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Speaker 1: All right, suckers, We've been talking all the time about

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Speaker 1: our our live tour me Cal Yanni, A lot of

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Speaker 1: special guests, live tour coming up. Everything's sold out. We've

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Speaker 1: got two dates left. Got a lock at home April fifteen.

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Speaker 1: In April sixteen, April fifteen, Masa Arts Center, Mace, Arizona.

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Speaker 1: So it's like your Phoenix Market April sixteen, City National Grove, Anaheim, California.

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Speaker 1: Again Me the Lavine Eagle O cal Special guests, Me

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Speaker 1: Eater Live April fifteen, Masa Arts Center, Mace, Arizona, April sixteen,

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Speaker 1: City National Grove, Anaheim, California. Get your tickets. Let's finish

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Speaker 1: this thing up. This is me Eat. Your podcast coming

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Speaker 1: at you shirtless, severely, vot bitten and in my case,

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Speaker 1: underwear listening Hunt podcast, you can't partake anything presented by

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Speaker 1: on X. Hunt creators are the most comprehensive digital mapping

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Speaker 1: system for hunters. Download the Hunt app from the iTunes

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Speaker 1: or Google play store. Nor where you stand with on X.

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Speaker 1: I think listeners ought to know that that phild engineer

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Speaker 1: has uh, he's gotta like he's not good at starting

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Speaker 1: that timer. You might have to go back behind the curtain.

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Speaker 1: You might have to go back into the might have

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Speaker 1: to go back into the back into the resumes. We're

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Speaker 1: just talking about mountainlins and calsambo. What a mountline does

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Speaker 1: when it drops down into like a pen full alloments.

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Speaker 1: If I was a mountainlined, I would be allowed with specialists.

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Speaker 1: That big neck, hard hard to miss. You could be drunk,

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Speaker 1: a drunk cap, get drunk, no matter what. You're gonna

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Speaker 1: get it with the net with the neck like that,

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Speaker 1: That's what I would be a I would be allowed

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Speaker 1: with specialist mountainlin. Yeah, they really like to keep their

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Speaker 1: heads high too. Would I would quickly depopulate the nation.

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Speaker 1: Would be a lama uh and epidemic of a llama

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Speaker 1: losses uh. A couple of things, do you I don't

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Speaker 1: know if you guys. There's a couple of news things

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Speaker 1: I want to talk about before we before we get

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Speaker 1: into it. Um that's gotta be. I haven't like dug

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Speaker 1: into this yet, but Disney's redoing they're doing I don't know,

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Speaker 1: they're doing a live action Bambi remake. I was told

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Speaker 1: about this yesterday. I believe man um live action, So

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Speaker 1: it's gonna be like you know that that's that's stupid

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Speaker 1: thing they did with the lions talking like people. Yes,

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Speaker 1: they're lion king. Real showed me the intro to the

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Speaker 1: lion King deal and then he explained that it is.

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Speaker 1: They didn't variate or they didn't vary the story at all.

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Speaker 1: It's the exact same story from the animated the full

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Speaker 1: animated version. Yeah, but it's just like actual lions being like,

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Speaker 1: what's up man? Phil called it derbank, So that's gonna

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Speaker 1: be like a buck anna be like, well, it's tough, man,

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Speaker 1: because you got these these lions, you know, voiced by humans,

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Speaker 1: but with absolutely no human facial expressions. Just it's yeah,

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Speaker 1: but I mean, deer is decidedly less. A deer is

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Speaker 1: decidedly less, uh sort of facially active, So it's gonna

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Speaker 1: be even worse than the lions. I hope there's a

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Speaker 1: part of that movie where, um you ever see the

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Speaker 1: trail camp footage of deer eating baby birds out of nest.

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Speaker 1: I hope that's part of the movie. That would be

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Speaker 1: a good part of the movie. Um, I would kill

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Speaker 1: to be. I've helped out in in the movie world

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Speaker 1: on on one script as far as like hunting accuracies

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Speaker 1: and it's something you did some consulting. Yeah, the Last

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Speaker 1: of the Mohicans. No, it was The Revenant, all the

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Speaker 1: Walking Out, yeah, which I was all excited for me

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Speaker 1: because I was if you didn't with any of old movies,

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Speaker 1: I was gonna smack you VIP resumes. Uh yeah, but

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Speaker 1: that was for for my buddy Collin helping him. And

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Speaker 1: it's just like this dude like a horse dude. No,

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Speaker 1: he's not a horse dude. It was up in Whitefish. Yeah,

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Speaker 1: he's a white Fish Guy's not a horse dude. A

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Speaker 1: little bit like a wrangler. He used to wrangle horses

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Speaker 1: for movies. No, he just kind of looks like that

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Speaker 1: type of person though you met him once anyway, Well,

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Speaker 1: I met a dude one's named that who was a

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Speaker 1: horse wrangler for movies. Oh no, I lived up in

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Speaker 1: that neck of the woods. No. I always call this

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Speaker 1: guy a young McConaughey because just because it was hair

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Speaker 1: more than anyway. No different guys. Yeah, but the movie

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Speaker 1: world just they fight so hard against reality. Oh yeah,

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Speaker 1: Like it's just they'd want no part of it. You know.

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Speaker 1: Did you see that thing I did that g Q breakdown?

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Speaker 1: That was fantastic, So like GQ, Like GQ magazine, they

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Speaker 1: have this thing they do the breakdown, so you can

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Speaker 1: go watch like a Navy seal breaking down Navy seal

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Speaker 1: scenes and movies. There's a chef breaking down cooking scenes

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Speaker 1: and movies. There's no, no, no, no, there's many of them.

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Speaker 1: Alex Donold the Climber breaks down climbing scenes and movies.

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Speaker 1: I didn't want to breaking down tracking and hunting scenes

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Speaker 1: and movies. And leading up to what I was talking

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Speaker 1: to someone and I was like, man, why don't these

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Speaker 1: movie people like, why don't they hire a guy to

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Speaker 1: come in and be like no, no, no no, no, no, no,

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Speaker 1: you know, you should make it like this. That'll seem

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Speaker 1: more real. And he said, oh, they do. They just

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Speaker 1: don't listen to him. They like to have him around

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Speaker 1: just you know, just to be like, oh, man, I

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Speaker 1: wouldn't do it like that. You know what, you know,

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Speaker 1: you don't got a tape here with a machete. And

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Speaker 1: they're like, in this movie, we do plus like we said, uh,

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Speaker 1: the general uh way of doing things. That has changed

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Speaker 1: quite a bit because you look at the reality of

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Speaker 1: the Robert Redford, Jeremiah Johnson Elk shot like that Elk died,

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Speaker 1: you pointed out, and they took some heat. They took

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Speaker 1: some heat for it, and Robert Redford kind of like

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Speaker 1: justified and explained it. And then in mcgwayn's movie Ranchodi

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Speaker 1: looks grace film never made um. They you know, they

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Speaker 1: shoot a steer with a sharp's rifle. Um. And he

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Speaker 1: expressed to me that he was glad they don't do

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Speaker 1: it that way anymore. They bought a steer and shot it.

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Speaker 1: And when you watch the movie, if you're familiar with

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Speaker 1: any kind of hunting or farming or anything, when you're

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Speaker 1: watching the movie, there's no confusion. You watched Last and Mohicans,

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Speaker 1: it's like when they shoot a Deer's like that, dear,

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Speaker 1: I don't know what happened to that deer. It wasn't shot.

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Speaker 1: That was just I don't know what it went from

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Speaker 1: a live deer to a stuffed thing somersault Yeah, yeah,

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Speaker 1: like stuffed like they threw a stuffed animal through the woods, somersaulting. Yeah.

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Speaker 1: I imagine how for the amount of folks uh that

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Speaker 1: are on a film set, how some could it could

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Speaker 1: probably cast a shadow over production for a day. If

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Speaker 1: if you're not un familiar with watching the light fade

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Speaker 1: from something's eyes. Anyone with sensitivities might want to come

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Speaker 1: to work late today. You know, I don't know. I'm

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Speaker 1: about ready to quit talking about I don't know, Phil,

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Speaker 1: Let me ask you. It just has an impartial observer.

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Speaker 1: Do you think we should um cease covering severed finger

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Speaker 1: stories or no? Well, what has the feedback been like? More?

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Speaker 1: It's just we get flooded with severed finger stories and images.

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Speaker 1: Have you gotten anybody that's saying you're you're making me

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Speaker 1: gag while I listen to your podcast. They just send

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Speaker 1: us more and more graphics. I have pictures of severed

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Speaker 1: fingers that would curl your hair. Okay, well, I think

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Speaker 1: I said. I sent one of my wife and she

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Speaker 1: was genuinely mad at me for two days. I would

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Speaker 1: be too. It was about midnight, I was in a

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Speaker 1: different time zone and I sent her an image. No,

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Speaker 1: no explanation. This is an audio medium, though, so I

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Speaker 1: think you know, I think you're okay. I want to

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Speaker 1: post them to Instagram, but I feel like i'd get banished.

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Speaker 1: Oh yeah, for sure. You got sent the grinder one, right.

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Speaker 1: That's that is haunting, especially if you grind your own meat,

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Speaker 1: because the hand when it gets eventually cut out of

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Speaker 1: the grinder is very familiar, very familiar. Tend to knee chunks.

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Speaker 1: I might start a page, separate page on the dark

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Speaker 1: web before I get anyways. A couple more finger stories. First,

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Speaker 1: Jim halfl finger. That's the hell of a name actually,

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Speaker 1: speaking of severed grandfather severed his finger at the railroad railhouse.

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Speaker 1: Call them Granda half a finger from most of that's fantastic. Yeah,

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Speaker 1: it's unusual. Last name you have tell tell people your

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Speaker 1: job real quick. Swiss German. My lame name is Swiss German.

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Speaker 1: I'm the wildfe Science coordinator for AS in the game

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Speaker 1: Fish department. But you got your like, you're in there, man.

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Speaker 1: You mix it up. You write articles, listen to stuff,

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Speaker 1: monitor stuff, argue. It's all interesting. Um. I started being

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Speaker 1: interest in Jim because he sends so many clarifications and corrections.

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Speaker 1: I don't want to be that guy. No, No, not

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Speaker 1: at all. No, you do it very respectfully. Like we'll

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Speaker 1: get a lot of guys that like sending a cracktion

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Speaker 1: or two and you can just see over the months,

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Speaker 1: you'll see him just become very agitated. But they're not

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Speaker 1: getting the level of attention they want and then they

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Speaker 1: just turned and then they turned like they like hate

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Speaker 1: you but still listen and you want to be like

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Speaker 1: you could not listen. Um, it doesn't accrue to him.

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Speaker 1: But here, okay, this guy is talking about Uh, this

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Speaker 1: guy is talking about another great story. So this guy's um.

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Speaker 1: This guy got married and his best man's dad had

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Speaker 1: retired and started. I don't understand. Is he tired, retired

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Speaker 1: and move to a golf course and he would kill

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Speaker 1: time by mowing the lawn. I feel like it must

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Speaker 1: have been a spare job, not volunteer. Would you move

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Speaker 1: to a golf course and volunteer to mow the golf course?

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Speaker 1: Listen to my grandpa would volunteer and mow lawns out

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Speaker 1: of the golf course that he loved. I did not

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Speaker 1: understand it. But my buddies who were working out at

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Speaker 1: that golf course as like caddies. They loved it. They're like, yeah,

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Speaker 1: I saw your grandpa came by on the more work today.

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Speaker 1: I've been anti golf my whole life, but I'm huge.

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Speaker 1: I'm super pro golf now. I don't want to tell

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Speaker 1: people why. I don't want to tell people about what

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Speaker 1: what happened with me in the flip flat flasher. But

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Speaker 1: now we're like major golf supporters. At least it's green space.

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Speaker 1: I'm not a golfer, but a major golf supporter. I

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Speaker 1: support the golf industry. My dad always said, friends with

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Speaker 1: the golf industry. Hit the bone chase. It hit the

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Speaker 1: bone chase. It look at those simps out there, hit

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Speaker 1: the bone chase. It. Oh no, listen. I'm a golf supporter,

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Speaker 1: but I mean, and I love all golfers, and I

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Speaker 1: support all golf courses, but uh, it's a moronic sport. Um. Anyways,

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Speaker 1: this guy's ut moll on the golf course. You can

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Speaker 1: just picture this. So he's he's in a more it's

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Speaker 1: got a roll bar, and he's coming in and there's

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Speaker 1: a there's a pole with a guideline a guy cable

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Speaker 1: coming off of it. So he realizes that the roll

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Speaker 1: bar in the cable are gonna make contact, so he

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Speaker 1: he's got it. He breaks as he realizes, and he

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Speaker 1: reaches up to put some up pressure on the guyline

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Speaker 1: to clear it from the roll bar, but then his

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Speaker 1: foot slips off of the brake. Phil, can you put

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Speaker 1: in a good noise that sounds like this, but it's

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Speaker 1: like a right I mean, is that the sound of

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Speaker 1: flesh or the sound of like, what's what's happening here?

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Speaker 1: With that noise? That's the cable cutting his finger off. Combination.

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Speaker 1: I think the most disturbing part of all of these

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Speaker 1: is there's rarely a scenario where I don't see myself

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Speaker 1: having narrowly avoided that happening to me, or I can't

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Speaker 1: be like, oh, I can see how I would do that.

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Speaker 1: There's a great detail, he says that his the tendon.

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Speaker 1: There's a tendons find their way into these stories. The

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Speaker 1: tendon is someone sent us a picture of it. It's

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Speaker 1: like a finger with like sixteen inches attendant. Like the

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Speaker 1: tendant came off up at the elbow. But the tendon,

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Speaker 1: he said, is wrapped around the cable. This is he's

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Speaker 1: a good writer. He says. It's similar if you took

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Speaker 1: a ribbon and run it along a pair of scissors

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Speaker 1: to coil it up. That's how he's describing the coil

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Speaker 1: of the tendon. And this man then getting up there

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Speaker 1: and unwrapping his h unwrapping his finger from the cable.

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Speaker 1: Another good figure story. It is the last one for today.

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Speaker 1: There's two stories. One has nothing to do with fingers.

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Speaker 1: Guy was saying, his h his old man's welder, and

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Speaker 1: he had a big weald and glove on and his

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Speaker 1: super hot chunk of slag got down as well and

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Speaker 1: glove and lodged against his wedding ring. His wedding ring

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Speaker 1: got so hot that it burned a scar circle around

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Speaker 1: his finger. Now he doesn't wear a wedding rings. He's

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Speaker 1: got a scar circle instead. He's got a scar as

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Speaker 1: a wedding ring. And a story. Uh yeah, oh two

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Speaker 1: more things, man, I just said one more, but two more? Yeah? Shoot,

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Speaker 1: what do you think, Jim? You get bored? No? I

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Speaker 1: like finger stories. It's not even a finger story. No,

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Speaker 1: I'm not bored. All right, we're talking there to day

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Speaker 1: we had an episode. We're talking all dropping stuff down

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Speaker 1: ice holes, and this guy drops three fifty seven Smith

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Speaker 1: and Weston down down the ice hole, which is easy

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Speaker 1: to be like, why absolutely why? Like that is not

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Speaker 1: a common part of my He said it was stainless,

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Speaker 1: and so the real bummers. He couldn't get it with

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Speaker 1: a magnet. He sends in a video of him in

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Speaker 1: his ice house. He gets his ice house ripping hot

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Speaker 1: with the heat and he's in his ice house but

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Speaker 1: his swim trunks. He goes down the whole, can't find it,

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Speaker 1: comes back up and he looks in like rough shape. Man.

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Speaker 1: He gets warm back up again, his buddies filming, and

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Speaker 1: it looks at like a totally rough shape. And he

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Speaker 1: gets psyched up enough and dives back down here again

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Speaker 1: and comes out pretty much. His buddy's like reeling back

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Speaker 1: in with a rope tied around his ankle, and he's

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Speaker 1: got that pistol. He says they were toting it around

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Speaker 1: because they kept seeing wolves out on the ice. Oh

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Speaker 1: my gosh, pretty funny. Uh that's good, all right, Uh,

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Speaker 1: Jim halflefinger, let's start out with this. So you know,

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Speaker 1: I guess first off, tell people like what your sort

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Speaker 1: of scope is your your the scope of your life's

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Speaker 1: work as a wildlife guy. So I spent twenty two

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Speaker 1: years as a regional biologist and too sound for his

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Speaker 1: on the game Fish Department, And in the last four

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Speaker 1: years I moved to kind of a statewide position called

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Speaker 1: Wilife Science Coordinator. And the gist of that job is

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Speaker 1: to have someone kind of free floating that can do

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Speaker 1: some of the deep dives into science and and make

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Speaker 1: sure that we've got good science supporting the policies and

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Speaker 1: the decisions we make as an agency. So that's pretty unusual.

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Speaker 1: We'll have a state wilife agency too, to be I

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Speaker 1: think forward thinking enough to have someone like that to

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Speaker 1: make sure that we're providing a good scientific foundation and

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Speaker 1: the things we do. And your work, uh, I know

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Speaker 1: that just from talking about various issues around the country.

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Speaker 1: Inherently your work spreads beyond Arizona because wildlife issues don't

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Speaker 1: stop at state lines, right, Yeah. And one of the

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Speaker 1: biggest reasons I'm involving a lot of westwide stuff is

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Speaker 1: I'm mom. Also, there's an association of of twenty four

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Speaker 1: Western state wildlife agency, state and provincial wilife agencies, and

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Speaker 1: it's called the Western Association Official Wildlife Agencies, and they

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Speaker 1: get together twice a year and they have some subcommittees

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Speaker 1: and some working groups, and I've chaired I've been on

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Speaker 1: the Milder Working Group UH for more than twenty years now,

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Speaker 1: and I've char it for the last thirteen or fourteen years,

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Speaker 1: and so as a as a chair that oversees a

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Speaker 1: meal deer expert from each of those twenty four Western agencies.

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Speaker 1: We as a group and and me as the chair,

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Speaker 1: are real involved in all the Western migration stuff. You

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Speaker 1: had Matt Kaufman here and and Kevin Monty talking about

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Speaker 1: some of the stuff they're doing. I've been working with

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Speaker 1: Matt and Kevin UM actually an awful lot on a

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Speaker 1: lot of these things in the West. But that that

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Speaker 1: position to the Western Association, sharing that group really puts

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Speaker 1: me um involved and in the seat to do a

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Speaker 1: lot of things throughout the West too. Uh. I know

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Speaker 1: some of the bigger things you get involved in, like

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Speaker 1: you know, all your big game and your charismatic megafauna. Um.

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Speaker 1: How low down in the what's the smallest thing involved in? Well,

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Speaker 1: my twenty two years as a regional biologist, I was

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Speaker 1: in charge of three species of quail, Google's turkey restoration

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Speaker 1: um in southeastern Arizona, mountain, lion's big horn, sheep, pronghorn,

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Speaker 1: all of all of the hunted species is what I

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Speaker 1: dealt with, from big game to small game. That was

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Speaker 1: most of my career and it's really the last four

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Speaker 1: years or so that I've been doing primarily a lot

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Speaker 1: of big game, a lot of big game Western stuff.

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Speaker 1: UM various miscellaneous science support for the agency, and then

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Speaker 1: Mexican wolf recovery, which I've been involved in for the

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Speaker 1: last ten years, oh for a decade now, we'll get

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Speaker 1: to that a little bit. I know. That's a yeah,

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Speaker 1: and it's a constantly changing landscape. It is in minefield.

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Speaker 1: You might say, al right, first question, some quick hit

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Speaker 1: or topics for you. Um, and a lot of this

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Speaker 1: is inspired by feedback you've given us when questions emerge

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Speaker 1: on other shows. One of the things we've emailed about

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Speaker 1: was this, and we've we've touched on this, like news

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Speaker 1: reports about this or confusion about this is uh, there's this.

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Speaker 1: It seems to be this emerging idea that people are like, well,

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Speaker 1: if if hunters go out and they want to like

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Speaker 1: hunters want to get big bucks, right, hunters want to

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Speaker 1: shoot big box, they want to shoot big bighorn sheep,

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Speaker 1: they want to shoot big moves. If you go out

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Speaker 1: and selectively target big bucks, are you changing the evolutionary

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Speaker 1: path of the species, Meaning you're putting on you know,

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Speaker 1: you're putting a selective pressure against big antler dear, This

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Speaker 1: is an argument against trophy hunting, right, and that by

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Speaker 1: doing that, you're making them. You're driving them to become smaller, right,

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Speaker 1: all right, you're buying it, not buying it. No, with

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Speaker 1: with servants with a deer family there there's no evidence

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Speaker 1: of that at all. But this all came to light.

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Speaker 1: It's not even that new. It's just once in a

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Speaker 1: while a reporter will learn about it and write an

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Speaker 1: article about it and think they're the first one to

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Speaker 1: write about it. But it really call That's a good

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Speaker 1: way of expressing how things like this come up and

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Speaker 1: they and they stay alive like that. Um, someone thinks that, hey,

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Speaker 1: I just found out this new thing, but everybody's been

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Speaker 1: discussing it for seventeen years, which has been about the

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Speaker 1: case with this. In two thousand three, David Colton came

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Speaker 1: out at we're talking about severed fingers. You don't feel

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Speaker 1: that way, you know, we can keep doing that, keep

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Speaker 1: doing that. These guys think they discovered severed fingers. So

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Speaker 1: there was a there was a paper in two thousand

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Speaker 1: three that really lit the world on fire on this

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Speaker 1: whole topic. He didn't hear two thousand three, two thousand three,

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Speaker 1: that's all long and that's really the genesis of all

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Speaker 1: this recent kind of interests in that in that topic.

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Speaker 1: But they there was a there's a population on the

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Speaker 1: east side of the Alberta Rockies and it's separated from

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Speaker 1: the main part of the Rockies Bigne. It's called Ram

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Speaker 1: Mountain and it's a it's a really small little dot

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Speaker 1: out away from the rest of the sheep populations. I

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Speaker 1: gotta stop you. Okay, you mentioned with servants, but now

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Speaker 1: we're talking about yep cheap. Yeah, right, to help people

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Speaker 1: get through that, And I just I just mentioned servants

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Speaker 1: right off the bat to to almost dismissed that because

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Speaker 1: and we can talk about some of the reasons and

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Speaker 1: tell me what servants are too, just because it's a

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Speaker 1: deer family, so it's a moose and alcan deer and

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Speaker 1: and um anything in the deer family with basically with

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Speaker 1: antlers with a few exceptions. So so this whole idea

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Speaker 1: of trophy hunters ruining the gene pool, degrading the gene pool.

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Speaker 1: Some of the popular media called evolution in reverse that

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Speaker 1: has really been focused on big horn cheap or why

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Speaker 1: out cheap and and it all comes from this one isolated,

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Speaker 1: unique population called Ram Mountain and Alberta. And they did

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Speaker 1: some research on there and they reported in two thousand

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Speaker 1: three in Nature that hunters selecting the largest rams were

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Speaker 1: actually causing a genetic change in the population, so that

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Speaker 1: there was smaller and smaller rams uh in that population.

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Speaker 1: And then that same author even came out in two

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Speaker 1: thousand and eight and said, well, my work in two

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Speaker 1: thousand three really probably over exaggerated the genetic component of that.

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Speaker 1: There's really more nutrition um than I originally said in

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Speaker 1: that paper, but it was too late. The popular media

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Speaker 1: took that and just ran with it, and you saw it.

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Speaker 1: You saw it everywhere, and part of it was for

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Speaker 1: people who don't like hunting and people who don't like

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Speaker 1: trophy hunting. It was such an irresistible story. Trophy under

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Speaker 1: something negative about trophy hunters, and some people just love that,

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Speaker 1: and so trophy hunters are ruining the gene pool, and

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Speaker 1: all the popular media picked up on that. And then

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Speaker 1: there's even some scientists who don't like trophy hunting and

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Speaker 1: don't like hunting, and so they started looking at other

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Speaker 1: data set and and see if they could produce a

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Speaker 1: paper that looked something similar, And all the subsequent papers

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Speaker 1: that came out they would cite the Ram mountain information,

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Speaker 1: which were later found out to be over exaggerated in

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Speaker 1: the genetic component, and these and these other scientists would

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Speaker 1: speculate um sighting Ram Mountain and then speculate that this

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Speaker 1: may be happening in these other areas, and it may

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Speaker 1: be happening with all big game, may be happening with

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Speaker 1: all species worldwide that humans harvest, and so these other

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Speaker 1: papers were just full of speculation. But every time someone

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Speaker 1: published a paper to speculate, someone else could cite the

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00:21:32,280 --> 00:21:35,359
Speaker 1: speculative paper and the Ram Mountain paper, and these started

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Speaker 1: to build this body of speculation. And and now we're

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Speaker 1: starting to get back and apply some science to that

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Speaker 1: and find out that it's it's it may happen in

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Speaker 1: a few cases, but it's certainly not widespread. But it's

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Speaker 1: too late. The public has has seen the popular message

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Speaker 1: and aren't reading scientific papers. But the bottom line is

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Speaker 1: if selection is intensive enough, it can affect the gene

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Speaker 1: pool in the future. What you need to think about

395
00:22:01,359 --> 00:22:05,240
Speaker 1: is in what cases is selection intensive enough to actually

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00:22:05,359 --> 00:22:09,000
Speaker 1: change the gene pool in cheap or or deer or

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Speaker 1: any other species that we hunt. And the answer is

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00:22:11,840 --> 00:22:13,960
Speaker 1: it's a very rare case. And and the case on

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00:22:14,080 --> 00:22:17,440
Speaker 1: Ram Mountain was unique because it was isolated. The population

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00:22:17,520 --> 00:22:21,160
Speaker 1: swelled and bottlenecked a few times, which can affect the genetics.

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00:22:21,840 --> 00:22:24,600
Speaker 1: And also they had a hunting regime there where it

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Speaker 1: was an unlimited number of hunters could hunt that little

403
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Speaker 1: isolated mountain range the isolated mountain, but they had to

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Speaker 1: be four fifths curl before they were legal to harvest.

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Speaker 1: And so that's a situation where the rams that have

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Speaker 1: faster growing horns, better genetics, faster growing horns are going

407
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Speaker 1: to get truncated. They're gonna get taken out of the

408
00:22:41,119 --> 00:22:43,159
Speaker 1: field as soon as they hit four fifths. And so

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Speaker 1: that's the case where the rams that have faster growing

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Speaker 1: horns are going to be removed at a higher proportion

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Speaker 1: than rams of slower growing horns. So that was the

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Speaker 1: basis of this Coldman and so there's it's so theoretically

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Speaker 1: and in practice there it's not flawed that in certain

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Speaker 1: situations that can happen. We did some more recent search

415
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Speaker 1: with with Kevin Montiese Lab Taylor Lashar is a graduate student,

416
00:23:03,960 --> 00:23:07,520
Speaker 1: where we took state big horn sheep records, and state

417
00:23:07,520 --> 00:23:10,359
Speaker 1: records were important because we had horn measurements and we

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Speaker 1: also had ages on those rams, which is something the

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00:23:12,320 --> 00:23:14,919
Speaker 1: Boone Crockett, Pope and Young Rocket books don't have ages.

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Speaker 1: They just have measurements, and they don't they don't record

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Speaker 1: the number annually on a horn um not not Buona Crockett. No,

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Speaker 1: it's measurements, you know. They got their measurement system and

423
00:23:23,880 --> 00:23:26,360
Speaker 1: then on the data sheet there they can put um

424
00:23:26,520 --> 00:23:28,880
Speaker 1: age on some of the species. But I'm not sure

425
00:23:28,880 --> 00:23:31,880
Speaker 1: if they even do it with big horn sheet on there. Yeah,

426
00:23:31,880 --> 00:23:33,119
Speaker 1: and the problem too is you have to be like

427
00:23:33,160 --> 00:23:35,800
Speaker 1: pretty well trained. Yeah, it's not it's not that easy.

428
00:23:35,840 --> 00:23:37,840
Speaker 1: There's some there's some experience that goes into it. But

429
00:23:37,920 --> 00:23:41,800
Speaker 1: state agencies do record age and record some measurements, sometimes

430
00:23:41,800 --> 00:23:45,320
Speaker 1: full Boone Crockett, sometimes just basis plus the length of

431
00:23:45,320 --> 00:23:47,800
Speaker 1: the horn. And so we went to the state records

432
00:23:47,960 --> 00:23:50,000
Speaker 1: and got all the state records we could assembled into

433
00:23:50,040 --> 00:23:52,960
Speaker 1: a database where we had age and we had the

434
00:23:53,000 --> 00:23:55,560
Speaker 1: antler or the horn measurements, and then we were able

435
00:23:55,560 --> 00:23:58,800
Speaker 1: to analyze these the sheep records and we were able

436
00:23:58,800 --> 00:24:03,720
Speaker 1: to to accommodator neutralized the effective age because obviously the

437
00:24:03,720 --> 00:24:05,879
Speaker 1: older the ramble, the bigger the horns. And so you

438
00:24:05,960 --> 00:24:07,919
Speaker 1: got it in your analysis, you've you've got to be

439
00:24:07,960 --> 00:24:10,800
Speaker 1: able to UM look at that and fair at that

440
00:24:10,920 --> 00:24:13,760
Speaker 1: part of the analysis out. And then we're also able

441
00:24:13,760 --> 00:24:16,280
Speaker 1: to look at some UM in d v I index,

442
00:24:16,280 --> 00:24:19,480
Speaker 1: which is a greenness index of satellite imagery, and we

443
00:24:19,560 --> 00:24:22,399
Speaker 1: were able to look at at nutrition and environment and

444
00:24:22,440 --> 00:24:25,080
Speaker 1: how that affected horn size in these in these states

445
00:24:25,080 --> 00:24:27,600
Speaker 1: and in these populations, and and in the end, we

446
00:24:27,720 --> 00:24:32,960
Speaker 1: analyzed UM data from thirty five years from seventy two

447
00:24:33,320 --> 00:24:37,919
Speaker 1: different hunt units around North America UM and and in

448
00:24:37,960 --> 00:24:42,399
Speaker 1: the end we found that of those seventy two units UM,

449
00:24:42,440 --> 00:24:45,280
Speaker 1: seventy eight percent of them were either stable or the

450
00:24:45,280 --> 00:24:49,120
Speaker 1: horn size was increasing, so only even showed a decline.

451
00:24:49,119 --> 00:24:51,600
Speaker 1: Now we don't even know yet what that decline is,

452
00:24:51,640 --> 00:24:54,280
Speaker 1: but in those twenty two that declined, only half of

453
00:24:54,280 --> 00:24:58,960
Speaker 1: those had a hunt regime that even even could possibly

454
00:24:59,040 --> 00:25:01,560
Speaker 1: exert some kind of stuf the pressure. You know, sometimes

455
00:25:01,600 --> 00:25:04,359
Speaker 1: you can just look at a hunt system and and

456
00:25:04,080 --> 00:25:07,480
Speaker 1: like a complete permit system that Arizona has, where someone

457
00:25:07,560 --> 00:25:11,720
Speaker 1: just takes just one rams monge, so you're not you

458
00:25:11,760 --> 00:25:13,800
Speaker 1: don't have that kind of selective pressure like you have

459
00:25:14,160 --> 00:25:16,920
Speaker 1: if you have unlimited number of hunters creaming that horn

460
00:25:16,960 --> 00:25:19,159
Speaker 1: size at a certain level. And so even in the

461
00:25:19,160 --> 00:25:22,800
Speaker 1: twenty two where they weren't stable or increasing in horn length,

462
00:25:22,840 --> 00:25:25,880
Speaker 1: they were decreasing UM still about half of those could

463
00:25:25,920 --> 00:25:29,199
Speaker 1: even have possibly been due to some selective pressure. And

464
00:25:29,240 --> 00:25:32,520
Speaker 1: so the bottom line is, even in sheep, which is

465
00:25:32,560 --> 00:25:36,080
Speaker 1: the only species that this has really been um found

466
00:25:36,160 --> 00:25:39,560
Speaker 1: in a in a controlled setting, it's very unusual to

467
00:25:39,600 --> 00:25:42,280
Speaker 1: have that kind of hunting regime that that would actually

468
00:25:42,560 --> 00:25:45,280
Speaker 1: apply that selected pressure to cause kind of genetic changes.

