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Speaker 1: If this is the me Eater Podcast coming at you shirtless, severely,

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Speaker 1: bug bitten, and in my case, underwear listening podcast, you

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Speaker 1: can't predict anything brought to you by first Light. When

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Speaker 1: I'm hunting, I need gear that won't quit. First Light builds,

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Speaker 1: no compromise, gear that keeps me in the field longer,

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Speaker 1: no shortcuts, just gear that works. Check it out at

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Speaker 1: first light dot com. That's f I R S T

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Speaker 1: L I t E dot com. Welcome to the me

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Speaker 1: Eater Podcast. Suckers listen. If you got little kids standing by,

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Speaker 1: you're gonna cover their ears because Randall's got a news item.

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Speaker 2: We are gonna bleep it right feels gonna leep the

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Speaker 2: whole good of course.

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Speaker 1: Yeah, we've done this in the past. Yes, So Randall

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Speaker 1: found us the Salacious Exchange on what platform?

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Speaker 2: This is? On Facebook?

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Speaker 1: You spent a lot of time there.

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Speaker 2: No, I have no I was looking at I was

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Speaker 2: looking at like you know.

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Speaker 1: Facebook marketplace stuff, and this popped up.

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Speaker 3: Yeah, and I have no idea. I have no idea

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Speaker 3: who this guy is. I did some research to find

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Speaker 3: out where he is. We won't name him.

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Speaker 1: But just set the scene.

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Speaker 3: He's he goes on I didn't come through your feet

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Speaker 3: like it was just algorithm.

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Speaker 2: It knows that.

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Speaker 1: I'd like this. That's not true. You're lying.

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Speaker 3: Oh, so I'll set the scene. There's a photo and

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Speaker 3: it's it's a bunch of packaged deer meat, and his

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Speaker 3: post reads I'll do a shortened version. Deer processors are

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Speaker 3: the biggest ripoffs of twenty twenty five, one hundred and

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Speaker 3: eighty five bucks for thirty packs of meat, which brings

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Speaker 3: the price over six bucks a pack, and I supplied

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Speaker 3: the meat. Then they want to get because you question

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Speaker 3: them on it. Lucky I didn't slap the shit out

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Speaker 3: of him.

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Speaker 1: I'm in the.

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Speaker 3: Process of processing my own, damn dear and the processor,

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Speaker 3: and hope they all go to out of bat Hope

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Speaker 3: they all go out of business, a bunch of ripoff bastards.

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Speaker 3: Then they me on five packs of sausage that cost

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Speaker 3: me fifteen dollars. Mind you, deer processing was eighty five

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Speaker 3: dollars before, Sleepy Joe for the same thing.

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Speaker 1: Omit. Well, back up, I'm interested. He feels that that

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Speaker 1: that he feels that the Biden administrations made me, made

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Speaker 1: wild game processing go up.

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Speaker 2: It's part of it. I think he also just thinks

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Speaker 2: that they're they're greedy, and.

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Speaker 1: They felt emboldened by greed. They felt emboldened by the

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Speaker 1: Biden administration to charge more.

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Speaker 3: Yeah, and I think the real like the real, uh,

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Speaker 3: this is this is.

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Speaker 1: That is true. I believe everything anybody tells me.

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Speaker 2: And you think this is like, this is it.

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Speaker 3: But there's two point nine k comments, so twenty nine

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Speaker 3: hundred comments, and I realized that this man is responding

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Speaker 3: to almost everyone that comments.

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Speaker 1: So he just wants the public to know. Just so

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Speaker 1: I'm understanding this, he just wants the public to know.

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Speaker 2: He's going to do Yeah, he's been he's going to

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Speaker 2: do it himself from.

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Speaker 1: Now now on. He's doing it himself. And he just

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Speaker 1: is putting this out to the public.

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Speaker 2: Yes.

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Speaker 3: So one one person commented, grow some balls and process

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Speaker 3: the deer yourself and retain all the meat for yourself.

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Speaker 3: And he responded six hours later and he said, I've

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Speaker 3: got some for you, Phil.

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Speaker 1: Are you bleeping out? Listeners already know the answer to this.

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Speaker 1: Are you bleeping out the balls? Yeah?

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Speaker 4: I think I think I think the balls in the

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Speaker 4: in the the initial comment, I will not bleep out

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Speaker 4: the balls. In the second comment, I will I think

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Speaker 4: the context is different. You know, No, that's not being bleeped.

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Speaker 5: Let's get back to talk about of balls. We've let

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Speaker 5: so much more fla so I'll just.

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Speaker 1: I'm in it trying to get another they experience.

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Speaker 3: Another gentleman commented, if you handle the work, you should

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Speaker 3: have to pull out your wallet. Then, eleven hours later,

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Speaker 3: the man responded, nobody asked the peanut gallery.

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Speaker 2: Nothing, so you can.

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Speaker 3: But but he did because he I know, I know

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Speaker 3: he did. Humans are full of contradictions.

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Speaker 1: How is putting? How is a Facebook post not asking

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Speaker 1: the peanut gallery?

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Speaker 3: Yeah, I don't think he's fully. Yeah, you should reflect

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Speaker 3: on your attitude before taking the life of another animal.

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Speaker 3: You should be more grateful, to which he responds, I

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Speaker 3: wouldn't think twice to take yours.

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Speaker 5: That's that's the one good one. That one got me.

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Speaker 5: That's good. Your mind here, your mind here?

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Speaker 1: Oh yeah, let me find uh because I'm a sucker

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Speaker 1: for a good year. Modjo Well, there's a couple threatened

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Speaker 1: to punch me.

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Speaker 2: There's a couple of your modjoke.

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Speaker 3: This This one says sleepy Joe is the problem? Question

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Speaker 3: Mark sounds like the problem is leapy so and so

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Speaker 3: who can't do his own deer. And he says, because

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Speaker 3: I was busy your.

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Speaker 1: Mom, that's good. What are you gonna bleep on on that?

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Speaker 5: I don't know.

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Speaker 4: I'm gonna feel it out and just see what see

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Speaker 4: what feels.

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Speaker 5: It feels right.

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Speaker 3: Then he brings his own profession while someone brings his

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Speaker 3: own professions. He says, sounds like you yourself and brought

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Speaker 3: it to the wrong butcher, just like when customers bring

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Speaker 3: to you for bubblegum welding, to which he responds, oh,

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Speaker 3: he's a welder. He says, yeah, okay, let's see your

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Speaker 3: weld smart ass, You nor nobody you know can do

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Speaker 3: what I do.

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Speaker 1: So it's turned into an indictment of his own welding.

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Speaker 3: Yeah, and then there's just rapid fire. Real men cut

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Speaker 3: up their own deer. Hugh pal, watch out. We got

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Speaker 3: a badass off. If you don't have time or knowledge

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Speaker 3: to put what you harvest in the freezer, you shouldn't

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Speaker 3: be hunting for you. Sounds like you was being lazy

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Speaker 3: and cost you more than you wanted to pay.

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Speaker 2: Now you're mad.

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Speaker 3: If you want to bitch, get off your ass and

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Speaker 3: do it yourself. And he says, you nobody's lazy but

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Speaker 3: your old lady.

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Speaker 1: Maybe it could be true.

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Speaker 2: Yeah, And then the other one was my this is

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Speaker 2: I'll end with this.

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Speaker 1: Uh.

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Speaker 3: He says, if you don't shoot a button buck, you'll

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Speaker 3: get more meat. And he says, does this look like

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Speaker 3: a button buck to you?

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Speaker 6: Then he has a picture of him holding the cut

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Speaker 6: off head in the back of the truck.

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Speaker 2: It is a nice buck.

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Speaker 7: Can I see that?

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Speaker 5: Karin? Do you know what bubble gum welding is?

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Speaker 7: It's I mean, is it just like doing a shoddy

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Speaker 7: job and.

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Speaker 3: Bubby gobby well gobby like gum stun on the other

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Speaker 3: side of the table.

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Speaker 7: Oh oh god, okay, thank you, thank.

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Speaker 5: You for until I did a little bit of welding

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Speaker 5: last year.

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Speaker 3: I was out duck hunting with Cal and I was

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Speaker 3: like a lull in the action and I just got

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Speaker 3: on Marketplace and I saw that and I screenshot. I

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Speaker 3: took like ten screenshots of the comments, and there's more there.

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Speaker 2: It's a rich text.

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Speaker 7: The guy exposed himself. I mean he exposed his face.

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Speaker 2: Oh yeah, no, I mean it's a personal pacebook.

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Speaker 5: Yeah, yeah, you.

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Speaker 2: Can if you go to his have him on the show.

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Speaker 2: He seems a little cantankerous.

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Speaker 5: Uh maybe remotely.

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Speaker 1: You know what's funny, you.

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Speaker 7: Know, the keep him my arms like.

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Speaker 1: I want to get moving along. We had a lot

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Speaker 1: to cover today. We're just so just so, ladies and gentlemen,

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Speaker 1: just so you know, we're gonna talk about Florida, Florida

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Speaker 1: bear hunt, a lot of news Florida bear hunt. We

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Speaker 1: got a heartwarming story from Canada. We're going to talk

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Speaker 1: about uh, Colorado wolf management, and and and the wrath

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Speaker 1: of the Trump administration. We're going to talk about a

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Speaker 1: lot of cractions. Oh, some stuff about jaguars and Arizona,

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Speaker 1: some stuff about mountain goats in Alaska. A lot of

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Speaker 1: stuff to talk about. What else is in here is

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Speaker 1: a thing called a desperate plea about skunks. Oh, Massachusetts

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Speaker 1: lobster hest Hmmm. I don't think we can get to

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Speaker 1: the subsistence. That's a big bucket. Anyways, obviously, lots of

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Speaker 1: stuff we got to cover. But real quick. You know,

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Speaker 1: the the Bobcat Championship game, No, the local school team won.

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Speaker 1: My buddy, very exciting. My kid's buddy was telling a story.

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Speaker 1: His family's all huge Bobcats fans. It goes to overtime

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Speaker 1: and so It's like very tense overtime moment and the

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Speaker 1: bobcast dude makes a catch in the end zone, which

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Speaker 1: ties the game up. It will then be decided by

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Speaker 1: the extra point.

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Speaker 8: Anyways, the minute he makes to catch his old man.

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Speaker 1: I was watching this dude, and you know what's funny,

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Speaker 1: I'm watching with my family, so I'm in the position

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Speaker 1: of knowing more than anybody. It's like that old leg

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Speaker 1: you know, I hate say it, but it's a it's

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Speaker 1: an old term, like the blind leading the blind. I

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Speaker 1: had a glimmer of vision leading a family of the

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Speaker 1: blind because I'm like, oh no, what happens now?

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Speaker 7: You know?

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Speaker 8: Because my wife she all surprised because Katie's been.

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Speaker 1: She's a big fan. She was on she was fired up.

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Speaker 1: But I know more of the rules, and I'm just

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Speaker 1: like better, I don't know, man, Like I'm better at

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Speaker 1: like that figuring out what's going on in a football

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Speaker 1: game than she is. Yeah, I just damn. She's more

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Speaker 1: invested in it. She likes going to the to the

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Speaker 1: the arena to watch the games. So anyways, my kid's

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Speaker 1: buddy his dad. The minute the dude makes the catch,

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Speaker 1: his dad in a moment of excitement curls his remote

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Speaker 1: control across the room, and when the remote control hits

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Speaker 1: the wall, it changes the channel and then dissolves. So

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Speaker 1: he's just scribing as old man trying to frantically his

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Speaker 1: TV back up and running. And by the time he

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Speaker 1: got this, by the time he got it back up,

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Speaker 1: the game was over.

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Speaker 7: Hes overtime missed.

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Speaker 1: He missed, you know, I mean, it was just this

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Speaker 1: old man that was like just so overwhelmed. That was hilarious. Uh,

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Speaker 1: heartwarming story to start. New York folks, here's a good

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Speaker 1: one for you. On a recent show, we covered a

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Speaker 1: We kind of dogged on him and goofed on him

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Speaker 1: a little bit, but we we covered a young struggling

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Speaker 1: Canadian hunter who lives in Alberta. Probably probably no, we

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Speaker 1: know he's in Alberta. Yeah, talking all about how he

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Speaker 1: he's hunted all these years and never sees nothing, never

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Speaker 1: gets nothing where to go. He says, they'll tell him

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Speaker 1: to go west, but then he sees a picture of

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Speaker 1: them with a deer and it looks like they went

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Speaker 1: the east. He thinks people lie to him, hunting all

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Speaker 1: these years, never got anything but a grouse. Well, we

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Speaker 1: covered him and goofed on him and with love. He

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Speaker 1: wrote in to say, uh, no, no, no, no, he didn't.

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Speaker 7: Right there, a bunch of Canadians.

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Speaker 1: Canadians wrote us helping him out.

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Speaker 9: That just goes to show you the difference between Canadians

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Speaker 9: and Americans.

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Speaker 1: Americans be like, here's my name is this letter there,

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Speaker 1: here's a letter that came in. Hey there, my name

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Speaker 1: is Steve van Brunt and I'm the treasurer of the

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Speaker 1: Calgary Fish and Game Association. By the sounds of his email,

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Speaker 1: I'd guess this hunter is in Calgary. Our group would

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Speaker 1: love to take him in and help him out. Please

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Speaker 1: forward him my info. I know the struggle. I also

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Speaker 1: started hunting in my twenties and went a few years

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Speaker 1: getting skunked at first. And he says, here's the for reference,

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Speaker 1: here's a picture of my first year, which I out

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Speaker 1: west in the mountains.

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Speaker 7: And if you look, it's not connected. The initial writer

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Speaker 7: in with this group and maybe we'll hear of his success.

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Speaker 1: Uh, here's here's a deal. Now, this is this is

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Speaker 1: pay we gotta do, we gotta do corrections now. Anyone

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Speaker 1: alive today knows that everyone talks about how we're in

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Speaker 1: this era of misinformation, right, We're like in this cultural

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Speaker 1: moment of we're just misinformation. Does everybody know that if

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Speaker 1: you're engaged in the national conversation and you're a news reader,

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Speaker 1: you would know that there is a You would know

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Speaker 1: whether you agree it or not, you would know that

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Speaker 1: there is a cophony of of like noise around fake

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Speaker 1: news misinformation, and it cuts both ways. During during during

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Speaker 1: the pandemic, you'd say that, hey, maybe it was a

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Speaker 1: lab leak, and you'd you'd be accused of misinformation, right,

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Speaker 1: which wound up being probably true. So it cuts both ways.

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Speaker 1: But there's this whole narrative of like there's no accountability, right,

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Speaker 1: there's no accountability. You just say, you say a re

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Speaker 1: you say a thing, and you could say something blatantly false,

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Speaker 1: and we don't have the mechanisms out there to correct misinformation.

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Speaker 9: And then it goes out there and does.

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Speaker 1: Its thing and it cuts both ways.

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Speaker 2: Whatever, But we have that mechanism here.

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Speaker 1: We have that here. And I'll point this out when

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Speaker 1: I participated in that, when I participated in the New

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Speaker 1: York Times Daily podcasts, I've been on a lot of

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Speaker 1: podcasts and I've hosted a lot of podcasts. Those suckers

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Speaker 1: fact check. Yeah what the guest says, Yeah, that would

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Speaker 1: shut down most podcasts.

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Speaker 5: Yeah, we started, they recorded you don't want me.

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Speaker 1: They go, they go to me and they're like, you

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Speaker 1: said X, you said why you said Z. We can't

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Speaker 1: corroborate Z. And I had to go and be, well,

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Speaker 1: give me five minutes and I'll show you right. And

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Speaker 1: then later that day I had to be like I

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Speaker 1: was wrong. I was wrong, and they caught it. Yeah, right,

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Speaker 1: no one does that. That would ruin. That would end

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Speaker 1: podcasting in America today. However, what we'd like to do

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Speaker 1: is we're going to create we want I want corrections

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Speaker 1: so bad that we're going to create a system by

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Speaker 1: which we reward corrections. So if we say something that's

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Speaker 1: off or incorrect, or if we miss something, or if

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Speaker 1: they're you know, but you know that thing that happens

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Speaker 1: where you lie by omission. M h. We caught our

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Speaker 1: kid lying by omission recently.

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Speaker 9: Left out a key detail hill.

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Speaker 1: The detail was so key, right the d He's like,

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Speaker 1: I'm gonna go do blank.

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Speaker 7: This is the oldest.

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Speaker 1: Yeah, I'm gonna go do blank. They're like, oh, this

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Speaker 1: doesn't sound like a problem, you know, And then like

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Speaker 1: a while later we realized that he left.

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Speaker 2: Off the other things he was doing.

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Speaker 1: Like let's say, you know, let's say let's say this

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Speaker 1: isn't it. Let's say you were like, Hey, I'm gonna

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Speaker 1: run down the road to the gas station, okay to

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Speaker 1: rob it. Yeah, right, that's not it. But to be

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Speaker 1: like a thing like that, and we're like, oh, that's what.

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Speaker 1: At what point were you planning on including that detail?

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Speaker 1: So he lied by omission, right, lied by omission. So

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Speaker 1: if we say something that's off incorrect, if we miss something,

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Speaker 1: if we if if we screw up by omission of

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Speaker 1: a thing, right, sure everything you said was correct, or

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Speaker 1: you the listener are thinking, you didn't say anything that

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Speaker 1: was wrong, but you left off something of such impact

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Speaker 1: that would have fundamentally changed the conversation you were having.

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Speaker 1: Feel free to write in, but.

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Speaker 9: They got to bring the receipts, right, They can't just

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Speaker 9: disagree with you.

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Speaker 1: Gotta bring the receipts. You got to show your wor.

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Speaker 7: Project concerning about it.

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Speaker 1: Please don't just send a bunch of dumb garbage in.

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Speaker 7: You can email the meat Eater podcast at the meadeater

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Speaker 7: dot com and we're going to be accumulating a bank

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Speaker 7: of this and corrections in a little while will formalize

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Speaker 7: a segment.

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Speaker 1: Yeah, we're talking about formalizing a segment, and we're talking

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Speaker 1: about rewarding the best correction.

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Speaker 9: Bhili, you're gonna have to come up with a corrections jingle.

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Speaker 1: Oh we can traditions.

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Speaker 4: Well, I had an idea where in the room you

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Speaker 4: all go one, two, three corrections and then I play

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Speaker 4: a sound like corrections.

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Speaker 5: Have like a combo deal. I don't know, we will

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Speaker 5: figure it out.

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Speaker 1: Fidd around the roof, coming back.

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Speaker 5: We've done this in the We've never.

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Speaker 1: We've never systematic by acknowledging it, but we've never formalized.

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Speaker 1: And what we're aiming toward doing is perhaps building a

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Speaker 1: correction of the week.

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Speaker 4: This is a live This is a live idea. I'm

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Speaker 4: thrown out there. Feel free to shut it down immediately.

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Speaker 4: Would you want people to send in like video clips

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Speaker 4: of them saying like, hey, this is this is John

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Speaker 4: from from Arkansas.

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Speaker 5: I got a correction for you.

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Speaker 1: We can play it. We can play it on.

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Speaker 2: Depending on the delivery.

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Speaker 5: Yeah, you could do that.

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Speaker 1: That would be if someone did do that.

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Speaker 9: We don't want Randall's guy doing that.

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Speaker 1: From Facebook, Phil, get out with the corrections.

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Speaker 5: I foresee. I just finished my thought. I foresee a

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Speaker 5: show that is corrections, because.

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Speaker 1: Then you got corrections to the corrections that's been a thing.

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Speaker 1: We don't need to do them all, so the warner

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Speaker 1: here's a cruestion.

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Speaker 5: Just pick the good corrections that we like.

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Speaker 1: No, the best correction is the correction that corrects the

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Speaker 1: biggest wrong correct For instance, like if someone's like, oh,

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Speaker 1: you said that it became a state in eighteen forty eight,

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Speaker 1: it actually became technically it became a state on at

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Speaker 1: eleven fifty nine, you know PM, the New Year's Eve,

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Speaker 1: eighteen forty seven, Like I don't care about that, yeah,

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Speaker 1: you know. But if it's like, hey man, you said

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Speaker 1: whatever that that that you know, I don't know. For example,

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Speaker 1: that we have some good trying I'll show here this

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Speaker 1: isn't a podcast correction, is a video correction, but it

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Speaker 1: has podcast tiens. We recently did a thing, a video

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Speaker 1: about our our Sandhill cranes, truly the Ribbin in the Sky.

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Speaker 7: If you haven't watched it, go to YouTube.

