd like to refer listeners to

1182
01:09:19,479 --> 01:09:21,880
Speaker 1: I can't remember the name of it. David Kwalman's book

1183
01:09:22,040 --> 01:09:25,920
Speaker 1: An Island Biogeography, which explains all this kind of stuff,

1184
01:09:26,960 --> 01:09:29,920
Speaker 1: why islands are so special, why do mammals shrink and

1185
01:09:31,240 --> 01:09:33,519
Speaker 1: lizards get huge, all that kind of stuff on islands.

1186
01:09:37,560 --> 01:09:39,439
Speaker 1: I don't know, man, I'm a real fence sitter on

1187
01:09:39,560 --> 01:09:41,439
Speaker 1: this one. It's kind of on the side of them.

1188
01:09:41,640 --> 01:09:43,080
Speaker 1: Here's why I'm on the side of the mule deer.

1189
01:09:43,360 --> 01:09:44,600
Speaker 1: I don't know. Go ahead, I don't know.

1190
01:09:45,479 --> 01:09:47,439
Speaker 2: Something else, just to PLoP in there. Right there's this

1191
01:09:47,560 --> 01:09:50,760
Speaker 2: buffalo herd. I think the highest number I ever got

1192
01:09:50,920 --> 01:09:53,040
Speaker 2: was like up to sixteen hundred or something like that.

1193
01:09:53,960 --> 01:09:57,160
Speaker 2: It's been there roughly the same amount of time as.

1194
01:09:57,080 --> 01:09:58,960
Speaker 1: These mule deers came in to film a movie.

1195
01:09:59,200 --> 01:10:02,639
Speaker 2: Yeah, right now, approximately one hundred there.

1196
01:10:02,720 --> 01:10:03,040
Speaker 1: Okay.

1197
01:10:04,400 --> 01:10:06,960
Speaker 2: They think there's roughly two thousand of these deer, or

1198
01:10:07,000 --> 01:10:10,400
Speaker 2: at least that's what the Callian Island Conservancy, the outfit are,

1199
01:10:10,479 --> 01:10:11,760
Speaker 2: and a lot of the locals and people that have

1200
01:10:11,880 --> 01:10:14,240
Speaker 2: hunted there. I think there's a lot less than two

1201
01:10:14,280 --> 01:10:14,800
Speaker 2: thousand deer.

1202
01:10:14,880 --> 01:10:18,240
Speaker 1: Could someone do the math if you go how many

1203
01:10:18,439 --> 01:10:21,040
Speaker 1: how many buffalo one hundred? We'll say it, so one

1204
01:10:21,200 --> 01:10:27,479
Speaker 1: hundred at let's say twelve hundred pounds, and how many

1205
01:10:27,520 --> 01:10:31,200
Speaker 1: deer two thousand, two thousand at let's say one hundred

1206
01:10:31,240 --> 01:10:37,160
Speaker 1: and twenty pounds. Oh wait, one hundred at what one

1207
01:10:37,280 --> 01:10:40,439
Speaker 1: hundred at twelve hundred. Someone's gonna write into correction about this.

1208
01:10:40,760 --> 01:10:43,320
Speaker 4: I'm going to say we're getting on Bang's ground.

1209
01:10:43,080 --> 01:10:45,160
Speaker 1: Here one hundred at twelve hundred.

1210
01:10:45,080 --> 01:10:49,080
Speaker 8: Especially since buffalo are grazers and er uh yeah, mule

1211
01:10:49,200 --> 01:10:50,440
Speaker 8: were are browsers.

1212
01:10:50,520 --> 01:10:53,360
Speaker 5: With those numbers, would be one hundred twenty thousand pounds

1213
01:10:53,600 --> 01:10:57,719
Speaker 5: of biomass for the bison versus two hundred and forty

1214
01:10:57,800 --> 01:10:59,599
Speaker 5: thousand for the mule deer.

1215
01:11:00,240 --> 01:11:03,200
Speaker 1: Mule deer's double twice as much bio mass and mule deer. Okay,

1216
01:11:03,880 --> 01:11:08,519
Speaker 1: going by those numbers, correction, I don't think that's going

1217
01:11:08,560 --> 01:11:09,120
Speaker 1: to get corrected.

1218
01:11:09,560 --> 01:11:18,000
Speaker 2: The buffalo are just a little less sort of iconic

1219
01:11:18,240 --> 01:11:21,320
Speaker 2: of the island than the sorry a little bit more

1220
01:11:21,439 --> 01:11:23,640
Speaker 2: than the deer. The deer are like very much a

1221
01:11:23,720 --> 01:11:25,600
Speaker 2: part of it. Locals love them, people love to go

1222
01:11:25,680 --> 01:11:28,200
Speaker 2: there and see them. But the buffalo are just a

1223
01:11:28,240 --> 01:11:32,160
Speaker 2: little bit cooler. There's you know, murals of buffalo, there's

1224
01:11:32,240 --> 01:11:35,479
Speaker 2: weather veins of buffalo, like that's it's very much a part.

1225
01:11:35,360 --> 01:11:37,720
Speaker 1: Of them when I went. When I went there, it

1226
01:11:37,880 --> 01:11:41,680
Speaker 1: was for this reason to check the buffalo, but when

1227
01:11:41,680 --> 01:11:43,880
Speaker 1: I'm not writing about it. But I went there to

1228
01:11:43,960 --> 01:11:45,640
Speaker 1: write about it, but I never got to it.

1229
01:11:46,080 --> 01:11:49,000
Speaker 2: Yeah, did I was I researching us going to do

1230
01:11:49,120 --> 01:11:53,720
Speaker 2: a hunt there at some point. But anyways, they've all

1231
01:11:53,800 --> 01:11:59,240
Speaker 2: been sterilized. So you would think that you couldn't keep

1232
01:11:59,280 --> 01:12:02,400
Speaker 2: these buffalo going, right, or they wouldn't if they're all

1233
01:12:02,439 --> 01:12:04,960
Speaker 2: sterilized and they're not going to reproduce, they're going to

1234
01:12:05,000 --> 01:12:06,960
Speaker 2: blink out. They're eventually going to blink out.

1235
01:12:07,960 --> 01:12:09,760
Speaker 1: We're not gonna sterilize two thousand deer.

1236
01:12:10,000 --> 01:12:14,479
Speaker 2: When that question was posed to the main scientists of

1237
01:12:14,600 --> 01:12:23,320
Speaker 2: the conservancy, she had a very, uh, lackluster, vague answer

1238
01:12:23,960 --> 01:12:27,160
Speaker 2: as to what's going to happen to those bison where

1239
01:12:27,640 --> 01:12:30,040
Speaker 2: it just at that moment, you really feel like she's

1240
01:12:30,200 --> 01:12:34,080
Speaker 2: a mouthpiece for this other, you know, thing that's going on.

1241
01:12:34,960 --> 01:12:38,040
Speaker 2: She's not necessarily in control because if you're going to

1242
01:12:38,120 --> 01:12:41,200
Speaker 2: take out two thousand deer, take out the hunter bison too, right,

1243
01:12:41,320 --> 01:12:43,400
Speaker 2: and just like don't have any of that kind of

1244
01:12:43,439 --> 01:12:48,400
Speaker 2: grazing going on on the landscape, right, But because the

1245
01:12:48,560 --> 01:12:52,400
Speaker 2: locals and the tourists and everything, there's even that much

1246
01:12:52,640 --> 01:12:57,840
Speaker 2: more you know, probably comes down to money and you know,

1247
01:12:57,960 --> 01:13:01,040
Speaker 2: attached to it. They're like, well, maybe we'll keep them

1248
01:13:01,600 --> 01:13:05,000
Speaker 2: around kind of a little bit. Now, we're not gonna

1249
01:13:05,000 --> 01:13:08,720
Speaker 2: get rid of them completely. Well, like I said, it's

1250
01:13:10,640 --> 01:13:14,599
Speaker 2: just it's just thick with uh with sort of all

1251
01:13:14,680 --> 01:13:17,479
Speaker 2: these just like little ideas of what's going on. Who's thinking?

1252
01:13:17,600 --> 01:13:17,640
Speaker 9: What?

1253
01:13:17,960 --> 01:13:19,240
Speaker 2: Why are they talk about.

1254
01:13:19,040 --> 01:13:21,600
Speaker 8: What they're gonna do, Like they're just gonna let the

1255
01:13:21,640 --> 01:13:24,200
Speaker 8: deer lay after they like, they're not gonna get used.