469
00:25:45,480 --> 00:25:50,400
Speaker 1: And all this is confounded terribly with with nutrition. More nutrition,

470
00:25:50,400 --> 00:25:52,439
Speaker 1: and animal gets the bigger the horns and antlers. The

471
00:25:52,440 --> 00:25:54,920
Speaker 1: older the animal gets, the bigger the horns and antlers,

472
00:25:55,000 --> 00:25:58,200
Speaker 1: And and there's um all kinds of obstacles, which is

473
00:25:58,240 --> 00:26:00,399
Speaker 1: a paper you saw that I wrote, all kinds of

474
00:26:00,400 --> 00:26:03,440
Speaker 1: obstacles that get in the way of hunters actually affecting

475
00:26:03,480 --> 00:26:05,679
Speaker 1: the gene pool. And when the hunter goes out and shoots,

476
00:26:06,040 --> 00:26:08,200
Speaker 1: passes up a spike and shoots an eight point white

477
00:26:08,200 --> 00:26:12,240
Speaker 1: tailed buck in Iowa, technically that's selection because they passed

478
00:26:12,280 --> 00:26:14,359
Speaker 1: up one buck and they selected a bigger buck. But

479
00:26:14,480 --> 00:26:17,119
Speaker 1: you have to look at the intensity of selection. Is

480
00:26:17,160 --> 00:26:21,560
Speaker 1: that anywhere near um intensive enough to cause any genetic changes?

481
00:26:21,760 --> 00:26:23,680
Speaker 1: And you think about all of the other things that

482
00:26:23,720 --> 00:26:26,040
Speaker 1: are removing animals from the population that have nothing to

483
00:26:26,080 --> 00:26:28,800
Speaker 1: do with horn or antlers size. You have, for example,

484
00:26:28,800 --> 00:26:31,520
Speaker 1: a fawn crop, you lose half of the fonds every

485
00:26:31,560 --> 00:26:35,720
Speaker 1: year before their first birthday UH in general, and those

486
00:26:35,760 --> 00:26:38,919
Speaker 1: losses of half of that annual cohort have nothing to

487
00:26:38,920 --> 00:26:41,280
Speaker 1: do with horn or antlers size. You've got mountain lions,

488
00:26:41,320 --> 00:26:44,240
Speaker 1: you've got predators killing adults that have nothing to do

489
00:26:44,280 --> 00:26:47,440
Speaker 1: with antler size. And the idea that hunters going out

490
00:26:48,160 --> 00:26:50,840
Speaker 1: during daylight hours in the hunt unit they have a

491
00:26:50,880 --> 00:26:55,560
Speaker 1: permit for only able to take males. The fact that

492
00:26:55,640 --> 00:26:59,080
Speaker 1: the idea that they're affecting that entire gene pool, it's

493
00:26:59,119 --> 00:27:01,400
Speaker 1: just ludicrous that you would apply that kind of pressure.

494
00:27:01,680 --> 00:27:03,960
Speaker 1: That could happen in some cases and cheap, but it's

495
00:27:04,000 --> 00:27:06,800
Speaker 1: pretty rare. Well, there's some so much conflicting data out

496
00:27:06,800 --> 00:27:11,320
Speaker 1: there too as to how much we're actually even we

497
00:27:11,560 --> 00:27:14,840
Speaker 1: I guess hunters in certain cases are actually even affecting behavior.

498
00:27:15,520 --> 00:27:17,920
Speaker 1: Like you see all these white tail papers that come

499
00:27:17,920 --> 00:27:20,160
Speaker 1: out and it's like, well the bucks have gone nocturnal.

500
00:27:20,280 --> 00:27:24,080
Speaker 1: It's like, well, no, we tracked them and they do

501
00:27:24,160 --> 00:27:26,040
Speaker 1: just as much walking around during the day as they

502
00:27:26,080 --> 00:27:30,800
Speaker 1: do at night. I mean, honing effects behavior hugely. Oh

503
00:27:30,880 --> 00:27:33,800
Speaker 1: of game animals, But like you look at these clubs

504
00:27:33,880 --> 00:27:38,320
Speaker 1: situations right where it's like you got five guys hunting,

505
00:27:39,040 --> 00:27:43,639
Speaker 1: you know, a thousand acres. They're out there, maybe twenty

506
00:27:43,680 --> 00:27:47,320
Speaker 1: five days total between the five guys, and they all

507
00:27:47,359 --> 00:27:50,359
Speaker 1: have the same story as Joe Dude going out on

508
00:27:50,440 --> 00:27:53,040
Speaker 1: public land. It's like the deer are so educated. Yeah,

509
00:27:53,080 --> 00:27:55,879
Speaker 1: but it's generational to the mean they're raised by. I mean,

510
00:27:55,920 --> 00:27:58,920
Speaker 1: these are animals that spend a year with their mothers,

511
00:27:58,920 --> 00:28:00,720
Speaker 1: spend a year with her mother, who's spent a year

512
00:28:00,720 --> 00:28:03,399
Speaker 1: with her mother. There's a learned you know, there's learned response.

513
00:28:03,400 --> 00:28:05,159
Speaker 1: I mean you just go look at landscapes where you

514
00:28:05,280 --> 00:28:08,000
Speaker 1: always had hunting and then took it away. Oh that

515
00:28:08,160 --> 00:28:12,040
Speaker 1: that spot that we hunted or Eric Siegfried from on

516
00:28:12,119 --> 00:28:16,119
Speaker 1: acc and I hunted this year. It's this funky access

517
00:28:16,240 --> 00:28:18,520
Speaker 1: deal where you kind of have to get up on

518
00:28:18,560 --> 00:28:25,400
Speaker 1: this rock room and I swear to God or more

519
00:28:25,480 --> 00:28:29,280
Speaker 1: of the mule deer dose just walked below staring at

520
00:28:29,320 --> 00:28:32,399
Speaker 1: that rock room like they just were it locked on

521
00:28:32,440 --> 00:28:34,359
Speaker 1: it and when you and your body sneak in and

522
00:28:34,480 --> 00:28:37,639
Speaker 1: always hunt Yellowstone. I mean you always always act like

523
00:28:37,640 --> 00:28:40,480
Speaker 1: you hunted somewhere else. But I mean you guys are

524
00:28:40,560 --> 00:28:43,680
Speaker 1: really well in all right, you and your body well

525
00:28:43,680 --> 00:28:47,479
Speaker 1: better than anybody else. Um. Do you get frustrated by

526
00:28:47,520 --> 00:28:50,440
Speaker 1: the way stuffs covered in the media. It's gotta make

527
00:28:50,480 --> 00:28:53,280
Speaker 1: you mad. Not not even a scientist, it does. But

528
00:28:53,360 --> 00:28:55,040
Speaker 1: when you know the science, and the public is not

529
00:28:55,080 --> 00:28:57,320
Speaker 1: reading scientific papers, when you know the science and you

530
00:28:57,360 --> 00:29:00,520
Speaker 1: see something like that just catch fire and run away

531
00:29:00,560 --> 00:29:03,360
Speaker 1: in the popular media and it's not true and it's exaggerated,

532
00:29:03,400 --> 00:29:05,960
Speaker 1: and everything that you read is just full of errors,

533
00:29:05,960 --> 00:29:08,160
Speaker 1: and and that's what everybody, that's what most of the

534
00:29:08,160 --> 00:29:10,760
Speaker 1: general public readings. And there's like credible places that run

535
00:29:10,800 --> 00:29:13,400
Speaker 1: with it too. Like National Geographic could cover the piss

536
00:29:13,440 --> 00:29:15,720
Speaker 1: out of a story like that. They would never cover

537
00:29:15,840 --> 00:29:18,080
Speaker 1: the like when it wanted, being that it wasn't accurate,

538
00:29:18,320 --> 00:29:20,720
Speaker 1: they would have zero interest in it because they love

539
00:29:20,800 --> 00:29:23,400
Speaker 1: anything that can be like a little bit like put

540
00:29:23,440 --> 00:29:26,960
Speaker 1: a little taint down hunting. They love it. They go

541
00:29:27,040 --> 00:29:28,440
Speaker 1: out of their way to find it. They would never

542
00:29:28,440 --> 00:29:29,920
Speaker 1: be like, oh, you know what turns out that that

543
00:29:29,960 --> 00:29:33,000
Speaker 1: wasn't actually true. Um, I mean like like the bias

544
00:29:33,080 --> 00:29:35,640
Speaker 1: is so within the organization like that, Like the bias

545
00:29:35,720 --> 00:29:38,000
Speaker 1: is so severe, and like you look at this thing

546
00:29:38,040 --> 00:29:41,400
Speaker 1: that's going on with Donald Trump Jr. Right, he's doing

547
00:29:41,400 --> 00:29:44,880
Speaker 1: a fundraiser. He's doing a fundraiser where they're gonna go

548
00:29:44,960 --> 00:29:49,040
Speaker 1: hunt ducks and blacktail deer, and the media is covering

549
00:29:49,040 --> 00:29:52,760
Speaker 1: it like a trophy animal hunt. That's a hunting ducks

550
00:29:52,760 --> 00:29:56,400
Speaker 1: and blacktails. Is a trophy animal hunt? Now, well, it's

551
00:29:56,440 --> 00:29:59,960
Speaker 1: like that's how, that's how it's described that you guys

552
00:30:00,000 --> 00:30:05,280
Speaker 1: saw the UM so that i u c n UH

553
00:30:06,000 --> 00:30:10,080
Speaker 1: is a body that I pay attention to for a

554
00:30:10,160 --> 00:30:14,480
Speaker 1: lot of conservation up to date conservation facts and knowledge

555
00:30:14,480 --> 00:30:19,600
Speaker 1: and UM A lot of stories came out earlier or

556
00:30:19,720 --> 00:30:22,719
Speaker 1: late last year on how the i u c n

557
00:30:23,040 --> 00:30:27,040
Speaker 1: has determined that trophy hunting is this terrible thing and

558
00:30:27,080 --> 00:30:31,120
Speaker 1: it's killing these animal populations. And you start reading into

559
00:30:31,160 --> 00:30:34,200
Speaker 1: it and you not not bush hunting, not bush me hunting.

560
00:30:34,840 --> 00:30:39,200
Speaker 1: But the paper is they're like, well, this is a

561
00:30:39,560 --> 00:30:43,720
Speaker 1: something that was being researched and it's not even the conclusion.

562
00:30:45,120 --> 00:30:47,240
Speaker 1: Somebody just took it and ran this out. This is

563
00:30:47,280 --> 00:30:50,320
Speaker 1: not our finding. But nobody covered that story. It was

564
00:30:50,360 --> 00:30:53,480
Speaker 1: always here it is. That's a good pushback some letters.

565
00:30:53,560 --> 00:30:56,520
Speaker 1: I think I sent you something recently with the conservation

566
00:30:56,560 --> 00:31:00,080
Speaker 1: front Lines is a is an email um service you

567
00:31:00,440 --> 00:31:02,280
Speaker 1: can subscribe to free and they have some really good

568
00:31:02,320 --> 00:31:05,080
Speaker 1: information about some scientists have gotten together and some some

569
00:31:05,120 --> 00:31:08,480
Speaker 1: people in Africa have gotten together and representing local African communities,

570
00:31:08,480 --> 00:31:12,880
Speaker 1: and the African communities are saying, how dare western um

571
00:31:13,000 --> 00:31:17,640
Speaker 1: people take away our livelihood? You know, this is sustainable conservation,

572
00:31:17,720 --> 00:31:21,440
Speaker 1: it's funding conservations, funding our villages, and how how dare

573
00:31:21,520 --> 00:31:24,920
Speaker 1: someone sitting there white house someplace in the US and

574
00:31:24,920 --> 00:31:27,200
Speaker 1: and say this isn't a good thing. Yeah, it's like

575
00:31:27,240 --> 00:31:31,720
Speaker 1: the it's like left wing imperialism. Man, the band's going on.

576
00:31:33,760 --> 00:31:37,440
Speaker 1: It's like it's like it's like a softer, gentler imperialism.

577
00:31:37,760 --> 00:31:41,760
Speaker 1: Do you think the UK bands are kind of a

578
00:31:41,760 --> 00:31:45,920
Speaker 1: little long term guilt laden thing is from the days

579
00:31:46,000 --> 00:31:51,360
Speaker 1: of British imperialism where it's like, yeah, that's fine all

580
00:31:51,400 --> 00:31:54,680
Speaker 1: they're like they're like tacking a little like the old pendulum.

581
00:31:56,200 --> 00:31:58,560
Speaker 1: Um Chaine Mahoney asked me to be on the u

582
00:31:58,640 --> 00:32:01,840
Speaker 1: c N Sustainable Use and Livelihoods Committee, So that's one

583
00:32:01,840 --> 00:32:04,320
Speaker 1: of the committees that he chairs and real active with

584
00:32:04,400 --> 00:32:06,760
Speaker 1: and it's all about this. I like the i u

585
00:32:06,800 --> 00:32:11,440
Speaker 1: c N ratings. Yeah, um, I tend to. I tend

586
00:32:11,480 --> 00:32:13,720
Speaker 1: to um. I tend to eat a lot of things

587
00:32:13,720 --> 00:32:17,600
Speaker 1: that are of least concern. Yeah, exactly. I was recently

588
00:32:17,600 --> 00:32:20,560
Speaker 1: looking at the mountain lion um um they changed it.

589
00:32:20,560 --> 00:32:23,560
Speaker 1: It says that it's decreasing. It says that the populations

590
00:32:23,560 --> 00:32:25,320
Speaker 1: are decading. Yeah, I looked at that. I understand for

591
00:32:25,360 --> 00:32:28,240
Speaker 1: the mountainline, I don't understand that either. In fact, one

592
00:32:28,240 --> 00:32:30,880
Speaker 1: of the main paper they cite for that um is

593
00:32:30,920 --> 00:32:34,000
Speaker 1: someone I worked with with Mexican Wolf Recovery. I sent

594
00:32:34,120 --> 00:32:35,920
Speaker 1: him an email with a link to that, and since

595
00:32:35,960 --> 00:32:39,320
Speaker 1: they were citing their work, I just asked him what

596
00:32:39,320 --> 00:32:40,800
Speaker 1: what is that all about? And I haven't heard from

597
00:32:40,880 --> 00:32:42,600
Speaker 1: him yet, but they get it. They I feel that

598
00:32:42,640 --> 00:32:44,200
Speaker 1: the i u c N does a little bit play

599
00:32:44,240 --> 00:32:48,200
Speaker 1: a predictive game. But but even that would not line

600
00:32:48,560 --> 00:32:51,200
Speaker 1: predicting a decline when something's on an increase, How do

601
00:32:51,200 --> 00:32:55,600
Speaker 1: you predict? Yeah, so that that's just apparently wrong. Yeah,

602
00:32:55,640 --> 00:32:59,600
Speaker 1: we should say International Union for the Conservation of Nature. Yeah,

603
00:32:59,640 --> 00:33:02,120
Speaker 1: if you go, you know, the Wikipedia gives a lot

604
00:33:02,120 --> 00:33:03,720
Speaker 1: of ink to the i U c N. So if

605
00:33:03,760 --> 00:33:06,120
Speaker 1: you type in any species, like if you're going the

606
00:33:06,120 --> 00:33:10,000
Speaker 1: other day, we're looking at uh, we're looking at um

607
00:33:10,040 --> 00:33:12,360
Speaker 1: the long tailed weasel, So the i U c N

608
00:33:12,440 --> 00:33:15,320
Speaker 1: long tail weasel. It would have it like population of

609
00:33:15,400 --> 00:33:18,720
Speaker 1: least concern, which is the which is like the best

610
00:33:18,760 --> 00:33:21,120
Speaker 1: news the species can get. The thing you want is

611
00:33:21,120 --> 00:33:23,360
Speaker 1: to be in the least concern and it's it's great

612
00:33:23,400 --> 00:33:26,200
Speaker 1: at out over. I don't know how many designations, and

613
00:33:26,920 --> 00:33:30,840
Speaker 1: it's six. It's a spectrum there and there's like a

614
00:33:30,920 --> 00:33:34,440
Speaker 1: most concern and then a critical concern. There's extinct. I

615
00:33:34,440 --> 00:33:38,520
Speaker 1: think we're just yeah, okay, next question we have before

616
00:33:38,600 --> 00:33:40,200
Speaker 1: you've done some work with that. We talked about Vale

617
00:33:40,240 --> 00:33:42,560
Speaker 1: guys all damn time. He's a good friend of mine,

618
00:33:42,880 --> 00:33:47,160
Speaker 1: good friend twenty years. Uh. In fact, I brought Ben

619
00:33:47,200 --> 00:33:51,040
Speaker 1: O'Brien val guys bone broth recipe. That's Vale for it.

620
00:33:53,120 --> 00:33:57,000
Speaker 1: That's good Val guys. Okay, we talked. We've covered this before.

621
00:33:58,520 --> 00:34:01,160
Speaker 1: Val guys had a he took at ab at what

622
00:34:01,400 --> 00:34:03,960
Speaker 1: I don't know if I want to redo it. He

623
00:34:04,040 --> 00:34:06,000
Speaker 1: took a stab on how the mule deer came to be.

624
00:34:07,520 --> 00:34:10,040
Speaker 1: I presented this as some mule dear researchers, and they

625
00:34:10,080 --> 00:34:13,719
Speaker 1: were they were not titillated by it. They didn't even

626
00:34:13,719 --> 00:34:17,080
Speaker 1: want to take it on. It was like fanciful and

627
00:34:17,280 --> 00:34:21,440
Speaker 1: like not understandable. But it was this idea that for

628
00:34:21,840 --> 00:34:24,359
Speaker 1: I'm gonna do a short version, hold your thumb out

629
00:34:25,120 --> 00:34:28,200
Speaker 1: and as you get bored, start going down. I was

630
00:34:28,200 --> 00:34:30,160
Speaker 1: gonna start in the plio scene. So you're doing better,

631
00:34:31,360 --> 00:34:34,279
Speaker 1: I'm not going okay, if you know you were here,

632
00:34:34,320 --> 00:34:35,239
Speaker 1: what we could do. Let me try to do a

633
00:34:35,239 --> 00:34:38,640
Speaker 1: crash course and what I had read he floored to

634
00:34:38,640 --> 00:34:41,040
Speaker 1: this idea that three million years ago and the like

635
00:34:41,080 --> 00:34:43,560
Speaker 1: what is now the southeastern US, There's always been white

636
00:34:43,560 --> 00:34:45,680
Speaker 1: tailed deer Kelson, I'm still up. What you do? Bang

637
00:34:45,680 --> 00:34:49,600
Speaker 1: your thumb of the hammer. Your kid asked me that too,

638
00:34:49,600 --> 00:34:51,560
Speaker 1: and I gotta tell you the same thing. I don't

639
00:34:51,640 --> 00:34:58,479
Speaker 1: know it n fifty right there? Uh what was I saying? Oh? Yeah,

640
00:34:58,520 --> 00:35:00,160
Speaker 1: there's always been white tailed deer and was not the

641
00:35:00,160 --> 00:35:03,560
Speaker 1: southeastern US. We had this big wet, you know, period

642
00:35:03,600 --> 00:35:07,720
Speaker 1: of of of lush growth, and these deer colonized coast

643
00:35:07,719 --> 00:35:12,400
Speaker 1: to coast, colonized the mid continent from the east coast

644
00:35:12,400 --> 00:35:14,600
Speaker 1: of the US to the west coast. Then there was

645
00:35:14,600 --> 00:35:16,600
Speaker 1: a big dry period and the empty in the middle

646
00:35:16,640 --> 00:35:20,160
Speaker 1: emptied out, and these deer on the west that were

647
00:35:20,200 --> 00:35:24,080
Speaker 1: remained on the west coast gradually evolved into black tails.

648
00:35:25,000 --> 00:35:28,160
Speaker 1: Then there was another period where it was moist and

649
00:35:28,200 --> 00:35:32,520
Speaker 1: conditions were good, and this population of black tails moved east.

650
00:35:33,200 --> 00:35:35,959
Speaker 1: The white tails, which had retreated to the southeastern US,

651
00:35:36,040 --> 00:35:39,120
Speaker 1: had moved back west. They met along the Rocky Front,

652
00:35:39,760 --> 00:35:45,520
Speaker 1: the Rocky Mountain Front, had sex um and spawned hybridized,

653
00:35:45,800 --> 00:35:49,839
Speaker 1: and then there was another great retraction. Blacktails went back

654
00:35:49,840 --> 00:35:52,279
Speaker 1: to the coast, white tails went back down to the southeast,

655
00:35:52,600 --> 00:35:57,440
Speaker 1: and this lingering population of these hybridized. I think it

656
00:35:57,520 --> 00:36:02,239
Speaker 1: was black tailed bucks making love to white tail does um,

657
00:36:02,360 --> 00:36:05,880
Speaker 1: that's your mule dere um? Yeah, And they said, uh,

658
00:36:06,280 --> 00:36:09,000
Speaker 1: I presented to some mule deer people and and they

659
00:36:09,120 --> 00:36:14,680
Speaker 1: had a response kind of like uh, let's move on. Well,

660
00:36:14,880 --> 00:36:17,120
Speaker 1: there was some there was some There was a scientific

661
00:36:17,120 --> 00:36:19,480
Speaker 1: basis for val coming up with that theory, which has

662
00:36:19,480 --> 00:36:23,239
Speaker 1: been superseded by other genetic work that came along time

663
00:36:23,280 --> 00:36:25,400
Speaker 1: for you to tell us, like what's up with all

664
00:36:25,400 --> 00:36:27,399
Speaker 1: the deals? So that was that was basically I think

665
00:36:27,440 --> 00:36:30,480
Speaker 1: it was it was glacier's advancing and receding rather than

666
00:36:30,520 --> 00:36:33,280
Speaker 1: wet and dry. I think probably it was changing environment,

667
00:36:33,400 --> 00:36:36,560
Speaker 1: changing habitats that were calling again split. But but regardless,

668
00:36:36,600 --> 00:36:39,680
Speaker 1: that's basically the story that that Val came up with,

669
00:36:39,760 --> 00:36:41,560
Speaker 1: and and he did that for a reason because when

670
00:36:41,560 --> 00:36:44,719
Speaker 1: they start first started doing genetic work, they found out

671
00:36:44,840 --> 00:36:49,080
Speaker 1: that blacktailed deer have completely different mitochondrial DNA than mule

672
00:36:49,160 --> 00:36:51,720
Speaker 1: there yet their subspecies. So there's two kinds of DNA.

673
00:36:51,840 --> 00:36:53,920
Speaker 1: There's there's DNA in the nucleus and you get this

674
00:36:54,120 --> 00:36:56,160
Speaker 1: nuclear DNA and you get half of that from your mother,

675
00:36:56,200 --> 00:36:58,880
Speaker 1: half from your father. There's another kind of DNA floating

676
00:36:58,880 --> 00:37:02,120
Speaker 1: around in the sets outside the nucleus called mitochondrial DNA

677
00:37:02,480 --> 00:37:04,799
Speaker 1: mighticondra DNA you only get from your mother, so it's

678
00:37:04,840 --> 00:37:06,480
Speaker 1: like a clone. It comes from your mother and your

679
00:37:06,520 --> 00:37:09,520
Speaker 1: grandmother and her mother. Yeah, that's how they like contract

680
00:37:09,640 --> 00:37:13,080
Speaker 1: down sort of the you know, like all of Western

681
00:37:13,120 --> 00:37:16,239
Speaker 1: Europe theoretically track all of Western Europe to like a

682
00:37:16,280 --> 00:37:20,920
Speaker 1: female to an mitochondrial eve so so the mitochondria, so

683
00:37:20,920 --> 00:37:23,760
Speaker 1: you can you want to analyze both types of DNA,

684
00:37:23,920 --> 00:37:26,840
Speaker 1: and they yield different answers to different kinds of questions,

685
00:37:26,880 --> 00:37:31,240
Speaker 1: But initial mitochondrial DNA analysis showed you think about, really,

686
00:37:31,320 --> 00:37:33,920
Speaker 1: the two black tailed deer subspecies are just subspecies of

687
00:37:34,000 --> 00:37:37,560
Speaker 1: mule deer. They're all oticoles Hemionus some subspecies, and then

688
00:37:37,600 --> 00:37:40,160
Speaker 1: you have white tail, which for a different species Virginianus.

689
00:37:40,680 --> 00:37:42,799
Speaker 1: And yet when they looked at the mitochondrial DNA, they

690
00:37:42,800 --> 00:37:45,200
Speaker 1: found out that mule deer and white tailed deer have

691
00:37:45,320 --> 00:37:48,640
Speaker 1: basically the same mitochondrial DNA, which is bizarre because they're

692
00:37:48,680 --> 00:37:51,879
Speaker 1: different species and and both of them, including mule deer,

693
00:37:52,080 --> 00:37:54,840
Speaker 1: have different mitochondrial DNA from black tail, so blacktails have

694
00:37:54,880 --> 00:37:58,400
Speaker 1: this unique mitochondrial DNA. So Val took that just thinking

695
00:37:58,400 --> 00:38:03,040
Speaker 1: about that, Val said, well, could probably occur if female

696
00:38:03,160 --> 00:38:06,239
Speaker 1: if if black tailed deer bred with white tailed deer

697
00:38:06,640 --> 00:38:10,440
Speaker 1: and in the offspring brought in that wet white tail

698
00:38:10,480 --> 00:38:12,840
Speaker 1: deer might have condrial DNA. So if you had female

699
00:38:13,440 --> 00:38:16,000
Speaker 1: white tailed deer breeding with black tail males and they

700
00:38:16,040 --> 00:38:18,560
Speaker 1: spawned some kind of the hybrid mule deer, then all

701
00:38:18,560 --> 00:38:21,560
Speaker 1: those mulder would have the same mitochondrial DNA as the

702
00:38:21,560 --> 00:38:24,560
Speaker 1: white tail because because it comes to the female line,

703
00:38:24,560 --> 00:38:26,839
Speaker 1: and so it was female white tail, then mulder would

704
00:38:26,840 --> 00:38:30,560
Speaker 1: have that same mitochondrial DNA and black tails would be different.

705
00:38:31,719 --> 00:38:34,640
Speaker 1: And so that just going on that that was a

706
00:38:34,680 --> 00:38:37,799
Speaker 1: basis of that's what inspired that. That's what inspired it.

707
00:38:37,880 --> 00:38:40,160
Speaker 1: So it made sense at the time, but later on

708
00:38:40,360 --> 00:38:43,359
Speaker 1: more work, especially with nuclear DNA, that you get half

709
00:38:43,360 --> 00:38:45,160
Speaker 1: from your mother, half from your father. You look at

710
00:38:45,239 --> 00:38:49,880
Speaker 1: muled or nuclear DNA and and it's it's closely aligned

711
00:38:49,920 --> 00:38:53,000
Speaker 1: with black tails. Blacktail and mule deer are all closely associated,

712
00:38:53,360 --> 00:38:55,799
Speaker 1: and then white tails completely different. So if they really

713
00:38:55,800 --> 00:38:57,960
Speaker 1: were hybrids, then the mule deer, when you look at

714
00:38:57,960 --> 00:39:00,200
Speaker 1: the nuclear DNA, they would have about half for the

715
00:39:00,200 --> 00:39:03,000
Speaker 1: white tailed genome and about half of the blacktail genome.

716
00:39:03,200 --> 00:39:06,560
Speaker 1: But they don't. Mule deer and blacktailed deer evolved as

717
00:39:06,640 --> 00:39:09,879
Speaker 1: one group and then black tailed deer split off during

718
00:39:09,960 --> 00:39:11,880
Speaker 1: one of the advances of the ice ages over in

719
00:39:11,880 --> 00:39:15,280
Speaker 1: the Pacific coast. So there, okay, So in this version

720
00:39:15,320 --> 00:39:23,879
Speaker 1: of events, mule deer um predated black tails. Yes, yea

721
00:39:24,600 --> 00:39:28,240
Speaker 1: in that version, but here sick of white tail looks

722
00:39:28,400 --> 00:39:30,360
Speaker 1: or sick of blacktail looks so damn much like a

723
00:39:30,360 --> 00:39:34,399
Speaker 1: white tail. I know that that under growth and everything, well,

724
00:39:34,480 --> 00:39:37,280
Speaker 1: even like metatarsal glands. There's other things where the black

725
00:39:37,280 --> 00:39:39,880
Speaker 1: tailed deer actually looks like a hybrid, which makes it

726
00:39:40,000 --> 00:39:42,200
Speaker 1: is confusing as hell, because the black tailed deer looks

727
00:39:42,239 --> 00:39:44,840
Speaker 1: almost like it's got some white tail like characteristics. But

728
00:39:44,880 --> 00:39:48,759
Speaker 1: when you're at genetics, the blacktail can't be can't be

729
00:39:48,800 --> 00:39:51,880
Speaker 1: a hybrid between those two, and so it's got to

730
00:39:51,920 --> 00:39:55,080
Speaker 1: be convergent evolution where they they kind of acquire traits

731
00:39:55,080 --> 00:39:57,680
Speaker 1: that are similar even though they're not um like dragon

732
00:39:58,400 --> 00:40:00,280
Speaker 1: m We talked about this the other day. Dragonfly asanna

733
00:40:00,320 --> 00:40:03,520
Speaker 1: hummingbirds both fly. That doesn't mean their cousins yep. So

734
00:40:03,560 --> 00:40:06,040
Speaker 1: we did genetic analysis. We did some genetic analysis all

735
00:40:06,120 --> 00:40:09,080
Speaker 1: up and down the coast in black tails from California

736
00:40:09,160 --> 00:40:12,800
Speaker 1: up to Oregon, Washington, British Columbia, and then mid British Columbia.

737
00:40:12,840 --> 00:40:15,800
Speaker 1: It starts you start getting into Sitka blacktails up into Alaska,

738
00:40:15,840 --> 00:40:17,879
Speaker 1: and we had them all and analyze all of those

739
00:40:17,920 --> 00:40:22,000
Speaker 1: and and found the highest concentration of genetic diversity was

740
00:40:22,040 --> 00:40:25,040
Speaker 1: the coast of Oregon and Washington in blacktail deer both

741
00:40:25,120 --> 00:40:29,000
Speaker 1: subspecies of blacktail deer and and geneticis population geneticis will

742
00:40:29,040 --> 00:40:30,920
Speaker 1: tell you that where you have a focal point with

743
00:40:31,000 --> 00:40:34,400
Speaker 1: high genetic diversity right there, and then lower genetic diversity

744
00:40:34,480 --> 00:40:37,520
Speaker 1: rating out from that. That indicates that was the refugium,

745
00:40:37,640 --> 00:40:41,200
Speaker 1: that's the that's ground zero for that species or that animal.

