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Speaker 1: This is me eater podcast coming at you shirtless, severely,

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

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Speaker 1: can't forget anything, all right, I want to get to

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Speaker 1: I want to do all the introductions and explain where

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Speaker 1: we're at. But first I've a quick question, is based

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Speaker 1: off of painting that I just ran into in the

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Speaker 1: entryway of the Wild Cheap Foundation. Um do wolves get

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Speaker 1: after big horns? I think I think, um mountain line

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Speaker 1: and clay mountain line probably a little bit more of

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Speaker 1: a problem, certainly in the lower forty eight, But yeah,

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Speaker 1: wolves definitely into a thin horn habitat and and big

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Speaker 1: time up in BC and in Alberta. You bet. It

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Speaker 1: just seems like they, I don't know, man, just feels

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Speaker 1: like like a little bit out of there, like that

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Speaker 1: kind of country, seems a little bit out of their

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Speaker 1: area of expertise. But they've him in the winter or

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Speaker 1: what the big horn like down here in lower forty

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Speaker 1: eight in the winter, Well they'll they'll hit them different

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Speaker 1: times of a year. But yeah, absolutely, Uh further south

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Speaker 1: desert big horns. She has great just referenced mountain lions

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Speaker 1: are a little bit tougher, tougher on sheep than wolves,

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Speaker 1: but uh, yeah, it's uh, it's a tough place to

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Speaker 1: make a living. Have there been cases where Mexican gray

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Speaker 1: wolves have killed desert big horns. Don't know about that yet,

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Speaker 1: you know, I don't. I don't have any documentation of that.

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Speaker 1: I have not heard that, but I'm sure they would. Yeah. Man,

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Speaker 1: it seems like a formidable like when you when you

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Speaker 1: factor the topography and then just like the horns structure

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Speaker 1: and stuff, it seems like a formidable foe. They really are.

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Speaker 1: If you if you look at the way the animals built,

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Speaker 1: you know, the way their eyes are positioned on their heads.

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Speaker 1: If you look at these mounts in this room, just

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Speaker 1: just look it. You know how much they see. Uh,

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Speaker 1: you know, their greatest defense. They see a long ways,

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Speaker 1: a lot further than than we do. If you look

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Speaker 1: at the country in which they live, it's the topography

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Speaker 1: is tough. There's always escaped terrain and places for those

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Speaker 1: animals to escape. So you know they've survived. Uh, they've

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Speaker 1: adapted and and learned to deal with predator issues through time.

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Speaker 1: But yeah, it's it's tough. There's a if you're there's

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Speaker 1: a guy I can't remember his name, the professor at

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Speaker 1: University of Alaska at Fairbanks, and he wrote like a

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Speaker 1: natural history book about Alaska, and in and he talks

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Speaker 1: about an eyewitness account of a friend of his who

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Speaker 1: watched a single Linx chase a doll ram donna, gully,

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Speaker 1: jump on its back and kill it with a bike

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Speaker 1: to the basement's neck. Yep, a lynx who's like a

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Speaker 1: snowshoe hair specialist. Well, it's just not it's it's not

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Speaker 1: just the four legged predators either. You have eagles and

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Speaker 1: and other things. In fact, I've observed firsthand golden eagles.

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Speaker 1: I was hiking an area one time, uh, working with sheep,

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Speaker 1: and in overhead I saw a lamb go by it.

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Speaker 1: No really, Oh yeah, so it's it's not just the

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Speaker 1: four legged prey. That's pretty nuts. I heard that they

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Speaker 1: kill them, But then though they carried him off, I

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Speaker 1: thought they just like ran them off. They somehow scared

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Speaker 1: him or spooked him or ran them off ledges and

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Speaker 1: then killed him. Yeah, observed it firsthand. They picked them up.

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Speaker 1: You know, they're small, tiny, a little lamb, Yeah, exactly.

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Speaker 1: We watched a golden eagle spend twenty minutes working over

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Speaker 1: a bull elk. Here's two gold two working over a

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Speaker 1: bull dive bomb in his head. And you could tell

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Speaker 1: us boy did not like he was agitated. Man, I've

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Speaker 1: flown surveys and almost had them land in the helicopter

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Speaker 1: with you, and they are a huge all right, so

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Speaker 1: we we should probably so, Like I said, we're at

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Speaker 1: the you guys called the World Headquarters, World Headquarters, Wildchief Foundation,

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Speaker 1: World Headquarters, Wild Cheap Foundation, Bozeman, Montana. Still in Bozeman,

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Speaker 1: Still in Boseman. It's almost almost Belgrade and almost four corners,

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Speaker 1: but it's it's a Bozeman address. So if I write

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Speaker 1: you a letter, I proposeman, Um, let's go around do uh,

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Speaker 1: let's go around to introductions. We'll do it like I

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Speaker 1: like to do it, as though I'm dealing cards. And

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Speaker 1: so you're up. Uh. Garrett Longs on the marketing and

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Speaker 1: communications director here Uh Exhibits and sponsors manager, store manager,

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Speaker 1: UM what else? Cre you clean? Toilet clean toilets um

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Speaker 1: on a frequent basis. And I came over here just recently,

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Speaker 1: about three months ago. I previously was the conservation leader

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Speaker 1: over at Sitka UM sick of gear just down the road, UM,

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Speaker 1: and came over here to just do real conservation work,

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Speaker 1: and it's been a blast. Man, it's been pretty cool.

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Speaker 1: So you guys probably have a you probably had a

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Speaker 1: relationship with this organization when you were there, because I

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Speaker 1: know Sake of does a lot of stuff in support

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Speaker 1: of Yeah, so so my job there it was actually

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Speaker 1: kind of inverse. So what it is here. I I

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Speaker 1: took in all the contracts, conservation contracts, and decided what

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Speaker 1: we spent money on prioritized conservation organizations. So it was

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Speaker 1: great actually coming to the Wild Cheap Foundation because they

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Speaker 1: were one of one of the groups that I use

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Speaker 1: as an example, you know, going through like forms and

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Speaker 1: things like that with other organizations like hey, this is

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Speaker 1: what we're looking for. These are the type of projects

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Speaker 1: we want to fund, um all that kind of stuff.

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Speaker 1: So it was pretty cool getting a call from Gray

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Speaker 1: But yeah, I had worked with them a lot, and

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Speaker 1: then I still work with them over there a lot

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Speaker 1: too because they support us very heavily. That's great, Go ahead,

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Speaker 1: sir uh Clay Brewer. I'm the Big Horn program lead

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Speaker 1: UH conservation director for the Wild Chief Foundation. I worked

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Speaker 1: for almost thirty years Texas Departs and while off department

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Speaker 1: was the did a lot of things. Was the the

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Speaker 1: big Horn mule deer prong horn guy for years. UH

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Speaker 1: served in various leadership roles. UH actually served as the

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Speaker 1: interim Widlife director for a year and a half and

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Speaker 1: and UH So my experience I have UH primarily on

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Speaker 1: the ground experience. UM, I'm not necessarily enamored with these

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Speaker 1: sorts of things that we're doing here today. I've I've

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Speaker 1: spent my life out in the middle of nowhere, and

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Speaker 1: I enjoy that that aspect of it. So UH, I

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Speaker 1: spent the majority of my my career restoring cheap big

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Speaker 1: horn cheap in Texas. They were extrapated by about nineteen sixty,

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Speaker 1: and so through our efforts that as late as nineteen

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Speaker 1: sixty and then got extrapated. The last documented sighting of

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Speaker 1: a native Texas big horn occurred October of nineteen fifty eight.

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Speaker 1: In the series D you have Little Mountains, which is

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Speaker 1: a little bit south of U of the Guadaloupe Mountains.