1256
01:13:24,800 --> 01:13:28,040
Speaker 2: No, yeah, there's no plan for it. It's not like

1257
01:13:28,120 --> 01:13:29,840
Speaker 2: they're going to donate at all to a food bank.

1258
01:13:30,320 --> 01:13:33,240
Speaker 1: So crystal ballet for me, based on your you're based

1259
01:13:33,280 --> 01:13:37,200
Speaker 1: on your twenty four hours of NonStop research, ye all night,

1260
01:13:37,880 --> 01:13:40,800
Speaker 1: Crystal ballet for me if you had to take just

1261
01:13:41,320 --> 01:13:42,720
Speaker 1: if we're gonna go, if we're gonna go to a

1262
01:13:42,800 --> 01:13:46,120
Speaker 1: prediction market thing and make a bet. Yeah, And I said,

1263
01:13:46,520 --> 01:13:51,280
Speaker 1: and in five years, uh, you know, in five years,

1264
01:13:51,360 --> 01:13:56,000
Speaker 1: Catalina Island will have no meal deer Like whatever, how

1265
01:13:56,000 --> 01:13:56,760
Speaker 1: are you gonna bet on it?

1266
01:13:57,720 --> 01:14:01,000
Speaker 2: I think that they will have mule. I think the

1267
01:14:01,080 --> 01:14:03,679
Speaker 2: main thing that's like a big sticking point to anybody

1268
01:14:03,840 --> 01:14:07,600
Speaker 2: that sort of tries to figure the story out is

1269
01:14:07,640 --> 01:14:10,400
Speaker 2: that it looks like they don't actually have a good

1270
01:14:10,520 --> 01:14:13,200
Speaker 2: survey of how many deer on the island. Some people

1271
01:14:13,240 --> 01:14:15,080
Speaker 2: are like there's five hundred. Some people are saying there's

1272
01:14:15,160 --> 01:14:18,120
Speaker 2: twenty two hundred. No one really knows, and so you

1273
01:14:18,200 --> 01:14:21,760
Speaker 2: can't really go anywhere. You can't extrapolate from there if

1274
01:14:21,800 --> 01:14:23,759
Speaker 2: you don't know exactly how many deer on this island,

1275
01:14:23,840 --> 01:14:25,200
Speaker 2: right and you think they can be able to figure

1276
01:14:25,280 --> 01:14:29,000
Speaker 2: that out. I'm imagining that because it's getting so much

1277
01:14:29,080 --> 01:14:33,240
Speaker 2: press that this lawsuit was filed, the California Divisional Wildlife

1278
01:14:33,400 --> 01:14:35,639
Speaker 2: is going to Fish and Game whatever they call themselves.

1279
01:14:35,680 --> 01:14:36,479
Speaker 1: They're gonna walk back.

1280
01:14:36,800 --> 01:14:39,240
Speaker 2: Yeah, they're gonna walk back that permit and gonna say, hey,

1281
01:14:39,400 --> 01:14:41,960
Speaker 2: hold on, we need to do this the right way.

1282
01:14:42,320 --> 01:14:44,519
Speaker 2: We're like, we're here to manage wildlife. Let's do it

1283
01:14:44,600 --> 01:14:47,200
Speaker 2: the right way. And so I think that it's probably

1284
01:14:47,240 --> 01:14:51,160
Speaker 2: gonna come back to a private lands management permit, which

1285
01:14:51,160 --> 01:14:53,200
Speaker 2: is what they're operating under now. And I had to

1286
01:14:53,240 --> 01:14:54,479
Speaker 2: have a hunting program.

1287
01:14:54,640 --> 01:14:56,160
Speaker 1: What they need to do is they need to go

1288
01:14:56,600 --> 01:15:01,720
Speaker 1: get take one of them big jets with a lot

1289
01:15:01,800 --> 01:15:08,879
Speaker 1: of seats in it. Go to Kasanovia, Wisconsin. Put everybody

1290
01:15:08,960 --> 01:15:12,920
Speaker 1: from Casanova, Wisconsin on that jet, and fly him out

1291
01:15:12,920 --> 01:15:16,720
Speaker 1: to Catalina for a big mooch, A big old I'm

1292
01:15:16,800 --> 01:15:18,040
Speaker 1: talking of big mooch.

1293
01:15:18,479 --> 01:15:20,639
Speaker 4: I feel like lemmings getting pushed it out.

1294
01:15:21,080 --> 01:15:23,320
Speaker 3: They'd all just run into town where they're saved.

1295
01:15:23,680 --> 01:15:27,599
Speaker 1: Doug's in charge. Doug Durant gets a map of the island,

1296
01:15:27,680 --> 01:15:32,040
Speaker 1: he gets his laser pointer. You sit here, you sit here,

1297
01:15:32,640 --> 01:15:35,920
Speaker 1: at ten, you do this. At ten twenty two, you

1298
01:15:36,040 --> 01:15:37,400
Speaker 1: get out of your blind.

1299
01:15:37,120 --> 01:15:37,560
Speaker 6: And do this.

1300
01:15:39,880 --> 01:15:43,880
Speaker 1: Big mooch sounds like fun, a little whittle him down.

1301
01:15:44,479 --> 01:15:47,360
Speaker 1: But here's my final take on it. Not that it matters.

1302
01:15:47,479 --> 01:15:50,280
Speaker 1: My final take on it is since like a thing

1303
01:15:50,320 --> 01:15:53,000
Speaker 1: I would factor in. You have so many areas you

1304
01:15:53,040 --> 01:15:55,479
Speaker 1: can point to where mule deer are not doing good.

1305
01:15:58,080 --> 01:16:01,120
Speaker 1: The island is so close to native meal deer range.

1306
01:16:01,280 --> 01:16:03,040
Speaker 1: I would take these two things and I would say,

1307
01:16:03,680 --> 01:16:05,400
Speaker 1: we have a lot of areas where mildeer are not

1308
01:16:05,520 --> 01:16:09,400
Speaker 1: doing good. This is sort of like honorary native meal

1309
01:16:09,439 --> 01:16:13,120
Speaker 1: deer range. Because it's so close. It's a bright spot

1310
01:16:13,240 --> 01:16:17,880
Speaker 1: for meal deer. They're doing well. There, it's more valuable

1311
01:16:18,240 --> 01:16:24,240
Speaker 1: to have it's more valuable to have reassurance about the

1312
01:16:24,320 --> 01:16:27,400
Speaker 1: long term ability of meal deer. I don't know. Maybe

1313
01:16:27,439 --> 01:16:29,519
Speaker 1: I'm wrong about this. Maybe it could be a potential

1314
01:16:29,600 --> 01:16:34,640
Speaker 1: source location for future reintroductions. I don't know. If I

1315
01:16:34,840 --> 01:16:40,320
Speaker 1: was emperor of the planet, I would say, lower the

1316
01:16:40,400 --> 01:16:45,080
Speaker 1: numbers through greater public hunting opportunities, get lower the numbers down.

1317
01:16:45,120 --> 01:16:47,000
Speaker 1: But let's set aside talk of eradication.

1318
01:16:47,520 --> 01:16:51,439
Speaker 8: It's also a population that's more than likely pretty safe

1319
01:16:51,479 --> 01:16:52,280
Speaker 8: from CWD.

1320
01:16:53,240 --> 01:16:58,639
Speaker 3: You know what I mean, if they were careful.

1321
01:16:59,000 --> 01:17:01,600
Speaker 2: What if I said it came at the cost of

1322
01:17:02,000 --> 01:17:06,960
Speaker 2: losing several you know, in native endemic species that only

1323
01:17:07,040 --> 01:17:09,439
Speaker 2: are found what are the species floral species that are

1324
01:17:09,479 --> 01:17:10,680
Speaker 2: only found on that island and.

1325
01:17:10,640 --> 01:17:14,679
Speaker 1: They're still there after one hundred years of grazing. Yeah,

1326
01:17:15,680 --> 01:17:17,680
Speaker 1: and have they done? Is everything they could do to

1327
01:17:18,360 --> 01:17:22,360
Speaker 1: uh recede? And like I'd had to know more, I'm

1328
01:17:22,439 --> 01:17:24,280
Speaker 1: just spitballing here. Yeah, we got to move on.

1329
01:17:24,479 --> 01:17:30,800
Speaker 2: I'm just saying if I'm just throwing that in there, like,

1330
01:17:30,880 --> 01:17:33,920
Speaker 2: would you still say, hey, we really need this little

1331
01:17:34,320 --> 01:17:35,479
Speaker 2: little micro No, I.