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Speaker 1: And we're currently making a video called our merganzas really

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Speaker 1: as bad as they say. Okay, so in our Sandhill

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Speaker 1: Crane video, we busted out our Warner Braxler sheer Force

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Speaker 1: test machine, which measures tenderness to this. Chris Calkins from

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Speaker 1: the University of Nebraska, who is a meat scientist, wrote

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Speaker 1: in to.

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Speaker 7: Say, wait, he was our guest.

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Speaker 1: Yeah, he was on episode to seventy seven. He came

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Speaker 1: out to talk about meat science. The episode that was

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Speaker 1: back when we had good names for our episodes. That

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Speaker 1: episode was called Red Cutter before we caved and started

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Speaker 1: using dumb names. Now he's a meat scientist.

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Speaker 5: So yeah, if you're going to go find this episode,

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Speaker 5: don't search like mediator what to know about meat. You're

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Speaker 5: gonna have to type.

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Speaker 1: In red red something you never think to write in.

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Speaker 1: Very difficult to find it, because something that no one

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Speaker 1: on the planet is searching.

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Speaker 2: Except for people who have already listened to the episode.

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Speaker 1: And remember every if they typed in meat Scientists, University Nebraska,

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Speaker 1: Wild Game, you won't find. You type in red Cutter,

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Speaker 1: you'll find this.

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Speaker 5: It's an extremely educational episode.

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Speaker 7: Listen like every year, just to refresh.

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Speaker 1: Yeah, all your questions about like all your questions, like

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Speaker 1: you know, when someone hits a deer and it goes

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Speaker 1: you hit a deer bad and it goes two miles

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Speaker 1: before you find it, and then people be like, well

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Speaker 1: that deer will be no good to eat because it

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Speaker 1: was stressed and the lactic acid. All those questions resolved.

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Speaker 1: Should you soak your meat and water? Should you soak

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Speaker 1: it in saltwater? All those questions was out. He wrote

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Speaker 1: in to say there's no Basically, he says, yeah, what

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Speaker 1: is he? Oh? Here it is, It's quick. This is

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Speaker 1: Chris Calkins, the meat scientist. I saw a recent Instagram

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Speaker 1: posts showing use of the meat sheer machine being used

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Speaker 1: on raw meat. Be aware there's hardly any relationship between

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Speaker 1: sheer force of raw versus cooked meat. For those who know,

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Speaker 1: it's a glaring error. We were taking raw sand Hill

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Speaker 1: crane in raw ribbi and measuring the tenderness and the

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Speaker 1: sand Hill crane blew away the ribbi in terms of tenderness?

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Speaker 5: Did you do it cooked? Also, we never did it.

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Speaker 1: And what was funny about it is I was noticing

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Speaker 1: that in the sheer force machine, sand Hill crane is half.

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Speaker 1: It's scoring like I can't remember the exact numbers. Basically,

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Speaker 1: it's scoring like a one point five bite force and

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Speaker 1: the ribbi is scoring a three point zero bite force.

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Speaker 1: But then when you cook them and eat them, there's

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Speaker 1: no discernible Like in my mind, there's no discernible difference.

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Speaker 1: He's saying, you can't do that, you gotta cook it.

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Speaker 1: Then sheer force tested.

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Speaker 7: So we did the wrong science.

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Speaker 1: It is okay, that's a great correction. In future, this

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Speaker 1: gentleman would maybe be walking away with correction of the week.

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Speaker 1: M M. For those Brody's going to visit your home

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Speaker 1: and cook you dinner and.

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Speaker 9: You can insult me or something and tell me I'm wrong.

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Speaker 1: Here's another correction. How game you are for that, Brady.

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Speaker 1: We recently had on an episode seven ninety six called

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Speaker 1: Heart of the Jaguar. We had on the author James Campbell,

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Speaker 1: and we discussed, among many things, jaguars and jaguar recovery

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Speaker 1: in Arizona. In that episode, we mentioned the biologist one

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Speaker 1: of the if not the leading servid researchers. He's gonna

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Speaker 1: he's not. He's gonna write a correction about that, saying

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Speaker 1: how he's not Amanda in regard to be one of

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Speaker 1: the leading servid researchers in America. I regard that to

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Speaker 1: be true. We mentioned Heffelfinger in the show, and I

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Speaker 1: even mentioned saying something that Heffelfinger might not like to hear.

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Speaker 1: In Heffelfinger we had a long conversation. Hefflefinger had some

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Speaker 1: very fair corrections. He was unhappy with references to the

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Speaker 1: Arizona Game and Fish Department not being supportive of jaguars

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Speaker 1: showing up in Arizona, and he had a mountain of

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Speaker 1: examples that he shared with me demonstrating quite the opposite

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Speaker 1: that the Zona Game and Fish Department has been entirely

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Speaker 1: hospitable to jaguars in Arizona. He says his agency has

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Speaker 1: always been very active in both planning and implement implementation

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Speaker 1: of jaguar conservation. The Arizona Game and Fish Department supports

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Speaker 1: the US Fish and Wildlife Services Jaguar Recovery Plan, which

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Speaker 1: focuses on core jaguar habitat in South and Central America

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Speaker 1: and Mexico, and that conservation efforts and funds for jaguar

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Speaker 1: conservation should be focused south of the border. He also

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Speaker 1: says although the Peripheral the peripheral habitat in Arizona doesn't

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Speaker 1: contribute to recovery, his department remains committed to protecting and

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Speaker 1: conserving those individuals that disperse into Arizona. Moving on to

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Speaker 1: a public service announcement. This doing this announcement goes against

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Speaker 1: my well being because I've already bought my raffles.

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Speaker 2: I was thinking.

440
00:24:48,119 --> 00:24:50,639
Speaker 1: The Outdoor Heritage Foundation.

441
00:24:51,040 --> 00:24:53,200
Speaker 7: Sorry, I'm about to knock your odds down because I

442
00:24:53,240 --> 00:24:55,440
Speaker 7: got the page open. I'm gonna get my credit card out.

443
00:24:57,400 --> 00:25:00,240
Speaker 1: The Outdoor Heritage Foundation of Alaska is raffling off a

444
00:25:00,320 --> 00:25:04,240
Speaker 1: chew Gatch Mountain Goat tag that's G eight hundred. That's

445
00:25:04,240 --> 00:25:07,360
Speaker 1: the tag number, which will come with a fully guided

446
00:25:07,960 --> 00:25:12,879
Speaker 1: hunting experience and a travel stipend, as well as a

447
00:25:13,000 --> 00:25:16,200
Speaker 1: Delta Junction Bison tag which is s I four hundred.

448
00:25:17,320 --> 00:25:20,840
Speaker 1: The money raise is it s I four hundred. I

449
00:25:20,840 --> 00:25:24,760
Speaker 1: think it's d I nless they changed it m I

450
00:25:24,760 --> 00:25:30,199
Speaker 1: feel like it should be di I. It's d I c.

451
00:25:30,200 --> 00:25:34,760
Speaker 7: I four oh three. That's what it says on the website.

452
00:25:35,520 --> 00:25:38,840
Speaker 1: Whatever. It's the Delta Junction Bison tag, so.

453
00:25:38,920 --> 00:25:41,360
Speaker 5: You get two tags if you win.

454
00:25:42,640 --> 00:25:44,680
Speaker 1: The money raise for these tags will go to fund

455
00:25:44,760 --> 00:25:48,359
Speaker 1: a collaring study being launched on the Chewgatch Mountain goat

456
00:25:48,400 --> 00:25:51,240
Speaker 1: population by the Palmer Fish and Game Office and will

457
00:25:51,280 --> 00:25:54,800
Speaker 1: also be used to support the organization's endowment fund. So

458
00:25:55,000 --> 00:25:59,639
Speaker 1: this organization, the Outdoor Heritage Foundation of Alaska, is raising

459
00:25:59,720 --> 00:26:04,440
Speaker 1: money with a mountain goat draw that they will turn

460
00:26:04,480 --> 00:26:09,639
Speaker 1: around and use to do research on that population of

461
00:26:09,680 --> 00:26:12,520
Speaker 1: mountain goats by going in and funding a collaring study

462
00:26:12,520 --> 00:26:16,800
Speaker 1: by Palmer Fishing Game. Now, of the many things I

463
00:26:16,920 --> 00:26:21,159
Speaker 1: enjoy following in life, I like following fir markets, and

464
00:26:21,240 --> 00:26:25,600
Speaker 1: I love following collaring studies. Looking at a map with

465
00:26:25,680 --> 00:26:28,240
Speaker 1: all the blips of where stuff goes. I like the

466
00:26:28,280 --> 00:26:30,720
Speaker 1: normal stuff animals do wearing a collar, and I like

467
00:26:30,760 --> 00:26:33,920
Speaker 1: the weird stuff animals do wearing a collar. Love coloring studies.

468
00:26:33,920 --> 00:26:37,040
Speaker 1: They're very enlightening about how things use habitat. Another great

469
00:26:37,040 --> 00:26:40,639
Speaker 1: thing about coloring studies is once you know how a population,

470
00:26:41,080 --> 00:26:43,600
Speaker 1: so it's a native population of mountain goats, once you

471
00:26:43,800 --> 00:26:47,560
Speaker 1: know how that population of mountain goats uses the landscape,

472
00:26:47,960 --> 00:26:52,760
Speaker 1: conservation efforts can be much more focused. Right. You might say, hey,

473
00:26:53,080 --> 00:26:55,800
Speaker 1: if we're going to protect habitats or do habitat work,

474
00:26:57,000 --> 00:26:59,119
Speaker 1: like where do these things actually go and what do

475
00:26:59,200 --> 00:27:01,000
Speaker 1: they use? And it helps you'd be very targeted in

476
00:27:01,040 --> 00:27:05,200
Speaker 1: conservation efforts, so collering studies are great. Both the bison

477
00:27:05,240 --> 00:27:08,439
Speaker 1: and the goat raffles are live. Now to back up

478
00:27:08,480 --> 00:27:12,760
Speaker 1: to this goat deal. For the goat tag, if you're

479
00:27:12,800 --> 00:27:15,639
Speaker 1: a not this is open to non residents. And the

480
00:27:15,720 --> 00:27:20,520
Speaker 1: catch here is unless you have a relative in Alaska,

481
00:27:21,520 --> 00:27:23,879
Speaker 1: and if you're a non resident of if you're an

482
00:27:23,920 --> 00:27:26,919
Speaker 1: Alaska non residence, so you don't live in Alaska, the

483
00:27:26,960 --> 00:27:29,439
Speaker 1: only way you can go hunt goats is if you

484
00:27:29,560 --> 00:27:32,439
Speaker 1: have a relative in Alaska, and you can hunt goats

485
00:27:32,440 --> 00:27:35,439
Speaker 1: with that person. Oh ornette, you got to hire a guide.

486
00:27:35,760 --> 00:27:38,560
Speaker 1: So when you draw this tag, the win. It's a

487
00:27:38,640 --> 00:27:42,840
Speaker 1: guided trip with the travel stipend to get you up there.

488
00:27:43,359 --> 00:27:46,320
Speaker 1: This is all expense paid goat tag. When I draw it,

489
00:27:47,520 --> 00:27:52,399
Speaker 1: I won't need those services because I'm already familiar with

490
00:27:52,400 --> 00:27:54,440
Speaker 1: the area. Oh ho, my brother, I don't need the

491
00:27:54,480 --> 00:27:58,320
Speaker 1: services for this. So what you're saying, I apply for

492
00:27:58,400 --> 00:28:00,880
Speaker 1: this tag. Here's the catch. Here's here's the weird part.

493
00:28:01,480 --> 00:28:07,760
Speaker 1: I apply for this tag every year every year.

494
00:28:08,200 --> 00:28:12,840
Speaker 7: Here's the crazy thing. These websites actually tell you how

495
00:28:12,880 --> 00:28:17,360
Speaker 7: many tickets have been sold, so you can look at

496
00:28:17,359 --> 00:28:20,680
Speaker 7: one of your chances. Is that right, now only two

497
00:28:20,720 --> 00:28:22,760
Speaker 7: hundred and fifty eight tickets for the goat.

498
00:28:22,880 --> 00:28:24,879
Speaker 1: What dude, I'm in the mix.

499
00:28:25,560 --> 00:28:27,000
Speaker 2: I'm in the mix for now.

500
00:28:27,760 --> 00:28:30,400
Speaker 1: I'm in the mix. I bought seventy I bought four

501
00:28:30,520 --> 00:28:32,119
Speaker 1: for seventy five. I'm going to get back in there.

502
00:28:33,760 --> 00:28:37,120
Speaker 1: I'm getting I was just getting, like, I just made

503
00:28:37,119 --> 00:28:41,880
Speaker 1: an opening offer with my seventy five dollars.

504
00:28:42,400 --> 00:28:44,200
Speaker 9: You can just tell them you don't need a guide.

505
00:28:44,200 --> 00:28:45,560
Speaker 9: You're like, I don't need that part.

506
00:28:45,560 --> 00:28:47,760
Speaker 1: I'm gonna put the money. I'm going to donate it back.

507
00:28:48,160 --> 00:28:50,720
Speaker 1: I'm gonna donate it back to the org. Gotcha. I

508
00:28:50,720 --> 00:28:53,080
Speaker 1: won't need it. I don't need the guide. Yeah, I'm

509
00:28:53,120 --> 00:28:55,440
Speaker 1: already in it. I'm already in the state draw.

510
00:28:55,560 --> 00:28:59,520
Speaker 9: Anyway, you're almost you're basically already hunting that goat.

511
00:28:59,720 --> 00:29:04,760
Speaker 1: Yeah, you're so close. So how do people find this

512
00:29:04,800 --> 00:29:08,120
Speaker 1: if you want to participate? Well, oh, the Delta Junction

513
00:29:08,240 --> 00:29:12,360
Speaker 1: Bison ticket package is like of the hunts in Alaska.

514
00:29:12,880 --> 00:29:17,120
Speaker 1: There's Delta Junction, the Chittner Herd, the Farewell Burn Herd,

515
00:29:17,200 --> 00:29:20,880
Speaker 1: the Copper River Herd. The Delta Herd is the like

516
00:29:21,160 --> 00:29:27,200
Speaker 1: road accessible. It's it's a very achievable hunt. They do

517
00:29:27,240 --> 00:29:30,080
Speaker 1: some there's some farming. Oddly, you know, there's not much

518
00:29:30,120 --> 00:29:34,080
Speaker 1: farming in Alaska. Obviously, there's some agricultural production around Delta Junction.

519
00:29:34,560 --> 00:29:36,400
Speaker 1: So a lot of these guys that have these ag

520
00:29:36,440 --> 00:29:39,760
Speaker 1: fields they charge a small trespass fee. It's like, if

521
00:29:39,760 --> 00:29:43,040
Speaker 1: you want to go hunt a really wild, free ranging

522
00:29:45,720 --> 00:29:48,680
Speaker 1: bison population that has buffalo that are able to move

523
00:29:48,720 --> 00:29:52,760
Speaker 1: across jurisdictions, and they're just like wild free roaming animals

524
00:29:52,800 --> 00:29:55,680
Speaker 1: managed as a big game species. This is a This

525
00:29:55,760 --> 00:29:59,000
Speaker 1: is an accessible hunt for people that don't know the

526
00:29:59,040 --> 00:30:01,200
Speaker 1: ins and outs of a LAS. You don't need to

527
00:30:01,200 --> 00:30:03,560
Speaker 1: be like a logistics wizard to pull off a Delta

528
00:30:03,640 --> 00:30:08,160
Speaker 1: Junction hunt. So we're forty tickets for five hundred bucks.

529
00:30:08,280 --> 00:30:12,160
Speaker 1: One ticket for twenty five bucks, goat fourteen for two

530
00:30:12,280 --> 00:30:16,480
Speaker 1: hundred all expense paid, four for seventy five. God that

531
00:30:16,560 --> 00:30:18,360
Speaker 1: makes me I just need I'm getting in there heavy

532
00:30:18,440 --> 00:30:21,640
Speaker 1: duty now. Yeah, keep bleep all that out, Phil, We'll

533
00:30:21,680 --> 00:30:22,960
Speaker 1: do so.

534
00:30:23,400 --> 00:30:26,920
Speaker 7: Uh. For the goat raffle, you have until March sixth,

535
00:30:27,120 --> 00:30:29,720
Speaker 7: The drawing is going to be the next day. For

536
00:30:29,800 --> 00:30:32,880
Speaker 7: the bison raffle, you have until the fourteenth. The drawing

537
00:30:33,440 --> 00:30:36,040
Speaker 7: is going to be on March fifteenth, and if you

538
00:30:36,160 --> 00:30:42,440
Speaker 7: go to the Outdoor Heritage Foundation of Alaska's website o

539
00:30:43,400 --> 00:30:51,160
Speaker 7: h FA k dot org forward slash raffles plural, you

540
00:30:51,240 --> 00:30:55,240
Speaker 7: will find links to purchase tickets.

541
00:30:55,440 --> 00:31:02,360
Speaker 1: Okay, don't buy, buy the bison ones. Moving on, we

542
00:31:02,440 --> 00:31:04,760
Speaker 1: got an email called a desperate plea. Advice needed now,

543
00:31:04,840 --> 00:31:06,280
Speaker 1: and I'll stay tu because we're gonna get to the

544
00:31:06,280 --> 00:31:09,800
Speaker 1: hard hitting We're gonna get to the hard hitting political,

545
00:31:09,960 --> 00:31:13,000
Speaker 1: politically devisive stuff down the road. Whenmber I was talking

546
00:31:13,000 --> 00:31:15,400
Speaker 1: about wolves and like the wrath of the Trump administration,

547
00:31:15,480 --> 00:31:20,480
Speaker 1: that's all coming. But first, a desperate plea. Dear Stephen Krewe,

548
00:31:20,640 --> 00:31:25,560
Speaker 1: this is someone writing in for help. Let me let

549
00:31:25,560 --> 00:31:27,520
Speaker 1: me begin by saying I love my wife and kids

550
00:31:27,600 --> 00:31:28,040
Speaker 1: very much.

551
00:31:28,280 --> 00:31:31,200
Speaker 2: That's always a great setup, but hey.

552
00:31:31,000 --> 00:31:34,440
Speaker 1: Some guys don't. Now. If he wrote in, say, let

553
00:31:34,480 --> 00:31:37,000
Speaker 1: me begin by saying I don't love my wife and kids.

554
00:31:37,160 --> 00:31:38,680
Speaker 2: Yeah, changes the heart.

555
00:31:38,680 --> 00:31:39,840
Speaker 1: I wouldn't cover the story.

556
00:31:40,080 --> 00:31:42,160
Speaker 7: Yeah, I wouldn't have put it in there, so I

557
00:31:42,160 --> 00:31:42,840
Speaker 7: would have read it.

558
00:31:42,880 --> 00:31:45,000
Speaker 2: He wouldn't have a problem if if he.

559
00:31:45,040 --> 00:31:46,880
Speaker 1: Was true, he wouldn't even have this problem.

560
00:31:47,000 --> 00:31:52,000
Speaker 5: Very titillating to start off a story with that, though, yeah, yeah, and.

561
00:31:52,200 --> 00:31:54,680
Speaker 1: You couldn't, he said, I don't love my wife. I

562
00:31:54,680 --> 00:31:57,840
Speaker 1: would have read, but I would never cover it. Yeah,

563
00:31:57,960 --> 00:32:00,560
Speaker 1: because I wouldn't be able to support that. He says,

564
00:32:00,560 --> 00:32:03,280
Speaker 1: I also love trapping. As you may or may not know,

565
00:32:03,360 --> 00:32:06,160
Speaker 1: skunk prices are pretty good this year. We know it well, buddy.

566
00:32:06,320 --> 00:32:09,520
Speaker 1: In fact, we covered it at on media or radio live.

567
00:32:10,880 --> 00:32:12,960
Speaker 1: With the fur market being down the past few years,

568
00:32:13,000 --> 00:32:15,440
Speaker 1: I was excited to see that skunks are averaging twenty

569
00:32:15,520 --> 00:32:19,920
Speaker 1: to thirty bucks in Oklahoma. Jeez, they were even higher.

570
00:32:20,280 --> 00:32:24,960
Speaker 1: Like here, sorry, it's a dog in the studio, excuse me,

571
00:32:26,880 --> 00:32:29,480
Speaker 1: they were even higher. This happened like a couple years ago.