746
00:40:41,520 --> 00:40:44,600
Speaker 1: And so likely the blacktail deer were isolated for a

747
00:40:44,600 --> 00:40:47,400
Speaker 1: long time during one of the many glacial advances and

748
00:40:47,480 --> 00:40:51,799
Speaker 1: receding over on that coast, and then gradually expanded out

749
00:40:51,840 --> 00:40:54,120
Speaker 1: from there with the receding of the glaciers. And so

750
00:40:54,120 --> 00:40:56,640
Speaker 1: so why does a sitka then look different than the

751
00:40:56,680 --> 00:40:58,640
Speaker 1: Colombian And I don't know the answer to why he

752
00:40:58,680 --> 00:41:00,799
Speaker 1: doesn't typically have a buy for hated antler like a

753
00:41:00,840 --> 00:41:05,520
Speaker 1: forked antler. Well, the mature could, but like they mean

754
00:41:05,560 --> 00:41:08,120
Speaker 1: that Washington, they tend to throw a rack a hell

755
00:41:08,120 --> 00:41:10,719
Speaker 1: of a lot like a white tail. They look they're small,

756
00:41:10,760 --> 00:41:12,560
Speaker 1: they're about the same side like that. The mature ones

757
00:41:12,600 --> 00:41:15,440
Speaker 1: will have the G two s. But sitkas have a

758
00:41:15,440 --> 00:41:18,360
Speaker 1: double white bib on their throat um. They're kind of

759
00:41:18,360 --> 00:41:21,560
Speaker 1: a different tail. They look real different. And that nobody

760
00:41:21,600 --> 00:41:24,120
Speaker 1: knows for sure what kind of separation there might have

761
00:41:24,160 --> 00:41:27,440
Speaker 1: been in some glacial period between Columbian black tail and

762
00:41:27,480 --> 00:41:31,480
Speaker 1: Sitka black tail. The sitka could just be a phenotypic

763
00:41:31,560 --> 00:41:34,719
Speaker 1: or a physical adaptation to that marine environment. Swimming and

764
00:41:34,760 --> 00:41:37,400
Speaker 1: living on islands in that kind of environment. It could

765
00:41:37,400 --> 00:41:41,240
Speaker 1: be adaptation and they're physically changing not so much because

766
00:41:41,280 --> 00:41:44,080
Speaker 1: of the separation. Nobody really knows that for sure. Do

767
00:41:44,120 --> 00:41:47,960
Speaker 1: you what's the refuge of the white tail? Like, like

768
00:41:48,040 --> 00:41:51,200
Speaker 1: how far back in time? Trying to think how to

769
00:41:51,200 --> 00:41:54,400
Speaker 1: express this question. If you had a time machine and

770
00:41:54,480 --> 00:41:57,319
Speaker 1: it said it like a random it just randomly throw

771
00:41:57,400 --> 00:42:00,960
Speaker 1: you back to randomize dates, and you wanted to set

772
00:42:00,960 --> 00:42:04,240
Speaker 1: a location on your time machine to maximize the chances

773
00:42:04,280 --> 00:42:06,359
Speaker 1: that you would stumble into a white tail, what would

774
00:42:06,360 --> 00:42:10,120
Speaker 1: you set Florida, Florida. Yeah, and there's a lot of

775
00:42:10,120 --> 00:42:12,400
Speaker 1: white tail fossils in Florida, in fact that they've been

776
00:42:12,400 --> 00:42:14,759
Speaker 1: hanging around there a long time. They have been. Yeah,

777
00:42:14,760 --> 00:42:16,960
Speaker 1: they've been in the place of seeing there's a there's

778
00:42:17,040 --> 00:42:20,760
Speaker 1: just a ton of of places seeing white tail fossils

779
00:42:20,760 --> 00:42:26,600
Speaker 1: in Florida. And actually brought you one ship. It's an

780
00:42:26,600 --> 00:42:28,920
Speaker 1: epicenter so that you can see that fossilized material and

781
00:42:28,960 --> 00:42:32,760
Speaker 1: that's just the just handed me a fossilized the bone

782
00:42:32,800 --> 00:42:36,560
Speaker 1: base from the skull so the pedicle, get the pedicle um,

783
00:42:36,680 --> 00:42:41,319
Speaker 1: the antler about inch and a half antler about an

784
00:42:41,360 --> 00:42:44,600
Speaker 1: inch of skull and it fields like stone and it

785
00:42:44,760 --> 00:42:48,400
Speaker 1: is stone. Yea. You know. The word pedicle comes from

786
00:42:48,520 --> 00:42:51,799
Speaker 1: George Bobin, famous antler researcher, George and and George and

787
00:42:51,840 --> 00:42:54,839
Speaker 1: his his father, Anthony and Anthony. They wrote a book

788
00:42:54,880 --> 00:42:57,200
Speaker 1: in nine called Horns Prong, Horns and Antlers and it's

789
00:42:57,239 --> 00:42:59,920
Speaker 1: like the Bible for Antler kind of antler science speaking

790
00:43:00,000 --> 00:43:05,280
Speaker 1: out um. But Anthony Bubinick Coin didn't coin the phrase pedicle,

791
00:43:05,320 --> 00:43:07,040
Speaker 1: but he told us how to pronounce it pedical. He

792
00:43:07,040 --> 00:43:10,359
Speaker 1: says it rhymes with medical. But Anthony Bubinick spoke about

793
00:43:10,400 --> 00:43:12,840
Speaker 1: six languages and English was like his fifth language. And

794
00:43:12,880 --> 00:43:14,719
Speaker 1: so I always think it's kind of funny that we're

795
00:43:14,760 --> 00:43:18,440
Speaker 1: all taking our pronunciation of from this guy who nobody

796
00:43:18,440 --> 00:43:21,399
Speaker 1: can understand when he spoke English. This is amazing, man.

797
00:43:21,440 --> 00:43:24,359
Speaker 1: This is out of Florida. Yeah, Florida. So this deer

798
00:43:24,400 --> 00:43:27,400
Speaker 1: was running around he bumped into masodons now and that's dated,

799
00:43:27,480 --> 00:43:32,839
Speaker 1: that's dated. Pleist to scene. Yeah. Jim. Also Broad's show

800
00:43:32,920 --> 00:43:38,520
Speaker 1: us a replica of a saber tooth tooth smile ad

801
00:43:38,560 --> 00:43:42,040
Speaker 1: on fake tal us his canine and smile. Ad On

802
00:43:42,200 --> 00:43:45,040
Speaker 1: is uh and this thing is leven inches long? Yeah,

803
00:43:45,400 --> 00:43:47,240
Speaker 1: smile and was not because they had a big smile

804
00:43:47,280 --> 00:43:50,160
Speaker 1: with those big tooth. The smile addon comes from. I

805
00:43:50,200 --> 00:43:51,920
Speaker 1: think it's meetly. I don't have how to pronounce it,

806
00:43:51,960 --> 00:43:55,799
Speaker 1: but it's Latin for double edged sword. I'd laugh. They

807
00:43:55,920 --> 00:43:58,239
Speaker 1: just jumped out. It's grabbed Phil. It would make a

808
00:43:58,320 --> 00:44:01,640
Speaker 1: bike ride to work a little bit eating, like you know,

809
00:44:01,680 --> 00:44:05,440
Speaker 1: I just killed him. I'd be like that, can you

810
00:44:05,480 --> 00:44:08,520
Speaker 1: believe that? Cow? That's what I would be. Moved real slow,

811
00:44:09,600 --> 00:44:12,760
Speaker 1: real slow. So Florida had a lot of white tails,

812
00:44:13,040 --> 00:44:19,600
Speaker 1: go ahead, caw. Florida also has the spring site where

813
00:44:19,640 --> 00:44:22,360
Speaker 1: they got all the fossils out of, including the giant

814
00:44:22,400 --> 00:44:28,160
Speaker 1: tortoise with not familiar with that giant tortoises that once

815
00:44:28,239 --> 00:44:32,680
Speaker 1: roamed what is now the United States, But they found

816
00:44:33,560 --> 00:44:39,160
Speaker 1: a tortoise shell in this spring in Florida that had

817
00:44:39,360 --> 00:44:43,200
Speaker 1: a spear point in it. I need to talk to

818
00:44:43,280 --> 00:44:45,760
Speaker 1: our I need to talk to our performer podcast guests.

819
00:44:46,800 --> 00:44:50,759
Speaker 1: So then you start digging into the actual paper. It's

820
00:44:50,800 --> 00:44:54,440
Speaker 1: like it was laying nearby. He was laying in the

821
00:44:54,480 --> 00:44:57,080
Speaker 1: shell as they brought the thing out, and they're like,

822
00:44:57,360 --> 00:45:00,480
Speaker 1: so it could be this, but very well would be this,

823
00:45:00,560 --> 00:45:05,360
Speaker 1: But then it's clear evidence of ceremonial turtles. This exactly.

824
00:45:05,400 --> 00:45:08,719
Speaker 1: It was a religious total. There was a paleontologist in

825
00:45:08,760 --> 00:45:12,080
Speaker 1: New Mexico that was knocking one of the arrow points,

826
00:45:12,160 --> 00:45:14,680
Speaker 1: knocking one of the little shoulders off and saying that

827
00:45:14,719 --> 00:45:17,680
Speaker 1: was indicative of Sandia man and and he wrote papers

828
00:45:17,680 --> 00:45:20,719
Speaker 1: and constructed this big because he always knocked the shoulder off.

829
00:45:20,800 --> 00:45:23,080
Speaker 1: But he but they found out later he would knocking

830
00:45:23,080 --> 00:45:25,160
Speaker 1: the shoulders off and saying it with diagnostic of this.

831
00:45:26,120 --> 00:45:28,400
Speaker 1: There's some bad that's some bad stuff. But he wasn't

832
00:45:28,440 --> 00:45:32,279
Speaker 1: doing it as a greater social experiment. Can I Can

833
00:45:32,320 --> 00:45:34,520
Speaker 1: I tell people what you were musing before we started

834
00:45:34,560 --> 00:45:37,480
Speaker 1: recording your observation about archaeology or is that just too hard?

835
00:45:37,680 --> 00:45:41,160
Speaker 1: That's fine, that's tell him yourself the truth. Yeah, truth

836
00:45:41,280 --> 00:45:43,480
Speaker 1: is hard. A friend of mine always call archaeology a

837
00:45:43,480 --> 00:45:46,200
Speaker 1: soft science because they just so much of it is

838
00:45:46,239 --> 00:45:48,120
Speaker 1: just made up. They'll find a toebone and then they'll

839
00:45:48,120 --> 00:45:50,280
Speaker 1: write a paper about what the home range was and

840
00:45:50,280 --> 00:45:52,680
Speaker 1: and what the color of the fur was. And unfortunately

841
00:45:52,680 --> 00:45:55,120
Speaker 1: there's just a lot of a lot of garbage. I

842
00:45:55,160 --> 00:45:58,000
Speaker 1: was looking into archaeological evidence of elk in Arizona, and

843
00:45:58,000 --> 00:46:00,520
Speaker 1: we're doing some Miriam Delk stuff. And and there was

844
00:46:00,520 --> 00:46:03,279
Speaker 1: a son who was a paleontologist and archaeologist and his

845
00:46:03,400 --> 00:46:06,440
Speaker 1: dad was too at the university, and he had forty

846
00:46:06,480 --> 00:46:11,239
Speaker 1: four thousand deer family bones out of this site in Arizona,

847
00:46:11,440 --> 00:46:13,600
Speaker 1: and he had like fourteen or so elk. And so

848
00:46:13,640 --> 00:46:16,120
Speaker 1: I was really interested in those elk specimens. And I

849
00:46:16,120 --> 00:46:18,080
Speaker 1: couldn't get ahold of the sun. But I talked to

850
00:46:18,120 --> 00:46:20,319
Speaker 1: the dad, and the dad says, all those were those

851
00:46:20,320 --> 00:46:22,080
Speaker 1: are big out icolio. So those are big meal there.

852
00:46:22,120 --> 00:46:23,920
Speaker 1: Those weren't elk. He didn't know what he was talking

853
00:46:23,960 --> 00:46:26,719
Speaker 1: about talking about his own son in his paper. So

854
00:46:26,920 --> 00:46:28,440
Speaker 1: there's a lot of that in there. And you just

855
00:46:28,480 --> 00:46:31,919
Speaker 1: got to really be skeptical and be cautious. He can't

856
00:46:31,960 --> 00:46:34,880
Speaker 1: read a paper and then just go, um, you know,

857
00:46:34,920 --> 00:46:38,480
Speaker 1: repeating it without some skepticism of thinking thinking about it.

858
00:46:38,560 --> 00:46:40,480
Speaker 1: When when I was when I was working on my Buffalo,

859
00:46:40,560 --> 00:46:44,000
Speaker 1: but um, it came up like I was came up

860
00:46:44,000 --> 00:46:47,520
Speaker 1: where I was reading about where there were accounts of

861
00:46:47,560 --> 00:46:53,400
Speaker 1: them occurring. And there's a lot of versions of why Buffalo,

862
00:46:53,440 --> 00:46:55,319
Speaker 1: New York became Buffalo New York. But you'll often read

863
00:46:55,320 --> 00:46:57,280
Speaker 1: in old books that, like, Buffalo New York was Buffalo

864
00:46:57,360 --> 00:46:59,840
Speaker 1: New York because someone had encountered Buffalo. I thought it

865
00:46:59,880 --> 00:47:05,080
Speaker 1: was the wings. Well, you know there's a I get

866
00:47:05,120 --> 00:47:06,239
Speaker 1: I think I get into it in the book hit

867
00:47:06,360 --> 00:47:08,560
Speaker 1: or explain or not. A bunch of different theories about

868
00:47:08,560 --> 00:47:11,319
Speaker 1: how it got the name, but it would not be

869
00:47:11,320 --> 00:47:13,680
Speaker 1: in that that. Sometimes you'll see distribution maps for where

870
00:47:13,719 --> 00:47:19,600
Speaker 1: buffalo roamed, bison bison bison roamed, and people have it

871
00:47:19,680 --> 00:47:22,759
Speaker 1: going up in New York. The range map. We'll go

872
00:47:22,840 --> 00:47:27,200
Speaker 1: up in New York and it comes from people included

873
00:47:27,239 --> 00:47:32,600
Speaker 1: because two skulls came out of some campsite, some excavation

874
00:47:32,640 --> 00:47:36,960
Speaker 1: of a campsite in New York, just the schools, and

875
00:47:37,120 --> 00:47:43,799
Speaker 1: both of them, uh had cultural markings on them, and

876
00:47:44,000 --> 00:47:47,480
Speaker 1: later people looked at it and thought were they living

877
00:47:47,480 --> 00:47:52,000
Speaker 1: here or did someone get some from someone and bring

878
00:47:52,000 --> 00:47:55,160
Speaker 1: them home? The same way copper that comes out of

879
00:47:55,160 --> 00:47:59,160
Speaker 1: Michigan's Upper Peninsula can be found anywhere in the Midwest

880
00:48:00,000 --> 00:48:03,160
Speaker 1: and trace back like people took stuff they thought stuff

881
00:48:03,239 --> 00:48:06,200
Speaker 1: was cool and brought home with them. Arizona parrot feathers

882
00:48:06,200 --> 00:48:08,440
Speaker 1: in Arizona and all kinds of things from Central Americas.

883
00:48:08,440 --> 00:48:11,359
Speaker 1: There was these big trade routes. And if you look

884
00:48:11,360 --> 00:48:15,160
Speaker 1: in the not the Last Elka North America book, I

885
00:48:15,160 --> 00:48:17,000
Speaker 1: think it was a one before it, or maybe it

886
00:48:17,040 --> 00:48:18,360
Speaker 1: was the last. No, it was the one before the

887
00:48:18,440 --> 00:48:21,000
Speaker 1: last one. And they show elk distribution all the way

888
00:48:21,040 --> 00:48:24,919
Speaker 1: down to Mexico City. And it's only because Montezuma had

889
00:48:24,960 --> 00:48:27,280
Speaker 1: some elk. He had a menagerie, he had a menagerie,

890
00:48:27,560 --> 00:48:30,000
Speaker 1: and he had some elk in the menagerie, and and

891
00:48:30,080 --> 00:48:32,600
Speaker 1: the people doing the distribution map to include Mexico City,

892
00:48:32,600 --> 00:48:34,880
Speaker 1: and in fact the elk really weren't in there. In

893
00:48:34,880 --> 00:48:42,160
Speaker 1: in Mexico, Cortez his his like recorders describe the first

894
00:48:42,400 --> 00:48:48,000
Speaker 1: the first bison ever witnessed by a European um was

895
00:48:48,080 --> 00:48:55,200
Speaker 1: probably in Montezumas menagerie witnessed by cortez expedition. And I

896
00:48:55,680 --> 00:48:59,000
Speaker 1: think that somehow and somehow they describe it as having

897
00:48:59,040 --> 00:49:02,640
Speaker 1: come from the north. Yeah, probably having come from the north,

898
00:49:02,719 --> 00:49:04,799
Speaker 1: and not that it lived there. The mealier was first

899
00:49:04,800 --> 00:49:11,480
Speaker 1: described um from the journals of u Laray, and he

900
00:49:11,520 --> 00:49:14,200
Speaker 1: first described what amelier looked like in the west, and

901
00:49:14,239 --> 00:49:16,879
Speaker 1: it was found out later that there was no such

902
00:49:16,960 --> 00:49:19,760
Speaker 1: person as Charles Lay, and that his journals were entirely

903
00:49:19,760 --> 00:49:22,560
Speaker 1: fabricated by someone they don't even know who, but entirely

904
00:49:22,600 --> 00:49:25,560
Speaker 1: fabricated the journals, taking pieces some of from Lewis and Clark,

905
00:49:25,800 --> 00:49:28,240
Speaker 1: some from different journals from explorers, and put it together

906
00:49:28,760 --> 00:49:31,040
Speaker 1: and and made up this story about Charles Lay, who

907
00:49:31,040 --> 00:49:33,240
Speaker 1: was in the West. He was captured by Sue Indians.

908
00:49:33,239 --> 00:49:35,920
Speaker 1: He was held captive for several years, um by the

909
00:49:36,000 --> 00:49:38,440
Speaker 1: by the tribe, and during that time he kept a

910
00:49:38,520 --> 00:49:42,200
Speaker 1: journal because and it was only because Western literature was

911
00:49:42,280 --> 00:49:45,680
Speaker 1: really popular. This is some late eighteen hundreds. I think

912
00:49:45,800 --> 00:49:48,880
Speaker 1: Western literature is really popular, and being held captive by

913
00:49:48,960 --> 00:49:51,960
Speaker 1: Native American tribes was like a really hot story. So

914
00:49:52,000 --> 00:49:54,359
Speaker 1: this guy just fabricated this whole thing. And so you'll

915
00:49:54,360 --> 00:49:56,680
Speaker 1: read even some of my early writings we were talking

916
00:49:56,719 --> 00:50:00,480
Speaker 1: about Charles Lay described the first meal. Dear, turns out

917
00:50:00,480 --> 00:50:06,120
Speaker 1: it's just christated. Everybody keeps repeating it over and over again. Well,

918
00:50:06,120 --> 00:50:09,000
Speaker 1: when we're talking ahead of this, um came right at

919
00:50:09,000 --> 00:50:11,680
Speaker 1: some point in time, you'd mentioned that you wanted to

920
00:50:11,719 --> 00:50:14,840
Speaker 1: discuss Elliott cous But let me tee that off with.

921
00:50:16,160 --> 00:50:18,759
Speaker 1: Do you accept ioul, like, who's your kind of one

922
00:50:18,760 --> 00:50:22,800
Speaker 1: of my favorite animals by far, definitely probably maybe first

923
00:50:22,880 --> 00:50:24,880
Speaker 1: or second favorite thing to go hunting for it maybe

924
00:50:24,880 --> 00:50:29,520
Speaker 1: third Turkey's mulder in white tail, I'm sorry, Turkey's mule deer.

925
00:50:30,280 --> 00:50:32,440
Speaker 1: Who's dear? In my mind depends what time of year

926
00:50:32,440 --> 00:50:34,000
Speaker 1: it is, which one of those is my favorite thing

927
00:50:34,040 --> 00:50:37,759
Speaker 1: to hunt. But our cu'se dear, like, do you accept

928
00:50:38,200 --> 00:50:40,680
Speaker 1: or what's the thinking? They're like a subspecies of the

929
00:50:40,680 --> 00:50:42,600
Speaker 1: white tales. They're just white tails and it happened to

930
00:50:42,640 --> 00:50:45,400
Speaker 1: be somewhere else. Yeah, there's no doubt there are subspecies

931
00:50:45,440 --> 00:50:48,120
Speaker 1: that that really evolved differently because they were in the

932
00:50:48,160 --> 00:50:51,680
Speaker 1: Sierra Madre of Mexico, and so they were really geographically

933
00:50:51,719 --> 00:50:55,279
Speaker 1: fairly isolated from the Sierra Madre. That's deer, okay, Yeah,

934
00:50:55,360 --> 00:50:57,320
Speaker 1: I mean when you get down, you get about halfway

935
00:50:57,360 --> 00:50:59,839
Speaker 1: down the Sierra Madre and they start getting all these

936
00:50:59,840 --> 00:51:02,920
Speaker 1: other subspecies names. But nobody's really done science on that

937
00:51:02,960 --> 00:51:05,400
Speaker 1: at all. We've got a small white tail throughout the

938
00:51:05,440 --> 00:51:08,160
Speaker 1: highlands of Mexico and none of them are probably any different,

939
00:51:08,440 --> 00:51:11,239
Speaker 1: probably basically Cole's dear all the way down through the

940
00:51:11,239 --> 00:51:14,520
Speaker 1: Sera Money cows dear man. Yeah, didn't you didn't you hear?

941
00:51:14,800 --> 00:51:17,120
Speaker 1: Didn't you hear? Yanni? A couple of weeks ago. You

942
00:51:17,120 --> 00:51:19,200
Speaker 1: guys know that you were a cow's dear man. This

943
00:51:19,239 --> 00:51:20,799
Speaker 1: is the first cow's dear man we've ever had in

944
00:51:20,840 --> 00:51:23,560
Speaker 1: this room. I had my fifteen minutes of fame a

945
00:51:23,560 --> 00:51:25,799
Speaker 1: couple of weeks ago, and Yanni said, there's like one

946
00:51:25,840 --> 00:51:30,600
Speaker 1: guy that says Cole screw him. That's my fifteen minutes.

947
00:51:30,640 --> 00:51:35,080
Speaker 1: They mentioned me mentioned, well, here's the deal, Elliot, cows.

948
00:51:35,120 --> 00:51:37,040
Speaker 1: That's how you pronounce it. And that's not what I heard.

949
00:51:37,560 --> 00:51:41,160
Speaker 1: You heard wrong. I already pronounced it cows. Yeah, that's

950
00:51:41,440 --> 00:51:45,720
Speaker 1: you know where that comes from? Chris Denham, Probably Chris Denham.

951
00:51:46,120 --> 00:51:49,680
Speaker 1: Chris Denham read um something Richard ockin Fells wrote, and

952
00:51:49,760 --> 00:51:52,960
Speaker 1: Richard ockin Fell's rights In his annotated bibliography of Kyle's

953
00:51:52,960 --> 00:51:56,080
Speaker 1: White Tail, he writes, it's it rhymes with house. And

954
00:51:56,120 --> 00:51:58,600
Speaker 1: I asked, I'm friends with I've known Richard for twenty years.

955
00:51:59,000 --> 00:52:00,560
Speaker 1: As Richard, where that come him? He said, well, I

956
00:52:00,600 --> 00:52:04,839
Speaker 1: talked to Neil Carmeny and um, and I visit Neil

957
00:52:04,880 --> 00:52:06,880
Speaker 1: Carmeny in the nursing home in Tucson every couple of

958
00:52:06,920 --> 00:52:09,200
Speaker 1: months I've been I've known for twenty five years. I

959
00:52:09,239 --> 00:52:11,239
Speaker 1: asked Neil, where does that come from? The cows and

960
00:52:11,280 --> 00:52:14,120
Speaker 1: he says, I know, we knew somebody that um spoke

961
00:52:14,200 --> 00:52:16,080
Speaker 1: some French. And he says, that's probably how it's pronounced.

962
00:52:16,120 --> 00:52:18,240
Speaker 1: So that's where that's where that cows thing came from.

963
00:52:18,560 --> 00:52:21,759
Speaker 1: Completely bogus. There's no question how to pronounce his name.

964
00:52:21,800 --> 00:52:24,640
Speaker 1: There's a huge question on how people want to refer

965
00:52:24,719 --> 00:52:27,279
Speaker 1: the deer. That's maybe different. Yeah, I think that those

966
00:52:27,280 --> 00:52:30,919
Speaker 1: two subjects have their own evolutionary path they do. Okay,

967
00:52:30,960 --> 00:52:33,000
Speaker 1: we go on, you calling whatever the hell you want, ladies, gentlemen.

968
00:52:33,360 --> 00:52:36,520
Speaker 1: If our guest here says cow was dear, he's referring,

969
00:52:36,560 --> 00:52:41,560
Speaker 1: of course, to you, cou's dear. It's really sad. I

970
00:52:42,400 --> 00:52:48,680
Speaker 1: nowhere in I would say linguistical or dud logical history,

971
00:52:49,000 --> 00:52:52,440
Speaker 1: do I know of a word where we're after learning

972
00:52:52,440 --> 00:52:56,359
Speaker 1: how to pronounce it correctly of the public not only

973
00:52:56,400 --> 00:53:00,680
Speaker 1: refuses to, but militantly refuses people. They I die, Yeah,

974
00:53:00,719 --> 00:53:03,280
Speaker 1: they get you know, he has riled up the most

975
00:53:04,840 --> 00:53:07,719
Speaker 1: cows your people. I would call him Cole, I called listen.

976
00:53:07,719 --> 00:53:09,640
Speaker 1: I call him cause you for a simple reason. The

977
00:53:09,680 --> 00:53:11,759
Speaker 1: people that introduced me to him and that I hung

978
00:53:11,760 --> 00:53:13,680
Speaker 1: out with and hunted him with first, that's what they

979
00:53:13,719 --> 00:53:16,200
Speaker 1: called him. I actually had Jay Scott's sake Cows on

980
00:53:16,280 --> 00:53:18,080
Speaker 1: his podcast one time. When I was on it, I

981
00:53:18,160 --> 00:53:20,319
Speaker 1: was like, did you just say what I thought you said?

982
00:53:20,680 --> 00:53:23,320
Speaker 1: So there's also like, um, you know, there's a spirited

983
00:53:23,320 --> 00:53:28,359
Speaker 1: debate around ska sitka, which confuses people because I think

984
00:53:28,360 --> 00:53:32,759
Speaker 1: sick of black tails. Anyhow, Elliot Cows Elliott Cow now

985
00:53:33,680 --> 00:53:37,239
Speaker 1: to put the name pronunciation to bed Elliot Cows. When

986
00:53:37,239 --> 00:53:39,759
Speaker 1: he wrote the Checklist of Birds in North America, he

987
00:53:39,760 --> 00:53:42,080
Speaker 1: added a footnote he was an ornithologist. He was mostly

988
00:53:42,080 --> 00:53:44,800
Speaker 1: an ornithologist. He never killed a deer. Someone named the

989
00:53:44,800 --> 00:53:47,680
Speaker 1: deer after him, so he wasn't really wasn't a dear guy.

990
00:53:47,800 --> 00:53:50,280
Speaker 1: He was really good ecologist. But he wrote the Checklist

991
00:53:50,320 --> 00:53:52,520
Speaker 1: of Birds in North America. And he has a footnote

992
00:53:52,840 --> 00:53:55,640
Speaker 1: where he explains how to pronounce his name. No he

993
00:53:55,719 --> 00:53:58,239
Speaker 1: does it says C and he says c O w

994
00:53:58,560 --> 00:54:02,600
Speaker 1: Z house. That's a lie, not a lie in black

995
00:54:02,600 --> 00:54:05,280
Speaker 1: and wh okay, here's a twitter. Hell makes a footnote

996
00:54:05,280 --> 00:54:06,960
Speaker 1: in their book about how to pronounce their last name.

997
00:54:06,960 --> 00:54:08,920
Speaker 1: It was a footnote on a bird species that was

998
00:54:08,960 --> 00:54:13,239
Speaker 1: also Cowsy I species. So he was explaining where that

999
00:54:13,320 --> 00:54:15,040
Speaker 1: where that name came from, and it was he was

1000
00:54:15,080 --> 00:54:17,600
Speaker 1: writing the book and he was explaining how his name

1001
00:54:17,640 --> 00:54:19,879
Speaker 1: was pronounced, but kind of pretentious. Okay, so you're right,

1002
00:54:20,080 --> 00:54:24,359
Speaker 1: you're right, it's Cole's right from Elliott cows Mouth. You're right,

1003
00:54:25,200 --> 00:54:30,400
Speaker 1: but we're talking about the deer. Yeah, we're talking about

1004
00:54:30,920 --> 00:54:38,000
Speaker 1: he's right. But so yeah, so say that there was

1005
00:54:38,040 --> 00:54:41,000
Speaker 1: someone who was who just had made huge contributions to

1006
00:54:41,640 --> 00:54:45,600
Speaker 1: outdoor education entertainment, had a podcast, had a TV show,

1007
00:54:46,360 --> 00:54:49,399
Speaker 1: and did so much for the industry that some dear

1008
00:54:49,440 --> 00:54:54,080
Speaker 1: biologists wanted to name a subspecies after him. Dear Odiocolius

1009
00:54:54,080 --> 00:54:56,800
Speaker 1: hemi owners for Nolla. And then so we go in

1010
00:54:56,880 --> 00:54:58,719
Speaker 1: the Cal's Deer. You and I go on the time

1011
00:54:58,760 --> 00:55:01,319
Speaker 1: machine and we go a hundred years in the future

1012
00:55:01,320 --> 00:55:02,680
Speaker 1: and we get out and we talked some deer hunters

1013
00:55:02,719 --> 00:55:05,400
Speaker 1: and they're talking about, yeah, we're all jack because we

1014
00:55:05,480 --> 00:55:09,120
Speaker 1: got tags for these rene a dear, you'd be like

1015
00:55:09,480 --> 00:55:13,400
Speaker 1: rene a dear French. The guy's name was Renella. The

1016
00:55:13,400 --> 00:55:15,759
Speaker 1: guy's name was Renella, and they trug and say, I'm

1017
00:55:15,800 --> 00:55:17,759
Speaker 1: gonna call it Renee I tell the day I die.

1018
00:55:18,560 --> 00:55:21,640
Speaker 1: He'd be like, it's kind of weird that, my dear,

1019
00:55:21,760 --> 00:55:24,000
Speaker 1: that's kind of weird. That was like named to honor me,

1020
00:55:24,080 --> 00:55:26,920
Speaker 1: and and the deer was named honor Elliot Cows. So no,

1021
00:55:27,080 --> 00:55:28,680
Speaker 1: you know what I'd say, I'd be like, no, dude,

1022
00:55:28,680 --> 00:55:32,080
Speaker 1: I totally understand. W you I don't think so, I

1023
00:55:32,080 --> 00:55:35,160
Speaker 1: don't think so. As a cous dear man, I understand.