1332
01:17:35,479 --> 01:17:38,640
Speaker 1: Would factor that in if there was a chance that

1333
01:17:38,720 --> 01:17:41,280
Speaker 1: there was an endemic plant species that was going to

1334
01:17:41,360 --> 01:17:44,280
Speaker 1: blink out and go extinct. And by and by having

1335
01:17:44,400 --> 01:17:46,200
Speaker 1: no meal deer, I knew that I could save that

1336
01:17:46,360 --> 01:17:49,920
Speaker 1: endemic plant species. And it was that binary that would

1337
01:17:49,920 --> 01:17:52,599
Speaker 1: make my decision much more complicated, and I would probably

1338
01:17:52,680 --> 01:17:55,880
Speaker 1: tip toward the endemic plant species. Keep an eye on

1339
01:17:55,920 --> 01:17:57,200
Speaker 1: the story for us, you honest.

1340
01:17:57,080 --> 01:18:01,759
Speaker 2: I will. There'll be plenty.

1341
01:18:04,000 --> 01:18:05,360
Speaker 1: Y'all would win a pair of boots.

1342
01:18:06,840 --> 01:18:07,840
Speaker 5: I haven't got to go yet.

1343
01:18:07,920 --> 01:18:10,560
Speaker 4: Well, you only, I'm the only point of comparison you have,

1344
01:18:10,760 --> 01:18:12,720
Speaker 4: So I'm trying to personally.

1345
01:18:12,920 --> 01:18:14,680
Speaker 1: Well, you know who's gonna be out, bro what you're

1346
01:18:14,680 --> 01:18:17,439
Speaker 1: gonna We're gonna have to hold the Coloradin's can't embarrass

1347
01:18:17,479 --> 01:18:19,519
Speaker 1: themselves anymore until they did. Story.

1348
01:18:20,000 --> 01:18:20,920
Speaker 3: We running out of town.

1349
01:18:20,960 --> 01:18:27,240
Speaker 1: We're gonna punt over dispenser for Rattlesnake Round Up Roundup This.

1350
01:18:27,400 --> 01:18:31,720
Speaker 5: Weekend, March thirteenth through the fifteenth is the sixty eighth

1351
01:18:31,960 --> 01:18:37,120
Speaker 5: annual World's largest Rattlesnake Round Up in seat Sweetwater, Texas.

1352
01:18:37,680 --> 01:18:39,880
Speaker 5: It's been going on since nineteen fifty eight. Not even

1353
01:18:39,960 --> 01:18:43,960
Speaker 5: COVID stopped them from having a couple of their festivals.

1354
01:18:44,240 --> 01:18:44,719
Speaker 1: That's great.

1355
01:18:44,840 --> 01:18:49,639
Speaker 5: There's a parade, a carnival, a gun and coin show, dance,

1356
01:18:49,840 --> 01:18:52,400
Speaker 5: guided rattlesnake hunts that you can sign up for. Those

1357
01:18:52,479 --> 01:18:56,160
Speaker 5: cost seventy five dollars to go catch one cooking competition

1358
01:18:56,280 --> 01:18:59,920
Speaker 5: with categories such as brisket, ribs, chili beans, Bloody Mary's,

1359
01:19:00,040 --> 01:19:03,400
Speaker 5: and of course rattlesnake. But the big attraction is the

1360
01:19:03,600 --> 01:19:08,240
Speaker 5: rattlesnake hunting contest and hunters they'll spend weeks or months

1361
01:19:08,479 --> 01:19:11,400
Speaker 5: catching rattlesnakes that will then get entered into the content.

1362
01:19:11,479 --> 01:19:13,720
Speaker 1: You can stock them up ahead of time far in

1363
01:19:13,840 --> 01:19:15,719
Speaker 1: advance the fishing.

1364
01:19:16,000 --> 01:19:18,200
Speaker 5: No, it's it's unclear to me. It seems as though

1365
01:19:18,200 --> 01:19:20,600
Speaker 5: you need to keep them alive to enter that, but

1366
01:19:20,800 --> 01:19:24,080
Speaker 5: I couldn't confirm that with anything. But you need to

1367
01:19:24,280 --> 01:19:25,240
Speaker 5: keep these snakes alive.

1368
01:19:25,720 --> 01:19:29,640
Speaker 8: Are they managed in any way like they are states rattlesnakes,

1369
01:19:29,680 --> 01:19:32,040
Speaker 8: like there's a limit, they're managed as some kind of like.

1370
01:19:32,280 --> 01:19:34,920
Speaker 5: They tell your game species on the website. You need

1371
01:19:35,000 --> 01:19:37,599
Speaker 5: to have a permit from the State of Texas whatever

1372
01:19:37,800 --> 01:19:40,680
Speaker 5: you know, like a small game permit whatever their equivalent is,

1373
01:19:40,760 --> 01:19:43,560
Speaker 5: your collection permit of some sort uh. And and for

1374
01:19:43,680 --> 01:19:47,240
Speaker 5: the first three thousand pounds of rattlesnakes brought in the

1375
01:19:47,400 --> 01:19:52,400
Speaker 5: Sweetwater jc's will pay twenty dollars per pound for those rattlesnakes.

1376
01:19:52,400 --> 01:19:53,080
Speaker 1: What do they want them for?

1377
01:19:54,360 --> 01:19:56,360
Speaker 5: We'll get to it, we'll get to it. But anyways,

1378
01:19:56,640 --> 01:19:59,080
Speaker 5: twenty dollars a pound like that. It was five dollars

1379
01:19:59,160 --> 01:20:01,760
Speaker 5: per pound in two thousand and six, so that's a

1380
01:20:01,800 --> 01:20:04,240
Speaker 5: fifteen dollars increase. And if you were doing inflation, that

1381
01:20:04,360 --> 01:20:07,719
Speaker 5: five dollars would be about nine dollars today. They've doubled

1382
01:20:07,720 --> 01:20:10,000
Speaker 5: even if you account for inflation, and what they're paying

1383
01:20:10,640 --> 01:20:13,920
Speaker 5: for the next five thousand pounds, they pay fifteen dollars

1384
01:20:14,000 --> 01:20:16,600
Speaker 5: per pound, and then they stop paying altogether if they

1385
01:20:16,680 --> 01:20:19,880
Speaker 5: have more than eight thousand pounds of rattlesnakes brought in?

1386
01:20:20,560 --> 01:20:23,040
Speaker 1: Is that is that the Phils put up a photo?

1387
01:20:23,760 --> 01:20:26,800
Speaker 1: Is that guy so confident in his snake chaps? He's

1388
01:20:26,880 --> 01:20:29,480
Speaker 1: just standing in among those rattles.

1389
01:20:29,160 --> 01:20:31,800
Speaker 5: Seems as though he is there's there's rattlesnakes on top

1390
01:20:31,840 --> 01:20:33,880
Speaker 5: of rattlesnakes, and he is within center, and.

1391
01:20:33,880 --> 01:20:35,320
Speaker 1: He's like, my chaps are good.

1392
01:20:35,400 --> 01:20:37,560
Speaker 4: Well, it looks like he's just flicking one off his

1393
01:20:37,680 --> 01:20:38,160
Speaker 4: boot there.

1394
01:20:38,280 --> 01:20:40,320
Speaker 3: Yeah, how many difference he should be done there one year.

1395
01:20:40,920 --> 01:20:42,719
Speaker 4: No, thank you, it's just terrible.

1396
01:20:42,880 --> 01:20:46,640
Speaker 5: The big snake guy, it is just the western diamondback

1397
01:20:46,800 --> 01:20:50,519
Speaker 5: that you can looks like there's a different species in there.

1398
01:20:50,880 --> 01:20:51,000
Speaker 1: Now.

1399
01:20:51,120 --> 01:20:54,719
Speaker 5: First prize. First prize for bringing in the most pounds

1400
01:20:54,760 --> 01:20:58,639
Speaker 5: of snakes is one thousand dollars. The longest snake gets

1401
01:20:58,760 --> 01:21:01,599
Speaker 5: five hundred dollars. All time record is an eighty one

1402
01:21:01,680 --> 01:21:03,920
Speaker 5: and a half inch rattlesnake.

1403
01:21:04,040 --> 01:21:04,720
Speaker 1: What's that come out?

1404
01:21:04,760 --> 01:21:07,120
Speaker 3: Two and feet almost seven?

1405
01:21:07,240 --> 01:21:12,760
Speaker 5: A little less than correction. Their website has results from

1406
01:21:12,760 --> 01:21:14,960
Speaker 5: the last decade, and from looking at these, it's clear

1407
01:21:15,040 --> 01:21:18,840
Speaker 5: that there is a Sweetwater rattlesnake hunting goat. Andy Lee

1408
01:21:18,960 --> 01:21:23,400
Speaker 5: has won five of the last nine contests, including in

1409
01:21:23,520 --> 01:21:26,720
Speaker 5: twenty twenty four and twenty twenty five.

