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Speaker 1: Oh hey, it's uncollective. Welcome to episode number eighty two.

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Speaker 1: We're here in snowy Bozeman, Montana a phil Yeah, the weather,

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Speaker 1: the weather has changed. It's winter. Yeah, skipped fall like

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Speaker 1: we usually do every every year. It yeah, it's skip fall.

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Speaker 1: I fall last about two days. We don't need fall.

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Speaker 1: But we got a great episode for you. Great would

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Speaker 1: be a loaded term. It's an interesting episode. We um

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Speaker 1: we have our editor in chief or at media or

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Speaker 1: anything to cut it on and we're gonna talk a

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Speaker 1: little bit about, you know, editorial decisions. How you make

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Speaker 1: a decision to run a podcast or not run a podcast,

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Speaker 1: what you want to do to it, whether to cut

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Speaker 1: it up. And that's because we had a very interesting,

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Speaker 1: uh and I would say contentious interview with Barry Gilbert.

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Speaker 1: Barry Gilberts author of a book called One of Us.

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Speaker 1: He was attacked by a grizzly bear in ninety seven

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Speaker 1: in yellow Stone and since then he's become a bear advocate. Uh.

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Speaker 1: He's also a biologist and a teacher. So we went

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Speaker 1: into the interview with a lot of interesting things to

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Speaker 1: talk about. We came out of it with a lot

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Speaker 1: of interesting sound bites and so you're gonna hear all

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Speaker 1: that coming up. But before we get to that, talk

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Speaker 1: about our friends at Yettie. Yet he was nice enough

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Speaker 1: recently to send me, not don't really send me. They

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Speaker 1: sent my son James a Rambler Junior twelve ounced kid's bottle.

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Speaker 1: He's got his name on it. Super cool, Phil, Your

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Speaker 1: kids are probably jealous. Yes, I told them all about it,

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Speaker 1: so they're very up. They started crying. I will pull

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Speaker 1: some strings to help him, Thank you so much. Maybe

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Speaker 1: even get Mango your dog personalized Yettie little Rambler. Yeah,

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Speaker 1: well maybe should get a dog bowl or a dog bit.

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Speaker 1: They also have those. Wow, I know it's legit over there.

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Speaker 1: Uh the Ramble Junior your kid's bottle. One for one thing,

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Speaker 1: as a small child, it's very hefty. Like to swing it,

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Speaker 1: you could really hurt another child now that I think.

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Speaker 1: I think it comes with pros and cons because because

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Speaker 1: you know they're going to drop it a lot wild Yes,

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Speaker 1: built for the child. I just made that up for

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Speaker 1: childs and wilds, so it's it's it's a great product

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Speaker 1: and he loves it. He carries it around, but to

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Speaker 1: swing it really could um. So just just a warning

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Speaker 1: once you get yours, Phil, don't let anybody whack your

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Speaker 1: kid with it. It's a great product though. Yeedie dot com,

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Speaker 1: Yedie dot com. Oh and first Light you have to

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Speaker 1: talk about them. You go to first Light dot com

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Speaker 1: right now, you're gonna see the mid season rut tree

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Speaker 1: stands set up from our boy Taylor Chamberlain. He's got

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Speaker 1: his whole system there. And another thing you ought to do?

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Speaker 1: Are my good buddy Mark Healy and are are very

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Speaker 1: good buddy, Ryan Callahan are in a film called Pressure.

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Speaker 1: If you don't know about Mark Heely, he's a world

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Speaker 1: class surfer, spear fisherman, everything Hawaii um and he learns

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Speaker 1: about the difference between hike and all mountains and swimming

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Speaker 1: in the water in this film. So you're gonna want

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Speaker 1: to go to first Light dot com. Check out those

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Speaker 1: a couple of things you're gonna enjoy it. And one

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Speaker 1: more thing, Phil, The inbox is flooding with not so

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Speaker 1: sharp moments. Unbelievable. I can't keep up. A lot of

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Speaker 1: them are getting tagged to spam, but I'm saving those

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Speaker 1: don't work, So we got lots of them. They want

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Speaker 1: to get their hands on a worksharp Field sharpener, Well,

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Speaker 1: work sharp, field Sharpener. Just so you know, if you

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Speaker 1: write into th HD at the Mediator dot com, we

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Speaker 1: told you this last week. But if you forgot, you're

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Speaker 1: right in your best not so sharp moment, your best

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Speaker 1: dumb story from some time outside or in. So we

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Speaker 1: don't really care where you were. Use your best pros.

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Speaker 1: And if we select you, work sharp is gonna send

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Speaker 1: you a field sharpener right to your house. Yes, entertaining concise, Yes,

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Speaker 1: just you know, story you tell your friends at a

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Speaker 1: bar or something not too short, not too long? Yeah right, Phil,

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Speaker 1: All right, let's get going, Episode number eighty two. Let's go.

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Speaker 1: I guess I grew up on an older road, a

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Speaker 1: bartle to the meadows. I always did what I've told

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Speaker 1: until I found out that my brand new clothes a

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Speaker 1: game second hand from the rich kids next door. And

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Speaker 1: I grew up fast. I guess I grew up. I mean,

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Speaker 1: there are a thousand things inside of my head I

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Speaker 1: wish I ain't seen, and now I just wanted through

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Speaker 1: a real bad dream or being, and like I'm coming

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Speaker 1: apart of the seems. But thank you Jack Daniel. No, Hey, everybody,

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Speaker 1: it's honey CECT Episode eighty two. What you know by now?

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Speaker 1: And we're here with Anthony Dakata, Hey man, Hey Ben,

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Speaker 1: what's going down? Well, I'm just trying to stay warm

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Speaker 1: in this beautiful fall weather. It's cold. It's cold in

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Speaker 1: this in the podcast studio, and we're we're going to

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Speaker 1: try we're gonna attempt to introduce an interview that you've

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Speaker 1: listened to, that I've listened to that Phil was a

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Speaker 1: part of. UM. I would say, it's how do you

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Speaker 1: describe How would you describe it? Anthony? Well, things escalated

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Speaker 1: quickly put it that way. He's got hot. Things got hot,

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Speaker 1: and um, it didn't. It didn't turned into as much

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Speaker 1: of a dialogue as I think that we had all hoped.

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Speaker 1: So let me introduce our character here, Barry Kay Gilbert.

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Speaker 1: And Barry is a a lot of things. Uh, he's

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Speaker 1: a bear advocate, he's a wildlife biologist. UM. But most notably,

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Speaker 1: he was attacked by a grizzly bear in nine seven

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Speaker 1: in Yelliston National Park. The grizzly bear, as you'll hear,

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Speaker 1: um removed parts of his face, scalped him um to

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Speaker 1: wear out one of his eyes. Some very gnarly, very

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Speaker 1: gnarly story that that he doesn't really like to sell

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Speaker 1: all that much. And I'm not real surprised he actually

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Speaker 1: teared up when we first started talking about it. And so,

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Speaker 1: you know, some decades later, he's still obviously, yeah, following

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Speaker 1: that tragedy that he's he's come back from, and so

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Speaker 1: in the years after he has become a bear advocate,

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Speaker 1: he's he's even in the moment as you're hearing the story,

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Speaker 1: he tells that he as he was fighting for his life,

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Speaker 1: he was asking those the rescuers to tell park rangers

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Speaker 1: not to kill the bear. Yeah, so I would say

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Speaker 1: he was. He was kind of there even before the attack.

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Speaker 1: And the attack, um, you know, it was a horrific experience,

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Speaker 1: but it only sort of drove him more, I think. Yeah.

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Speaker 1: So he was born in Kingston, Ontario, is a PhD

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Speaker 1: in zoology from Duke University, a lot of a lot

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Speaker 1: of street cred and has done came to Bosman to

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Speaker 1: do a bunch of public speaking events, and we were

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Speaker 1: hooked up with him and wanted to chat with him.

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Speaker 1: And really the impetus, as I think should be obvious

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Speaker 1: for a while, you'd want to talk to somebody like

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Speaker 1: that one. He went through a life changing experience about

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Speaker 1: as gnarly as it possibly gets with wild creatures, so

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Speaker 1: that that story is interesting. His rescue is interesting. We

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Speaker 1: do talk about that in the interview, the way that

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Speaker 1: he was rescued and how is his life was saved

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Speaker 1: by some very brave people. So that's interesting. But like

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Speaker 1: the turn, his turn really into a voice for bears,

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Speaker 1: grizzly bears specifically, um is interesting. It's just an interesting turn.

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Speaker 1: And he wrote a book called One of Us that

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Speaker 1: talks about his time with bears. He spent a lot

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Speaker 1: of time around bears. He feels very strongly, as you'll

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Speaker 1: hear soon about them. And it's interesting from an editorial perspective.

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Speaker 1: You're our editor in chief, Anthey, when we we decide

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Speaker 1: to have people on like this that had divergent views

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Speaker 1: from ours, and he does, I mean he is he

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Speaker 1: is I would say, clearly anti hunting, clearly more so

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Speaker 1: than I thought once we got him in the room.

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Speaker 1: But I knew that he was at some level against

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Speaker 1: killing bears. But that doesn't really bother me because I

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Speaker 1: think any conversation in this room can can have a

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Speaker 1: good outcome. So that's what we went into it with.

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Speaker 1: That's the editorial decision you're making there to try to

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Speaker 1: make sure to give this very interesting guy a voice

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Speaker 1: here his story and if possible, you know, workout come

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Speaker 1: to some sort of conclusion on what he believes about bears,

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Speaker 1: what hunters believe, what the North American model says, what

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Speaker 1: the endangered species X says. Get that all together in

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Speaker 1: a way that is compelling for you guys to listen to.

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Speaker 1: What's compelling? So I like, it's hard for me. I'm

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Speaker 1: not gonna go back and re listen to the interview

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Speaker 1: because it just is that contentious. Barry about thirty minutes

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Speaker 1: into it, threatened to leave. I talked him down off

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Speaker 1: that ledge, and then I would say, from there it

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Speaker 1: got it went off the rails even further than it

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Speaker 1: had uh to that point. And so you know, what

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Speaker 1: do you like when I when I'm thinking about this,

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Speaker 1: when we first got finished recording, I'm thinking should we

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Speaker 1: run this? You know? And so luckily you're here to

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Speaker 1: help me make that decision. Um So what's your what

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Speaker 1: do you think about this? Obviously we're gonna run it,

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Speaker 1: but what's the decision making process? I I think, um,

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Speaker 1: as you said to come in and have different people

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Speaker 1: come in here and talking about hunting and wildlife and

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Speaker 1: conservation and these kinds of issues. We don't all have

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Speaker 1: to agree. And what's interesting is when you get different perspectives. So,

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Speaker 1: you know, I think this was not exactly even what

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Speaker 1: we're hoping with that right, it does go off the rails.

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Speaker 1: It does get kind of weird. Um, But I think

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Speaker 1: it's useful to listen to, hopefully entertaining, but also useful because, um,

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Speaker 1: you get a sense of people who you know, maybe

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Speaker 1: have different values and we do and see things a

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Speaker 1: different way, and how um it can kind of color

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Speaker 1: you know, listen to this guy is experienced, he's knowledgeable,

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Speaker 1: he's a scientist. I don't doubt his cred but clearly

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Speaker 1: his views were his his beliefs were colored by his

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Speaker 1: personal views, just like ours are. And it came across

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Speaker 1: very clear, especially towards the end of the interview when

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Speaker 1: he starts getting to some others stuff. It's really what

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Speaker 1: he thought, Yeah, Trump guns, Yeah, you know the media

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Speaker 1: things like that. No, I think it's it illustrates that

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Speaker 1: one thing I think that is unfortunate here because I

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Speaker 1: think by all intents, coming into this bear seems to

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Speaker 1: be you know, a sharp guy with a lot of

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Speaker 1: great experience and things in part on folks with the

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Speaker 1: virgin views from again from mine. But I think what

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Speaker 1: this ends up showing, what's what's dangerous here is that

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Speaker 1: when you're so attached to a worldview like he is,

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Speaker 1: I mean, he's attached to this, the world view that

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Speaker 1: bear shouldn't be killed, that we should um do anything

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Speaker 1: we can to protect bears in their habitat and grow

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Speaker 1: their populations. He you become so attached to that worldview,

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Speaker 1: it's there. You can't see any other points of view,

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Speaker 1: or or at some level unwilling to to be moved

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Speaker 1: in one direction or the other. I mean that I

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Speaker 1: don't think there's any within conservation, especially within wild life.

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Speaker 1: I don't think that. I don't think you can lean

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Speaker 1: back on any universal truths because old Mother nature, the

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Speaker 1: natural world has very few universal truths. But when it

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Speaker 1: comes specifically to like large predators like grizzly bears, there

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Speaker 1: just isn't. You have to look at every ecosystem and

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Speaker 1: look at every animal. It's hard to just say kill

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Speaker 1: them all or save them all. It's just a tough

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Speaker 1: way to go, especially you know, you throw in their

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Speaker 1: human beings interaction with wildlife, and um, you know you're

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Speaker 1: not looking at it in a vacuum. You know there's

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Speaker 1: been development, there's been habitat loss. It can't go. Um,

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Speaker 1: you have to factor all those kinds of conflicts in.

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Speaker 1: And what she said is true, like you know, for

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Speaker 1: someone who has those plaefs. He kept Um, he didn't

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Speaker 1: seem to me that he wanted to be challenged. And

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Speaker 1: you know, he kept saying he did not want to

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Speaker 1: be He did not see. He kept calling saying that

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Speaker 1: you as a journalist, um, as if your role was

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Speaker 1: to just let him say whatever he wanted, just give

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Speaker 1: him a platform to say whatever he wanted without you

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Speaker 1: challenging him. And UM, you know you have been trained

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Speaker 1: as a journalist. We do a lot of journalism here,

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Speaker 1: but that's not exactly what this is either. You know

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Speaker 1: what we're it's a hunting collective. We very clearly have

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Speaker 1: certain set of beliefs, just like we're like, you know,

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Speaker 1: we like a nice walk on the beach whatever. Yeah,

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Speaker 1: you're right, I mean we have like And I told him,

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Speaker 1: I said, I'm not to be honest, I'm not a

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Speaker 1: grizzly bear hunting advocate. I'm not out there on the

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Speaker 1: stump for like, let's you have to hunt bears or else.

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Speaker 1: But I am an advocate of our model, the conservation,

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Speaker 1: and we should be able to talk about that in

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Speaker 1: a way that it's not confrontational and it's just looking

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Speaker 1: at hey, here have been the benefits of this model.

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Speaker 1: It's not perfect. As I said to him a few

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Speaker 1: times throughout the interview, he just wasn't having that now.

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Speaker 1: He didn't he didn't really want to talk about that.

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Speaker 1: He wanted to talk about what he wanted to talk

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Speaker 1: about and not be challenged on his points. That's that's

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Speaker 1: how I saw it to it, Phil, I mean, you

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Speaker 1: were in the room. It's like here's a man that

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Speaker 1: not you, Phil, but Barry that came in here. I'm

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Speaker 1: mean there was there was There was clear like anger

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Speaker 1: in the room. He his hands were shaking. He slammed

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Speaker 1: his book on the ground, on the on the table

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Speaker 1: once and it seemingly came came out of nowhere. Yeah,

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Speaker 1: I mean people will hear it. I mean I think

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Speaker 1: another thing, I think you mentioning valarious guys, to which

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Speaker 1: you'll hear in the interview he has a history with

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Speaker 1: without guys like seems seemed to be a personal one,

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Speaker 1: and I think that kind of changed the tone of

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Speaker 1: the conversation as well, Um, because those two men have

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Speaker 1: different views as well as a personal relationship. It sounded like, yeah,

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Speaker 1: they definitely had something professional interaction, right, Yeah, but he

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Speaker 1: he wanted to you know, when he got angry, he's

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Speaker 1: let's I didn't come here to talk about this, let's

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Speaker 1: stick to bears. But then the second half the interview

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Speaker 1: he got into some weird stuff that was far off

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Speaker 1: the topic. And that's where and that's where like being

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Speaker 1: respectful to Bear as I can be, um, and that's

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Speaker 1: where it where my decision making process kicks into. Do

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Speaker 1: we run this when somebody is just flying off the

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Speaker 1: handle about things that aren't germane to anything that we

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Speaker 1: sat down to chat about. And I'm not These aren't

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Speaker 1: things that I'm just gonna fly off the handle about.

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Speaker 1: If I'm gonna talk about him, I'm gonna be thoughtful,

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Speaker 1: I'm gonna be measured, and I'm gonna make sure the

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Speaker 1: person sitting in the room with me can contribute to

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Speaker 1: the conversation in a rational way. These are things that

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Speaker 1: so I'm just not going to jump into those conversations.

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Speaker 1: But for me, and I know a lot of people

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Speaker 1: say this, when we run these types of interviews, why

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Speaker 1: would you give this person a platform? Why does they

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Speaker 1: deserve a voice? Why do I have to be exposed

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Speaker 1: to this lines of thinking? But I think the opposite.

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Speaker 1: I think it's important to hear from folks that have

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Speaker 1: these perspectives. Um, We've done it a few times already

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Speaker 1: on the podcast. It has varying results. I mean, I

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Speaker 1: think again, this one, I think unfortunately for for for

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Speaker 1: Mr Gilbert, and maybe for this conversation even Um, I

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Speaker 1: think unfortunately he comes off a little bit like the

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Speaker 1: stereotypical animal rights advocate activists, and with someone who who

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Speaker 1: even as a biologist, showed a lot of emotion and

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Speaker 1: his reasoning and and the way that he spoke about bears,

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Speaker 1: which is something I think hunters always charge for for

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Speaker 1: these types of folks. Yeah, they're they're so wrapped in

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Speaker 1: these ideologies. They can't see past their love of an

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Speaker 1: animals see actually what it is, which is very surprising

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Speaker 1: given the fact that here's a guy who actually has

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Speaker 1: been has been around them, and has been attacked by one. Yeah. Absolutely,

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Speaker 1: and just what you said, I mean to give voice

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Speaker 1: or a platform for that. I think it is important

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Speaker 1: not only for us, but for for every everyone who

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Speaker 1: cares about these things to listen to that kind of stuff.

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Speaker 1: You know, you hear the comment that you know, living

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Speaker 1: in an echo chamber, right, if you're only around people who,

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Speaker 1: um say what you think, you're not going to understand

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Speaker 1: the bigger picture and what some threats are. You won't understand. Hey,

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Speaker 1: not everybody likes this, and this is what I have

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Speaker 1: to do to to get that point across about why

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Speaker 1: these these activities, why hunting is important, what it means

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Speaker 1: to me. Um, you won't be able to do that

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Speaker 1: if you don't understand or really hear other points of view.

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Speaker 1: And I think I would say that same thing to Berry, like,

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Speaker 1: if you're just gonna sit in this place and get

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Speaker 1: angry when somebody challenges you, you're never gonna be able

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Speaker 1: to articulate your ideas in a way that's meaningful. Um.

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Speaker 1: I said about it before. It's like taking your ideas

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Speaker 1: to the gym, you know, strengthen them up, because if

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Speaker 1: somebody they're sitting across from you that's intelligent, thoughtful and

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Speaker 1: can challenge you on some of the even the most

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Speaker 1: basis things that you believe. That's when you get to

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Speaker 1: understand really one if you're right, if there's any chinks

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Speaker 1: in the old armor, and two, UM, if you can

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Speaker 1: really defend the points that you think you can defend.

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Speaker 1: So it's something that you know in this us on

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Speaker 1: this show where we're really just talking to people that

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Speaker 1: I think is an important one introspection for me, but

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Speaker 1: also for our community. This is a person that UM

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Speaker 1: doesn't believe what we believe. And it's very clear in

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Speaker 1: this conversation that he did not believe we believe. And

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Speaker 1: it is a shame because I think there were some

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Speaker 1: points that he made that would be worth UM talking

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Speaker 1: about more in depth, but it didn't work out that way.

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Speaker 1: It's kind of undercut by a lot of the other stuff. Yeah,

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Speaker 1: I had a decision and Phil we talked about this.

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Speaker 1: I had a decision to make somewhere during the conversation

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Speaker 1: UM whether to just to to to push him very

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Speaker 1: hard and see exactly I'd be like, I just didn't

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Speaker 1: know what was going to happen. The dude was pretty

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Speaker 1: fired up. I didn't know if we were like he

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Speaker 1: was gonna stand up and throw something at me if

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Speaker 1: I continue to push him. Well, I think he handled

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Speaker 1: it good towards the end when he went off the rails.

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Speaker 1: And like you said, you didn't want to get into

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Speaker 1: a debate about something that had nothing to do with

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Speaker 1: what we're talking about. Even though it must have been

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Speaker 1: hard to bite your tongue, you just said, let's get

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Speaker 1: back to Barry exactly, and just in the time that

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Speaker 1: we had the animal rights activists on there in Berkeley,

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Speaker 1: it's similar. I mean you you end like and and

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Speaker 1: let me just say, for point of fact, after we

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Speaker 1: stopped recording, Barry Gilbert couldn't have been nicer, couldn't have

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Speaker 1: been nicer. He we had the conversation, he complimented my

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Speaker 1: interviewing skills. We talked about some of the paintings in

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Speaker 1: the office. He was asking about who the who the

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Speaker 1: artists were, and he said, he give me his card.

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Speaker 1: It was very it was just a nice interaction before

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Speaker 1: and after. And so there's there's something we'll let you

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Speaker 1: all get into it and hear it, but there's something

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Speaker 1: that happened within in this room, within the conversation that

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Speaker 1: kind of made it go off the rails, way off

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Speaker 1: the rails. So for a point of fact, just it's

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Speaker 1: I don't know what you're gonn to get out of

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Speaker 1: it other than just a couple of guys in a

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Speaker 1: room and it gets heated. Um, here Ben trying to

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Speaker 1: talk somebody out back into the room out. Yeah, it's like,

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Speaker 1: don't leave, man, I think we can do something here

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Speaker 1: because I I don't think I was fired up during it,

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Speaker 1: like a confused sure, absolutely confused, Um, like dumbfounded, like yeah, man,

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Speaker 1: what a lot of that happens in there? Um. But again,

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Speaker 1: I think all of these conversations they can't always go

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Speaker 1: to the script. They're not always going to be what

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Speaker 1: they're expected to be, and there's some learning from each

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Speaker 1: one of them. Um, I'll let you guys figure out

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Speaker 1: what the learning from this one. When you know, tell

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Speaker 1: us right in right into tc at dot com. So, um,

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Speaker 1: I don't think we're talking anymore about it. We're not

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Speaker 1: gonna have any other There's a lot going on in

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Speaker 1: the old right now. But I think it's proper to

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Speaker 1: just prep you for what you're about to hear and

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Speaker 1: then let you experience it, right Phil, Yeah, I think

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Speaker 1: I mean stick around and listen to it. Yeah, Phil

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Speaker 1: has to Phil has to edit these things, spend time

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Speaker 1: with it. I have to listen to it again, and

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Speaker 1: I'm kind of stressed out about it. Yeah, like I

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Speaker 1: destribe your stress stress feel like what Well. I I

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Speaker 1: was talking to Korean, our podcast producer upstairs yesterday. I'm

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Speaker 1: kind of like a cringe phobic person. So if I

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Speaker 1: can feel tension in a room or anything like that,

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Speaker 1: I just get very, uh uncomfortable intense and if I

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Speaker 1: have the option to leave the room, I will And

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Speaker 1: I could not leave the room during this interview. You

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Speaker 1: So I'm so I mean, but some people are are

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Speaker 1: a fan of that, you know, so stick around if

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Speaker 1: you want to to to be a part of it.