1024
00:55:36,480 --> 00:55:39,120
Speaker 1: But but there's a twist to that story. So Elliot

1025
00:55:39,160 --> 00:55:43,040
Speaker 1: Cows and Elliet Cows father Samuel and his grandfather Peter,

1026
00:55:44,120 --> 00:55:46,799
Speaker 1: they pronounced it cows. He was an ornithologist, not a

1027
00:55:46,800 --> 00:55:50,960
Speaker 1: dear guy. But did he like muse on or like, like, uh,

1028
00:55:51,160 --> 00:55:52,960
Speaker 1: did he was he like, oh, there's this little ship

1029
00:55:53,040 --> 00:55:55,719
Speaker 1: and deer running around or I'm not sure if well

1030
00:55:55,800 --> 00:55:59,640
Speaker 1: he did. He wrote Quadrupeds of Our Kinds of Deer

1031
00:55:59,680 --> 00:56:02,000
Speaker 1: and Error Zone. I think he wrote this great written

1032
00:56:02,040 --> 00:56:05,239
Speaker 1: about it. I like that word kinds. We talked about

1033
00:56:05,280 --> 00:56:07,360
Speaker 1: sub species and races. And he wrote a paper of

1034
00:56:07,480 --> 00:56:11,680
Speaker 1: kinds of deer that we do, that whole series kinds

1035
00:56:11,680 --> 00:56:13,640
Speaker 1: of So he's written about all kinds of you know,

1036
00:56:13,640 --> 00:56:16,880
Speaker 1: all the mammals and deer too, but not in detail.

1037
00:56:16,960 --> 00:56:19,719
Speaker 1: He wasn't really a dear person um in detail. But

1038
00:56:19,760 --> 00:56:22,920
Speaker 1: there's a twist to the cows story. So he Elliott

1039
00:56:22,960 --> 00:56:27,080
Speaker 1: cows and and at least two generations back um pronounced

1040
00:56:27,080 --> 00:56:30,200
Speaker 1: at cows. But he says that back in France, I

1041
00:56:30,200 --> 00:56:32,160
Speaker 1: don't know how many generations that would be we're talking about.

1042
00:56:32,960 --> 00:56:35,880
Speaker 1: He's a Frenchman from the name is French, and so

1043
00:56:36,000 --> 00:56:39,520
Speaker 1: his family originally came from northern France moved to southern England.

1044
00:56:39,760 --> 00:56:42,080
Speaker 1: And he says in that same footnote when when they

1045
00:56:42,120 --> 00:56:46,640
Speaker 1: moved to southern England, the name was changed, was changed

1046
00:56:46,719 --> 00:56:50,279
Speaker 1: or bastardized in and they started pronouncing it cows. And

1047
00:56:50,320 --> 00:56:54,839
Speaker 1: in France it was two syllables kuai's. Dad's what I'm

1048
00:56:54,840 --> 00:56:57,399
Speaker 1: switching too for the deer kuai's. And so if people

1049
00:56:57,440 --> 00:56:59,960
Speaker 1: are going to argue that that's their basis for saying coup's,

1050
00:57:00,040 --> 00:57:02,239
Speaker 1: then I want to hear him saying kuaiz dear. That's

1051
00:57:02,239 --> 00:57:06,000
Speaker 1: what I'm switching to get around all of them, like

1052
00:57:06,080 --> 00:57:09,640
Speaker 1: hard hitting Arizona flat brim dudes and be like, wait, yeah,

1053
00:57:09,680 --> 00:57:12,680
Speaker 1: I'd like to inter rest in these ka I like

1054
00:57:12,760 --> 00:57:15,200
Speaker 1: how you held out until you found a reasonable out.

1055
00:57:17,920 --> 00:57:21,880
Speaker 1: I can't something contrary, and I need to find a

1056
00:57:21,880 --> 00:57:24,840
Speaker 1: way to get out of this. There's some people in

1057
00:57:24,880 --> 00:57:29,440
Speaker 1: Elliott Cows's family back before him that spelled their name

1058
00:57:29,520 --> 00:57:32,400
Speaker 1: CEO w e s instead of you in the middle.

1059
00:57:32,720 --> 00:57:35,600
Speaker 1: They put CEO w e s because they were tired

1060
00:57:35,600 --> 00:57:39,360
Speaker 1: of people misspronouncing it. Cou's probably. I have a newspaper

1061
00:57:39,480 --> 00:57:47,040
Speaker 1: article about uh an uncle of mine. No, my father's

1062
00:57:47,160 --> 00:57:52,400
Speaker 1: uncle hit a accidentally like crash his car into a

1063
00:57:52,440 --> 00:57:58,280
Speaker 1: policeman's car. An irishman named Philip to me, and Philip

1064
00:57:58,320 --> 00:58:00,240
Speaker 1: to me went home and got his pistol and back

1065
00:58:00,280 --> 00:58:02,080
Speaker 1: and shot and killed my dad's uncle. I have a

1066
00:58:02,120 --> 00:58:04,840
Speaker 1: newspaper article about it. But in that article my family

1067
00:58:04,960 --> 00:58:10,280
Speaker 1: is r I N E l l I uh huh

1068
00:58:10,400 --> 00:58:14,320
Speaker 1: so in the article or okay, and that's the only play. Yeah.

1069
00:58:14,360 --> 00:58:16,120
Speaker 1: My dad said he grew up with his grandma pulling

1070
00:58:16,160 --> 00:58:18,440
Speaker 1: that she kept the clothes in the box, and she

1071
00:58:18,520 --> 00:58:20,840
Speaker 1: pulled him down and show everybody the bloody shirt with

1072
00:58:20,920 --> 00:58:23,360
Speaker 1: a bullet hole in it. But the article about it

1073
00:58:23,440 --> 00:58:26,720
Speaker 1: describes him as with R I N yellow I. So

1074
00:58:27,120 --> 00:58:29,880
Speaker 1: he perhaps right, you know, just like people. I'm just

1075
00:58:29,920 --> 00:58:32,000
Speaker 1: I'm just coming on the way that names morph and

1076
00:58:32,120 --> 00:58:34,600
Speaker 1: change and yeah, and you're like, how like what like

1077
00:58:34,680 --> 00:58:36,840
Speaker 1: what pronounced you? What? I mean, how that dude pronounced

1078
00:58:36,840 --> 00:58:38,440
Speaker 1: his last name? I don't know, did you say ronella

1079
00:58:38,680 --> 00:58:39,920
Speaker 1: or do you have some the whole other way of

1080
00:58:39,960 --> 00:58:42,880
Speaker 1: doing it. My my family was originally from deeked in

1081
00:58:42,960 --> 00:58:46,280
Speaker 1: Switzerland in the seventeen hundreds and two miles from deek

1082
00:58:46,320 --> 00:58:50,959
Speaker 1: in Switzerland is helful thinking helful thinking Switzerland, and there's

1083
00:58:50,960 --> 00:58:52,920
Speaker 1: helful fingers back there now and they spell it the

1084
00:58:52,960 --> 00:58:55,000
Speaker 1: same way, which is kind of unique because names do

1085
00:58:55,200 --> 00:58:58,400
Speaker 1: change when they switch continents and things, but still spelt

1086
00:58:58,400 --> 00:59:03,840
Speaker 1: that way. Uh. Lasting on Elliott Cows, do you understand

1087
00:59:03,840 --> 00:59:06,200
Speaker 1: like I read like he was what was his what

1088
00:59:06,280 --> 00:59:09,080
Speaker 1: was his thing about levitation that I'd rather he was

1089
00:59:09,120 --> 00:59:13,400
Speaker 1: into levitation? Levitation? No, I just read that he was.

1090
00:59:14,360 --> 00:59:16,920
Speaker 1: He's probably on something stupid like his Wikipedia page, but

1091
00:59:17,120 --> 00:59:19,600
Speaker 1: read that he's like in into levitation. No, you can

1092
00:59:19,640 --> 00:59:24,160
Speaker 1: get the I bought that publication for likes Um online

1093
00:59:24,160 --> 00:59:26,560
Speaker 1: on Kindle. I don't know if it's available other places,

1094
00:59:26,560 --> 00:59:29,320
Speaker 1: probably other other places, but it's a short thing. It's

1095
00:59:29,320 --> 00:59:30,960
Speaker 1: more of a paper than a book, but they make

1096
00:59:31,000 --> 00:59:33,840
Speaker 1: it look like it's a book, and it's really entertaining

1097
00:59:34,440 --> 00:59:38,640
Speaker 1: because he as a scientist. He's talking about, well, okay,

1098
00:59:38,640 --> 00:59:43,440
Speaker 1: people don't believe in levitation, but basically, I we should

1099
00:59:43,520 --> 00:59:45,720
Speaker 1: hold out the idea that there's a lot of things

1100
00:59:45,720 --> 00:59:48,280
Speaker 1: in the natural world we don't understand and we can't explain.

1101
00:59:48,640 --> 00:59:51,480
Speaker 1: In future research will probably explain it. And he kind

1102
00:59:51,480 --> 00:59:53,680
Speaker 1: of felt that way about levitation, that we don't know

1103
00:59:53,720 --> 00:59:56,200
Speaker 1: what it is now he's been totally swindled by people

1104
00:59:56,240 --> 00:59:58,880
Speaker 1: who are levitating in front of him. But he said,

1105
00:59:58,920 --> 01:00:00,960
Speaker 1: you know, we don't understand it out, but future, in

1106
01:00:01,000 --> 01:00:04,720
Speaker 1: the future, science might might unravel what that's all about.

1107
01:00:04,880 --> 01:00:08,560
Speaker 1: Because people don't have any problem believing in in centrifugal

1108
01:00:08,640 --> 01:00:12,040
Speaker 1: force or gravity. Like if he took the Earth and

1109
01:00:12,080 --> 01:00:14,680
Speaker 1: you spun it wouldn't people levitate because the centrifugal force.

1110
01:00:14,800 --> 01:00:17,400
Speaker 1: He was talking about these forces as being understood and

1111
01:00:17,720 --> 01:00:20,320
Speaker 1: we just don't understand that one. He said. Everybody in

1112
01:00:20,360 --> 01:00:24,200
Speaker 1: the world, uh, it doesn't believe in levitation, except he

1113
01:00:24,240 --> 01:00:26,600
Speaker 1: says Christians, of course, I mean they have no problem

1114
01:00:26,600 --> 01:00:29,640
Speaker 1: believing that christiscended into Heaven through levitation, So so the

1115
01:00:29,680 --> 01:00:31,880
Speaker 1: Christians believe in levitation, so they're open to the idea.

1116
01:00:32,080 --> 01:00:34,760
Speaker 1: That's right, that was, says his tongue in cheek. But

1117
01:00:34,880 --> 01:00:37,600
Speaker 1: he talks in there about he he ends it kind

1118
01:00:37,640 --> 01:00:40,080
Speaker 1: of odd. He talks about how his wife, which he

1119
01:00:40,120 --> 01:00:43,040
Speaker 1: refers to a Mrs c in there, and and so

1120
01:00:43,160 --> 01:00:48,360
Speaker 1: those probably just gave up on that. So he talks

1121
01:00:48,360 --> 01:00:50,959
Speaker 1: about his wife and a friend and this big oak table,

1122
01:00:51,000 --> 01:00:52,360
Speaker 1: and they put their hands on the table and they

1123
01:00:52,400 --> 01:00:54,720
Speaker 1: tried to move it, and the table started bumping and

1124
01:00:54,760 --> 01:00:57,680
Speaker 1: moving by itself, and you totally convinced that they were

1125
01:00:57,680 --> 01:00:59,560
Speaker 1: doing this, And they pulled away from the table, and

1126
01:00:59,600 --> 01:01:03,640
Speaker 1: the table kept bumping and being agitated with nobody touching it.

1127
01:01:04,040 --> 01:01:06,480
Speaker 1: And then at the end of that kind of bizarre story,

1128
01:01:06,640 --> 01:01:08,160
Speaker 1: maybe he was getting seen out at the end of

1129
01:01:08,200 --> 01:01:10,600
Speaker 1: his career. The end of that story, he says, and

1130
01:01:10,680 --> 01:01:17,760
Speaker 1: therein lies my theory of telekinetic levitation. I'nnced. Now it's

1131
01:01:17,760 --> 01:01:21,880
Speaker 1: an interesting read, it's pretty entertaining, it's pretty short. Uh,

1132
01:01:22,120 --> 01:01:23,760
Speaker 1: this is a this is a question that cannot be

1133
01:01:23,800 --> 01:01:29,840
Speaker 1: answered to my satisfaction. Um, I'm gonna phrase it in

1134
01:01:29,840 --> 01:01:36,080
Speaker 1: an annoying way. Why do dear lose their antlers? Evolutionarily

1135
01:01:36,280 --> 01:01:39,280
Speaker 1: or how does it happen? When it happened? Why do

1136
01:01:39,360 --> 01:01:42,040
Speaker 1: they evolutionarily? Why why should then? Yeah, I say it's

1137
01:01:42,040 --> 01:01:44,720
Speaker 1: annoying because you can't go like, we don't know why

1138
01:01:44,960 --> 01:01:48,560
Speaker 1: you We could speculate about things that may have. Right,

1139
01:01:48,760 --> 01:01:51,200
Speaker 1: there's some good reasons to lose antlers. You break a time,

1140
01:01:51,280 --> 01:01:53,640
Speaker 1: you got a new set next year. That's a great horn.

1141
01:01:53,680 --> 01:01:55,480
Speaker 1: You don't get a new set, No, you don't. But

1142
01:01:55,840 --> 01:01:57,520
Speaker 1: they're not gonna break as much as times though. You

1143
01:01:57,520 --> 01:02:00,960
Speaker 1: know you'll broom the tips off and sinicize, and that

1144
01:02:01,040 --> 01:02:04,120
Speaker 1: would that really drive No, I'm not alone. I don't think,

1145
01:02:04,600 --> 01:02:07,040
Speaker 1: not alone, but you know, you think if you're over

1146
01:02:07,120 --> 01:02:09,960
Speaker 1: wintering and you're trying to make it through winter on

1147
01:02:10,000 --> 01:02:12,400
Speaker 1: harsh winter range and through deep snow, be nice not

1148
01:02:12,480 --> 01:02:14,760
Speaker 1: to have, especially a moose, those big bones on your head.

1149
01:02:14,800 --> 01:02:17,520
Speaker 1: I mean they're being an advantage to to losing those

1150
01:02:17,600 --> 01:02:19,760
Speaker 1: during the wintertime. But you can't beat the hell out

1151
01:02:19,760 --> 01:02:21,640
Speaker 1: of stuff trying to kill you. No, tell you what

1152
01:02:21,680 --> 01:02:27,440
Speaker 1: the answer is probably is let's go nutritional signaling. And

1153
01:02:27,840 --> 01:02:30,880
Speaker 1: you've heard about that work. It gives you and it

1154
01:02:30,920 --> 01:02:35,600
Speaker 1: gives the animal an annual expression of its physical condition

1155
01:02:35,680 --> 01:02:39,080
Speaker 1: and its fitness for females to select the animals they

1156
01:02:39,080 --> 01:02:41,840
Speaker 1: are able to acquire the most resources, grow the biggest

1157
01:02:41,840 --> 01:02:45,680
Speaker 1: antlers because they're they're luxury organs. They grow after the

1158
01:02:45,720 --> 01:02:48,920
Speaker 1: body has been satisfied the nutritions. Yeah, like the difference

1159
01:02:49,000 --> 01:02:52,160
Speaker 1: in driving a car or having a picture of a

1160
01:02:52,200 --> 01:02:55,800
Speaker 1: sweet car you used to have. It sounds like a

1161
01:02:55,800 --> 01:03:02,160
Speaker 1: personal story, okay, But but here you've got an annual

1162
01:03:02,200 --> 01:03:06,520
Speaker 1: expression of of how fit you are, and it's up

1163
01:03:06,520 --> 01:03:09,080
Speaker 1: to the minute and and getting bigger every year. You

1164
01:03:09,080 --> 01:03:11,160
Speaker 1: don't as a yearling, yearling moose, you don't want to

1165
01:03:11,160 --> 01:03:15,520
Speaker 1: grow this gigantic fifty um set of antlers. But here, annually,

1166
01:03:15,920 --> 01:03:18,280
Speaker 1: as your body grows and as you get no more

1167
01:03:18,360 --> 01:03:21,880
Speaker 1: nutrition and maybe become dominant, you can you can express

1168
01:03:21,960 --> 01:03:24,640
Speaker 1: that and say, look, ladies, look at look at I got. Yeah,

1169
01:03:24,640 --> 01:03:27,720
Speaker 1: but horned, here's the problem with that. Horned animals have

1170
01:03:27,840 --> 01:03:31,600
Speaker 1: the same luxury. They just keep growing, right. But there's

1171
01:03:31,640 --> 01:03:34,320
Speaker 1: sometimes where it's like a two year old big horn

1172
01:03:34,800 --> 01:03:37,960
Speaker 1: is gonna wind up having the biggest horns ever. It's

1173
01:03:38,000 --> 01:03:41,160
Speaker 1: like a big ass horned big horn is old. Mm hmm.

1174
01:03:41,760 --> 01:03:44,960
Speaker 1: They you know, servants, the dear Family evolved in Asia,

1175
01:03:45,720 --> 01:03:49,560
Speaker 1: bob is evolved don't know where, probably Europe someplace. And

1176
01:03:49,600 --> 01:03:52,360
Speaker 1: so the the animals get on these different evolutionary tracks

1177
01:03:52,400 --> 01:03:56,280
Speaker 1: and you get you get characteristics that just develop independently

1178
01:03:56,320 --> 01:03:59,360
Speaker 1: and and and now looking at them now, they may

1179
01:03:59,360 --> 01:04:01,960
Speaker 1: not make sense when you compare them, like what you're

1180
01:04:02,000 --> 01:04:06,080
Speaker 1: saying that they just had They just had different um pathways.

1181
01:04:06,080 --> 01:04:10,800
Speaker 1: There's a procolius in in Asia. Some fossils were Looking

1182
01:04:10,840 --> 01:04:13,439
Speaker 1: at a set of fossils, it looks like at least

1183
01:04:13,480 --> 01:04:16,360
Speaker 1: that was the conclusion. Some of them shed their antlers

1184
01:04:16,440 --> 01:04:19,000
Speaker 1: every year and some of them didn't in that form.

1185
01:04:19,440 --> 01:04:21,520
Speaker 1: And so that's thought of as maybe being the root

1186
01:04:21,640 --> 01:04:24,200
Speaker 1: of the servant family, of the deer family. That's right

1187
01:04:24,240 --> 01:04:26,360
Speaker 1: at the point where animals have these things on their

1188
01:04:26,360 --> 01:04:29,360
Speaker 1: heads and then they're dropping off every year or not

1189
01:04:29,640 --> 01:04:33,360
Speaker 1: dropping off every year. We had a really really neat

1190
01:04:33,920 --> 01:04:38,040
Speaker 1: kind of expression of the the you know, the health

1191
01:04:38,040 --> 01:04:41,680
Speaker 1: of the animal being represented in the antlers. Um sam

1192
01:04:41,760 --> 01:04:46,760
Speaker 1: baits producer here at meat Eater. She shout her first

1193
01:04:46,840 --> 01:04:51,600
Speaker 1: mule deer buck and it was a really neat buck

1194
01:04:53,040 --> 01:04:56,800
Speaker 1: and everything about it. From my look at the deer,

1195
01:04:56,840 --> 01:04:59,080
Speaker 1: it was like, boy, this is a mature deer. The

1196
01:04:59,160 --> 01:05:01,280
Speaker 1: antlers aren't that big big, and they're kind of an

1197
01:05:01,400 --> 01:05:07,880
Speaker 1: interesting formation, and uh, you could have laid uh, you know,

1198
01:05:08,640 --> 01:05:11,560
Speaker 1: two year old deer next to this, probably three or

1199
01:05:11,640 --> 01:05:14,000
Speaker 1: four year old deer, and the two year old deer

1200
01:05:14,080 --> 01:05:18,440
Speaker 1: would have bigger antlers um. But then when he started

1201
01:05:18,480 --> 01:05:20,640
Speaker 1: dressing the deer, the deer had been shot the year before.

1202
01:05:22,360 --> 01:05:25,160
Speaker 1: There's also leg injuries. Front leg injuries will produce a

1203
01:05:25,200 --> 01:05:27,440
Speaker 1: non typical point on the same side as the front

1204
01:05:27,520 --> 01:05:31,960
Speaker 1: leg injury. Rear leg injuries. You say that like opposite, No,

1205
01:05:32,120 --> 01:05:34,280
Speaker 1: not always, but oh you know, I knew. I thought

1206
01:05:34,320 --> 01:05:36,200
Speaker 1: it was always opposite. I didn't know his front leg

1207
01:05:36,440 --> 01:05:39,440
Speaker 1: front leg is the same side. It's called a contralateral effect.

1208
01:05:39,520 --> 01:05:42,280
Speaker 1: And and so the rear leg or left rear lego

1209
01:05:42,360 --> 01:05:45,360
Speaker 1: producer um messed up at around the on the right

1210
01:05:45,400 --> 01:05:47,400
Speaker 1: side the next year. So a lot of theories are

1211
01:05:47,480 --> 01:05:49,920
Speaker 1: like some kind of counterbalancing, which doesn't make a lot

1212
01:05:49,960 --> 01:05:52,480
Speaker 1: of sense. Some people some tell you, well, the deer

1213
01:05:52,560 --> 01:05:55,160
Speaker 1: is probably back there licking his injury and he's damaging

1214
01:05:55,280 --> 01:05:58,480
Speaker 1: that opposite side antler. But I think it's more neurological.

1215
01:05:58,560 --> 01:06:01,640
Speaker 1: I think it's the way the right rain um manages

1216
01:06:01,680 --> 01:06:04,440
Speaker 1: the left side of the body and vice versa. I

1217
01:06:04,560 --> 01:06:07,640
Speaker 1: think it's something with that damage to the left side

1218
01:06:07,640 --> 01:06:13,240
Speaker 1: of your leg is neurologically affecting the other side. Um okay,

1219
01:06:13,280 --> 01:06:15,640
Speaker 1: so tell me why they how they lose their antlers?

1220
01:06:16,640 --> 01:06:18,840
Speaker 1: What's going on? One minute're kicking ass, You've got some antlers.

1221
01:06:18,880 --> 01:06:22,000
Speaker 1: You're fighting? Yeah, I mean you can pick up you

1222
01:06:22,040 --> 01:06:25,320
Speaker 1: can pick up the animal by the and then and

1223
01:06:25,400 --> 01:06:29,120
Speaker 1: then the the after the breeding season, to stosterone levels,

1224
01:06:29,280 --> 01:06:31,760
Speaker 1: mostly to stoster and a lot of other hormones. There's

1225
01:06:31,760 --> 01:06:33,960
Speaker 1: this big orchestra of hormones rising and falling throughout the

1226
01:06:34,040 --> 01:06:36,440
Speaker 1: year in a in a deer, but really to stosterone

1227
01:06:36,480 --> 01:06:38,800
Speaker 1: is a driver. And after the breeding season to stosterone

1228
01:06:38,880 --> 01:06:42,840
Speaker 1: levels plummet. And it's that that plummeting of testosterone. There's

1229
01:06:42,840 --> 01:06:47,360
Speaker 1: this this certain layer of bone cells between the temporary

1230
01:06:47,360 --> 01:06:50,120
Speaker 1: antler material and the top of the pedicle. It's called

1231
01:06:50,200 --> 01:06:53,920
Speaker 1: osteo class, and they're real sensitive to hormonal changes and

1232
01:06:53,960 --> 01:06:58,600
Speaker 1: then dropping to stosterone erodes those osteo class and antlers

1233
01:06:58,640 --> 01:07:01,760
Speaker 1: just fall off. They must be strong sons of bitches though. Yeah, right,

1234
01:07:03,320 --> 01:07:06,640
Speaker 1: Like you've seen deer, like you could hit a deer

1235
01:07:06,720 --> 01:07:09,360
Speaker 1: on the antler sometimes break the skull and it busts

1236
01:07:09,360 --> 01:07:14,160
Speaker 1: the skull in half. M Yeah, but then a dropping testosterone,

1237
01:07:14,160 --> 01:07:17,520
Speaker 1: a hormonal shift will cause whatever that glue is off

1238
01:07:18,680 --> 01:07:21,760
Speaker 1: and that doesn't take that long. I mean he's kicking

1239
01:07:21,760 --> 01:07:24,480
Speaker 1: as November, then a couple months later his antler falls off.

1240
01:07:25,880 --> 01:07:29,560
Speaker 1: Yelping and growing new ones in a couple of months

1241
01:07:29,600 --> 01:07:33,760
Speaker 1: prior to November. You could squeeze the tip of those

1242
01:07:33,760 --> 01:07:37,080
Speaker 1: antlers off your hands, get blood on your hands. I've

1243
01:07:37,120 --> 01:07:41,000
Speaker 1: talked to a number of guys have gone up, remember

1244
01:07:41,040 --> 01:07:43,560
Speaker 1: the circumstances going up and grabbed the deer to dragon,

1245
01:07:43,640 --> 01:07:46,760
Speaker 1: had the antler come off in her hand. It was happening.

1246
01:07:47,040 --> 01:07:50,920
Speaker 1: Shed antlers quicker if they're nutritionally depraved or if they

1247
01:07:51,000 --> 01:07:53,680
Speaker 1: get sick or something. I don't really cause that, it messes.

1248
01:07:53,720 --> 01:07:55,560
Speaker 1: It just kind of messes with their hormone system and

1249
01:07:56,400 --> 01:07:58,920
Speaker 1: may lose their the sauceron may go down quicker just

1250
01:07:58,960 --> 01:08:02,200
Speaker 1: because they're kind of sick. What do you think it

1251
01:08:02,280 --> 01:08:06,720
Speaker 1: takes um? You know, people talk about areas of big Bucks,

1252
01:08:07,960 --> 01:08:11,920
Speaker 1: and you know what, when I was like coming up

1253
01:08:11,960 --> 01:08:15,360
Speaker 1: as a young man, everybody was excited about the genetics

1254
01:08:15,920 --> 01:08:19,960
Speaker 1: that place got great genetics, right, And then we talked

1255
01:08:20,000 --> 01:08:22,599
Speaker 1: to some guys. You've done some work with Matt Coffin

1256
01:08:22,720 --> 01:08:29,000
Speaker 1: and and his colleague Kevin. Kevin looks at nutrition, and

1257
01:08:29,240 --> 01:08:32,599
Speaker 1: they've done studies have taken deer from supposedly shitty genetic

1258
01:08:32,680 --> 01:08:38,080
Speaker 1: areas or supposedly stupendous genetic areas, changing changing their diet

1259
01:08:38,200 --> 01:08:42,320
Speaker 1: to match diet of deer from areas that are contradictory

1260
01:08:42,400 --> 01:08:45,200
Speaker 1: to that, meaning like you take a deer from an

1261
01:08:45,200 --> 01:08:48,240
Speaker 1: area that supposed he has shitty genetics and put it

1262
01:08:48,360 --> 01:08:50,679
Speaker 1: on the same diet as a deer from an area

1263
01:08:50,720 --> 01:08:53,200
Speaker 1: that suppose he has great genetics, and lone behold, they

1264
01:08:53,200 --> 01:08:57,200
Speaker 1: went looking exactly the same. And he got into and

1265
01:08:57,360 --> 01:09:00,599
Speaker 1: we discussed like, not only is it that animal is nutrition,

1266
01:09:01,040 --> 01:09:05,040
Speaker 1: but it's the nutrition of its mother when she becomes pregnant, right,

1267
01:09:05,360 --> 01:09:07,320
Speaker 1: and his aunt, Like whether he's going to be a

1268
01:09:07,400 --> 01:09:11,040
Speaker 1: stomp or buck could be decided by the condition of

1269
01:09:11,160 --> 01:09:13,240
Speaker 1: his mother when she becomes pregnant. It could, Yeah, it

1270
01:09:13,240 --> 01:09:15,680
Speaker 1: can be decided condition of his mother right before she

1271
01:09:15,720 --> 01:09:18,040
Speaker 1: becomes pregnant, the condition she's in when she becomes pregnant.

1272
01:09:18,240 --> 01:09:21,640
Speaker 1: Epigenetics that probably epigenetic it's a maternal effect, is what

1273
01:09:21,920 --> 01:09:24,720
Speaker 1: Kevin research and talked about. Probably there's a thing called

1274
01:09:24,760 --> 01:09:28,400
Speaker 1: epigenetics that is kind of a new field or finding someone.

1275
01:09:28,520 --> 01:09:32,040
Speaker 1: Not we but there's some amazing things where an animal

1276
01:09:32,160 --> 01:09:35,320
Speaker 1: has genetics and passes on the genetic code. And we

1277
01:09:35,400 --> 01:09:38,880
Speaker 1: always thought of it, like Gregor Mendel, Mendelian genetics was

1278
01:09:39,000 --> 01:09:42,040
Speaker 1: just like whatever genes you had, that's what got expressed

1279
01:09:42,040 --> 01:09:46,000
Speaker 1: in the young. We're finding out that environmental influences like

1280
01:09:46,120 --> 01:09:49,840
Speaker 1: nutrition can actually switch genes on and off. So so

1281
01:09:49,880 --> 01:09:52,519
Speaker 1: the genetic code doesn't change because it can't change, but

1282
01:09:52,680 --> 01:09:55,400
Speaker 1: which genes get expressed and turned on and off can

1283
01:09:55,520 --> 01:09:58,880
Speaker 1: change depending on if if you've got good nutrition or

1284
01:09:58,920 --> 01:10:03,240
Speaker 1: poor nutrition, And so really amazing things where it looks

1285
01:10:03,360 --> 01:10:07,200
Speaker 1: like it's actually genetic effects, but it's the genes are

1286
01:10:07,240 --> 01:10:09,800
Speaker 1: the same, there's just more different ones are active. It's

1287
01:10:09,800 --> 01:10:14,040
Speaker 1: really amazing, amazing stuff, certainly not my expertise, but cool stuff.

1288
01:10:14,040 --> 01:10:16,080
Speaker 1: And that's probably what's behind this maternal effect where the

1289
01:10:16,160 --> 01:10:20,040
Speaker 1: condition of the female can can actually affect the antlers

1290
01:10:20,080 --> 01:10:24,280
Speaker 1: of her male offspring when they're mature, because it's certain, yeah,

1291
01:10:24,400 --> 01:10:27,559
Speaker 1: it's got enough enough gas for certain things to kick

1292
01:10:27,640 --> 01:10:30,640
Speaker 1: in or it turns on. It's the methylation process. And

1293
01:10:30,680 --> 01:10:32,439
Speaker 1: I only sund that to to sound smart because I

1294
01:10:32,439 --> 01:10:35,280
Speaker 1: don't know anything about the methylation process. But that's the

1295
01:10:35,479 --> 01:10:39,920
Speaker 1: vehicle um in in the DNA transcription that turned genes

1296
01:10:40,000 --> 01:10:41,840
Speaker 1: on and off. And that's what's at the heart of that.