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Speaker 1: Usually we're talking about something vanishing. It's twenty years earlier.

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Speaker 1: Nineteen sixty was what what we guess. Anyway, So after that, UH,

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Speaker 1: lots of work, lots of transplants, lots of things, going on.

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Speaker 1: But uh, bighorns sheep at late eighteen hundred population levels

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Speaker 1: right now, was anybody okay? In nineteen sixty in Texas

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Speaker 1: after the last one vanished? Was it? What a day

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Speaker 1: later they started recovery? I mean, were they were already

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Speaker 1: paying attention to it as they were on their way out. Well,

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Speaker 1: there was a guy hired in the forties and uh,

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Speaker 1: this is a guy by the name of Birch Carson.

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Speaker 1: He was hired to document the decline a bighorn cheap

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Speaker 1: in Texas. And so today, well I give I'll give

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Speaker 1: you my experience. I was a younger guy then and

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Speaker 1: and was hiking through the mountains and it was actually, uh,

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Speaker 1: we we did and still got all of our own

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Speaker 1: sheep hunts. So I was preparing the first first had

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Speaker 1: a sheep hunter coming here. You mean the state guys,

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Speaker 1: State of Texas. Yes, and you guys give out how

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Speaker 1: many tags every year? Well it varies down now fifteen

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Speaker 1: sixteen seventeen tags every year. So we've come along ways.

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Speaker 1: So if you draw a big horn tag in Texas,

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Speaker 1: you go out and hunt with a you go out

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Speaker 1: or guided by a state biologist. Or well, if you

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Speaker 1: buy a state tag. Uh, they're also private landowner tags.

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Speaker 1: That's a little bit different. Um. Some some hunters prefer

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Speaker 1: to bring their own their own guide, which which is fine.

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Speaker 1: We like that too. Um it makes us no difference.

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Speaker 1: But uh so anywather you you asked me about the

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Speaker 1: did they see it coming? And and um, Texas was

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Speaker 1: no different than the rest of the states where you

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Speaker 1: you hear about the domestic sheep issues. And we lost

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Speaker 1: our sheep for the very same reasons. And so a

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Speaker 1: guy by the name of Birch Carson was hired in

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Speaker 1: the forties to document the disappearance of big horn sheep

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Speaker 1: in Texas. And so I was getting ready for sheep hunt,

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Speaker 1: and I was hiking along that It was in January,

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Speaker 1: and it was pretty cool, cool in the mountains, and um,

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Speaker 1: so I was. I was walking down the ridge, and

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Speaker 1: I decided to get off the ridge and I started

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Speaker 1: hiking down a deer trail. And so I walked the

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Speaker 1: deer trail for a ways and I came into an opening,

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Speaker 1: a small bowl in the bottom of these three just

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Speaker 1: three knobs around and and he got steel. The wind

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Speaker 1: stop blowing and it got steel. And I thought, man,

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Speaker 1: this would be a great place to eat my lunch,

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Speaker 1: took my pack frame off, sat out on the ground.

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Speaker 1: I looked over on the ground. It said there was

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Speaker 1: a carving in the rocket. It said W. B. Carson,

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Speaker 1: sheep inspector in ninety And so he became a hobby

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Speaker 1: of mine. Uh. I spent a lot of time by myself,

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Speaker 1: and so I started looking for these things. And every

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Speaker 1: time I thought I was the only human being to

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Speaker 1: ever see this, I would look around on the ground

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Speaker 1: and I would find another carving and it would say

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Speaker 1: cheap inspector, Uh Burt W B. Carson. And so I

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Speaker 1: found caves the guy lived in. There's one. There's a

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Speaker 1: cave in the Texas Mountains where the guy's clothes are

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Speaker 1: still hanging in the cave today. And so so he

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Speaker 1: documented the decline. That's nuts man, That's like Boone and

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Speaker 1: Boone's day, right through names on. Oh, it's it's it's

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Speaker 1: interesting history. There there's a a guy named Bob Anderson.

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Speaker 1: You guys are probably familiar with great rams one to three. Um.

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Speaker 1: He became interested in in Birch Carson and so he uh,

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Speaker 1: he actually wrote a book, He's got one. I wrote

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Speaker 1: the forward for his book and and Uh, he never

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Speaker 1: has published it. He hadn't done anything with it, so

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Speaker 1: he's trying to figure out who his audience was. But

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Speaker 1: it's called something like the Desert Wonder or something like that.

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Speaker 1: So the guy was a taxidermist and just interesting history.

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Speaker 1: World War two veteran. Uh was injured in World War

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Speaker 1: Two and came back and hiked those mountains with a

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Speaker 1: limp and so, you know, pretty rough country. So uh

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Speaker 1: So a short time later, in the mid fifties, there

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Speaker 1: was a cooperative agreement developed between the the at that time,

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Speaker 1: the Texas Game Fish and I wish your commission um

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Speaker 1: boone and Crockett Club, Arizona Game and Fish Department. Uh,

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Speaker 1: I'm trying to remember who else Wildlife Management Institute. Uh

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Speaker 1: we brought sheep in from Arizona and uh try and

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Speaker 1: in the early years there, uh you know, in the

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Speaker 1: early nineteen hundreds, like most jurisdictions, it was people focused

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Speaker 1: on protections. Uh there were like in Texas nineteen o

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Speaker 1: three there was a hunting prohibition enacted and so then

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Speaker 1: then in the mid fifties it was propagation. Um. You know,

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Speaker 1: there's always a joke running around in those days. Most states,

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Speaker 1: the Desert Bighorn Council was formed in the fifties because

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Speaker 1: every state was in the same boat. And uh, some

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Speaker 1: people would have you know, they only had two sheep left,

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Speaker 1: and they knew him by name, you know, and Bob

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Speaker 1: didn't feel so well. It was it was kind of

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Speaker 1: the joke, the running joke, and so so anyway, so

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Speaker 1: propagation efforts were implemented in the mid nineteen fifties and

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Speaker 1: and since that time, UH two seven while sheeper translocated

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Speaker 1: to Texas. Uh coming out of Arizona, no different places.

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Speaker 1: I'm sorry, and I think I think I have those

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Speaker 1: numbers wrong. It's more like it's it's it's uh. I

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Speaker 1: think a total of a hundred and seven came from Nevada,

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Speaker 1: thirty one from Arizona, six from Mexico, and too from Utah.

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Speaker 1: So that's the lineage of of today's desert bighorn populations

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Speaker 1: in Texas. And so, uh so we worked together. We

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Speaker 1: we traded. In the early years, we traded Arizona, UH

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Speaker 1: four pronghorn they they had, they were short on pronghorn

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Speaker 1: at that time. Texas had plenty of prong horns. So

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Speaker 1: we would swamp animals and and more recently, I can

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Speaker 1: tell you I was at a in in those days.