572
00:32:29,480 --> 00:32:33,040
Speaker 1: There's like that spike in beaver. Prices for cowboy hats

573
00:32:33,680 --> 00:32:36,120
Speaker 1: and dudes got so hard after Beaver's it's just like

574
00:32:36,680 --> 00:32:39,320
Speaker 1: they dropped. And in the skunk, I don't think the

575
00:32:39,360 --> 00:32:43,520
Speaker 1: skunk is like, I don't know that the skunk explosion

576
00:32:43,880 --> 00:32:47,080
Speaker 1: is gonna hold up, so I think it's already dipping

577
00:32:47,120 --> 00:32:49,640
Speaker 1: from harvest. A lot of guys catching a lot of skunks. Anyways,

578
00:32:49,640 --> 00:32:52,320
Speaker 1: twenty to thirty bucks in Oklahoma. That being back to

579
00:32:52,360 --> 00:32:54,560
Speaker 1: the letter that being said, my son and I have

580
00:32:54,600 --> 00:32:58,280
Speaker 1: started to target skunks more than usual. He says, Now,

581
00:32:58,280 --> 00:33:01,640
Speaker 1: I am no Jared Maya Johnson, but we're looking at

582
00:33:01,680 --> 00:33:04,600
Speaker 1: a nice little payday with all the skunks we've been catching.

583
00:33:06,280 --> 00:33:07,640
Speaker 1: I don't understand that reference.

584
00:33:08,320 --> 00:33:09,240
Speaker 2: He's doing pretty good.

585
00:33:09,680 --> 00:33:13,200
Speaker 1: He's really not, because there's no part of Jeremiah Johnson

586
00:33:13,200 --> 00:33:16,160
Speaker 1: where he's excelling at any sort of for harvesting.

587
00:33:16,760 --> 00:33:22,240
Speaker 5: As Jeremiah Johnson. He feels like he's a great trapper Jeremiah,

588
00:33:22,280 --> 00:33:26,400
Speaker 5: and that he himself is not comparable to a great trapper.

589
00:33:26,600 --> 00:33:28,600
Speaker 5: That maybe Jeremiah he's still doing well.

590
00:33:28,880 --> 00:33:31,400
Speaker 1: If he said no, I'm no Craig O'Gorman.

591
00:33:33,120 --> 00:33:35,000
Speaker 5: That would make sense to three people.

592
00:33:35,120 --> 00:33:44,560
Speaker 1: Or I'm no Slim Peterson, I'm no Hawbaker, I'm no

593
00:33:44,680 --> 00:33:50,200
Speaker 1: Mercer long Seth Morrison, I'm no John Graham. Sure, I'm

594
00:33:50,200 --> 00:33:57,880
Speaker 1: no Jeremiah Johnson. But to go on, he's no Jeremiah Johnson,

595
00:33:57,880 --> 00:33:59,600
Speaker 1: but he's looking at a nice little payday with all

596
00:33:59,600 --> 00:34:02,520
Speaker 1: the skunk he's been catching. Well. I came home last

597
00:34:02,600 --> 00:34:04,640
Speaker 1: night and sat on the couch after a good trap

598
00:34:04,720 --> 00:34:08,440
Speaker 1: line checking. My wife broke down in tears and proceeded

599
00:34:08,440 --> 00:34:12,640
Speaker 1: to tell me she can't live like this. Anymore, Buddy,

600
00:34:12,719 --> 00:34:19,560
Speaker 1: I have gotten the same notes. She then says she's

601
00:34:19,640 --> 00:34:22,760
Speaker 1: tired of my truck and the garage smelling like a skunk.

602
00:34:24,239 --> 00:34:26,239
Speaker 1: He says, I didn't get spray, so it's not that bad.

603
00:34:27,360 --> 00:34:29,239
Speaker 1: But she can just get a little whiff of it

604
00:34:29,320 --> 00:34:29,799
Speaker 1: here and there.

605
00:34:30,080 --> 00:34:31,440
Speaker 2: I bet it's probably worth.

606
00:34:33,000 --> 00:34:33,280
Speaker 6: Terrible.

607
00:34:33,360 --> 00:34:35,880
Speaker 1: Let me tell you something, buddy, Let me finish up.

608
00:34:37,239 --> 00:34:39,719
Speaker 1: He goes on, I am in a predicament. I love

609
00:34:39,800 --> 00:34:41,880
Speaker 1: my wife, but I'm not about to sell all my

610
00:34:41,960 --> 00:34:44,680
Speaker 1: trap and stuff and sign my son up for piano lessons.

611
00:34:44,719 --> 00:34:47,759
Speaker 1: What should I do? Is there a happy medium in

612
00:34:47,840 --> 00:34:52,439
Speaker 1: my situation? Ps? If y'all need a new turkey spot

613
00:34:52,480 --> 00:34:58,200
Speaker 1: in Oklahoma, I'd love to take you out Bryce from Oklahoma. Here.

614
00:34:58,680 --> 00:35:02,920
Speaker 1: That odor is one of the those odors. Let me

615
00:35:02,960 --> 00:35:04,680
Speaker 1: put to you this way. My dad always like to

616
00:35:04,680 --> 00:35:07,279
Speaker 1: tell story. When he was a little boy, he lived

617
00:35:07,280 --> 00:35:13,719
Speaker 1: by a foundry an all day long. Don't from the foundry.

618
00:35:14,480 --> 00:35:17,000
Speaker 1: People would say, they'd come to his neighborhood and people go,

619
00:35:17,080 --> 00:35:21,440
Speaker 1: what is that noise, to which people in the neighborhood go,

620
00:35:21,560 --> 00:35:27,799
Speaker 1: what noise? Mhmm, right, You, my friend, might be acclimated.

621
00:35:28,280 --> 00:35:31,240
Speaker 1: You might be getting acclimated to the skunk smelly?

622
00:35:32,520 --> 00:35:35,080
Speaker 7: Am I the only person and I have I'm not

623
00:35:35,280 --> 00:35:39,320
Speaker 7: in a household where skunks get trapped. If I drive

624
00:35:39,520 --> 00:35:43,080
Speaker 7: by it, I just never you know, pleas I never

625
00:35:43,200 --> 00:35:48,680
Speaker 7: think it's bad. It doesn't.

626
00:35:48,800 --> 00:35:49,520
Speaker 1: It doesn't.

627
00:35:50,719 --> 00:35:57,919
Speaker 3: By proximity road kills skunk is nothing but run over

628
00:35:58,000 --> 00:35:59,840
Speaker 3: a road kills skunk and get a little bit of

629
00:35:59,840 --> 00:36:02,680
Speaker 3: it stuck up under your vehicle and it just stays

630
00:36:02,719 --> 00:36:03,959
Speaker 3: there for two weeks.

631
00:36:04,360 --> 00:36:07,840
Speaker 7: But it doesn't smell like it doesn't smell rotten like

632
00:36:07,920 --> 00:36:10,839
Speaker 7: things that would turn me off. Is like something that's

633
00:36:10,880 --> 00:36:11,800
Speaker 7: like rotting.

634
00:36:12,239 --> 00:36:14,040
Speaker 4: I had my cat come home at two in the

635
00:36:14,080 --> 00:36:18,480
Speaker 4: morning drenched in skunk, and that completely altered my brain,

636
00:36:18,560 --> 00:36:20,480
Speaker 4: which rewired, and I hate I can't do it now

637
00:36:20,480 --> 00:36:22,160
Speaker 4: because my heart house smelled like it for a week.

638
00:36:22,280 --> 00:36:25,600
Speaker 9: This thing is it can like make something smell just

639
00:36:25,640 --> 00:36:31,120
Speaker 9: by being near. It goes the air and coats. Like

640
00:36:31,760 --> 00:36:34,120
Speaker 9: remember we were in that you were we were out

641
00:36:34,160 --> 00:36:37,000
Speaker 9: at Jake's place and you were skinning that skunk and

642
00:36:37,080 --> 00:36:39,640
Speaker 9: we had a couple of beaver thighs sitting like ten

643
00:36:39,680 --> 00:36:44,280
Speaker 9: feet away to eat, oh nowhere near, and you couldn't

644
00:36:44,320 --> 00:36:44,640
Speaker 9: eat those.

645
00:36:45,440 --> 00:36:49,600
Speaker 1: Yeah, years ago, Remember we auctioned off in the auction

646
00:36:49,680 --> 00:36:51,960
Speaker 1: house of bodies, that bottle of genuine skunk.

647
00:36:52,040 --> 00:36:53,080
Speaker 7: Yeah, since I do.

648
00:36:53,239 --> 00:36:56,680
Speaker 1: So. We were extracting that with hypodermic needles. You buy

649
00:36:56,680 --> 00:37:04,280
Speaker 1: it murdocks like hard like large boarder cattle injectors. Ye. Well,

650
00:37:04,400 --> 00:37:11,080
Speaker 1: we were like surgical about doing it, and all I did.

651
00:37:11,320 --> 00:37:13,280
Speaker 1: I didn't want to throw my hyperdermic needle.

652
00:37:13,040 --> 00:37:16,839
Speaker 7: Out, so you washed it and kept it.

653
00:37:17,000 --> 00:37:20,920
Speaker 1: No, I didn't. There was the one oversight. So I

654
00:37:20,960 --> 00:37:24,840
Speaker 1: had the hypodermic needle in my garage and my wife

655
00:37:24,880 --> 00:37:28,040
Speaker 1: is having a shit fit about the skunk smell in

656
00:37:28,080 --> 00:37:30,879
Speaker 1: her car on everything. I had a whole embarrassing thing

657
00:37:30,920 --> 00:37:38,479
Speaker 1: happened at the barber shop. So I'm like, Katie, there

658
00:37:38,680 --> 00:37:44,799
Speaker 1: is no nothing in that garage. It's just like a

659
00:37:44,840 --> 00:37:48,640
Speaker 1: residual smell that'll dissipate. But it wouldn't. And I eventually

660
00:37:48,640 --> 00:37:55,000
Speaker 1: realized that hypodermic needle. So she's probably right. You're probably

661
00:37:55,080 --> 00:37:59,920
Speaker 1: wrong if you had a way to take your whole,

662
00:38:00,000 --> 00:38:04,120
Speaker 1: well all aspects of your skunk operation to an outbuilding.

663
00:38:04,480 --> 00:38:06,920
Speaker 9: He needs a skin and shed, Yeah, just build a shed.

664
00:38:06,800 --> 00:38:09,480
Speaker 1: Or but you might not have that. You might not

665
00:38:09,560 --> 00:38:14,040
Speaker 1: have that luxury It might just have to be the

666
00:38:14,160 --> 00:38:21,239
Speaker 1: you teller. Trapping season don't last all year, I don't know,

667
00:38:21,640 --> 00:38:26,759
Speaker 1: Or you take the whole entire operation and they don't

668
00:38:26,800 --> 00:38:31,000
Speaker 1: park your truck in the garage, the entire operation. When

669
00:38:31,000 --> 00:38:33,239
Speaker 1: you walk out of your shed, you walk out of

670
00:38:33,239 --> 00:38:35,239
Speaker 1: your shed in your underwear.

671
00:38:35,560 --> 00:38:37,240
Speaker 2: Yeah, she's already in tears.

672
00:38:37,480 --> 00:38:40,480
Speaker 3: So I think, I don't know if the trapping season

673
00:38:40,520 --> 00:38:41,879
Speaker 3: is only part of the year is going to work.

674
00:38:41,920 --> 00:38:43,680
Speaker 3: I think I think he needs to start looking at

675
00:38:43,719 --> 00:38:47,959
Speaker 3: the shed, looking at the naked the more dramatic step here.

676
00:38:47,960 --> 00:38:48,640
Speaker 2: But he might not.

677
00:38:48,920 --> 00:38:52,640
Speaker 1: My story about the hyper dermot needle is being you

678
00:38:52,840 --> 00:39:05,239
Speaker 1: have to take entire operation boots, gloves, hat, clothes, truck, backpack.

679
00:39:06,400 --> 00:39:10,640
Speaker 1: The entire operation has to move to where you When

680
00:39:10,680 --> 00:39:13,840
Speaker 1: you walk away from skunk Land, you walk away in

681
00:39:13,880 --> 00:39:14,680
Speaker 1: your underwear.

682
00:39:15,000 --> 00:39:17,520
Speaker 9: To be fair, you love your wife and kids very much,

683
00:39:17,600 --> 00:39:19,920
Speaker 9: but you haven't moved your operation off site.

684
00:39:21,280 --> 00:39:23,239
Speaker 1: Yeah, but I'm not doing twenty skunks.

685
00:39:23,560 --> 00:39:23,920
Speaker 2: True.

686
00:39:24,040 --> 00:39:28,560
Speaker 1: I'm good for like a skunk, I mean a skunk now,

687
00:39:28,600 --> 00:39:29,120
Speaker 1: and then.

688
00:39:29,360 --> 00:39:35,120
Speaker 9: A handful of like you know, this guy, might you know,

689
00:39:35,239 --> 00:39:36,520
Speaker 9: be a little more thoughtful than you.

690
00:39:36,600 --> 00:39:39,000
Speaker 1: I don't know. She is crying.

691
00:39:41,360 --> 00:39:43,960
Speaker 5: I think he's a little bit hard on the piano lessons.

692
00:39:44,320 --> 00:39:46,680
Speaker 5: I think there's a lot of value in piano lessons.

693
00:39:47,160 --> 00:39:48,880
Speaker 1: He's making a point, but yeah.

694
00:39:51,120 --> 00:39:56,000
Speaker 5: Point. You know, I'm just saying, maybe he could use

695
00:39:56,040 --> 00:40:00,359
Speaker 5: his proceeds pay for some piano lessons and say, look

696
00:40:00,400 --> 00:40:01,440
Speaker 5: what the kids getting out of it?

697
00:40:01,480 --> 00:40:03,879
Speaker 9: As long as that kid hasn't been handling a skunk.

698
00:40:04,000 --> 00:40:04,840
Speaker 1: He's got the kid.

699
00:40:05,600 --> 00:40:09,200
Speaker 5: Skunks are black and white, pianos are black and white.

700
00:40:11,120 --> 00:40:13,520
Speaker 1: Good point, man, it all goes together. Yeah, I think

701
00:40:13,520 --> 00:40:15,200
Speaker 1: he was making a point. I don't. I don't think

702
00:40:15,280 --> 00:40:18,319
Speaker 1: skunk trapping and piano plant are totally incompatible. But I

703
00:40:18,360 --> 00:40:21,960
Speaker 1: think that you would find you would find that there

704
00:40:22,040 --> 00:40:25,640
Speaker 1: is an inverse correlation to prowess on the piano and

705
00:40:25,719 --> 00:40:27,839
Speaker 1: prowess as a skunk trapper. I think that you would

706
00:40:27,840 --> 00:40:28,279
Speaker 1: find that.

707
00:40:29,600 --> 00:40:31,960
Speaker 5: Does Dale Brisbye know about these high skunk traps?

708
00:40:32,000 --> 00:40:33,440
Speaker 1: I told them about it, and he said, I'm not

709
00:40:33,520 --> 00:40:38,799
Speaker 1: that broke. I didn't want to take it up with him.

710
00:40:38,800 --> 00:40:40,120
Speaker 1: I don't want to argue about it. I thought he

711
00:40:40,160 --> 00:40:43,080
Speaker 1: was wrong. Here's some news from Massachusetts. This is fascinating

712
00:40:44,719 --> 00:40:49,759
Speaker 1: something I hadn't really thought about. Well, I have thought

713
00:40:49,760 --> 00:40:52,640
Speaker 1: about it. Listeners will know that in the past I

714
00:40:52,719 --> 00:40:56,640
Speaker 1: had it was it remains unresolved. Unsolved. There's an unsolved

715
00:40:56,680 --> 00:40:59,320
Speaker 1: mystery where I there was a fish heist in our office,

716
00:41:00,080 --> 00:41:02,799
Speaker 1: know how it's still it was in our last office. Yeah,

717
00:41:03,480 --> 00:41:06,160
Speaker 1: there was a major fish heist in our last office

718
00:41:06,400 --> 00:41:10,560
Speaker 1: and it was never solved. Someone stole a small fortune's

719
00:41:10,560 --> 00:41:16,759
Speaker 1: worth of seafood and we never called them, never caught them.

720
00:41:16,840 --> 00:41:17,640
Speaker 1: But check this out.

721
00:41:18,120 --> 00:41:20,040
Speaker 5: I thought I was allowed to take that stuff.

722
00:41:22,040 --> 00:41:26,880
Speaker 1: There have been these like high profile, like organized crime level.

723
00:41:27,000 --> 00:41:31,280
Speaker 1: So this is a story reported in Forbes from Massachusetts,

724
00:41:32,800 --> 00:41:39,360
Speaker 1: these like well organized, high profile thefts of massive amounts

725
00:41:39,360 --> 00:41:42,920
Speaker 1: of seafood, and the gist of the article saying, when

726
00:41:42,920 --> 00:41:50,120
Speaker 1: you like these aren't these aren't things with barcodes and

727
00:41:50,239 --> 00:41:51,160
Speaker 1: serial numbers.

728
00:41:51,640 --> 00:41:52,759
Speaker 5: That's the reason they like them.

729
00:41:53,000 --> 00:41:57,080
Speaker 1: Yeah, so it's like you're stealing lobster. So like unmarked,

730
00:41:57,120 --> 00:42:01,960
Speaker 1: like completely unmarked stuff. That's very easy. See it's something

731
00:42:01,960 --> 00:42:04,160
Speaker 1: I never thought of. Like a big load of seafood

732
00:42:04,280 --> 00:42:09,799
Speaker 1: on a truck is very hard to track. Yeah, it's

733
00:42:09,880 --> 00:42:12,839
Speaker 1: it's hard to track, and it's easy to move. It's

734
00:42:12,840 --> 00:42:15,400
Speaker 1: easy to move. They got these guys that just stole

735
00:42:16,480 --> 00:42:25,400
Speaker 1: forty thousand like hear me out forty thousand pounds of

736
00:42:25,520 --> 00:42:30,839
Speaker 1: lobster meat from a warehouse in Massachusetts, estimated to be

737
00:42:31,239 --> 00:42:36,840
Speaker 1: worth four hundred thousand dollars. The lobster was supposed to

738
00:42:36,880 --> 00:42:40,440
Speaker 1: go to costcos in Illinois and Minnesota.

739
00:42:40,920 --> 00:42:43,520
Speaker 5: You think that's like king crab legs in the show,

740
00:42:43,760 --> 00:42:47,040
Speaker 5: or do you think it's lobster? But then they're sorry lobster.

741
00:42:47,360 --> 00:42:49,719
Speaker 1: So I keep seeing lobster meat, I feel like it

742
00:42:49,800 --> 00:42:52,240
Speaker 1: must be tail. Would you picture going to a cost

743
00:42:52,280 --> 00:42:53,440
Speaker 1: co and finding tails?

744
00:42:54,400 --> 00:42:54,800
Speaker 5: Tails?

745
00:42:54,960 --> 00:42:57,000
Speaker 9: Sometimes it's not picked.

746
00:42:58,200 --> 00:43:00,960
Speaker 7: They're not like the main lobster tails.

747
00:43:01,080 --> 00:43:05,560
Speaker 1: They're the no, these aren't rotic lives or tails, spine,

748
00:43:05,600 --> 00:43:09,680
Speaker 1: the spiny lobster tails. Yeah, when it keeps pointing out meat,

749
00:43:09,800 --> 00:43:14,120
Speaker 1: I'm assuming they're not moving live lobster, but maybe like tails.

750
00:43:14,760 --> 00:43:17,480
Speaker 1: And they're like they're at the time it is reporting,

751
00:43:17,520 --> 00:43:19,840
Speaker 1: they're pointing out that it's already gone on the black.

752
00:43:19,640 --> 00:43:23,879
Speaker 3: Market for half price, which that's what my takeaway, Yeah,

753
00:43:24,120 --> 00:43:25,440
Speaker 3: getting more black market lobster.

754
00:43:25,440 --> 00:43:28,720
Speaker 1: They probably these thieves probably moved at two hundred thousand dollars.

755
00:43:28,960 --> 00:43:31,840
Speaker 1: But this guy goes on to say that you're probably

756
00:43:31,880 --> 00:43:34,680
Speaker 1: seeing or you're probably seeing and when you hear about

757
00:43:34,719 --> 00:43:38,000
Speaker 1: how this stuff goes on. This analyst here is saying,

758
00:43:38,040 --> 00:43:45,720
Speaker 1: you're seeing old school organized crime intersecting with cybercrime. These

759
00:43:45,760 --> 00:43:54,640
Speaker 1: guys basically not basically, these criminals impersonated a legitimate trucking company. Okay,

760
00:43:55,640 --> 00:44:00,880
Speaker 1: they go to a warehouse with a truck, it's labeled

761
00:44:01,160 --> 00:44:05,000
Speaker 1: and everything, and they know about the they know about

762
00:44:05,040 --> 00:44:08,360
Speaker 1: the lobster being there, they know about the shipment happening.