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Speaker 1: All right, We'll stick around for th HDS Most can

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Speaker 1: tentious interview ever with Dr Barry Kay Gilbert enjoy. I

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Speaker 1: guess I grew up on an alder road, Mr Barry Gilber.

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Speaker 1: How are you, sir? Very good? Nice to be in Bozeman. Yeah,

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Speaker 1: how are you enjoying your Bozeman times thus far? It's

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Speaker 1: been great. I'm staying up in the Mountain zeesa town

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Speaker 1: and uh, it's a really nice wild country. I'm gonna

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Speaker 1: be going down to Yellstone A couple of days too,

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Speaker 1: so that'll be good. Can never get enough of that country. Well,

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Speaker 1: welcome to to the media studios and to the Hunting Collective.

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Speaker 1: Thanks for coming and really appreciate your time. Uh. I

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Speaker 1: don't think I would guess that a lot of our

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Speaker 1: listeners are unaware of your story, which I'm I'm glad

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Speaker 1: to kind of go through it in detail. Yes, it was.

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Speaker 1: It was a time forty two years ago, and it's

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Speaker 1: in my book that I just written. Called one of

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Speaker 1: us a biologist walk among bears. I'll get my plug

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Speaker 1: in ear, but a trained professional. Yeah. I started out

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Speaker 1: with grizzly bear work, trying to work on human their interactions,

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Speaker 1: how people were affecting bears in Yellowstone and Uh I

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Speaker 1: was out with a graduate student, UH ten miles from

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Speaker 1: the nearest road up the Indian Creek Trail near a

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Speaker 1: Big Horn Pass and U I U saw grizzly bears

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Speaker 1: in the morning when we get up throum six o'clock,

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Speaker 1: and they were so far away that I suggested my

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Speaker 1: student we take a big circle around. UH. The bears

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Speaker 1: and bush whack up a distant ridge which was nine thousand,

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Speaker 1: two hundred feet the long and the short was that

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Speaker 1: he stopped for a nature call and I went over

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Speaker 1: the ridge and stayed lowd so I wouldn't get help

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Speaker 1: barking when they saw me on the skyline and I

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Speaker 1: was hunched older and moving swiftly, so I wouldn't the

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Speaker 1: up there on the skyline, And unfortunately I charged a

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Speaker 1: their lying and at Steve Dad and it was a

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Speaker 1: female with cuts, and uh she didn't think much of that.

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Speaker 1: In fact, she came out need like a freight train

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Speaker 1: with their claws hitting the ground and put me in

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Speaker 1: the hospital for two months. She basically took off the

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Speaker 1: side of my face, my nose and ears and scout me.

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Speaker 1: And I ended up with shortly short of a thousand

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Speaker 1: stitches in my head. But I had a magnificent rescue.

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Speaker 1: I told them not to kill that there. It was

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Speaker 1: something that I did in a surprise encounter with a

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Speaker 1: bad assumption, and uh I went back. Within a couple

426
00:23:45,280 --> 00:23:49,200
Speaker 1: of years, my student went to Assemity to study easier

427
00:23:49,359 --> 00:23:52,680
Speaker 1: easier going there's and he got a good master's thesis

428
00:23:52,680 --> 00:23:56,960
Speaker 1: out of that, and uh, I got an opportunity, I

429
00:23:57,000 --> 00:23:59,280
Speaker 1: think it was four or five years later, to go

430
00:23:59,359 --> 00:24:04,879
Speaker 1: to Captain National Park where now upwards of fifty or

431
00:24:04,960 --> 00:24:09,119
Speaker 1: sixty round there's come down on the salmon streams and

432
00:24:09,400 --> 00:24:12,359
Speaker 1: there are five hundred, six hundred people a day walking

433
00:24:12,400 --> 00:24:17,479
Speaker 1: along them. When I started the research in three UH

434
00:24:18,119 --> 00:24:21,840
Speaker 1: it was of course a time of fewer interactions, but

435
00:24:21,960 --> 00:24:25,920
Speaker 1: they still knew that the bears were being bumped off

436
00:24:26,000 --> 00:24:31,000
Speaker 1: the river. And UH I designed to study two, gather

437
00:24:31,320 --> 00:24:36,240
Speaker 1: very detailed data. Vote there numbers on the river and

438
00:24:36,320 --> 00:24:39,160
Speaker 1: people numbers through the day and through the week from

439
00:24:39,320 --> 00:24:43,400
Speaker 1: dantill dusk. We did sampling, a four hour sampling. Yeah,

440
00:24:43,400 --> 00:24:46,080
Speaker 1: the lot to unpack there when we rushed through some

441
00:24:46,119 --> 00:24:49,840
Speaker 1: stuff I want to definitely cover. I mean, it's seven

442
00:24:49,840 --> 00:24:52,560
Speaker 1: when the attack occurred, and you say forty two years

443
00:24:52,600 --> 00:24:57,080
Speaker 1: now from that time, and obviously so much of your

444
00:24:57,119 --> 00:25:00,240
Speaker 1: life has kind of been defined by by that moment

445
00:25:00,280 --> 00:25:03,240
Speaker 1: when you you know, when you look back on that day. Um,

446
00:25:03,280 --> 00:25:06,000
Speaker 1: there's so much to go through. But I thought the

447
00:25:06,040 --> 00:25:08,200
Speaker 1: most amazing part as I'm reading your story and people

448
00:25:08,200 --> 00:25:10,600
Speaker 1: can read it in one of us, UM, and I

449
00:25:10,600 --> 00:25:13,480
Speaker 1: was reading your stories as you've written, you're talking about

450
00:25:13,480 --> 00:25:18,000
Speaker 1: the rescue. You know, a thousand suitures, you're basically scalped,

451
00:25:18,200 --> 00:25:22,000
Speaker 1: You're you're losing a bunch of blood. And then how

452
00:25:22,080 --> 00:25:23,960
Speaker 1: you are rescued that day. Can we go through that,

453
00:25:24,359 --> 00:25:28,240
Speaker 1: you know, the moment that that your your student Bruce

454
00:25:28,280 --> 00:25:30,159
Speaker 1: found you and then and then called this in And

455
00:25:31,040 --> 00:25:34,520
Speaker 1: that's very interesting to me. Yeah, the short story, there's

456
00:25:34,520 --> 00:25:38,520
Speaker 1: a whole chapter. Actually, the second chapter is the Martless rescue.

457
00:25:38,640 --> 00:25:42,119
Speaker 1: I had, Uh we had a park Service radio and

458
00:25:42,200 --> 00:25:47,960
Speaker 1: my student ticked that up and got onto the main

459
00:25:48,119 --> 00:25:50,720
Speaker 1: channel with the park Service. They shut down the whole

460
00:25:50,760 --> 00:25:56,320
Speaker 1: communication system just to talk to us, and uh and uh,

461
00:25:56,960 --> 00:26:00,280
Speaker 1: my students said that I was badly enough injured. Well,

462
00:26:00,359 --> 00:26:02,760
Speaker 1: he asked me how I was, and I occurred to

463
00:26:02,800 --> 00:26:07,280
Speaker 1: the gargled, I'm okay, I think I'm me I'm still alive.

464
00:26:07,359 --> 00:26:11,560
Speaker 1: But then I thought, Bruce, tell him I'm dying, because

465
00:26:11,600 --> 00:26:14,240
Speaker 1: I really was dying. I was bleeding out right there.

466
00:26:14,840 --> 00:26:20,359
Speaker 1: And uh. They launched a small Nash type helicopter. They

467
00:26:20,359 --> 00:26:26,480
Speaker 1: found a plilot downtown shopping Jim Thompson. Yeah, Nartilius guy.

468
00:26:26,600 --> 00:26:31,000
Speaker 1: Uh and he got in this sort of rickety uh

469
00:26:31,280 --> 00:26:36,920
Speaker 1: uh helicopter that was losing its supercharger and he's coming

470
00:26:36,960 --> 00:26:39,399
Speaker 1: in at nine thousand feet trying to pick up a

471
00:26:39,440 --> 00:26:41,720
Speaker 1: guy in a windstorm, I mean the air out there,

472
00:26:41,880 --> 00:26:45,160
Speaker 1: and he couldn't land next to me anyway. He landed

473
00:26:45,160 --> 00:26:48,640
Speaker 1: in the small valley next door. Uh, and he brought

474
00:26:48,680 --> 00:26:51,359
Speaker 1: with him Tom Black, who was the leader of the

475
00:26:51,400 --> 00:26:57,000
Speaker 1: rescue operations, and Uh, Tom realized when he saw me

476
00:26:57,200 --> 00:27:01,479
Speaker 1: with Jim that they needed some serious help there. So

477
00:27:01,520 --> 00:27:06,119
Speaker 1: they called smoke jumpers from West Jellostone smoke jump base,

478
00:27:06,760 --> 00:27:12,480
Speaker 1: and a d C three launched from there with eight

479
00:27:12,520 --> 00:27:17,400
Speaker 1: smoke jumpers who dropped packages right almost hit me. Uh

480
00:27:17,480 --> 00:27:22,440
Speaker 1: and uh. The guys did a nartilust job getting me stabilized,

481
00:27:22,680 --> 00:27:26,359
Speaker 1: and they took me down to Lake Hospital, which was

482
00:27:26,440 --> 00:27:31,200
Speaker 1: maybe twenty minutes by chopper and uh lo and behold,

483
00:27:31,359 --> 00:27:36,760
Speaker 1: the University Utah Medical Center had rotated in for Vietnam

484
00:27:36,920 --> 00:27:39,720
Speaker 1: Toronto surgeons who are just going up for a couple

485
00:27:39,760 --> 00:27:42,720
Speaker 1: of weeks at a clinic. And so these guys had

486
00:27:42,760 --> 00:27:45,760
Speaker 1: seen people blown apart by shrapnel and all kinds of

487
00:27:46,119 --> 00:27:51,280
Speaker 1: nasty wounds. And they further stabilized me, and then the

488
00:27:51,359 --> 00:27:54,960
Speaker 1: ambulance took me out to West Yellowstone Airport and a

489
00:27:55,080 --> 00:27:58,119
Speaker 1: Salt Lake had sent up a basically a flying operating

490
00:27:58,200 --> 00:28:02,520
Speaker 1: room and got me down and they started working on

491
00:28:02,600 --> 00:28:07,159
Speaker 1: the love them clock at night and eleven hour surgery

492
00:28:08,080 --> 00:28:11,480
Speaker 1: closing all those wounds, and of course then you gotta

493
00:28:11,520 --> 00:28:15,560
Speaker 1: beat the section infections. Infections. Every time we talk about

494
00:28:15,600 --> 00:28:17,480
Speaker 1: bear attacks, that's that's the thing that you try to

495
00:28:17,480 --> 00:28:19,399
Speaker 1: talk about, is when you have an open wound that

496
00:28:19,480 --> 00:28:22,760
Speaker 1: was caused by an animal. They've got one filthy mouth, yeah,

497
00:28:22,960 --> 00:28:24,639
Speaker 1: and they can't and you can't really just close that

498
00:28:24,640 --> 00:28:29,960
Speaker 1: wind right back up. I was just colored with toodes. Yeah,

499
00:28:30,119 --> 00:28:32,200
Speaker 1: that's unbelievable. I can laugh now. It's sort of like

500
00:28:32,280 --> 00:28:35,240
Speaker 1: gallows here there. But it was nip and tuck. I

501
00:28:35,840 --> 00:28:37,800
Speaker 1: my attempt at shur in the hospital kept going out

502
00:28:37,840 --> 00:28:39,480
Speaker 1: around a hundred and four. You know, I could have

503
00:28:39,520 --> 00:28:42,440
Speaker 1: clocked out right then right then. Do you ever do

504
00:28:42,440 --> 00:28:46,160
Speaker 1: you think of moments during during I'm sure what was

505
00:28:46,280 --> 00:28:50,360
Speaker 1: kind of like a and very intense and very wild

506
00:28:50,520 --> 00:28:52,400
Speaker 1: whirlwind to get out of there, to get you know,

507
00:28:52,480 --> 00:28:55,560
Speaker 1: there's some serendipity involved with with your medical care too.

508
00:28:56,800 --> 00:28:58,680
Speaker 1: It was there moments in there where you thought, you know,

509
00:28:58,760 --> 00:29:01,840
Speaker 1: this is this is it for me? You need dying

510
00:29:01,960 --> 00:29:07,680
Speaker 1: or or the end of the research either both. Just

511
00:29:07,760 --> 00:29:10,720
Speaker 1: I'm interested in moments during that time that's a good question.

512
00:29:10,840 --> 00:29:13,560
Speaker 1: I don't dwell on that, and I don't like to

513
00:29:13,560 --> 00:29:18,200
Speaker 1: talk publican too much about it, but uh, you know,

514
00:29:18,280 --> 00:29:20,840
Speaker 1: you get a TV producer, stick of candle in your

515
00:29:20,840 --> 00:29:23,360
Speaker 1: face and Dr Gilder, howd you feel when you lost

516
00:29:23,400 --> 00:29:24,920
Speaker 1: your face and you thought you were going to die

517
00:29:24,960 --> 00:29:27,120
Speaker 1: in your family was going to be without a husband,

518
00:29:27,480 --> 00:29:31,400
Speaker 1: And I thought, you know, f you dons of those

519
00:29:31,480 --> 00:29:36,000
Speaker 1: kind of things. But I realized that I was close

520
00:29:36,040 --> 00:29:37,880
Speaker 1: to death. And one day in the hospital, I was

521
00:29:37,880 --> 00:29:42,760
Speaker 1: watching television and I saw turtle walk across on the

522
00:29:42,800 --> 00:29:45,600
Speaker 1: television screen and I started to cry and I couldn't

523
00:29:45,640 --> 00:29:49,640
Speaker 1: stop crying. I knew I was going to live. So, yeah,

524
00:29:49,720 --> 00:29:54,280
Speaker 1: there you go. I choke him out the already years later. Yeah,

525
00:29:54,600 --> 00:29:56,880
Speaker 1: but we're not gonna We're not gonna go. I just

526
00:29:56,920 --> 00:30:00,000
Speaker 1: wanted to, you know, kind of just understand a little

527
00:30:00,040 --> 00:30:02,960
Speaker 1: bit of well, and it's a reasonable question because then

528
00:30:03,000 --> 00:30:04,880
Speaker 1: the next one is, well, how the heck did you

529
00:30:05,080 --> 00:30:08,360
Speaker 1: decide to go back and study even bigger? There's exactly

530
00:30:08,520 --> 00:30:12,040
Speaker 1: so exactly and when you're it's it's hard to And

531
00:30:12,080 --> 00:30:14,560
Speaker 1: again we were talking before this, we I know, with

532
00:30:14,680 --> 00:30:16,960
Speaker 1: this podcast and with our company or to media or

533
00:30:17,000 --> 00:30:19,479
Speaker 1: were a media company, and we know we look at

534
00:30:19,480 --> 00:30:22,040
Speaker 1: the numbers, we look at what people want to hear about,

535
00:30:22,080 --> 00:30:24,840
Speaker 1: and when we talk about bear attacks, more people listen,

536
00:30:25,480 --> 00:30:28,760
Speaker 1: more people pay attention, and we don't. You know, I'm

537
00:30:28,760 --> 00:30:30,400
Speaker 1: not going to base our audience to say it's just

538
00:30:30,440 --> 00:30:33,680
Speaker 1: a sensationalist part of it, but there is some version

539
00:30:33,720 --> 00:30:35,800
Speaker 1: of that intrigue for well, you know, there's a lot

540
00:30:35,840 --> 00:30:39,200
Speaker 1: of both ignorance and fear, and that's very normal. I

541
00:30:39,200 --> 00:30:43,080
Speaker 1: don't say that to the majority towards people, but if

542
00:30:43,120 --> 00:30:45,880
Speaker 1: we really want to fear something, we had to fear

543
00:30:45,960 --> 00:30:49,320
Speaker 1: the automo deal it. It kills and names more people,

544
00:30:49,360 --> 00:30:54,040
Speaker 1: and you can go on YouTube or whatever and see

545
00:30:54,840 --> 00:30:58,160
Speaker 1: people's arms with their watch still on and that there's

546
00:30:58,200 --> 00:31:01,920
Speaker 1: torn and pieces. You don't see that with automobiles. All

547
00:31:01,920 --> 00:31:05,360
Speaker 1: that sort of stuff happens and you don't get visuals

548
00:31:05,440 --> 00:31:08,320
Speaker 1: of it. Actually, my wife, as I was going out

549
00:31:08,360 --> 00:31:10,240
Speaker 1: hunting not too long a couple weeks ago, she said,

550
00:31:10,280 --> 00:31:11,960
Speaker 1: are there gonna be bears? Are you gonna get attacked?

551
00:31:11,960 --> 00:31:13,560
Speaker 1: And there's been bear at tax recently. I said, I'm

552
00:31:13,560 --> 00:31:15,880
Speaker 1: more it's more dangerous for me to drive over to

553
00:31:15,920 --> 00:31:17,960
Speaker 1: the hunting spot because I I've been there than it

554
00:31:18,040 --> 00:31:19,600
Speaker 1: is to actually out there, and I believe I believe

555
00:31:19,640 --> 00:31:23,360
Speaker 1: that solely, and I don't let My personal belief is

556
00:31:23,440 --> 00:31:26,640
Speaker 1: I can't let that inherent there's danger and inherited everything,

557
00:31:27,120 --> 00:31:30,200
Speaker 1: and to sensationalize one version of it, because it seems

558
00:31:30,200 --> 00:31:31,959
Speaker 1: a little bit more visceral, a little bit more scary,

559
00:31:32,360 --> 00:31:35,320
Speaker 1: it's just not intellectually honest for me. So I just

560
00:31:35,360 --> 00:31:39,440
Speaker 1: try to sing with everything. Only the sociologists could tell

561
00:31:39,520 --> 00:31:43,280
Speaker 1: us why we're so obsessed with carnivores attacking people. Maybe

562
00:31:43,280 --> 00:31:46,480
Speaker 1: it's a control thing, but look at the numbers of

563
00:31:46,560 --> 00:31:50,960
Speaker 1: people have been dying from otioid. It's seven hundred thousand people.

564
00:31:51,240 --> 00:31:54,600
Speaker 1: Yet too grizzly. Their attacks will get held a lot

565
00:31:54,640 --> 00:31:58,320
Speaker 1: more pressed than all these deaths of fine young people

566
00:31:58,880 --> 00:32:01,960
Speaker 1: that are on a draw that shouldn't be on the market. Yeah,

567
00:32:01,960 --> 00:32:05,040
Speaker 1: you know that that there's those comparisons are they're pretty

568
00:32:05,040 --> 00:32:08,360
Speaker 1: stark when you start to think about how like you said,

569
00:32:08,400 --> 00:32:10,360
Speaker 1: one and we've we've had, like I said, four bear

570
00:32:10,480 --> 00:32:12,960
Speaker 1: tacks in the Gravelly Mountain range here in south of

571
00:32:13,000 --> 00:32:16,760
Speaker 1: Bosan recently, and when I was traveling around prior to

572
00:32:16,760 --> 00:32:19,440
Speaker 1: Elk opening day, we had more I had more conversations

573
00:32:19,440 --> 00:32:21,560
Speaker 1: with hunters that I know in the industry and without

574
00:32:21,560 --> 00:32:25,200
Speaker 1: the industry that about grizzy bears and I did about ELK.

575
00:32:25,520 --> 00:32:27,520
Speaker 1: We weren't talking about like what did you see? What

576
00:32:27,560 --> 00:32:29,240
Speaker 1: bull were you on? We're talking about are there grizzly

577
00:32:29,280 --> 00:32:31,800
Speaker 1: bears in your area? And the other thing about hunters

578
00:32:31,920 --> 00:32:35,240
Speaker 1: is some of them have the John Wayne neath that.

579
00:32:35,400 --> 00:32:38,240
Speaker 1: If they've got a three fifty seven magnum or something,

580
00:32:38,320 --> 00:32:41,680
Speaker 1: they'll be stopping that there. Believe me, you won't be

581
00:32:41,760 --> 00:32:44,960
Speaker 1: stopping there with a tistel. Your arms will be jumping

582
00:32:45,040 --> 00:32:47,840
Speaker 1: like like your heart, it'll be trying to get out

583
00:32:47,840 --> 00:32:51,880
Speaker 1: of your chest. And unless you've had combat training, Uh,

584
00:32:52,040 --> 00:32:54,080
Speaker 1: if you really wanted to defend yourself to something like

585
00:32:54,120 --> 00:32:56,680
Speaker 1: a short barrel shotgun or a testle, go to a

586
00:32:56,720 --> 00:32:58,720
Speaker 1: garbage don't get one of your friends to roll a

587
00:32:58,760 --> 00:33:02,280
Speaker 1: truck tired down at you from the hill. And you

588
00:33:02,320 --> 00:33:05,960
Speaker 1: stop that truck dire tire with a with a pistol

589
00:33:06,080 --> 00:33:09,600
Speaker 1: or a shotgun. And if you can stand there and

590
00:33:09,680 --> 00:33:14,160
Speaker 1: stop that remaining cool, you'd be okay with killing it there.

591
00:33:14,240 --> 00:33:17,959
Speaker 1: But who wants to kill it there? What do you mean, spray?

592
00:33:18,480 --> 00:33:21,520
Speaker 1: I'm a believer. I think the studies of it are

593
00:33:21,680 --> 00:33:26,160
Speaker 1: are sufficient. Uh. People always say, well, it doesn't work

594
00:33:26,280 --> 00:33:30,080
Speaker 1: every time. Well, of course it doesn't work every time. Uh,

595
00:33:30,560 --> 00:33:34,760
Speaker 1: skunks developed pretty good bear spray and they still get eaten.