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Speaker 1: The it was a finale convention, and people were coming

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Speaker 1: by my booth from the state of Nevada, and so

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Speaker 1: we're pretty upset with Texas. And I couldn't figure out why,

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Speaker 1: what the what the story was, and I thought, man,

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Speaker 1: just having a bad day. And so later on, I, uh,

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Speaker 1: I was reading newspaper and the headlines with letters about

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Speaker 1: three inches big said state of Nevada trades turkeys for

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Speaker 1: big orange sheep. And so the the the Nevadas were

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Speaker 1: not real happy about that trade, and and so but

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Speaker 1: if it if it were not for that, then none

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Speaker 1: of us would have any wildlife. Um, and so as

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Speaker 1: as time went on in our case, Uh, what's interesting

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Speaker 1: about that is the landowners. You know, we had problems

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Speaker 1: with with disease issues in the thirties and and lost

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Speaker 1: all of our sheep later on. It was a slow progression,

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Speaker 1: we lost those sheep. And so we worked Texas a

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Speaker 1: private landowners state, uh ninety seven percent privately owned, but

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Speaker 1: uh domestic sheep. Landowners raised domestic sheep. And then later

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Speaker 1: on the land the very landowners that we worked with,

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Speaker 1: that where the problems occurred years ago. Are the very

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Speaker 1: same landowners that helped us restore sheep today their descendants

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Speaker 1: and so we did that together. And so, like I said,

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Speaker 1: today we're probably eighteen hundred animals. Um, so we've surpassed

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Speaker 1: the late the late eighteen hundred population levels and and

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Speaker 1: numbers continue to spandu expand populations continue to grow, and

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Speaker 1: so so far, so good. Uh but it only took

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Speaker 1: you know, sixty years or so or seventy years for

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Speaker 1: that to happen. Start figuring out. Yeah, we'll dig into

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Speaker 1: that whole story called Bunch's interesting and then honest of course,

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Speaker 1: go ahead. Scott Peckham, I'm the big game ecologist for

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Speaker 1: the Confederated Tribes of the Matila Indian Reservation in northeast

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Speaker 1: Oregon in southeast Washington. So I work on anything pur

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Speaker 1: view of the big game headline and uh so wear

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Speaker 1: a lot of hats. I should tell you all about

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Speaker 1: the Elk tag I drew. That would be good. I

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Speaker 1: heard extreme in the southeast corner of the state. You

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Speaker 1: know it real well. Points I've seen some big animals

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Speaker 1: in that part of the country. But I know people

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Speaker 1: that really know, really well. I know the sheep country

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Speaker 1: better than the Elk country there, but I do see

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Speaker 1: big bulls in there when I'm doing sheep work. So

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Speaker 1: so you you focus on sheep in that area. Uh.

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Speaker 1: Typically yeah, in in Southeast Washington, I'm usually up there

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Speaker 1: working on the sort of the Hell's Canyon initiative work

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Speaker 1: that's going on. Um, you you back up like like

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Speaker 1: you inform and back up the tribe's perspective on big

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Speaker 1: game management exactly, because that's interesting because you're actually looking

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Speaker 1: at two different states. Yes, yeah, almost three, but yeah,

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Speaker 1: to both Southeast Washington. So there's three tribes under under

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Speaker 1: one treaty UM, the Walla Walla, Cayuse and you Matila

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Speaker 1: Um and they are traditional territory expanded that the state

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Speaker 1: boundaries there. So most of the northern Blue Mountains were

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Speaker 1: towards um Past Look, Grand Oregon, down south towards John Day,

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Speaker 1: so parts of various basins. So what's your like, what's

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Speaker 1: your professional mandate? Then? To basically protect, conserve and restore

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Speaker 1: big game populations and their habitat. That's our program mission

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Speaker 1: and that's that's a directive coming from those tribes. Yes,

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Speaker 1: we have a first foods mission for our Department Natural

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Speaker 1: Resources which is fairly well staffy of about a hundred employees,

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Speaker 1: and d and R itself. Our wildlife programs pretty small

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Speaker 1: about nine employees. Um. But yeah, under the big game mantra,

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Speaker 1: we are that's our directive to protect, restore, and enhance

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Speaker 1: habitat and populations. And I'm guessing you most coordinate with

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Speaker 1: states and all the time. Yea, we work on because

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Speaker 1: basically a lot of the wildlife habitat where the treaty

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Speaker 1: hunting occurs, where the rights are allowed to exercise or

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Speaker 1: treaty hunting right is on federal public lands. So we

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Speaker 1: work with the land managers of BLM and Force Service,

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Speaker 1: and then we work with the states obviously because they

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Speaker 1: tend to do more of the population level management, so

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Speaker 1: we coordinate with them pretty closely like the Feds. Got

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Speaker 1: the Feds are administering a lot of the landscape, but

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Speaker 1: the states are administering a lot of the wildlife a

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Speaker 1: lands exactly, so decisions about land use and land management planning.

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Speaker 1: We're very involved in that with the with the four

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Speaker 1: Service and BLM, and you can spend a lot to

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Speaker 1: have looking at sheep I do that is that unfortunate?

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Speaker 1: Is that a high priority Um, i'd say yes, just

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Speaker 1: conservation wise, Um, the tribe is is very interested in

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Speaker 1: expanding UM populations of sheep. We have a lot of

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Speaker 1: historically good sheep habitat and in those parts of the country. Um,

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Speaker 1: you've been I think you've been to Hell's Canyon. Yeah,

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Speaker 1: but I've gone out looking at big horns and that

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Speaker 1: those populations have struggled. Um. So there's a lot of

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Speaker 1: good work that could be done, and so I think

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Speaker 1: that's where our interest is. Um. Obviously there's you've probably

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Speaker 1: heard about the mule deer issues that are going on.

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Speaker 1: We have, we do have declines and mule deer populations,

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Speaker 1: and but elk are pretty stable, large populations of elk

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Speaker 1: in the Blue Mountains, which you'll get to see. Um.

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Speaker 1: But yeah, sheep is a sort of our biggest conservation

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Speaker 1: concern on on the big game front. I don't want

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Speaker 1: to get ahead of ourselves. Was that because things are

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Speaker 1: getting worse, because they could be so much better? Um.

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Speaker 1: I think in our corner of the world there it's

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Speaker 1: we're sort of at a stagnant stagnant sort of population

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Speaker 1: has leveled off, So I think we could there's a

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Speaker 1: lot we can improve. I think we can make some

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Speaker 1: gains for sure, for sure, but we're not We haven't

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Speaker 1: had a disease, a large die off in several years,

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Speaker 1: but we're only a little ways away from one. We're

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Speaker 1: always on the cusps. So I think there's a lot

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Speaker 1: of work we can do and this kind of forum

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Speaker 1: is a good place to discuss that. And go ahead.

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Speaker 1: Steve gray Thornton, I'm the president of CEO UM. We're

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Speaker 1: here obviously at the at the World headquarters, but we

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Speaker 1: also maintain offices and Cody. We have UM an education

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Speaker 1: coordinator in Nevada. Clay is remote in Texas. We've got

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Speaker 1: a lobbyist in Washington, d c. And in our Montana

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Speaker 1: conservation director is also in Germany, so we we base

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Speaker 1: international operations out of Germany. We work in Kazakhstan, Kyrgyzstan

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Speaker 1: to Jakostan. Isn't it funny how everyone hates lobbyists, But

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Speaker 1: lobbyists can come from any like people just like are like, oh,

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Speaker 1: we lobbyists and you registered. That must be negative. But

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Speaker 1: to think that they are like conservation lobbyists, you know,

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Speaker 1: visional lobbyists, like some guy out to do something evil,

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Speaker 1: you know he does he does he does smoke cigars,

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Speaker 1: so he plays you know, he plays that lobbyist role. Well,

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Speaker 1: you know, we other lobbying on behalf of wild but

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Speaker 1: he's lobbying on behalf of you know, wild sheep and

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Speaker 1: wild Chief restoration. But you know, we called him our

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Speaker 1: advocate and and our legislative affairs director and finally just

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Speaker 1: just just call me a obvious. That's what everyone knows

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Speaker 1: that I am. So you know, we just cut to

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Speaker 1: the chase, and that's what he is. We were just

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Speaker 1: I was just back with him two weeks ago, spent

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Speaker 1: three days advocate advocating for big horn sheep programs and

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Speaker 1: tin horn cheap programs. So when you when you guys

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Speaker 1: are doing that, like when you're down in d c um,

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Speaker 1: what are are you meeting with it? Do you tend

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Speaker 1: to be meeting with individual politicians? Defind me meeting like

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Speaker 1: more on the agency level both. So we we meet

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Speaker 1: with the federal agencies. So all the Land Management U

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Speaker 1: s U S four service. Most bighorn sheep live on

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Speaker 1: uh US for SARS LAMB. But in claim what eighty

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Speaker 1: somewhat percent of bighorn chep live on on the force

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Speaker 1: um BLM. Interesting enough, as huge holdings in Alaska. Alaska's

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Speaker 1: got of all doll sheep and thin horn sheep in

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Speaker 1: North America, so pretty pretty huge population there, forty to

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Speaker 1: fifty dollar sheep. Um. So we we you know, we

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Speaker 1: meet with the BLM, we meet with a four service

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Speaker 1: at times, will meet with the US Fish and Wildlife Service,

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Speaker 1: at times, will meet with the National Park Service, and

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Speaker 1: then on the hill will we'll meet with representatives and

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Speaker 1: senators and their staff. So um, pretty pretty broad bay. See.