1410
01:21:27,840 --> 01:21:29,840
Speaker 1: That guy on the show, what's his name? Andy Lee?

1411
01:21:30,000 --> 01:21:31,360
Speaker 1: Can you get him on the show?

1412
01:21:31,600 --> 01:21:34,080
Speaker 5: I've got some more details for you on Andy. Last

1413
01:21:34,160 --> 01:21:36,679
Speaker 5: year he brought in six hundred and fifty one pounds

1414
01:21:36,720 --> 01:21:40,679
Speaker 5: of rattlesnakes, which beat second place by thirty nine pounds.

1415
01:21:41,280 --> 01:21:44,679
Speaker 5: Here's some good journalism, Steve. When I googled Andy's name,

1416
01:21:45,120 --> 01:21:48,519
Speaker 5: I learned that he owns a pest control business in Texas.

1417
01:21:49,120 --> 01:21:52,320
Speaker 1: He's got a hot line. He is double dipping.

1418
01:21:52,400 --> 01:21:55,160
Speaker 5: First someone pays him to come a snake from under

1419
01:21:55,200 --> 01:21:57,760
Speaker 5: their porch, and then he goes and enters it. In

1420
01:21:57,840 --> 01:21:58,519
Speaker 5: this context, this.

1421
01:21:58,560 --> 01:22:00,559
Speaker 1: Does not dissuade me from wanting them on the show.

1422
01:22:00,640 --> 01:22:03,320
Speaker 5: No, I'm with you. But last year, last year, with

1423
01:22:03,439 --> 01:22:05,160
Speaker 5: that winning weight, if he would have entered it in

1424
01:22:05,200 --> 01:22:07,960
Speaker 5: the first three thousand pounds, he would have made fourteen

1425
01:22:08,040 --> 01:22:08,599
Speaker 5: thousand dollars.

1426
01:22:08,640 --> 01:22:10,479
Speaker 3: How many snake does it say how many snakes? It

1427
01:22:10,600 --> 01:22:11,280
Speaker 3: does fifty?

1428
01:22:11,520 --> 01:22:14,200
Speaker 5: It's It doesn't say it's you. It's always measured in pounds.

1429
01:22:14,360 --> 01:22:16,760
Speaker 5: On their webs there is right there there there he is.

1430
01:22:16,840 --> 01:22:20,479
Speaker 5: That's his the business he owns Andy Lee, who's was

1431
01:22:20,560 --> 01:22:24,040
Speaker 5: his wife. Then they owned the business together. Now Steve asked,

1432
01:22:24,040 --> 01:22:27,880
Speaker 5: what happens to these snakes? They're registered, then they're skinned, battered,

1433
01:22:27,960 --> 01:22:30,080
Speaker 5: deep fried and sold at the concession stands.

1434
01:22:30,320 --> 01:22:33,080
Speaker 1: You're not eating up that many snakes. Phil's got a

1435
01:22:33,120 --> 01:22:34,240
Speaker 1: picture of that.

1436
01:22:35,000 --> 01:22:36,400
Speaker 5: They said they're eating them there.

1437
01:22:37,280 --> 01:22:39,280
Speaker 1: They're going through that whole batch of snakes.

1438
01:22:39,960 --> 01:22:40,280
Speaker 5: I don't know.

1439
01:22:40,479 --> 01:22:42,559
Speaker 3: And the skins gone to a separate market.

1440
01:22:42,960 --> 01:22:45,439
Speaker 5: It doesn't say what they do with the skins. Phil's

1441
01:22:45,439 --> 01:22:47,760
Speaker 5: got a picture of how all them skinning in a

1442
01:22:47,840 --> 01:22:48,280
Speaker 5: line there?

1443
01:22:48,320 --> 01:22:48,680
Speaker 1: Look at that?

1444
01:22:48,920 --> 01:22:51,120
Speaker 6: Oh yeah, making some very fishing.

1445
01:22:52,120 --> 01:22:56,639
Speaker 5: On average, there are four thousand pounds of rattlesnakes brought

1446
01:22:56,680 --> 01:22:59,160
Speaker 5: in each year. The record was set in twenty sixteen

1447
01:22:59,479 --> 01:23:03,880
Speaker 5: when twenty five thousand pounds of diamondbacks were captured. There

1448
01:23:03,960 --> 01:23:06,000
Speaker 5: must have been something with the weather that year that

1449
01:23:06,360 --> 01:23:09,400
Speaker 5: just made a boom of rattlesnakes. Now here's the most

1450
01:23:09,439 --> 01:23:10,040
Speaker 5: amazing part.

1451
01:23:10,080 --> 01:23:10,360
Speaker 1: I think.

1452
01:23:10,680 --> 01:23:13,240
Speaker 5: I found a quote from Texas A and M in

1453
01:23:13,360 --> 01:23:16,240
Speaker 5: two thousand and six that said they estimate the roundup

1454
01:23:16,320 --> 01:23:20,719
Speaker 5: captures one percent of the state's entire western diamondback population

1455
01:23:21,080 --> 01:23:22,280
Speaker 5: every year, every year.

1456
01:23:22,520 --> 01:23:25,280
Speaker 1: But they have I wonder have you Have you encountered

1457
01:23:25,360 --> 01:23:28,360
Speaker 1: what sort of harvest rate, like a state would have

1458
01:23:28,560 --> 01:23:32,880
Speaker 1: deer harvest, and they're gonna kill ten percent, eleven percent,

1459
01:23:33,000 --> 01:23:36,280
Speaker 1: twelve percent of the state's deer. So I don't know

1460
01:23:36,320 --> 01:23:39,599
Speaker 1: about the fecundity of rattlesnakes, but I'm guessing one percent

1461
01:23:39,800 --> 01:23:41,320
Speaker 1: as well within recovery.

1462
01:23:41,560 --> 01:23:44,439
Speaker 5: I imagine if this is the world's largest version of

1463
01:23:44,520 --> 01:23:47,320
Speaker 5: this and it still exists, then yeah, they're not worried

1464
01:23:47,320 --> 01:23:50,720
Speaker 5: about hurting the western diamondback population. In Texas if it

1465
01:23:51,240 --> 01:23:53,840
Speaker 5: continues on now it's very popular in the community. They

1466
01:23:53,840 --> 01:23:56,280
Speaker 5: expect twenty five thousand visitors this year. Again, it's this

1467
01:23:56,360 --> 01:23:59,240
Speaker 5: weekend that pumps an eight million dollars to the local economy.

1468
01:23:59,280 --> 01:24:01,679
Speaker 5: So go check it out if you live in Central Texas.

1469
01:24:02,400 --> 01:24:04,800
Speaker 3: What's up with the bloody handprints.

1470
01:24:04,320 --> 01:24:04,760
Speaker 4: On the wall?

1471
01:24:05,040 --> 01:24:07,320
Speaker 1: Well, I think they're taking them hands that are all

1472
01:24:07,360 --> 01:24:09,000
Speaker 1: bloody and pressing them on that wall.

1473
01:24:09,320 --> 01:24:12,400
Speaker 3: Yeah, well I get that part. Interesting.

1474
01:24:12,600 --> 01:24:14,320
Speaker 4: It's amazing, beautiful y.

1475
01:24:14,400 --> 01:24:18,720
Speaker 1: It's like little cave paintings. Yeah, oh yeah, I'll say it.

1476
01:24:18,960 --> 01:24:26,519
Speaker 5: Sixty eighth annual World's Largest Rattlesnake Round Up Sweetwater, Texas Central.

1477
01:24:26,720 --> 01:24:29,599
Speaker 5: Excellent reporting, thank you they did best or now.

1478
01:24:29,800 --> 01:24:33,680
Speaker 1: No, I think it's I mean, there the quality of

1479
01:24:33,800 --> 01:24:39,040
Speaker 1: the reporting delivery, but it just didn't make as much gravy. Okay,

1480
01:24:40,840 --> 01:24:45,320
Speaker 1: I'm still third. It's what what is it when you

1481
01:24:45,439 --> 01:24:50,240
Speaker 1: just don't even get mentioned, like pictures at the at

1482
01:24:50,240 --> 01:24:53,080
Speaker 1: the Olympics, you got the gold, silver, and bronze, you know,

1483
01:24:53,320 --> 01:24:56,080
Speaker 1: but they don't even let a guy get on the You.

1484
01:24:56,160 --> 01:24:56,960
Speaker 3: Got to compete.