596
00:33:35,320 --> 00:33:41,040
Speaker 1: So you know, Uh, but it's it'll blind and make

597
00:33:41,120 --> 00:33:45,080
Speaker 1: the bears choke and filler lungs. And people say, oh,

598
00:33:45,080 --> 00:33:47,400
Speaker 1: well of the window blow back. No it won't. It's

599
00:33:47,440 --> 00:33:51,160
Speaker 1: got so much pressure with that gas, it'll just go out. Uh.

600
00:33:51,320 --> 00:33:53,160
Speaker 1: You know, I've shown people how to use it lots

601
00:33:53,160 --> 00:33:57,560
Speaker 1: of times. I'm a believer. But you know, the unknown

602
00:33:57,680 --> 00:34:00,720
Speaker 1: aspect of it is that when you stay and there

603
00:34:00,720 --> 00:34:04,560
Speaker 1: with your weapon there spray, your behavior is tells that

604
00:34:04,640 --> 00:34:08,320
Speaker 1: there that you're not a chicken. If if you don't

605
00:34:08,360 --> 00:34:11,400
Speaker 1: have a bear spray, your instinct is to run, which

606
00:34:11,440 --> 00:34:14,759
Speaker 1: I did, because you have to get some distance. Maybe

607
00:34:14,760 --> 00:34:19,080
Speaker 1: you can collapse, maybe you can wet your pants. But um,

608
00:34:19,120 --> 00:34:23,520
Speaker 1: if you're holding bear spray, you're standing facing the bear,

609
00:34:23,920 --> 00:34:25,920
Speaker 1: and of course you have to believe it's gonna work,

610
00:34:26,840 --> 00:34:30,040
Speaker 1: which it does. Then the bear says, hell, no, I

611
00:34:30,120 --> 00:34:32,319
Speaker 1: was just wanted to chase you, but I don't want

612
00:34:32,360 --> 00:34:34,880
Speaker 1: to fight you. Yeah, you and what choice you like

613
00:34:34,920 --> 00:34:36,880
Speaker 1: you said, what choices when when you're facing down a

614
00:34:36,920 --> 00:34:38,440
Speaker 1: bear like that. There's a lot of things you can

615
00:34:38,480 --> 00:34:40,799
Speaker 1: say you would do, but until you've been in that situation,

616
00:34:41,040 --> 00:34:43,520
Speaker 1: I would like to say, you know, we were talking

617
00:34:43,520 --> 00:34:46,600
Speaker 1: about this, h one of our editors outside early today,

618
00:34:46,600 --> 00:34:49,400
Speaker 1: when we were thinking about you coming in. I was saying,

619
00:34:49,400 --> 00:34:52,960
Speaker 1: like carrying a pistol, we all think, oh, we'll do it.

620
00:34:52,960 --> 00:34:55,279
Speaker 1: It's just I'd like to have both rather than just one.

621
00:34:56,120 --> 00:34:57,799
Speaker 1: I was thinking of, and it's something I had never

622
00:34:57,840 --> 00:35:01,160
Speaker 1: really considered, is that I feel safer with a pistol

623
00:35:01,160 --> 00:35:03,080
Speaker 1: in my hand than I do bear spray, just innately,

624
00:35:03,320 --> 00:35:06,279
Speaker 1: just sure, I feel the pistols more powerful, so I'm

625
00:35:06,280 --> 00:35:08,840
Speaker 1: probably gonna reach that for before I reach for bear spray.

626
00:35:08,920 --> 00:35:11,919
Speaker 1: But to your point, and I've I've shot three gun

627
00:35:11,960 --> 00:35:14,799
Speaker 1: matches in different competitions where in practice I can hit

628
00:35:15,360 --> 00:35:17,080
Speaker 1: you know, I can hit a pretty I can hit

629
00:35:17,120 --> 00:35:18,960
Speaker 1: the ten ring with the pistol. And then when somebody's

630
00:35:18,960 --> 00:35:21,600
Speaker 1: behind me timing me, and they're fifteen other people watching,

631
00:35:21,640 --> 00:35:23,400
Speaker 1: and I've got to run up to a thing and shoot,

632
00:35:23,680 --> 00:35:26,600
Speaker 1: there's any pressure applied. I am the most inaccurate person

633
00:35:27,080 --> 00:35:29,120
Speaker 1: that you could ever So to try to even compare

634
00:35:29,120 --> 00:35:32,600
Speaker 1: to that, which is, you know, tangibly comparable to the

635
00:35:32,680 --> 00:35:36,000
Speaker 1: moment of frenzy and there's a bear, you know, coming down,

636
00:35:36,040 --> 00:35:38,319
Speaker 1: and I think it's it's it's difficult to do well,

637
00:35:38,480 --> 00:35:40,759
Speaker 1: you know. I was on the ground with There's a

638
00:35:40,800 --> 00:35:44,279
Speaker 1: lot and we did some darting for collering for a

639
00:35:44,360 --> 00:35:49,040
Speaker 1: lawge owner. I don't do any callering myself for nine projects.

640
00:35:49,040 --> 00:35:53,640
Speaker 1: But whenever I was out on the ground, I carried

641
00:35:53,719 --> 00:36:02,279
Speaker 1: a shotgun pump mossburg with you know, slugs and deer

642
00:36:02,320 --> 00:36:07,920
Speaker 1: shot buck shot, and I I figured always carried their spray,

643
00:36:07,920 --> 00:36:10,200
Speaker 1: and their spray was the first reach for me. I'm

644
00:36:10,239 --> 00:36:13,200
Speaker 1: not a I'm a gun guy, but I'm not a

645
00:36:13,840 --> 00:36:18,399
Speaker 1: hundred a big game. Uh. I figure that I might

646
00:36:18,440 --> 00:36:20,719
Speaker 1: have to use the shotgun to shoot a there off

647
00:36:20,840 --> 00:36:24,280
Speaker 1: my student. I want to backups. I want their spray

648
00:36:24,640 --> 00:36:27,800
Speaker 1: and then if there's got them down, I can walk

649
00:36:27,880 --> 00:36:30,080
Speaker 1: up and plug them in the head or the neck

650
00:36:30,200 --> 00:36:33,560
Speaker 1: or the shoulders or do whatever you can. You know,

651
00:36:33,680 --> 00:36:37,040
Speaker 1: you're running on instinct there. They don't have their shooting

652
00:36:37,160 --> 00:36:41,200
Speaker 1: classes like they have sailboat classes. You know, yes that, yeah,

653
00:36:41,200 --> 00:36:43,000
Speaker 1: that would be a difficult and I know FWP for

654
00:36:43,080 --> 00:36:46,520
Speaker 1: some time they had a trailer they would pull around

655
00:36:46,520 --> 00:36:49,200
Speaker 1: that had a charging bear saying, and they would say

656
00:36:49,200 --> 00:36:53,720
Speaker 1: that that woman is speaking tonight at at the Lindley Center,

657
00:36:54,120 --> 00:36:56,520
Speaker 1: just before I give the talk. Yeah. So like then

658
00:36:56,560 --> 00:36:58,960
Speaker 1: they would do bear spray training. And I don't want

659
00:36:58,960 --> 00:37:00,319
Speaker 1: to get the number one, but it was a very

660
00:37:00,360 --> 00:37:02,239
Speaker 1: small percentage of people that could get the bear spray

661
00:37:02,280 --> 00:37:04,640
Speaker 1: and effectively get it in the air before that bear,

662
00:37:05,239 --> 00:37:11,640
Speaker 1: that charging fake bear, We're talking milliseconds there, decides to charge, uh,

663
00:37:11,760 --> 00:37:16,640
Speaker 1: standing facing it and hoping to God, uh that it's

664
00:37:16,680 --> 00:37:19,680
Speaker 1: a bluff charge and you can change your underwear later,

665
00:37:20,120 --> 00:37:21,960
Speaker 1: you know. And I I was telling you before, I'm

666
00:37:21,960 --> 00:37:24,399
Speaker 1: an East Coast kid. We just didn't. I never had

667
00:37:24,400 --> 00:37:26,319
Speaker 1: to think about this hunting my entire life or even

668
00:37:26,320 --> 00:37:28,840
Speaker 1: going outside for any reason. And now I've got a

669
00:37:28,840 --> 00:37:32,880
Speaker 1: small son three years old. Every basically every time I

670
00:37:32,960 --> 00:37:35,200
Speaker 1: hunt in the National forest around here, any public lands

671
00:37:35,200 --> 00:37:37,680
Speaker 1: there are, there is the chance. Even sometimes it's more

672
00:37:37,680 --> 00:37:40,440
Speaker 1: remote than others, other times it's more elevated than others.

673
00:37:40,480 --> 00:37:42,400
Speaker 1: But there always is a chance that I'm going to

674
00:37:42,520 --> 00:37:45,120
Speaker 1: run into a grizzly bear. Always, And it's a different

675
00:37:45,160 --> 00:37:48,359
Speaker 1: feeling and that's why we love the wilderness. You think

676
00:37:48,400 --> 00:37:51,400
Speaker 1: the bear owed that it's not the same wilderness exactly.

677
00:37:51,440 --> 00:37:54,279
Speaker 1: You know exactly that we say. I always say, like you,

678
00:37:55,320 --> 00:37:57,279
Speaker 1: if you would remove and we've done this as a

679
00:37:57,880 --> 00:38:01,440
Speaker 1: as a nation, like remove the predator predators from the

680
00:38:01,520 --> 00:38:03,960
Speaker 1: environment with the elk. The elk aren't elk anymore if

681
00:38:03,960 --> 00:38:07,000
Speaker 1: they're not being preyed upon by these things that have chased.

682
00:38:07,120 --> 00:38:10,440
Speaker 1: So their elkness has derived somehow by their instincts that

683
00:38:10,480 --> 00:38:15,359
Speaker 1: are elevated by the evolved with wolves, cougars, whatever. So

684
00:38:15,440 --> 00:38:17,200
Speaker 1: you know, the way we think of elk is is

685
00:38:17,280 --> 00:38:20,560
Speaker 1: very much informed by you know, our prong horn is

686
00:38:20,600 --> 00:38:25,080
Speaker 1: faster than any carnivore. It evolved with a with a

687
00:38:25,160 --> 00:38:28,960
Speaker 1: North American cheetah, which was a lion that they found

688
00:38:29,000 --> 00:38:32,759
Speaker 1: in sinkholes and u and why only which is really interesting.

689
00:38:33,400 --> 00:38:36,440
Speaker 1: There were thor pronghorn at one time. They're six I

690
00:38:36,560 --> 00:38:39,480
Speaker 1: forget which some double horned and all that sort of stuff.

691
00:38:39,520 --> 00:38:42,640
Speaker 1: But there's only one left. But that baby can run.

692
00:38:42,760 --> 00:38:46,800
Speaker 1: You know, nothing can catch that pronghorn. Isn't it really interesting?

693
00:38:46,840 --> 00:38:50,280
Speaker 1: So I studied them for two years. It was wonderful,

694
00:38:50,320 --> 00:38:54,480
Speaker 1: and Yellowstone mostly sent in marketing. It was sort of

695
00:38:54,520 --> 00:38:57,080
Speaker 1: technical stuff, but I just loved the going out watching

696
00:38:57,120 --> 00:39:02,040
Speaker 1: pronghorn behavior. Yeah, they're interesting all one thing like during

697
00:39:02,440 --> 00:39:04,880
Speaker 1: you know, during the attack that you already mentioned, but

698
00:39:04,920 --> 00:39:08,000
Speaker 1: I wanted to return to um in the hours after

699
00:39:08,000 --> 00:39:11,640
Speaker 1: the attack, when when things were pretty dire, you wrote

700
00:39:11,760 --> 00:39:15,000
Speaker 1: that you said that you asked that the bear not

701
00:39:15,200 --> 00:39:18,640
Speaker 1: be destroyed. That's the quote, the words that not one

702
00:39:18,680 --> 00:39:21,520
Speaker 1: of the range of how many bears they had killed,

703
00:39:21,560 --> 00:39:24,239
Speaker 1: and that I could I can remember they sort of

704
00:39:24,320 --> 00:39:28,319
Speaker 1: anger welling up and these saying, please don't do that,

705
00:39:28,960 --> 00:39:32,600
Speaker 1: don't track this there they knew it went downhill, bloody

706
00:39:32,640 --> 00:39:37,040
Speaker 1: footprints our downhill. I never saw the dave that. Of course,

707
00:39:37,080 --> 00:39:39,759
Speaker 1: I didn't see anything after that, but I have the

708
00:39:39,920 --> 00:39:43,960
Speaker 1: color slides of the rescue because the helicopter pilot grabbed

709
00:39:44,000 --> 00:39:47,359
Speaker 1: my thirty five million here camel and took pictures, which

710
00:39:47,400 --> 00:39:51,840
Speaker 1: is crazy. Yeah. Yeah, I think the stories as I

711
00:39:51,880 --> 00:39:54,200
Speaker 1: was reading Love Your rescuers were as interesting as anything.

712
00:39:54,239 --> 00:39:57,160
Speaker 1: The people that they were, isn't that. Yeah. Jim Compson

713
00:39:57,239 --> 00:39:59,879
Speaker 1: did a wonderful job describing and I quoted him comes

714
00:40:00,480 --> 00:40:04,200
Speaker 1: uh in the book because he talked about he'd been

715
00:40:04,320 --> 00:40:07,319
Speaker 1: two tours in Vietnam, and that day he had more

716
00:40:07,320 --> 00:40:12,760
Speaker 1: adrenaline pumping than on any any operation in Vietnam. So uh,

717
00:40:12,800 --> 00:40:15,800
Speaker 1: and he isn't the guy that exaggerates easily. Yeah, I

718
00:40:15,840 --> 00:40:18,480
Speaker 1: mean that's what struck me. I mean, did you I

719
00:40:18,480 --> 00:40:22,320
Speaker 1: think from the moment where you're near death and asking

720
00:40:22,360 --> 00:40:24,160
Speaker 1: for this bear not to be destroyed as his as

721
00:40:24,239 --> 00:40:26,719
Speaker 1: his common occurrence when there's a bear attack, they'll go

722
00:40:26,760 --> 00:40:29,600
Speaker 1: in and dispatch the bear if they can find it. Yeah,

723
00:40:29,960 --> 00:40:33,840
Speaker 1: go back to especially if it's predatory, it's different, you know,

724
00:40:34,280 --> 00:40:38,360
Speaker 1: the surprise encounter, but if you get there that that

725
00:40:38,560 --> 00:40:43,799
Speaker 1: has surprise encounters all the time at the time, right, Yeah,

726
00:40:44,000 --> 00:40:46,839
Speaker 1: take me back to um, you're kind of the first

727
00:40:46,880 --> 00:40:49,799
Speaker 1: time that you were interested in bears, maybe the first

728
00:40:49,840 --> 00:40:52,279
Speaker 1: moment that you remember or or something in your life

729
00:40:52,320 --> 00:40:55,240
Speaker 1: that was very important that got you ahead of that direction.

730
00:40:55,320 --> 00:40:59,680
Speaker 1: You know. I started working with There's really accidentally, I

731
00:40:59,760 --> 00:41:03,520
Speaker 1: was a wildlife biologists for the Province of Alberta and

732
00:41:03,640 --> 00:41:07,440
Speaker 1: There's were wrecking havoc with the yards or a paris

733
00:41:07,520 --> 00:41:12,480
Speaker 1: up there, and uh uh, Young Barry Gilbert was supposed

734
00:41:12,520 --> 00:41:15,359
Speaker 1: to come up with some kind of management solution. So

735
00:41:15,480 --> 00:41:19,360
Speaker 1: we did some uh studies on sixty b yards using

736
00:41:19,560 --> 00:41:22,960
Speaker 1: electric fences and taste the version conditioning where we used

737
00:41:23,360 --> 00:41:25,759
Speaker 1: a chemical called lithium chlora. I'd try to make the

738
00:41:25,800 --> 00:41:28,640
Speaker 1: bear sick and then they'd be off eating honey. So

739
00:41:29,520 --> 00:41:35,480
Speaker 1: uh to be frank. I started out as a biology

740
00:41:35,600 --> 00:41:38,040
Speaker 1: major wanting to do fisheries work, and I had a

741
00:41:38,040 --> 00:41:40,440
Speaker 1: couple of summers there I was at on sword fishing

742
00:41:40,440 --> 00:41:45,560
Speaker 1: boats and that stuff. Then I went to graduate school

743
00:41:45,920 --> 00:41:49,280
Speaker 1: and one places I've played was the University of Miami

744
00:41:49,320 --> 00:41:52,520
Speaker 1: because they had shark studies and I thought, this guy's

745
00:41:52,920 --> 00:41:57,719
Speaker 1: a junkie third nasty animals. But I didn't get accepted there.

746
00:41:57,760 --> 00:42:00,319
Speaker 1: I got accepted at Duke, and the professor wanted to

747
00:42:00,360 --> 00:42:04,920
Speaker 1: study of dear behavior and a young another young relationships,

748
00:42:04,920 --> 00:42:09,000
Speaker 1: and that's what I did my master's on communication and

749
00:42:09,160 --> 00:42:11,560
Speaker 1: thallow deer of all things. And then I did a

750
00:42:12,719 --> 00:42:17,680
Speaker 1: communication really yeah, that was heard from I think the

751
00:42:17,680 --> 00:42:23,120
Speaker 1: New York Zoo that was so averse to being near

752
00:42:23,200 --> 00:42:25,120
Speaker 1: people know that he could see them. So they gave

753
00:42:25,160 --> 00:42:28,960
Speaker 1: them to my professor Duke, and he had enough money

754
00:42:29,000 --> 00:42:32,600
Speaker 1: to build a nile enclosure and release them there. But

755
00:42:32,719 --> 00:42:37,040
Speaker 1: what I did was just shorten it because they're talking bearrass.

756
00:42:37,120 --> 00:42:40,600
Speaker 1: But I studied the bonding between mother and young and

757
00:42:41,040 --> 00:42:44,840
Speaker 1: baby dear and people, and I found out, uh, that

758
00:42:44,920 --> 00:42:47,520
Speaker 1: are there that I sat with for six hours on

759
00:42:47,640 --> 00:42:51,640
Speaker 1: its first day beside it had a changed behavior towards

760
00:42:51,680 --> 00:42:55,560
Speaker 1: people five years later, and none of the other dear did.

761
00:42:55,800 --> 00:43:01,200
Speaker 1: So it was an imprinting study basically. But uh then

762
00:43:01,280 --> 00:43:03,960
Speaker 1: when I you know, I got my job trying to

763
00:43:04,640 --> 00:43:08,960
Speaker 1: save v rds from black bears in Alberta, I uh,

764
00:43:09,600 --> 00:43:13,719
Speaker 1: I applied for a teaching job at Utah State, and uh,

765
00:43:13,840 --> 00:43:16,879
Speaker 1: I've done pronghorn work in Yellowstone. I thought I loved

766
00:43:16,880 --> 00:43:21,800
Speaker 1: the Yellowstone because the animals are more natural and anywhere

767
00:43:21,800 --> 00:43:24,480
Speaker 1: else they're not haunted. You can approach them. And I

768
00:43:25,040 --> 00:43:27,960
Speaker 1: looked at buck behavior, territorial behavior, and all that sort

769
00:43:28,000 --> 00:43:32,120
Speaker 1: of stuff. And then when I came back, uh, Yellowstone

770
00:43:32,200 --> 00:43:35,479
Speaker 1: wanted a study of bears and people on trails because

771
00:43:35,520 --> 00:43:37,759
Speaker 1: they knew that neither bears would be in bump off

772
00:43:37,760 --> 00:43:40,239
Speaker 1: trails or people were running into too many of them

773
00:43:40,360 --> 00:43:44,320
Speaker 1: females and cubs, uh like up Pelican Creek or something

774
00:43:44,400 --> 00:43:47,880
Speaker 1: like that. And they in fact had a student carry

775
00:43:47,960 --> 00:43:51,680
Speaker 1: Gunther did his master's on just that issue after I

776
00:43:52,000 --> 00:43:54,120
Speaker 1: a couple of years after I got involved, and he's

777
00:43:54,160 --> 00:43:57,600
Speaker 1: now the chief bear manager there, but he was up

778
00:43:57,640 --> 00:44:01,200
Speaker 1: on a mountaintop looking at bear people interactions from the

779
00:44:01,280 --> 00:44:06,640
Speaker 1: two kilometers away, so he he was much safer. Of course,

780
00:44:06,960 --> 00:44:10,319
Speaker 1: I wanted to be as close as was safe. And

781
00:44:10,560 --> 00:44:14,560
Speaker 1: here the bears. Bears do a lot of low level

782
00:44:14,680 --> 00:44:20,239
Speaker 1: chuffing and when they alarmed there there youngsters, when they

783
00:44:20,520 --> 00:44:25,080
Speaker 1: there's something dangerous, they go there's a throat click that

784
00:44:25,160 --> 00:44:27,520
Speaker 1: goes on that you have to be quite a way

785
00:44:27,600 --> 00:44:31,080
Speaker 1: from the waterfalls and everything else to to hear that.

786
00:44:31,600 --> 00:44:33,600
Speaker 1: But that doesn't mean I want to, you know, sit

787
00:44:33,640 --> 00:44:38,319
Speaker 1: on a chair next to six bears and hear them talk. So, yeah,

788
00:44:38,400 --> 00:44:41,040
Speaker 1: you were, you wanted to be. You felt like, is

789
00:44:41,360 --> 00:44:43,360
Speaker 1: it a part of your research that drew you to

790
00:44:43,440 --> 00:44:46,200
Speaker 1: bears want to be close? That's what it sounds like, obviously, Yeah,

791
00:44:46,239 --> 00:44:49,320
Speaker 1: but it was I think it'd be closer to problem solving.

792
00:44:49,360 --> 00:44:52,440
Speaker 1: I had a feeling and knowing a lot about observational

793
00:44:52,480 --> 00:44:56,560
Speaker 1: study of theirs used using an anthropological approach. You go

794
00:44:56,640 --> 00:45:00,640
Speaker 1: into the culture, you sit down. It's like they say,

795
00:45:00,760 --> 00:45:04,120
Speaker 1: the average Inuit family as a husband and wife and

796
00:45:04,160 --> 00:45:10,200
Speaker 1: two children and an anthropologist. You've got to be uh

797
00:45:10,280 --> 00:45:14,000
Speaker 1: in the culture to understand what's going on, you know.

798
00:45:14,480 --> 00:45:18,799
Speaker 1: And the Craig has studied their's first grizzlies in the Yellowstone,

799
00:45:18,840 --> 00:45:21,640
Speaker 1: but they captured all of theirs at dumps, so that

800
00:45:21,760 --> 00:45:25,799
Speaker 1: was a dump culture, and uh, they didn't spend much

801
00:45:25,880 --> 00:45:28,279
Speaker 1: time at all looking at their behavior. One of the

802
00:45:28,400 --> 00:45:31,799
Speaker 1: students looked at so called territorial behavior, but what he

803
00:45:31,880 --> 00:45:35,440
Speaker 1: was really looking at is a uh bunch of fighting

804
00:45:35,480 --> 00:45:38,720
Speaker 1: and threats between theirs that are trying to eat garbage.