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Speaker 1: The issues that we're dealing with are primarily land use issues, UM,

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Speaker 1: some grazing issues and um separation issues between domestic sheep

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Speaker 1: and bighorn sheep and now even sinhorn sheep. Yeah. That

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Speaker 1: that that's why I'd like to get you in spensive time, Max.

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Speaker 1: I think that's that's kind of seems like where so

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Speaker 1: much of the conversation is right now around sheep. I

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Speaker 1: want to do a little bit of backing up and

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Speaker 1: I'll let you guys. You guys just kind of decide

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Speaker 1: by making quick glances among each other to see who

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Speaker 1: should handle what. But I want to like really quickly

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Speaker 1: bring people up to speed on just like sheep taxonomy,

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Speaker 1: which I think can be a little bit confusing. We

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Speaker 1: don't need to go global. We'll just keep it North America.

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Speaker 1: But is a fair to is like when you say,

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Speaker 1: like bighorn thin horn, is that a fair? Is that

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Speaker 1: a fair? If you're gonna take all of our country

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Speaker 1: sheep or US and Canada, it makes some sort of division.

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Speaker 1: It seems like people start with bighorn thin horn. You

385
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Speaker 1: bet so, so you have you know, let's let's take

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Speaker 1: North America's as Mexico, US and Canada perfect um so

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Speaker 1: In in Mexico you have the desert bighorn sheep. Um

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Speaker 1: in in the lower forty eight you have the rocky

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Speaker 1: mountain bighorn sheep and the desert big worn sheep. Then

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Speaker 1: we've got you know, there's kind of uh um splitters

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Speaker 1: and lumpers. There's there's some divisions that come off of

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Speaker 1: there's a California bighorn sheep that's really a rocky mountain

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Speaker 1: and it didn't come from California, came from British Columbia

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Speaker 1: of all places. Um, there's a Sierra Nevada bighorn sheep.

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Speaker 1: There's a Peninsula desert bighorn sheep. So there's there's a

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Speaker 1: bunch of kind of subspecies. But the bottom line is

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Speaker 1: there's desert, big worn sheep, rocky mountain bighorn sheep, and

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Speaker 1: then as we go north, you've got the stone sheep,

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Speaker 1: which is primarily a Northern Britge Columbia and that's a

400
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Speaker 1: thin horn sheep. That's a thin horn. And then the

401
00:23:04,359 --> 00:23:07,360
Speaker 1: white sheep is a doll. So the stone sheep range

402
00:23:07,640 --> 00:23:12,760
Speaker 1: in BC UM depends on the research you're looking at,

403
00:23:12,760 --> 00:23:14,920
Speaker 1: but there's some new DNA studies that are that are

404
00:23:16,080 --> 00:23:18,760
Speaker 1: pushing to the point that that's really the only place

405
00:23:18,800 --> 00:23:21,679
Speaker 1: they are uh, and that the stone sheep, and we

406
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Speaker 1: still call them that, but the stone sheep that are

407
00:23:23,600 --> 00:23:26,560
Speaker 1: in in the Yukon territory are actually fan in sheep

408
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Speaker 1: or just a a cross if you will, and dark

409
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Speaker 1: pelliage of a cross between a white sheep a doll

410
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Speaker 1: sheep and the stone sheep and the doll sheep are

411
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Speaker 1: in Alaska, Yukon and Northwestern or just the color phase

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Speaker 1: of the dolls. Yeah, which really irritates people because if

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Speaker 1: you you know, you think you got your four North

414
00:23:47,160 --> 00:23:49,560
Speaker 1: American wild cheep right, like that's a big thing. You

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Speaker 1: want to get your desert, your rocky mountain your stones

416
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Speaker 1: and your dolls. But you know they're starting to say

417
00:23:56,920 --> 00:24:00,000
Speaker 1: and explain this to me earlier. Now they're going, well,

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00:24:00,600 --> 00:24:03,560
Speaker 1: maybe that dolls is just that, or that stones what

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00:24:03,600 --> 00:24:05,440
Speaker 1: you think is the stones is actually just a color

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Speaker 1: phase of an actual doll. So would be like you

421
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Speaker 1: going around and saying, man, yeah, I've I've shot a

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Speaker 1: black bear and a grizzly bear, and then finding out

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Speaker 1: actually your black bear was or your what you think

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00:24:16,600 --> 00:24:19,560
Speaker 1: was your grizzly bear or just a brown phase black bear. Yeah,

425
00:24:19,560 --> 00:24:22,040
Speaker 1: I got you. But but like when you get up,

426
00:24:22,480 --> 00:24:25,240
Speaker 1: I want to confuse myself, don't. I want to stay

427
00:24:25,320 --> 00:24:29,800
Speaker 1: stay below the US Canada border for a minute. When

428
00:24:29,800 --> 00:24:33,200
Speaker 1: you hear of the California, the California is a rocky,

429
00:24:33,520 --> 00:24:35,520
Speaker 1: And then you hear in the old days that people

430
00:24:35,520 --> 00:24:39,560
Speaker 1: have said either the Audubon was a rocky in the

431
00:24:39,560 --> 00:24:42,760
Speaker 1: Missouri River bricks. We actually have an Audubon in our

432
00:24:43,200 --> 00:24:47,920
Speaker 1: conference room now extinct, although there's some debate on that

433
00:24:48,040 --> 00:24:50,960
Speaker 1: with with DNA, you know, the the DNA studies that

434
00:24:51,000 --> 00:24:52,639
Speaker 1: we can do now and the research, you know, the

435
00:24:53,160 --> 00:24:56,919
Speaker 1: samples we can use. Um, there's even some conflict of

436
00:24:56,920 --> 00:25:00,359
Speaker 1: what or not the Audubon was truly a set brit

437
00:25:00,320 --> 00:25:02,800
Speaker 1: substance that's I was reading about recently. But the bottom

438
00:25:02,800 --> 00:25:06,119
Speaker 1: line is we've we've repatriated big horn sheep into the

439
00:25:06,200 --> 00:25:09,600
Speaker 1: area that the Audubon was the Missouri River breaks, which

440
00:25:09,640 --> 00:25:14,040
Speaker 1: just kind of the classic beautiful, big, rocky mountain sheep

441
00:25:14,080 --> 00:25:18,320
Speaker 1: of of Montana. And then so now jump up into

442
00:25:18,359 --> 00:25:20,760
Speaker 1: Canada and going up into Alaska, like at the time

443
00:25:20,800 --> 00:25:23,720
Speaker 1: of European contact, would it just looked like one continuous

444
00:25:23,800 --> 00:25:26,560
Speaker 1: string of sheep that just happened to get whiter the

445
00:25:26,640 --> 00:25:30,199
Speaker 1: more farther north you went. Or were those populations like

446
00:25:30,240 --> 00:25:35,000
Speaker 1: broken up? No, they were broken up, And um, you