1485
01:24:57,120 --> 01:25:00,200
Speaker 1: Yeah, yeah, no, Randal, I'm just joking, man. I'll thought

1486
01:25:00,640 --> 01:25:02,320
Speaker 1: I thought you did a great job. Maybe I could

1487
01:25:02,320 --> 01:25:03,680
Speaker 1: tilt the scales a little more. So.

1488
01:25:03,840 --> 01:25:07,360
Speaker 5: Back to the Trump America the beautiful card, the Center

1489
01:25:07,400 --> 01:25:11,400
Speaker 5: of Biological what is it, the Center for Biological.

1490
01:25:10,880 --> 01:25:12,360
Speaker 1: Diversity, anti hunting organization.

1491
01:25:12,439 --> 01:25:15,200
Speaker 5: They are suing him for doing that. They started that

1492
01:25:15,280 --> 01:25:17,599
Speaker 5: lawsuit in December. I reached out to them for an

1493
01:25:17,680 --> 01:25:18,920
Speaker 5: update on the lawsuits.

1494
01:25:19,280 --> 01:25:21,240
Speaker 3: I was going to talk about those folks in my

1495
01:25:22,400 --> 01:25:23,080
Speaker 3: Their update is.

1496
01:25:23,080 --> 01:25:24,800
Speaker 5: They don't have an update yet, but they're working on

1497
01:25:24,880 --> 01:25:27,439
Speaker 5: it behind the scenes, so we don't know what the

1498
01:25:27,520 --> 01:25:29,720
Speaker 5: fate of By the time they wrap it up, this

1499
01:25:29,800 --> 01:25:31,760
Speaker 5: card will no longer even be good.

1500
01:25:32,040 --> 01:25:38,439
Speaker 1: So should they do a lot of postures understood a.

1501
01:25:40,040 --> 01:25:40,160
Speaker 2: Right?

1502
01:25:40,200 --> 01:25:42,720
Speaker 5: But what what would say best case scenario for them

1503
01:25:42,800 --> 01:25:46,520
Speaker 5: happens and they win this lawsuit against the Trump administration,

1504
01:25:46,640 --> 01:25:49,800
Speaker 5: then we're going to reissue I don't know, a thousand cards.

1505
01:25:50,320 --> 01:25:52,800
Speaker 4: Well maybe someone who chooses to buy their pass in

1506
01:25:52,880 --> 01:25:53,840
Speaker 4: December of this year.

1507
01:25:54,520 --> 01:25:57,720
Speaker 1: They have a People for the Ethical Treatment of Animals

1508
01:25:57,960 --> 01:26:02,600
Speaker 1: esque Wing Center for Biologically. They use some of the

1509
01:26:02,720 --> 01:26:06,880
Speaker 1: same type of people to think up campaigns that they're like,

1510
01:26:07,200 --> 01:26:10,439
Speaker 1: oh no, no, no, it's not that we'll win, it's

1511
01:26:10,600 --> 01:26:12,680
Speaker 1: just that it will be reported on this is right

1512
01:26:12,720 --> 01:26:13,400
Speaker 1: in their wheelhouse.

1513
01:26:13,680 --> 01:26:15,720
Speaker 5: For what they would do is have a lawsuit like this.

1514
01:26:16,400 --> 01:26:18,400
Speaker 1: All right, Brody, I'm down real sorry buddy.

1515
01:26:19,360 --> 01:26:21,880
Speaker 3: No, but you did say they do things to posture.

1516
01:26:23,439 --> 01:26:28,880
Speaker 8: They the Center for Biologic Biological Diversity, like they got

1517
01:26:28,920 --> 01:26:32,280
Speaker 8: something done in Colorado, which is not good.

1518
01:26:32,479 --> 01:26:34,000
Speaker 2: Next, well, it's.

1519
01:26:33,880 --> 01:26:34,479
Speaker 1: Not done done.

1520
01:26:34,680 --> 01:26:35,519
Speaker 3: It's not done done.

1521
01:26:35,600 --> 01:26:39,400
Speaker 1: But you think it's going to pass It already passed. No,

1522
01:26:39,520 --> 01:26:40,639
Speaker 1: but you think it's gonna become law.

1523
01:26:41,840 --> 01:26:45,479
Speaker 3: But it already. They're just in the rule making process now.

1524
01:26:46,880 --> 01:26:49,280
Speaker 1: Yeah, but I thought the rule making process would get

1525
01:26:49,520 --> 01:26:52,840
Speaker 1: so like that it wouldn't go, or people were thinking

1526
01:26:52,880 --> 01:26:53,439
Speaker 1: it wouldn't go.

1527
01:26:53,840 --> 01:26:56,000
Speaker 3: We'll see, we'll report on it next week.

1528
01:27:01,080 --> 01:27:02,000
Speaker 1: That one needs time.

1529
01:27:02,080 --> 01:27:03,400
Speaker 4: Couldn't have scripted it any better?

1530
01:27:03,520 --> 01:27:07,200
Speaker 1: Yeah, that one needs time? Yeah, okay, going over for

1531
01:27:07,280 --> 01:27:08,040
Speaker 1: our final story?

1532
01:27:09,400 --> 01:27:10,200
Speaker 2: Is our final story?

1533
01:27:12,040 --> 01:27:16,640
Speaker 1: Yeah right, yeah, going over for a final story. I

1534
01:27:16,760 --> 01:27:19,800
Speaker 1: heard a very interesting thing recently. My brother Danny up

1535
01:27:19,840 --> 01:27:24,080
Speaker 1: in Alaska has a buddy. My brother Danny works for

1536
01:27:24,080 --> 01:27:26,520
Speaker 1: the US Fish and Wildlife Service. He has a colleague

1537
01:27:28,760 --> 01:27:32,439
Speaker 1: who is a he'll he'll explain what he does. Well.

1538
01:27:32,960 --> 01:27:37,440
Speaker 1: I was hearing about learning about that one when imports

1539
01:27:37,520 --> 01:27:40,679
Speaker 1: come into the country. Right, there's a there's a customs

1540
01:27:40,800 --> 01:27:45,240
Speaker 1: process around processing imports, and and here's where you would

1541
01:27:45,240 --> 01:27:49,000
Speaker 1: look for like illegal wildlife imports, meaning things you could

1542
01:27:49,040 --> 01:27:51,280
Speaker 1: imagine like someone opens up a crate and they're like,

1543
01:27:51,400 --> 01:27:54,160
Speaker 1: good lord, it's full of rhino horns, Like that's gonna

1544
01:27:54,160 --> 01:27:57,080
Speaker 1: be a problem, right, But there are other things that

1545
01:27:57,160 --> 01:28:01,400
Speaker 1: you might not know about that that customs official look at.

1546
01:28:01,760 --> 01:28:04,920
Speaker 1: And US Fish and Wildlife Service when it comes to

1547
01:28:05,000 --> 01:28:08,360
Speaker 1: wildlife issues, that is there, that is their turf, okay.

1548
01:28:09,000 --> 01:28:10,880
Speaker 1: And I was learning about the thing I had no

1549
01:28:11,040 --> 01:28:15,360
Speaker 1: idea that it even existed, is that people make fake

1550
01:28:16,400 --> 01:28:21,839
Speaker 1: eyelashes out of mink fur. And since it's a wildlife product,

1551
01:28:21,920 --> 01:28:24,080
Speaker 1: it needs to be imported in a certain way. And

1552
01:28:24,160 --> 01:28:32,400
Speaker 1: I was learning about how wildlife officials will detect find

1553
01:28:32,720 --> 01:28:38,800
Speaker 1: and seese incoming fake eyelashes made of mink, which I

1554
01:28:39,000 --> 01:28:43,679
Speaker 1: feel are being worn by people who have no idea

1555
01:28:43,800 --> 01:28:51,639
Speaker 1: what they're wearing. Definitely not over to our guests, ready, Phil, Yeah, God,

1556
01:28:51,680 --> 01:28:52,599
Speaker 1: you didn't see that coming.

1557
01:28:53,240 --> 01:28:54,880
Speaker 7: And I thought there'll be a little bit more to

1558
01:28:54,960 --> 01:28:55,840
Speaker 7: do before we bring him in.

1559
01:28:55,920 --> 01:28:56,960
Speaker 2: But hey, he's here.

1560
01:28:57,880 --> 01:29:01,200
Speaker 6: Yeah, Like you know, women and fake eyelashes.

1561
01:29:02,680 --> 01:29:03,280
Speaker 4: History of that.

1562
01:29:03,640 --> 01:29:06,799
Speaker 1: But that's okay, Brian Olen. How's it going.