805
00:45:38,880 --> 00:45:41,320
Speaker 1: And you'll read that a lot like in Yellowstone forty

806
00:45:41,520 --> 00:45:45,400
Speaker 1: fifty years ago, that most of the grizzly bear interactions

807
00:45:45,400 --> 00:45:47,440
Speaker 1: were at like at the dunk, that's where most of

808
00:45:47,480 --> 00:45:50,239
Speaker 1: the bears got their food. Yeah, the growth rate so

809
00:45:50,640 --> 00:45:53,120
Speaker 1: dump fed theirs were much better than the ones that

810
00:45:53,160 --> 00:45:57,120
Speaker 1: were feeding on cutthroat trout or white bark kind seds

811
00:45:57,280 --> 00:45:59,480
Speaker 1: or any of the other things they eat. It's just

812
00:45:59,520 --> 00:46:01,400
Speaker 1: a lot of ea here to get to. You know.

813
00:46:01,480 --> 00:46:04,279
Speaker 1: One of the dumps, Trout Creek dump I read in

814
00:46:04,320 --> 00:46:07,360
Speaker 1: the late fifties had fifty one thousand cans of guardeny

815
00:46:07,400 --> 00:46:10,000
Speaker 1: just come in and compactors were just dumping all this stuff.

816
00:46:10,000 --> 00:46:12,840
Speaker 1: And you know in a park you got Todato's steak

817
00:46:12,920 --> 00:46:15,839
Speaker 1: bones and PRK chops, and why wouldn't a bear habituated

818
00:46:15,920 --> 00:46:18,040
Speaker 1: going in there and get a snack man? That's an

819
00:46:18,080 --> 00:46:20,680
Speaker 1: easy one. Absolutely. So as you as you you know,

820
00:46:20,760 --> 00:46:25,160
Speaker 1: developed through the years with bears, when did did well?

821
00:46:25,239 --> 00:46:27,759
Speaker 1: Two questions is kind of the same. Did things change

822
00:46:27,800 --> 00:46:29,840
Speaker 1: for you where you saw bears a certain way? And

823
00:46:29,840 --> 00:46:31,919
Speaker 1: then the proximity to bears and the time you spent

824
00:46:32,040 --> 00:46:34,160
Speaker 1: kind of change what they are because I mean, you're

825
00:46:34,200 --> 00:46:36,880
Speaker 1: now I would say. People will say a noted authority

826
00:46:36,960 --> 00:46:39,560
Speaker 1: on like people in bears, like how do people in

827
00:46:39,600 --> 00:46:43,839
Speaker 1: bears co exist? When did it? Did it change for you? Ever? Oh? Absolutely?

828
00:46:44,000 --> 00:46:48,960
Speaker 1: And uh the time I can remember, well, I wasn't

829
00:46:49,560 --> 00:46:55,279
Speaker 1: totally aware of how much difference there was. But when

830
00:46:55,320 --> 00:46:58,400
Speaker 1: I went to Katmai and Brooks River and saw bears

831
00:46:58,480 --> 00:47:02,760
Speaker 1: walking up and down the trails with people on the beaches,

832
00:47:02,800 --> 00:47:07,040
Speaker 1: with people, uh, anglers fly casting in the middle of

833
00:47:07,040 --> 00:47:10,840
Speaker 1: the river there's going by, I said to myself, something

834
00:47:10,920 --> 00:47:13,360
Speaker 1: really different is going on here, and I want to

835
00:47:13,400 --> 00:47:16,400
Speaker 1: know what the difference is between mountain bears that aren't

836
00:47:16,520 --> 00:47:20,319
Speaker 1: very well fed. Some of them, like Denalie bears, are

837
00:47:20,360 --> 00:47:23,719
Speaker 1: grazing and eating insects for eighteen hours a day. And

838
00:47:23,800 --> 00:47:29,080
Speaker 1: these uh salmon living bears that they can eat twenty

839
00:47:29,120 --> 00:47:31,320
Speaker 1: three salmon in an hour and a half. I counted

840
00:47:31,360 --> 00:47:34,800
Speaker 1: one that did that, and then they go and sleep

841
00:47:34,880 --> 00:47:36,799
Speaker 1: for a good bit of the day. They've got all

842
00:47:36,800 --> 00:47:41,600
Speaker 1: the calories they need. And but in order to access

843
00:47:41,920 --> 00:47:46,279
Speaker 1: the salmon river, they have to be able to tolerate people. Well,

844
00:47:46,320 --> 00:47:48,920
Speaker 1: they also have to tolerate other theres because these are

845
00:47:49,120 --> 00:47:53,359
Speaker 1: bears that aren't that are defensive of their turf, and uh,

846
00:47:53,640 --> 00:47:56,400
Speaker 1: you can't have much turf when you're on a Sandon street.

847
00:47:56,960 --> 00:47:59,480
Speaker 1: And then you ask the question, well, why don't there's

848
00:47:59,480 --> 00:48:02,239
Speaker 1: flight and are And the answer I think is it

849
00:48:02,360 --> 00:48:05,279
Speaker 1: isn't worth it. If you and I were kind of

850
00:48:05,400 --> 00:48:10,040
Speaker 1: hungry and the table here was covered with sixteen steaks,

851
00:48:10,880 --> 00:48:13,480
Speaker 1: uh t blow and steaks, I'm not gonna start fighting

852
00:48:13,520 --> 00:48:17,160
Speaker 1: you for you know fifteen of them. Both of us

853
00:48:17,200 --> 00:48:19,400
Speaker 1: are going to sit down and start eating. And that's

854
00:48:19,400 --> 00:48:23,680
Speaker 1: that's what bears do. It's and now there's though, could

855
00:48:23,719 --> 00:48:27,920
Speaker 1: be much more aggressive. And one of the questions I ask,

856
00:48:28,040 --> 00:48:31,279
Speaker 1: now and I have haven't got the answer is what

857
00:48:31,320 --> 00:48:35,520
Speaker 1: does all of capturing and collering bears do. It might

858
00:48:35,560 --> 00:48:41,080
Speaker 1: be making nan haters, woman haters, people haters out of

859
00:48:41,120 --> 00:48:45,040
Speaker 1: some bears. Now as an example something I see, Well, yeah,

860
00:48:45,200 --> 00:48:47,919
Speaker 1: you can make up all the coins of stories you want.

861
00:48:47,960 --> 00:48:52,320
Speaker 1: You're probably against callering, which I am, especially in the

862
00:48:52,400 --> 00:48:55,600
Speaker 1: National Park now that we've done it for fifty years.

863
00:48:55,640 --> 00:48:59,279
Speaker 1: But nobody's other studied the change and behavior theres as

864
00:48:59,320 --> 00:49:04,480
Speaker 1: a result of collering them. Now, one example, it's indicative

865
00:49:04,560 --> 00:49:07,320
Speaker 1: to me. It was a bear studied by Bart Schlyer,

866
00:49:07,800 --> 00:49:12,000
Speaker 1: there's master's thesis. Uh, they're fifteen, ended up killing Roger

867
00:49:12,120 --> 00:49:16,759
Speaker 1: Ney in the Rainbow Creek campground west of West Yellowstone.

868
00:49:17,000 --> 00:49:22,200
Speaker 1: That there have been captured eighteen times ever since. It

869
00:49:22,320 --> 00:49:26,440
Speaker 1: was a club and it kept Schreyer Schlyer, Art Schlyer

870
00:49:26,760 --> 00:49:30,239
Speaker 1: up the tree for four hours. It really wanted to

871
00:49:30,280 --> 00:49:35,480
Speaker 1: eat his lunch and his shorts and his ears. Yeah.

872
00:49:35,840 --> 00:49:41,640
Speaker 1: So to me, uh, you've gotta make the linkage that

873
00:49:42,280 --> 00:49:44,440
Speaker 1: if you keep capturing their's and you've probably seen this

874
00:49:44,520 --> 00:49:47,680
Speaker 1: on television, you opened the gate for a Culdert trap

875
00:49:47,719 --> 00:49:49,840
Speaker 1: and that bear wants to tear the truck on the

876
00:49:49,880 --> 00:49:52,120
Speaker 1: trap and everything apart and then it runs up when

877
00:49:52,120 --> 00:49:56,520
Speaker 1: you guys blow the horn. So you changed the relationship

878
00:49:56,600 --> 00:49:59,120
Speaker 1: of theirs to people. And one of in my talk

879
00:49:59,160 --> 00:50:04,200
Speaker 1: tonight at the the Center, UH will be about uh

880
00:50:04,480 --> 00:50:09,720
Speaker 1: contrasts in there's in different places and they're just like anthropologists,

881
00:50:09,760 --> 00:50:15,120
Speaker 1: you know. In the famous anthropologist France Bois went to

882
00:50:15,160 --> 00:50:18,160
Speaker 1: the Arctic in the eighteen hundreds to study the Inuit.

883
00:50:18,880 --> 00:50:21,680
Speaker 1: He thought he was just going to study people, you know,

884
00:50:21,719 --> 00:50:26,120
Speaker 1: another primitive people that eat meat. Totally, he found that

885
00:50:26,160 --> 00:50:30,000
Speaker 1: their whole worldview was so different than the European one

886
00:50:30,040 --> 00:50:32,280
Speaker 1: that he was familiar with. I think he was a German,

887
00:50:32,880 --> 00:50:36,239
Speaker 1: and uh that set him off on a on a

888
00:50:36,320 --> 00:50:41,160
Speaker 1: course in life to say, you know, anthropologists don't study people.

889
00:50:41,680 --> 00:50:45,480
Speaker 1: They study different cultures in different places. Cultural anthropologists, I'm

890
00:50:45,520 --> 00:50:47,680
Speaker 1: not talking about the ones that collect bones, you know,

891
00:50:47,760 --> 00:50:51,880
Speaker 1: physical anthropologists. Yeah. We we had just had a gentleman

892
00:50:51,920 --> 00:50:54,839
Speaker 1: named Dr Larry's Geist on the podcast a couple episodes ago,

893
00:50:54,840 --> 00:50:57,640
Speaker 1: and he's got the author of our North American Mile Conservation,

894
00:50:57,800 --> 00:51:01,239
Speaker 1: and he talked he studied wolves in North America as

895
00:51:01,280 --> 00:51:04,560
Speaker 1: compared to wolves in Russia and Siberia, which are heavily

896
00:51:04,600 --> 00:51:09,200
Speaker 1: predatory on humans and very opportunistic when it comes to us.

897
00:51:10,239 --> 00:51:13,520
Speaker 1: I'd like to see the evidence of that because American

898
00:51:13,640 --> 00:51:16,959
Speaker 1: students um so he was so his studies. I won't

899
00:51:16,960 --> 00:51:19,040
Speaker 1: speak for him, but he has some books on some

900
00:51:19,080 --> 00:51:22,719
Speaker 1: stories and of specifically Russian wolves in their attack that

901
00:51:23,080 --> 00:51:26,080
Speaker 1: he shouldn't but he was looking at as much as

902
00:51:26,080 --> 00:51:30,360
Speaker 1: you say, the comparison of wolf attacks and the violence

903
00:51:30,400 --> 00:51:34,560
Speaker 1: with wolves in you know, eastern Eastern Europe and other places,

904
00:51:35,320 --> 00:51:37,920
Speaker 1: why it's different in North Americas. There's less evidence of

905
00:51:37,920 --> 00:51:40,839
Speaker 1: that much much much less aviagent wolf of the tax

906
00:51:40,880 --> 00:51:44,200
Speaker 1: on humans here in North American how almost none. Yeah,

907
00:51:44,480 --> 00:51:48,600
Speaker 1: And so he's looking into how these things. That's it's

908
00:51:48,600 --> 00:51:50,320
Speaker 1: super interesting to me. And we had a lot of people,

909
00:51:50,719 --> 00:51:52,720
Speaker 1: you know, want to disagree with his stance on wolves,

910
00:51:52,560 --> 00:51:55,120
Speaker 1: and my point to them was, look, this guy is

911
00:51:55,440 --> 00:51:59,800
Speaker 1: taking research from Germany, from Siberia, from Russia and comparing

912
00:51:59,800 --> 00:52:02,319
Speaker 1: it to North America and shaping So it's a very

913
00:52:02,360 --> 00:52:06,160
Speaker 1: different worldview than just and that goes to my point

914
00:52:06,200 --> 00:52:09,680
Speaker 1: that you can't generalize these wolves have different cultures just

915
00:52:09,800 --> 00:52:12,920
Speaker 1: like and solve all. We had nan eating lions that

916
00:52:13,080 --> 00:52:17,239
Speaker 1: didn't do anything but capture Chinese railroad workers out of

917
00:52:17,239 --> 00:52:20,239
Speaker 1: their sleeping cars and eat them. Yeah, we're gonna have

918
00:52:20,360 --> 00:52:23,400
Speaker 1: David Kuaman on hopefully soon. Yeah, try to talk to

919
00:52:23,440 --> 00:52:26,360
Speaker 1: him about Monster for God his book. That's just a

920
00:52:26,480 --> 00:52:28,000
Speaker 1: very interesting thing to me. Like I said, I'm no

921
00:52:28,760 --> 00:52:32,319
Speaker 1: expert on predators are bear biologists, but there is you know,

922
00:52:32,480 --> 00:52:34,640
Speaker 1: when you talk about bears, they're not it's not a monolith,

923
00:52:34,680 --> 00:52:37,080
Speaker 1: it's not sure, you know, and it's it's the illustrated.

924
00:52:38,040 --> 00:52:40,839
Speaker 1: Don't you think we stereotyped them though? I mean if

925
00:52:40,880 --> 00:52:44,279
Speaker 1: you got a crowd of people and said, Okay, I'm

926
00:52:44,280 --> 00:52:45,840
Speaker 1: going to give you a word and I want you

927
00:52:45,920 --> 00:52:49,400
Speaker 1: to write a word down that goes with it, and

928
00:52:49,480 --> 00:52:52,080
Speaker 1: if you said grizzly there, what do you think people

929
00:52:52,120 --> 00:52:55,080
Speaker 1: would write? Yeah? I mean it goes both ways, right,

930
00:52:55,120 --> 00:52:57,239
Speaker 1: it goes in the way like Paddington Bear he has

931
00:52:57,960 --> 00:53:00,359
Speaker 1: he wears shorts and goes to them all and we

932
00:53:00,520 --> 00:53:02,120
Speaker 1: you know, I want did a think about Yeah, but

933
00:53:02,200 --> 00:53:05,080
Speaker 1: we're talking grizzly bears. Yeah, I think if you had

934
00:53:05,120 --> 00:53:07,440
Speaker 1: the term grizzly, then you start to get into you

935
00:53:07,480 --> 00:53:11,160
Speaker 1: start to get into that. But there's I think it's

936
00:53:11,160 --> 00:53:14,040
Speaker 1: clearly your view on bears in mind different a lot

937
00:53:14,080 --> 00:53:15,440
Speaker 1: of ways, and I think that's maybe one of them,

938
00:53:15,480 --> 00:53:19,600
Speaker 1: because I I do think pragmatically, there's two ends of

939
00:53:19,640 --> 00:53:21,640
Speaker 1: that spectrum. Right. I look at my three year old son.

940
00:53:21,760 --> 00:53:25,000
Speaker 1: He's surrounded by fluffy, cuddly brown bears. Grizzly bears. They

941
00:53:25,000 --> 00:53:28,000
Speaker 1: sell them at the Yellowstone, you know, park stores, and

942
00:53:28,040 --> 00:53:32,560
Speaker 1: like we we um we personify and anthromorphized bears and

943
00:53:32,600 --> 00:53:35,520
Speaker 1: ways that I don't think we understand. But in the

944
00:53:35,560 --> 00:53:38,760
Speaker 1: in the same vein, we also sensationalize the more violent

945
00:53:38,840 --> 00:53:41,320
Speaker 1: nature of bears as well. So I think there's two

946
00:53:41,480 --> 00:53:43,640
Speaker 1: sides of the coin, well at least, and there's a

947
00:53:43,640 --> 00:53:47,399
Speaker 1: whole field of the differences. Yeah, they're all over the map. Yeah,

948
00:53:47,600 --> 00:53:51,960
Speaker 1: you know, I clarified in my mind by saying these

949
00:53:51,960 --> 00:53:55,680
Speaker 1: are values. We're talking about values, and you and I

950
00:53:55,719 --> 00:53:58,640
Speaker 1: started talking about, well, let's have a hunting season on

951
00:53:58,680 --> 00:54:02,840
Speaker 1: bald eagles. Well, that's there's no biological reason not to

952
00:54:02,920 --> 00:54:06,680
Speaker 1: shoot eagles. There's a value reason. People love them. They're

953
00:54:06,760 --> 00:54:10,000
Speaker 1: dig we don't eat them, and then they don't do

954
00:54:10,040 --> 00:54:13,520
Speaker 1: any damage to us. Unless you're orn a fish hat tree.

955
00:54:13,560 --> 00:54:16,120
Speaker 1: Oh yeah, unless you're unless you're on the Prince of

956
00:54:16,160 --> 00:54:19,439
Speaker 1: Wales Island, and you see little like street buzzards over there,

957
00:54:19,440 --> 00:54:22,919
Speaker 1: and again, like I think your value systems, they're still

958
00:54:23,000 --> 00:54:26,160
Speaker 1: beautiful and they're still nervelous to watch. I am not

959
00:54:26,239 --> 00:54:28,920
Speaker 1: a their lother. Uh. Somebody asked me out of an

960
00:54:28,960 --> 00:54:32,000
Speaker 1: audience a couple of days ago whether I loved theirs. Well,

961
00:54:33,040 --> 00:54:35,080
Speaker 1: I could get all technical and say, what do you

962
00:54:35,080 --> 00:54:39,880
Speaker 1: mean by love? I mean I love my six or

963
00:54:39,960 --> 00:54:42,320
Speaker 1: something like this, or I love my Golden Retriever, or

964
00:54:42,400 --> 00:54:48,440
Speaker 1: I loved my sailboat. But if you love, there's uh

965
00:54:48,640 --> 00:54:52,360
Speaker 1: the bad kind of love. There's a sympathetic fallacy if

966
00:54:52,719 --> 00:54:57,440
Speaker 1: which Timothy Treadwell suffered from. I knew tim he called

967
00:54:57,920 --> 00:55:04,520
Speaker 1: their advice and another Tuck didn't well. He was one

968
00:55:04,520 --> 00:55:06,719
Speaker 1: of those that thought of he was real nice to

969
00:55:06,800 --> 00:55:09,439
Speaker 1: bears and loved them. They would love him back, and

970
00:55:09,600 --> 00:55:14,959
Speaker 1: most of them tolerated him. He was a wildlife uh

971
00:55:15,239 --> 00:55:18,120
Speaker 1: abuser in a way. He approached them much more than

972
00:55:18,160 --> 00:55:22,240
Speaker 1: he should have in the park. Shore should have kicked

973
00:55:22,239 --> 00:55:27,200
Speaker 1: his lily white Ayshota there actually, but he uh, he've

974
00:55:27,320 --> 00:55:30,480
Speaker 1: ended up being killed by a bear late in the

975
00:55:30,560 --> 00:55:34,040
Speaker 1: season that I think probably was a nan heater and

976
00:55:34,080 --> 00:55:37,240
Speaker 1: it had bad teeth, and it was old, had been captured.

977
00:55:37,360 --> 00:55:40,880
Speaker 1: I'm not saying captured nat him the killer, but that

978
00:55:41,000 --> 00:55:44,120
Speaker 1: bear was intent on eating people. Yeah, and I think

979
00:55:44,120 --> 00:55:45,680
Speaker 1: that do you? Is how I feel about it. I

980
00:55:45,760 --> 00:55:49,040
Speaker 1: wonder if you agree that it's incombat upon us as

981
00:55:49,120 --> 00:55:52,840
Speaker 1: humans to understand a bear, understand what it does, especially

982
00:55:52,880 --> 00:55:55,400
Speaker 1: me as a hunter. I gotta understand kind of not

983
00:55:55,560 --> 00:55:57,560
Speaker 1: just that single bear, but what a bear is and

984
00:55:57,560 --> 00:55:59,880
Speaker 1: how I can better interact. And also it's motivation of

985
00:56:00,000 --> 00:56:02,600
Speaker 1: the toms motivations, right, you need to know. And so

986
00:56:02,640 --> 00:56:05,800
Speaker 1: if I'm just like Timothy treadwell, if I am ignorant

987
00:56:05,800 --> 00:56:07,239
Speaker 1: to the motivations of a bear, and I want to,

988
00:56:07,360 --> 00:56:10,600
Speaker 1: you know, somehow apply my own emotional values to the bear.

989
00:56:10,920 --> 00:56:12,839
Speaker 1: That's not doing the bear any justice because that sucker

990
00:56:12,920 --> 00:56:14,680
Speaker 1: is going to kill you, and then we're gonna kill it,

991
00:56:15,160 --> 00:56:17,880
Speaker 1: and then you're both it's a wild and it's not.

992
00:56:18,120 --> 00:56:20,600
Speaker 1: It's not a little kid with a third coat. Yeah,

993
00:56:20,800 --> 00:56:23,680
Speaker 1: you know. As as as evidence, I think your words,

994
00:56:23,719 --> 00:56:25,000
Speaker 1: I think to a lot of people and a lot

995
00:56:25,000 --> 00:56:27,520
Speaker 1: of writings and things I've read about you and stuff

996
00:56:27,560 --> 00:56:31,040
Speaker 1: you've written, I think your scars one stop people to

997
00:56:31,160 --> 00:56:33,800
Speaker 1: make them listen, but to our our evidence of someone

998
00:56:33,840 --> 00:56:37,800
Speaker 1: who can understand what a bear is so so holy.

999
00:56:38,480 --> 00:56:40,960
Speaker 1: And then and then step away from that and try

1000
00:56:41,000 --> 00:56:44,000
Speaker 1: to determine, you know, what a bear really means to you,

1001
00:56:44,080 --> 00:56:45,680
Speaker 1: and then to us as a society, and then to

1002
00:56:45,800 --> 00:56:49,799
Speaker 1: wild life, and and it's it's a relationship, Isn't that sure?