447
00:25:35,000 --> 00:25:37,320
Speaker 1: know there is there is certainly a difference between a

448
00:25:37,359 --> 00:25:40,600
Speaker 1: bighorn sheep and a thin horn sheep. Um, so that

449
00:25:40,760 --> 00:25:42,679
Speaker 1: the thin horn sheep and I don't know exactly what

450
00:25:42,800 --> 00:25:46,920
Speaker 1: latitude they're they're above, but um, you know those the

451
00:25:47,600 --> 00:25:51,320
Speaker 1: stones and the dolls definitely look different than than a

452
00:25:51,400 --> 00:25:53,680
Speaker 1: rocky mountain big horn, the rocky mountain bighorn or down

453
00:25:53,680 --> 00:25:58,280
Speaker 1: in southern b c um, you know, the the front

454
00:25:58,280 --> 00:26:02,000
Speaker 1: of the Rockies in Alberta, and then basically go down

455
00:26:02,040 --> 00:26:07,399
Speaker 1: through the Dakotas a little bit in Nebraska, um Clay

456
00:26:07,520 --> 00:26:10,680
Speaker 1: was just in Oklahoma. We now have a bighorn sheep

457
00:26:10,680 --> 00:26:14,439
Speaker 1: in Oklahoma, um and then desert in Texas. And then

458
00:26:14,480 --> 00:26:18,640
Speaker 1: you kind of as you go west, um and and

459
00:26:18,640 --> 00:26:20,680
Speaker 1: and further south, you get into the deserts. But there's

460
00:26:20,720 --> 00:26:24,560
Speaker 1: some some states that have both. Nevada has the Nelson Bighorn,

461
00:26:24,920 --> 00:26:28,760
Speaker 1: Rocky Mountain bighorn, and Colorado around I'm sorry California bighorn,

462
00:26:29,280 --> 00:26:32,240
Speaker 1: but we really treat those. We treat the California and

463
00:26:32,240 --> 00:26:34,680
Speaker 1: the Rocky is the same. If if you look at

464
00:26:34,680 --> 00:26:37,480
Speaker 1: the work and how it was done. You know, everybody

465
00:26:37,600 --> 00:26:40,840
Speaker 1: names something in the in the eighteen hundreds, they everybody

466
00:26:40,840 --> 00:26:43,399
Speaker 1: threw a label on it. And and then there was

467
00:26:43,440 --> 00:26:47,800
Speaker 1: a guy named Colwan about nineteen forty or so, uh

468
00:26:47,840 --> 00:26:52,440
Speaker 1: that that actually maybe the sixties, Uh, I can't remember exactly,

469
00:26:52,440 --> 00:26:54,560
Speaker 1: but anyway, he did a lot of the original work,

470
00:26:54,600 --> 00:26:58,240
Speaker 1: and they were measuring skulls and horns and and look

471
00:26:58,240 --> 00:27:01,960
Speaker 1: at it different ways. Well in the nineties, Uh, Rob

472
00:27:02,040 --> 00:27:05,080
Speaker 1: Ramy and John wey Housing uh did some of that

473
00:27:05,200 --> 00:27:08,440
Speaker 1: same work. And when it all came out, I mean,

474
00:27:08,720 --> 00:27:11,320
Speaker 1: I guess the short and I tend to think simple

475
00:27:11,359 --> 00:27:15,600
Speaker 1: and cheaper sheep. Uh, and and they described stones and

476
00:27:15,680 --> 00:27:18,560
Speaker 1: dolls to the north. So it's really to two species

477
00:27:19,520 --> 00:27:21,800
Speaker 1: rocky mountain or or big orange sheep to the south,

478
00:27:21,840 --> 00:27:24,240
Speaker 1: and and uh, thin horns to the north. And then

479
00:27:24,240 --> 00:27:28,520
Speaker 1: the subspecies they described three rocky mountains. They said California's

480
00:27:28,520 --> 00:27:31,280
Speaker 1: are the same. And there's lots of discussion, a lot

481
00:27:31,280 --> 00:27:32,760
Speaker 1: of states don't agree, and a lot of a lot

482
00:27:32,800 --> 00:27:35,119
Speaker 1: of folks go round and round over that. But then

483
00:27:35,160 --> 00:27:38,360
Speaker 1: they were Sierra Nevada and deserts and uh, but there

484
00:27:38,400 --> 00:27:43,560
Speaker 1: were they were measuring orbitals and taking various gold measurements

485
00:27:43,600 --> 00:27:46,600
Speaker 1: and uh, this will be ironed out very soon that

486
00:27:46,720 --> 00:27:50,360
Speaker 1: the genomics work that's occurring right now will answer every

487
00:27:50,359 --> 00:27:53,680
Speaker 1: one of these questions. Just so just stand by. It's coming. Yeah.

488
00:27:53,680 --> 00:27:56,160
Speaker 1: It's interesting to watch the way the genetics work has changed,

489
00:27:56,160 --> 00:27:58,240
Speaker 1: because when I was working on I was working in

490
00:27:58,280 --> 00:28:01,200
Speaker 1: my book American Buffalo, and you read, you know, back

491
00:28:01,240 --> 00:28:03,720
Speaker 1: a hundred years and people had there were seven different kinds,

492
00:28:03,760 --> 00:28:07,560
Speaker 1: you know, and it was mostly just different people not

493
00:28:07,720 --> 00:28:11,920
Speaker 1: orchestrating their activities. But we're seeing something somewhere and giving

494
00:28:11,920 --> 00:28:13,960
Speaker 1: it a name, and seeing something somewhere giving it a name,

495
00:28:14,800 --> 00:28:18,760
Speaker 1: and then always very eager to identify UH populations that

496
00:28:18,760 --> 00:28:20,879
Speaker 1: weren't there anymore and have it be that it was

497
00:28:20,920 --> 00:28:26,080
Speaker 1: something entirely different. In Texas, they had Texana, Uh, they

498
00:28:26,080 --> 00:28:28,680
Speaker 1: felt they had a different subspecies in Texas. It was

499
00:28:28,800 --> 00:28:33,240
Speaker 1: most likely Mexicana that subspecies, so it wasn't unique. But

500
00:28:33,520 --> 00:28:36,960
Speaker 1: you'll still hear people talk about that, are there any

501
00:28:37,000 --> 00:28:42,320
Speaker 1: places in uh? Are there any places in Canada where

502
00:28:43,400 --> 00:28:46,720
Speaker 1: a big horn and a thin horn sheep would run

503
00:28:46,720 --> 00:28:50,280
Speaker 1: into each other? You know, I've thought about that. In fact,

504
00:28:50,360 --> 00:28:53,440
Speaker 1: we were kicking around that that very thing earlier and

505
00:28:53,440 --> 00:28:58,840
Speaker 1: and it's uh, honestly no. But again, sheep or sheep, um?

506
00:28:58,880 --> 00:29:02,680
Speaker 1: You know, they they uh for for what we know,

507
00:29:02,800 --> 00:29:05,960
Speaker 1: the chances of them crossing paths probably slammed the none

508
00:29:06,280 --> 00:29:09,720
Speaker 1: just the habitat that they use and those sorts of things.