1297
01:10:42,439 --> 01:10:44,800
Speaker 1: If you took what's your theory on this? And why

1298
01:10:44,840 --> 01:10:48,200
Speaker 1: hasn't someone done yet? Get yourself a couple cuz dear

1299
01:10:50,240 --> 01:10:55,200
Speaker 1: bring them up to Iowa. What happens to him? Do

1300
01:10:55,320 --> 01:10:56,920
Speaker 1: they just die because they don't like it? Because it's

1301
01:10:57,439 --> 01:10:59,760
Speaker 1: they get bigger, They would get bigger. Nobody's done it

1302
01:11:00,080 --> 01:11:03,240
Speaker 1: UM that I know of, because c w D don't

1303
01:11:03,240 --> 01:11:06,439
Speaker 1: want to be moving animals around, you can't, you know.

1304
01:11:06,640 --> 01:11:09,200
Speaker 1: We had a we had a conversation with someone at UM,

1305
01:11:10,200 --> 01:11:12,519
Speaker 1: someone who does some work with Rocky Mountain Elk Foundation,

1306
01:11:12,680 --> 01:11:14,360
Speaker 1: was talking about with c w D just like the

1307
01:11:14,439 --> 01:11:18,719
Speaker 1: whole thing of like moving out. It's just done, man, Yeah,

1308
01:11:19,000 --> 01:11:21,360
Speaker 1: but do we need to move much? I mean we're

1309
01:11:21,360 --> 01:11:27,800
Speaker 1: still really now. It's unfinished work man. Yeah, but that's

1310
01:11:27,840 --> 01:11:34,360
Speaker 1: a that's a concern to move the the habituated Elk

1311
01:11:35,040 --> 01:11:37,560
Speaker 1: out of the state. And they had to that that

1312
01:11:37,720 --> 01:11:40,519
Speaker 1: lucky elk that somebody chose to feed is now at

1313
01:11:40,720 --> 01:11:48,400
Speaker 1: the Veterinary Research Station, full full life. So they get bigger,

1314
01:11:48,439 --> 01:11:50,639
Speaker 1: they would get bigger. Yeah, I don't you know there

1315
01:11:50,720 --> 01:11:53,960
Speaker 1: would they stop being the gray ghost. I don't good

1316
01:11:54,040 --> 01:11:55,880
Speaker 1: question what their pellege would do, whether you get like

1317
01:11:55,920 --> 01:11:58,240
Speaker 1: a rusty red coat in the summer, which we normally

1318
01:11:58,280 --> 01:12:01,600
Speaker 1: don't get. But I don't there. They're they've been so separated,

1319
01:12:01,640 --> 01:12:05,240
Speaker 1: and they're good legitimate subspecies. They're smaller. We did some

1320
01:12:05,720 --> 01:12:08,080
Speaker 1: genetic work. Bunda Crockett and Pope and Young paid for

1321
01:12:08,200 --> 01:12:11,160
Speaker 1: some genetic work that I orchestrated with some real geneticist

1322
01:12:11,640 --> 01:12:14,120
Speaker 1: where we found a genetic marker that will identify a

1323
01:12:14,200 --> 01:12:16,280
Speaker 1: cow's white tailed deer from the other white tailed deer.

1324
01:12:16,600 --> 01:12:19,160
Speaker 1: So you could bring me a rack of skull plate

1325
01:12:19,520 --> 01:12:21,160
Speaker 1: and we could test that and tell whether it's Cole's

1326
01:12:21,160 --> 01:12:22,519
Speaker 1: white til or not. And Buona Crowt and Pope and

1327
01:12:22,560 --> 01:12:24,719
Speaker 1: Young are using that to keep their record books clean.

1328
01:12:24,800 --> 01:12:28,439
Speaker 1: Now someone enters the new world record cow's white tail,

1329
01:12:28,479 --> 01:12:30,599
Speaker 1: and it's a skullplate that Grandpa had in the attic

1330
01:12:30,680 --> 01:12:34,240
Speaker 1: and Grandpa sett he shot it south of Tucson back

1331
01:12:34,360 --> 01:12:36,240
Speaker 1: and this has happened, and we do a genetic test

1332
01:12:36,320 --> 01:12:41,040
Speaker 1: and yeah, family stories sometimes get twisted and chains, and

1333
01:12:41,120 --> 01:12:43,280
Speaker 1: so we've done that and we've found some of these

1334
01:12:43,280 --> 01:12:45,120
Speaker 1: animals they're not cow's white tail, and so they're not

1335
01:12:45,200 --> 01:12:48,599
Speaker 1: they can't be included. That's a bomber man. Someone gets

1336
01:12:48,600 --> 01:12:50,760
Speaker 1: confused about the butt grampa shot in Alberta and the

1337
01:12:50,800 --> 01:12:57,200
Speaker 1: bucket shot in Arizona. That's what it is. Uh, we

1338
01:12:57,280 --> 01:12:58,599
Speaker 1: had the thing where we were You wanted to bring

1339
01:12:58,680 --> 01:13:02,599
Speaker 1: up something about Neanderthals. Why, yeah, I didn't. I've sent

1340
01:13:02,640 --> 01:13:05,000
Speaker 1: you a bunch of the Ndfel papers just because you

1341
01:13:05,400 --> 01:13:07,479
Speaker 1: are you interested. I think it's just you and I

1342
01:13:07,520 --> 01:13:10,120
Speaker 1: are in the same boat, were interested spectators and what

1343
01:13:10,280 --> 01:13:12,760
Speaker 1: the scientists are doing. But the reason why, be the

1344
01:13:12,840 --> 01:13:16,560
Speaker 1: reason I'm when Neanderthal man is uh into him is

1345
01:13:16,640 --> 01:13:23,679
Speaker 1: because in my life, they have gone from these crude

1346
01:13:25,040 --> 01:13:28,720
Speaker 1: right and these crude like you know, you know, like

1347
01:13:28,880 --> 01:13:31,000
Speaker 1: beating their lady over there on the rock and dragging

1348
01:13:31,040 --> 01:13:36,360
Speaker 1: her home kind of thing, to being just increasingly complex

1349
01:13:36,439 --> 01:13:40,880
Speaker 1: and sophisticated. And it's oh, they were free divers. They

1350
01:13:40,960 --> 01:13:43,360
Speaker 1: built a raft and I was like, yeah, they were

1351
01:13:43,400 --> 01:13:47,880
Speaker 1: having free divers. They had art. They like to carve things.

1352
01:13:48,280 --> 01:13:49,880
Speaker 1: I was so I was trying to get cal that

1353
01:13:49,960 --> 01:13:52,600
Speaker 1: put a thing in Cal's weekend review where um, I

1354
01:13:52,680 --> 01:13:54,840
Speaker 1: had a whole joke crafted up for Calvity, wouldn't use it.

1355
01:13:56,920 --> 01:13:58,560
Speaker 1: I was waiting for the story. I wasn't even the

1356
01:13:58,600 --> 01:14:00,240
Speaker 1: story to come out where it was review old that

1357
01:14:00,320 --> 01:14:05,080
Speaker 1: Neanderthals had laptops. They don't happen, because every story about

1358
01:14:05,080 --> 01:14:08,400
Speaker 1: in Airthals now is like, oh, they were just great,

1359
01:14:08,600 --> 01:14:13,559
Speaker 1: nice people, nice smart people. Doing start testing this out

1360
01:14:14,560 --> 01:14:17,479
Speaker 1: by every time you see somebody eating oysters, you stare

1361
01:14:17,520 --> 01:14:20,920
Speaker 1: at him and you go, you neander Well, they're two

1362
01:14:20,960 --> 01:14:24,120
Speaker 1: percent of VIRGINO. Well, I'm a little bit Well do

1363
01:14:24,160 --> 01:14:26,040
Speaker 1: you have you done twenty three? No? I did the

1364
01:14:26,080 --> 01:14:28,479
Speaker 1: other one. I'm a little less than less than average

1365
01:14:28,479 --> 01:14:32,599
Speaker 1: on Neanderthal Rogan. I had a good laugh. Joe Rogan,

1366
01:14:32,720 --> 01:14:38,080
Speaker 1: he's like running ahead. He's running heavy. That's not surprising.

1367
01:14:38,200 --> 01:14:42,040
Speaker 1: It's a sanginal crest and the eyebrows. I think it's

1368
01:14:42,120 --> 01:14:45,600
Speaker 1: rather real heavy. He was saying, But you know that

1369
01:14:45,760 --> 01:14:53,680
Speaker 1: that miniature hominid that they found in Flores Island, Yeah, Florences.

1370
01:14:54,680 --> 01:14:57,160
Speaker 1: I think I'm missing a syllable. But three ft tall

1371
01:14:57,680 --> 01:15:01,320
Speaker 1: at maturity. They're running on almost all all Neanderthal and

1372
01:15:01,439 --> 01:15:04,800
Speaker 1: Denisovan jeans or genetics. I mean they come from that

1373
01:15:04,880 --> 01:15:09,599
Speaker 1: Neanderthal stock, not from modern human stock. Yeah. At once

1374
01:15:09,680 --> 01:15:11,400
Speaker 1: upon a time, you could have walked. You could have

1375
01:15:11,439 --> 01:15:16,840
Speaker 1: wandered around Southern Europe Mediterranean area, and just like you

1376
01:15:16,880 --> 01:15:19,599
Speaker 1: can wander around um here and be like, oh, there's

1377
01:15:19,600 --> 01:15:21,320
Speaker 1: a black tail deer. Oh there's mild deer. There's a

1378
01:15:21,320 --> 01:15:23,679
Speaker 1: white tail, there's a couzier. How did these all fit together?

1379
01:15:23,920 --> 01:15:27,080
Speaker 1: You could have roamed the land and run into like

1380
01:15:27,360 --> 01:15:30,960
Speaker 1: different kinds of different folks. Yeah, different kind of folks

1381
01:15:32,760 --> 01:15:37,320
Speaker 1: did some amount of love making multiple time. But paper

1382
01:15:37,439 --> 01:15:39,680
Speaker 1: just came out with the Neanderthal showing that wasn't just

1383
01:15:39,880 --> 01:15:42,200
Speaker 1: one kind of unique population where they interbred and it

1384
01:15:42,240 --> 01:15:45,000
Speaker 1: spread out from there. But it was a real complex

1385
01:15:45,760 --> 01:15:48,519
Speaker 1: over a long period of time, thousands and thousands, probably

1386
01:15:48,600 --> 01:15:50,880
Speaker 1: hundreds of thousands, well at least tens of thousands of years,

1387
01:15:51,280 --> 01:15:54,040
Speaker 1: a whole bunch of different interbreeding events between and that

1388
01:15:54,840 --> 01:15:59,880
Speaker 1: and really messing with people or not into it people.

1389
01:16:00,040 --> 01:16:03,559
Speaker 1: Would you coming from one spot, would you like trying

1390
01:16:03,600 --> 01:16:09,519
Speaker 1: to pick up other species? You're saying could as if

1391
01:16:09,560 --> 01:16:12,120
Speaker 1: it's past tense. I feel like you're trying to call

1392
01:16:12,200 --> 01:16:15,640
Speaker 1: me out here. Probably like back in the day you

1393
01:16:15,640 --> 01:16:17,160
Speaker 1: would have been like, I'm gonna go check out that

1394
01:16:17,200 --> 01:16:21,720
Speaker 1: other camp. What are those anyway? Yeah? I think so,

1395
01:16:21,920 --> 01:16:25,439
Speaker 1: I'm gonna bring a some cookies over there. And we're

1396
01:16:25,439 --> 01:16:30,000
Speaker 1: speaking past tense hypothetically. Back then, people with all the

1397
01:16:30,040 --> 01:16:33,960
Speaker 1: oysters and muscles and doing the free diving a pretty

1398
01:16:33,960 --> 01:16:36,120
Speaker 1: good crew. Kind of small? Was it the was it

1399
01:16:36,200 --> 01:16:39,000
Speaker 1: the unattractive modern humans though, that were more likely to

1400
01:16:39,080 --> 01:16:41,439
Speaker 1: breed with Andrew? I would love to know man, and

1401
01:16:41,479 --> 01:16:43,760
Speaker 1: I'd like know like when they sat around talking or

1402
01:16:43,800 --> 01:16:46,800
Speaker 1: they talking about how you know, like, was it like

1403
01:16:47,880 --> 01:16:53,320
Speaker 1: if you were krol Magnet or you know, and you

1404
01:16:53,439 --> 01:16:55,560
Speaker 1: hooked up with the Neanderthal? Was it like did you

1405
01:16:55,720 --> 01:17:00,120
Speaker 1: try to like keep quiet about it right, We're like wow, know?

1406
01:17:00,760 --> 01:17:04,120
Speaker 1: Or did you brag it up? I would load? No,

1407
01:17:06,000 --> 01:17:09,160
Speaker 1: I got along with the time activities. I'll be engaging

1408
01:17:09,200 --> 01:17:14,000
Speaker 1: in some day. Um. Yeah. Did you have any burning

1409
01:17:14,040 --> 01:17:17,120
Speaker 1: observation about him? No? I just just like them. I

1410
01:17:17,240 --> 01:17:19,320
Speaker 1: like that the h is back in the name, you know,

1411
01:17:19,360 --> 01:17:21,519
Speaker 1: it was Neanderthal. And then for a period of time

1412
01:17:21,720 --> 01:17:25,200
Speaker 1: someone said neander tall because because it's it's the cow's

1413
01:17:25,600 --> 01:17:29,160
Speaker 1: dealing because damn valley in Germany. I don't give what

1414
01:17:29,240 --> 01:17:32,040
Speaker 1: they call their value. But but not all the papers

1415
01:17:32,080 --> 01:17:34,040
Speaker 1: have the H back in though. That was good because

1416
01:17:34,120 --> 01:17:36,400
Speaker 1: it was kind of awkward to say. I never know

1417
01:17:36,479 --> 01:17:39,120
Speaker 1: what to do in those circumstances, man, like how I

1418
01:17:39,160 --> 01:17:43,040
Speaker 1: went to switch. I've switched to pronghorn, trying to switch.

1419
01:17:43,520 --> 01:17:47,519
Speaker 1: I even labeled my meat pronghorn. No, it confuses people. Yeah,

1420
01:17:47,560 --> 01:17:51,040
Speaker 1: you don't believe me, you go look hell yeah, And

1421
01:17:51,080 --> 01:17:54,519
Speaker 1: I've given it to people and they've registered confusion. Really,

1422
01:17:54,920 --> 01:17:57,360
Speaker 1: that's so funny. You don't label your packages prong horn.

1423
01:17:57,760 --> 01:18:03,680
Speaker 1: I do not. They don't antilo capra on my go.

1424
01:18:05,439 --> 01:18:08,559
Speaker 1: You know, there was eighteen eighteen different types of primitive

1425
01:18:08,680 --> 01:18:12,840
Speaker 1: antilo capra pronghorn families in North America eighteen million years ago.

1426
01:18:13,120 --> 01:18:16,360
Speaker 1: For eighteen million years, we had eighteen different types of

1427
01:18:16,400 --> 01:18:19,559
Speaker 1: prong worns. Some had corkscrew horn corps, some had three

1428
01:18:19,640 --> 01:18:22,640
Speaker 1: horn cores on both sides, six total horn cores. A

1429
01:18:22,720 --> 01:18:25,040
Speaker 1: lot of them had two on each side. I wrote

1430
01:18:25,760 --> 01:18:30,360
Speaker 1: a field guide it's called a Bestieri of Ancestral antilocaporates

1431
01:18:30,680 --> 01:18:35,240
Speaker 1: and it's illustration, wrote that, yeah, with another machine man.

1432
01:18:35,439 --> 01:18:38,479
Speaker 1: Well that's interesting stuff. Eighteen different kinds of prong worn

1433
01:18:38,520 --> 01:18:41,120
Speaker 1: and they all went extinct except for the American pronghorn

1434
01:18:41,200 --> 01:18:43,599
Speaker 1: that we have. And so we had illustrations that Randy

1435
01:18:43,640 --> 01:18:47,760
Speaker 1: bab did illustrations of each one of those skulls. And

1436
01:18:47,840 --> 01:18:50,519
Speaker 1: then I wrote a paragraph which was anything we knew

1437
01:18:50,560 --> 01:18:52,200
Speaker 1: about it. And we had a map of where the

1438
01:18:52,240 --> 01:18:54,000
Speaker 1: fossils have been found, so it was like a little

1439
01:18:54,040 --> 01:18:58,240
Speaker 1: field guide. How far are you, Florida. There's different kinds

1440
01:18:58,240 --> 01:19:00,960
Speaker 1: always over there. If you would have named it kinds

1441
01:19:01,520 --> 01:19:04,880
Speaker 1: of a kind of you would have been on the

1442
01:19:04,920 --> 01:19:07,559
Speaker 1: same shelf. You know. Whenever I started getting depressed about

1443
01:19:07,880 --> 01:19:10,840
Speaker 1: all the animals aren't around anymore, I always to help

1444
01:19:11,000 --> 01:19:14,839
Speaker 1: not be depressed, I remind myself that the largest animal

1445
01:19:15,040 --> 01:19:21,280
Speaker 1: to ever exist larger than the biggest of Brontosaurus or

1446
01:19:21,560 --> 01:19:25,639
Speaker 1: argent two soaurus, the biggest animal to ever have ever

1447
01:19:25,880 --> 01:19:30,479
Speaker 1: existed on Earth. Right now, it's still here, right, We're

1448
01:19:30,479 --> 01:19:34,680
Speaker 1: in the good old days. The biggest animal ever is

1449
01:19:34,760 --> 01:19:37,320
Speaker 1: here right now, the good old days of megafono. We've

1450
01:19:37,320 --> 01:19:41,439
Speaker 1: got them now. Yeah, Because you get looking at my

1451
01:19:41,520 --> 01:19:44,000
Speaker 1: kids like dinosaur books and I need to look at that.

1452
01:19:44,040 --> 01:19:46,639
Speaker 1: I'm like man kind of little jealous about that. Oh

1453
01:19:46,920 --> 01:19:50,439
Speaker 1: so jealous. I just to lay eyes and get your

1454
01:19:50,479 --> 01:19:53,960
Speaker 1: brain wrapped around the scale. I want, I want it.

1455
01:19:54,160 --> 01:19:55,680
Speaker 1: We talked a lot about whether they have been a

1456
01:19:55,680 --> 01:19:58,960
Speaker 1: good eating or not. One of my kids thinks they

1457
01:19:59,000 --> 01:20:00,360
Speaker 1: would have been on one of the things. They wouldn't

1458
01:20:00,360 --> 01:20:04,519
Speaker 1: have been very good eating. Yeah, I don't know. Reptile Like, Okay,

1459
01:20:04,560 --> 01:20:07,519
Speaker 1: moving on, this is a little bit I want to

1460
01:20:07,560 --> 01:20:09,960
Speaker 1: talk about, like you really mixed up in the wolf world.

1461
01:20:11,200 --> 01:20:14,160
Speaker 1: I am. Yeah. I would put on the Mexican wolf

1462
01:20:14,200 --> 01:20:18,160
Speaker 1: Recovery team in December and was on it for two years.

1463
01:20:18,240 --> 01:20:22,920
Speaker 1: Resigned in December of UM and with my resignation letter

1464
01:20:23,000 --> 01:20:26,439
Speaker 1: added ah about a fourteen page report sighting all of

1465
01:20:26,520 --> 01:20:31,120
Speaker 1: the scientific process flaws that were that I saw in

1466
01:20:31,760 --> 01:20:33,679
Speaker 1: the writing of what was supposed to be the draft

1467
01:20:33,760 --> 01:20:35,479
Speaker 1: recovery plan at that time. That's what we were put

1468
01:20:35,520 --> 01:20:38,560
Speaker 1: together for a couple of months later, the remainder of

1469
01:20:38,600 --> 01:20:42,439
Speaker 1: the team UM went had and submitted a report had

1470
01:20:42,520 --> 01:20:45,160
Speaker 1: so many flaws. As I pointed out, Fish and Wilad

1471
01:20:45,200 --> 01:20:47,479
Speaker 1: Servis couldn't do anything with it. They couldn't they couldn't

1472
01:20:47,479 --> 01:20:51,840
Speaker 1: make that their their draft plan. Um. They just stakeholders

1473
01:20:51,840 --> 01:20:55,479
Speaker 1: weren't involved. State agencies were just seen as, uh, maybe

1474
01:20:55,520 --> 01:20:58,560
Speaker 1: stakeholders will we'll talk to you later. Um. And it

1475
01:20:58,600 --> 01:21:02,360
Speaker 1: went nowhere. So back away up They're like, what's the problem,

1476
01:21:02,439 --> 01:21:05,680
Speaker 1: Like what happened we used to have? I mean, the

1477
01:21:05,800 --> 01:21:08,080
Speaker 1: wolves were like continue they had them in Alaska. There

1478
01:21:08,160 --> 01:21:10,320
Speaker 1: was no like place without them. They just ran all

1479
01:21:10,400 --> 01:21:13,840
Speaker 1: right down into Mexico. And people mistakenly just think about

1480
01:21:13,880 --> 01:21:18,160
Speaker 1: the Mexican wolf as um just the southern part of

1481
01:21:18,280 --> 01:21:21,599
Speaker 1: a blending of different wolf sizes and wolf subspecies throughout

1482
01:21:21,640 --> 01:21:24,400
Speaker 1: the continent. We used to have a twenty four wolf

1483
01:21:24,439 --> 01:21:27,920
Speaker 1: subspecies in North America and Rohn no Wack boiled that

1484
01:21:28,040 --> 01:21:31,360
Speaker 1: down to five that seemed ecologically different in different areas.

1485
01:21:33,000 --> 01:21:36,679
Speaker 1: Um Arctic, well, there was a um occide and Talus,

1486
01:21:36,720 --> 01:21:39,320
Speaker 1: which is a big Canadian wolf, and in Alaska and

1487
01:21:39,360 --> 01:21:41,320
Speaker 1: then New Bliss, which is mid continent most of the

1488
01:21:41,400 --> 01:21:44,880
Speaker 1: United States, and then Bailey I, which is the Mexican wolf,

1489
01:21:45,320 --> 01:21:51,280
Speaker 1: and then there was the Arctic wolf and I can't

1490
01:21:51,320 --> 01:21:52,800
Speaker 1: remember what the other one one. In the Arctic wolves

1491
01:21:52,800 --> 01:21:55,519
Speaker 1: they run white a fair bit, yea, yea. And so

1492
01:21:55,720 --> 01:21:59,000
Speaker 1: the Canadian down in the Canadian High Arctic, Elsmere Island

1493
01:21:59,040 --> 01:22:01,519
Speaker 1: and that sort of thing. And so so these are

1494
01:22:01,600 --> 01:22:03,760
Speaker 1: kind of groups of wolves that it kind of makes sense.

1495
01:22:04,120 --> 01:22:07,960
Speaker 1: The Mexican wolf is not just the southern tip of

1496
01:22:08,080 --> 01:22:12,559
Speaker 1: a big wolf distribution that blended um freely with New Bliss,

1497
01:22:12,600 --> 01:22:15,160
Speaker 1: the other wolf to the north. The Mexican wolf evolved

1498
01:22:15,200 --> 01:22:17,439
Speaker 1: in the Sierra Madre, like we're talking about white tails.

1499
01:22:17,760 --> 01:22:22,000
Speaker 1: And that's another reason Mexican wolves are physically different. They're

1500
01:22:22,040 --> 01:22:25,559
Speaker 1: genetically different. They're the most genetically different wolf subspecies when

1501
01:22:25,600 --> 01:22:28,719
Speaker 1: they look at genetics. But they weren't just in Mexico,

1502
01:22:29,520 --> 01:22:32,519
Speaker 1: and they were only in Mexico and the Sky Islands

1503
01:22:32,560 --> 01:22:35,439
Speaker 1: in southern Arizona and southwestern New Mexico. That was the

1504
01:22:35,520 --> 01:22:38,639
Speaker 1: historical range of the Mexican wolf. Some of those almost

1505
01:22:38,680 --> 01:22:43,360
Speaker 1: overlaps with Cosier and and Got and Got Turkey and

1506
01:22:43,479 --> 01:22:48,560
Speaker 1: so and and evolutionary ecologists will talk about subspecies just

1507
01:22:48,680 --> 01:22:50,880
Speaker 1: have more support when there's a whole bunch of other

1508
01:22:51,040 --> 01:22:54,160
Speaker 1: unrelated animals that have that same distribution. It just makes

1509
01:22:54,200 --> 01:22:57,840
Speaker 1: sense that there are some ecological forces that allowed those

1510
01:22:57,920 --> 01:23:01,679
Speaker 1: animals of different types to to evolve a little bit differently.

1511
01:23:01,720 --> 01:23:04,640
Speaker 1: As a subspecies, and in that same range you have

1512
01:23:04,760 --> 01:23:08,679
Speaker 1: this like very different type of turkey, very different type

1513
01:23:08,680 --> 01:23:10,479
Speaker 1: of deer, very different type of quail. And if you

1514
01:23:10,520 --> 01:23:14,000
Speaker 1: look at ecological zones plants in the plant community, that

1515
01:23:14,160 --> 01:23:17,040
Speaker 1: that whole Um Madri and oak woodland, they call it

1516
01:23:17,400 --> 01:23:19,920
Speaker 1: that the Sierra Madre is is typical of is different

1517
01:23:19,960 --> 01:23:22,599
Speaker 1: than the Muggian rim in northern Arizona northern New Mexico.

1518
01:23:22,800 --> 01:23:24,960
Speaker 1: So it all makes sense that and and all of

1519
01:23:25,080 --> 01:23:29,760
Speaker 1: the about twenty different mammalogists and ecologists subscribe abscribe the

1520
01:23:29,960 --> 01:23:34,040
Speaker 1: Mexican wolf historical range like that southern Arizona, southern New

1521
01:23:34,080 --> 01:23:36,519
Speaker 1: Mexico and all of the Sierra Madre. Now, some of

1522
01:23:36,560 --> 01:23:39,120
Speaker 1: the Mexican wolves skull measurements have shown that some of

1523
01:23:39,200 --> 01:23:41,760
Speaker 1: the Mexican wolves would disperse up into the Muggian rim

1524
01:23:41,840 --> 01:23:44,120
Speaker 1: like you would expect to the Muggian rims central Arizona

1525
01:23:44,360 --> 01:23:47,439
Speaker 1: and the Healand National Forest in central New Mexico. So

1526
01:23:47,560 --> 01:23:50,360
Speaker 1: some of the Mexican wolves dispersed up there. Those wolves

1527
01:23:50,400 --> 01:23:53,920
Speaker 1: in northern Arizona northern New Mexico were measurably larger. The

1528
01:23:53,960 --> 01:23:56,680
Speaker 1: skull measurements everything were larger, and they some of those

1529
01:23:56,760 --> 01:23:59,040
Speaker 1: would dispersed down the Muggian rim. If you look at

1530
01:23:59,120 --> 01:24:02,360
Speaker 1: the like Google Earth and you just zoom out, you

1531
01:24:02,439 --> 01:24:05,040
Speaker 1: see the Sierra Madrea, this big green patch where the

1532
01:24:05,200 --> 01:24:08,599
Speaker 1: Mexican wolf was, and then the southern Rockies is another

1533
01:24:08,760 --> 01:24:11,960
Speaker 1: huge green patch. And in between there there's this healand

1534
01:24:12,040 --> 01:24:15,439
Speaker 1: national force Muggian rim with non wolf habitat to the

1535
01:24:15,520 --> 01:24:17,439
Speaker 1: north of it, non wolf habitat to the south of it.

1536
01:24:17,560 --> 01:24:21,559
Speaker 1: So Mexican wolves dispersed up, bigger wolves, neubialists dispersed south,

1537
01:24:21,960 --> 01:24:24,880
Speaker 1: and those wolves from skull measurements, those wolves in the

1538
01:24:25,040 --> 01:24:28,200
Speaker 1: central Arizona, New Mexico are intermediate in size. Actually, the

1539
01:24:28,760 --> 01:24:31,280
Speaker 1: males group better with Mexican wolves down there, and the

1540
01:24:31,320 --> 01:24:33,680
Speaker 1: females group with the northern wolves. Con indication that they

1541
01:24:33,720 --> 01:24:36,519
Speaker 1: were intermediate between those two forms. So we did have

1542
01:24:36,640 --> 01:24:39,640
Speaker 1: some geographic separation which accounts for the genetic differences of

1543
01:24:39,640 --> 01:24:43,280
Speaker 1: physical differences in Mexican wolves. They're not just um some

1544
01:24:43,439 --> 01:24:46,040
Speaker 1: subspecies that's blending in with all the other subspecies. There's

1545
01:24:46,080 --> 01:24:49,120
Speaker 1: some reasons why they're geographically and and all those other

1546
01:24:49,160 --> 01:24:53,720
Speaker 1: reasons why they're different. Uh, give me the pros and

1547
01:24:53,800 --> 01:24:55,880
Speaker 1: cons as much as you're comfortable, Like, what are the

1548
01:24:55,920 --> 01:24:59,840
Speaker 1: pros and cons with trying to bring them back? I

1549
01:25:00,000 --> 01:25:02,759
Speaker 1: think they I mean, Mexican wolves were a native wildlife

1550
01:25:02,800 --> 01:25:06,640
Speaker 1: species um in the Southwest, and I think if if

1551
01:25:06,720 --> 01:25:08,439
Speaker 1: we as hunters are going to thump our chest and

1552
01:25:08,479 --> 01:25:11,760
Speaker 1: talk about out bringing elk back and bringing turkeys back

1553
01:25:11,840 --> 01:25:15,000
Speaker 1: and all these species that we call unendangered, we can't

1554
01:25:15,040 --> 01:25:17,200
Speaker 1: stop at the predators. I mean, I just think it

1555
01:25:17,240 --> 01:25:19,280
Speaker 1: makes sense. We just need to they have a place

1556
01:25:19,400 --> 01:25:22,040
Speaker 1: in the in the Southwest, and and we need to

1557
01:25:22,080 --> 01:25:24,240
Speaker 1: be working to bring them back. Most of the public

1558
01:25:24,760 --> 01:25:26,920
Speaker 1: thinks bowls are pretty cool. They want to see wolves back,

1559
01:25:27,439 --> 01:25:30,160
Speaker 1: and so as hunters do we really want to position

1560
01:25:30,200 --> 01:25:32,360
Speaker 1: ourselves on the other side of the table from them

1561
01:25:32,400 --> 01:25:34,519
Speaker 1: and say, no, we don't want to bring wolves back

1562
01:25:34,720 --> 01:25:37,800
Speaker 1: because um, they eat elk and we want to hunt

1563
01:25:37,840 --> 01:25:40,559
Speaker 1: out might impact our elk counting. So there's some real

1564
01:25:40,760 --> 01:25:43,519
Speaker 1: challenges with bringing wolves back, but that doesn't mean we

1565
01:25:43,560 --> 01:25:45,479
Speaker 1: shouldn't do it. We we need to have programs to

1566
01:25:45,520 --> 01:25:49,240
Speaker 1: work with lifetock industry to to make sure those operators

1567
01:25:49,360 --> 01:25:52,000
Speaker 1: and it's usually only a few operators that are uh

1568
01:25:52,120 --> 01:25:54,639
Speaker 1: impacted heavily, but those that are impact heavily. We should

1569
01:25:54,640 --> 01:25:57,000
Speaker 1: have programs that help them out. We can't just say, well,

1570
01:25:57,080 --> 01:25:58,960
Speaker 1: you're a grazing on public land and we're gonna bring

1571
01:25:59,000 --> 01:26:00,519
Speaker 1: wols back and we don't care about what happens to you.