1003
00:56:50,600 --> 00:56:53,839
Speaker 1: We relate as humans to theirs, and we should be

1004
00:56:53,880 --> 00:56:57,919
Speaker 1: relating to Mother Earth in a similar way. Respect care

1005
00:56:58,040 --> 00:57:03,560
Speaker 1: for it, naked continue. I'm originally an Easterner, still an

1006
00:57:03,680 --> 00:57:06,200
Speaker 1: I guess because that's where I live. But I spent

1007
00:57:06,280 --> 00:57:07,960
Speaker 1: a lot of time in the West, and I kept

1008
00:57:08,000 --> 00:57:12,239
Speaker 1: asking myself, now, all these people that that consider themselves

1009
00:57:12,280 --> 00:57:16,040
Speaker 1: true Westerners, how could you possibly want to eliminate grizzly

1010
00:57:16,080 --> 00:57:17,960
Speaker 1: There's which is so much a part of the West.

1011
00:57:18,400 --> 00:57:19,920
Speaker 1: Who wants to eliminate grizz But we got a lot

1012
00:57:19,920 --> 00:57:22,400
Speaker 1: of people that want to eliminate grizzly bears. I think

1013
00:57:22,440 --> 00:57:26,200
Speaker 1: we do? You think so? Well? Uh? Look at Wyoming

1014
00:57:26,240 --> 00:57:29,880
Speaker 1: and Montana and Idaho had planned for the so called

1015
00:57:29,960 --> 00:57:33,880
Speaker 1: recovery of the Yellowstone Greater Yellowstone ecosystem. Grizzly there that

1016
00:57:34,000 --> 00:57:37,000
Speaker 1: want the ultimate hunting season immediately they were going to

1017
00:57:37,160 --> 00:57:41,800
Speaker 1: have twenty three tournits sent out. That means that there

1018
00:57:41,840 --> 00:57:45,439
Speaker 1: will never connect with any other Uh. I know we're

1019
00:57:45,440 --> 00:57:48,840
Speaker 1: talking hunting turn that's we're not talking ranchers that can

1020
00:57:48,880 --> 00:57:51,200
Speaker 1: now shoot them and make up their own story. You

1021
00:57:51,240 --> 00:57:56,840
Speaker 1: know some sheep sheep herder, industrial sheep herder, or ranchers that,

1022
00:57:57,920 --> 00:58:01,320
Speaker 1: in my view, most of them have resolutely no interest

1023
00:58:01,360 --> 00:58:06,480
Speaker 1: in having grizzly bears around. And you can understand it. Yeah,

1024
00:58:06,480 --> 00:58:09,040
Speaker 1: I think that's again, there's not a monolith there. I

1025
00:58:09,040 --> 00:58:11,520
Speaker 1: mean you're looking at like when when they studied bears

1026
00:58:11,520 --> 00:58:13,880
Speaker 1: in Yellowstone there was a the demographic care was like

1027
00:58:13,880 --> 00:58:18,080
Speaker 1: what two acres and they're looking at Okay, I think

1028
00:58:18,080 --> 00:58:21,600
Speaker 1: it's six D seventy four bears this area can hold, right,

1029
00:58:21,840 --> 00:58:27,360
Speaker 1: and they think that they think, Yeah, the best I

1030
00:58:27,400 --> 00:58:31,480
Speaker 1: can do is say within the I'm a staunch believer

1031
00:58:31,560 --> 00:58:33,440
Speaker 1: in the North American model, and I think we should

1032
00:58:33,800 --> 00:58:35,840
Speaker 1: talk about bald eagles and some things like that too.

1033
00:58:35,840 --> 00:58:38,880
Speaker 1: But within our North American model, who are trusting these

1034
00:58:38,880 --> 00:58:42,240
Speaker 1: state biologists they're hired to do a job. Well, there's

1035
00:58:42,280 --> 00:58:43,680
Speaker 1: a lot of times we disagree with them, a lot

1036
00:58:43,720 --> 00:58:46,240
Speaker 1: of times we agree with them. But they're telling me, Okay,

1037
00:58:46,320 --> 00:58:49,320
Speaker 1: this this area can old six seventy four bears if

1038
00:58:50,040 --> 00:58:53,360
Speaker 1: within our model. That is, I think if you look

1039
00:58:53,400 --> 00:58:55,360
Speaker 1: at the Endangered Species Act and all these other things,

1040
00:58:56,000 --> 00:58:58,400
Speaker 1: when that animals are covered, hunting them to me is

1041
00:58:58,440 --> 00:59:00,840
Speaker 1: a positive thing, right because not looking at the killing

1042
00:59:00,840 --> 00:59:04,280
Speaker 1: of the individual. Let me give you another data back

1043
00:59:04,320 --> 00:59:08,520
Speaker 1: of the Enlote math. People love to talk about the

1044
00:59:08,600 --> 00:59:11,280
Speaker 1: bear's going from three hundred out to the park Service

1045
00:59:11,400 --> 00:59:14,560
Speaker 1: killed so many of them three and they've gone to

1046
00:59:14,800 --> 00:59:18,960
Speaker 1: six hundred, seven hundred bears now and uh, the North

1047
00:59:19,000 --> 00:59:23,040
Speaker 1: American model people will say wow, and the recovery people, wow,

1048
00:59:23,440 --> 00:59:27,840
Speaker 1: they've doubled hundred increase. But if I give you, uh,

1049
00:59:28,000 --> 00:59:31,480
Speaker 1: fifty thousand grizzly bears is the number that are estimated

1050
00:59:31,840 --> 00:59:35,080
Speaker 1: in North America. When they go from three hundred to

1051
00:59:35,160 --> 00:59:38,720
Speaker 1: six hundred, that's going from point at six to one

1052
00:59:38,760 --> 00:59:42,400
Speaker 1: point two. And since when there's one point two of

1053
00:59:42,440 --> 00:59:46,560
Speaker 1: the original population recovery, let's hunt them and kill them. Well,

1054
00:59:46,560 --> 00:59:48,000
Speaker 1: you're looking at it, but you're looking at the greater

1055
00:59:48,080 --> 00:59:51,520
Speaker 1: Yellowstone ecosystem. So the bear pope police within that ecosystem

1056
00:59:51,680 --> 00:59:54,000
Speaker 1: does have a carrying capacity. There has to be. But

1057
00:59:54,120 --> 00:59:57,200
Speaker 1: we have all their habitat in Idaho and Montana where

1058
00:59:57,240 --> 01:00:00,760
Speaker 1: bears would go and not be eating cows and all

1059
01:00:00,760 --> 01:00:02,600
Speaker 1: that sort of stuff. But when you old on a

1060
01:00:02,680 --> 01:00:05,960
Speaker 1: hunt that is on the border of the Greater Elstone ecosystem,

1061
01:00:06,280 --> 01:00:10,360
Speaker 1: you dropped the gate on all the movements of those bears.

1062
01:00:10,440 --> 01:00:14,640
Speaker 1: Not only that some jerk water poacher can say, oh,

1063
01:00:14,680 --> 01:00:17,880
Speaker 1: I was attacked and I shot that they're there. There

1064
01:00:17,880 --> 01:00:21,560
Speaker 1: are no witnesses say that. There's a reductive way to

1065
01:00:21,640 --> 01:00:24,080
Speaker 1: think about it, right, I don't think about hunters and

1066
01:00:24,120 --> 01:00:29,160
Speaker 1: posters certainly different things altogether. I came to the interview

1067
01:00:29,280 --> 01:00:31,960
Speaker 1: you with you not to argue with you. I'm giving

1068
01:00:32,160 --> 01:00:34,280
Speaker 1: my point of view, and I don't want to argue

1069
01:00:34,280 --> 01:00:36,000
Speaker 1: with you either. I want well you seem to be

1070
01:00:36,280 --> 01:00:39,400
Speaker 1: so I'm be honest about it. I'm not here to

1071
01:00:39,480 --> 01:00:42,040
Speaker 1: argue with you at okay at all. This is not

1072
01:00:42,120 --> 01:00:43,760
Speaker 1: the way that we approach these things. But I do

1073
01:00:43,880 --> 01:00:46,160
Speaker 1: want I don't want to talk about it. I don't

1074
01:00:46,160 --> 01:00:48,000
Speaker 1: want to avoid it because it's because we don't agree.

1075
01:00:48,000 --> 01:00:51,880
Speaker 1: I mean, I think you're here because but there you

1076
01:00:52,000 --> 01:00:55,480
Speaker 1: are a believer and biased to the North American model.

1077
01:00:55,720 --> 01:00:58,640
Speaker 1: You're not just a journalist right now, Well, I just

1078
01:00:58,680 --> 01:01:00,480
Speaker 1: tell you I believe in the North American but I

1079
01:01:00,480 --> 01:01:03,600
Speaker 1: think that I think the value of yours. It may

1080
01:01:03,640 --> 01:01:05,840
Speaker 1: not be mine for sure, but I think that's an

1081
01:01:05,840 --> 01:01:09,800
Speaker 1: interesting way to go about this conversation. We have differing values.

1082
01:01:09,840 --> 01:01:13,000
Speaker 1: Where can we come and find middle ground, because like

1083
01:01:13,080 --> 01:01:14,840
Speaker 1: that's an important thing to do, especially when it comes

1084
01:01:14,840 --> 01:01:17,200
Speaker 1: to an animals important it's a grizzly bear. Because where

1085
01:01:17,240 --> 01:01:19,919
Speaker 1: we can find middle ground is I don't I don't

1086
01:01:19,960 --> 01:01:22,640
Speaker 1: devalue to hunt grizzly bear. And I already told you,

1087
01:01:22,760 --> 01:01:25,240
Speaker 1: well maybe not on on maybe before we hit record,

1088
01:01:25,320 --> 01:01:28,000
Speaker 1: but I'm not I don't hunt grizzly bears if somebody

1089
01:01:28,000 --> 01:01:30,200
Speaker 1: handing me a tag at all, but taken in my

1090
01:01:30,240 --> 01:01:35,360
Speaker 1: pocket hunters alcan deer. I know thou Geist quite well

1091
01:01:35,400 --> 01:01:37,760
Speaker 1: at he's one of the guys that's pumped out as

1092
01:01:37,800 --> 01:01:42,720
Speaker 1: an academic the North American model. He really doesn't like carnivores.

1093
01:01:42,880 --> 01:01:47,480
Speaker 1: He's never studied, uh their viewing. I was I was

1094
01:01:48,560 --> 01:01:52,560
Speaker 1: on sabbatical for six months with thu Geist in his university.

1095
01:01:52,880 --> 01:01:55,680
Speaker 1: He gave me some room. He never asked me any

1096
01:01:55,760 --> 01:01:59,880
Speaker 1: questions about theirs or anything. And you know, let me

1097
01:02:00,320 --> 01:02:03,680
Speaker 1: let me tell you about hunters. It isn't about their

1098
01:02:03,760 --> 01:02:06,960
Speaker 1: hunters that I disagree with. It's hunters that believe that

1099
01:02:07,120 --> 01:02:11,120
Speaker 1: there's and cougars are taking their ungulates, they're out their

1100
01:02:11,200 --> 01:02:16,560
Speaker 1: dear and and uh Alaska caribou. Now, if we start

1101
01:02:16,640 --> 01:02:21,600
Speaker 1: managing from state and federal fishing game units, if we

1102
01:02:21,680 --> 01:02:26,800
Speaker 1: start managing uh pronghorn, deer, elk you name it, Uh,

1103
01:02:28,520 --> 01:02:32,440
Speaker 1: we're game ranching if we kill all the predators. So

1104
01:02:33,040 --> 01:02:35,640
Speaker 1: any hunter, any hunter would said this table and argue

1105
01:02:35,680 --> 01:02:38,960
Speaker 1: that predators need to be killed so they can go hunting.

1106
01:02:39,360 --> 01:02:41,920
Speaker 1: That's not that's not part of what I think the

1107
01:02:41,960 --> 01:02:46,240
Speaker 1: core hunts Colorado Fishing Game just did that. They invited

1108
01:02:46,720 --> 01:02:50,280
Speaker 1: wildlife services, you know, the gopher chokers that work for

1109
01:02:50,320 --> 01:02:56,480
Speaker 1: the federal government. Uh, they want to kill cougars and

1110
01:02:56,640 --> 01:02:59,960
Speaker 1: black there's because they believe that they're knocking down the

1111
01:03:00,040 --> 01:03:04,360
Speaker 1: newly neil dear population. There's no evidence that they're doing that,

1112
01:03:04,760 --> 01:03:08,560
Speaker 1: but it's quite a popular program presumably. And the garden

1113
01:03:08,600 --> 01:03:11,760
Speaker 1: that if you're a Colorado and I were, our tax

1114
01:03:11,800 --> 01:03:15,760
Speaker 1: money will be paid for to kill cougars and black bears.

1115
01:03:16,200 --> 01:03:22,720
Speaker 1: So that's a position that isn't science based. It's based

1116
01:03:22,760 --> 01:03:27,960
Speaker 1: on if you like greed of hunters, they think every well,

1117
01:03:28,240 --> 01:03:30,520
Speaker 1: I won't tell you what hunters think, but I mean

1118
01:03:30,600 --> 01:03:34,200
Speaker 1: there's a belief that when a cougar kills the deer,

1119
01:03:34,320 --> 01:03:36,760
Speaker 1: that's the deer that you and me can't put in

1120
01:03:36,800 --> 01:03:40,320
Speaker 1: our freezer. I've been in the hunting industry for twelve

1121
01:03:40,360 --> 01:03:45,360
Speaker 1: or thirteen years. I've never heard that. Never. Well, that's

1122
01:03:45,480 --> 01:03:50,560
Speaker 1: that's what Colorado and an Anchorage, uh sorry, Alaska is

1123
01:03:50,600 --> 01:03:56,040
Speaker 1: doing it. The Gloria Game has that as a policy. Now,

1124
01:03:56,040 --> 01:03:59,480
Speaker 1: it comes not from tree huggers. It comes from hunters.

1125
01:04:00,080 --> 01:04:03,880
Speaker 1: They don't want to lose caribou. There's old their hunting

1126
01:04:03,920 --> 01:04:08,320
Speaker 1: going on. They don't want to lose cariboo, noose, uh whatever,

1127
01:04:08,800 --> 01:04:14,040
Speaker 1: other ungulates, bighorn sheep, to any carnivor. Because the Board

1128
01:04:14,040 --> 01:04:18,760
Speaker 1: of Game is UH is allowing hunters to kill bears

1129
01:04:19,440 --> 01:04:23,000
Speaker 1: uh in the dam with cubs in Alaska. In Alaska,

1130
01:04:23,560 --> 01:04:26,760
Speaker 1: that's a policy. Now, are you sure about that? Because

1131
01:04:26,800 --> 01:04:28,320
Speaker 1: I know that there. I wouldn't say it if I

1132
01:04:28,360 --> 01:04:32,640
Speaker 1: wasn't sure. There was two hunters that did that and

1133
01:04:32,680 --> 01:04:36,880
Speaker 1: they were prosecuted. How long ago, oh, within a year.

1134
01:04:37,960 --> 01:04:39,840
Speaker 1: So I don't have. I don't have those game lalls

1135
01:04:39,840 --> 01:04:42,360
Speaker 1: in front of you, but I'm well, I know a

1136
01:04:42,440 --> 01:04:46,720
Speaker 1: bunch of their biologists and one of them was a

1137
01:04:46,840 --> 01:04:53,120
Speaker 1: lead researcher who's now living in Montana, and he argued

1138
01:04:53,120 --> 01:04:58,200
Speaker 1: with me. He says, the the government tells us to

1139
01:04:58,600 --> 01:05:03,920
Speaker 1: manage carnivor's for the minimum number, and they open up

1140
01:05:04,840 --> 01:05:08,800
Speaker 1: killing ground. There's and five or six hundred are killed

1141
01:05:09,400 --> 01:05:12,920
Speaker 1: in Alaska every year and part of the goal is

1142
01:05:12,960 --> 01:05:18,040
Speaker 1: to reduce the number. And they other people they've had

1143
01:05:18,040 --> 01:05:23,200
Speaker 1: shooting wolves from aircraft. You know, you know that whole story. Well,

1144
01:05:23,200 --> 01:05:28,800
Speaker 1: that doesn't that doesn't come from some accountant in Anchorage.

1145
01:05:28,840 --> 01:05:32,000
Speaker 1: You know, that comes from pressured by the hunters that

1146
01:05:32,080 --> 01:05:36,680
Speaker 1: want just like commercial fishermen don't want uh individuals netting

1147
01:05:36,720 --> 01:05:40,040
Speaker 1: so Dan manny king salmon, they want to net them all.

1148
01:05:40,520 --> 01:05:42,400
Speaker 1: I mean, I think, yeah, I don't agree with that

1149
01:05:42,440 --> 01:05:47,480
Speaker 1: at all. I think that's a pretty bombastic statement about

1150
01:05:47,560 --> 01:05:50,479
Speaker 1: all hunters. This or that. I didn't say a hunter.

1151
01:05:50,920 --> 01:05:54,360
Speaker 1: I'm talking about policy. I'm talking about policy. I'm talking

1152
01:05:54,400 --> 01:05:57,880
Speaker 1: about hunter motivation. Because if you don't believe that the

1153
01:05:58,040 --> 01:06:03,480
Speaker 1: government policy pull politicians aren't listening to the people on

1154
01:06:03,520 --> 01:06:07,600
Speaker 1: the land that want to do these things. Politicians, of

1155
01:06:07,600 --> 01:06:10,320
Speaker 1: course they are, yeah, saying that at all. I'm saying that, like,

1156
01:06:10,360 --> 01:06:13,240
Speaker 1: if you look at the way our model of conservation works,

1157
01:06:13,640 --> 01:06:17,000
Speaker 1: hunters hundred dollars Pittman Robertson dollars paid for a lot

1158
01:06:17,240 --> 01:06:20,400
Speaker 1: of grizzly bear studies and a lot of grizzly bear

1159
01:06:20,800 --> 01:06:24,160
Speaker 1: uh projects within the Greater Yellowstone ecosystem. It does that

1160
01:06:24,200 --> 01:06:30,960
Speaker 1: in Alaska Douse too. If you buy a rifle uh

1161
01:06:31,760 --> 01:06:34,120
Speaker 1: in the pim roor somebody think that I buy fishing

1162
01:06:34,600 --> 01:06:38,320
Speaker 1: licenses fifty bucks and I don't catch a salmon. But

1163
01:06:38,400 --> 01:06:40,360
Speaker 1: I don't know. I think that's I don't think it's

1164
01:06:40,400 --> 01:06:43,200
Speaker 1: generally the argument I would make anyway. But I think

1165
01:06:43,280 --> 01:06:45,800
Speaker 1: that there's there's some things that are intertwined there that

1166
01:06:45,840 --> 01:06:47,920
Speaker 1: you can't just say, yeah, we're not going to solve

1167
01:06:47,920 --> 01:06:50,160
Speaker 1: it in an hour. No, No, And I think it's

1168
01:06:50,240 --> 01:06:52,680
Speaker 1: it's still a fine. Like I would just say, have

1169
01:06:52,720 --> 01:06:55,600
Speaker 1: flatly disagree with saying that hunters are driving policy to

1170
01:06:55,800 --> 01:06:58,400
Speaker 1: have less grizzly bears. Every hunter I've had in this

1171
01:06:58,480 --> 01:07:01,400
Speaker 1: room on this podcast, it doesn't matter where they're from.

1172
01:07:01,440 --> 01:07:06,120
Speaker 1: I didn't say I want to put ranchers in there too.

1173
01:07:06,760 --> 01:07:09,240
Speaker 1: You don't believe there are some hunters that would like

1174
01:07:09,320 --> 01:07:13,000
Speaker 1: to have fewer carnivores eating deer and elk. Sure, but

1175
01:07:13,080 --> 01:07:14,840
Speaker 1: I don't think that's driving policy, and I don't think

1176
01:07:14,880 --> 01:07:18,880
Speaker 1: that's the prevailing feeling. Fine, last the sociologists, they'll tell you,

1177
01:07:19,560 --> 01:07:22,000
Speaker 1: I mean, we need studies of just those questions. I

1178
01:07:22,040 --> 01:07:24,840
Speaker 1: would like to see that, and I liked I wouldn't

1179
01:07:24,840 --> 01:07:27,880
Speaker 1: presume to say that that the hunter is the every

1180
01:07:27,920 --> 01:07:31,720
Speaker 1: single hunter in every single state and all these policies. Um,

1181
01:07:31,880 --> 01:07:34,120
Speaker 1: we're the great conservationists. We have a lot of flaws

1182
01:07:34,120 --> 01:07:38,640
Speaker 1: in our in our community and trophy hunting and sounding

1183
01:07:38,760 --> 01:07:43,720
Speaker 1: you sound defensive to me, that's fine in what way? Well,

1184
01:07:43,800 --> 01:07:47,320
Speaker 1: you're you're attacking what I say about hundred motivation. You're

1185
01:07:47,360 --> 01:07:51,160
Speaker 1: saying all some are some rogue or some guy does this.

1186
01:07:52,440 --> 01:07:58,720
Speaker 1: I taught wildlife management, So does that qualify the policy? Why?

1187
01:07:58,760 --> 01:08:02,320
Speaker 1: I've studied where policy comes from. I tried to do

1188
01:08:02,520 --> 01:08:07,360
Speaker 1: studies in Utah on black bears. The guys that control

1189
01:08:07,440 --> 01:08:10,240
Speaker 1: the money wouldn't let me do any studies. They took

1190
01:08:10,280 --> 01:08:14,000
Speaker 1: it to a private university b y U because I

1191
01:08:14,040 --> 01:08:19,200
Speaker 1: was considered to be anti sheep, anti cows and somewhere,

1192
01:08:19,240 --> 01:08:22,960
Speaker 1: and I suggested that there were some troat streams and

1193
01:08:23,080 --> 01:08:26,519
Speaker 1: salmon streams in Utah, believe it or not, where there's

1194
01:08:26,600 --> 01:08:30,200
Speaker 1: command to feed on spawning salmon. The guy looked at

1195
01:08:30,240 --> 01:08:32,439
Speaker 1: me like I had rocks in my head that people

1196
01:08:32,479 --> 01:08:36,600
Speaker 1: would want to watch bears eat salmon, and Alaska is

1197
01:08:36,720 --> 01:08:39,639
Speaker 1: as a gold mine. Right now. There are sixty companies

1198
01:08:39,640 --> 01:08:44,439
Speaker 1: and Bertie's colony alone that authored their viewing as part

1199
01:08:44,479 --> 01:08:49,240
Speaker 1: of their eco tourism. Watching bears and photographing bears is

1200
01:08:49,280 --> 01:08:53,479
Speaker 1: a land office business. Now people don't want them. Something

1201
01:08:53,520 --> 01:08:58,280
Speaker 1: like nine of the people pulled in various Columbia we're

1202
01:08:58,320 --> 01:09:02,920
Speaker 1: against their hunting. Now there's a surplus of bears that

1203
01:09:02,960 --> 01:09:06,719
Speaker 1: could be hunted according to the model. The hunting was ended.