509
00:29:09,800 --> 00:29:14,000
Speaker 1: But they're like they're geographically separated by barriers that they're

510
00:29:14,000 --> 00:29:18,000
Speaker 1: not likely to cross. You guys have some cool graphics

511
00:29:18,000 --> 00:29:22,680
Speaker 1: in here that show what the where the popular the

512
00:29:22,720 --> 00:29:28,760
Speaker 1: population distribution now relative to when things were really dire

513
00:29:28,800 --> 00:29:33,400
Speaker 1: and bad, relative to when things were like relatively unexploited

514
00:29:33,880 --> 00:29:38,240
Speaker 1: to what year do you have to go back um

515
00:29:38,360 --> 00:29:40,160
Speaker 1: before you hit like what would have been kind of

516
00:29:40,200 --> 00:29:45,640
Speaker 1: like pre contact baseline, meaning no extrapated like no extrapated regional,

517
00:29:45,880 --> 00:29:49,440
Speaker 1: no regional extra pations. You know, that's that's a very

518
00:29:49,440 --> 00:29:56,920
Speaker 1: tough question. There was a seaton in the earnest seaton, yeah,

519
00:29:57,000 --> 00:29:59,800
Speaker 1: you know, or were the numbers one point five to

520
00:30:00,000 --> 00:30:05,719
Speaker 1: to millions something something so exactly, there's no doubt about it.

521
00:30:05,760 --> 00:30:08,760
Speaker 1: And and there are folks today that will they will

522
00:30:08,840 --> 00:30:10,880
Speaker 1: argue with those numbers are a lot more effective in

523
00:30:11,000 --> 00:30:13,520
Speaker 1: arguing those numbers than I am. At least the confidence

524
00:30:13,520 --> 00:30:16,880
Speaker 1: intervals really wide on well exactly exactly, and so you

525
00:30:16,880 --> 00:30:19,440
Speaker 1: know that that's a tough thing. But you know, if

526
00:30:19,480 --> 00:30:22,400
Speaker 1: you if you try to read you know, some of

527
00:30:22,400 --> 00:30:24,640
Speaker 1: the accounts Lewis and Clarks, and you know how much

528
00:30:24,640 --> 00:30:27,160
Speaker 1: did they you know, they talked about many many animals.

529
00:30:27,160 --> 00:30:30,360
Speaker 1: I don't know what that means. Uh, but if you

530
00:30:30,360 --> 00:30:32,760
Speaker 1: you know all the way, you you can trace some

531
00:30:32,800 --> 00:30:35,600
Speaker 1: of that. It's particularly desert big horns, uh, you know,

532
00:30:35,800 --> 00:30:39,560
Speaker 1: seventeen hundreds and things like that. When the kunky stators

533
00:30:39,600 --> 00:30:44,120
Speaker 1: were traveling, you know, the missions, the priests described what

534
00:30:44,160 --> 00:30:46,800
Speaker 1: they observed and it's so it's pretty interesting. But the

535
00:30:46,880 --> 00:30:50,080
Speaker 1: numbers are always tough. Um. You know, if you look

536
00:30:50,120 --> 00:30:53,720
Speaker 1: at in the fifties, what we do know is that

537
00:30:53,800 --> 00:30:57,160
Speaker 1: numbers have probably declined to about fifteen thousand, seventeen thousand

538
00:30:57,200 --> 00:31:00,440
Speaker 1: animals something like that, So they got pretty low. So

539
00:31:00,560 --> 00:31:04,080
Speaker 1: unless Seaton was wildly off, there was still a big reduction.

540
00:31:04,600 --> 00:31:07,680
Speaker 1: It was a far more than their work today. You know,

541
00:31:08,080 --> 00:31:10,680
Speaker 1: in terms of counting numbers. You guys familiar with how

542
00:31:10,800 --> 00:31:13,440
Speaker 1: for a long time the fashionable number for bison was

543
00:31:13,480 --> 00:31:16,320
Speaker 1: sixty million. And like you look into where that number

544
00:31:16,360 --> 00:31:19,520
Speaker 1: came from, Well, Seaton kind of like collated the whole thing,

545
00:31:19,560 --> 00:31:22,520
Speaker 1: but it came from basically a big herd going by.

546
00:31:22,600 --> 00:31:26,000
Speaker 1: It seemed to take days to go by. Later, Colonel

547
00:31:26,040 --> 00:31:30,240
Speaker 1: Dodge of Dodge City infamy has a conversation with another

548
00:31:30,280 --> 00:31:33,120
Speaker 1: guy who saw the same thing, and hell, he must

549
00:31:33,160 --> 00:31:38,000
Speaker 1: have been three miles away. And through this right comes

550
00:31:38,040 --> 00:31:41,040
Speaker 1: this like wild estimation of how many there must be.

551
00:31:41,880 --> 00:31:43,880
Speaker 1: So it is frustrating reading this book right now. Grizzlies

552
00:31:43,920 --> 00:31:46,920
Speaker 1: in the Southwest, and the first part of the book

553
00:31:47,400 --> 00:31:53,440
Speaker 1: is trying to collate all the cases or someone identified one,

554
00:31:54,000 --> 00:31:58,680
Speaker 1: but you get into just terminology yep, and being like,

555
00:31:58,880 --> 00:32:01,600
Speaker 1: is this what is this guy talking about like, what

556
00:32:01,800 --> 00:32:08,200
Speaker 1: is you know, whoever's keeping records during the Coronado expedition.

557
00:32:08,960 --> 00:32:11,800
Speaker 1: What is he talking about when he says X, is

558
00:32:11,840 --> 00:32:14,000
Speaker 1: that what he means? And I don't know. I'll say

559
00:32:14,000 --> 00:32:16,560
Speaker 1: to your story of the only Grizzly barri kill in Texas,

560
00:32:17,560 --> 00:32:24,680
Speaker 1: I just read about that, yeah, in the Smithsonian, you know,

561
00:32:25,120 --> 00:32:27,560
Speaker 1: so I can see that like exceedingly difficult to get

562
00:32:27,560 --> 00:32:31,280
Speaker 1: a sense of what was where, but you could picture that.

563
00:32:32,280 --> 00:32:34,480
Speaker 1: I mean, like it's fair to say, like like you

564
00:32:34,520 --> 00:32:39,480
Speaker 1: take like Nevada, you take Montana was like more of

565
00:32:39,520 --> 00:32:42,520
Speaker 1: it was sheep country than not. Oh yeah, if you

566
00:32:42,560 --> 00:32:45,040
Speaker 1: look at if you look at the mountains of Nevada

567
00:32:45,040 --> 00:32:47,840
Speaker 1: and look how's laid out, and compare that to say Texas.

568
00:32:48,440 --> 00:32:50,520
Speaker 1: You know, you can see just only the far west

569
00:32:50,560 --> 00:32:52,840
Speaker 1: part of Texas. And if you look at at where

570
00:32:52,880 --> 00:32:55,360
Speaker 1: Scott works, Uh, you know, just just some of the

571
00:32:55,920 --> 00:32:59,440
Speaker 1: heritage the Native Americans have passed down the stories and

572
00:32:59,520 --> 00:33:02,440
Speaker 1: picture as. We have a pretty good, good good idea

573
00:33:02,520 --> 00:33:06,800
Speaker 1: where they occurred. Uh again that's interested just representational art. Uh,

574
00:33:06,840 --> 00:33:09,320
Speaker 1: Like these people are drawing them so familiar with them.