1563
01:29:09,960 --> 01:29:11,320
Speaker 10: O, good morning, Yeah, it's going well.

1564
01:29:11,439 --> 01:29:13,519
Speaker 11: I guess I should have worn some some eyelashes today,

1565
01:29:13,560 --> 01:29:16,120
Speaker 11: so I could have demonstrated that for you, but I

1566
01:29:16,360 --> 01:29:18,840
Speaker 11: didn't didn't include that in my morning routine.

1567
01:29:18,960 --> 01:29:22,960
Speaker 1: So you're forgiven. Lay this out for us, like like

1568
01:29:23,400 --> 01:29:27,880
Speaker 1: layout for us, what form these things take, how you

1569
01:29:28,240 --> 01:29:31,680
Speaker 1: know about them, where they come from. Whatever you got for.

1570
01:29:31,800 --> 01:29:34,559
Speaker 10: Us, gotcha.

1571
01:29:35,720 --> 01:29:38,559
Speaker 11: So yeah, I didn't know about them. Not surprisingly before

1572
01:29:38,560 --> 01:29:42,040
Speaker 11: I started this job about five years ago. We all

1573
01:29:42,080 --> 01:29:46,840
Speaker 11: know about fake eyelashes, but there is a pre significant

1574
01:29:47,600 --> 01:29:51,559
Speaker 11: quantity of them being made from mink, certainly also made

1575
01:29:51,600 --> 01:29:56,880
Speaker 11: from like silk and other synthetic materials. But they looked

1576
01:29:56,920 --> 01:29:59,920
Speaker 11: like just like a half moon or crescent moon shape,

1577
01:30:00,520 --> 01:30:05,680
Speaker 11: like adhesive strip with individual pieces of mink care I

1578
01:30:05,760 --> 01:30:07,040
Speaker 11: guess just attached or glued on.

1579
01:30:07,160 --> 01:30:07,320
Speaker 1: There.

1580
01:30:10,040 --> 01:30:13,160
Speaker 11: They're when you like do some research on them and

1581
01:30:13,200 --> 01:30:15,280
Speaker 11: say that they're they're more fluttery looking a little more

1582
01:30:15,360 --> 01:30:18,439
Speaker 11: naturally looking, the the mink hare ones versus the synthetic ones.

1583
01:30:20,280 --> 01:30:22,200
Speaker 11: So there's there's some ways you can kind of once

1584
01:30:22,240 --> 01:30:24,040
Speaker 11: you look at five or six hundred of these things,

1585
01:30:24,080 --> 01:30:25,960
Speaker 11: you can kind of tell them tell them apart pretty easily.

1586
01:30:26,040 --> 01:30:29,800
Speaker 11: But the mink care kind of tapers to a point,

1587
01:30:30,240 --> 01:30:33,040
Speaker 11: whereas like the synthetic materials are more like truncated and chopped.

1588
01:30:34,080 --> 01:30:35,559
Speaker 10: You can kind of tell that with the naked eye.

1589
01:30:37,200 --> 01:30:39,200
Speaker 10: But so, yeah, we're inspecting these.

1590
01:30:40,800 --> 01:30:42,880
Speaker 11: Kind of you know, it comes and goes in waves,

1591
01:30:42,960 --> 01:30:48,240
Speaker 11: but daily across the US and we're here in Anchorage, Alaska,

1592
01:30:48,360 --> 01:30:51,800
Speaker 11: so most of our imports are coming from from Southeast Asia.

1593
01:30:53,280 --> 01:30:56,200
Speaker 11: So yeah, we're we're looking at air cargo coming in

1594
01:30:56,520 --> 01:30:59,000
Speaker 11: and trying to trying to stop these and make sure

1595
01:30:59,000 --> 01:31:00,799
Speaker 11: they're imported in the direct manner.

1596
01:31:01,320 --> 01:31:03,360
Speaker 1: What would be the correct man or like they're not

1597
01:31:03,600 --> 01:31:09,519
Speaker 1: like a mink eyelash isn't necessarily illegal, it's just the

1598
01:31:09,560 --> 01:31:12,000
Speaker 1: way they're bringing them in. They're not declaring them as

1599
01:31:12,040 --> 01:31:13,799
Speaker 1: a wildlife product. Is that the problem?

1600
01:31:14,840 --> 01:31:20,200
Speaker 11: Yeah, Yeah, so mink art particularly highly protected. Like you

1601
01:31:20,320 --> 01:31:23,240
Speaker 11: mentioned rhyan o horn. Obviously they're not in the same level.

1602
01:31:23,880 --> 01:31:27,720
Speaker 11: Most of these are farmed mink, and so they just

1603
01:31:28,320 --> 01:31:32,080
Speaker 11: need to have a few things done. If you're commercially importing,

1604
01:31:32,160 --> 01:31:35,040
Speaker 11: you got to have an import permit from US and

1605
01:31:35,120 --> 01:31:38,280
Speaker 11: then yeah, you have to declare every shipment as it arrives,

1606
01:31:39,200 --> 01:31:41,560
Speaker 11: declare it to the genus and species, so we know what,

1607
01:31:42,240 --> 01:31:46,519
Speaker 11: oh what, what animal you're using and the quantity. So

1608
01:31:46,680 --> 01:31:51,080
Speaker 11: that's that's the biggest like violation for the mink eyelashes.

1609
01:31:51,120 --> 01:31:54,000
Speaker 11: Is there just failing to declare or failure to obtain

1610
01:31:54,040 --> 01:31:54,559
Speaker 11: a license.

1611
01:31:55,640 --> 01:31:55,760
Speaker 6: Uh?

1612
01:31:55,960 --> 01:31:58,759
Speaker 1: So do this for people. You told me how this works.

1613
01:31:58,880 --> 01:32:00,960
Speaker 1: But let's say someone's sitting that home right now and

1614
01:32:01,000 --> 01:32:05,680
Speaker 1: they're just curious if they're fake eyelashes are made of

1615
01:32:05,840 --> 01:32:09,400
Speaker 1: mink or not. Tell them the little tests you do

1616
01:32:09,640 --> 01:32:12,360
Speaker 1: to find out what exactly you're looking at.

1617
01:32:13,520 --> 01:32:13,760
Speaker 2: Sure.

1618
01:32:14,320 --> 01:32:17,000
Speaker 11: Yeah, So if you have a pair that maybe took

1619
01:32:17,040 --> 01:32:20,240
Speaker 11: off and you already wore once or twice, you can

1620
01:32:20,360 --> 01:32:24,439
Speaker 11: just take a match and burn part of that and

1621
01:32:25,600 --> 01:32:27,560
Speaker 11: to get a good whiff and see what it smells like.

1622
01:32:27,680 --> 01:32:32,400
Speaker 10: And if it smells like burned hair like or like petroleum.

1623
01:32:31,920 --> 01:32:34,320
Speaker 11: Plastic, that'll tell you right off the bat if it's

1624
01:32:34,400 --> 01:32:36,519
Speaker 11: if it's a natural product or a synthetic product.

1625
01:32:36,920 --> 01:32:39,960
Speaker 1: Huh. How many times if you had to get like

1626
01:32:40,040 --> 01:32:45,560
Speaker 1: you've been there five years, how many different times have

1627
01:32:45,760 --> 01:32:49,719
Speaker 1: you encountered mink eyelashes coming into your port?

1628
01:32:52,880 --> 01:32:56,080
Speaker 10: Hundreds? Oh yeah, hundreds.

1629
01:32:56,160 --> 01:33:00,479
Speaker 11: It's not every day anymore, but uh that these things

1630
01:33:00,560 --> 01:33:02,680
Speaker 11: kind of come and go in waves. So much of

1631
01:33:02,720 --> 01:33:06,360
Speaker 11: it is driven by like the fashion industry and what's popular.

1632
01:33:06,439 --> 01:33:08,360
Speaker 11: And I think right now we're kind of at like

1633
01:33:08,840 --> 01:33:11,960
Speaker 11: a lull at least in our port of what we're seeing.

1634
01:33:13,560 --> 01:33:16,280
Speaker 11: So maybe there's some you know, people are starting to

1635
01:33:16,360 --> 01:33:18,800
Speaker 11: realize that they are made of mink and they don't

1636
01:33:18,800 --> 01:33:21,360
Speaker 11: want that. But it seems like it's on a downward

1637
01:33:21,400 --> 01:33:26,320
Speaker 11: trend right now. But you know, like ten years ago

1638
01:33:26,400 --> 01:33:29,479
Speaker 11: it was probably tenfold amount of products coming in.