763
00:44:09,080 --> 00:44:11,640
Speaker 1: They pose as the legitimate shipper.

764
00:44:11,880 --> 00:44:16,439
Speaker 9: Well, they like it's like identity theft, Like they get

765
00:44:16,480 --> 00:44:19,040
Speaker 9: the account numbers and all the information.

766
00:44:19,239 --> 00:44:21,920
Speaker 7: It's both like physical on the trucks, and then like

767
00:44:21,960 --> 00:44:24,680
Speaker 7: on the back end with the communications.

768
00:44:23,960 --> 00:44:26,040
Speaker 2: They've hacked all the delivery information.

769
00:44:26,239 --> 00:44:31,680
Speaker 1: They have a fraudulent load listing. And then they got

770
00:44:31,680 --> 00:44:34,640
Speaker 1: their guy comes in, they got dispatchers.

771
00:44:34,080 --> 00:44:36,760
Speaker 7: Right, very sophisticated stuff.

772
00:44:37,560 --> 00:44:39,920
Speaker 3: And then they drive off and they drive off and

773
00:44:39,960 --> 00:44:43,080
Speaker 3: then the actual truck shows up looking for the lobster

774
00:44:43,200 --> 00:44:44,239
Speaker 3: that they already took off.

775
00:44:44,400 --> 00:44:45,440
Speaker 1: That's a good part of the movie.

776
00:44:45,600 --> 00:44:47,520
Speaker 2: Yeah, it's a great part of the movie.

777
00:44:48,400 --> 00:44:50,759
Speaker 5: It's just two hundred thousand.

778
00:44:51,960 --> 00:44:54,400
Speaker 1: Seems like, I know, it's like it's too risky for that.

779
00:44:54,440 --> 00:44:57,000
Speaker 5: Right, it seems like, is it enough, I would say

780
00:44:57,040 --> 00:44:59,040
Speaker 5: if you were telling me, oh, well, they've done it

781
00:44:59,160 --> 00:45:02,160
Speaker 5: hundreds of times over which later we learned that there

782
00:45:02,239 --> 00:45:05,080
Speaker 5: was a crab that I think, what did you say annually?

783
00:45:07,360 --> 00:45:10,800
Speaker 5: What was the number annually? It was in the billions,

784
00:45:11,480 --> 00:45:11,839
Speaker 5: wasn't it.

785
00:45:12,960 --> 00:45:15,000
Speaker 9: Yeah, And they could be involved with all kinds. They

786
00:45:15,000 --> 00:45:18,839
Speaker 9: could be picking up televisions and computers, and they could

787
00:45:18,880 --> 00:45:20,760
Speaker 9: be doing this with all different kinds of stuff.

788
00:45:20,800 --> 00:45:23,400
Speaker 1: But this this being reported, like, this is going to

789
00:45:23,440 --> 00:45:25,879
Speaker 1: make their lives more difficult. But yeah, there's been other

790
00:45:25,960 --> 00:45:29,040
Speaker 1: seafood heightsts. Yeah, but the part of it, I mean,

791
00:45:29,080 --> 00:45:31,040
Speaker 1: it's all interesting. The part of it was interesting to

792
00:45:31,040 --> 00:45:33,319
Speaker 1: me is that you're just able to move huge that

793
00:45:33,360 --> 00:45:36,600
Speaker 1: you can just move black market huge quantities of seafood.

794
00:45:36,960 --> 00:45:38,879
Speaker 9: But if you said it, like you said, if it's

795
00:45:39,040 --> 00:45:42,480
Speaker 9: organized crime, they probably already have those connections, right, Like

796
00:45:42,760 --> 00:45:43,959
Speaker 9: they know they know how.

797
00:45:43,880 --> 00:45:46,160
Speaker 1: To move forty thousand pounds lot.

798
00:45:46,280 --> 00:45:47,360
Speaker 2: So this is all told.

799
00:45:48,280 --> 00:45:52,560
Speaker 3: Cargo theft is estimated to be a thirty five billion

800
00:45:52,640 --> 00:45:57,240
Speaker 3: dollar loss the National Insurance Crime Bureau. Yeah, that includes

801
00:45:57,680 --> 00:46:00,200
Speaker 3: that includes electronics, pharmaceutical.

802
00:45:59,600 --> 00:46:02,760
Speaker 1: But point about the net unless you're doing this, unless

803
00:46:02,760 --> 00:46:05,560
Speaker 1: they're just doing this all the time. If you imagine

804
00:46:05,560 --> 00:46:08,000
Speaker 1: that you're a one off criminal enterprise and you have

805
00:46:08,120 --> 00:46:11,160
Speaker 1: this where you got you got four people involved, six

806
00:46:11,200 --> 00:46:13,720
Speaker 1: people involved, and in the end you net two hundred

807
00:46:13,760 --> 00:46:15,000
Speaker 1: thousand bucks.

808
00:46:14,800 --> 00:46:18,239
Speaker 9: That's not even net, that's not your retirement plan.

809
00:46:18,520 --> 00:46:19,399
Speaker 1: Yeah, it's like.

810
00:46:21,160 --> 00:46:23,400
Speaker 7: It's so easy for them to do. I wonder how

811
00:46:23,480 --> 00:46:27,480
Speaker 7: much the crab heist was. And then there's other, you know,

812
00:46:27,640 --> 00:46:30,600
Speaker 7: seafood heist going on, so maybe they just have it.

813
00:46:30,520 --> 00:46:34,839
Speaker 5: And they can just quickly easy and is another big one.

814
00:46:35,040 --> 00:46:36,120
Speaker 5: I think we've even covered that.

815
00:46:36,160 --> 00:46:38,040
Speaker 1: Well, this has covered the glass eel deal.

816
00:46:38,760 --> 00:46:43,040
Speaker 3: This is how you get to the the classic film

817
00:46:43,120 --> 00:46:46,799
Speaker 3: trope of one last heist, because they need to do

818
00:46:46,920 --> 00:46:49,120
Speaker 3: one last heist so.

819
00:46:49,040 --> 00:46:51,200
Speaker 2: That they can finally ride off into the sunset.

820
00:46:52,080 --> 00:46:56,400
Speaker 3: So yeah, the forty pounds of lobster was good, but

821
00:46:56,480 --> 00:46:59,000
Speaker 3: if we can get another forty thousand pounds of lobster,

822
00:46:59,880 --> 00:47:00,399
Speaker 3: I'm not.

823
00:47:00,360 --> 00:47:01,240
Speaker 2: Doing this anymore.

824
00:47:01,360 --> 00:47:02,959
Speaker 1: Yeah exactly, you know, like.

825
00:47:02,880 --> 00:47:06,280
Speaker 2: The town I've paid these oceans films. Yeah, exactly.

826
00:47:09,640 --> 00:47:12,160
Speaker 1: Florida bear hunt results, harvest results. We've covered this a

827
00:47:12,160 --> 00:47:16,480
Speaker 1: whole bunch Florida a decade ago. This is we always

828
00:47:16,480 --> 00:47:18,840
Speaker 1: tell the stories. Was one of my favorite kind of

829
00:47:18,880 --> 00:47:23,520
Speaker 1: like I don't know wildlife policy stories of the last

830
00:47:24,280 --> 00:47:28,920
Speaker 1: decade or so is Florida ran a bear hunt a

831
00:47:28,960 --> 00:47:32,839
Speaker 1: decade ago and their first bear hunting forever, I can't

832
00:47:32,840 --> 00:47:35,239
Speaker 1: remember exactly how long, but their first hunt in decades,

833
00:47:35,840 --> 00:47:38,600
Speaker 1: they ran a bear hunt. When they put together the

834
00:47:38,600 --> 00:47:40,880
Speaker 1: bear hunt, they decided on a quota system, so it

835
00:47:40,920 --> 00:47:46,160
Speaker 1: was an open hunt with a cap and it's like

836
00:47:46,280 --> 00:47:48,880
Speaker 1: anyone with a license can go out and hunt bears.

837
00:47:48,960 --> 00:47:52,160
Speaker 1: And their plan was to shut the license, to shut

838
00:47:52,200 --> 00:47:55,440
Speaker 1: the hunt down at three hundred bears, I think is

839
00:47:55,440 --> 00:48:03,120
Speaker 1: what it was, and they within a couple of days

840
00:48:04,440 --> 00:48:06,359
Speaker 1: hit their quota. In some of the units, they hit

841
00:48:06,360 --> 00:48:09,239
Speaker 1: their quota right away. When they built it in, they

842
00:48:09,280 --> 00:48:12,080
Speaker 1: built in that there was a twenty four hour window,

843
00:48:12,239 --> 00:48:15,520
Speaker 1: so as they approached their bear quota, people have to

844
00:48:15,560 --> 00:48:17,399
Speaker 1: report the bear as soon as they kill it. As

845
00:48:17,400 --> 00:48:19,800
Speaker 1: they approached the bear quota, their plan was to shut

846
00:48:19,800 --> 00:48:22,440
Speaker 1: it down, but there was a twenty four hour window

847
00:48:22,480 --> 00:48:25,680
Speaker 1: to shut it down. During that twenty four hour period,

848
00:48:25,680 --> 00:48:29,560
Speaker 1: the hunters were killing so many bears in Florida that

849
00:48:29,680 --> 00:48:33,320
Speaker 1: during the twenty four hour shutdown period some units in Florida,

850
00:48:33,400 --> 00:48:39,840
Speaker 1: the bear harvest overshot the quota in a couple units,

851
00:48:41,239 --> 00:48:44,320
Speaker 1: and so in two days of this open hunt in Florida,

852
00:48:44,320 --> 00:48:47,280
Speaker 1: in a two day span, they killed three hundred bears,

853
00:48:47,680 --> 00:48:52,120
Speaker 1: all right, and the anti hunters, the animal rights folks,

854
00:48:52,200 --> 00:48:56,879
Speaker 1: had a conniption about this. They felt like, oh my god,

855
00:48:56,920 --> 00:48:59,280
Speaker 1: they botched the whole thing. They killed too many bears.

856
00:48:59,600 --> 00:49:03,120
Speaker 1: On the flotside, that was half of the reality. The

857
00:49:03,160 --> 00:49:07,120
Speaker 1: other half of the reality was people said, man, we

858
00:49:07,200 --> 00:49:09,200
Speaker 1: must have a lot of bears. Right. There's two ways

859
00:49:09,160 --> 00:49:11,080
Speaker 1: of looking at this whole story, but it was a

860
00:49:11,120 --> 00:49:14,520
Speaker 1: real black eye for Florida. Florida didn't do any bear

861
00:49:14,600 --> 00:49:17,400
Speaker 1: hunts now. They just did another bear hunt. And on

862
00:49:17,440 --> 00:49:20,160
Speaker 1: this bear hunt, they tried a new model. On this

863
00:49:20,200 --> 00:49:24,799
Speaker 1: bear hunt, they tried a tag draw model where they

864
00:49:24,840 --> 00:49:29,160
Speaker 1: did a lottery to give out a smaller handful of

865
00:49:29,600 --> 00:49:35,200
Speaker 1: bear tags. What happened, as we reported on previous shows,

866
00:49:35,400 --> 00:49:37,879
Speaker 1: what happened is the animal rights people all come in

867
00:49:38,760 --> 00:49:43,360
Speaker 1: and they start saying, Hey, we're gonna go apply for

868
00:49:43,440 --> 00:49:48,080
Speaker 1: bear tags and then not use them. So they're gonna

869
00:49:48,120 --> 00:49:50,480
Speaker 1: give out the requisite They're gonna give out the allotted

870
00:49:50,520 --> 00:49:54,279
Speaker 1: number of bear tags. Any you guys, They're gonna we're

871
00:49:54,280 --> 00:49:58,080
Speaker 1: gonna award one hundred and seventy two bear tags. And

872
00:49:58,120 --> 00:49:59,839
Speaker 1: the animal rights people are like, yeah, but we're gonna

873
00:49:59,880 --> 00:50:03,880
Speaker 1: get all those bear tags and not use them. Prior

874
00:50:03,920 --> 00:50:06,280
Speaker 1: to the hunt, the Fish and Wildlife Commission in Florida,

875
00:50:06,320 --> 00:50:10,160
Speaker 1: their basic attitude was, go ahead, buddy, because you're just

876
00:50:10,239 --> 00:50:15,080
Speaker 1: buying licenses and funding our agency by buying licenses. Next year,

877
00:50:15,760 --> 00:50:19,960
Speaker 1: we'll take the formula and we'll adjust if our objective

878
00:50:20,000 --> 00:50:22,160
Speaker 1: is to kill let's say whatever. Let's say their objective

879
00:50:22,200 --> 00:50:24,319
Speaker 1: is to kill a hundred bears. If you do your

880
00:50:24,360 --> 00:50:27,040
Speaker 1: little scheme and we give out a hunt, let's say

881
00:50:27,040 --> 00:50:30,279
Speaker 1: we gave out two hundred tags expecting to kill one

882
00:50:30,400 --> 00:50:33,640
Speaker 1: hundred bears, and we give out two hundred tags and

883
00:50:33,719 --> 00:50:37,040
Speaker 1: kill fifty bears, well guess what. Next year, we'll give

884
00:50:37,080 --> 00:50:40,439
Speaker 1: out four hundred tags and we're going to get it right.

885
00:50:40,560 --> 00:50:42,680
Speaker 1: Buy all the fake licenses you want. We thank you

886
00:50:42,719 --> 00:50:46,200
Speaker 1: for the money, was their attitude. Well, they did their hunt,

887
00:50:46,360 --> 00:50:50,000
Speaker 1: and lo and behold, they came in. They ran the

888
00:50:50,080 --> 00:50:55,120
Speaker 1: season from December sixth to December twenty eight. They had

889
00:50:55,160 --> 00:50:57,680
Speaker 1: a good hunt, but they came in below objective.

890
00:50:58,880 --> 00:51:02,799
Speaker 5: But oh, is that clear that it's that the objective

891
00:51:02,880 --> 00:51:04,600
Speaker 5: was to kill one hundred and seventy two.

892
00:51:05,000 --> 00:51:06,920
Speaker 9: That's a bad number of tags issue.

893
00:51:07,000 --> 00:51:10,520
Speaker 1: Yeah, they killed fifty two, and I think that they

894
00:51:10,560 --> 00:51:13,920
Speaker 1: had they had they were comfortable with a much larger harvest.

895
00:51:14,000 --> 00:51:15,440
Speaker 1: What was the harvest they were comfortable with.

896
00:51:17,680 --> 00:51:19,800
Speaker 9: I don't know if they said they said a number.

897
00:51:19,840 --> 00:51:23,400
Speaker 9: They just said that they're they're like, the success rate

898
00:51:23,520 --> 00:51:25,880
Speaker 9: was lower than they had planned on, but it's still

899
00:51:26,480 --> 00:51:27,000
Speaker 9: pretty good.

900
00:51:27,120 --> 00:51:31,319
Speaker 1: Yep, they're pleased. But it was on the low end

901
00:51:31,320 --> 00:51:34,160
Speaker 1: of expected. So here's here's the grey irony. Here's what

902
00:51:34,200 --> 00:51:38,080
Speaker 1: always happens. This happened. Let me give you another verse. Well,

903
00:51:38,160 --> 00:51:39,399
Speaker 1: let me tell you what happened. I'll give you another

904
00:51:39,400 --> 00:51:43,440
Speaker 1: example to happen. So the animal rights community says, we're

905
00:51:43,440 --> 00:51:45,600
Speaker 1: going to screw your bear hunt and we're going to

906
00:51:45,960 --> 00:51:50,040
Speaker 1: apply for all these tags and then don't hunt them. Okay,

907
00:51:50,440 --> 00:51:52,400
Speaker 1: So they do the hunt, They issue one hundred and

908
00:51:52,400 --> 00:51:56,640
Speaker 1: seventy two tags, they kill, Remember me, Agan, how many

909
00:51:56,680 --> 00:51:59,600
Speaker 1: got round fifty? They killed fifty two bears? What is

910
00:51:59,600 --> 00:52:03,399
Speaker 1: the animal rights community say? The lack of success these

911
00:52:03,520 --> 00:52:06,920
Speaker 1: hunters had goes to show there aren't enough bears to

912
00:52:06,920 --> 00:52:12,399
Speaker 1: support the hunt. It's like in California. When California banned

913
00:52:12,480 --> 00:52:17,480
Speaker 1: using hounds to mountain lion hunt, the efficacy rate plummeted,

914
00:52:19,200 --> 00:52:23,279
Speaker 1: So they ban the use of hounds. The Animal rights

915
00:52:23,360 --> 00:52:25,960
Speaker 1: or the group's petition, they banned the use of hounds

916
00:52:26,000 --> 00:52:29,839
Speaker 1: to hunt. Then you see in the following years, efficacy

917
00:52:29,920 --> 00:52:33,279
Speaker 1: rate of lion hunting drops drops drops because you can't

918
00:52:33,320 --> 00:52:35,440
Speaker 1: use hounds to hunt. Where do they go and say,

919
00:52:35,680 --> 00:52:39,640
Speaker 1: oh my gosh, mountain lion efficacy rates are so low.

920
00:52:39,760 --> 00:52:45,000
Speaker 1: Now it must be there's no lions. So they create

921
00:52:45,040 --> 00:52:47,839
Speaker 1: a scenario and then they use that scenario turn around

922
00:52:47,920 --> 00:52:51,040
Speaker 1: and use it against the wildlife manager. So here they're

923
00:52:51,040 --> 00:52:56,239
Speaker 1: making the case, jeez, it went so shittily thanks to

924
00:52:56,680 --> 00:52:59,440
Speaker 1: us doing what we did. That now we can turn

925
00:52:59,480 --> 00:53:03,920
Speaker 1: around and use that low harvest against the agency by saying,

926
00:53:04,239 --> 00:53:06,759
Speaker 1: must not be that many bears. Success rates are very low,

927
00:53:07,160 --> 00:53:09,359
Speaker 1: even though we're all sitting on tags that we didn't hunt.

928
00:53:09,440 --> 00:53:12,080
Speaker 9: Yeah, it'd be interesting to know how many of those

929
00:53:12,160 --> 00:53:16,200
Speaker 9: tag holders were deliberately not gonna hunt and then go

930
00:53:16,280 --> 00:53:18,000
Speaker 9: with a success rate based on that.

931
00:53:18,200 --> 00:53:22,719
Speaker 1: You know, yep, he goes. They go on to say,

932
00:53:22,560 --> 00:53:25,560
Speaker 1: they go in their press release, they say Hey, the

933
00:53:25,640 --> 00:53:29,000
Speaker 1: hunter's success rate was very close to other states with

934
00:53:29,080 --> 00:53:31,000
Speaker 1: similar hunt parameters.

935
00:53:31,400 --> 00:53:32,920
Speaker 5: Do you know if that's it? Good?

936
00:53:33,000 --> 00:53:35,439
Speaker 1: Well, I'm glad for him. I mean, if they had

937
00:53:35,440 --> 00:53:38,960
Speaker 1: had a mistake again, right, let's say they had given

938
00:53:39,000 --> 00:53:40,600
Speaker 1: one hundred and seventy two tags, I don't know what

939
00:53:40,600 --> 00:53:42,600
Speaker 1: their objective was. If they gave one hundred and seventy

940
00:53:42,600 --> 00:53:44,839
Speaker 1: two and one hundred and seventy two people killed a bear,

941
00:53:45,920 --> 00:53:48,520
Speaker 1: then I don't know. Then they'd be people would be

942
00:53:48,600 --> 00:53:50,760
Speaker 1: using that against them. It'd be another like what a slaughter?

943
00:53:51,040 --> 00:53:54,560
Speaker 1: You know, So here's the moving forward.

944
00:53:55,000 --> 00:53:58,520
Speaker 5: Yep, can non reds apply for that tag?

945
00:53:58,600 --> 00:54:01,080
Speaker 1: You know, I'm not aware. That's a great question, i'd assume.

946
00:54:01,160 --> 00:54:08,040
Speaker 1: So I'm not positive. Man, I wanted to get all into.

947
00:54:10,160 --> 00:54:14,080
Speaker 7: This is just you can probably hit it lightly because

948
00:54:14,360 --> 00:54:17,200
Speaker 7: public comments is open non resident.