575
00:33:09,360 --> 00:33:12,760
Speaker 1: Same story of Texas. I can show you pictographs of

576
00:33:12,880 --> 00:33:16,240
Speaker 1: big horn sheep in Texas that, uh, but but numbers

577
00:33:16,240 --> 00:33:19,800
Speaker 1: we you know, it's it's it's an educated guest, that's

578
00:33:19,800 --> 00:33:22,320
Speaker 1: for sure. I think it's a fair assumption to say

579
00:33:22,360 --> 00:33:24,160
Speaker 1: that we had a lot of sheep and they were

580
00:33:24,280 --> 00:33:27,560
Speaker 1: their distribution what's why they're they're the use of them

581
00:33:27,600 --> 00:33:31,320
Speaker 1: culturally and and for materials and food was widespread. People

582
00:33:31,320 --> 00:33:34,440
Speaker 1: were the first explorers were encountering big encountering big horn

583
00:33:34,600 --> 00:33:37,600
Speaker 1: bows out waiting to Nebraska and out into the plains,

584
00:33:37,680 --> 00:33:40,680
Speaker 1: the plains Indians were using bows man a big horn

585
00:33:40,760 --> 00:33:43,400
Speaker 1: sheep horns, Now, wasn't it most common though, like right

586
00:33:44,280 --> 00:33:47,840
Speaker 1: out of the park because they they were coming basically

587
00:33:47,840 --> 00:33:51,200
Speaker 1: being traded for and you know, the the pictograph record

588
00:33:51,320 --> 00:33:53,920
Speaker 1: is very widespread. So I think it's it's fair assumption

589
00:33:53,920 --> 00:33:55,160
Speaker 1: to say we had a lot of sheep. They were

590
00:33:55,160 --> 00:33:57,400
Speaker 1: widely distributed, Um a lot. There was a lot of

591
00:33:57,440 --> 00:34:01,480
Speaker 1: cultures that were built around sheet um. And obviously I

592
00:34:01,480 --> 00:34:04,680
Speaker 1: think you've probably read Journal of Trapper. I mean some

593
00:34:04,760 --> 00:34:07,440
Speaker 1: of his descriptions. This is a guy that's seen Yellowstone

594
00:34:07,480 --> 00:34:10,600
Speaker 1: Park area and it's sort of in prime form and

595
00:34:10,920 --> 00:34:14,279
Speaker 1: using descriptions of immense numbers of mountain sheep in the

596
00:34:14,280 --> 00:34:16,120
Speaker 1: winter time. So like I think someone that uses the

597
00:34:16,160 --> 00:34:19,279
Speaker 1: word immense numbers, you know, this isn't a herd of

598
00:34:19,840 --> 00:34:21,680
Speaker 1: or fifteen sheep on the side of a hill. It's

599
00:34:21,920 --> 00:34:23,840
Speaker 1: the winter range was new rout. There was a lot

600
00:34:23,880 --> 00:34:26,920
Speaker 1: of sheep there. Have you read Francis Parkman's Oregon Trail?

601
00:34:27,200 --> 00:34:30,799
Speaker 1: I have not. So he he was a historian and

602
00:34:30,920 --> 00:34:34,319
Speaker 1: he wrote like at the time, the definitive history of

603
00:34:34,320 --> 00:34:36,640
Speaker 1: the French and Indian War. But he had health problems.

604
00:34:36,719 --> 00:34:39,879
Speaker 1: It was told to come out and spend time out

605
00:34:39,920 --> 00:34:41,759
Speaker 1: in the west, and he comes out and travels on

606
00:34:41,800 --> 00:34:45,279
Speaker 1: the Oregon Trail. I think this is eighty six. He

607
00:34:45,360 --> 00:34:49,440
Speaker 1: actually winds up traveling with the Oglala Sioux probably was

608
00:34:49,480 --> 00:34:52,200
Speaker 1: in the same camp with Crazy Horse when Crazy Horse

609
00:34:52,280 --> 00:34:55,680
Speaker 1: was thirteen. They go up into the Black Hills to

610
00:34:56,160 --> 00:35:00,320
Speaker 1: get lodgepole pine for tent lodgepoles. The guys he's album

611
00:35:00,360 --> 00:35:02,920
Speaker 1: with get onto a big herd of big horns and

612
00:35:03,040 --> 00:35:06,719
Speaker 1: kill a bunch by throwing rocks down at them. So

613
00:35:06,760 --> 00:35:09,800
Speaker 1: you get like, that's not too that's like a side.

614
00:35:09,840 --> 00:35:13,040
Speaker 1: There must be like sizeable groups if that's your hunting strategies.

615
00:35:13,080 --> 00:35:17,040
Speaker 1: The hurl rocks down and successfully kill a bunch those

616
00:35:17,120 --> 00:35:19,560
Speaker 1: those kind of accounts that I think we're piecing all

617
00:35:19,600 --> 00:35:23,600
Speaker 1: that that information to gather cultural accounts, early explorer accounts,

618
00:35:23,640 --> 00:35:26,000
Speaker 1: we know what their range is in modern day we

619
00:35:26,040 --> 00:35:28,120
Speaker 1: know how many sheep of the habitat can support, so

620
00:35:28,200 --> 00:35:30,480
Speaker 1: we can kind of piece it together, you know, like

621
00:35:30,600 --> 00:35:32,480
Speaker 1: what the numbers look like. So if you if you

622
00:35:32,520 --> 00:35:34,520
Speaker 1: had to express like how bad it got, what's the

623
00:35:34,520 --> 00:35:36,600
Speaker 1: best way to express how bad it? God? Because you

624
00:35:36,600 --> 00:35:38,840
Speaker 1: could is it because you don't know the beginning numbers,

625
00:35:38,840 --> 00:35:41,120
Speaker 1: So it's hard to do it numerically, Like how do

626
00:35:41,120 --> 00:35:43,440
Speaker 1: you guys think about it? When you think about restoration?

627
00:35:44,280 --> 00:35:49,120
Speaker 1: Is it filling in the map or is it achieving numbers? Yeah,

628
00:35:49,160 --> 00:35:50,759
Speaker 1: it's a little bit of both. If you know, you

629
00:35:50,800 --> 00:35:52,799
Speaker 1: look in your you're referencing to this map that we've

630
00:35:52,800 --> 00:35:55,360
Speaker 1: got in our in our conference room, and you know,

631
00:35:55,480 --> 00:35:57,920
Speaker 1: let's say, if we're using Seaton's numbers of you know,

632
00:35:57,960 --> 00:36:00,000
Speaker 1: one to two million sheep, let's use a lower numb

633
00:36:00,040 --> 00:36:03,760
Speaker 1: umber of one million um. You know, throughout North America

634
00:36:03,840 --> 00:36:06,360
Speaker 1: we reduce those in the nineteen sixties down to twenty

635
00:36:06,360 --> 00:36:12,640
Speaker 1: five thousand. So in what's now the US all the

636
00:36:12,680 --> 00:36:17,240
Speaker 1: North North America, US, Canada, Mexico, bign Okay, so not

637
00:36:17,239 --> 00:36:19,520
Speaker 1: not not because not the thin horns, the thin horn

638
00:36:19,680 --> 00:36:22,960
Speaker 1: range is actually still distributions still pretty much the same

639
00:36:23,160 --> 00:36:26,120
Speaker 1: because they haven't come up against like the obstacles. They haven't.

640
00:36:26,320 --> 00:36:28,440
Speaker 1: Uh and that's and that's that's what you're trying to prevent.

641
00:36:28,560 --> 00:36:30,680
Speaker 1: But but the big horns did. So you know, you're

642
00:36:30,680 --> 00:36:33,360
Speaker 1: looking at you know, if it's five hundred or one million,

643
00:36:33,440 --> 00:36:35,920
Speaker 1: or one point five or two million dollars, we are

644
00:36:35,960 --> 00:36:39,880
Speaker 1: two million sheep. We reduced those numbers down to twenty

645
00:36:39,880 --> 00:36:42,920
Speaker 1: five thousand by the late nineteen sixties. Today we're at

646
00:36:42,920 --> 00:36:45,880
Speaker 1: about eighty five thousand big horn sheep in in Canada,

647
00:36:46,440 --> 00:36:56,799
Speaker 1: US and Mexico, in all of North America. And at

648
00:36:56,800 --> 00:36:59,040
Speaker 1: the I want to talk about why it got that way,

649
00:36:59,120 --> 00:37:01,480
Speaker 1: But at the low a point with sheep, were you

650
00:37:01,680 --> 00:37:04,480
Speaker 1: then finding that you had states I know we talked

651
00:37:04,480 --> 00:37:08,319
Speaker 1: about Texas. Were there multiple states that had completely run out?