1572
01:26:00,720 --> 01:26:02,200
Speaker 1: We need to work with them where it's not gonna

1573
01:26:02,240 --> 01:26:05,160
Speaker 1: work at all. And as far as the big game populations,

1574
01:26:06,040 --> 01:26:10,120
Speaker 1: you when where we have wolves, we have some hotspots

1575
01:26:10,120 --> 01:26:13,160
Speaker 1: where wolves have impact elk populations and we need to

1576
01:26:13,200 --> 01:26:16,439
Speaker 1: have management flexibility to do something about that when that happens.

1577
01:26:16,479 --> 01:26:18,679
Speaker 1: Predators have to be managed just like we managed prey.

1578
01:26:19,120 --> 01:26:22,240
Speaker 1: But in a lot of areas, wolves are back on

1579
01:26:22,280 --> 01:26:25,439
Speaker 1: the landscape and they're not heavily impacting elk populations, and

1580
01:26:25,560 --> 01:26:27,560
Speaker 1: so I just think we need to make room for

1581
01:26:27,960 --> 01:26:30,120
Speaker 1: for wolves on the on the landscape. They belong here.

1582
01:26:30,720 --> 01:26:35,920
Speaker 1: You know, you've been involved in state wildlife for your career.

1583
01:26:37,120 --> 01:26:39,559
Speaker 1: There's a lot of tension between it seizes, a lot

1584
01:26:39,600 --> 01:26:41,320
Speaker 1: of not seems. I mean there there is. There's a

1585
01:26:41,360 --> 01:26:44,479
Speaker 1: lot of tension between federal wildlife management decisions and state

1586
01:26:44,520 --> 01:26:48,519
Speaker 1: wildlife management decisions. Um, do you think it's fair to say,

1587
01:26:48,960 --> 01:26:52,240
Speaker 1: just look back at at American history, it's fair to

1588
01:26:52,320 --> 01:26:58,439
Speaker 1: say that if there was no federal oversight of endangered species,

1589
01:26:58,479 --> 01:27:02,200
Speaker 1: and there was no federal wildlife involvement. It would be

1590
01:27:02,680 --> 01:27:07,280
Speaker 1: fair to say that it wouldn't have happened there were

1591
01:27:07,360 --> 01:27:09,320
Speaker 1: We wouldn't have done any real we wouldn't have done

1592
01:27:09,360 --> 01:27:12,840
Speaker 1: any active reintroduction efforts that would have been at to

1593
01:27:13,000 --> 01:27:16,280
Speaker 1: this point in time that would have been spawned by

1594
01:27:16,360 --> 01:27:19,519
Speaker 1: the states. And talking about wolves specifically, yeah, yeah, I

1595
01:27:19,600 --> 01:27:21,760
Speaker 1: think I think it's something that's been, like for better

1596
01:27:21,880 --> 01:27:25,160
Speaker 1: or worse, the state's top now And when I talked

1597
01:27:25,360 --> 01:27:27,639
Speaker 1: poorly about the when I was on the Mexican wolf

1598
01:27:27,760 --> 01:27:32,000
Speaker 1: recovery team and that effort, we reinitiated that in two

1599
01:27:32,080 --> 01:27:36,960
Speaker 1: thousand fifteen and in December, and Fishing Wild Services did

1600
01:27:36,960 --> 01:27:40,400
Speaker 1: it completely different. Fishing Wild Service invited state agency people

1601
01:27:40,720 --> 01:27:43,200
Speaker 1: to the table in a series of workshops to develop

1602
01:27:43,600 --> 01:27:46,320
Speaker 1: um a recovery plan that they would they would then right.

1603
01:27:46,840 --> 01:27:49,040
Speaker 1: And that was a whole different process because we had

1604
01:27:49,080 --> 01:27:51,799
Speaker 1: a neutral facilitator who was in charge of a population

1605
01:27:51,920 --> 01:27:55,680
Speaker 1: viability analysis instead of in past efforts, it's been some

1606
01:27:56,280 --> 01:28:01,479
Speaker 1: some academics that are very advocacy oriented, very protectionists oriented,

1607
01:28:01,520 --> 01:28:03,240
Speaker 1: and they were in charge of writing the recovery plan

1608
01:28:03,320 --> 01:28:07,160
Speaker 1: which didn't work repeatedly. This The recovery team that I

1609
01:28:07,280 --> 01:28:10,040
Speaker 1: was on was the fourth recovery team to try to

1610
01:28:10,120 --> 01:28:12,400
Speaker 1: write a revision of the Mexic wolf recovery Plan. There

1611
01:28:12,439 --> 01:28:14,680
Speaker 1: was one written in eighty two. It wasn't adequate, it

1612
01:28:14,680 --> 01:28:16,920
Speaker 1: didn't have recovery criteria, and everybody agreed it need to

1613
01:28:16,920 --> 01:28:20,040
Speaker 1: be rewritten. They kept failing because you can't get a

1614
01:28:20,040 --> 01:28:23,680
Speaker 1: handful of academics with a real protectionist kind of attitude

1615
01:28:23,680 --> 01:28:26,559
Speaker 1: together and have them right a Mexican wolf recovery plan.

1616
01:28:26,720 --> 01:28:31,080
Speaker 1: Explain to protectionist attitude, not ever wanting a wolf to

1617
01:28:31,120 --> 01:28:33,920
Speaker 1: die at the hands of man, no matter what I mean,

1618
01:28:34,040 --> 01:28:38,000
Speaker 1: Just like we want to craft some recovery criteria that

1619
01:28:38,080 --> 01:28:40,360
Speaker 1: will make it nearly impossible for them to ever be

1620
01:28:40,479 --> 01:28:43,400
Speaker 1: delisted and leave the protection of the federal government, which

1621
01:28:43,439 --> 01:28:46,160
Speaker 1: is not what the Endangered Species Act is. Danger Species

1622
01:28:46,200 --> 01:28:48,640
Speaker 1: Act is is that we're supposed to. It's like an

1623
01:28:48,680 --> 01:28:52,479
Speaker 1: emergency room. Someone just ready to are almost close to dying.

1624
01:28:52,720 --> 01:28:54,559
Speaker 1: You bring in an emergency room and you just get

1625
01:28:54,640 --> 01:28:56,760
Speaker 1: them well enough so that they're not going to die,

1626
01:28:56,840 --> 01:28:59,120
Speaker 1: and then you hand them over to um. You put

1627
01:28:59,200 --> 01:29:00,439
Speaker 1: them in a hospital bed, You put them in the

1628
01:29:00,479 --> 01:29:02,639
Speaker 1: hospital and then you monitor them and then you improve

1629
01:29:02,720 --> 01:29:04,920
Speaker 1: their health. Endangered Species Act is supposed to be like

1630
01:29:05,040 --> 01:29:07,320
Speaker 1: that with species, where we're just ready to lose them,

1631
01:29:07,600 --> 01:29:09,320
Speaker 1: we do everything we can to save them. We get

1632
01:29:09,360 --> 01:29:11,519
Speaker 1: them up to a certain level where we're comfortable that

1633
01:29:11,560 --> 01:29:14,160
Speaker 1: they're not no longer in danger of extinction, and then

1634
01:29:14,240 --> 01:29:16,000
Speaker 1: we pass them off to the state agencies and they

1635
01:29:16,040 --> 01:29:18,240
Speaker 1: manage them like all the other carnivores. They manage. Yeah.

1636
01:29:18,240 --> 01:29:20,760
Speaker 1: I've often joked in in some with some species. It's

1637
01:29:20,800 --> 01:29:23,840
Speaker 1: become the my favorite animal protection Act. It is, it

1638
01:29:23,880 --> 01:29:26,880
Speaker 1: absolutely is, and that's does such a disservice to the

1639
01:29:27,040 --> 01:29:29,519
Speaker 1: two thousand other species that are listed on the Endangered

1640
01:29:29,520 --> 01:29:31,920
Speaker 1: Species Act. We've got species that legitimately are going to

1641
01:29:31,960 --> 01:29:34,519
Speaker 1: blink out and we're gonna lose. And we've got four

1642
01:29:34,600 --> 01:29:38,320
Speaker 1: thousand wolves in the in the western Great Lakes, and

1643
01:29:38,439 --> 01:29:41,400
Speaker 1: we've got people writing scientific papers and filing lawsuits saying

1644
01:29:41,400 --> 01:29:44,000
Speaker 1: they're still in danger of extinction. And we've got fifteen

1645
01:29:44,040 --> 01:29:47,400
Speaker 1: hundred in the Northern Rockies that are delisted, got sixty

1646
01:29:47,479 --> 01:29:51,800
Speaker 1: five thousand in Alaska and Canada, hundred ten thousand wolves worldwide,

1647
01:29:52,560 --> 01:29:54,680
Speaker 1: and and we can't delist the wolves in the four

1648
01:29:54,720 --> 01:29:57,599
Speaker 1: thousand wolves in the Great Lakes region when the recovery

1649
01:29:57,600 --> 01:30:00,639
Speaker 1: criteria was about fifteen hundred wolves, and we four thousand

1650
01:30:00,680 --> 01:30:04,960
Speaker 1: and wolves and we've got four thousand, and people are

1651
01:30:05,040 --> 01:30:07,680
Speaker 1: still suing saying they're still in danger of extinction and

1652
01:30:08,120 --> 01:30:11,200
Speaker 1: we can't do that. We need to we need to

1653
01:30:11,200 --> 01:30:13,680
Speaker 1: work together on the other two thousand species that need

1654
01:30:13,760 --> 01:30:16,960
Speaker 1: our help where they're legitimately going to disappear from the earth. Jim,

1655
01:30:17,000 --> 01:30:19,760
Speaker 1: what do you say to And I'm sure you've heard

1656
01:30:19,840 --> 01:30:23,840
Speaker 1: this argument, because I have many times as well. There's

1657
01:30:23,840 --> 01:30:29,639
Speaker 1: a value in having this animal on the endangered species

1658
01:30:29,720 --> 01:30:34,320
Speaker 1: list because it brings attention to the endangered species. I

1659
01:30:34,439 --> 01:30:37,519
Speaker 1: tell you it's gonna bring that. Is that provision written

1660
01:30:37,560 --> 01:30:41,320
Speaker 1: into the Endangered Species Act? The last time says oh,

1661
01:30:41,520 --> 01:30:45,639
Speaker 1: and but you've heard of this. I'm not that familiar

1662
01:30:45,640 --> 01:30:47,840
Speaker 1: with this argument. But I mean, at some point, doesn't

1663
01:30:47,840 --> 01:30:51,000
Speaker 1: it kind of matter about the access Oh god, yeah,

1664
01:30:51,200 --> 01:30:55,479
Speaker 1: absolutely absolutely. But it's like, well, you know, nobody's gonna

1665
01:30:55,600 --> 01:31:00,840
Speaker 1: care about the whatever snail or butter or fly if

1666
01:31:00,920 --> 01:31:05,920
Speaker 1: we don't have the grizzly bear. Yeah, it's gonna That

1667
01:31:06,000 --> 01:31:08,240
Speaker 1: doesn't even kind of surprise me. But I haven't heard

1668
01:31:08,280 --> 01:31:12,320
Speaker 1: that this, if, if, this is the kind of thing

1669
01:31:12,400 --> 01:31:15,160
Speaker 1: that's gonna gonna ruin the Endangered Species Act is going

1670
01:31:15,200 --> 01:31:17,639
Speaker 1: to destroy the Endangered Species at some of these people

1671
01:31:18,200 --> 01:31:20,880
Speaker 1: pushing and pushing and pushing at these ridiculous notions that

1672
01:31:21,200 --> 01:31:24,080
Speaker 1: we need to still have federal protection on a species

1673
01:31:24,120 --> 01:31:27,880
Speaker 1: like wolf is just gonna fuel the fire and we'll

1674
01:31:27,920 --> 01:31:31,759
Speaker 1: have the Endangered Species Act completely renovated. Oh, it's already happening.

1675
01:31:32,280 --> 01:31:36,760
Speaker 1: People get like some state agencies get so frustrated and

1676
01:31:37,200 --> 01:31:40,280
Speaker 1: certain you know, live style groups whatever, get so frustrated

1677
01:31:40,320 --> 01:31:43,040
Speaker 1: with the conversations around grizzly bears and wolves that when

1678
01:31:43,080 --> 01:31:45,160
Speaker 1: they hear it's like what happened Like it's like kind

1679
01:31:45,160 --> 01:31:47,120
Speaker 1: of like the level of damage that happened to the

1680
01:31:47,600 --> 01:31:50,040
Speaker 1: e s a around the spot at owl. It's like

1681
01:31:50,160 --> 01:31:53,519
Speaker 1: you turn these animals into something where the animal becomes

1682
01:31:53,600 --> 01:31:57,920
Speaker 1: symbolic of a kind of foot dragging, and then the

1683
01:31:58,080 --> 01:32:01,000
Speaker 1: Act becomes that it's just like a thing used to

1684
01:32:02,120 --> 01:32:07,280
Speaker 1: wield power about grizzly bear management, and people just get piste. Yep,

1685
01:32:07,479 --> 01:32:09,800
Speaker 1: that's not gonna end well, not gonna end well. We

1686
01:32:09,880 --> 01:32:12,000
Speaker 1: need to get these species up so they're no longer

1687
01:32:12,040 --> 01:32:14,000
Speaker 1: in danger of extinction, which is what the Act is,

1688
01:32:14,400 --> 01:32:16,720
Speaker 1: and then pass them off to the state agencies and

1689
01:32:17,000 --> 01:32:19,719
Speaker 1: and ed bangs lad the wolf recovery in the Northern Rockies,

1690
01:32:19,720 --> 01:32:23,160
Speaker 1: he's fishing wallead service of quote unquote FED. He told

1691
01:32:23,240 --> 01:32:25,880
Speaker 1: everybody the entire time. He says, our goal is to

1692
01:32:25,960 --> 01:32:28,840
Speaker 1: get these up above the recovery criteria that everybody agreed

1693
01:32:28,880 --> 01:32:30,600
Speaker 1: on and pass it off to the states. They do

1694
01:32:30,680 --> 01:32:33,519
Speaker 1: a great job managing wildlife, and that's what my goal

1695
01:32:33,880 --> 01:32:36,200
Speaker 1: is to recover in the in the Rockies. That that's

1696
01:32:36,240 --> 01:32:39,240
Speaker 1: the thing too that happens that that is troublesome. Is

1697
01:32:39,640 --> 01:32:42,880
Speaker 1: this this thing that it's the feeds. Listen, it's the FEDS.

1698
01:32:43,800 --> 01:32:48,280
Speaker 1: They keep proposing wolves get delisted in the Great Lakes.

1699
01:32:48,400 --> 01:32:51,120
Speaker 1: It's the FEDS that proposed the grizzly bears. But people

1700
01:32:51,160 --> 01:32:53,040
Speaker 1: were like, oh, the Feds. Yeah, the Feds are the

1701
01:32:53,080 --> 01:32:54,320
Speaker 1: ones saying they want to deal it. They're the ones

1702
01:32:54,360 --> 01:32:55,920
Speaker 1: that put them up for delisting, and they get sued

1703
01:32:56,000 --> 01:32:57,920
Speaker 1: and they're not allowed to because the lawsuits. Yeah, it's

1704
01:32:57,920 --> 01:33:00,200
Speaker 1: like a handful of like you know, it's anti money

1705
01:33:00,200 --> 01:33:03,920
Speaker 1: groups that kind of masquerade as environmental groups or that

1706
01:33:04,120 --> 01:33:07,160
Speaker 1: that do both, that serve both functions. What what is

1707
01:33:07,320 --> 01:33:10,360
Speaker 1: the most hurtful when you go to some of these

1708
01:33:10,920 --> 01:33:13,639
Speaker 1: UH fish and wildlife meetings and you have you see

1709
01:33:13,680 --> 01:33:18,360
Speaker 1: this argument being played out before you. Is is they're

1710
01:33:18,400 --> 01:33:21,680
Speaker 1: trying to kill them all and state agencies will just

1711
01:33:21,760 --> 01:33:23,360
Speaker 1: kill them all and they'll be on the endangered species

1712
01:33:23,720 --> 01:33:26,840
Speaker 1: and and it's you know, they don't believe in like, well, listen,

1713
01:33:26,920 --> 01:33:29,720
Speaker 1: we have this mandate that says this is what we

1714
01:33:29,840 --> 01:33:32,360
Speaker 1: are supposed to do, and we just spend a shipload

1715
01:33:32,400 --> 01:33:33,800
Speaker 1: of money and get them off the list. And I

1716
01:33:33,960 --> 01:33:37,000
Speaker 1: just I want to say, how familiar are you with

1717
01:33:37,560 --> 01:33:39,800
Speaker 1: how we got rid of wolves in the first place

1718
01:33:39,960 --> 01:33:43,599
Speaker 1: and that time frame. I'm like, if people were trying

1719
01:33:43,640 --> 01:33:46,800
Speaker 1: to kill wolves now, they would be gone. They would

1720
01:33:46,840 --> 01:33:49,360
Speaker 1: be gone gone because we did it very very well

1721
01:33:49,840 --> 01:33:54,360
Speaker 1: in a time without satellites, without GPS, without two way communication,

1722
01:33:55,120 --> 01:33:57,799
Speaker 1: Like we just use a little bit of poison. Yeah,

1723
01:33:57,880 --> 01:34:00,680
Speaker 1: And what what a lot of pro wolf groups and

1724
01:34:00,880 --> 01:34:02,840
Speaker 1: it sounds funny because I'm pro wolf too, but but

1725
01:34:03,000 --> 01:34:06,160
Speaker 1: a lot a lot of the protections groups won't acknowledge

1726
01:34:06,320 --> 01:34:09,880
Speaker 1: is that the contributions of sportsmen through the decades have

1727
01:34:10,040 --> 01:34:13,760
Speaker 1: brought back the prey base in in huge numbers that

1728
01:34:13,880 --> 01:34:17,400
Speaker 1: allows us to recover wolves, not just a better kind

1729
01:34:17,439 --> 01:34:20,720
Speaker 1: of conservation ethic that the population has, which is true,

1730
01:34:21,360 --> 01:34:23,519
Speaker 1: it's the prey base. We couldn't do it if if

1731
01:34:23,560 --> 01:34:26,560
Speaker 1: we didn't have all of this prey Jim talked a

1732
01:34:26,560 --> 01:34:30,680
Speaker 1: little bit about your article were you the article you

1733
01:34:30,720 --> 01:34:33,600
Speaker 1: wrote where you talk about the public's enthusiasm for like

1734
01:34:33,760 --> 01:34:39,360
Speaker 1: trophic cascades, that trophic cascades also becomes like everybody's favorite word. Yeah,

1735
01:34:39,560 --> 01:34:42,360
Speaker 1: favorite phrase. That's that's another thing like trophy hunting, that

1736
01:34:42,800 --> 01:34:46,960
Speaker 1: that far outpaced the science behind it. So you're always

1737
01:34:47,000 --> 01:34:49,760
Speaker 1: playing trophic cascades. We need to do that and then

1738
01:34:49,800 --> 01:34:52,599
Speaker 1: talk about the you know whatever. He's like all hopped

1739
01:34:52,640 --> 01:34:54,200
Speaker 1: up on the idea that all it takes is a

1740
01:34:54,280 --> 01:34:57,639
Speaker 1: couple of wolves and their their rivers run clear again.

1741
01:34:57,760 --> 01:35:01,400
Speaker 1: And yeah, so tropic cascades just basically a trophic level

1742
01:35:01,439 --> 01:35:04,439
Speaker 1: in in ecology is like the vegetations one trophic level,

1743
01:35:04,640 --> 01:35:07,320
Speaker 1: and then you may have elk representing the second trophic

1744
01:35:07,439 --> 01:35:10,160
Speaker 1: level above that helk eating the vegetation, and then you

1745
01:35:10,240 --> 01:35:12,920
Speaker 1: have a third trophic level, which might be wolves which

1746
01:35:13,240 --> 01:35:16,120
Speaker 1: eat the elk, and so you have these three trophic levels,

1747
01:35:16,160 --> 01:35:18,519
Speaker 1: and the idea of trophic cascades is that if you've

1748
01:35:18,520 --> 01:35:22,680
Speaker 1: got a situation where you've got elk really impacting, overpopulated

1749
01:35:22,720 --> 01:35:25,320
Speaker 1: elk impacting the vegetation, and you've got too many elk,

1750
01:35:25,760 --> 01:35:28,879
Speaker 1: you bring in wolves on that third trophic level. Wolves

1751
01:35:28,960 --> 01:35:31,799
Speaker 1: impact the elk in such a way that that it relaxed,

1752
01:35:31,880 --> 01:35:34,640
Speaker 1: It relaxes the grazing pressure on the vegetation, and you

1753
01:35:34,720 --> 01:35:37,799
Speaker 1: have more vegetation and you have this recovery of vegetation.

1754
01:35:37,880 --> 01:35:41,240
Speaker 1: So the idea is adding wolves to that system cascades

1755
01:35:41,600 --> 01:35:44,360
Speaker 1: this effect through the trophic levels and where you have

1756
01:35:44,479 --> 01:35:47,240
Speaker 1: actually the addition of wolves affecting how much vegetation there is.

1757
01:35:47,320 --> 01:35:51,280
Speaker 1: So that's basically trophic cascades. So in Yellowstone they put

1758
01:35:51,360 --> 01:35:53,600
Speaker 1: wolves in a ninety five. They put fourteen wolves one

1759
01:35:53,680 --> 01:35:56,439
Speaker 1: year and seventeen the next, and that wolf population grew.

1760
01:35:56,520 --> 01:35:59,000
Speaker 1: But that was Can I interrupt you to use a

1761
01:35:59,080 --> 01:36:02,639
Speaker 1: quote from that era? Yeah? Um, it was in your article.

1762
01:36:03,240 --> 01:36:10,400
Speaker 1: Where's that quote around? Someone described Yellowstone as three thousand,

1763
01:36:10,479 --> 01:36:14,800
Speaker 1: four hundred square miles of paradise surrounded by reality. That

1764
01:36:14,920 --> 01:36:20,679
Speaker 1: was that was that he's the leader of the wolf recovery.

1765
01:36:20,680 --> 01:36:24,720
Speaker 1: In the Rocky Mountain. Very pragmatic. Um, awesome guy. And

1766
01:36:25,080 --> 01:36:27,920
Speaker 1: and so everybody's talking about what's happening in Yellowstone and

1767
01:36:27,960 --> 01:36:31,000
Speaker 1: getting all excited about whatever's happening Yellowstone. That's what's gonna

1768
01:36:31,000 --> 01:36:34,160
Speaker 1: happen everywhere when we put wolves everywhere. But Yellowstone is

1769
01:36:34,240 --> 01:36:36,760
Speaker 1: a whole different deal. And and so that's where he said,

1770
01:36:36,800 --> 01:36:41,120
Speaker 1: that's paradise pause surrounded by reality. And that's so true

1771
01:36:41,160 --> 01:36:44,040
Speaker 1: because what happened in Yellowstone, no matter what happened to Yellowstone,

1772
01:36:44,360 --> 01:36:46,880
Speaker 1: it can't be replicated on on a working landscape with

1773
01:36:47,000 --> 01:36:49,000
Speaker 1: people trying to make a living and working on that

1774
01:36:49,160 --> 01:36:53,519
Speaker 1: landscape that's not Yellowstone everywhere. So so the trophic cascades

1775
01:36:53,560 --> 01:36:56,760
Speaker 1: and in Yellowstone released the World of nine already five

1776
01:36:56,840 --> 01:36:59,200
Speaker 1: years later, some scientists went in there and they measured

1777
01:36:59,280 --> 01:37:02,680
Speaker 1: aspen growth in the northern range, and they concluded that

1778
01:37:02,880 --> 01:37:07,400
Speaker 1: aspen growth was responding. And since the wolves really had

1779
01:37:07,400 --> 01:37:10,479
Speaker 1: an impact of the number of elk yet that they

1780
01:37:10,960 --> 01:37:14,559
Speaker 1: surmised or they theorized that wolves were just chasing elk

1781
01:37:14,680 --> 01:37:18,120
Speaker 1: out of areas where wolf were wolves were chasing elk

1782
01:37:18,360 --> 01:37:20,879
Speaker 1: where the elk would camp out and feed in riparian

1783
01:37:20,960 --> 01:37:24,519
Speaker 1: areas in places. So this scaring elk around by the

1784
01:37:24,600 --> 01:37:28,760
Speaker 1: wolves was distributing the grazing pressure and causing uh A

1785
01:37:29,160 --> 01:37:32,960
Speaker 1: response in the aspen. And that that just kind of

1786
01:37:33,080 --> 01:37:36,920
Speaker 1: speculative paper um was just like the trophy hunting thing.

1787
01:37:36,960 --> 01:37:40,599
Speaker 1: It lit a fuse on on the um popular media

1788
01:37:40,760 --> 01:37:43,840
Speaker 1: and everybody started talking about how the wolf was the

1789
01:37:43,920 --> 01:37:46,519
Speaker 1: savior of the environment. All we did was add wolves.

1790
01:37:46,800 --> 01:37:50,080
Speaker 1: And now we have vegetation responding. We have butterflies coming back,

1791
01:37:50,200 --> 01:37:52,720
Speaker 1: we have bees coming back, we have songbirds, we have

1792
01:37:52,800 --> 01:37:56,560
Speaker 1: beavers coming back to Yellowstone, we have vegetation responding. And

1793
01:37:56,760 --> 01:38:00,080
Speaker 1: and created this narrative based on just a little it

1794
01:38:00,280 --> 01:38:03,880
Speaker 1: of measurement of of aspen in some riperion areas, and

1795
01:38:03,960 --> 01:38:07,200
Speaker 1: the popular media went crazy. They captured the imagination. They

1796
01:38:07,360 --> 01:38:10,519
Speaker 1: love that story. Can you imagine now not only do

1797
01:38:10,640 --> 01:38:13,000
Speaker 1: we do we just want to put wolves back on

1798
01:38:13,040 --> 01:38:15,439
Speaker 1: the landscape, but now we have to put wolves on

1799
01:38:15,479 --> 01:38:19,080
Speaker 1: the landscape to renovate all of this degraded ecosystems. And

1800
01:38:19,120 --> 01:38:20,840
Speaker 1: it's all we need is to add wolves. So can

1801
01:38:20,840 --> 01:38:24,640
Speaker 1: you imagine if they had opened up UM hunting and

1802
01:38:24,760 --> 01:38:29,160
Speaker 1: Yellowstone would have done and they saw corresponding growth and

1803
01:38:29,240 --> 01:38:31,880
Speaker 1: aspens in the news cycle of do you think the

1804
01:38:31,960 --> 01:38:38,479
Speaker 1: news would be champion of cascade? Right, anything can can

1805
01:38:39,160 --> 01:38:42,840
Speaker 1: can precipitate a trophic cascade like that, and so so

1806
01:38:43,040 --> 01:38:46,160
Speaker 1: this firestorm of popular media and then a YouTube video

1807
01:38:46,760 --> 01:38:50,040
Speaker 1: just about everybody has seen. It's got forty million views.

1808
01:38:50,600 --> 01:38:53,720
Speaker 1: That's some British producer um with kind of a David

1809
01:38:53,760 --> 01:38:56,120
Speaker 1: Attenborough kind of that's all it takes, man, You put it,

1810
01:38:56,200 --> 01:38:58,720
Speaker 1: you put it, You put an old brit like, you know,

1811
01:38:59,560 --> 01:39:01,400
Speaker 1: because where they kind of like guy rid of nature

1812
01:39:01,720 --> 01:39:03,040
Speaker 1: to one of those guys at the helm of a

1813
01:39:03,120 --> 01:39:06,759
Speaker 1: nature video and people are like, and that's what happened.

1814
01:39:06,840 --> 01:39:08,640
Speaker 1: He starts out the video saying in the deer and

1815
01:39:08,680 --> 01:39:10,479
Speaker 1: they show these elk running, he says, and the deer

1816
01:39:10,760 --> 01:39:12,920
Speaker 1: gets scared out of And so it's full of errors.

1817
01:39:13,240 --> 01:39:15,280
Speaker 1: But it's got forty million views. And you talk to

1818
01:39:15,320 --> 01:39:17,400
Speaker 1: anyone on the street. Thousand people sent me that video.

1819
01:39:17,560 --> 01:39:20,160
Speaker 1: Oh I bet, I bet, and anybody on the street

1820
01:39:20,200 --> 01:39:22,320
Speaker 1: will when you ask him about Yellowstone and wolves say

1821
01:39:22,400 --> 01:39:25,600
Speaker 1: oh that In the title of the the video was

1822
01:39:25,960 --> 01:39:28,639
Speaker 1: when wolves changed rivers, and it was about them having

1823
01:39:28,800 --> 01:39:31,960
Speaker 1: such a strong ecological effect in the Yellowstone ecosystem that

1824
01:39:32,360 --> 01:39:35,120
Speaker 1: river courses were changing and vegetation was coming back. The

1825
01:39:35,280 --> 01:39:39,880
Speaker 1: problem with that whole story is that it's not just wolves.

1826
01:39:40,120 --> 01:39:44,320
Speaker 1: They released the wolves in shortly after that, they had

1827
01:39:44,439 --> 01:39:46,920
Speaker 1: a hundred year drought, the worst drought in a hundred years.

1828
01:39:47,200 --> 01:39:49,080
Speaker 1: They had a couple of years in that next decade

1829
01:39:49,160 --> 01:39:52,599
Speaker 1: with with heavy snows at that time that that knocked

1830
01:39:52,880 --> 01:39:56,560
Speaker 1: elk recruitment back. Grizzly bear populations increased so much that

1831
01:39:56,680 --> 01:40:00,479
Speaker 1: they documented three times the elk the calf elk predation

1832
01:40:00,520 --> 01:40:03,680
Speaker 1: by grizzly bears than than before we had wolves. There

1833
01:40:03,720 --> 01:40:07,040
Speaker 1: was hydrological changes in Yellowstone. We had the fires in

1834
01:40:08,080 --> 01:40:11,519
Speaker 1: huge changes. Their moose populations were dropping, Cougar population for

1835
01:40:11,600 --> 01:40:15,679
Speaker 1: coming up all the beaver reintroductions right see you here

1836
01:40:15,960 --> 01:40:19,320
Speaker 1: very nearby, Yes, in the Galton. Yeah, so you hear that.