949
00:54:17,320 --> 00:54:23,919
Speaker 1: Yeah, Trump reviews federal subsistence program in Alaska. Now Here,

950
00:54:25,840 --> 00:54:29,880
Speaker 1: this is a doozy. I stated to get in this

951
00:54:29,920 --> 00:54:33,480
Speaker 1: because this is an hour long conversation and it's not

952
00:54:33,600 --> 00:54:34,279
Speaker 1: settled yet.

953
00:54:34,440 --> 00:54:37,720
Speaker 7: Right, Maybe light touched a lot about how it's not settling.

954
00:54:37,960 --> 00:54:44,319
Speaker 1: Come back to sixty percent of Alaska's federal land. In Alaska,

955
00:54:44,440 --> 00:54:50,960
Speaker 1: there is a thing called federal subsistence hunting, where people

956
00:54:51,000 --> 00:54:59,640
Speaker 1: that live in rural communities in Alaska and in defined

957
00:55:00,200 --> 00:55:07,480
Speaker 1: rural areas in Alaska. Residents of defined rural areas in

958
00:55:07,480 --> 00:55:11,600
Speaker 1: Alaska can often hunt and fish on federal lands under

959
00:55:11,640 --> 00:55:16,600
Speaker 1: different regulations than everybody else. It's the it's federal subsistence.

960
00:55:16,640 --> 00:55:21,880
Speaker 9: So on there's three tiers, right, there's native, then there's

961
00:55:21,920 --> 00:55:26,000
Speaker 9: like residence subsistence, and then there's like there's state's kind

962
00:55:26,000 --> 00:55:26,759
Speaker 9: of recreation.

963
00:55:26,960 --> 00:55:29,640
Speaker 1: Well, there's there's here's why it takes an hour because

964
00:55:29,640 --> 00:55:36,319
Speaker 1: there's state subsistence. So here here's an example. Let's say

965
00:55:36,320 --> 00:55:40,360
Speaker 1: you're a resident of Alaska. There are some harvests that

966
00:55:40,400 --> 00:55:44,280
Speaker 1: are state subsistence harvests, for instance, sablefish or black codon

967
00:55:44,800 --> 00:55:50,840
Speaker 1: that's state subsistence. You could live in downtown Anchorage and

968
00:55:51,000 --> 00:55:54,000
Speaker 1: go and you can travel to an area that has

969
00:55:54,040 --> 00:55:58,719
Speaker 1: a state subsistence hunt or a state subsistence fishery and

970
00:55:58,760 --> 00:56:04,320
Speaker 1: you can participate in the area. So you could be

971
00:56:04,400 --> 00:56:08,279
Speaker 1: from an urban area but participate in a state subsistence

972
00:56:08,360 --> 00:56:10,520
Speaker 1: hunt as long as you're in the area where the

973
00:56:10,560 --> 00:56:16,120
Speaker 1: state subsistence hunt occurs. For federal subsistence practices, on federal lands,

974
00:56:16,160 --> 00:56:20,720
Speaker 1: you have to be a resident of that area. Okay,

975
00:56:20,800 --> 00:56:24,160
Speaker 1: you can do federal subsistence activities in your area, and

976
00:56:24,200 --> 00:56:29,080
Speaker 1: it might be increased bag limits, earlier hunting seasons, fisheries

977
00:56:29,120 --> 00:56:31,279
Speaker 1: that aren't open to other people, and it's that's the

978
00:56:31,320 --> 00:56:36,520
Speaker 1: federal subsistence thing. What it allows is you can't the

979
00:56:36,640 --> 00:56:40,400
Speaker 1: state can't go in on some issues. They can't go

980
00:56:40,520 --> 00:56:45,239
Speaker 1: in and make hunting seasons and fishing opportunities that are

981
00:56:45,280 --> 00:56:49,480
Speaker 1: applied solely to Native Alaskans. What they can do is

982
00:56:49,520 --> 00:56:51,719
Speaker 1: they can say on federal lands, they can say, if

983
00:56:51,760 --> 00:56:53,840
Speaker 1: you live in this area, and it might be a

984
00:56:53,920 --> 00:56:58,520
Speaker 1: predominantly Native area, if you live in this area, you

985
00:56:58,719 --> 00:57:01,879
Speaker 1: have different rules and regulations for hunting and fish certain

986
00:57:01,960 --> 00:57:07,840
Speaker 1: hunting and fishing practices on federal lands. Many oftentimes and

987
00:57:07,880 --> 00:57:10,839
Speaker 1: this is this is my personal view, some of the

988
00:57:10,880 --> 00:57:18,880
Speaker 1: Federal Subsistence Board decisions are there's some areas where they

989
00:57:18,960 --> 00:57:21,720
Speaker 1: have some major overreach in my view as the outsider

990
00:57:21,760 --> 00:57:23,640
Speaker 1: looking in, you mean, like being.

991
00:57:23,400 --> 00:57:26,280
Speaker 9: Too liberal with what they allow some people to do.

992
00:57:27,360 --> 00:57:30,920
Speaker 1: No, not as much that as they've They've created a

993
00:57:31,000 --> 00:57:35,480
Speaker 1: lot of controversy in Alaska by making certain things like

994
00:57:35,520 --> 00:57:39,840
Speaker 1: in Western Brooks Range that like caribou hunting, moose hunting

995
00:57:39,960 --> 00:57:44,280
Speaker 1: for big game, you know, whatever decision that says it's

996
00:57:44,360 --> 00:57:48,800
Speaker 1: it's federal subsistence only, meaning that people from other parts,

997
00:57:48,920 --> 00:57:51,840
Speaker 1: not people from outside the state. Not only people from

998
00:57:51,880 --> 00:57:55,480
Speaker 1: outside the state, but people from outside of that area

999
00:57:55,560 --> 00:57:58,200
Speaker 1: can no longer hunt that area or taking sheep doll

1000
00:57:58,240 --> 00:58:02,080
Speaker 1: sheep units in the range and the Federal Subsistence Board

1001
00:58:02,160 --> 00:58:06,120
Speaker 1: coming in and saying only Federal subsistence people can hunt

1002
00:58:06,120 --> 00:58:10,600
Speaker 1: this hunt, and it could be what they've allowed to

1003
00:58:10,640 --> 00:58:16,000
Speaker 1: creep into their decision making process is not necessarily the

1004
00:58:16,000 --> 00:58:20,400
Speaker 1: health of the species being hunted, but it's social considerations,

1005
00:58:20,960 --> 00:58:24,640
Speaker 1: meaning people communities in the western Brooks Range say hey,

1006
00:58:24,680 --> 00:58:28,080
Speaker 1: we're sick of people from outside of our area coming

1007
00:58:28,120 --> 00:58:31,120
Speaker 1: in to hunt. So the Federal Subsistence Board saying, okay,

1008
00:58:31,640 --> 00:58:34,600
Speaker 1: we'll make it that they can't. That has caused an

1009
00:58:34,720 --> 00:58:38,840
Speaker 1: enormous amount of controversy in certain areas. The Federal Subsistence

1010
00:58:38,880 --> 00:58:43,520
Speaker 1: Board just made a very strange decision. They came in

1011
00:58:43,560 --> 00:58:50,680
Speaker 1: and declared catch a can Alaska to be Federal subsistence eligible.

1012
00:58:51,280 --> 00:58:54,080
Speaker 1: So now you have a town that has a Walmart

1013
00:58:57,560 --> 00:59:00,440
Speaker 1: and a Starbucks and.

1014
00:59:00,400 --> 00:59:04,080
Speaker 9: A bunch of crappy gift shops for cruise people.

1015
00:59:04,120 --> 00:59:12,360
Speaker 1: And gift stores. It's a full on town with an airport.

1016
00:59:13,600 --> 00:59:17,560
Speaker 1: The Federal Subsistence Board shocked everybody, most everybody, and came

1017
00:59:17,600 --> 00:59:20,480
Speaker 1: in and said, ketch a Can is federal subsistence.

1018
00:59:21,080 --> 00:59:26,760
Speaker 7: On what grounds? But like from their perspective, if they're

1019
00:59:26,760 --> 00:59:30,000
Speaker 7: putting forth this on serious grounds, what are they claiming?

1020
00:59:30,680 --> 00:59:34,000
Speaker 7: There are there are people who could benefit.

1021
00:59:35,040 --> 00:59:37,280
Speaker 1: Here's the here's the I'll give you the best argument.

1022
00:59:37,360 --> 00:59:39,040
Speaker 7: I mean, I know I tried to understand that they.

1023
00:59:38,880 --> 00:59:41,680
Speaker 1: Can't because there's a there's a there are a lot

1024
00:59:41,720 --> 00:59:44,840
Speaker 1: of Native Alaskans in ketcha Can, right, and you can't

1025
00:59:45,240 --> 00:59:51,360
Speaker 1: grant They can't grant just Native Alaskans, right, yep. So

1026
00:59:51,440 --> 00:59:55,440
Speaker 1: you have indigenous people in ketcha Can, they can't grant

1027
00:59:55,560 --> 01:00:03,320
Speaker 1: them these these honey fishing privileges on that you can

1028
01:00:03,400 --> 01:00:08,640
Speaker 1: only grant it to the tribes right under federal subsistence.

1029
01:00:09,840 --> 01:00:12,320
Speaker 1: But the minute you do that for federal you can't.

1030
01:00:12,360 --> 01:00:15,680
Speaker 1: So you have to say the jurisdiction. Everyone living in

1031
01:00:15,680 --> 01:00:21,320
Speaker 1: this jurisdiction. So now that the guy I know that

1032
01:00:21,520 --> 01:00:24,720
Speaker 1: Walmart owns Walmart, but the guy that owns the grocery

1033
01:00:24,720 --> 01:00:30,360
Speaker 1: store is now federal subsistence and they can do hunting

1034
01:00:30,360 --> 01:00:33,160
Speaker 1: and fishing practices like.

1035
01:00:33,840 --> 01:00:37,280
Speaker 7: In practice, in practice, if that's lived out, will that

1036
01:00:37,520 --> 01:00:44,080
Speaker 7: still end up benefiting tribal members who they're seeking to.

1037
01:00:45,240 --> 01:00:51,000
Speaker 1: That tribal members were instrumental in petitioning, like Native Alaskans

1038
01:00:51,320 --> 01:00:57,480
Speaker 1: from the area were instrumental in petitioning to get federal

1039
01:00:57,480 --> 01:01:02,080
Speaker 1: subsistence status, But the federal subs assistance status falls of

1040
01:01:02,120 --> 01:01:05,200
Speaker 1: the whole town. And many people quite rightfully are looking

1041
01:01:05,240 --> 01:01:10,360
Speaker 1: at the irony of taking a town that has chain hotels,

1042
01:01:11,040 --> 01:01:19,320
Speaker 1: a Super eight, a Walmart, cruise ship docks, Delta Airline flights,

1043
01:01:19,320 --> 01:01:25,680
Speaker 1: Alaska Airline flights, United Airline flights, a ferry system, cars,

1044
01:01:25,800 --> 01:01:29,880
Speaker 1: like taking a full on city, a full on urban

1045
01:01:30,000 --> 01:01:34,240
Speaker 1: center and saying you need to you Basically you're saying

1046
01:01:34,920 --> 01:01:40,520
Speaker 1: you people rely on a subsistence lifestyle and should be

1047
01:01:40,600 --> 01:01:47,440
Speaker 1: granted subsistence harvest authority, and other people looking at being like,

1048
01:01:47,560 --> 01:01:49,720
Speaker 1: how in the world can you live in a town

1049
01:01:50,000 --> 01:01:54,680
Speaker 1: with a Walmart and an airport and be reliant on

1050
01:01:54,760 --> 01:01:55,960
Speaker 1: subsistence practices?

1051
01:01:56,040 --> 01:01:58,280
Speaker 5: And why I know you said earlier that they can't

1052
01:01:58,360 --> 01:02:01,760
Speaker 5: give it, just give it to the natives, and why is.

1053
01:02:01,720 --> 01:02:05,560
Speaker 1: That it's unconstitutional. I don't know the full legal history

1054
01:02:05,560 --> 01:02:09,600
Speaker 1: of why that can't happen. It's unconstitutional. Here's what else

1055
01:02:09,640 --> 01:02:14,120
Speaker 1: makes this story interesting. Where a lot of this subsistence

1056
01:02:14,200 --> 01:02:17,400
Speaker 1: activity is going to wind up taking place is on

1057
01:02:18,200 --> 01:02:22,480
Speaker 1: another town and another island that already has because another

1058
01:02:22,520 --> 01:02:27,040
Speaker 1: island that very much is rural and is very remote,

1059
01:02:27,960 --> 01:02:30,920
Speaker 1: and the people on that island have federal subsistence. So

1060
01:02:31,040 --> 01:02:33,320
Speaker 1: now people out there are like, oh man, wait a minute,

1061
01:02:33,320 --> 01:02:35,080
Speaker 1: where do you think they're going to be doing all

1062
01:02:35,120 --> 01:02:38,360
Speaker 1: this federal subsistence activity. It's going to be in our

1063
01:02:38,400 --> 01:02:40,919
Speaker 1: federal subsistence area. So now you got one. You got

1064
01:02:40,920 --> 01:02:45,520
Speaker 1: people from one federal subsistence area who are like, dude,

1065
01:02:45,840 --> 01:02:49,800
Speaker 1: you people aren't rural, and I know you're all coming

1066
01:02:49,840 --> 01:02:55,080
Speaker 1: to our area to hunt. Yeah. So, for these various reasons,

1067
01:02:55,120 --> 01:02:57,800
Speaker 1: when I laid out about stuff from doll sheep units,

1068
01:02:57,920 --> 01:03:00,880
Speaker 1: and I'm not even fully like I have very complex

1069
01:03:00,960 --> 01:03:03,320
Speaker 1: personal thoughts about this whole thing, I'm trying to as

1070
01:03:03,400 --> 01:03:06,959
Speaker 1: much as possible lay out the issue that will cover

1071
01:03:07,040 --> 01:03:09,400
Speaker 1: when we cover this. We're going to cover this big

1072
01:03:09,440 --> 01:03:10,000
Speaker 1: time later.

1073
01:03:10,200 --> 01:03:11,200
Speaker 5: This is the light touch.

1074
01:03:11,320 --> 01:03:13,440
Speaker 1: This is the light touch. It's so complicated.

1075
01:03:13,760 --> 01:03:16,440
Speaker 9: The thing is where like if it goes through like

1076
01:03:16,560 --> 01:03:19,480
Speaker 9: what's to stop like Anchorage or Fairbanks from you know

1077
01:03:19,520 --> 01:03:19,960
Speaker 9: what I mean?

1078
01:03:20,080 --> 01:03:29,320
Speaker 1: Yeah, So sci Safari Club International has a thing they've asked,

1079
01:03:29,840 --> 01:03:34,040
Speaker 1: this has been put forward. They have asked the administration,

1080
01:03:34,560 --> 01:03:39,240
Speaker 1: the current administration, to do a review of Hey, what

1081
01:03:39,400 --> 01:03:43,640
Speaker 1: is going on with the federal subsistence program in Alaska?

1082
01:03:43,680 --> 01:03:46,000
Speaker 1: And a couple of the questions are raising is they've

1083
01:03:46,000 --> 01:03:50,040
Speaker 1: recently added new board members, So it's like, what is

1084
01:03:50,120 --> 01:03:53,040
Speaker 1: up with the what is up with who is on

1085
01:03:53,080 --> 01:03:57,760
Speaker 1: the board? Are we talking about health of wildlife species

1086
01:03:57,840 --> 01:04:01,240
Speaker 1: or are we talking about social friction? What is the

1087
01:04:01,280 --> 01:04:03,840
Speaker 1: decision making process? What are some of the things that

1088
01:04:03,920 --> 01:04:10,280
Speaker 1: happened lately, and just basically doing a review of the process.

1089
01:04:12,400 --> 01:04:16,600
Speaker 1: Native groups in Alaska are worried about this. What's that said?

1090
01:04:16,600 --> 01:04:18,080
Speaker 5: I'm looking forward to hearing more.

1091
01:04:18,840 --> 01:04:20,360
Speaker 1: We're gonna do a full cover on it.

1092
01:04:22,920 --> 01:04:27,120
Speaker 9: Yeah, what's the timeline on this? Like as far as them.

1093
01:04:27,000 --> 01:04:29,520
Speaker 1: You read that from exacting up then we're gonna move

1094
01:04:29,520 --> 01:04:30,520
Speaker 1: on other news stories.

1095
01:04:30,600 --> 01:04:36,040
Speaker 7: Yeah, public comments by February thirteenth.

1096
01:04:36,560 --> 01:04:39,760
Speaker 1: Oh, speaking of February thirteenth and Safari Club hold on it.

1097
01:04:39,880 --> 01:04:42,880
Speaker 1: What am I going down there? So I'm trying to

1098
01:04:42,920 --> 01:04:45,840
Speaker 1: find right now, that's your birthday? Why no? But check

1099
01:04:45,880 --> 01:04:52,280
Speaker 1: this out on give me a minute. Not then.

1100
01:04:54,000 --> 01:04:55,400
Speaker 9: Where are they taking comments?

1101
01:04:55,480 --> 01:04:55,720
Speaker 4: Is not?

1102
01:04:55,880 --> 01:04:56,200
Speaker 1: Then?

1103
01:04:57,040 --> 01:04:58,680
Speaker 7: Oh you mean when you're going to.

1104
01:05:00,200 --> 01:05:00,760
Speaker 1: With Morgan?

1105
01:05:00,920 --> 01:05:04,160
Speaker 3: Yeah, February eighteenth to twenty first is this is SCI

1106
01:05:04,200 --> 01:05:05,240
Speaker 3: shows the dates.

1107
01:05:05,000 --> 01:05:14,360
Speaker 1: For this show. Okay, if you on YouTube watched our Africa.

1108
01:05:14,120 --> 01:05:16,600
Speaker 7: Series and if you didn't like, you need to.

1109
01:05:16,680 --> 01:05:18,600
Speaker 1: Or listen to all the three million podcasts we did

1110
01:05:18,640 --> 01:05:20,920
Speaker 1: about it. Yeah, I'm going to be at the SCI

1111
01:05:21,120 --> 01:05:24,000
Speaker 1: convention in Nashville with Morgan Potter. So if you're going

1112
01:05:24,040 --> 01:05:26,800
Speaker 1: to the SCI show, Morgan Potter and I are going

1113
01:05:26,840 --> 01:05:29,000
Speaker 1: to do a presentation. So the professional hunter I was

1114
01:05:29,080 --> 01:05:31,200
Speaker 1: hunting with who's been on the podcast. We're going to

1115
01:05:31,200 --> 01:05:37,439
Speaker 1: be in Nashville doing a presentation at SCI about that

1116
01:05:37,600 --> 01:05:42,240
Speaker 1: trip about wildlife management Africa, about things that were assumed

1117
01:05:42,280 --> 01:05:44,040
Speaker 1: and learned, just the whole story of it. So if

1118
01:05:44,040 --> 01:05:46,919
Speaker 1: you want to come check that out. Tickets you get

1119
01:05:46,920 --> 01:05:52,680
Speaker 1: tickets through SCI. I have no I'm going ticket prices.

1120
01:05:52,760 --> 01:05:54,960
Speaker 1: All that money goes to SCILL. It all goes to

1121
01:05:54,960 --> 01:05:57,280
Speaker 1: support SCI. I am not taking a dip into this,

1122
01:05:57,520 --> 01:05:59,480
Speaker 1: So when you get in, you got to buy a ticket.

1123
01:05:59,760 --> 01:06:02,040
Speaker 1: But the ticket is not to me. The ticket is

1124
01:06:02,080 --> 01:06:04,480
Speaker 1: to support SCI because this is one of their biggest

1125
01:06:04,480 --> 01:06:08,880
Speaker 1: fundraising it's a nonprofit, it's one of their biggest fundraising opportunities.

1126
01:06:09,680 --> 01:06:12,360
Speaker 1: Is this, So when you get your ticket, you're supporting SCI,

1127
01:06:12,480 --> 01:06:19,160
Speaker 1: not me. Mountain lion kills women in Colorado. A hiker.

1128
01:06:19,920 --> 01:06:23,920
Speaker 1: They even give her name, Kristin Marie Kovach, forty six

1129
01:06:24,000 --> 01:06:27,360
Speaker 1: years old, killed on New Year's Day in northern Colorado.

1130
01:06:27,360 --> 01:06:29,320
Speaker 1: Go ahead, brod, this is your neck of the woods.