1204
01:09:06,760 --> 01:09:10,599
Speaker 1: It became political and they stopped the hunt. So that's

1205
01:09:10,720 --> 01:09:13,280
Speaker 1: it's a different policy. That's a difficult situation, right because

1206
01:09:13,280 --> 01:09:15,639
Speaker 1: you can't At the same time, you wouldn't want if

1207
01:09:15,640 --> 01:09:18,120
Speaker 1: there are so like hunters out there that are driving

1208
01:09:18,120 --> 01:09:21,600
Speaker 1: policy based on less predators, if that is, if that

1209
01:09:21,680 --> 01:09:23,720
Speaker 1: does exist and that is prevailing, you wouldn't want that

1210
01:09:23,760 --> 01:09:26,080
Speaker 1: to drive policy, and you wouldn't want folks in Vancouver

1211
01:09:26,520 --> 01:09:29,439
Speaker 1: to tell, you know, central British Columbia, the folks near

1212
01:09:29,479 --> 01:09:32,679
Speaker 1: Quinnel and some on these logging towns where there there's

1213
01:09:33,120 --> 01:09:36,320
Speaker 1: you know, cohabitation issues, and there's hunting economy, and there's

1214
01:09:36,320 --> 01:09:38,439
Speaker 1: all these things that are happening at the same way.

1215
01:09:38,439 --> 01:09:40,519
Speaker 1: You wouldn't want somebody in Vancouver who has never seen

1216
01:09:40,560 --> 01:09:43,439
Speaker 1: a grizzy bear to vote on and have dominion over,

1217
01:09:43,560 --> 01:09:45,720
Speaker 1: you know, how bears are managed in those areas, Like

1218
01:09:45,840 --> 01:09:48,600
Speaker 1: both of those things would be wrong. Those people in

1219
01:09:48,760 --> 01:09:53,400
Speaker 1: Vancouver are interested. Bears are a public resource to be

1220
01:09:53,520 --> 01:09:58,120
Speaker 1: managed as a as a public trust. It's a heritage

1221
01:09:58,240 --> 01:10:00,960
Speaker 1: that it doesn't belong to any buddy, and it belongs

1222
01:10:00,960 --> 01:10:04,200
Speaker 1: to everybody. You and I have as much right to

1223
01:10:05,360 --> 01:10:09,640
Speaker 1: have an opinion and vote on federal lands in Alaska,

1224
01:10:09,840 --> 01:10:14,840
Speaker 1: and that person in Vancouver has every right to say

1225
01:10:14,880 --> 01:10:18,040
Speaker 1: that there's should not be hunted. Well, we need to

1226
01:10:18,040 --> 01:10:20,759
Speaker 1: give them the right perspectives and the right information say

1227
01:10:20,920 --> 01:10:22,840
Speaker 1: there there there can't be you know, I've been to

1228
01:10:23,840 --> 01:10:25,599
Speaker 1: I've been to Vancouver, I've been in New York City.

1229
01:10:25,640 --> 01:10:29,280
Speaker 1: There's no way that someone in New York City could

1230
01:10:29,439 --> 01:10:33,880
Speaker 1: could accurately understand the ecosystem of the Greater Yellowstone. Well,

1231
01:10:33,920 --> 01:10:35,880
Speaker 1: what you're saying to me is that they don't have

1232
01:10:35,920 --> 01:10:38,479
Speaker 1: the same values that you did. I would say, that's true.

1233
01:10:39,920 --> 01:10:44,200
Speaker 1: You are you gonna say that their values aren't legitimate?

1234
01:10:44,400 --> 01:10:47,800
Speaker 1: Years are I would say that their perspectives aren't the

1235
01:10:47,840 --> 01:10:50,400
Speaker 1: same as somebody who's who's closer to bears. I think

1236
01:10:50,400 --> 01:10:53,320
Speaker 1: your stories is very much about that, your perspective, the

1237
01:10:53,360 --> 01:10:55,600
Speaker 1: proximity to bear a lot of people want to be

1238
01:10:55,640 --> 01:10:58,320
Speaker 1: close to it there without a K forty seven if

1239
01:10:58,360 --> 01:11:01,640
Speaker 1: they had one. So yeah, I don't think that's an

1240
01:11:01,680 --> 01:11:03,840
Speaker 1: unfortunate I think it's an unfortunate you. And I let

1241
01:11:03,840 --> 01:11:06,519
Speaker 1: me just say quickly kind of how what I feel,

1242
01:11:07,040 --> 01:11:09,920
Speaker 1: just me personally, and I think probably this company I

1243
01:11:09,920 --> 01:11:12,600
Speaker 1: would just maybe represent me I feel, especially when you

1244
01:11:12,600 --> 01:11:18,040
Speaker 1: go back to the Great Yellowstone ecosystem, I feel when

1245
01:11:18,520 --> 01:11:20,759
Speaker 1: and this is not me as a hunter dictating policy,

1246
01:11:20,760 --> 01:11:23,480
Speaker 1: I think it's the reverse. Based on our model of conservation.

1247
01:11:23,560 --> 01:11:26,519
Speaker 1: Knowing that hunting, to me is a sustainable use of

1248
01:11:26,520 --> 01:11:28,840
Speaker 1: a natural resources, I think matches a little bit of

1249
01:11:28,880 --> 01:11:31,439
Speaker 1: what you're saying. And in the line that hunting is

1250
01:11:31,479 --> 01:11:34,920
Speaker 1: sustainable use of natural resource, I'm saying within our model,

1251
01:11:35,200 --> 01:11:38,280
Speaker 1: wildlife is a public trust. We're we are going to

1252
01:11:38,320 --> 01:11:41,880
Speaker 1: rely on state game officials and biologists who we fund

1253
01:11:41,960 --> 01:11:46,240
Speaker 1: through our dollars. Yeah. I mean just because it's the

1254
01:11:46,240 --> 01:11:48,639
Speaker 1: party line doesn't make it wrong. I didn't say that.

1255
01:11:48,720 --> 01:11:51,280
Speaker 1: I said it's the party line, and it's a it's

1256
01:11:51,280 --> 01:11:54,400
Speaker 1: a statement of values, but it's a statement of values

1257
01:11:54,479 --> 01:11:57,000
Speaker 1: that are people by people that are pro hunting. And

1258
01:11:57,040 --> 01:12:00,200
Speaker 1: as you and I covered before, not to overdo it.

1259
01:12:00,920 --> 01:12:03,599
Speaker 1: If we have the North American model, we'd be shooting

1260
01:12:03,640 --> 01:12:07,240
Speaker 1: eagles and sandhill cranes. Well, we can, we can choose,

1261
01:12:07,280 --> 01:12:08,800
Speaker 1: we say in hill cranes a lot. I mean, you

1262
01:12:08,800 --> 01:12:14,000
Speaker 1: can get Utah. I'm out of touch with that. It

1263
01:12:14,080 --> 01:12:16,680
Speaker 1: was the reason I say it is that it was

1264
01:12:16,680 --> 01:12:20,559
Speaker 1: an issue that got shot down. Pardon the fun in

1265
01:12:20,680 --> 01:12:24,799
Speaker 1: Utah because people didn't want crane shot. It wasn't because

1266
01:12:24,840 --> 01:12:28,680
Speaker 1: there wasn't a surplus. I I teach wildlife management right,

1267
01:12:28,720 --> 01:12:32,240
Speaker 1: and I was sucked into the North American model, just

1268
01:12:32,320 --> 01:12:36,360
Speaker 1: as I was sucked into the multiple use model. Uh.

1269
01:12:36,479 --> 01:12:39,040
Speaker 1: We talked of the multiple use of public lands, but

1270
01:12:39,120 --> 01:12:43,440
Speaker 1: when you look at what's going on, it's private interests

1271
01:12:43,439 --> 01:12:48,800
Speaker 1: like ranchers. UH and tender operators that are are the

1272
01:12:48,840 --> 01:12:54,040
Speaker 1: top dogs and wildlife and recreation and skiing whatever our

1273
01:12:54,200 --> 01:12:58,639
Speaker 1: way down in the so called multiple use. Multiple uses

1274
01:12:58,680 --> 01:13:01,760
Speaker 1: give a little bit to every body, but in actuality

1275
01:13:02,680 --> 01:13:05,919
Speaker 1: the resource goes to the big money guys, wire houser,

1276
01:13:06,720 --> 01:13:12,559
Speaker 1: industrial ranchers, cheap grazing fees. Uh, let's not get into that.

1277
01:13:12,640 --> 01:13:17,920
Speaker 1: But multiply used. I have my dean who's used to

1278
01:13:17,960 --> 01:13:22,160
Speaker 1: see the uh ecological world through the eyes of the cow.

1279
01:13:22,320 --> 01:13:26,160
Speaker 1: He was a Texan say that multiply use is a

1280
01:13:26,200 --> 01:13:29,160
Speaker 1: is a bogus concept. And I don't want to see

1281
01:13:29,640 --> 01:13:35,360
Speaker 1: management of wildlife just representing the interests of hunters like

1282
01:13:35,439 --> 01:13:40,240
Speaker 1: the North American model that becomes game ranching. In in

1283
01:13:40,400 --> 01:13:43,000
Speaker 1: the North America modelement it says that that hunting is

1284
01:13:43,000 --> 01:13:45,160
Speaker 1: a tool for conservation. It's not the other way around.

1285
01:13:45,160 --> 01:13:48,599
Speaker 1: Conservations are not a tool for hunters. Um. And that's

1286
01:13:48,680 --> 01:13:50,679
Speaker 1: that's how I believe. That's what I believe. I believe

1287
01:13:50,760 --> 01:13:56,360
Speaker 1: that hunting has benefited not only as benefited not only deer,

1288
01:13:56,960 --> 01:14:02,479
Speaker 1: but birds, elk and it's and if it adut and

1289
01:14:02,560 --> 01:14:05,320
Speaker 1: we brought them back through the North American No, no, no,

1290
01:14:06,360 --> 01:14:09,080
Speaker 1: it was brought back by conservations to New York City

1291
01:14:09,360 --> 01:14:13,360
Speaker 1: or initially, and then they of the states asked for them.

1292
01:14:13,439 --> 01:14:16,000
Speaker 1: The ship all over the United States. We had to

1293
01:14:16,000 --> 01:14:18,640
Speaker 1: reintroduce them. We did. We did that turkeys. That was

1294
01:14:18,680 --> 01:14:22,160
Speaker 1: market hunting. That wasn't hunting. That was the mass killing

1295
01:14:22,160 --> 01:14:26,760
Speaker 1: of something for market, which was within the North American models.

1296
01:14:26,400 --> 01:14:30,479
Speaker 1: That's that's history. Let's not go there. Yeah, and I

1297
01:14:30,520 --> 01:14:33,679
Speaker 1: think that you're you're making out the model like it's

1298
01:14:33,920 --> 01:14:37,880
Speaker 1: some some kind of value system that somehow it is

1299
01:14:37,920 --> 01:14:40,439
Speaker 1: close to Heaven. It's not perfect, and there's and there's

1300
01:14:40,479 --> 01:14:41,960
Speaker 1: a lot of things in the modern sense that we

1301
01:14:41,960 --> 01:14:45,160
Speaker 1: could do to Let's just leave that. That's highly debatable model.

1302
01:14:45,600 --> 01:14:48,800
Speaker 1: It isn't it isn't all sure. No, I don't think

1303
01:14:48,800 --> 01:14:50,360
Speaker 1: it's all great. I think there's a lot of things,

1304
01:14:50,520 --> 01:14:54,479
Speaker 1: and I think, you know, large charismatic predators are are

1305
01:14:54,560 --> 01:14:56,400
Speaker 1: one of the things that needs to be addressed within

1306
01:14:56,479 --> 01:15:00,280
Speaker 1: the greater conversation. And that's why I kind of resent you,

1307
01:15:00,760 --> 01:15:03,439
Speaker 1: uh asking me to come in here and talk about

1308
01:15:03,439 --> 01:15:05,800
Speaker 1: grizzly bears, and all I've got in a lot of

1309
01:15:05,840 --> 01:15:09,280
Speaker 1: ways is a god damned lecture about the North American

1310
01:15:09,320 --> 01:15:12,680
Speaker 1: model and how biased I am so let's wrap this up.

1311
01:15:13,120 --> 01:15:16,000
Speaker 1: I've I've spent my time. You know, you guys aren't

1312
01:15:16,040 --> 01:15:18,400
Speaker 1: even giving me a baseball cap for coming in here,

1313
01:15:18,960 --> 01:15:24,080
Speaker 1: and now you're foisting your view over the radio about

1314
01:15:24,439 --> 01:15:29,640
Speaker 1: the North American model their biology. We can tisk me

1315
01:15:29,720 --> 01:15:32,920
Speaker 1: about my goddamn book. We can continue talking about grizzly

1316
01:15:32,920 --> 01:15:35,840
Speaker 1: bears in your book. I wanted to. I don't want

1317
01:15:35,840 --> 01:15:39,640
Speaker 1: to continue. Are you sure? Yes? I think I'm sorry that.

1318
01:15:39,880 --> 01:15:41,960
Speaker 1: I'm sorry that it's contentious. I didn't. It was not

1319
01:15:42,080 --> 01:15:43,920
Speaker 1: meant to be that way. Well, you don't know how

1320
01:15:44,080 --> 01:15:48,479
Speaker 1: you behave. Then I've had somebody asked me to come in,

1321
01:15:48,960 --> 01:15:52,240
Speaker 1: asked me about my forty five years of research and

1322
01:15:53,320 --> 01:15:56,679
Speaker 1: give me the kind of defense you're giving me about

1323
01:15:57,080 --> 01:15:59,880
Speaker 1: big game hunting, and you're acting like I've got some

1324
01:16:00,120 --> 01:16:04,120
Speaker 1: kind of uh left wing, weird old view. I'm not

1325
01:16:04,120 --> 01:16:06,160
Speaker 1: not at all. Well, that's the way I feel. I

1326
01:16:06,200 --> 01:16:08,920
Speaker 1: can I'm sorry, I can only tell you the way

1327
01:16:08,960 --> 01:16:12,639
Speaker 1: I feel. Okay, you can defend yourself, you see whatever,

1328
01:16:12,800 --> 01:16:15,720
Speaker 1: Like you can chot this whole thing up, and I'm

1329
01:16:15,760 --> 01:16:18,200
Speaker 1: not going to chop it up at all. If you don't, like,

1330
01:16:18,479 --> 01:16:21,280
Speaker 1: we can we can say that there you go putting

1331
01:16:21,400 --> 01:16:23,760
Speaker 1: some words in them. Though I don't want you not

1332
01:16:23,920 --> 01:16:26,360
Speaker 1: to air it. I want good things to be done

1333
01:16:26,400 --> 01:16:30,200
Speaker 1: for bears, grizzly bears, and I let's talk about that.

1334
01:16:30,240 --> 01:16:31,720
Speaker 1: Let's let's talk about what you want to do for

1335
01:16:31,760 --> 01:16:36,760
Speaker 1: grizzly bears and put it out. I pointed out how

1336
01:16:37,280 --> 01:16:40,160
Speaker 1: going from three hundred to six hundred and fifty is

1337
01:16:40,200 --> 01:16:45,280
Speaker 1: not recovery in my view, it's not recovery. Okay, you

1338
01:16:45,320 --> 01:16:49,400
Speaker 1: can't make the case genetically. If we're talking about whales

1339
01:16:49,479 --> 01:16:52,200
Speaker 1: in the North Atlantic, any species you want to pick,

1340
01:16:52,240 --> 01:16:55,880
Speaker 1: spurn whales whatever. Three thousand is about the number for

1341
01:16:56,080 --> 01:17:01,959
Speaker 1: genetically minimum numbers of the animals to continue on forether, Uh,

1342
01:17:02,120 --> 01:17:06,760
Speaker 1: we have fifty thousand grizzly bears, and somehow one increase

1343
01:17:07,320 --> 01:17:12,280
Speaker 1: in a small number. It's easy to double a small number, right. Uh.

1344
01:17:12,360 --> 01:17:15,040
Speaker 1: If you had two dollars and I gave the two dollars,

1345
01:17:15,040 --> 01:17:19,320
Speaker 1: well you just got hundreds per cent richer. That's uh,

1346
01:17:19,360 --> 01:17:24,080
Speaker 1: that's balder dash. So anyway, I'm I'm understand, I understand.

1347
01:17:24,120 --> 01:17:27,280
Speaker 1: I don't want and listen, I did not intend for

1348
01:17:27,320 --> 01:17:29,480
Speaker 1: it to get heat it. I did not intend for

1349
01:17:29,479 --> 01:17:31,680
Speaker 1: for that to be the situation. You've given your time here,

1350
01:17:31,720 --> 01:17:35,120
Speaker 1: and I respect that. I'm not in any way trying

1351
01:17:35,120 --> 01:17:38,800
Speaker 1: to push my views on you or on vice versa.

1352
01:17:38,960 --> 01:17:42,160
Speaker 1: I think maybe we can close better debating you will

1353
01:17:42,240 --> 01:17:47,760
Speaker 1: admitting I want to talk about Grizzly Bears, and so

1354
01:17:48,120 --> 01:17:50,880
Speaker 1: I didn't come in here for a debate. I'll get

1355
01:17:50,960 --> 01:17:54,240
Speaker 1: hate mail, I'm sure, and people will write me about

1356
01:17:54,280 --> 01:17:56,679
Speaker 1: my book and calling me all kinds of natives. Great,

1357
01:17:57,040 --> 01:17:59,240
Speaker 1: but I want to see your evidence. I want to

1358
01:17:59,280 --> 01:18:02,840
Speaker 1: know what your experiences. Because I spent my life and

1359
01:18:02,920 --> 01:18:07,640
Speaker 1: almost gave my life for grizzly Bears. Let's talk about

1360
01:18:07,520 --> 01:18:09,160
Speaker 1: what I would like to talk about that. Let's move

1361
01:18:09,200 --> 01:18:12,760
Speaker 1: on from where we disagree and talk about your time

1362
01:18:12,800 --> 01:18:15,400
Speaker 1: with bears and your philosophies and cohabitation and those things.

1363
01:18:15,400 --> 01:18:17,719
Speaker 1: So this is absolutely what I want to talk about.

1364
01:18:18,200 --> 01:18:22,439
Speaker 1: And again I will say, I apologize that that this

1365
01:18:22,439 --> 01:18:25,840
Speaker 1: went away, that you're not accept your apologies, it's not okay,

1366
01:18:25,880 --> 01:18:28,880
Speaker 1: that's not a big deal. I don't what I did

1367
01:18:28,920 --> 01:18:31,400
Speaker 1: not mean for that to happen. I did not. I

1368
01:18:31,439 --> 01:18:33,400
Speaker 1: did not come here to have some debate. In fact,

1369
01:18:33,640 --> 01:18:35,439
Speaker 1: I read a lot about you and was very excited

1370
01:18:35,520 --> 01:18:38,680
Speaker 1: just to have this conversation about cohabitation and what you think.

1371
01:18:38,720 --> 01:18:41,000
Speaker 1: So if we can get to that, I'd love to.

1372
01:18:41,080 --> 01:18:44,120
Speaker 1: But if you like to try and to make the

1373
01:18:44,160 --> 01:18:49,720
Speaker 1: case that you can't generalize the grizzly bears, there's a

1374
01:18:49,760 --> 01:18:56,840
Speaker 1: tendency even along PhD their researchers to uh stereotype their

1375
01:18:56,920 --> 01:18:59,879
Speaker 1: view of theirs. If you call her there's you captured

1376
01:19:00,000 --> 01:19:04,599
Speaker 1: and abused them and you haven't watched them. Uh. So

1377
01:19:04,800 --> 01:19:10,080
Speaker 1: I'm an animal behavior is to use an anthropological approach, right.

1378
01:19:10,240 --> 01:19:13,760
Speaker 1: And what I've seen now and I find marvelous, is

1379
01:19:13,800 --> 01:19:18,400
Speaker 1: that we can see grizzly bears as different cultures. They

1380
01:19:18,520 --> 01:19:21,200
Speaker 1: learn things and pass along to their young. In Alaska

1381
01:19:21,240 --> 01:19:23,759
Speaker 1: they swim out to island, some as far as thirty

1382
01:19:23,760 --> 01:19:27,000
Speaker 1: miles to raid seed third nests, and that's a trait,

1383
01:19:27,439 --> 01:19:30,160
Speaker 1: a cultural trait that they've learned. And we can go

1384
01:19:30,360 --> 01:19:34,840
Speaker 1: uh to Yellowstone and see in the fifties a garbage

1385
01:19:34,880 --> 01:19:38,120
Speaker 1: don't there that can be there. The craigheads called an

1386
01:19:38,160 --> 01:19:41,720
Speaker 1: equal center and related to salmon streams. So I think

1387
01:19:41,800 --> 01:19:46,240
Speaker 1: that's uh breaking out of the ignorant model that all

1388
01:19:46,360 --> 01:19:50,599
Speaker 1: bears are pretty much the same, unpredictable goneat your mama.

1389
01:19:51,240 --> 01:19:54,759
Speaker 1: Uh kind of thing. And people generate a lot of fear.

1390
01:19:55,240 --> 01:19:58,799
Speaker 1: But if we think of them as a sentient animal

1391
01:19:58,960 --> 01:20:03,559
Speaker 1: like chimta zis or wolves, we realize that they have

1392
01:20:03,920 --> 01:20:09,040
Speaker 1: a social life, they have mother young relationships. Wolves are

1393
01:20:09,080 --> 01:20:12,280
Speaker 1: are violent killers. If you know their watch a bear

1394
01:20:13,080 --> 01:20:16,240
Speaker 1: or a wolf take a on a baby. Help they

1395
01:20:16,360 --> 01:20:19,080
Speaker 1: did alive. They just pulled big chunks off at need

1396
01:20:19,080 --> 01:20:22,479
Speaker 1: it while it's trying to breathe and escape. So I

1397
01:20:22,520 --> 01:20:28,960
Speaker 1: don't I know the different sides of theirs, but uh,

1398
01:20:29,320 --> 01:20:32,719
Speaker 1: they are a different culture. We have another, you know again,

1399
01:20:32,760 --> 01:20:37,480
Speaker 1: the anthropological one. We wouldn't say, oh, I'm an anthropologist.

1400
01:20:37,520 --> 01:20:41,240
Speaker 1: I study people. People say, well, what tribes do you study?