1837
01:40:19,520 --> 01:40:23,479
Speaker 1: The bee they made that whole upper Madison and Gallant

1838
01:40:23,520 --> 01:40:26,960
Speaker 1: and beaver recovery areas. So the wolves didn't bring the

1839
01:40:27,000 --> 01:40:30,200
Speaker 1: beavers back biologistic and crates um and released them and

1840
01:40:30,320 --> 01:40:33,760
Speaker 1: the beaver's coming coming upstream and damning is part of

1841
01:40:33,840 --> 01:40:37,439
Speaker 1: the hydrological changes um in that in that ecosystem, that

1842
01:40:37,560 --> 01:40:39,280
Speaker 1: that was really caused by the beavers. But the beavers

1843
01:40:39,320 --> 01:40:42,280
Speaker 1: don't have a paparazzi following them and and champion everything

1844
01:40:42,360 --> 01:40:43,880
Speaker 1: that they do, and so the beavers didn't get any

1845
01:40:43,880 --> 01:40:51,240
Speaker 1: credit for that's right. That's so funny though, because you're like, well, yeah,

1846
01:40:51,479 --> 01:40:53,639
Speaker 1: just add wolves, just add wolves and read what we're

1847
01:40:53,640 --> 01:40:55,720
Speaker 1: talking about, whether it's a beaver or a wolf, is

1848
01:40:56,320 --> 01:41:01,720
Speaker 1: heavy heavy handed management. And also we were killing cow

1849
01:41:01,800 --> 01:41:04,679
Speaker 1: elk off of the park in the wintertime and hunts

1850
01:41:04,720 --> 01:41:06,280
Speaker 1: as a way to try to trim the herds. That's

1851
01:41:06,320 --> 01:41:09,000
Speaker 1: what we do. We killed females and those uh cow

1852
01:41:09,120 --> 01:41:11,240
Speaker 1: tags were probably held a little longer than we thought

1853
01:41:11,360 --> 01:41:13,800
Speaker 1: as the elk population was going down. So there's a

1854
01:41:13,920 --> 01:41:16,920
Speaker 1: storm of things that caused the elk population to go

1855
01:41:17,000 --> 01:41:20,320
Speaker 1: from nineteen thousand down to less than four thousand, and

1856
01:41:20,479 --> 01:41:22,599
Speaker 1: some people wanted to pin all that on the wolf,

1857
01:41:22,680 --> 01:41:24,720
Speaker 1: and the wolf did all that, and it's just such

1858
01:41:24,760 --> 01:41:28,360
Speaker 1: a simplistic thing that happened. But but a lot of

1859
01:41:28,439 --> 01:41:30,479
Speaker 1: research has come on now. Matt Kaufman, who you had

1860
01:41:30,520 --> 01:41:33,320
Speaker 1: on the show, published a paper in two where he

1861
01:41:33,400 --> 01:41:37,920
Speaker 1: did a more robust, more widespread, more scientific analysis of

1862
01:41:38,240 --> 01:41:40,880
Speaker 1: of aspen in that same area in the Northern Range

1863
01:41:40,920 --> 01:41:45,200
Speaker 1: and and showed that Aspen wasn't recovering actually even despite

1864
01:41:45,280 --> 01:41:48,040
Speaker 1: a sixty in decline in the elk population, So at

1865
01:41:48,080 --> 01:41:50,599
Speaker 1: that point it wasn't just a behavioral thing. We've got

1866
01:41:50,680 --> 01:41:53,839
Speaker 1: six decline in the elk and it's still can't document

1867
01:41:54,160 --> 01:41:57,479
Speaker 1: an aspen recovery. And so it's a really complicated thing

1868
01:41:57,600 --> 01:42:01,120
Speaker 1: with a whole bunch of factors feeding into it. And

1869
01:42:01,240 --> 01:42:05,000
Speaker 1: to sit back and say wolves changed Yellowstone and renovated

1870
01:42:05,000 --> 01:42:08,120
Speaker 1: the whole ecosystem is is a fallacy. But but what

1871
01:42:08,200 --> 01:42:10,679
Speaker 1: do you want? What everybody knows. But when someone wants

1872
01:42:10,720 --> 01:42:12,400
Speaker 1: to come in, and they want to come in and

1873
01:42:12,520 --> 01:42:16,080
Speaker 1: be like, let's have a normal, reasonable conversation about this,

1874
01:42:16,960 --> 01:42:20,479
Speaker 1: you get accused of being like anti wolf. You have

1875
01:42:20,560 --> 01:42:22,240
Speaker 1: a quote one of your things, you wrote, I came here.

1876
01:42:22,320 --> 01:42:24,200
Speaker 1: It was you were someone else who said, we don't

1877
01:42:24,280 --> 01:42:26,320
Speaker 1: have to make the wolf out to be a hero

1878
01:42:26,760 --> 01:42:30,360
Speaker 1: to justify recovery. That why can't we just talk about

1879
01:42:30,439 --> 01:42:35,639
Speaker 1: it in a way that's I'm asking you, Why can't

1880
01:42:35,640 --> 01:42:38,240
Speaker 1: it just be talked about in a matter of fact way,

1881
01:42:38,479 --> 01:42:40,360
Speaker 1: like is this the right thing to do? How do

1882
01:42:40,439 --> 01:42:42,160
Speaker 1: we do it correctly? But not have it be that

1883
01:42:42,280 --> 01:42:46,000
Speaker 1: we need to like spend these wild yachts. It's too polarized.

1884
01:42:46,000 --> 01:42:47,760
Speaker 1: We've got everybody at the poles and nobody in the

1885
01:42:47,800 --> 01:42:49,840
Speaker 1: middle when it comes to wolves, and and I think

1886
01:42:49,880 --> 01:42:52,840
Speaker 1: that evolved because of of wolf recovery in the Northern

1887
01:42:52,920 --> 01:42:55,960
Speaker 1: Rockies and wolves are getting and they crossed two thousand two.

1888
01:42:56,080 --> 01:42:59,880
Speaker 1: I think they they exceeded recovery criteria and weren't the

1889
01:43:00,040 --> 01:43:03,880
Speaker 1: listed by Congress unfortunately until they were five times the

1890
01:43:03,960 --> 01:43:07,360
Speaker 1: original recovery criteria. And do you have these these these

1891
01:43:07,439 --> 01:43:10,759
Speaker 1: groups suing to keep wolves protected on an Endangered Species

1892
01:43:10,800 --> 01:43:13,439
Speaker 1: Act even as that population grows and grows and grows.

1893
01:43:13,720 --> 01:43:17,160
Speaker 1: I think that creates so much pull to one pole

1894
01:43:17,640 --> 01:43:21,160
Speaker 1: that you had an equal and opposite reaction the opposite way,

1895
01:43:21,520 --> 01:43:25,680
Speaker 1: with people pulling equally hard and equally unrealistic things that

1896
01:43:25,760 --> 01:43:28,080
Speaker 1: they were saying on the other side. And and it

1897
01:43:28,200 --> 01:43:31,439
Speaker 1: just got so violent. Everybody is still in their corners

1898
01:43:31,760 --> 01:43:34,639
Speaker 1: instead of meeting in the middle and just talking NEUTRALI

1899
01:43:34,640 --> 01:43:38,720
Speaker 1: about it. The opposite of your trophic cascade person, the

1900
01:43:39,360 --> 01:43:43,720
Speaker 1: equally ridiculous opposite, is your person who is just in

1901
01:43:44,000 --> 01:43:49,360
Speaker 1: love with the idea of surplus killing. Yeah, they love it,

1902
01:43:49,960 --> 01:43:53,240
Speaker 1: they love it, right, it's like the other extreme extreme.

1903
01:43:53,320 --> 01:43:58,720
Speaker 1: It's the it's the MSNBC, Fox News split is trophic, cascade,

1904
01:43:59,040 --> 01:44:04,479
Speaker 1: surplus killing. What is the middle like? If you, I

1905
01:44:04,560 --> 01:44:06,200
Speaker 1: know it's not your business, but what is the middle

1906
01:44:06,240 --> 01:44:08,479
Speaker 1: ground like layout for me? Like not only it has

1907
01:44:08,520 --> 01:44:12,400
Speaker 1: it doesn't need to be your opinion, articulate an opinion

1908
01:44:12,720 --> 01:44:15,439
Speaker 1: that based on all of your exposure to people a

1909
01:44:15,479 --> 01:44:19,519
Speaker 1: different opinions about wolves. Imagine if you will, the most

1910
01:44:19,920 --> 01:44:25,719
Speaker 1: sort of like moderate, kind of level headed, consensus minded

1911
01:44:26,439 --> 01:44:31,240
Speaker 1: sentence about collection of sentences about wolves. There's there's not

1912
01:44:31,320 --> 01:44:33,720
Speaker 1: many people there, but I feel like I'm close and

1913
01:44:33,760 --> 01:44:35,880
Speaker 1: I feel like I'm close to that because the wolves

1914
01:44:35,920 --> 01:44:38,040
Speaker 1: to me are not on a pedestal as some religious

1915
01:44:38,080 --> 01:44:41,160
Speaker 1: deity that's going to save the world. And I certainly

1916
01:44:41,200 --> 01:44:43,760
Speaker 1: don't hate wolves. Wolves are just the largest member of

1917
01:44:43,760 --> 01:44:47,679
Speaker 1: the carnivore family, and and agencies manage foxes, we manage coyotes.

1918
01:44:47,760 --> 01:44:50,759
Speaker 1: We couldn't manage wolves the same way. They're just another

1919
01:44:50,920 --> 01:44:53,519
Speaker 1: native um species. And if we just look at them

1920
01:44:53,600 --> 01:44:56,120
Speaker 1: that way and say, let's bring it back onto the landscape,

1921
01:44:56,400 --> 01:44:59,519
Speaker 1: and when they're causing some unacceptable losses to livestock or

1922
01:44:59,520 --> 01:45:02,400
Speaker 1: an accept the losses to native other native species like

1923
01:45:02,520 --> 01:45:04,439
Speaker 1: el ker deer, then were going to manage them. We

1924
01:45:04,720 --> 01:45:07,880
Speaker 1: bring that population down in that focal area, solve that problem,

1925
01:45:08,320 --> 01:45:11,120
Speaker 1: and in other areas where they're not causing any problems

1926
01:45:11,160 --> 01:45:14,439
Speaker 1: and they're just restored to the landscape for good. Um.

1927
01:45:14,600 --> 01:45:17,240
Speaker 1: I don't know why more people can't look at it

1928
01:45:17,320 --> 01:45:19,680
Speaker 1: that way, but but they don't. It's very appealing and

1929
01:45:20,520 --> 01:45:23,679
Speaker 1: I know, I mean, they're just they're just big dogs.

1930
01:45:23,800 --> 01:45:25,880
Speaker 1: They're just another canaid out there. I don't know why

1931
01:45:25,960 --> 01:45:28,559
Speaker 1: they have to be so special. If you imagine looking

1932
01:45:28,600 --> 01:45:34,360
Speaker 1: into a crystal ball, UM, take the Northern Great Lakes.

1933
01:45:35,280 --> 01:45:39,720
Speaker 1: Will we get um? Will they be delisted to stay? Eventually? Yes?

1934
01:45:39,960 --> 01:45:42,080
Speaker 1: I think pretty soon. I mean I don't I don't

1935
01:45:42,080 --> 01:45:43,800
Speaker 1: know how you can justify leaving him on the list.

1936
01:45:43,880 --> 01:45:47,760
Speaker 1: I do think maybe this year they'll be delisted. Does it?

1937
01:45:47,920 --> 01:45:50,360
Speaker 1: Does it? Um? I know you don't do politics, but

1938
01:45:50,400 --> 01:45:52,800
Speaker 1: I don't know. If you need to answer this, you

1939
01:45:52,840 --> 01:45:58,920
Speaker 1: probably can't answer this. Does will that happen independent whatever

1940
01:45:59,000 --> 01:46:02,599
Speaker 1: happens with the next administration, Like does that have its

1941
01:46:02,640 --> 01:46:04,640
Speaker 1: own life course? Or does there need to be some

1942
01:46:04,760 --> 01:46:08,519
Speaker 1: like very top down pressure on that There isn't a

1943
01:46:08,600 --> 01:46:12,040
Speaker 1: lot of top down um pressure because I think there's

1944
01:46:12,040 --> 01:46:16,040
Speaker 1: safeguards against you know, like directives like that. There's there's

1945
01:46:16,080 --> 01:46:18,800
Speaker 1: influence there. There's no way you can take politics out

1946
01:46:18,800 --> 01:46:21,680
Speaker 1: of endangered species management, and certainly not wolf management. So

1947
01:46:21,720 --> 01:46:27,360
Speaker 1: there's always gonna be some political pressures and political um considerations.

1948
01:46:27,439 --> 01:46:29,560
Speaker 1: That's just part of wildlife management. It's not it's not

1949
01:46:29,720 --> 01:46:32,719
Speaker 1: pure science, for sure. It's it's an application of science

1950
01:46:32,800 --> 01:46:37,160
Speaker 1: and social science to manage wildlife. So I think in

1951
01:46:37,439 --> 01:46:40,040
Speaker 1: the future they'll be delisted. They certainly will be what

1952
01:46:40,320 --> 01:46:42,320
Speaker 1: what we can't do, And I've heard people say this

1953
01:46:42,479 --> 01:46:44,720
Speaker 1: is okay. I agree with delisting the Northern Rockies. I

1954
01:46:44,760 --> 01:46:47,920
Speaker 1: agree with the listing the Great Lakes, but we we

1955
01:46:48,200 --> 01:46:50,800
Speaker 1: need wolves in more places, and so we need to

1956
01:46:50,880 --> 01:46:53,639
Speaker 1: keep them listed in all of the other places until

1957
01:46:53,680 --> 01:46:56,760
Speaker 1: they recovered. That's not what the s A does. If

1958
01:46:56,840 --> 01:46:59,519
Speaker 1: they're not in danger of extinction anymore in too big

1959
01:46:59,600 --> 01:47:02,439
Speaker 1: popular nations, then we don't. We don't just move those

1960
01:47:02,479 --> 01:47:05,560
Speaker 1: polygons around the country until we get wolves everywhere we

1961
01:47:05,680 --> 01:47:07,879
Speaker 1: want wolves. Yeah, I know, I a little bit disagree

1962
01:47:07,920 --> 01:47:11,799
Speaker 1: with you because those ideas weren't around at the time

1963
01:47:12,120 --> 01:47:16,800
Speaker 1: they were delisted. But it makes it um It makes

1964
01:47:16,840 --> 01:47:20,560
Speaker 1: it better and easier to work being there. If you

1965
01:47:20,600 --> 01:47:22,600
Speaker 1: look at grizzly bears, it makes sense to me that

1966
01:47:22,720 --> 01:47:28,000
Speaker 1: we would just we would gradually, as it's acceptable, d

1967
01:47:28,240 --> 01:47:33,800
Speaker 1: list some some idea of population groups rather than saying that,

1968
01:47:34,920 --> 01:47:37,599
Speaker 1: you know, rather than like undoing the whole protection across

1969
01:47:37,640 --> 01:47:39,880
Speaker 1: the entirety of the lower forty eight, we would be like, Okay,

1970
01:47:39,960 --> 01:47:42,240
Speaker 1: this region is cool. That region is cool, but that

1971
01:47:42,360 --> 01:47:44,760
Speaker 1: region is cool. That region is not cool. What you're

1972
01:47:44,760 --> 01:47:47,479
Speaker 1: talking about is those are subpopulations that were all part

1973
01:47:47,560 --> 01:47:50,880
Speaker 1: of the recovery, and so one subpopulation is doing really good,

1974
01:47:51,200 --> 01:47:53,479
Speaker 1: then definitely we want to take that one off off

1975
01:47:53,560 --> 01:47:55,600
Speaker 1: the table. We want to delist that, and we do

1976
01:47:55,720 --> 01:47:58,519
Speaker 1: want to keep those other ones because they're right from

1977
01:47:58,560 --> 01:48:02,320
Speaker 1: the start part of the whole recovery plant. Whereas in

1978
01:48:02,680 --> 01:48:06,200
Speaker 1: in gray Wolves, the whole recovery plan was three populations

1979
01:48:06,200 --> 01:48:07,680
Speaker 1: of a hundred, and then it was increased of three

1980
01:48:07,720 --> 01:48:10,720
Speaker 1: populations of a hundred fifty in the northern Great Lakes

1981
01:48:10,760 --> 01:48:13,479
Speaker 1: area there and and we reached that and exceeded that

1982
01:48:13,560 --> 01:48:16,479
Speaker 1: by five times, and then the western Great Lakes it

1983
01:48:16,680 --> 01:48:20,599
Speaker 1: was um like four hundred. In Minnesota where they're just threatened.

1984
01:48:20,720 --> 01:48:23,840
Speaker 1: And then it was a hundred more in Wisconsin and

1985
01:48:23,880 --> 01:48:26,920
Speaker 1: the up and they exceeded that a long time ago.

1986
01:48:27,000 --> 01:48:32,639
Speaker 1: And so those are too independent recovery processes and they've

1987
01:48:32,680 --> 01:48:36,280
Speaker 1: both been satisfied. There was a grizzly bear example. That

1988
01:48:36,560 --> 01:48:40,759
Speaker 1: one that they're delisting is just part of the overall

1989
01:48:40,840 --> 01:48:45,280
Speaker 1: recovery plan. Um, I'm gonna do another crystal ball one

1990
01:48:45,360 --> 01:48:49,800
Speaker 1: for you. What let's say pick a comfortable number twenty years,

1991
01:48:49,840 --> 01:48:55,360
Speaker 1: twenty five years. What are some states that um might

1992
01:48:55,520 --> 01:48:58,760
Speaker 1: have population of wolves that don't. Now if you just

1993
01:48:58,880 --> 01:49:03,519
Speaker 1: kind of look at the trick question, no, no, the

1994
01:49:03,600 --> 01:49:07,479
Speaker 1: biological aspects and the political aspects. If you'd asked this

1995
01:49:07,600 --> 01:49:10,040
Speaker 1: question twenty years ago, there's been some real surprises. Yeah,

1996
01:49:10,400 --> 01:49:12,640
Speaker 1: right right. Some of the Washington you'd have been like

1997
01:49:12,880 --> 01:49:17,960
Speaker 1: California people like bullshit, right, But here we are so um,

1998
01:49:19,320 --> 01:49:23,439
Speaker 1: you know, is Nebraska right, Like, is Nebraska gonna be

1999
01:49:23,520 --> 01:49:26,920
Speaker 1: like wow? Who the thought? Now Nebraska has a wolf pack?

2000
01:49:27,640 --> 01:49:29,639
Speaker 1: And you'd have to say Utah in Colorado because we've

2001
01:49:29,640 --> 01:49:32,120
Speaker 1: got wolves going into those naturally going into those areas

2002
01:49:32,439 --> 01:49:34,759
Speaker 1: as it is, and I think and Mexican wolf recovery

2003
01:49:35,520 --> 01:49:38,320
Speaker 1: we've since two thousand nine, the Mexican wolf population has

2004
01:49:38,360 --> 01:49:41,240
Speaker 1: been increased in average at twelve percent per year, so

2005
01:49:41,400 --> 01:49:43,880
Speaker 1: that the mixing wolf population is going up and up

2006
01:49:44,000 --> 01:49:48,280
Speaker 1: and increasing towards a recovery goal. And yet I still

2007
01:49:48,320 --> 01:49:51,919
Speaker 1: get emails that say the Mexican wolf is spiraling towards extinction.

2008
01:49:52,040 --> 01:49:54,240
Speaker 1: Press the click the button here to donate to help

2009
01:49:54,320 --> 01:49:57,680
Speaker 1: us save the wolves against the evil state and federal agencies.

2010
01:49:58,040 --> 01:50:01,000
Speaker 1: And I think maybe they have my ground pinned sideways

2011
01:50:01,040 --> 01:50:04,840
Speaker 1: in their office or something and they think it's going wrong.

2012
01:50:04,880 --> 01:50:06,840
Speaker 1: I think they hung it up wrong because the graph

2013
01:50:06,960 --> 01:50:09,320
Speaker 1: is going up and up. So I I do feel

2014
01:50:09,360 --> 01:50:11,360
Speaker 1: that Mexican wolves are gonna be I don't know when

2015
01:50:11,439 --> 01:50:14,240
Speaker 1: recovery will happen, because we're still in the early stages recovery,

2016
01:50:14,320 --> 01:50:16,640
Speaker 1: but that situation is gonna look a lot better. We're

2017
01:50:16,680 --> 01:50:19,240
Speaker 1: gonna have more wolves in in Mexico, and we've got

2018
01:50:19,320 --> 01:50:21,840
Speaker 1: two recovery areas in the US and Mexico because it

2019
01:50:21,840 --> 01:50:25,519
Speaker 1: has been a true binational um process. And then we're

2020
01:50:25,520 --> 01:50:27,400
Speaker 1: gonna have some of the rocky mountain states really gonna

2021
01:50:27,400 --> 01:50:30,640
Speaker 1: expand into those rocky mountain states. And and really I

2022
01:50:30,760 --> 01:50:34,320
Speaker 1: think a lot of this angst and polarity is going

2023
01:50:34,400 --> 01:50:38,800
Speaker 1: to relax once people have wolves around and realize they're

2024
01:50:38,840 --> 01:50:41,240
Speaker 1: not that bad and if we have management ability to

2025
01:50:41,360 --> 01:50:43,640
Speaker 1: take care of problems where they where they happen. I

2026
01:50:43,720 --> 01:50:46,120
Speaker 1: think in cases where wolves have been here a while,

2027
01:50:46,520 --> 01:50:49,840
Speaker 1: like for example, Alaska and Canada, they're not that big

2028
01:50:49,880 --> 01:50:51,360
Speaker 1: a deal because they've had them for a while, and

2029
01:50:51,439 --> 01:50:54,800
Speaker 1: I think all this stuff will will settle down twenty

2030
01:50:54,920 --> 01:50:57,439
Speaker 1: years or so. That's a really funny thing about friends

2031
01:50:57,479 --> 01:51:00,479
Speaker 1: of mine that just really don't like wolves. I got

2032
01:51:00,760 --> 01:51:04,479
Speaker 1: friends as hate wolves and um because what they what

2033
01:51:04,640 --> 01:51:07,080
Speaker 1: they what their belief of what they'll do to the

2034
01:51:07,160 --> 01:51:09,680
Speaker 1: game populations. But the Sun's bitches all want to hunt

2035
01:51:09,680 --> 01:51:12,519
Speaker 1: in Alaska, right, I'm like, yeah, you would like it.

2036
01:51:13,280 --> 01:51:16,400
Speaker 1: Another thing I mentioned David Meach. David Meach has been

2037
01:51:16,439 --> 01:51:19,960
Speaker 1: working on wolves for sixty years, which sounds those are,

2038
01:51:20,080 --> 01:51:22,680
Speaker 1: but he has. He's been working Elsmere Island every year

2039
01:51:23,000 --> 01:51:26,759
Speaker 1: on Archtally Worlds for sixty years, and and he he's

2040
01:51:26,880 --> 01:51:28,840
Speaker 1: very pragmatic about wolves. You would think some of the

2041
01:51:28,960 --> 01:51:33,000
Speaker 1: devoted your entire their entire life to wolves and wolf biology,

2042
01:51:33,360 --> 01:51:36,400
Speaker 1: but he's very pragmatic. He's the one that says um.

2043
01:51:36,680 --> 01:51:39,920
Speaker 1: Wolves are neither st nor sinners, except by those who

2044
01:51:40,040 --> 01:51:42,639
Speaker 1: try to make themselves so they're not. They're just they're

2045
01:51:42,680 --> 01:51:47,759
Speaker 1: just um canaans there. And the public perception I find

2046
01:51:47,960 --> 01:51:51,240
Speaker 1: is so skewed as to what a healthy population is.

2047
01:51:51,840 --> 01:51:57,560
Speaker 1: And people like to have this very unrealistic idea of

2048
01:51:58,920 --> 01:52:03,240
Speaker 1: how animals spread out on a landscape. So if there's

2049
01:52:03,280 --> 01:52:06,880
Speaker 1: a healthy population, it means I see them where I go.

2050
01:52:07,600 --> 01:52:10,000
Speaker 1: And like, we're looking at this big picture of Hell's

2051
01:52:10,040 --> 01:52:13,360
Speaker 1: Canyon that is chock full elk, but there's no elk

2052
01:52:13,439 --> 01:52:16,280
Speaker 1: in the picture, and people are like, something is wrong.

2053
01:52:17,520 --> 01:52:20,240
Speaker 1: And I've been at these public meetings. I had so

2054
01:52:20,520 --> 01:52:25,160
Speaker 1: many really cool wolf encounters in the UH Catcham area

2055
01:52:25,320 --> 01:52:29,080
Speaker 1: Catching Ranger District, and UH go to public meetings and

2056
01:52:29,200 --> 01:52:32,200
Speaker 1: it's like doom and gloom and the wolf population is

2057
01:52:32,240 --> 01:52:35,040
Speaker 1: going down and the hunters are killing them all and

2058
01:52:35,160 --> 01:52:39,559
Speaker 1: the damn Cattle Owners Association is killing them all. Shut up,

2059
01:52:40,640 --> 01:52:43,880
Speaker 1: And it's because people aren't seeing wolves when they're I mean,

2060
01:52:44,000 --> 01:52:46,400
Speaker 1: some of these people were obviously not walking on trails,

2061
01:52:46,439 --> 01:52:49,720
Speaker 1: but they said they were right. Um, but they're not

2062
01:52:49,760 --> 01:52:51,280
Speaker 1: seeing them when they're walking their dogs, and they're not

2063
01:52:51,320 --> 01:52:53,160
Speaker 1: seeing when they're driving their cars and he's seeing long

2064
01:52:53,240 --> 01:53:00,240
Speaker 1: tail weasels. Either, that's not that's not charismatic enough, Paul Jazz,

2065
01:53:00,320 --> 01:53:02,280
Speaker 1: I think they're very charismatic. I was with a lot

2066
01:53:02,360 --> 01:53:05,800
Speaker 1: of non game biologists last night, and uh, they're big

2067
01:53:05,880 --> 01:53:10,080
Speaker 1: fans of the weasel family. Are we gonna be arguing

2068
01:53:10,080 --> 01:53:12,800
Speaker 1: about jaguars and ten years No, I don't think so

2069
01:53:14,479 --> 01:53:18,240
Speaker 1: argue about jaguars. Do you want to restore jaguars? I

2070
01:53:18,600 --> 01:53:22,759
Speaker 1: was involved in one workshop recently um talking about jaguars

2071
01:53:22,800 --> 01:53:24,479
Speaker 1: and jaguars don't want to restore them. I just want

2072
01:53:24,560 --> 01:53:27,120
Speaker 1: them to wander back in and be cool. Well I do,

2073
01:53:27,280 --> 01:53:29,760
Speaker 1: I think everybody. Most everybody does. They don't know that

2074
01:53:29,840 --> 01:53:31,720
Speaker 1: I'm arguing yet that we put them in crates and

2075
01:53:31,920 --> 01:53:34,479
Speaker 1: turn them out. But the one workshop I was at

2076
01:53:34,520 --> 01:53:38,880
Speaker 1: where there's uh three advocacy groups that got together and

2077
01:53:38,960 --> 01:53:42,720
Speaker 1: wrote a big manuscript advocating translocating from Mexico into the

2078
01:53:42,800 --> 01:53:46,920
Speaker 1: muggy on Rim and the Healing Esgtional. This is pondrosa

2079
01:53:46,960 --> 01:53:51,439
Speaker 1: pine um forest and was never um, never habitat where

2080
01:53:51,439 --> 01:53:54,360
Speaker 1: they stayed. The southwest Arizona, New Mexico has always been

2081
01:53:54,680 --> 01:53:57,720
Speaker 1: places where transient animals came up. We haven't documented a

2082
01:53:58,560 --> 01:54:02,960
Speaker 1: female with young jaguar in the US in Arizona and

2083
01:54:03,000 --> 01:54:06,080
Speaker 1: New Mexico anyway for a hundred and twenty years. There

2084
01:54:06,120 --> 01:54:09,080
Speaker 1: hasn't been a female since since nineteen sixty three, and

2085
01:54:09,160 --> 01:54:10,639
Speaker 1: then a bunch of been a bunch of been killed

2086
01:54:10,680 --> 01:54:13,479
Speaker 1: in photographs since then. No females. Yeah, well, what about

2087
01:54:13,520 --> 01:54:17,519
Speaker 1: if you went back into you know, like man right, Yeah,

2088
01:54:17,560 --> 01:54:20,000
Speaker 1: we don't know that. And and there were there were jaguars,

2089
01:54:20,040 --> 01:54:22,600
Speaker 1: and there were some females in some reproduction. But but

2090
01:54:22,720 --> 01:54:24,280
Speaker 1: this was a marginary. If you look at the Native

2091
01:54:24,320 --> 01:54:28,360
Speaker 1: American tribes, they have like no jaguar motif, not part

2092
01:54:28,400 --> 01:54:30,559
Speaker 1: of any of their stories. That tells you. That tells

2093
01:54:30,600 --> 01:54:34,040
Speaker 1: you something about how common it was in the Southwest

2094
01:54:34,080 --> 01:54:37,760
Speaker 1: and interesting and so we we definitely want to um

2095
01:54:38,320 --> 01:54:40,880
Speaker 1: make sure they can come back up and go back

2096
01:54:40,960 --> 01:54:43,840
Speaker 1: to Mexico they want. There was. Alan Rabinowitz is probably

2097
01:54:43,880 --> 01:54:47,000
Speaker 1: the most famous jaguar person. He started Panthera, which is

2098
01:54:47,000 --> 01:54:52,320
Speaker 1: a wild cat group worldwide. He's established jaguar conservation areas

2099
01:54:52,360 --> 01:54:55,280
Speaker 1: and refuges in South American Central America. Devoted his whole

2100
01:54:55,320 --> 01:54:59,320
Speaker 1: life to jaguars and and when he talked about well

2101
01:54:59,320 --> 01:55:02,520
Speaker 1: the fish Wallet's Ofervice was being pressured by some environmental

2102
01:55:02,560 --> 01:55:06,320
Speaker 1: groups to designate critical habitat in Arizona, New Mexico. And

2103
01:55:06,400 --> 01:55:08,320
Speaker 1: when he heard that, he wrote not fed in in

2104
01:55:08,520 --> 01:55:11,280
Speaker 1: New York Times and said, this is ridiculous, is a

2105
01:55:11,360 --> 01:55:14,520
Speaker 1: ridiculous waste of money. That we've got a hundred seventy

2106
01:55:14,640 --> 01:55:19,000
Speaker 1: hundred seventy three thousand jaguars estimated from Sonora down to

2107
01:55:19,280 --> 01:55:23,400
Speaker 1: southern South America, and and some groups are saying this

2108
01:55:23,560 --> 01:55:26,360
Speaker 1: little dry arid land on the northern end of their

2109
01:55:26,400 --> 01:55:28,920
Speaker 1: distribution where they really just kind of moved in and

2110
01:55:29,000 --> 01:55:33,440
Speaker 1: moved out. Historically that is should be designated critical habitat

2111
01:55:33,480 --> 01:55:36,280
Speaker 1: and critical habitat as part of the ESA Endangered Species Act,

2112
01:55:36,760 --> 01:55:39,560
Speaker 1: and and habits had to be designated as critical habitat

2113
01:55:39,960 --> 01:55:42,440
Speaker 1: has to be critical to the conservation of the species.

2114
01:55:43,000 --> 01:55:46,080
Speaker 1: And the Fishing Wildad Service did population viability analyses where

2115
01:55:46,120 --> 01:55:48,760
Speaker 1: they included Arizona, New Mexico, and then they excluded them.

2116
01:55:49,120 --> 01:55:51,160
Speaker 1: And and as you would expect with a hundred and

2117
01:55:51,160 --> 01:55:54,760
Speaker 1: seventy three thousand jaguars elsewhere, that didn't change the probability

2118
01:55:54,800 --> 01:55:57,800
Speaker 1: of extinction um at all. And in Mexico itself has

2119
01:55:58,000 --> 01:56:01,280
Speaker 1: four thousand, eight hundred jaguars estimate, didn't that increased in

2120
01:56:01,360 --> 01:56:05,960
Speaker 1: the last decade. And so there's Arizona patriot man, I

2121
01:56:06,040 --> 01:56:10,400
Speaker 1: want American jaguars. Well, the groups that are asking for

2122
01:56:10,520 --> 01:56:14,640
Speaker 1: translocation up into Ariza into Central Arizona, New Mexico. At

2123
01:56:14,680 --> 01:56:16,840
Speaker 1: that meeting were some people that were involved in the

2124
01:56:16,920 --> 01:56:20,160
Speaker 1: conservation of jaguars in central Mexico where they are, and

2125
01:56:20,280 --> 01:56:23,560
Speaker 1: those people said, you're at you want to transplicate how

2126
01:56:23,640 --> 01:56:27,080
Speaker 1: many that's more than we estimate are in this northernmost

2127
01:56:27,120 --> 01:56:30,080
Speaker 1: population of jaguars. You can't you can't be taking our jaguars.