1639
01:33:30,160 --> 01:33:36,200
Speaker 1: You know, how fashion becomes self parody, like meaning a

1640
01:33:36,320 --> 01:33:40,680
Speaker 1: thing becomes fashionable and then it just tries to one

1641
01:33:40,800 --> 01:33:43,960
Speaker 1: up itself, right, like like a hole in your jeens

1642
01:33:44,240 --> 01:33:47,320
Speaker 1: that's fashionable, so someone then eventually it's that the whole

1643
01:33:47,400 --> 01:33:50,040
Speaker 1: front of your jeans is gone or there's holes from

1644
01:33:50,120 --> 01:33:54,639
Speaker 1: top to bottom because it's self parodies itself. Are mink

1645
01:33:54,720 --> 01:33:58,639
Speaker 1: eyelashes subtle or are they like you want to see

1646
01:33:58,720 --> 01:34:03,080
Speaker 1: big eyelashes? Check these out? Like, how would you rank

1647
01:34:03,160 --> 01:34:04,680
Speaker 1: a mink eyelash? Oh?

1648
01:34:05,320 --> 01:34:08,920
Speaker 11: Yeah, like on flutterly flutteriness, I'd say they're they're up

1649
01:34:08,960 --> 01:34:10,400
Speaker 11: there and they amount of flutter they have.

1650
01:34:11,400 --> 01:34:15,160
Speaker 1: So it's an exaggerated eyelash. It's like a big eyelash.

1651
01:34:15,720 --> 01:34:18,920
Speaker 11: Well at times it is, yes, but like there's so

1652
01:34:19,000 --> 01:34:22,640
Speaker 11: many variations that you'll see that smaller, more kind of

1653
01:34:22,840 --> 01:34:26,040
Speaker 11: petite ones and ones that are just comically large but

1654
01:34:26,439 --> 01:34:28,040
Speaker 11: got So you could.

1655
01:34:27,880 --> 01:34:31,160
Speaker 1: Be and still be wearing mink. You could be classy

1656
01:34:31,240 --> 01:34:32,840
Speaker 1: in mink, or you could be not in mink.

1657
01:34:33,000 --> 01:34:34,759
Speaker 10: Sounds like I think you'd be classy.

1658
01:34:35,520 --> 01:34:38,080
Speaker 1: Now here's another question, if you don't mind adding in

1659
01:34:38,200 --> 01:34:42,280
Speaker 1: on this, are you able to share with us a

1660
01:34:42,479 --> 01:34:48,800
Speaker 1: handful of other wildlife products that you've seen show up

1661
01:34:48,960 --> 01:34:52,599
Speaker 1: in your area of jurisdiction over your career there? Are

1662
01:34:52,640 --> 01:34:54,640
Speaker 1: you able to share some other examples of things that

1663
01:34:54,760 --> 01:34:58,400
Speaker 1: you might that your agency might find coming into Port

1664
01:34:58,840 --> 01:35:01,200
Speaker 1: and Anchorage ELASTICA sure.

1665
01:35:02,840 --> 01:35:04,840
Speaker 11: A lot of what we see is products we don't

1666
01:35:04,840 --> 01:35:08,760
Speaker 11: see too many live live animals. A lot of those

1667
01:35:08,800 --> 01:35:11,320
Speaker 11: are you know, they don't want their live animals to

1668
01:35:11,400 --> 01:35:14,160
Speaker 11: sit on the tarmac when it's like negative twenty out,

1669
01:35:14,640 --> 01:35:15,439
Speaker 11: I just don't survive.

1670
01:35:15,560 --> 01:35:16,120
Speaker 1: So you're not a.

1671
01:35:18,720 --> 01:35:22,320
Speaker 10: No, not typically, although we just had some yesterday. I

1672
01:35:22,439 --> 01:35:23,599
Speaker 10: can't talk about those too much.

1673
01:35:23,680 --> 01:35:27,280
Speaker 11: But in the past past years, like we had a

1674
01:35:28,439 --> 01:35:33,559
Speaker 11: a viper come in in a pringles can from Southeast

1675
01:35:33,600 --> 01:35:37,760
Speaker 11: Asia and that was that was a Yeah, that was

1676
01:35:37,760 --> 01:35:40,479
Speaker 11: an eye opener. So that's you know, like one of

1677
01:35:40,560 --> 01:35:45,280
Speaker 11: the more surprising Like, hey, but most of what we

1678
01:35:45,320 --> 01:35:52,920
Speaker 11: see is parts and products, feathers, shells, turtle products, turtle

1679
01:35:52,960 --> 01:35:57,080
Speaker 11: shell products, and occasionally live live animals like birds.

1680
01:35:58,640 --> 01:36:01,280
Speaker 4: Has a question, Steve, go ahead, right, we have all

1681
01:36:01,320 --> 01:36:06,360
Speaker 4: those products, how many of those are like banned outright

1682
01:36:06,560 --> 01:36:09,040
Speaker 4: versus how many of those are simply trying to slide

1683
01:36:09,080 --> 01:36:10,080
Speaker 4: in undeclared.

1684
01:36:11,560 --> 01:36:13,960
Speaker 11: Yeah, so that's that's part of our gig is to

1685
01:36:14,040 --> 01:36:16,240
Speaker 11: facilitate the legal trades. So we're there to find the

1686
01:36:16,320 --> 01:36:18,519
Speaker 11: real bad stuff, but also you know, help people do

1687
01:36:18,640 --> 01:36:25,840
Speaker 11: it legally. Most you know, like the real bad stuff

1688
01:36:25,840 --> 01:36:29,200
Speaker 11: we don't see super often, like the rhino horn, the

1689
01:36:32,240 --> 01:36:34,439
Speaker 11: elephant tusks, like we see that stuff, but it's it's

1690
01:36:34,520 --> 01:36:38,400
Speaker 11: pretty rare compared to like, oh, you're importing shell jewelry

1691
01:36:39,640 --> 01:36:41,880
Speaker 11: that has to be declared. So that's of course more common.

1692
01:36:41,920 --> 01:36:44,280
Speaker 11: The more common the animal, the more common we're seeing

1693
01:36:44,320 --> 01:36:44,519
Speaker 11: the thing.

1694
01:36:44,680 --> 01:36:47,639
Speaker 1: So are you often involved in the work of let's

1695
01:36:47,640 --> 01:36:52,360
Speaker 1: say someone's importing shell jewelry, does it fall on your

1696
01:36:52,439 --> 01:36:57,519
Speaker 1: agency to try to determine what is the genus and species,

1697
01:36:57,560 --> 01:37:00,160
Speaker 1: because I imagine it could be like very hard to

1698
01:37:00,240 --> 01:37:05,120
Speaker 1: figure out if it's polished shell, right, how you'd ever

1699
01:37:05,200 --> 01:37:08,160
Speaker 1: begin to understand like is it, what is it from?

1700
01:37:08,439 --> 01:37:10,280
Speaker 1: You know, where did it come from, and what did

1701
01:37:10,320 --> 01:37:10,840
Speaker 1: they make it with?

1702
01:37:11,800 --> 01:37:15,880
Speaker 11: Yeah, yeah, so it's it's upon the importer to declare

1703
01:37:15,880 --> 01:37:18,800
Speaker 11: it to the genus and species level, and they would

1704
01:37:18,880 --> 01:37:21,840
Speaker 11: rely on their exporter quite a bit for that. So

1705
01:37:21,920 --> 01:37:25,840
Speaker 11: it's not like it's not our position to determine that,

1706
01:37:25,920 --> 01:37:27,800
Speaker 11: but we do have to spend a lot of time

1707
01:37:29,880 --> 01:37:33,400
Speaker 11: trying to id things because the importers, you know, in

1708
01:37:33,680 --> 01:37:35,000
Speaker 11: illegal cases.

1709
01:37:34,680 --> 01:37:37,040
Speaker 10: They don't want to do that anyway. So we need

1710
01:37:37,120 --> 01:37:40,000
Speaker 10: to be able to do that to know that this

1711
01:37:40,160 --> 01:37:42,120
Speaker 10: might be a protected species or it may not be.

1712
01:37:43,720 --> 01:37:46,240
Speaker 1: Meaning someone could someone could try to bring in a

1713
01:37:46,320 --> 01:37:50,400
Speaker 1: thing that could be that they could be declaring it

1714
01:37:50,520 --> 01:37:55,760
Speaker 1: as something permissible, but you'd have the obligation of verifying

1715
01:37:56,000 --> 01:37:59,720
Speaker 1: that it was what they're saying it is exactly whether

1716
01:37:59,760 --> 01:38:02,920
Speaker 1: that intention a mistake or intentional. It could be a

1717
01:38:03,000 --> 01:38:04,000
Speaker 1: thing that would happen.