1401
01:20:42,080 --> 01:20:45,880
Speaker 1: Because uh, and I could say any kind. I could say, well,

1402
01:20:45,920 --> 01:20:48,760
Speaker 1: I study gangs in Chicago. It's a different tribe than

1403
01:20:48,840 --> 01:20:55,240
Speaker 1: the Mandoga more or uh Samoans or something like that. Well,

1404
01:20:55,240 --> 01:20:58,160
Speaker 1: I think your point is something that I that's something

1405
01:20:58,240 --> 01:21:01,360
Speaker 1: worth looking into. Because bears at the same time or

1406
01:21:01,400 --> 01:21:03,439
Speaker 1: like can be and we've already kind of covered this

1407
01:21:03,479 --> 01:21:06,839
Speaker 1: through the from like the personification of bears persus violence,

1408
01:21:06,840 --> 01:21:11,280
Speaker 1: that bears are very social, very a lot of times gregarious,

1409
01:21:11,320 --> 01:21:13,000
Speaker 1: and then you spend a lot of times, I'm sure

1410
01:21:13,000 --> 01:21:15,439
Speaker 1: in close proximity to bears where they're doing things that

1411
01:21:16,280 --> 01:21:18,479
Speaker 1: people love to watch bears. I love the watchers when

1412
01:21:18,479 --> 01:21:20,040
Speaker 1: I see a bear and yellows and I stop and

1413
01:21:20,040 --> 01:21:22,439
Speaker 1: get out and get the bonos. You know, in the end,

1414
01:21:22,520 --> 01:21:26,519
Speaker 1: we stereotype them through As I mentioned, the PhDs that

1415
01:21:26,640 --> 01:21:34,040
Speaker 1: only do computer population analysis don't know theirs. They know

1416
01:21:34,840 --> 01:21:39,760
Speaker 1: uh numbers of theirs, and if they've captured them, they've

1417
01:21:39,800 --> 01:21:45,880
Speaker 1: dealt with a angry captured there that would love to

1418
01:21:45,920 --> 01:21:50,040
Speaker 1: get at them and chew their face off. So is

1419
01:21:50,080 --> 01:21:52,400
Speaker 1: there away from like a biology standpoint, and you know,

1420
01:21:52,640 --> 01:21:55,479
Speaker 1: from your standpoint, to kind of meld those two things together,

1421
01:21:55,800 --> 01:21:57,840
Speaker 1: like the data and and and all the things that

1422
01:21:57,880 --> 01:22:00,720
Speaker 1: are collected and then the feeling of this is what

1423
01:22:00,800 --> 01:22:03,600
Speaker 1: a bear is because I think what I think what

1424
01:22:03,640 --> 01:22:06,200
Speaker 1: you're saying is like there's a bareness. Bears are there

1425
01:22:06,240 --> 01:22:08,080
Speaker 1: a certain way when you're around them, and you must

1426
01:22:08,240 --> 01:22:10,160
Speaker 1: understand the bear. Is there a way to kind of

1427
01:22:10,160 --> 01:22:13,400
Speaker 1: meld those two things together and effectively, Well, if you

1428
01:22:13,680 --> 01:22:16,320
Speaker 1: if you're dealing with oathen minded people, they are willing

1429
01:22:16,400 --> 01:22:22,439
Speaker 1: to consider another view of theirs rather than just recover them.

1430
01:22:22,479 --> 01:22:25,040
Speaker 1: So let's play the numbers games. So let's get to

1431
01:22:25,160 --> 01:22:29,920
Speaker 1: six fifty and then drop the protection. I don't think

1432
01:22:29,920 --> 01:22:35,600
Speaker 1: we should drop the protection, but uh, it's about oathen mindedness,

1433
01:22:36,040 --> 01:22:39,519
Speaker 1: and uh, I don't. I don't see any way that

1434
01:22:39,880 --> 01:22:42,639
Speaker 1: people are going to change. I mean, I read uh

1435
01:22:42,800 --> 01:22:46,720
Speaker 1: population literature. I appreciate the effort that those guys go

1436
01:22:46,840 --> 01:22:51,920
Speaker 1: to are then involved in callering programs with with satellite

1437
01:22:52,160 --> 01:22:55,280
Speaker 1: callers because I thought the data would stop some timber

1438
01:22:55,320 --> 01:22:58,799
Speaker 1: operations that were hurting bears. I don't believe that anymore.

1439
01:22:59,040 --> 01:23:02,760
Speaker 1: I don't believe that science is giving us better management

1440
01:23:02,800 --> 01:23:06,240
Speaker 1: all the time, because politicians come in for the wealthy

1441
01:23:06,320 --> 01:23:11,960
Speaker 1: the corporation's tender companies mining oil and gas, and they say,

1442
01:23:12,360 --> 01:23:16,160
Speaker 1: screw the greater sage gross. We used to have millions

1443
01:23:16,160 --> 01:23:19,840
Speaker 1: of them. We don't even have ten square niles where

1444
01:23:19,840 --> 01:23:22,760
Speaker 1: there's nothing that can come in on stage gross. To me,

1445
01:23:22,920 --> 01:23:26,559
Speaker 1: sage gross is my favorite third. I studied them at

1446
01:23:26,600 --> 01:23:28,960
Speaker 1: a distance, and in Utah, I used to go on

1447
01:23:29,000 --> 01:23:31,479
Speaker 1: the early morning down to Hardware ranch, which was an

1448
01:23:31,479 --> 01:23:35,520
Speaker 1: elk branch, and uh take pictures of them and watch them.

1449
01:23:35,560 --> 01:23:38,920
Speaker 1: They're just fabulous birds that they don't get the time

1450
01:23:38,960 --> 01:23:41,679
Speaker 1: of day anymore. Well, this brand meat eater and and

1451
01:23:41,920 --> 01:23:45,639
Speaker 1: Steve Ronella guy founded it. We've he's been very active.

1452
01:23:45,720 --> 01:23:48,160
Speaker 1: Me less. So I wish I had understood that issue

1453
01:23:48,200 --> 01:23:51,320
Speaker 1: more um with the governor former governors of Yoma, governor

1454
01:23:51,360 --> 01:23:53,479
Speaker 1: meat and things like that, of of making sure that

1455
01:23:53,560 --> 01:23:57,960
Speaker 1: this that that stage bust see that greater um sage

1456
01:23:57,960 --> 01:24:01,200
Speaker 1: gross habitat has been has been looked after and maintained.

1457
01:24:01,200 --> 01:24:02,879
Speaker 1: That's a tough thing to do in a state like Wyoming.

1458
01:24:02,920 --> 01:24:07,599
Speaker 1: So because the ranchers are controlling the politics and they

1459
01:24:07,680 --> 01:24:11,200
Speaker 1: put cows on all our our least land which is

1460
01:24:11,560 --> 01:24:16,320
Speaker 1: subsidized grazing. And that will be another program you convicted

1461
01:24:16,479 --> 01:24:23,040
Speaker 1: back for a laugh about Well, it's it's so uh bizarre,

1462
01:24:23,960 --> 01:24:29,719
Speaker 1: Uh what h ranchers get away with dollar thirty nine

1463
01:24:30,960 --> 01:24:34,000
Speaker 1: for animal unit month that needs They can graze an

1464
01:24:34,040 --> 01:24:37,360
Speaker 1: animal on your land and my land for a month

1465
01:24:37,479 --> 01:24:39,720
Speaker 1: for a dollar and a half or less, and it

1466
01:24:39,760 --> 01:24:44,320
Speaker 1: hasn't changed in thirty years. That's a giveaway to ranchers.

1467
01:24:44,400 --> 01:24:48,400
Speaker 1: That's why people like George Worthner and not in journal,

1468
01:24:49,000 --> 01:24:53,439
Speaker 1: uh your local journal here with editor Todd Wilkinson, do

1469
01:24:53,600 --> 01:24:56,519
Speaker 1: such a nice job because he's trying to educate people

1470
01:24:56,840 --> 01:25:00,639
Speaker 1: about what's actually going on. But if you're love with

1471
01:25:01,200 --> 01:25:06,880
Speaker 1: the independent ranchers being the lifeblood of the West, uh,

1472
01:25:07,000 --> 01:25:09,639
Speaker 1: you're in favor of a lot of stuff that's harming

1473
01:25:09,720 --> 01:25:13,200
Speaker 1: the environment. We've had two hundred years of sheep grazing

1474
01:25:13,760 --> 01:25:16,360
Speaker 1: and cattle grazing since the more and Thons first came

1475
01:25:16,439 --> 01:25:20,360
Speaker 1: to Utah, for example, and they ran sheep everywhere until

1476
01:25:20,439 --> 01:25:24,639
Speaker 1: erosion uh pulled the mountains down and the Forest Service

1477
01:25:24,680 --> 01:25:28,200
Speaker 1: came in and took it over. And so we don't

1478
01:25:28,720 --> 01:25:32,880
Speaker 1: right now, we don't have a square mile of land

1479
01:25:32,920 --> 01:25:35,840
Speaker 1: that hasn't been grazed somehow. So we don't even know

1480
01:25:35,880 --> 01:25:39,360
Speaker 1: how lush the West was. That's what's incredible. And you

1481
01:25:39,400 --> 01:25:41,680
Speaker 1: know what they call at the ecologists call that the

1482
01:25:41,720 --> 01:25:46,439
Speaker 1: shifting baseline. Yeah, yeah, I think it's a reality and

1483
01:25:46,960 --> 01:25:49,719
Speaker 1: it's not really well, I guess it's a theory because

1484
01:25:49,760 --> 01:25:55,120
Speaker 1: it works so often, is there? Um, Like I said,

1485
01:25:55,120 --> 01:25:57,680
Speaker 1: I've I've this reminds me of like some some of

1486
01:25:57,720 --> 01:26:00,160
Speaker 1: the conversation I had when I went to to talk

1487
01:26:00,240 --> 01:26:03,559
Speaker 1: to you know, vegan philosophers and trying to like work

1488
01:26:03,640 --> 01:26:07,160
Speaker 1: through some of the things, like some of the real

1489
01:26:07,240 --> 01:26:09,840
Speaker 1: broad things where we disagree and get get down to

1490
01:26:09,920 --> 01:26:13,840
Speaker 1: that um and I think, yeah. I mean, if you've

1491
01:26:13,840 --> 01:26:17,879
Speaker 1: pointed out how you feel certain groups, you know, diverge

1492
01:26:17,920 --> 01:26:20,760
Speaker 1: when it comes to conservation policy and biology and when

1493
01:26:20,760 --> 01:26:25,200
Speaker 1: it comes to their motivations for whatever they do. I

1494
01:26:25,240 --> 01:26:28,320
Speaker 1: feel I feel real strongly about the group we have

1495
01:26:28,400 --> 01:26:30,519
Speaker 1: here at Meat Eater, and and this the audience of

1496
01:26:30,560 --> 01:26:33,120
Speaker 1: this podcast. There's a lot of people that care about

1497
01:26:33,120 --> 01:26:36,120
Speaker 1: their being more bears and the and the a lot

1498
01:26:36,200 --> 01:26:39,439
Speaker 1: of those people one are wrestling with what to do

1499
01:26:39,640 --> 01:26:42,000
Speaker 1: hunt bears or not? Is this the thing that is

1500
01:26:42,040 --> 01:26:45,000
Speaker 1: with our value system? So there's a lot of that

1501
01:26:45,040 --> 01:26:47,000
Speaker 1: I've seen, But then there's also a lot of like

1502
01:26:47,040 --> 01:26:50,280
Speaker 1: trusting in uh the model, but all of that is

1503
01:26:50,360 --> 01:26:52,559
Speaker 1: kind of based on the value system of I'd like

1504
01:26:52,600 --> 01:26:54,679
Speaker 1: there to be more bears. I think that this thing

1505
01:26:55,439 --> 01:26:58,320
Speaker 1: that we've come up with would allow them to be

1506
01:26:58,360 --> 01:27:01,960
Speaker 1: more bears. And I think obviously for your standpoint, you

1507
01:27:01,960 --> 01:27:03,920
Speaker 1: you want there to be more bears too, and so

1508
01:27:04,120 --> 01:27:06,240
Speaker 1: but but you know, let me give you an example

1509
01:27:06,280 --> 01:27:09,000
Speaker 1: you're talking about maybe we can come together on something.

1510
01:27:09,080 --> 01:27:12,200
Speaker 1: I have a colleague at Utah State who had a

1511
01:27:12,280 --> 01:27:16,479
Speaker 1: master's thesis student who was going to ask what do

1512
01:27:16,840 --> 01:27:22,000
Speaker 1: Utah's think about wolves coming into Utah? He almost lost

1513
01:27:22,040 --> 01:27:24,759
Speaker 1: his job because he was going to ask the question.

1514
01:27:25,200 --> 01:27:28,120
Speaker 1: I talked to him yesterday and the day before. Now,

1515
01:27:28,560 --> 01:27:33,439
Speaker 1: that is a form of political censure, even about a question.

1516
01:27:33,880 --> 01:27:36,320
Speaker 1: I mean, that sort of thing drives me goddamn nuts

1517
01:27:37,120 --> 01:27:41,800
Speaker 1: because here, here is a belief system that you can't

1518
01:27:41,840 --> 01:27:45,280
Speaker 1: even ask a question about a controversial issue. Why do

1519
01:27:45,360 --> 01:27:47,080
Speaker 1: you think it is with wolves and bears that that is?

1520
01:27:47,160 --> 01:27:50,960
Speaker 1: I mean, you're obviously, you know, like you're passionate about it. I'm,

1521
01:27:51,040 --> 01:27:52,680
Speaker 1: like I said, I'm not. I haven't spent as much

1522
01:27:52,680 --> 01:27:56,160
Speaker 1: time with it as you, but I'm but I'm as

1523
01:27:56,200 --> 01:27:59,519
Speaker 1: objective as I can in the data and the science.

1524
01:27:59,520 --> 01:28:03,200
Speaker 1: And that's what I've done with my students. I don't say, uh,

1525
01:28:03,840 --> 01:28:07,280
Speaker 1: your thesis will be much better if you make a

1526
01:28:07,280 --> 01:28:12,400
Speaker 1: lot of statements about how nice and more bears would be. No,

1527
01:28:12,640 --> 01:28:17,320
Speaker 1: so you say what your results are in the implications

1528
01:28:17,360 --> 01:28:21,080
Speaker 1: of them for management. Right, So that's the way, Yeah,

1529
01:28:21,120 --> 01:28:22,840
Speaker 1: we should talk about And I was doing a little

1530
01:28:22,840 --> 01:28:24,519
Speaker 1: bit of I will admit I didn't get as far

1531
01:28:24,640 --> 01:28:28,200
Speaker 1: enough as I wanted into this, Like your your thoughts

1532
01:28:28,280 --> 01:28:32,720
Speaker 1: on how expanded bear populations, expanded bear habitat, expanded bear

1533
01:28:32,800 --> 01:28:35,559
Speaker 1: protections would work. I think that's an important thing to cover.

1534
01:28:35,680 --> 01:28:38,280
Speaker 1: We haven't covered that. We should, so run us through

1535
01:28:38,360 --> 01:28:41,000
Speaker 1: kind of your philosophies when it comes to that. Well,

1536
01:28:41,080 --> 01:28:45,240
Speaker 1: we have protections as the Europeans have for keeping wolves

1537
01:28:45,520 --> 01:28:48,719
Speaker 1: away from cattle. For example, there are breeds of dogs,

1538
01:28:48,760 --> 01:28:53,560
Speaker 1: mountain dogs that are race of sheep and basically stop predation.

1539
01:28:54,040 --> 01:28:56,080
Speaker 1: But you know, the French and the Spanish are still

1540
01:28:56,120 --> 01:28:58,880
Speaker 1: fighting over brown there's they're bringing them back in three

1541
01:28:58,960 --> 01:29:03,280
Speaker 1: or four areas, and uh, in Sweden they're expanding from

1542
01:29:03,720 --> 01:29:06,280
Speaker 1: in a Norway and the Norwegians don't like them at

1543
01:29:06,320 --> 01:29:08,519
Speaker 1: all because they raise a lot of sheep. They also

1544
01:29:08,640 --> 01:29:14,960
Speaker 1: kill whales in large numbers. Uh. I think it's always

1545
01:29:14,960 --> 01:29:19,599
Speaker 1: going to be contentious because partly it's it still goes

1546
01:29:19,640 --> 01:29:24,519
Speaker 1: back to values. People don't like to believe that, but

1547
01:29:24,680 --> 01:29:29,680
Speaker 1: they United States has tremendous differences of opinion. You have

1548
01:29:29,720 --> 01:29:35,080
Speaker 1: a president right now whose view of women is pretty atrocious,

1549
01:29:35,680 --> 01:29:39,479
Speaker 1: but he is pretty damn popular. He didn't win the

1550
01:29:39,560 --> 01:29:42,360
Speaker 1: vote in the United States, but he has a lot

1551
01:29:42,400 --> 01:29:44,880
Speaker 1: of people backing him. I don't know what they think

1552
01:29:45,000 --> 01:29:47,960
Speaker 1: he's going to bring to the middle class because he's

1553
01:29:48,000 --> 01:29:53,639
Speaker 1: the richest condmn we've rather seen in the presidential chair.

1554
01:29:53,760 --> 01:29:59,560
Speaker 1: I think, uh so, it's it's about values and uh

1555
01:29:59,760 --> 01:30:02,200
Speaker 1: P don't seem to want to shift that much. I'm

1556
01:30:02,360 --> 01:30:07,040
Speaker 1: I'm to get on the gun issue. Uh. The United

1557
01:30:07,080 --> 01:30:09,960
Speaker 1: States to me, I was born in Canada, raised to

1558
01:30:10,360 --> 01:30:13,280
Speaker 1: went through university and then went the States, and the

1559
01:30:13,320 --> 01:30:17,519
Speaker 1: American government paid for much of my education, uh through

1560
01:30:17,560 --> 01:30:22,280
Speaker 1: the spotnik era. But uh the United States is a

1561
01:30:22,320 --> 01:30:25,960
Speaker 1: gun culture through and through and the rest of the

1562
01:30:26,000 --> 01:30:30,719
Speaker 1: countries of the world can't understand this Second Amendment, which

1563
01:30:30,760 --> 01:30:38,280
Speaker 1: is such a so abused, regulated, militious. Uh So you've

1564
01:30:38,280 --> 01:30:41,800
Speaker 1: got values there that people won't bend on. There are

1565
01:30:41,840 --> 01:30:45,320
Speaker 1: more guns than people in the United States Canada. I

1566
01:30:46,160 --> 01:30:50,120
Speaker 1: wanted to get a shotgun. I've handled shotguns. I've owned

1567
01:30:50,280 --> 01:30:54,599
Speaker 1: three fifty seven magnums rifles. I've certified the Park Service

1568
01:30:54,640 --> 01:30:58,719
Speaker 1: to handle weapons. I couldn't buy a gun in Canada

1569
01:30:58,760 --> 01:31:01,400
Speaker 1: until I spent a week on learning how to handle

1570
01:31:01,479 --> 01:31:05,439
Speaker 1: guns and then paying a hundred dollars for a permit

1571
01:31:05,520 --> 01:31:09,599
Speaker 1: to be able to eave and have the shotgun. So, uh,

1572
01:31:09,640 --> 01:31:13,160
Speaker 1: there there's two countries that are very similar. We have

1573
01:31:14,000 --> 01:31:18,320
Speaker 1: much in common. Uh. And I like the americansistently government

1574
01:31:18,400 --> 01:31:21,600
Speaker 1: much more than the Canadian by and large, because you

1575
01:31:21,600 --> 01:31:24,200
Speaker 1: can see the ass off people if they don't If

1576
01:31:24,840 --> 01:31:26,640
Speaker 1: e p. A doesn't do what it's supposed to do,

1577
01:31:26,760 --> 01:31:32,360
Speaker 1: we can't sue organizations in a parliamentary system. That's my

1578
01:31:32,479 --> 01:31:39,200
Speaker 1: personal grief. But getting back to values. People are so

1579
01:31:39,520 --> 01:31:44,960
Speaker 1: intent on guns being for protection, their sprays for protection.

1580
01:31:45,160 --> 01:31:48,920
Speaker 1: Get a knife for protection. You don't need a a

1581
01:31:49,080 --> 01:31:54,479
Speaker 1: K forty seven or Collisha cough to defend yourself. How

1582
01:31:54,479 --> 01:31:58,240
Speaker 1: many people in America use a weapon to defend their

1583
01:31:58,320 --> 01:32:03,479
Speaker 1: for their family. Just get back to bears. You should

1584
01:32:03,479 --> 01:32:07,040
Speaker 1: probably go back to bears. That is another program. I

1585
01:32:07,080 --> 01:32:11,560
Speaker 1: think that, Um, the value system is an interesting is

1586
01:32:11,560 --> 01:32:14,439
Speaker 1: an interesting thing to say, and it's the basis of

1587
01:32:14,439 --> 01:32:16,599
Speaker 1: all policy. Yeah, and I think it's in There's some

1588
01:32:16,640 --> 01:32:18,840
Speaker 1: cultural things that we've already addressed, but I think in

1589
01:32:19,160 --> 01:32:22,360
Speaker 1: a value system way. UM. I think maybe I'm a

1590
01:32:22,400 --> 01:32:25,680
Speaker 1: little more positive about it, uh, because I think that

1591
01:32:25,800 --> 01:32:28,200
Speaker 1: one of the great redeeming values I think of all

1592
01:32:28,280 --> 01:32:30,719
Speaker 1: North America that that's not the case in the continent

1593
01:32:30,760 --> 01:32:35,080
Speaker 1: of Africa. It's questionable in Europe in some ways, just

1594
01:32:35,080 --> 01:32:37,200
Speaker 1: because they're so split up and the countries are so small.

1595
01:32:38,320 --> 01:32:41,200
Speaker 1: Um in North America, especially in the United States, that

1596
01:32:41,280 --> 01:32:45,000
Speaker 1: we have this value where everyone, most everyone that you

1597
01:32:45,040 --> 01:32:46,479
Speaker 1: come in contact with, if you say, like, do you

1598
01:32:46,479 --> 01:32:48,360
Speaker 1: want more wild life? Do you want more places to go?