1131
01:06:29,760 --> 01:06:32,680
Speaker 9: I was right outside Estes Park, which is right outside

1132
01:06:32,840 --> 01:06:37,440
Speaker 9: Rocky Mountain National Park, where you like kind of resorties,

1133
01:06:37,640 --> 01:06:44,000
Speaker 9: touristy town, popular hiking trail and some other fight hikers.

1134
01:06:44,160 --> 01:06:45,600
Speaker 5: Have you personally hiked that trail?

1135
01:06:46,440 --> 01:06:47,200
Speaker 2: No, I don't.

1136
01:06:47,240 --> 01:06:49,200
Speaker 9: I mean I may have back when, way back when,

1137
01:06:49,240 --> 01:06:50,240
Speaker 9: when I lived in Boulder.

1138
01:06:50,280 --> 01:06:50,720
Speaker 1: I don't know.

1139
01:06:50,840 --> 01:06:52,440
Speaker 9: I mean I've been in that area a bunch. But

1140
01:06:52,520 --> 01:06:57,080
Speaker 9: either way, some other hikers founder and uh, it was

1141
01:06:57,120 --> 01:07:00,560
Speaker 9: determined she had been killed by a mountain lion. They

1142
01:07:00,760 --> 01:07:05,960
Speaker 9: went in and I think killed two juveniles. And I

1143
01:07:05,960 --> 01:07:10,200
Speaker 9: don't know where they're at with getting the.

1144
01:07:08,960 --> 01:07:11,960
Speaker 1: The lion that I heard from I heard through the

1145
01:07:12,000 --> 01:07:16,280
Speaker 1: grapevine that they were looking for the adult.

1146
01:07:16,720 --> 01:07:20,120
Speaker 9: Yeah, I haven't heard whether. I mean, you'd think they

1147
01:07:20,120 --> 01:07:22,960
Speaker 9: would have got on that line pretty quick, but who knows.

1148
01:07:23,920 --> 01:07:26,040
Speaker 1: I yeah, but yeah, of course it would be if

1149
01:07:26,040 --> 01:07:26,960
Speaker 1: it's like a predatory.

1150
01:07:29,680 --> 01:07:31,959
Speaker 9: But you know, like the whole thing kind of goes

1151
01:07:32,000 --> 01:07:37,760
Speaker 9: to whether like lions attack more people in states where

1152
01:07:37,800 --> 01:07:40,760
Speaker 9: they don't get hunted versus where they do. Like line

1153
01:07:40,800 --> 01:07:44,240
Speaker 9: hunting is legal in Colorado, it might not take place

1154
01:07:44,280 --> 01:07:49,200
Speaker 9: a lot in this particular area. But it's like when

1155
01:07:49,200 --> 01:07:51,400
Speaker 9: you get into that whole thing, it's like it happens

1156
01:07:51,440 --> 01:07:53,240
Speaker 9: so rarely that it's.

1157
01:07:53,120 --> 01:07:55,880
Speaker 1: Like it remains a non issue. Yeah, exactly, But it

1158
01:07:56,000 --> 01:07:58,920
Speaker 1: remains a non issue. If we covered people getting zap

1159
01:07:58,960 --> 01:08:03,440
Speaker 1: by lightning, like we always covered people getting killed by

1160
01:08:03,480 --> 01:08:06,440
Speaker 1: wild if we covered people getting zapp by lightning, we

1161
01:08:06,480 --> 01:08:09,040
Speaker 1: would have a lot we would there would be much

1162
01:08:09,080 --> 01:08:11,640
Speaker 1: more coverage. Yeah.

1163
01:08:11,800 --> 01:08:15,080
Speaker 3: One thing I saw was that the on that same trail,

1164
01:08:15,160 --> 01:08:19,760
Speaker 3: a guy was attacked in the fall and he hit

1165
01:08:19,800 --> 01:08:23,519
Speaker 3: it with a stick and managed to scare it off.

1166
01:08:23,600 --> 01:08:27,640
Speaker 3: But then I guess there have also been cases of

1167
01:08:28,040 --> 01:08:30,360
Speaker 3: people walking pets in that area that have had their

1168
01:08:30,400 --> 01:08:32,960
Speaker 3: pets attacked, so it seems.

1169
01:08:33,760 --> 01:08:36,600
Speaker 9: It's probably a lion. That's just like, it's not like

1170
01:08:36,680 --> 01:08:38,439
Speaker 9: this is out in the middle of nowhere, you know.

1171
01:08:38,600 --> 01:08:43,160
Speaker 3: Yeah, the guy was the guy was encountered encountered a

1172
01:08:43,240 --> 01:08:47,120
Speaker 3: lion in November when he was running and it rushed him,

1173
01:08:47,120 --> 01:08:48,439
Speaker 3: but he beat it off.

1174
01:08:48,479 --> 01:08:52,080
Speaker 1: So it seems like they're here. Here's the crazy probabi.

1175
01:08:52,520 --> 01:08:54,559
Speaker 1: Thanks Phil, What are you gonna bleep out?

1176
01:08:55,120 --> 01:08:55,800
Speaker 5: Just just move on.

1177
01:08:57,760 --> 01:09:00,479
Speaker 1: Here. Here's here's where this whole thing with mountaine attacks

1178
01:09:00,479 --> 01:09:02,519
Speaker 1: gets weird. Is you had that you had that summer.

1179
01:09:03,560 --> 01:09:05,840
Speaker 1: This is a few handful of years ago now where

1180
01:09:06,240 --> 01:09:13,000
Speaker 1: Washington State had its first ever recorded human fatality from

1181
01:09:13,040 --> 01:09:15,880
Speaker 1: a mountain lion attack. Yeah, and then right on the

1182
01:09:15,920 --> 01:09:18,000
Speaker 1: heels of that, I think it was in this order,

1183
01:09:18,760 --> 01:09:22,080
Speaker 1: Oregon had its first one in something like ninety years

1184
01:09:23,479 --> 01:09:27,759
Speaker 1: right together, and then a bunch of other high profile cases.

1185
01:09:27,760 --> 01:09:30,240
Speaker 1: We had a kid on who's sitting right where yann

1186
01:09:30,240 --> 01:09:32,360
Speaker 1: he's sitting right now, who him and his brother were

1187
01:09:32,400 --> 01:09:34,519
Speaker 1: attacking and his brother was killed in a mountain lion attack.

1188
01:09:35,280 --> 01:09:41,799
Speaker 1: It's like, it seems beyond seems like it it seems

1189
01:09:41,840 --> 01:09:45,520
Speaker 1: as though you're seeing more and more there's different explanations

1190
01:09:45,520 --> 01:09:47,920
Speaker 1: to be like, there's more lines on the landscape, there's

1191
01:09:47,960 --> 01:09:51,520
Speaker 1: more people on the landscape, there's more recreation on the landscape.

1192
01:09:51,680 --> 01:09:54,280
Speaker 1: One of the more interesting things someone has mentioned to me,

1193
01:09:54,880 --> 01:09:58,719
Speaker 1: we have a friend who works in mountain lion depredation issues,

1194
01:09:58,800 --> 01:10:02,040
Speaker 1: works problem lines things, spent his whole career on mountain lions.

1195
01:10:03,000 --> 01:10:07,160
Speaker 1: He had like just an observation from throughout his career.

1196
01:10:07,160 --> 01:10:12,280
Speaker 1: He was in the Pacific Northwest, and it's like just

1197
01:10:12,280 --> 01:10:15,360
Speaker 1: an it's an individual, it's a very well informed individual's

1198
01:10:15,400 --> 01:10:19,640
Speaker 1: observation that early in his career, any mountain lion that

1199
01:10:19,760 --> 01:10:25,280
Speaker 1: brushed up against like the human lion barrier was was

1200
01:10:25,320 --> 01:10:28,599
Speaker 1: a dead lion. He's like, in the old days, if

1201
01:10:28,600 --> 01:10:31,200
Speaker 1: a lion came on someone's porch, it was a dead lion.

1202
01:10:32,800 --> 01:10:35,120
Speaker 1: If a lion came through town, it was a dead lion.

1203
01:10:36,680 --> 01:10:41,080
Speaker 1: He says, as tolerance has increased, and as people have

1204
01:10:41,160 --> 01:10:43,320
Speaker 1: been reluctant to they like, oh, look, that's so cool,

1205
01:10:43,360 --> 01:10:46,040
Speaker 1: there's a lion on my porch. Which he's not passing

1206
01:10:46,120 --> 01:10:49,720
Speaker 1: judgment on it, but he's saying, as tolerance an acceptability

1207
01:10:49,720 --> 01:10:53,520
Speaker 1: of lions has increased as people have gotten comfortable with wildlife,

1208
01:10:53,520 --> 01:10:55,880
Speaker 1: and people have gotten where it's not. You know, you

1209
01:10:55,920 --> 01:10:57,880
Speaker 1: don't call the cops because you saw a mountain lion

1210
01:10:57,880 --> 01:11:01,840
Speaker 1: cut across your backyard. He says, I would expect to

1211
01:11:01,880 --> 01:11:05,479
Speaker 1: see more of this sort of thing happen. It doesn't

1212
01:11:05,479 --> 01:11:08,120
Speaker 1: mean that it's becoming like a pandemic. It doesn't mean

1213
01:11:08,160 --> 01:11:10,679
Speaker 1: it's becoming like anything other than a freak occurrence, because,

1214
01:11:10,720 --> 01:11:13,120
Speaker 1: like I would expect to see that with increased tolerance,

1215
01:11:13,120 --> 01:11:14,720
Speaker 1: you're going to have increased interactions.

1216
01:11:14,800 --> 01:11:18,240
Speaker 9: Yeah, and those lions that are experiencing increased tolerance also

1217
01:11:18,400 --> 01:11:21,679
Speaker 9: developed their own increased tolerance for being around people.

1218
01:11:21,760 --> 01:11:23,720
Speaker 1: Yeah. You know they're like, oh no, no, they're not

1219
01:11:23,760 --> 01:11:25,639
Speaker 1: a problem. You can go right up to them.

1220
01:11:25,720 --> 01:11:26,400
Speaker 5: Yeah.

1221
01:11:26,479 --> 01:11:28,520
Speaker 1: It's like they don't do anything.

1222
01:11:28,400 --> 01:11:31,160
Speaker 9: But to demonstrate like how rare it is. At first,

1223
01:11:31,240 --> 01:11:33,080
Speaker 9: when I read this sentence, I thought it was funny,

1224
01:11:33,080 --> 01:11:35,040
Speaker 9: but then I thought about it. It was the first

1225
01:11:35,120 --> 01:11:38,479
Speaker 9: fatal attack in Colorado by a mountain lion in this century,

1226
01:11:38,520 --> 01:11:41,439
Speaker 9: And you're like, oh, wow, was it? But this century

1227
01:11:41,479 --> 01:11:43,439
Speaker 9: is twenty five years so and.

1228
01:11:43,400 --> 01:11:45,160
Speaker 1: Where was the guy? Remember the guy that put that

1229
01:11:45,200 --> 01:11:46,720
Speaker 1: one in a stranglehold?

1230
01:11:47,200 --> 01:11:47,360
Speaker 2: Oh?

1231
01:11:47,439 --> 01:11:51,480
Speaker 1: Yeah, I mean it was a strangle babe. Wasn't that Colorado?

1232
01:11:51,800 --> 01:11:53,080
Speaker 5: I believe it was.

1233
01:11:52,880 --> 01:11:54,599
Speaker 9: It was that little It was a little line.

1234
01:11:54,680 --> 01:11:55,519
Speaker 5: It was like a juvie.

1235
01:11:55,600 --> 01:11:55,800
Speaker 1: Yeah.

1236
01:11:56,080 --> 01:12:01,360
Speaker 7: Was it also Colorado where there are four old ladies.

1237
01:12:02,560 --> 01:12:04,200
Speaker 1: Was Yeah?

1238
01:12:04,200 --> 01:12:06,840
Speaker 3: Another thing bikes, bikes seem to have like a lot

1239
01:12:06,880 --> 01:12:09,719
Speaker 3: of there. There seemed to be a lot of mountain

1240
01:12:09,720 --> 01:12:11,439
Speaker 3: biking incidents with lions.

1241
01:12:11,880 --> 01:12:12,559
Speaker 9: I'm okay with that.

1242
01:12:12,640 --> 01:12:13,320
Speaker 2: And there was the one.

1243
01:12:13,320 --> 01:12:16,280
Speaker 3: And there's a grizzly bear up by glacier that ended

1244
01:12:16,360 --> 01:12:18,519
Speaker 3: up killing a guy on a bike. But it's like

1245
01:12:18,600 --> 01:12:21,120
Speaker 3: as more and more people are traveling quickly and silently

1246
01:12:21,160 --> 01:12:22,519
Speaker 3: in the woods, he hit that.

1247
01:12:23,160 --> 01:12:24,920
Speaker 2: Yeah, that was.

1248
01:12:24,920 --> 01:12:27,800
Speaker 1: A weird story because the dude hit it. Yeah, the

1249
01:12:27,880 --> 01:12:29,360
Speaker 1: dude behind him.

1250
01:12:29,720 --> 01:12:31,600
Speaker 2: Oh really No, the dude.

1251
01:12:31,360 --> 01:12:37,320
Speaker 1: Behind him, I believe boogied. Mhmm, took off. The guy

1252
01:12:37,360 --> 01:12:41,400
Speaker 1: that hit the bear got killed by the bear. Also

1253
01:12:41,439 --> 01:12:44,000
Speaker 1: in Colorado. Take it away, Brody.

1254
01:12:44,600 --> 01:12:48,840
Speaker 9: Back to the wolf desk in Colorado. Yeah, people think.

1255
01:12:49,760 --> 01:12:52,679
Speaker 1: The wolf where the wolf desk intersects with the raft

1256
01:12:52,760 --> 01:12:53,680
Speaker 1: of the administration.

1257
01:12:56,640 --> 01:12:59,400
Speaker 9: Oh, come on, it's not just a theory.

1258
01:13:00,120 --> 01:13:01,120
Speaker 1: Well, no, here's the deal.

1259
01:13:01,960 --> 01:13:05,200
Speaker 9: Let's let's argue after we talk about.

1260
01:13:06,920 --> 01:13:09,880
Speaker 1: But you got to include the water deal. Oh, we will, Okay,

1261
01:13:09,920 --> 01:13:10,240
Speaker 1: go ahead.

1262
01:13:12,240 --> 01:13:16,000
Speaker 9: So the FED, we talk about Colorado wolves all the time.

1263
01:13:16,479 --> 01:13:18,799
Speaker 9: They're kind of out of standstill right now with getting

1264
01:13:18,840 --> 01:13:21,840
Speaker 9: new ones to introduce because the FED said, you can't

1265
01:13:21,840 --> 01:13:24,879
Speaker 9: get them from Alaska, you can't get them from Canada.

1266
01:13:26,520 --> 01:13:30,400
Speaker 9: Now they've stepped in and said, if you don't comply

1267
01:13:30,800 --> 01:13:36,160
Speaker 9: with certain like showing us certain like record keeping things

1268
01:13:36,240 --> 01:13:39,639
Speaker 9: and and and certain practices, you're going to do down

1269
01:13:39,680 --> 01:13:42,200
Speaker 9: the line and introducing more wolves. Like if you don't

1270
01:13:42,200 --> 01:13:45,679
Speaker 9: comply with what we say, we're just gonna shut down

1271
01:13:45,720 --> 01:13:48,760
Speaker 9: your whole reintroduction program and we're going to take over

1272
01:13:49,560 --> 01:13:53,200
Speaker 9: management of wolves in the state of Colorado. So that's

1273
01:13:53,040 --> 01:13:56,880
Speaker 9: that's the uh, that's what's going on. Some of the

1274
01:13:57,000 --> 01:14:05,599
Speaker 9: reasons for stepping in where that Colorado knowingly introduced livestock killers,

1275
01:14:06,479 --> 01:14:11,400
Speaker 9: that Colorado released wolves last January without really letting anyone

1276
01:14:11,439 --> 01:14:13,880
Speaker 9: know when and where they were going to do it.

1277
01:14:14,479 --> 01:14:19,280
Speaker 9: So there's like tension between Colorado and the Federal the

1278
01:14:19,400 --> 01:14:22,040
Speaker 9: US Fish and Wildlife as far as management policies.

1279
01:14:22,120 --> 01:14:23,960
Speaker 1: And then they went outside the country to get the

1280
01:14:23,960 --> 01:14:25,719
Speaker 1: wolves yeh, which was not part of their management.

1281
01:14:25,720 --> 01:14:28,879
Speaker 9: They ultimately yeah, I mean they tried everywhere, and ultimately

1282
01:14:28,880 --> 01:14:32,960
Speaker 9: I think got some from British Columbia after the.

1283
01:14:33,720 --> 01:14:37,479
Speaker 1: Yeah they brought in the state currently has twenty to

1284
01:14:37,520 --> 01:14:41,840
Speaker 1: thirty wolves, several new pups born in twenty twenty five.

1285
01:14:42,479 --> 01:14:45,240
Speaker 1: Fifteen they brought in fifteen from Canada, and.

1286
01:14:45,200 --> 01:14:49,559
Speaker 9: I think they've I forget the exact number, like, out

1287
01:14:49,560 --> 01:14:54,080
Speaker 9: of the total number they've introduced, I think they've maybe

1288
01:14:54,200 --> 01:14:56,880
Speaker 9: killed again, look it up real quick, but I think

1289
01:14:56,880 --> 01:15:01,960
Speaker 9: they've They've had to like lethally remove ten of the

1290
01:15:01,960 --> 01:15:02,439
Speaker 9: ones that.

1291
01:15:02,760 --> 01:15:05,479
Speaker 1: I know that they I know that they have, and

1292
01:15:05,520 --> 01:15:07,519
Speaker 1: I know that that was even done in a very

1293
01:15:07,600 --> 01:15:09,599
Speaker 1: some of that was done in a pretty low key fashion.

1294
01:15:09,760 --> 01:15:09,960
Speaker 5: Yeah.

1295
01:15:10,760 --> 01:15:10,880
Speaker 7: Uh.

1296
01:15:11,160 --> 01:15:13,760
Speaker 1: They had one boogie over to New Mexico.

1297
01:15:13,800 --> 01:15:19,320
Speaker 9: Yeah, which is very close to a population of endangered

1298
01:15:19,680 --> 01:15:20,799
Speaker 9: Mexican gray wolves.

1299
01:15:20,920 --> 01:15:23,800
Speaker 1: That one killed some that one killed some livestock, and

1300
01:15:23,800 --> 01:15:24,880
Speaker 1: they brought it back home.

1301
01:15:25,880 --> 01:15:27,360
Speaker 9: What'd your buddy cook think about that?

1302
01:15:27,400 --> 01:15:30,280
Speaker 1: I haven't asked them anyway.

1303
01:15:30,920 --> 01:15:36,400
Speaker 9: So possible outcomes here a complete federal takeover where Colorado CPW,

1304
01:15:36,600 --> 01:15:39,799
Speaker 9: Colorado Parks and Wildlife has no authority to manage wolves

1305
01:15:39,800 --> 01:15:43,880
Speaker 9: in their own state, and the Feds could come in

1306
01:15:44,000 --> 01:15:46,840
Speaker 9: and kill the wolves. That are there, they could relocate

1307
01:15:46,880 --> 01:15:51,720
Speaker 9: them like Colorado wouldn't have a say, the reintroduction could

1308
01:15:51,760 --> 01:15:52,360
Speaker 9: be halted.

1309
01:15:53,240 --> 01:15:53,679
Speaker 1: Uh.

1310
01:15:53,760 --> 01:15:58,040
Speaker 9: So it's pretty interesting considering what else is going on

1311
01:15:58,160 --> 01:16:02,040
Speaker 9: at the same time as this. There's a bill moving

1312
01:16:02,080 --> 01:16:06,879
Speaker 9: through Congress right now, like the House just approved delisting wolves.

1313
01:16:07,040 --> 01:16:09,479
Speaker 9: It hasn't gone through the Senate yet, and I don't

1314
01:16:09,560 --> 01:16:12,160
Speaker 9: know that it'll make it through the Senate. But that

1315
01:16:12,200 --> 01:16:14,639
Speaker 9: would throw a wrench into this whole thing, true, because

1316
01:16:15,479 --> 01:16:17,640
Speaker 9: then the Feds might not have the power to do

1317
01:16:17,680 --> 01:16:19,720
Speaker 9: what they want to do here. But there's also like

1318
01:16:20,800 --> 01:16:24,360
Speaker 9: this big beef going on between Trump and Polis.

1319
01:16:24,520 --> 01:16:24,680
Speaker 7: Uh.