2128
01:56:30,120 --> 01:56:33,040
Speaker 1: I mean, we're trying to conserve that there so so,

2129
01:56:33,800 --> 01:56:35,920
Speaker 1: and then that got a lot of people looking at

2130
01:56:35,960 --> 01:56:38,160
Speaker 1: the carpet and scratching their heads like, oh, we didn't

2131
01:56:38,160 --> 01:56:39,879
Speaker 1: think of that. We're just gonna go get some jaguars

2132
01:56:39,960 --> 01:56:41,800
Speaker 1: and bring them up here. I didn't, you know, I

2133
01:56:41,920 --> 01:56:45,640
Speaker 1: never knew It's something I should research more or read

2134
01:56:45,720 --> 01:56:51,720
Speaker 1: up on. Mores like how oft and how many? Right?

2135
01:56:52,440 --> 01:56:54,240
Speaker 1: Like how many were? Really? I'd like to know. I'll

2136
01:56:54,280 --> 01:56:55,800
Speaker 1: send you a book, like what is the sort of

2137
01:56:55,960 --> 01:56:57,840
Speaker 1: you know I've seen it? I read a book um

2138
01:56:58,600 --> 01:57:00,960
Speaker 1: not too long ago, and it was it was just

2139
01:57:01,160 --> 01:57:06,000
Speaker 1: an exhaustive catalog of everything that could have possibly have

2140
01:57:06,160 --> 01:57:09,560
Speaker 1: been a reference of grizzly bears in the Southwest. So

2141
01:57:09,720 --> 01:57:13,839
Speaker 1: it's Mexico. It got up into Collar, yet it covered

2142
01:57:13,960 --> 01:57:16,480
Speaker 1: basically Colorado South. It was sort of like it was

2143
01:57:16,520 --> 01:57:20,080
Speaker 1: just a thing efter thing like from back the Spanish

2144
01:57:20,960 --> 01:57:26,480
Speaker 1: you know, early you know, Frontier day ranchers archaeological record,

2145
01:57:26,640 --> 01:57:30,240
Speaker 1: like everything that pointed to where were they? What was

2146
01:57:30,280 --> 01:57:33,360
Speaker 1: it like? I'd like to see that on jaguars if

2147
01:57:33,400 --> 01:57:35,920
Speaker 1: it was if it was in fact that this is

2148
01:57:36,040 --> 01:57:39,520
Speaker 1: always fringe and theyate straight up and this is just

2149
01:57:39,640 --> 01:57:42,160
Speaker 1: like the natural edge of their habitat, and just like

2150
01:57:42,800 --> 01:57:45,680
Speaker 1: you might you know, you know, Mountain Lion might kind

2151
01:57:45,680 --> 01:57:47,480
Speaker 1: of like flirt with the Alaska border now and then,

2152
01:57:47,520 --> 01:57:50,680
Speaker 1: but you'd hardly call Alaska like Mountain Lion country. But

2153
01:57:50,880 --> 01:57:52,960
Speaker 1: now and then one might turn up and they do.

2154
01:57:53,640 --> 01:57:55,960
Speaker 1: If that was the case, then I guess my ask

2155
01:57:56,080 --> 01:57:59,520
Speaker 1: would be that we take the necessary steps to let

2156
01:57:59,600 --> 01:58:03,040
Speaker 1: that contin new happening. Definitely, Yeah, I agree with just

2157
01:58:03,200 --> 01:58:05,520
Speaker 1: not jaguars and crates up into the Ponderous Pine. That

2158
01:58:05,720 --> 01:58:08,400
Speaker 1: seems really weird that that, but from from a from

2159
01:58:08,440 --> 01:58:12,800
Speaker 1: a like from a armchair expert, not not even that

2160
01:58:12,960 --> 01:58:16,040
Speaker 1: an armchair curious person. That strikes me as being a

2161
01:58:16,120 --> 01:58:18,480
Speaker 1: little bit much. That Ellen Robin wits I mentioned when

2162
01:58:18,600 --> 01:58:20,920
Speaker 1: when Fishing Wild Service was trying to designate which they

2163
01:58:20,960 --> 01:58:24,200
Speaker 1: did designate critical habitat in Arizona, New Mexico for the jaguar,

2164
01:58:24,720 --> 01:58:27,720
Speaker 1: like the third third attempt, Ellen rabin Witz did his

2165
01:58:27,800 --> 01:58:31,840
Speaker 1: New York Times uh article or op ed saying that

2166
01:58:31,960 --> 01:58:33,520
Speaker 1: was the most ridiculous thing in the world that you're

2167
01:58:33,560 --> 01:58:37,160
Speaker 1: wasting money talking about critical habitat and and all the

2168
01:58:37,200 --> 01:58:39,320
Speaker 1: effects of critical habitat and Arizona. So here's a guy

2169
01:58:39,360 --> 01:58:41,840
Speaker 1: that devoted his whole life and he's like at bangs

2170
01:58:41,880 --> 01:58:44,960
Speaker 1: with wolves. He's just pragmatic. He said, that's not critical

2171
01:58:45,080 --> 01:58:47,320
Speaker 1: to the conservation of the species. But there's no doubt

2172
01:58:47,360 --> 01:58:50,240
Speaker 1: everybody wants to make sure that um, they're able to

2173
01:58:50,280 --> 01:58:52,080
Speaker 1: still come up and use that habit that come back.

2174
01:58:52,160 --> 01:58:55,280
Speaker 1: Because I've been in in mountain ranges where I know

2175
01:58:55,360 --> 01:58:57,880
Speaker 1: there's a jaguar in that mountain Rangil Mountain Island, and

2176
01:58:57,960 --> 01:58:59,640
Speaker 1: it's pretty cool just to know that my son and

2177
01:58:59,680 --> 01:59:02,440
Speaker 1: I want time carried to have Elena that he shot

2178
01:59:02,520 --> 01:59:06,080
Speaker 1: off a tall mountain in the Coyote Mountains and in

2179
01:59:06,200 --> 01:59:08,080
Speaker 1: the dark through the thick brush, and we had a

2180
01:59:08,080 --> 01:59:11,040
Speaker 1: bloody have Alina on our shoulders. And I knew that

2181
01:59:11,200 --> 01:59:13,680
Speaker 1: the jaguar, the jaguar that we knew about, was in

2182
01:59:13,800 --> 01:59:15,960
Speaker 1: that part of the mountain range at that time. So

2183
01:59:16,080 --> 01:59:18,520
Speaker 1: that has a little element of interest when when you're

2184
01:59:18,520 --> 01:59:21,120
Speaker 1: out there awes lots. The same way when right when

2185
01:59:21,160 --> 01:59:24,320
Speaker 1: we left Sonora this year, you know, the article came

2186
01:59:24,360 --> 01:59:29,920
Speaker 1: out on the camera traps catching down there group. Yeah,

2187
01:59:29,920 --> 01:59:31,800
Speaker 1: well they got them in that you know that King

2188
01:59:31,960 --> 01:59:35,640
Speaker 1: Ranch area down there in South Texas. Yeah there, Well,

2189
01:59:35,720 --> 01:59:37,760
Speaker 1: and it's what's funny there is they're spending all this

2190
01:59:38,320 --> 01:59:42,120
Speaker 1: uh a version of things, is it? What's funny there

2191
01:59:42,240 --> 01:59:44,840
Speaker 1: is there like doing a lot of awes lot recovery work.

2192
01:59:45,560 --> 01:59:48,240
Speaker 1: And then it turns out that's sort of the strongest um.

2193
01:59:49,360 --> 01:59:53,040
Speaker 1: You know, the strongest populations are coming off these large

2194
01:59:53,120 --> 01:59:55,680
Speaker 1: cattle ranches. Yeah, there's two populations. Ones on a National

2195
01:59:55,720 --> 01:59:58,400
Speaker 1: Wilife Refuge and another one is on the Uturi Ranch,

2196
01:59:58,480 --> 02:00:01,360
Speaker 1: and I think the neighboring ranches and that's that's private

2197
02:00:01,480 --> 02:00:03,440
Speaker 1: lands and you've got that the old mandatory who I

2198
02:00:03,480 --> 02:00:07,480
Speaker 1: think passed away recently. I've permitted, have you just committed

2199
02:00:07,480 --> 02:00:11,720
Speaker 1: to us a lot conservation? And very much Yeah, it's

2200
02:00:11,800 --> 02:00:14,480
Speaker 1: very much private lands. You've you've got to be managing

2201
02:00:14,520 --> 02:00:16,880
Speaker 1: on private lands. It's Mike Twis and and there's a

2202
02:00:16,920 --> 02:00:19,920
Speaker 1: graduate student that, um did I know from Arizona that's

2203
02:00:19,920 --> 02:00:22,280
Speaker 1: down there working on osla's right now. But I knowing

2204
02:00:22,320 --> 02:00:24,480
Speaker 1: Mike Twois who's run that program since I did my

2205
02:00:24,520 --> 02:00:28,000
Speaker 1: master's agreed down there. But obviously that that species has

2206
02:00:28,040 --> 02:00:31,680
Speaker 1: a little bit northerly range than than the jaguars. It's

2207
02:00:31,760 --> 02:00:33,560
Speaker 1: kind of well, it's kind of the same in Arizona.

2208
02:00:33,600 --> 02:00:35,480
Speaker 1: It's kind of the same. There's historical records that come

2209
02:00:35,560 --> 02:00:39,160
Speaker 1: up through central Arizona or so, but not not a

2210
02:00:39,280 --> 02:00:42,160
Speaker 1: breeding population in Arizona like there is in Texas. South

2211
02:00:42,240 --> 02:00:45,200
Speaker 1: Texas are breeding if sixty some Austles that they know

2212
02:00:45,280 --> 02:00:47,480
Speaker 1: I'm out there there, But Arizona it's the same thing.

2213
02:00:47,560 --> 02:00:49,040
Speaker 1: It's one here and one there. And we have so

2214
02:00:49,120 --> 02:00:52,320
Speaker 1: many cameras in in those mountain ranges now that we're

2215
02:00:52,400 --> 02:00:55,400
Speaker 1: capturing what's sneaking around in there. I checked, are there

2216
02:00:55,400 --> 02:01:01,040
Speaker 1: any in Arizona right now, Oh jaguars, uh yes, right

2217
02:01:01,080 --> 02:01:04,760
Speaker 1: now as well as of September, and I know there

2218
02:01:04,840 --> 02:01:07,040
Speaker 1: was one around then. It turned up. It's high turned

2219
02:01:07,080 --> 02:01:10,280
Speaker 1: up on social media, got shot shot in Mexico. Back

2220
02:01:10,280 --> 02:01:12,320
Speaker 1: to Mexico and got shot. Yeah, there's there's a different

2221
02:01:12,400 --> 02:01:15,080
Speaker 1: one that. When I was down by Douglas in September,

2222
02:01:15,400 --> 02:01:17,600
Speaker 1: someone told me about one that was down there. I

2223
02:01:17,640 --> 02:01:19,240
Speaker 1: don't know if I can say where. I probably won't

2224
02:01:19,240 --> 02:01:21,640
Speaker 1: say where, but in the US and it got picked

2225
02:01:21,720 --> 02:01:24,160
Speaker 1: up by a trail camera. Houndsmen founded No, a lot

2226
02:01:24,200 --> 02:01:26,800
Speaker 1: of trail cams I had. I had checking out a

2227
02:01:26,920 --> 02:01:29,160
Speaker 1: lion that a hunter killed, because all the mountain lions

2228
02:01:29,200 --> 02:01:31,360
Speaker 1: get checked out at the game at Fish office, and

2229
02:01:31,520 --> 02:01:33,120
Speaker 1: he was he got it out of the Santa Ritos

2230
02:01:33,120 --> 02:01:34,400
Speaker 1: and he said they had a bunch of cameras in

2231
02:01:34,400 --> 02:01:37,400
Speaker 1: the Santa Rita mountains. This was several years ago. And

2232
02:01:37,520 --> 02:01:39,440
Speaker 1: I said, oh, you got a bunch of cameras, said

2233
02:01:39,640 --> 02:01:41,800
Speaker 1: you ever get one of them spotted cats. He goes

2234
02:01:41,840 --> 02:01:44,760
Speaker 1: yeah all the time, that's cool, and like wow, I

2235
02:01:44,800 --> 02:01:47,640
Speaker 1: mean hunters have trail cams out and they're getting jaguars

2236
02:01:47,640 --> 02:01:49,480
Speaker 1: on their trail camp. We've talked about this. There's a

2237
02:01:49,520 --> 02:01:52,640
Speaker 1: book called Candid Creatures, and it's like trail cam images

2238
02:01:53,400 --> 02:01:58,240
Speaker 1: and there's a jaguar standing in the snow. The only

2239
02:01:58,360 --> 02:02:00,880
Speaker 1: images like the only image I think maybe like the

2240
02:02:00,960 --> 02:02:04,360
Speaker 1: only image in existence or something of the jaguars. There's

2241
02:02:04,440 --> 02:02:06,680
Speaker 1: you're talking about the historical record of jaguars. We have

2242
02:02:06,840 --> 02:02:09,800
Speaker 1: that list that the Game Fish Department maintained of jaguar

2243
02:02:09,880 --> 02:02:13,480
Speaker 1: records going all the way back, but a lot of those,

2244
02:02:13,560 --> 02:02:15,920
Speaker 1: even in more recent times are like like some of

2245
02:02:15,960 --> 02:02:18,000
Speaker 1: the jaguar records that some of these groups for using

2246
02:02:18,080 --> 02:02:20,720
Speaker 1: for their modeling was some high school teachers saw black

2247
02:02:20,760 --> 02:02:24,640
Speaker 1: jaguar across the road, and black jaguars the color phase.

2248
02:02:24,680 --> 02:02:27,400
Speaker 1: It's a jungle phase. It's an Amazon thing. You never

2249
02:02:27,520 --> 02:02:30,320
Speaker 1: have black jaguars in Mexico and to the north. Never.

2250
02:02:30,720 --> 02:02:32,440
Speaker 1: So someone says they see a black jaguar, we know

2251
02:02:32,600 --> 02:02:34,800
Speaker 1: right away, well it wasn't a jaguar. I'm not sure

2252
02:02:34,840 --> 02:02:36,320
Speaker 1: what it was. Yeah, it's hard to start. I mean

2253
02:02:36,400 --> 02:02:38,440
Speaker 1: there's a there's a thing of like measuring the validity

2254
02:02:38,600 --> 02:02:41,560
Speaker 1: right right, and so we've got like three classes class one,

2255
02:02:41,600 --> 02:02:44,200
Speaker 1: Class two, Class three. I forgot what the criteria are,

2256
02:02:44,280 --> 02:02:48,360
Speaker 1: but it's to rank them for for veracity, for um,

2257
02:02:48,600 --> 02:02:51,160
Speaker 1: how reliable they are. But some of those, some of

2258
02:02:51,240 --> 02:02:54,000
Speaker 1: those are are just sightings, and some groups will want

2259
02:02:54,000 --> 02:02:56,680
Speaker 1: to include those as reliable and not. So you have

2260
02:02:56,760 --> 02:02:58,960
Speaker 1: to be careful. And that's why a table like that's

2261
02:02:59,000 --> 02:03:01,680
Speaker 1: a important. But there's a book called Borderland Jaguars. You

2262
02:03:01,760 --> 02:03:04,520
Speaker 1: have not seen that one, Okay, I'll send it to you.

2263
02:03:04,840 --> 02:03:07,720
Speaker 1: Carlos Lopos Gonzales and and Dave Brown and and in

2264
02:03:07,880 --> 02:03:11,000
Speaker 1: there they have probably not as complete as our list,

2265
02:03:11,080 --> 02:03:14,040
Speaker 1: but they have an account of the historical records of jaguars.

2266
02:03:14,080 --> 02:03:15,520
Speaker 1: I'd like to see it. I need to get my

2267
02:03:15,600 --> 02:03:20,000
Speaker 1: opinion straight. I know I like them, all right, everybody's

2268
02:03:20,040 --> 02:03:22,600
Speaker 1: I'd like to get pounced and scratched, kind of scratched

2269
02:03:22,640 --> 02:03:25,360
Speaker 1: by one, kind of just to leave a scar. You

2270
02:03:25,480 --> 02:03:28,200
Speaker 1: have to. It's cool to know that there's jaguars out

2271
02:03:28,240 --> 02:03:34,800
Speaker 1: there right across the packs. Man. One nice scratch, rub

2272
02:03:34,960 --> 02:03:36,920
Speaker 1: some dirt in there to get it infected through. Yeah,

2273
02:03:39,600 --> 02:03:41,600
Speaker 1: got your final thoughts questions? Yeah, I dude, I got

2274
02:03:41,720 --> 02:03:43,720
Speaker 1: I got a question for you. I was talking with

2275
02:03:43,880 --> 02:03:47,800
Speaker 1: a buddy of mine, uh this morning on my drive

2276
02:03:47,840 --> 02:03:50,560
Speaker 1: back over here, and and he's I was checking in

2277
02:03:50,640 --> 02:03:53,360
Speaker 1: with him because he's well for a service dude, and

2278
02:03:53,440 --> 02:03:56,600
Speaker 1: he's getting getting grant money and he's getting a lot

2279
02:03:56,640 --> 02:03:59,040
Speaker 1: of in kine cash for habitat work on his place,

2280
02:03:59,120 --> 02:04:02,920
Speaker 1: and this is kind of his retirement job, as he

2281
02:04:03,040 --> 02:04:06,720
Speaker 1: calls it, learning to be a farmer, and he's uh

2282
02:04:07,120 --> 02:04:11,800
Speaker 1: planting a bunch of plant species and and setting his

2283
02:04:11,920 --> 02:04:18,640
Speaker 1: place up for muleteer winning habitat and upland game Big

2284
02:04:18,960 --> 02:04:24,040
Speaker 1: loves loves the pheasants and quail. And he is kind

2285
02:04:24,040 --> 02:04:27,080
Speaker 1: of running me through his list of what he's got

2286
02:04:27,240 --> 02:04:32,040
Speaker 1: coming up and some of his successes and failures. And uh,

2287
02:04:32,520 --> 02:04:34,920
Speaker 1: I said, well, yeah, a lot of work right now,

2288
02:04:35,040 --> 02:04:38,240
Speaker 1: but hopefully you'll figure out how to strike a balance.

2289
02:04:38,880 --> 02:04:44,960
Speaker 1: He's like, yeah, I don't think so. He's like, to

2290
02:04:45,040 --> 02:04:46,480
Speaker 1: be honest with you, I'm not sure any of the

2291
02:04:46,520 --> 02:04:50,200
Speaker 1: ship is supposed to be here. And I mean, he

2292
02:04:50,400 --> 02:04:54,320
Speaker 1: is working with ecologists and he's got a litany of

2293
02:04:54,680 --> 02:04:59,160
Speaker 1: really good contacts from his past life. But that did

2294
02:04:59,360 --> 02:05:01,760
Speaker 1: just make me think of this question, like do you

2295
02:05:01,960 --> 02:05:06,600
Speaker 1: find yourself ever get kind of bogged down in the

2296
02:05:06,760 --> 02:05:11,320
Speaker 1: management of things, Like we've been manipulating landscapes and species

2297
02:05:12,280 --> 02:05:16,640
Speaker 1: for so long do you ever kind of get to

2298
02:05:16,720 --> 02:05:19,840
Speaker 1: these points where you're like, sure, I guess screw it,

2299
02:05:20,320 --> 02:05:22,400
Speaker 1: because it's not we're so far away from what it

2300
02:05:22,600 --> 02:05:25,960
Speaker 1: was or what we think it was. I don't think so.

2301
02:05:26,440 --> 02:05:28,120
Speaker 1: I mean, I don't. I don't think I get get

2302
02:05:28,200 --> 02:05:31,360
Speaker 1: that discouraged. There's there's things like in the wolf Recovery

2303
02:05:31,400 --> 02:05:34,320
Speaker 1: world where I just wish it wasn't a constant stream

2304
02:05:34,360 --> 02:05:37,480
Speaker 1: of litigation and litigation and litigation. Wish we could just

2305
02:05:37,560 --> 02:05:41,120
Speaker 1: get on with the business of conserving um carnivores and

2306
02:05:41,480 --> 02:05:45,600
Speaker 1: managing them as um as species. But but uh, I don't.

2307
02:05:45,760 --> 02:05:48,040
Speaker 1: I think I'm optimistic. I think there's just a lot

2308
02:05:48,120 --> 02:05:51,040
Speaker 1: of really good work going on right now throughout the West,

2309
02:05:51,120 --> 02:05:57,040
Speaker 1: habitat wise and and movement wise and everything that's great.

2310
02:05:59,200 --> 02:06:02,080
Speaker 1: Phil Someoney's addressed the elephant in the room that like,

2311
02:06:02,120 --> 02:06:04,320
Speaker 1: basically Janice has nothing to do with the show anymore.

2312
02:06:05,600 --> 02:06:08,800
Speaker 1: He's moved on to bigger he's he's out of honest

2313
02:06:08,880 --> 02:06:11,360
Speaker 1: once to get us out on assignments content I was

2314
02:06:11,400 --> 02:06:15,360
Speaker 1: assuming I was coming, and he's all busy with we

2315
02:06:15,440 --> 02:06:16,920
Speaker 1: got a lot of we've got a lot of irons

2316
02:06:16,960 --> 02:06:18,520
Speaker 1: in the fire and and he's tending to a couple.

2317
02:06:19,640 --> 02:06:23,680
Speaker 1: Got well, yeah, he's out ice fishing. But you don't

2318
02:06:23,680 --> 02:06:25,120
Speaker 1: have any you don't have your thing with That makes

2319
02:06:25,160 --> 02:06:27,640
Speaker 1: the honest sounds anymore, do you? I was thinking about

2320
02:06:27,640 --> 02:06:30,560
Speaker 1: bringing it to uh to Nashville next week, so you

2321
02:06:30,640 --> 02:06:36,720
Speaker 1: know he won't be there either. No, you got he's

2322
02:06:36,840 --> 02:06:40,440
Speaker 1: changing his damn thing. He's not even like a co host. Know,

2323
02:06:41,640 --> 02:06:44,520
Speaker 1: he's abandoned, he's moved on. He's he's left the nest.

2324
02:06:44,800 --> 02:06:48,520
Speaker 1: He's just busy. Yeah. Yeah, if you weren't cracking the whip,

2325
02:06:51,800 --> 02:06:55,400
Speaker 1: it's not true outdoors, Yeah, too much skin. He's missing

2326
02:06:55,480 --> 02:06:59,600
Speaker 1: some good skiing though, isn't he? I just said him

2327
02:06:59,600 --> 02:07:01,280
Speaker 1: to know what about out that it's puke in the

2328
02:07:01,360 --> 02:07:04,080
Speaker 1: nar man he's in final Like, I went to high

2329
02:07:04,080 --> 02:07:06,560
Speaker 1: school about forty minutes south of there, in college about

2330
02:07:06,560 --> 02:07:09,360
Speaker 1: an hour northwest of there, so familiar with that country.

2331
02:07:09,720 --> 02:07:12,960
Speaker 1: The only uh, all everything skiers say is annoying, But uh,

2332
02:07:14,200 --> 02:07:15,560
Speaker 1: I just hear one good one the other day is

2333
02:07:15,640 --> 02:07:19,280
Speaker 1: someone's talking about the powder and he said, um, that

2334
02:07:19,440 --> 02:07:23,720
Speaker 1: nar isn't gonna shred itself. I love it. I love it.

2335
02:07:26,440 --> 02:07:29,600
Speaker 1: Blower all right, Jeff Helen fingering what what's your favorite

2336
02:07:29,680 --> 02:07:31,560
Speaker 1: of all the pamphlets and books you read? I think

2337
02:07:31,600 --> 02:07:35,400
Speaker 1: you you say that your masterpieces the jack Book, Hunts

2338
02:07:35,440 --> 02:07:38,240
Speaker 1: and Recipes. Yep. And that's even available as a pdf

2339
02:07:38,560 --> 02:07:41,760
Speaker 1: on my website deer nut dot com. Um, just the

2340
02:07:42,160 --> 02:07:46,240
Speaker 1: doughy r nut dot com. Um. I've got a whole

2341
02:07:46,240 --> 02:07:48,640
Speaker 1: bunch of PDFs that are magazine articles that I've written

2342
02:07:48,840 --> 02:07:50,760
Speaker 1: and you can. I've got Deer of the Southwest. I

2343
02:07:50,840 --> 02:07:53,400
Speaker 1: brought you a copy which is Cow's white Tail and

2344
02:07:53,440 --> 02:07:57,240
Speaker 1: Desert Meal Deer in the Southwest Northern Mexico. Um. That's

2345
02:07:57,240 --> 02:08:02,160
Speaker 1: available on the website and um my Instagram Jim Deer

2346
02:08:02,800 --> 02:08:04,560
Speaker 1: and and deer has an E after the end, like

2347
02:08:04,680 --> 02:08:06,880
Speaker 1: John Deere. Fact, it's a little John Deer logo that

2348
02:08:06,960 --> 02:08:08,600
Speaker 1: photoshop to look like a meal there. Do you want

2349
02:08:08,600 --> 02:08:12,760
Speaker 1: wanna come down and do a jack rabbit hunt with you, man? Yeah, definitely, definitely.

2350
02:08:13,080 --> 02:08:15,560
Speaker 1: I'd like to you guarantee me that we'll get tons

2351
02:08:15,560 --> 02:08:18,000
Speaker 1: of them right without trying very hard? Well, no, you

2352
02:08:18,160 --> 02:08:20,240
Speaker 1: you drive around if you want tons, you drive around

2353
02:08:20,240 --> 02:08:21,560
Speaker 1: and shoot him out of the window. And we don't

2354
02:08:21,600 --> 02:08:24,080
Speaker 1: do that. We walk, I mean walk the land, so

2355
02:08:24,320 --> 02:08:26,360
Speaker 1: we don't walk back with tons, but it's a fun hunt.

2356
02:08:28,000 --> 02:08:29,720
Speaker 1: You get bit up by Mike's quite a bit with those.

2357
02:08:30,360 --> 02:08:32,520
Speaker 1: No they're not no mighty, No, they've got they've got

2358
02:08:32,560 --> 02:08:36,800
Speaker 1: a couple of internal parasites like the the butt fly larva,

2359
02:08:37,320 --> 02:08:40,040
Speaker 1: a big thumb size cute. When they get under the skin,

2360
02:08:41,160 --> 02:08:43,920
Speaker 1: it doesn't affect the meat. But we in our junior

2361
02:08:44,000 --> 02:08:45,960
Speaker 1: jack camp that I developed for kids ten years ago,

2362
02:08:46,000 --> 02:08:47,800
Speaker 1: we bring kids together and we we show them how

2363
02:08:47,800 --> 02:08:50,120
Speaker 1: to jack rabbit hunt, show them how to um clean

2364
02:08:50,240 --> 02:08:53,240
Speaker 1: and cook the jack rabbits. We find some of those big,

2365
02:08:53,480 --> 02:08:56,040
Speaker 1: ugly but fly larva under the skin and and we

2366
02:08:56,240 --> 02:08:59,960
Speaker 1: turned a liability into a positive. When we we still

2367
02:09:00,080 --> 02:09:02,480
Speaker 1: did we brought a little scale, no, we started weighing

2368
02:09:02,520 --> 02:09:04,360
Speaker 1: them and we gave out an award for the largest

2369
02:09:04,440 --> 02:09:06,960
Speaker 1: buttfly large that s the kids are going, Do I

2370
02:09:07,040 --> 02:09:08,320
Speaker 1: have one? Do I have one? Does mine have one?

2371
02:09:08,400 --> 02:09:10,920
Speaker 1: Can you start on? So when you grab them, see

2372
02:09:10,920 --> 02:09:12,400
Speaker 1: I thought, because you guys are down where it doesn't

2373
02:09:12,400 --> 02:09:15,000
Speaker 1: get cold and winter enough, when you grab him your arms,

2374
02:09:15,040 --> 02:09:17,480
Speaker 1: don't just get them by min now. And we hunt

2375
02:09:17,560 --> 02:09:19,879
Speaker 1: them there open ye around but we hunt them October

2376
02:09:19,960 --> 02:09:22,920
Speaker 1: to March, just a season so we can keep the meat,

2377
02:09:23,080 --> 02:09:28,160
Speaker 1: and there is less ectoparasites on them, yep, as opposed

2378
02:09:28,160 --> 02:09:31,000
Speaker 1: to the endo inside were outside like like the like

2379
02:09:31,080 --> 02:09:33,600
Speaker 1: the insects on the outside. But it's not not bad

2380
02:09:33,640 --> 02:09:35,240
Speaker 1: at all. I mean, you just don't when you grab them,

2381
02:09:35,240 --> 02:09:37,960
Speaker 1: they're nice and clean, and you skin them and you've

2382
02:09:38,000 --> 02:09:41,440
Speaker 1: got some really nice clean meat that cooks up like beeft. Wow,

2383
02:09:41,880 --> 02:09:44,920
Speaker 1: how much did you learn, Phil? Like on one to ten,

2384
02:09:45,320 --> 02:09:48,480
Speaker 1: we're paying attention. It was a solid eight. You guys,

2385
02:09:49,000 --> 02:09:51,320
Speaker 1: You guys ran the gamut. He was so many things

2386
02:09:51,400 --> 02:09:54,320
Speaker 1: were talked about. Yeah, yeah, you're soaking it up. Soaking

2387
02:09:54,360 --> 02:09:57,480
Speaker 1: it up. Mostly I was fantasizing about my Neanderthal mingling

2388
02:09:59,240 --> 02:10:01,720
Speaker 1: in this hypothet nicole situation. I feel had to go back.

2389
02:10:01,800 --> 02:10:05,480
Speaker 1: He went back behind that curtain for a while. That's right.

2390
02:10:06,720 --> 02:10:10,080
Speaker 1: It's imagining like a Romeo and Juliet's situation forbidden love.

2391
02:10:10,280 --> 02:10:15,920
Speaker 1: Phil search history is that sounds like a movie. I

2392
02:10:16,000 --> 02:10:18,240
Speaker 1: know tonight, I'm gonna want it tomorrow. I try to

2393
02:10:18,320 --> 02:10:25,400
Speaker 1: tap into Phil's incognito search that you don't want to,

2394
02:10:26,880 --> 02:10:33,640
Speaker 1: all right, Jim Halflefinger outdoorsman biologists, man in the man

2395
02:10:33,720 --> 02:10:37,720
Speaker 1: in the arena, A man in the arena when it

2396
02:10:37,840 --> 02:10:42,280
Speaker 1: comes to wildlife and wildlife management and UM and a

2397
02:10:42,360 --> 02:10:46,040
Speaker 1: great advocate for hunters and wildlife. Thank you for joining us.

2398
02:10:46,480 --> 02:11:03,160
Speaker 1: Thanks it would great be here. Comp