1718
01:38:04,920 --> 01:38:09,400
Speaker 11: Yeah, I like snake skins. You know there's there's protected snakes,

1719
01:38:09,400 --> 01:38:11,360
Speaker 11: and there's there's non protected stakes. So if you were

1720
01:38:12,080 --> 01:38:13,960
Speaker 11: wanting to try to sneak something in without permits, you

1721
01:38:14,040 --> 01:38:18,120
Speaker 11: might call it, you know, a water snake versus a

1722
01:38:18,200 --> 01:38:19,160
Speaker 11: ball python.

1723
01:38:18,960 --> 01:38:21,360
Speaker 1: Or something understood understood. You know what I didn't do

1724
01:38:21,400 --> 01:38:23,840
Speaker 1: a good job of when I when I started out, Brian,

1725
01:38:23,920 --> 01:38:26,439
Speaker 1: can you can you tell everybody what your you know,

1726
01:38:26,560 --> 01:38:29,840
Speaker 1: your agency, but also what your specific job title would be,

1727
01:38:29,960 --> 01:38:31,640
Speaker 1: like what is your what is your what is your

1728
01:38:31,720 --> 01:38:33,759
Speaker 1: I don't know, you know what's on your badge?

1729
01:38:34,680 --> 01:38:34,880
Speaker 10: Yeah?

1730
01:38:34,960 --> 01:38:37,559
Speaker 11: Yeah, So I'm a I'm a wildlife inspector. I worked

1731
01:38:37,600 --> 01:38:40,760
Speaker 11: for the Office of Law Enforcement, which is a law

1732
01:38:40,840 --> 01:38:44,280
Speaker 11: enforcement division of the US Fish and Wildlife Service, And

1733
01:38:44,400 --> 01:38:47,400
Speaker 11: so we work at all the ports of entry across.

1734
01:38:47,120 --> 01:38:47,759
Speaker 1: The US.

1735
01:38:49,040 --> 01:38:52,439
Speaker 11: And uh we combat the legal wildlife trafficking trade. And

1736
01:38:52,520 --> 01:38:54,719
Speaker 11: then like I said, facilitate the legal trade.

1737
01:38:56,080 --> 01:38:58,920
Speaker 1: Got it? And then you are you are based within?

1738
01:39:00,240 --> 01:39:02,240
Speaker 1: Are you within the Anchorage Airport? Like where do you

1739
01:39:02,280 --> 01:39:04,439
Speaker 1: Where do you sit right now? Yeah?

1740
01:39:04,600 --> 01:39:07,360
Speaker 11: So, uh me and I'm at the Anchorage Airport. We

1741
01:39:07,439 --> 01:39:11,639
Speaker 11: have an international side, so I'm at the office here today.

1742
01:39:11,680 --> 01:39:15,439
Speaker 11: We also have people over at sorting facility for like

1743
01:39:15,520 --> 01:39:19,400
Speaker 11: the air cargo so we get most of our most

1744
01:39:19,439 --> 01:39:21,600
Speaker 11: of our cargoes coming in from Southeast Asia on the

1745
01:39:21,760 --> 01:39:25,280
Speaker 11: on the air side of things. We also have outports

1746
01:39:25,479 --> 01:39:30,400
Speaker 11: that we cover for like the the the highways between

1747
01:39:30,479 --> 01:39:33,080
Speaker 11: Canada and in the US, like alcan Well, we'll cover

1748
01:39:33,200 --> 01:39:33,599
Speaker 11: that as well.

1749
01:39:34,200 --> 01:39:38,000
Speaker 1: Got one last question for you. Say a fellow went

1750
01:39:38,120 --> 01:39:41,439
Speaker 1: over to Africa and he did some hunting, and he

1751
01:39:41,600 --> 01:39:45,360
Speaker 1: lives in Anchorage, and he waits a million years and

1752
01:39:45,520 --> 01:39:48,519
Speaker 1: finally the stuff he got in Africa arrives for him.

1753
01:39:49,400 --> 01:39:50,559
Speaker 1: Do you get to take a peek?

1754
01:39:52,120 --> 01:39:55,240
Speaker 11: Yeah, yeah, just yesterday I was inspecting a shipment from

1755
01:39:55,280 --> 01:40:00,439
Speaker 11: South Africa. So yeah, even non commercial personal ship have

1756
01:40:00,560 --> 01:40:05,000
Speaker 11: to be declared. So they'll arrive on cargo and we'll

1757
01:40:05,040 --> 01:40:07,679
Speaker 11: go over there and make sure what they're declaring is accurate.

1758
01:40:08,320 --> 01:40:11,080
Speaker 11: If there's permits to collect, they'll collect those and stamp

1759
01:40:11,160 --> 01:40:12,960
Speaker 11: them and help them fill out paperwork.

1760
01:40:13,120 --> 01:40:14,200
Speaker 10: And yeah.

1761
01:40:14,320 --> 01:40:15,880
Speaker 11: Yeah, that's kind of a fun thing of our job

1762
01:40:15,960 --> 01:40:18,519
Speaker 11: is to kind of see that that exotic stuff coming in.

1763
01:40:19,280 --> 01:40:21,320
Speaker 1: You know what, I'm realizing he might be a very

1764
01:40:21,400 --> 01:40:26,559
Speaker 1: good trivia mm hmm. Contestant on Wildlife Questions a lot

1765
01:40:26,560 --> 01:40:31,840
Speaker 1: of analogy Wildlife Questions Brian asked, thanks for coming on

1766
01:40:31,960 --> 01:40:34,080
Speaker 1: the show and explaining all that to us. Man, I

1767
01:40:34,200 --> 01:40:36,360
Speaker 1: want to go get me a set of these eyelashes

1768
01:40:36,400 --> 01:40:39,400
Speaker 1: and put them on. We should have done that today.

1769
01:40:39,479 --> 01:40:40,439
Speaker 4: I thought about doing that.

1770
01:40:40,920 --> 01:40:42,800
Speaker 6: Yeah, there's some pictures in there.

1771
01:40:42,800 --> 01:40:48,360
Speaker 1: I don't know. All right, thank you very much, officer.

1772
01:40:48,400 --> 01:40:50,760
Speaker 1: Appreciate you taking the time to talk to us. I'm

1773
01:40:50,760 --> 01:40:53,240
Speaker 1: gonna start growing up to people lightening their eyelashes on

1774
01:40:53,360 --> 01:41:00,680
Speaker 1: fire and smelling all right, thank you very much. All Right,

1775
01:41:00,760 --> 01:41:03,040
Speaker 1: ladies and gentlemen, thanks for joining the News Show. Come

1776
01:41:03,080 --> 01:41:05,479
Speaker 1: on next week and you're gonna hear Brody talk all

1777
01:41:05,520 --> 01:41:07,920
Speaker 1: about a thing that I don't understand well because I

1778
01:41:07,960 --> 01:41:08,960
Speaker 1: thought it was something different.

1779
01:41:10,680 --> 01:41:13,599
Speaker 2: Okay, Brod, these guys were cut out for him.

1780
01:41:14,600 --> 01:41:18,800
Speaker 1: I thought the rule making process would prove so impossible

1781
01:41:18,880 --> 01:41:20,320
Speaker 1: that it was like some kind of problem.

1782
01:41:21,120 --> 01:41:24,200
Speaker 8: Let's hope that was that's what happens. But it's not

1783
01:41:24,360 --> 01:41:27,200
Speaker 8: officially lie yet. They gotta go through some stuff.

1784
01:41:27,320 --> 01:41:31,479
Speaker 3: Butioned.

1785
01:41:31,720 --> 01:41:35,880
Speaker 1: Just when you thought Colorado, the animal rights community in

1786
01:41:35,960 --> 01:41:40,639
Speaker 1: Colorado could not embarrass their state anymore, they do next

1787
01:41:40,720 --> 01:41:41,920
Speaker 1: week on the News Show.

1788
01:41:44,120 --> 01:41:55,240
Speaker 9: When you out into the sunset, I thought would never

1789
01:41:55,960 --> 01:42:07,800
Speaker 9: stop streaming. I thought I would never stop screaming your name.

1790
01:42:14,960 --> 01:42:17,800
Speaker 1: But I ran out of breath.

1791
01:42:18,080 --> 01:42:23,640
Speaker 5: So I took in some more, and I started

1792
01:42:24,120 --> 01:42:30,840
Speaker 9: To screaming, loud, screaming,