1320
01:16:24,840 --> 01:16:28,000
Speaker 9: You know, Trump has beefs with a lot of governors

1321
01:16:28,000 --> 01:16:33,160
Speaker 9: from Democratic states. There was a water program.

1322
01:16:32,680 --> 01:16:35,200
Speaker 1: But he had that little hugathon with the new mayor

1323
01:16:35,360 --> 01:16:36,479
Speaker 1: of New York.

1324
01:16:37,200 --> 01:16:38,320
Speaker 2: Did they love each other?

1325
01:16:39,280 --> 01:16:41,720
Speaker 1: Which if I think of like a threat to America,

1326
01:16:42,280 --> 01:16:47,560
Speaker 1: I think of that dude. Yeah, a lot of threats

1327
01:16:46,560 --> 01:16:49,800
Speaker 1: that he's not managing wolves anywhere though, ye.

1328
01:16:53,240 --> 01:16:57,400
Speaker 9: But yeah, so like what was their name, Tina Peters?

1329
01:16:57,720 --> 01:16:57,880
Speaker 1: Then?

1330
01:16:58,000 --> 01:17:02,439
Speaker 9: Right, so there was the woman that what did she do? Randall?

1331
01:17:02,520 --> 01:17:06,400
Speaker 3: She was like she she was an elections clerk and she.

1332
01:17:08,920 --> 01:17:10,200
Speaker 2: After she certified the.

1333
01:17:10,160 --> 01:17:11,400
Speaker 9: Election, messing with stuff.

1334
01:17:11,439 --> 01:17:15,160
Speaker 3: She yeah, she lets someone come in and copy the

1335
01:17:15,200 --> 01:17:18,559
Speaker 3: hard drives off of their voting machines and gave them

1336
01:17:18,600 --> 01:17:21,040
Speaker 3: passwords to the voting machines and did a bunch of

1337
01:17:21,320 --> 01:17:22,000
Speaker 3: stuff like that.

1338
01:17:22,600 --> 01:17:24,839
Speaker 2: So she some some random guy from the internet.

1339
01:17:24,920 --> 01:17:28,080
Speaker 1: She got convicted of that, like violating her charter as

1340
01:17:28,120 --> 01:17:29,080
Speaker 1: an elections official.

1341
01:17:29,200 --> 01:17:32,360
Speaker 9: Trump pardoned her, but she was convicted under a on

1342
01:17:32,439 --> 01:17:38,679
Speaker 9: a state charge, so it was like a symbolic symbolic pardon,

1343
01:17:39,040 --> 01:17:41,400
Speaker 9: and Polis is like, yeah, it doesn't mean anything.

1344
01:17:41,960 --> 01:17:46,360
Speaker 1: Trump didn't like that, and then he blocked this water bill. Yes,

1345
01:17:47,479 --> 01:17:51,360
Speaker 1: the Laura Bobart was behind Lauren. Yeah. Yeah. And then

1346
01:17:51,400 --> 01:17:54,519
Speaker 1: she said, well, this is all about Epstein and other

1347
01:17:54,520 --> 01:17:57,759
Speaker 1: people are like, no, it's all about Yeah.

1348
01:17:57,920 --> 01:18:01,120
Speaker 9: Now I doubt Trump is like dig into like Wolf

1349
01:18:01,200 --> 01:18:02,840
Speaker 9: management in Colorado, but.

1350
01:18:03,080 --> 01:18:07,759
Speaker 1: Yeah, this is all in Brody's mind. In Brody's mind.

1351
01:18:07,520 --> 01:18:11,599
Speaker 9: I think it all comes back to the they have beef.

1352
01:18:11,920 --> 01:18:15,439
Speaker 1: They have beef, for sure, Yeah, they have beef. And

1353
01:18:15,479 --> 01:18:20,160
Speaker 1: it's like, hey, we're gonna make your life difficult. And

1354
01:18:20,160 --> 01:18:24,439
Speaker 1: and Polis and Polus's husband are big Wolf supporters. They are,

1355
01:18:24,560 --> 01:18:28,040
Speaker 1: so it could be He's like, I'm gonna stick it

1356
01:18:28,080 --> 01:18:31,000
Speaker 1: to young wolves too now. But he's got in that

1357
01:18:31,040 --> 01:18:35,880
Speaker 1: way though. This has been the state has by and large.

1358
01:18:36,000 --> 01:18:38,720
Speaker 1: If they had called me, I would have said, here's

1359
01:18:38,760 --> 01:18:40,320
Speaker 1: what I think you'll do about wolves, and it would

1360
01:18:40,439 --> 01:18:42,080
Speaker 1: not have been what they did. Yeah.

1361
01:18:42,120 --> 01:18:45,880
Speaker 9: That like, they bungled a lot of stuff badly unfortunately,

1362
01:18:45,880 --> 01:18:48,439
Speaker 9: because I have a lot of like love for Colorado

1363
01:18:48,520 --> 01:18:50,720
Speaker 9: Parks and wildlife. They I think they do a lot

1364
01:18:50,760 --> 01:18:52,960
Speaker 9: of great stuff. I just think this wolf thing was

1365
01:18:53,120 --> 01:18:54,200
Speaker 9: but this wasn't them.

1366
01:18:55,200 --> 01:18:57,720
Speaker 5: You can't. You can't the architects of this.

1367
01:18:57,960 --> 01:19:01,559
Speaker 9: But they got there. They were in charge of of

1368
01:19:01,680 --> 01:19:02,679
Speaker 9: releasing the wolves.

1369
01:19:02,720 --> 01:19:06,360
Speaker 1: They liken underdress that look.

1370
01:19:06,720 --> 01:19:11,240
Speaker 9: The director of CPW resigned because he was going to

1371
01:19:11,280 --> 01:19:12,639
Speaker 9: get canned over the wolf thing.

1372
01:19:13,400 --> 01:19:17,080
Speaker 1: But they did just for you know, I'm telling listeners,

1373
01:19:17,120 --> 01:19:19,519
Speaker 1: you already know the story. There was a there was

1374
01:19:19,560 --> 01:19:23,439
Speaker 1: a ballad initiative. In the ballad initiative, I can't remember

1375
01:19:23,479 --> 01:19:26,800
Speaker 1: the language, but the ballad initiative, when it passed, it

1376
01:19:26,960 --> 01:19:31,240
Speaker 1: set in motion the state agency.

1377
01:19:31,320 --> 01:19:31,880
Speaker 9: Yeah, they were.

1378
01:19:31,960 --> 01:19:35,080
Speaker 1: They used to make a plan and execute on a plan,

1379
01:19:35,840 --> 01:19:39,240
Speaker 1: and they were very quick to do it. They were.

1380
01:19:39,400 --> 01:19:42,519
Speaker 1: When I talked about the bungling is the world got

1381
01:19:42,640 --> 01:19:45,880
Speaker 1: very complicated for them as well. If you remember, because

1382
01:19:45,960 --> 01:19:50,639
Speaker 1: wolves were walking in from Wyom. It like everything got weird.

1383
01:19:51,439 --> 01:19:53,360
Speaker 1: And then other states were like, and I don't know

1384
01:19:53,360 --> 01:19:56,560
Speaker 1: why this is. Other states like I'm not giving you wolves.

1385
01:19:58,880 --> 01:20:03,800
Speaker 1: No one besides the state agency directors probably will ever

1386
01:20:03,960 --> 01:20:09,160
Speaker 1: know why that decision was made. I think the wild Idaho,

1387
01:20:09,560 --> 01:20:13,759
Speaker 1: Colorado would say I'm not giving you our wolves.

1388
01:20:13,080 --> 01:20:15,320
Speaker 9: Not Wyoming, Montana and Idaho.

1389
01:20:16,080 --> 01:20:20,360
Speaker 1: Sorry what I said, now, if someone could come explain

1390
01:20:20,439 --> 01:20:24,800
Speaker 1: to me, like what what phone conversation led to them

1391
01:20:24,880 --> 01:20:27,759
Speaker 1: saying We're not helping you out by giving you wolves

1392
01:20:28,120 --> 01:20:30,040
Speaker 1: which we're hunting.

1393
01:20:30,400 --> 01:20:33,000
Speaker 9: Well, I mean there had like there has been word

1394
01:20:33,040 --> 01:20:35,639
Speaker 9: out of Wyoming. They're like, we're not gonna help you

1395
01:20:36,800 --> 01:20:40,400
Speaker 9: put more wolves around our borders that can come back

1396
01:20:40,439 --> 01:20:45,280
Speaker 9: and yeah, but like if you put more wolves in Colorado,

1397
01:20:45,439 --> 01:20:46,839
Speaker 9: more wolves go back into.

1398
01:20:46,640 --> 01:20:49,040
Speaker 1: What like sure they'll want to get back home. Yeah.

1399
01:20:49,760 --> 01:20:52,160
Speaker 1: So that's and then and then they tried to work

1400
01:20:52,200 --> 01:20:55,719
Speaker 1: with they tried to work with tribal entities they did

1401
01:20:55,880 --> 01:20:58,720
Speaker 1: to get wolves, and then you know, I remember, you know,

1402
01:20:58,880 --> 01:21:00,439
Speaker 1: one was like, hey, you can have some of these

1403
01:21:00,439 --> 01:21:02,880
Speaker 1: ones that were dealing death to cattle.

1404
01:21:04,920 --> 01:21:08,120
Speaker 9: But they also the tribal thing didn't work out because

1405
01:21:10,520 --> 01:21:16,439
Speaker 9: they wanted the tribal like wildlife managers in Colorado to

1406
01:21:16,479 --> 01:21:20,080
Speaker 9: be able to have their own management authority over wolves

1407
01:21:20,080 --> 01:21:23,200
Speaker 9: that would end up in Colorado on reservations there, and

1408
01:21:23,520 --> 01:21:27,040
Speaker 9: they didn't agree to that anyway.

1409
01:21:27,720 --> 01:21:30,720
Speaker 1: Whether or not, it's like the vindictiveness of the administration

1410
01:21:31,000 --> 01:21:34,880
Speaker 1: and they are I mean, they are some vengeful cats. Yep.

1411
01:21:35,160 --> 01:21:37,800
Speaker 1: Like if that is driving this, I don't know, but

1412
01:21:37,880 --> 01:21:40,960
Speaker 1: I like, sure maybe, but I could picture this becoming

1413
01:21:40,960 --> 01:21:43,320
Speaker 1: an issue because this was a real This has been

1414
01:21:43,320 --> 01:21:47,000
Speaker 1: a sore This has been a sore subject for a

1415
01:21:47,040 --> 01:21:50,880
Speaker 1: lot of agricultural producers in Colorado. And these are people

1416
01:21:50,920 --> 01:21:53,720
Speaker 1: that will have the ear that will have the ear

1417
01:21:53,760 --> 01:21:57,720
Speaker 1: of the administration yep. And basically they're saying, you need

1418
01:21:57,760 --> 01:22:00,800
Speaker 1: to be you need the mandate to call Colorado is

1419
01:22:01,840 --> 01:22:03,800
Speaker 1: you need to operate with a lot more clarity about

1420
01:22:03,840 --> 01:22:06,040
Speaker 1: what's going on and what's your plan and whoever you moved,

1421
01:22:06,120 --> 01:22:08,160
Speaker 1: what wolves are you moved where? And what did they do?

1422
01:22:08,320 --> 01:22:11,320
Speaker 9: Yeah, and they've got to provide all that information and

1423
01:22:11,640 --> 01:22:15,120
Speaker 9: those plan details by February eighteenth, So a little over

1424
01:22:15,160 --> 01:22:17,559
Speaker 9: a month from now, we'll have some more information on this.

1425
01:22:17,960 --> 01:22:20,880
Speaker 1: Here's the funny part. Here's like another part about why

1426
01:22:20,920 --> 01:22:26,120
Speaker 1: this why their plan is peculiar. Colorado, So they got

1427
01:22:26,160 --> 01:22:28,600
Speaker 1: what do they got right now? Twenty to thirty? I

1428
01:22:28,680 --> 01:22:33,559
Speaker 1: think Colorado's goal is thirty to fifty. They have no

1429
01:22:34,320 --> 01:22:38,280
Speaker 1: mechanism in place. They don't even have a prayer of

1430
01:22:38,320 --> 01:22:43,040
Speaker 1: a mechanism in place to do any population control on

1431
01:22:43,080 --> 01:22:46,240
Speaker 1: wolves right thirty. When you say thirty to fifty, it's

1432
01:22:46,240 --> 01:22:51,680
Speaker 1: like you are just you are baiting. My kids use

1433
01:22:51,720 --> 01:22:55,439
Speaker 1: the term rage baiting, like for me to rage big

1434
01:22:55,560 --> 01:22:57,400
Speaker 1: rand I don't know how about that rage band rand

1435
01:22:57,560 --> 01:22:59,720
Speaker 1: say something to provoke, say sith, I know it's going

1436
01:22:59,760 --> 01:23:01,920
Speaker 1: to pay y'all. Yeah, it's easy to rage bait Randall.

1437
01:23:02,840 --> 01:23:04,920
Speaker 1: I was rage baiting you recently about some issue. I

1438
01:23:04,920 --> 01:23:09,920
Speaker 1: can't remember what it was. I think it was like

1439
01:23:10,439 --> 01:23:16,360
Speaker 1: gender issues around sports participations. I was rage bait and

1440
01:23:16,400 --> 01:23:19,080
Speaker 1: Randall he was sitting right rare, sitting right now, very effectively.

1441
01:23:19,080 --> 01:23:22,439
Speaker 1: I rage baited him. Now, I think when they go

1442
01:23:22,479 --> 01:23:24,519
Speaker 1: and say like, oh no, we just want thirty to fifty,

1443
01:23:24,680 --> 01:23:28,080
Speaker 1: you're like rage baiting wildlife managers because you're like, how

1444
01:23:28,160 --> 01:23:34,120
Speaker 1: in the world, what do you mean you don't have

1445
01:23:34,320 --> 01:23:38,840
Speaker 1: a pathway toward doing any kind of like control. There's

1446
01:23:38,920 --> 01:23:42,040
Speaker 1: no way in the state of Colorado under current regular

1447
01:23:42,120 --> 01:23:46,160
Speaker 1: rules and regulations, under the current administration, Colorado will never

1448
01:23:46,960 --> 01:23:50,400
Speaker 1: stop it at that, will never have a hunt. These

1449
01:23:50,439 --> 01:23:52,679
Speaker 1: are the same people that almost just damn near shut

1450
01:23:52,760 --> 01:23:57,040
Speaker 1: down bobcat hunting, mountain lion hunting. Colorado is never gonna

1451
01:23:57,080 --> 01:24:03,040
Speaker 1: have with this governor, Colorado will never have a wolf hunt.

1452
01:24:03,880 --> 01:24:05,519
Speaker 1: So when they're like, oh, we just want thirty.

1453
01:24:05,280 --> 01:24:06,920
Speaker 9: To fifty, they stop.

1454
01:24:07,040 --> 01:24:09,920
Speaker 1: But what stops it at fifty? Yeah, it's it's lunacy.

1455
01:24:10,000 --> 01:24:12,560
Speaker 1: It's like you're gonna have the way you have it

1456
01:24:12,680 --> 01:24:16,040
Speaker 1: set up, You're gonna have whatever the carrying capacity of

1457
01:24:16,080 --> 01:24:18,040
Speaker 1: the state is, which is way more than that.

1458
01:24:18,600 --> 01:24:21,679
Speaker 9: It's a lot. Considering how many in the state of College.

1459
01:24:21,760 --> 01:24:25,160
Speaker 1: It's like you have hundreds. When you say thirty to fifty,

1460
01:24:25,200 --> 01:24:27,719
Speaker 1: it's like, what would get what would give you that number?

1461
01:24:28,000 --> 01:24:30,880
Speaker 9: How many? How many are in Montana?

1462
01:24:31,520 --> 01:24:33,080
Speaker 1: Do we know seven hundred or something?

1463
01:24:33,120 --> 01:24:35,280
Speaker 9: Eightndred, Colorado's got twice as many.

1464
01:24:35,280 --> 01:24:38,360
Speaker 1: Elk as Man, don't say bleep that outfiit until we

1465
01:24:38,439 --> 01:24:43,080
Speaker 1: get the right number over one thousand, Okay, that's pretty good.

1466
01:24:43,160 --> 01:24:46,960
Speaker 1: Actually leave it in there. You make that louder.

1467
01:24:47,840 --> 01:24:51,120
Speaker 9: Sure, but we'll know more in the month.

1468
01:24:53,040 --> 01:24:58,880
Speaker 1: Yep, if they so a couple of things to watch.

1469
01:24:58,920 --> 01:25:01,240
Speaker 1: Here is a again, and I don't know what this

1470
01:25:01,280 --> 01:25:08,200
Speaker 1: will happen. Members of Congress are looking to dlist. This

1471
01:25:08,240 --> 01:25:10,320
Speaker 1: is where it is all. All this stuff gets so tricky.

1472
01:25:10,560 --> 01:25:12,880
Speaker 1: Members of Congress are moving to DLST wolves in the

1473
01:25:12,920 --> 01:25:17,680
Speaker 1: lower forty eight. So the House already has Yeah, so

1474
01:25:20,680 --> 01:25:24,800
Speaker 1: how previous administrations, how wolves have been managed? They've been

1475
01:25:24,800 --> 01:25:28,880
Speaker 1: managed by these distinct populations. So we talked about well,

1476
01:25:28,920 --> 01:25:33,800
Speaker 1: Northern Great Lakes, so the wolves in northern Michigan, Northern Wisconsin,

1477
01:25:34,040 --> 01:25:37,519
Speaker 1: northern Minnesota. We've toyed with do we dlist that little

1478
01:25:37,560 --> 01:25:40,200
Speaker 1: clump or not? And then we had this big conversation

1479
01:25:40,479 --> 01:25:42,160
Speaker 1: do we dlist in.

1480
01:25:42,760 --> 01:25:47,080
Speaker 9: Well they did dlist, they did, but I'm saying we

1481
01:25:47,240 --> 01:25:51,120
Speaker 9: used to talk about the wolf habitat as chunks.

1482
01:25:51,880 --> 01:25:55,479
Speaker 1: So we've had this long argument about the Northern Great

1483
01:25:55,560 --> 01:25:59,920
Speaker 1: Lakes list or d list. Oh so sorry, d list

1484
01:26:00,160 --> 01:26:03,519
Speaker 1: or not? And then the Northern Rockies d list or not?

1485
01:26:04,240 --> 01:26:07,920
Speaker 1: And it's been a ping pong. In the Northern Great Lakes,

1486
01:26:07,960 --> 01:26:11,799
Speaker 1: they were delisted. Then they were relisted in the Northern Rockies.

1487
01:26:11,880 --> 01:26:16,000
Speaker 1: They were delisted so you could still be fighting about

1488
01:26:16,000 --> 01:26:17,880
Speaker 1: like what about this little chunk of ground, what about

1489
01:26:17,880 --> 01:26:20,160
Speaker 1: this little chunk of ground. Now they're saying, you know what, bro,

1490
01:26:20,280 --> 01:26:27,240
Speaker 1: We're done talking about little chunks. We're talking about the

1491
01:26:27,280 --> 01:26:31,240
Speaker 1: country and not argue anymore about the Northern Great Lakes

1492
01:26:31,320 --> 01:26:33,280
Speaker 1: or whatever. Just like they're like done with it now,

1493
01:26:33,920 --> 01:26:38,240
Speaker 1: and it's like, this is one of the things. This

1494
01:26:38,320 --> 01:26:41,000
Speaker 1: is one of the things where people in wildlife politics,

1495
01:26:41,000 --> 01:26:42,599
Speaker 1: this is one of the things where people go wrong.

1496
01:26:42,880 --> 01:26:47,320
Speaker 1: Is you know Maduro the president of Venezuela.

1497
01:26:47,600 --> 01:26:49,280
Speaker 9: I've heard of them right now.

1498
01:26:50,920 --> 01:26:55,160
Speaker 1: A few days ago he had a great offer, not

1499
01:26:55,240 --> 01:27:00,559
Speaker 1: if you did prior to him getting detained. He was

1500
01:27:00,600 --> 01:27:05,160
Speaker 1: like like, here, listen, you, your cronies, your family, your henchmen,

1501
01:27:06,080 --> 01:27:09,360
Speaker 1: can go will drop sanctions and you can leave the

1502
01:27:09,400 --> 01:27:13,440
Speaker 1: country and you can go and do be in exile

1503
01:27:13,720 --> 01:27:21,120
Speaker 1: in Turkey. Take it or leave it. He didn't take it. Now,

1504
01:27:21,120 --> 01:27:23,200
Speaker 1: I'm not getting in the legality all I'm saying, they

1505
01:27:23,240 --> 01:27:27,080
Speaker 1: laid it out. He said, nope, not doing it. Now.