1599
01:32:48,479 --> 01:32:51,120
Speaker 1: Most people would raise your hand and say yes, regardless

1600
01:32:51,160 --> 01:32:53,320
Speaker 1: of if they're an urban nite or if they live

1601
01:32:53,320 --> 01:32:55,960
Speaker 1: in Montana or whatever. As we talked about earlier, their's

1602
01:32:55,960 --> 01:32:58,360
Speaker 1: perspectives are different because they live in different places and

1603
01:32:58,400 --> 01:33:01,280
Speaker 1: they come to those values quite a patriot. But you know,

1604
01:33:01,439 --> 01:33:05,160
Speaker 1: if you look at people wanting more national parks, when

1605
01:33:05,160 --> 01:33:07,840
Speaker 1: they bring a park into an area, what do you

1606
01:33:07,920 --> 01:33:12,439
Speaker 1: think the locals want? No? Is the answer. And they

1607
01:33:12,520 --> 01:33:14,880
Speaker 1: just took bears Ears and chopped it in half. Hey

1608
01:33:14,960 --> 01:33:19,320
Speaker 1: and Utah. It turns out if you do an economic analysis,

1609
01:33:19,600 --> 01:33:22,880
Speaker 1: every county that had a national park near it, And

1610
01:33:22,960 --> 01:33:26,439
Speaker 1: this is true in Alaska for huge You and I

1611
01:33:26,520 --> 01:33:29,680
Speaker 1: own a huge amount. I'm there a con citizen by

1612
01:33:29,720 --> 01:33:33,719
Speaker 1: the way, naturalized. We own a lot of public land

1613
01:33:33,720 --> 01:33:39,080
Speaker 1: in Alaska, and it is making Alaska a bundle a bundle. Yet,

1614
01:33:39,240 --> 01:33:42,720
Speaker 1: if you asked Alaska's what do you think of the

1615
01:33:42,760 --> 01:33:45,720
Speaker 1: Park Service coming in and that guy Jimmy Carter, that

1616
01:33:45,800 --> 01:33:50,360
Speaker 1: tobacco guy uh setting aside a lot of land. They

1617
01:33:50,400 --> 01:33:53,000
Speaker 1: would tell you that keep the hell keep them the

1618
01:33:53,000 --> 01:33:56,400
Speaker 1: hell out. We Alaskans are we know how to look

1619
01:33:56,439 --> 01:33:59,120
Speaker 1: after our land. Do you recognize that and agree that?

1620
01:33:59,120 --> 01:34:01,160
Speaker 1: That's the reason I sit on the board of a

1621
01:34:01,160 --> 01:34:03,760
Speaker 1: group that's called the back Country Hunters and Anglers were

1622
01:34:03,880 --> 01:34:07,240
Speaker 1: very much a we're pro public lands, pro federal control.

1623
01:34:07,280 --> 01:34:10,080
Speaker 1: Those plans I followed them because they're anti a t V,

1624
01:34:10,320 --> 01:34:12,720
Speaker 1: because a t V s and small the deals are

1625
01:34:12,760 --> 01:34:16,160
Speaker 1: getting into the five country. And so to a program

1626
01:34:16,320 --> 01:34:19,719
Speaker 1: on not bikes too. We've been talking a lot about

1627
01:34:20,720 --> 01:34:22,800
Speaker 1: We've been talking a lot about e bikes here lately too.

1628
01:34:22,800 --> 01:34:24,559
Speaker 1: But I think I sit on the board of that

1629
01:34:25,400 --> 01:34:27,400
Speaker 1: that group, and I sit on that board because I

1630
01:34:27,439 --> 01:34:30,400
Speaker 1: think that there's a there's a huge movement. The public

1631
01:34:30,439 --> 01:34:34,360
Speaker 1: land movement within hunting is huge. Um. You know, the

1632
01:34:35,240 --> 01:34:38,040
Speaker 1: opinions that you reference, I think are are old. I

1633
01:34:38,080 --> 01:34:41,880
Speaker 1: think the new version of the American hunting mindset and

1634
01:34:41,880 --> 01:34:45,479
Speaker 1: the American hunting value system includes federally controlled public lands

1635
01:34:45,479 --> 01:34:50,040
Speaker 1: that are managed for wildlife. Alaska wildlife are just some

1636
01:34:50,240 --> 01:34:53,160
Speaker 1: wild I hope all wildlife. That's not always been the case.

1637
01:34:54,120 --> 01:34:57,960
Speaker 1: But we are talking groups that are out for some wildlife. Well,

1638
01:34:58,160 --> 01:35:02,400
Speaker 1: they're anti carnivore, we've they have no use for song birds,

1639
01:35:02,800 --> 01:35:06,479
Speaker 1: you know. But it's totally they're political as hell too.

1640
01:35:06,520 --> 01:35:09,760
Speaker 1: I think that their name I probably got a case

1641
01:35:09,800 --> 01:35:12,080
Speaker 1: of denial going on. Well, but I think, like I said,

1642
01:35:12,080 --> 01:35:13,679
Speaker 1: you've got a lot of strong opinions, man, I dig

1643
01:35:13,720 --> 01:35:17,200
Speaker 1: it um. But I think in general, I believe that

1644
01:35:17,439 --> 01:35:21,439
Speaker 1: the hunting, the sustainable hunting movement that I'm a part of,

1645
01:35:21,479 --> 01:35:24,080
Speaker 1: and that's that there's hundreds of thousands of people that

1646
01:35:24,320 --> 01:35:27,280
Speaker 1: follow this and listen to this and understand. I'm trying

1647
01:35:27,280 --> 01:35:29,760
Speaker 1: to trying to teach it, trying to understand it better.

1648
01:35:29,800 --> 01:35:32,760
Speaker 1: I taught it as a positive value when it's done right.

1649
01:35:32,960 --> 01:35:37,160
Speaker 1: Beats market hunting, beats poaching, beats that's what we're talking about.

1650
01:35:37,200 --> 01:35:38,920
Speaker 1: I think we could do everything, we could beat holes

1651
01:35:38,960 --> 01:35:41,120
Speaker 1: and everything and be anti This strands to that, but

1652
01:35:41,160 --> 01:35:44,080
Speaker 1: that's that's what That's what I believe is can be

1653
01:35:44,120 --> 01:35:46,920
Speaker 1: the future will be the future, and it's something that

1654
01:35:46,960 --> 01:35:49,200
Speaker 1: we can all agree on and we can get into

1655
01:35:49,280 --> 01:35:52,320
Speaker 1: like far right wing, this far left wing that. But

1656
01:35:52,320 --> 01:35:55,680
Speaker 1: but I don't well, I'd like I'd like to have

1657
01:35:55,840 --> 01:36:00,960
Speaker 1: sometimes get only women wildlife managers to command because there's

1658
01:36:00,960 --> 01:36:03,759
Speaker 1: a cultural shift going on there. I I was asked

1659
01:36:03,800 --> 01:36:07,400
Speaker 1: to be a consultant on their viewing policy for the province.

1660
01:36:07,680 --> 01:36:13,680
Speaker 1: I was paid two to review their draft report on

1661
01:36:13,760 --> 01:36:18,960
Speaker 1: their viewing big deal in British Columbia. Uh. British Clumbia

1662
01:36:19,000 --> 01:36:24,360
Speaker 1: has a nailed dominated hunter mentality in the in the

1663
01:36:24,960 --> 01:36:29,920
Speaker 1: fishing game that it's hard to describe. But the people

1664
01:36:29,960 --> 01:36:33,760
Speaker 1: that wrote that they're viewing were bright young women who

1665
01:36:33,880 --> 01:36:37,160
Speaker 1: weren't hunters. I don't know whether hunters or not. I'm

1666
01:36:37,200 --> 01:36:40,680
Speaker 1: not against hunting you and I could. I'd love to

1667
01:36:40,840 --> 01:36:46,160
Speaker 1: shoot a noose and take it home. But I I

1668
01:36:46,320 --> 01:36:50,920
Speaker 1: really appreciated the difference that these women brought because they

1669
01:36:50,960 --> 01:36:56,000
Speaker 1: didn't have a culture that there's are not anything as

1670
01:36:56,040 --> 01:36:58,519
Speaker 1: good as a care there or a moose on an article,

1671
01:36:58,560 --> 01:37:00,479
Speaker 1: as you know what I'm saying, Oh no in And

1672
01:37:00,560 --> 01:37:03,479
Speaker 1: I think they can be objective a lot easier than

1673
01:37:03,560 --> 01:37:06,679
Speaker 1: a bunch of jobs like us. And I think in general,

1674
01:37:06,760 --> 01:37:09,639
Speaker 1: like I don't I don't look at people. LE would say,

1675
01:37:09,880 --> 01:37:11,400
Speaker 1: I try not to look people just look at it.

1676
01:37:11,479 --> 01:37:13,280
Speaker 1: Oh your gender makes you different or your color makes

1677
01:37:13,280 --> 01:37:15,639
Speaker 1: you different. Like, but you're right though, in the way

1678
01:37:15,760 --> 01:37:21,120
Speaker 1: that our audience is mail, hunting culture has predominantly been met. Now,

1679
01:37:21,960 --> 01:37:24,840
Speaker 1: how we fix that, Well, there's that's arguable. Well it

1680
01:37:24,920 --> 01:37:27,240
Speaker 1: needs we need more and better perspective. That's the only

1681
01:37:27,280 --> 01:37:28,880
Speaker 1: way to do this, the right way, just talking to

1682
01:37:28,880 --> 01:37:32,880
Speaker 1: diversity and a single single thinking that used to be

1683
01:37:33,280 --> 01:37:36,640
Speaker 1: of course, drove all my friends who are nailed by

1684
01:37:36,720 --> 01:37:41,280
Speaker 1: and large not because of the hunting culture, that it

1685
01:37:41,439 --> 01:37:46,520
Speaker 1: invaded the management of all our wildlife, not just some wildlife,

1686
01:37:46,600 --> 01:37:49,160
Speaker 1: but all of it. So I think that's changing, and

1687
01:37:49,240 --> 01:37:51,120
Speaker 1: I'm very positive, but I think it's I think it's

1688
01:37:51,200 --> 01:37:53,360
Speaker 1: changing too. And I think we've had lots of conversations.

1689
01:37:54,280 --> 01:37:56,120
Speaker 1: Like I said, we just talked about geist and and

1690
01:37:57,040 --> 01:38:00,360
Speaker 1: a lot of a lot of opinions that are people

1691
01:38:00,400 --> 01:38:02,719
Speaker 1: would say, oh, that's negative predator. And then he'll slide

1692
01:38:02,720 --> 01:38:05,280
Speaker 1: a book across the table that has stories of Russian

1693
01:38:05,400 --> 01:38:07,360
Speaker 1: that has he's got a book that he wants to

1694
01:38:07,360 --> 01:38:09,960
Speaker 1: try to get us to publish that is just from Russia,

1695
01:38:10,400 --> 01:38:13,800
Speaker 1: stories of wolf attacks on humans and and some of

1696
01:38:13,880 --> 01:38:16,519
Speaker 1: the different things and and a lot of people got

1697
01:38:16,600 --> 01:38:19,439
Speaker 1: that twisted around, I thought, because I said, look, this

1698
01:38:19,479 --> 01:38:21,559
Speaker 1: guy's just and he did a lot of study comparing

1699
01:38:21,640 --> 01:38:24,200
Speaker 1: what's happening North America, what's happening, and trying to figure

1700
01:38:24,240 --> 01:38:26,680
Speaker 1: out what what is driving the wolves to do what

1701
01:38:26,760 --> 01:38:29,519
Speaker 1: they do, not kill them all, save them all, because

1702
01:38:29,560 --> 01:38:32,879
Speaker 1: neither of those things I think can really be applied

1703
01:38:32,920 --> 01:38:38,400
Speaker 1: to what we're currently working on. It's good, good information

1704
01:38:38,560 --> 01:38:42,200
Speaker 1: data or whatever on wolves killing people who miss grow

1705
01:38:43,000 --> 01:38:45,360
Speaker 1: I mean overnight. You can't even get a person that's

1706
01:38:45,360 --> 01:38:48,840
Speaker 1: watched a car accident describe what's actually happening. And as

1707
01:38:48,880 --> 01:38:52,759
Speaker 1: far as writing a book about all the wolf attacks

1708
01:38:52,840 --> 01:38:55,599
Speaker 1: on humans, you could write a book on the man

1709
01:38:55,720 --> 01:39:00,360
Speaker 1: that killed their children, uh, and write a book on

1710
01:39:00,600 --> 01:39:04,160
Speaker 1: going from country to country to see what fathers have

1711
01:39:04,560 --> 01:39:09,559
Speaker 1: killed their children, and uh, it turns out that men

1712
01:39:09,680 --> 01:39:13,200
Speaker 1: that haven't fathered the children were stepfathers are the biggest

1713
01:39:13,640 --> 01:39:17,840
Speaker 1: group of people that kill our children. So there's some

1714
01:39:18,000 --> 01:39:21,240
Speaker 1: evolution going on here and some sociology that we're just

1715
01:39:21,880 --> 01:39:25,280
Speaker 1: starting to crack the surface. So I say that because

1716
01:39:25,960 --> 01:39:30,519
Speaker 1: you can say the wolves uh kill people, and there's

1717
01:39:30,520 --> 01:39:34,320
Speaker 1: all this data from Europe, you're playing into the fear

1718
01:39:34,400 --> 01:39:37,879
Speaker 1: of wolves and the anti wolve sentiment in North America

1719
01:39:38,000 --> 01:39:41,360
Speaker 1: because they're other than a couple of cases of rabies,

1720
01:39:41,800 --> 01:39:45,519
Speaker 1: there haven't been wolves. Wolves are the hardest animals to

1721
01:39:45,600 --> 01:39:51,679
Speaker 1: get to kill people, and any other idea you can say, well,

1722
01:39:52,800 --> 01:39:56,719
Speaker 1: you know, talking about grabbing women's crotches, that's just locker

1723
01:39:56,800 --> 01:40:00,439
Speaker 1: room cock. Like Trump's wife said, I don't read with that.

1724
01:40:01,840 --> 01:40:06,400
Speaker 1: It isn't just locker room talk. It's a deplorable behavior.

1725
01:40:06,720 --> 01:40:09,360
Speaker 1: And I think some of the stuff about wolves is

1726
01:40:09,360 --> 01:40:12,400
Speaker 1: also deplorable. Well, I ranted it when I was in

1727
01:40:12,640 --> 01:40:14,479
Speaker 1: in Berkeley talking to folks. They would bring up when

1728
01:40:14,479 --> 01:40:17,479
Speaker 1: we were talking about animal rights per se, they would

1729
01:40:17,520 --> 01:40:21,680
Speaker 1: bring up things like slavery and rape and like all

1730
01:40:21,720 --> 01:40:23,920
Speaker 1: these really what I would say, like raally far out

1731
01:40:24,000 --> 01:40:27,680
Speaker 1: analogies that kind of stopped the conversation, and I just like,

1732
01:40:27,840 --> 01:40:31,920
Speaker 1: listen and similar with these, you know, fathers and kids things.

1733
01:40:32,640 --> 01:40:34,080
Speaker 1: I don't know where to do with that because I

1734
01:40:34,160 --> 01:40:37,880
Speaker 1: just I feel like it's far away because it's a stereotype,

1735
01:40:37,960 --> 01:40:41,280
Speaker 1: and there's a stereotype about the danger from wolves. Wow,

1736
01:40:41,360 --> 01:40:43,639
Speaker 1: But you know, I don't know, like I said, I'm

1737
01:40:43,640 --> 01:40:48,280
Speaker 1: not I don't speak for other guests. Saying it's a stereotype. Well,

1738
01:40:48,320 --> 01:40:51,120
Speaker 1: I'm sure there's a stereotype. Well there's it's perpetuated bout

1739
01:40:51,160 --> 01:40:54,160
Speaker 1: Hollywood's perpetuated in lots of ways. And I don't want

1740
01:40:54,200 --> 01:40:59,880
Speaker 1: to increase the stereotype negative. You've told me about south Side,

1741
01:40:59,880 --> 01:41:02,240
Speaker 1: Now heard anybody to talk about all the studies in

1742
01:41:02,360 --> 01:41:07,400
Speaker 1: Europe and all I said about wolves killing people? Never

1743
01:41:07,479 --> 01:41:09,760
Speaker 1: heard of it. I'm not. I'm not telling you that

1744
01:41:09,840 --> 01:41:12,080
Speaker 1: to like perpetuate a stereotype and telling you because guess what,

1745
01:41:12,560 --> 01:41:15,840
Speaker 1: that's what the end of the result is. Don't sit

1746
01:41:15,920 --> 01:41:18,519
Speaker 1: there as a journalism and tell me that you bring

1747
01:41:18,640 --> 01:41:22,599
Speaker 1: up a particular issue treated in a certain way, isn't

1748
01:41:23,240 --> 01:41:26,040
Speaker 1: isn't increasing a stereotype. Sorry, I didn't mean to keep

1749
01:41:26,160 --> 01:41:29,960
Speaker 1: hitting your equipment here. I know Gilbert kept hitting, but

1750
01:41:30,080 --> 01:41:34,080
Speaker 1: he will knock the microphone around, throwing stuff at us.

1751
01:41:34,680 --> 01:41:37,160
Speaker 1: Um I think that. No, I'm not trying to petuate

1752
01:41:37,720 --> 01:41:42,880
Speaker 1: I don't have I don't have it, and that I am.

1753
01:41:43,040 --> 01:41:46,760
Speaker 1: But journalists, I mean, look, listen, you can't defend that.

1754
01:41:46,880 --> 01:41:50,840
Speaker 1: Journalists don't have much effect. I mean that's what your

1755
01:41:50,920 --> 01:41:54,720
Speaker 1: business is. You're you're selling a product, and unfortunately a

1756
01:41:54,800 --> 01:41:57,760
Speaker 1: lot of newspapers, the lord blood. We used to say

1757
01:41:57,840 --> 01:42:01,360
Speaker 1: in civil rights, Uh you asked that. You see, you're

1758
01:42:01,360 --> 01:42:03,680
Speaker 1: going to have a march on campus in favor of

1759
01:42:04,120 --> 01:42:10,479
Speaker 1: integration there on talking North Carolina years ago, the news

1760
01:42:10,600 --> 01:42:13,599
Speaker 1: media would say, if you think there's gonna be blood,

1761
01:42:14,040 --> 01:42:20,519
Speaker 1: call us right, what does that mean? I don't know.

1762
01:42:22,040 --> 01:42:26,040
Speaker 1: What do you think? M hm, try not to I

1763
01:42:26,080 --> 01:42:29,559
Speaker 1: don't know. Man's let me just let me just finish

1764
01:42:29,640 --> 01:42:32,800
Speaker 1: the statement. It's about if there's violence, we love it.

1765
01:42:32,960 --> 01:42:36,360
Speaker 1: We're gonna carry it on our on our program. Alright,

1766
01:42:37,000 --> 01:42:43,720
Speaker 1: let's just end it there. I guess I grew up

1767
01:42:43,800 --> 01:42:51,280
Speaker 1: on an older all right, guys, that was interesting, right, Phil, Yeah,

1768
01:42:51,280 --> 01:42:53,280
Speaker 1: I think you stopped at about the right time. I

1769
01:42:53,320 --> 01:42:55,639
Speaker 1: would say, yeah, I don't like I don't draw many lines,

1770
01:42:55,760 --> 01:42:58,840
Speaker 1: but I let it. Probably let it go on way

1771
01:42:58,880 --> 01:43:02,280
Speaker 1: too long. I think it was. It was worth the effort.

1772
01:43:02,360 --> 01:43:05,080
Speaker 1: I'd say. I couldn't believe when he was out to leave,

1773
01:43:05,360 --> 01:43:07,080
Speaker 1: I thought you were just going to let him walk out,

1774
01:43:07,280 --> 01:43:09,960
Speaker 1: and I was expecting you kept you kept him in

1775
01:43:10,000 --> 01:43:12,000
Speaker 1: the room. And I mean the interview went on for

1776
01:43:12,000 --> 01:43:14,479
Speaker 1: about an hour and twenty minutes. That's a solid interview.

1777
01:43:15,120 --> 01:43:17,760
Speaker 1: Where about where it fell apart where it nearly fell

1778
01:43:17,800 --> 01:43:21,280
Speaker 1: apart several times. UM, so yeah, I thought it was.

1779
01:43:21,600 --> 01:43:23,200
Speaker 1: I thought you did a good job. Well, thanks Phil.

1780
01:43:23,200 --> 01:43:26,120
Speaker 1: I appreciate that, um, and I appreciate everybody sticking in

1781
01:43:26,120 --> 01:43:28,040
Speaker 1: and listening to that. That was it was one again

1782
01:43:29,000 --> 01:43:32,120
Speaker 1: and thanks to Mr Anthony Lecada for joining us me's

1783
01:43:32,200 --> 01:43:35,000
Speaker 1: editor in chief. It's one that we talked about a lot.

1784
01:43:35,120 --> 01:43:39,560
Speaker 1: I mean it really drove like some some energy in

1785
01:43:39,640 --> 01:43:43,800
Speaker 1: the room when we were done, like he kind of

1786
01:43:43,880 --> 01:43:47,559
Speaker 1: set a buzz the office because our our man Barry

1787
01:43:47,640 --> 01:43:50,080
Speaker 1: kind of came in and little fire. Yeah. I I

1788
01:43:50,200 --> 01:43:52,240
Speaker 1: left the room and I started walking around the office

1789
01:43:52,800 --> 01:43:54,880
Speaker 1: and I realized I had no purpose to where I

1790
01:43:54,960 --> 01:43:56,560
Speaker 1: was going. I was, I just needed to kind of

1791
01:43:56,760 --> 01:43:58,960
Speaker 1: keep moving. It was. It was bizarre and I was

1792
01:43:59,280 --> 01:44:02,080
Speaker 1: I was just getting energy plenty jittery after that. I

1793
01:44:02,080 --> 01:44:05,479
Speaker 1: mean it was. It was a strange happenstance. It was

1794
01:44:05,600 --> 01:44:09,920
Speaker 1: not to be expected. But um, hopefully it was an

1795
01:44:10,040 --> 01:44:13,720
Speaker 1: entertaining and somewhat informative version of the Hunting Collective, a

1796
01:44:13,800 --> 01:44:17,439
Speaker 1: different version what you normally get. And so thank you

1797
01:44:17,520 --> 01:44:19,960
Speaker 1: for listening. We won't get into any other big asks

1798
01:44:20,040 --> 01:44:22,000
Speaker 1: of you today. We'll let you just digest what you heard.

1799
01:44:22,280 --> 01:44:24,040
Speaker 1: I'm sure you'll have some comments. Hit me up on

1800
01:44:24,120 --> 01:44:26,599
Speaker 1: social media or the t h T at the media

1801
01:44:26,640 --> 01:44:29,439
Speaker 1: dot Com. Happy to talk through it with you if

1802
01:44:29,479 --> 01:44:32,360
Speaker 1: it needs some Catharsis after this one. So next week

1803
01:44:33,520 --> 01:44:36,400
Speaker 1: back to the normal show, right Phil, hopefully? I don't know.

1804
01:44:36,680 --> 01:44:38,559
Speaker 1: You don't you can't make any promises. I can't make

1805
01:44:38,560 --> 01:44:40,760
Speaker 1: any promise. I'm gonna have a white claw. We'll see

1806
01:44:40,760 --> 01:44:44,599
Speaker 1: you next time by because I can't go a week

1807
01:44:44,680 --> 01:45:15,200
Speaker 1: without doing run with drinking. Don't sit in as the boss, fool.

1808
01:45:15,360 --> 01:45:18,559
Speaker 1: Stop the grow roots feeling like in all on our

1809
01:45:18,760 --> 01:45:22,040
Speaker 1: baross shoes. All tell me, what is that a