1506
01:27:27,320 --> 01:27:31,800
Speaker 1: He's sitting in jail in Brooklyn or Manhattan wherever. Hell.

1507
01:27:31,800 --> 01:27:36,439
Speaker 1: He is my message, my message to my message to

1508
01:27:36,520 --> 01:27:45,120
Speaker 1: people in wildlife politics. You screwed up by fighting the

1509
01:27:45,160 --> 01:27:48,960
Speaker 1: Northern Great Lakes. You've screwed up by fighting those agencies

1510
01:27:49,400 --> 01:27:53,479
Speaker 1: and not delisting in the Northern Great Lakes. You're screwing

1511
01:27:53,560 --> 01:27:56,519
Speaker 1: up by not delisting grizzly bears in the Northern Continental

1512
01:27:56,520 --> 01:28:00,240
Speaker 1: Divide ecosystem and in the Yellowstone the Greater Yellowstone ecosystem.

1513
01:28:00,280 --> 01:28:03,240
Speaker 1: Because what's gonna happen next is you're gonna you have

1514
01:28:03,320 --> 01:28:05,920
Speaker 1: a good offer on the table, you didn't take it.

1515
01:28:06,360 --> 01:28:08,360
Speaker 1: And what's gonna happen next is you're gonna wind up

1516
01:28:08,360 --> 01:28:12,000
Speaker 1: in a jail in Brooklyn, yep. Because they're gonna be like,

1517
01:28:12,080 --> 01:28:13,439
Speaker 1: I'm done dealing with you. Guys.

1518
01:28:14,360 --> 01:28:17,200
Speaker 9: No wolves are listening, blanket blanket.

1519
01:28:17,040 --> 01:28:21,600
Speaker 1: Because you shoot yourself in the foot by being unreasonable

1520
01:28:21,640 --> 01:28:24,559
Speaker 1: all the time. I don't even know who I'm talking to.

1521
01:28:26,120 --> 01:28:27,400
Speaker 7: There are so many.

1522
01:28:28,280 --> 01:28:29,080
Speaker 1: Do you follow me?

1523
01:28:29,479 --> 01:28:31,599
Speaker 7: Oh, I definitely follow It's.

1524
01:28:31,479 --> 01:28:34,559
Speaker 1: Just like you. They should have never they should have

1525
01:28:34,720 --> 01:28:37,120
Speaker 1: never blocked the D listing.

1526
01:28:37,160 --> 01:28:38,479
Speaker 5: You're not gonna get into the legality.

1527
01:28:38,880 --> 01:28:39,880
Speaker 4: We talked about this already.

1528
01:28:40,560 --> 01:28:42,840
Speaker 1: No no legality, here's the deal. But what I meant

1529
01:28:42,840 --> 01:28:47,360
Speaker 1: by that, the legality meaning like, uh, my kid was like, hey,

1530
01:28:47,439 --> 01:28:50,200
Speaker 1: is what they did in Venezuela illegal? And I'm like,

1531
01:28:50,479 --> 01:28:54,080
Speaker 1: anything that happens outside of the country, any conversation about

1532
01:28:54,080 --> 01:29:01,599
Speaker 1: being illegal or illegal is like by what mecham right,

1533
01:29:01,680 --> 01:29:05,320
Speaker 1: by what mechanism, Like, as far as I know, Putin's

1534
01:29:05,360 --> 01:29:09,240
Speaker 1: not incarcerated, right, people like the invasion of Ukraine was illegal,

1535
01:29:09,280 --> 01:29:13,479
Speaker 1: It's like, Okay, what are you doing? We have our

1536
01:29:14,040 --> 01:29:14,800
Speaker 1: who's not in jail?

1537
01:29:14,800 --> 01:29:18,479
Speaker 7: Trump's Joe procedure for generally how we enter.

1538
01:29:18,400 --> 01:29:23,120
Speaker 1: Into our jurisdiction. Are what the point I was making,

1539
01:29:23,160 --> 01:29:26,760
Speaker 1: I said, the legality of it is like within the

1540
01:29:26,880 --> 01:29:31,080
Speaker 1: US we have a system when when you start talking

1541
01:29:31,080 --> 01:29:35,240
Speaker 1: about global leaders we're like, oh, what what they did

1542
01:29:35,280 --> 01:29:39,320
Speaker 1: in North Korea was illegal? It's kind of like it's

1543
01:29:39,320 --> 01:29:42,440
Speaker 1: just it's academic. It's academic.

1544
01:29:43,320 --> 01:29:48,559
Speaker 7: Well, we have international governing Melosovich.

1545
01:29:48,880 --> 01:29:52,559
Speaker 1: Okay, tell that to Maduro. What I'm saying is generally,

1546
01:29:52,600 --> 01:29:54,719
Speaker 1: when you're talking about institutional law.

1547
01:29:54,680 --> 01:29:59,080
Speaker 8: I know, but when you're talking about when you're talking

1548
01:29:59,120 --> 01:30:03,960
Speaker 8: about global actions, when you're talking about global actions that

1549
01:30:04,200 --> 01:30:08,400
Speaker 8: like nation states that take global actions, and then pundits

1550
01:30:08,439 --> 01:30:09,360
Speaker 8: start talking about.

1551
01:30:09,120 --> 01:30:10,920
Speaker 1: I don't even know if this is legal, I just

1552
01:30:11,000 --> 01:30:16,920
Speaker 1: tune it out because I'm like, it's inconsequential. This isn't partisan,

1553
01:30:16,960 --> 01:30:18,880
Speaker 1: I would say. I would say it's like, it's inconsequence.

1554
01:30:18,920 --> 01:30:20,519
Speaker 3: I would say it no, not to make it. I'm

1555
01:30:20,560 --> 01:30:22,240
Speaker 3: not making it partisan. But I would say, like a

1556
01:30:22,360 --> 01:30:25,760
Speaker 3: nation that it that is sanctioned by international bodies and

1557
01:30:25,800 --> 01:30:30,559
Speaker 3: they can't feed people. They suffer consequences for doing things

1558
01:30:30,560 --> 01:30:33,400
Speaker 3: that are illegal under international law. It's like there are

1559
01:30:33,520 --> 01:30:36,400
Speaker 3: there are It's when the big guy on the block

1560
01:30:36,520 --> 01:30:40,280
Speaker 3: does it and there aren't consequences, it might still be illegal,

1561
01:30:40,280 --> 01:30:42,439
Speaker 3: but you get away with it. Yeah, but we but

1562
01:30:42,640 --> 01:30:46,320
Speaker 3: international bodies enforce international law all the time.

1563
01:30:46,640 --> 01:30:50,280
Speaker 1: When Saudi Arabia, whoever in Saudi Arabe, when they killed

1564
01:30:50,360 --> 01:30:54,479
Speaker 1: the journalist Koshogi mm hmm, people loved pointing out, boy,

1565
01:30:54,760 --> 01:30:58,719
Speaker 1: that's illegal, Like do you think do you think they care.

1566
01:31:00,200 --> 01:31:02,800
Speaker 7: Whether something is illegal?

1567
01:31:03,280 --> 01:31:05,600
Speaker 2: I don't remember people saying that was illegal.

1568
01:31:07,479 --> 01:31:10,160
Speaker 1: It was, but I don't remember. I don't remember.

1569
01:31:10,280 --> 01:31:10,959
Speaker 9: We're talking.

1570
01:31:13,080 --> 01:31:15,759
Speaker 3: No, but I don't remember the main talking point being

1571
01:31:15,800 --> 01:31:17,560
Speaker 3: that this is illegal.

1572
01:31:18,360 --> 01:31:19,720
Speaker 5: Send your correction.

1573
01:31:19,400 --> 01:31:22,479
Speaker 1: Here about this, because I don't know this is listen.

1574
01:31:22,800 --> 01:31:25,040
Speaker 1: No one listens to the show for international I don't know.

1575
01:31:25,080 --> 01:31:27,559
Speaker 1: I'm not good at internationals. I'm good at wildlife.

1576
01:31:28,640 --> 01:31:29,240
Speaker 5: Talking about.

1577
01:31:30,560 --> 01:31:32,719
Speaker 1: I was trying here's the deal. I just made a mistake.

1578
01:31:32,800 --> 01:31:36,600
Speaker 1: I was trying to draw some parallels, and I tiptoed

1579
01:31:36,680 --> 01:31:39,320
Speaker 1: out of my area of expertise by drawing some parallels.

1580
01:31:39,560 --> 01:31:43,320
Speaker 1: The comment I made about the legality is the whether

1581
01:31:43,439 --> 01:31:47,120
Speaker 1: or not, like the legality of US nabbing someone that

1582
01:31:47,120 --> 01:31:50,400
Speaker 1: we have under indictment who happens to lead another country,

1583
01:31:50,400 --> 01:31:52,280
Speaker 1: like I wasn't getting into that. What I was getting

1584
01:31:52,280 --> 01:31:57,160
Speaker 1: at was I was trying to draw parallels between when

1585
01:31:57,240 --> 01:32:01,439
Speaker 1: you when people and this this cut list is like

1586
01:32:01,600 --> 01:32:05,040
Speaker 1: a widespread issue. You have a sweet deal going and

1587
01:32:05,080 --> 01:32:08,439
Speaker 1: you don't take it, then you wind up getting stumng.

1588
01:32:09,120 --> 01:32:13,439
Speaker 1: My message to people who wolf preservationists and grizzly bear

1589
01:32:13,520 --> 01:32:20,559
Speaker 1: preservationists is you've had some very reasonable efforts from your

1590
01:32:20,600 --> 01:32:24,160
Speaker 1: own agency. The US Fish and Wildlife Service has moved

1591
01:32:24,720 --> 01:32:27,479
Speaker 1: to delist wolves in the Northern Great Lakes and for

1592
01:32:27,479 --> 01:32:30,800
Speaker 1: the US Fish and Wildlife Service has moved the agency,

1593
01:32:30,960 --> 01:32:35,599
Speaker 1: the federal agency in that's responsible for the management of

1594
01:32:35,640 --> 01:32:41,160
Speaker 1: the species, has moved to dlist for a very good reason,

1595
01:32:41,439 --> 01:32:44,880
Speaker 1: like because it because they met the recovery objectives. The

1596
01:32:46,360 --> 01:32:54,200
Speaker 1: animal rights organizations through legal action, block those delistings. That

1597
01:32:54,479 --> 01:32:58,840
Speaker 1: generates an enormous amount of hostility. And what you will

1598
01:32:58,880 --> 01:33:02,920
Speaker 1: then find is that people in the political world, people

1599
01:33:02,960 --> 01:33:07,360
Speaker 1: in leadership, are going to say, I'm now done playing around.

1600
01:33:08,600 --> 01:33:12,400
Speaker 1: I'm going around, and I'm doing it this way because

1601
01:33:12,400 --> 01:33:20,479
Speaker 1: I'm sick of these little mm hmm, petty, isolated instant arguments.

1602
01:33:22,720 --> 01:33:24,439
Speaker 1: Agree leaved out of it.

1603
01:33:25,800 --> 01:33:28,759
Speaker 3: You make a great if we still had creative names

1604
01:33:28,800 --> 01:33:31,240
Speaker 3: for podcast episodes, that could.

1605
01:33:31,080 --> 01:33:40,280
Speaker 6: Be and anybody wanting to know about Wolf de listing

1606
01:33:40,400 --> 01:33:41,719
Speaker 6: could obviously type.

1607
01:33:44,640 --> 01:33:48,200
Speaker 1: Because here's the deal man, Yeah, because here's the deal

1608
01:33:48,520 --> 01:33:51,639
Speaker 1: I am. I am a very avid reader of the news,

1609
01:33:52,840 --> 01:33:55,519
Speaker 1: but there's news that I understand the news that I

1610
01:33:55,560 --> 01:34:00,600
Speaker 1: try to understand. I understand wildlife news in America, but

1611
01:34:00,680 --> 01:34:03,479
Speaker 1: I don't understand. I just read it like I like

1612
01:34:03,560 --> 01:34:08,880
Speaker 1: to follow along, but I don't have informed opinion about it.

1613
01:34:09,000 --> 01:34:11,719
Speaker 1: So when I start talking about Venezuela, I would advise

1614
01:34:11,760 --> 01:34:17,599
Speaker 1: a listening to just tune out, don't change, don't listen

1615
01:34:17,600 --> 01:34:20,479
Speaker 1: to something different, but just turn it down. When I

1616
01:34:20,520 --> 01:34:21,200
Speaker 1: start talking.

1617
01:34:21,080 --> 01:34:24,040
Speaker 2: On the football, we're no football.

1618
01:34:24,120 --> 01:34:28,360
Speaker 5: Yeah, turn it down, no football, turn it up.

1619
01:34:28,760 --> 01:34:30,960
Speaker 7: You were like you were on a roll earlier today

1620
01:34:31,000 --> 01:34:32,759
Speaker 7: you're talking about over time.

1621
01:34:33,000 --> 01:34:35,559
Speaker 1: Yeah. I tiptoed into some areas I shouldn't. We should

1622
01:34:35,640 --> 01:34:37,519
Speaker 1: beleeve it all out. I tiptoed into some arias where

1623
01:34:37,520 --> 01:34:39,679
Speaker 1: I don't belong. I was just trying to be helpful.

1624
01:34:39,840 --> 01:34:44,120
Speaker 1: I was trying to be helpful some people. I'm trying

1625
01:34:44,160 --> 01:34:44,639
Speaker 1: to be helpful.

1626
01:34:44,880 --> 01:34:45,320
Speaker 5: It works.

1627
01:34:47,960 --> 01:34:48,920
Speaker 1: Is that it for news today?

1628
01:34:49,000 --> 01:34:51,960
Speaker 7: Yeah? We gotta stay tuned for all these things. These

1629
01:34:52,000 --> 01:34:54,799
Speaker 7: are continuing, ongoing issues.

1630
01:34:55,040 --> 01:34:57,960
Speaker 1: Let's make a plan then people can listen in on

1631
01:34:58,000 --> 01:35:01,800
Speaker 1: the plan making. How are we gonna really tackle the

1632
01:35:01,840 --> 01:35:07,439
Speaker 1: whole soup to nuts on federal subsistence programming history.

1633
01:35:07,760 --> 01:35:12,200
Speaker 9: We need to do a whole episode on it. You

1634
01:35:12,280 --> 01:35:14,839
Speaker 9: got plenty of people we could be talking to from Alaska.

1635
01:35:15,439 --> 01:35:19,880
Speaker 1: Like I didn't bring up the anachronism anilka, but a

1636
01:35:19,960 --> 01:35:24,240
Speaker 1: Milka ties into this. We're gonna tackle it because the

1637
01:35:24,280 --> 01:35:27,080
Speaker 1: reason I want this isn't just for people. Here's here's

1638
01:35:27,080 --> 01:35:28,600
Speaker 1: why I want to tackle this. A lot of the

1639
01:35:28,600 --> 01:35:33,599
Speaker 1: stuff we talk about on the show, it's like there's

1640
01:35:33,680 --> 01:35:36,960
Speaker 1: the thing, and then there's the sort of context of

1641
01:35:37,000 --> 01:35:40,439
Speaker 1: the thing, and so all these issues and Danger Species

1642
01:35:40,439 --> 01:35:45,920
Speaker 1: Act stuff, wolf delisting, you know, federal subsistence, Florida bear hunting.

1643
01:35:46,360 --> 01:35:50,640
Speaker 1: They're all these little they're interesting news stories. They're interesting

1644
01:35:50,800 --> 01:35:54,840
Speaker 1: events and occurrences that had happened. But by learning about them,

1645
01:35:56,479 --> 01:36:01,320
Speaker 1: you learn about how the hunting regulars that you live under.

1646
01:36:01,600 --> 01:36:03,639
Speaker 1: Like maybe you live in Indiana, which we haven't talked

1647
01:36:03,640 --> 01:36:07,439
Speaker 1: about today, you'll start to go like, oh, that's why

1648
01:36:07,720 --> 01:36:10,559
Speaker 1: stuff is the way it is where I live. By

1649
01:36:10,640 --> 01:36:12,960
Speaker 1: watching these things come up, and so it's more than

1650
01:36:13,040 --> 01:36:16,519
Speaker 1: just voyeurism of looking in at what's happening in other states,

1651
01:36:16,520 --> 01:36:21,880
Speaker 1: but it's I feel that it helps you better understand

1652
01:36:23,080 --> 01:36:26,600
Speaker 1: wildlife management where you live or where you go. Like

1653
01:36:26,640 --> 01:36:30,400
Speaker 1: the mechanisms at play, the terminology at play, the way

1654
01:36:30,479 --> 01:36:33,040
Speaker 1: that the Feds rub against the states, and they rub

1655
01:36:33,080 --> 01:36:36,200
Speaker 1: against the non governmental organizations and they rub against the

1656
01:36:36,840 --> 01:36:40,080
Speaker 1: and the animal rights lobbying arms, right, it's all. It

1657
01:36:40,120 --> 01:36:43,120
Speaker 1: all helps you put together a national picture of you know,

1658
01:36:43,160 --> 01:36:45,040
Speaker 1: when you go down to a river and you cast

1659
01:36:45,040 --> 01:36:47,040
Speaker 1: a baiting there and a fish bites and you pull

1660
01:36:47,040 --> 01:36:48,920
Speaker 1: the fish in, you go like, oh, that's why that

1661
01:36:48,920 --> 01:36:51,439
Speaker 1: fish is there, or that's why I can't keep that

1662
01:36:51,520 --> 01:36:52,800
Speaker 1: fish m hm.

1663
01:36:53,640 --> 01:36:55,960
Speaker 9: Yeah, and some of these saying like the Florida bear hunt,

1664
01:36:56,040 --> 01:36:59,280
Speaker 9: like might not seem like it's a national issue, but

1665
01:36:59,360 --> 01:37:02,720
Speaker 9: it is, like after what's happened in New Jersey and

1666
01:37:02,960 --> 01:37:06,960
Speaker 9: Washington and other places with bear hunting, like I consider

1667
01:37:07,000 --> 01:37:07,920
Speaker 9: it a national thing.

1668
01:37:08,040 --> 01:37:13,680
Speaker 1: Yeah, it's national news. Buddy, mm hmmm. All right, everybody.

1669
01:37:14,520 --> 01:37:17,920
Speaker 1: You know what else we didn't get into m the

1670
01:37:17,960 --> 01:37:24,240
Speaker 1: whole shootout in Michigan over Oh yeah, the whole shootout

1671
01:37:24,280 --> 01:37:25,719
Speaker 1: in Michigan over wild boards.

1672
01:37:28,120 --> 01:37:31,040
Speaker 9: Buddy deadly Tedy.

1673
01:37:30,120 --> 01:37:33,800
Speaker 1: Text about it, but we text a lot about c

1674
01:37:34,000 --> 01:37:35,439
Speaker 1: w D, and he knows that he and I don't

1675
01:37:35,479 --> 01:37:38,560
Speaker 1: agree on c w D, so he likes to inundate

1676
01:37:38,640 --> 01:37:48,240
Speaker 1: me with things arguing his perspective. But because he's he's like, he, yeah,

1677
01:37:48,280 --> 01:37:50,080
Speaker 1: we don't see eyed eye on it.

1678
01:37:50,120 --> 01:37:53,840
Speaker 7: Is there any other Is there any hog news coming

1679
01:37:53,880 --> 01:37:56,080
Speaker 7: out of other states? I haven't looked into that yet,

1680
01:37:56,120 --> 01:37:58,880
Speaker 7: Like populations.

1681
01:37:58,640 --> 01:38:00,639
Speaker 1: No, I don't know nothing super we're hot that I'm

1682
01:38:00,680 --> 01:38:03,280
Speaker 1: aware of. But the Michigan. We're gonna tell the Michigan.

1683
01:38:03,200 --> 01:38:04,639
Speaker 9: Something happened up in Canada.

1684
01:38:05,160 --> 01:38:06,679
Speaker 2: We're not still recording, are we, Phil?

1685
01:38:07,280 --> 01:38:10,040
Speaker 1: You should probably turn it off, Phil, you turn it off.

1686
01:38:09,960 --> 01:38:13,040
Speaker 7: Back, okay, bye see.

1687
01:38:13,040 --> 01:38:14,760
Speaker 3: I don't know if no one has their head set on,

1688
01:38:14,880 --> 01:38:37,960
Speaker 3: I have no idea