652
00:37:08,680 --> 00:37:11,160
Speaker 1: You bet, you bet. You know if you look at

653
00:37:11,239 --> 00:37:13,040
Speaker 1: you know, some of the data that will show you know,

654
00:37:13,080 --> 00:37:18,240
Speaker 1: we'll we'll reference remnant population. Some were just gone. Texas gone.

655
00:37:19,239 --> 00:37:22,480
Speaker 1: Um Nevada was down to a remnant population. They're they're

656
00:37:22,520 --> 00:37:25,560
Speaker 1: an absolute incredible success store. You know they had they

657
00:37:25,560 --> 00:37:27,359
Speaker 1: had a hundred or two hundred. You know, what does

658
00:37:27,400 --> 00:37:30,400
Speaker 1: remnant mean? Two hundred sheep. They're up to eleven thousand

659
00:37:30,480 --> 00:37:32,600
Speaker 1: desert big ones right now. They probably got about twelve

660
00:37:32,600 --> 00:37:35,080
Speaker 1: thousand to thirteen thousand big one cheap in Nevada today,

661
00:37:35,080 --> 00:37:37,160
Speaker 1: and they were down to what's called a remnant remnant

662
00:37:37,480 --> 00:37:41,640
Speaker 1: one in venties, which would be sub one. So it's

663
00:37:41,680 --> 00:37:45,360
Speaker 1: pretty amazing. Um, what states are like the big holdouts

664
00:37:46,120 --> 00:37:51,120
Speaker 1: wym means strong states. Troma did pretty well. Um, I

665
00:37:51,160 --> 00:37:55,680
Speaker 1: think Montana did pretty well. Hanging all around them pretty well.

666
00:37:55,719 --> 00:38:00,760
Speaker 1: But still who was who was housing? Uh? What states

667
00:38:00,840 --> 00:38:07,080
Speaker 1: provided the last refugia for the deserts desert big horns? Like?

668
00:38:07,120 --> 00:38:09,480
Speaker 1: What states? What had like wound up one of all

669
00:38:09,560 --> 00:38:14,239
Speaker 1: the smoke clear clay Arizona, New Mexico didn't. No, New

670
00:38:14,280 --> 00:38:16,799
Speaker 1: Mexico was down. So they were way down pretty much

671
00:38:16,880 --> 00:38:21,319
Speaker 1: pretty much Mexico and in Arizona, California. You know they

672
00:38:22,200 --> 00:38:26,000
Speaker 1: I don't remember, hello the numbers got in California. Uh,

673
00:38:26,200 --> 00:38:28,239
Speaker 1: Nevada's got I mean most of them are remnant. It

674
00:38:28,600 --> 00:38:32,440
Speaker 1: was rough and Mexico held onto some actually co did

675
00:38:32,719 --> 00:38:36,520
Speaker 1: um in the Sierra Madre where you know most of

676
00:38:36,520 --> 00:38:44,080
Speaker 1: it was just well in the Bajaah so yeah, because

677
00:38:44,080 --> 00:38:48,600
Speaker 1: Baja Man. Like as far as like representational art, yeah,

678
00:38:49,239 --> 00:38:52,200
Speaker 1: tah North. I've been spent time down there. Man. There's

679
00:38:52,200 --> 00:38:55,560
Speaker 1: tons of picto grass, big big horns in held here,

680
00:38:55,600 --> 00:38:58,200
Speaker 1: you know, and they've and they've held their own even today.

681
00:38:58,320 --> 00:39:01,319
Speaker 1: I mean they've they do pretty well. Um. I mean

682
00:39:01,320 --> 00:39:04,040
Speaker 1: there are a lot of sheep uh in Sonora alone.

683
00:39:04,080 --> 00:39:07,680
Speaker 1: I can't remember the numbers exactly, but there are probably

684
00:39:07,719 --> 00:39:13,360
Speaker 1: in so Norma, Mexico alone, probably just in that state.

685
00:39:13,400 --> 00:39:16,640
Speaker 1: And then we hunt down I never run into one.

686
00:39:16,840 --> 00:39:20,600
Speaker 1: Must be the wrong part of the Um. What was

687
00:39:20,640 --> 00:39:23,640
Speaker 1: the dry like I kind of already know this answer

688
00:39:24,400 --> 00:39:27,240
Speaker 1: because I know it was like disease and pot hunting,

689
00:39:27,960 --> 00:39:33,920
Speaker 1: like what made it so bad? Like how did it

690
00:39:33,960 --> 00:39:37,400
Speaker 1: get so bad? Well, there were there were lots of things,

691
00:39:38,280 --> 00:39:43,560
Speaker 1: the combination of things, um, civilization, railroads were moving in

692
00:39:43,640 --> 00:39:47,439
Speaker 1: the blanket term uh and all the wonders that it brings. Yeah,

693
00:39:47,480 --> 00:39:49,719
Speaker 1: and and Scott can speak to this stuff a little

694
00:39:49,719 --> 00:39:52,600
Speaker 1: bit further north. And but as far as the stuff

695
00:39:52,640 --> 00:39:55,800
Speaker 1: in in the south, you know, if you read Texas history,

696
00:39:56,120 --> 00:39:59,440
Speaker 1: the railroad came through, and you'd read a counch where

697
00:39:59,640 --> 00:40:03,440
Speaker 1: you know they were feeding railroad workers. Uh. And a

698
00:40:03,480 --> 00:40:05,719
Speaker 1: guy would hunt meat for the railroads and he would

699
00:40:05,800 --> 00:40:09,560
Speaker 1: hit the hit hit where our prime habitat is and

700
00:40:09,560 --> 00:40:11,960
Speaker 1: he would say that had him in a box canyon

701
00:40:11,960 --> 00:40:14,440
Speaker 1: and I got every one of them. And and so

702
00:40:14,600 --> 00:40:17,440
Speaker 1: he would take the meat back feed railroad workers. But

703
00:40:18,200 --> 00:40:21,600
Speaker 1: it was disease issues and a competition for forage and

704
00:40:22,400 --> 00:40:25,799
Speaker 1: limited water and forage with with domestic livestock that it

705
00:40:25,880 --> 00:40:28,239
Speaker 1: that had come in later, and and people were trying

706
00:40:28,239 --> 00:40:31,239
Speaker 1: to feed their families. It was tough places to to

707
00:40:31,320 --> 00:40:33,799
Speaker 1: make a living. So if you if you break out,

708
00:40:34,920 --> 00:40:39,160
Speaker 1: let's see you break out market hunting. Um. And who's

709
00:40:39,200 --> 00:40:42,720
Speaker 1: that famous photographer that used to work out a mile city,

710
00:40:42,880 --> 00:40:46,800
Speaker 1: Uh Hoffman l A. Hoffman. He was taking pictures in

711
00:40:46,840 --> 00:40:50,560
Speaker 1: the early eighteen eighties of market hunter camps where they

712
00:40:50,560 --> 00:40:52,400
Speaker 1: had this all kinds of big horns lined up to

713
00:40:52,400 --> 00:40:55,640
Speaker 1: their killing along the Yellowstone. But if you're gonna take out,

714
00:40:55,800 --> 00:40:57,600
Speaker 1: if you're gonna divide it, like, let's say you had

715
00:40:57,680 --> 00:41:01,000
Speaker 1: habitat issues, Okay, so crazy comp this and water whatever,

716
00:41:02,040 --> 00:41:07,239
Speaker 1: market hunting and disease are are they teared out or

717
00:41:07,320 --> 00:41:11,840
Speaker 1: they all just equal players? Oh no, it's if typically,

718
00:41:11,920 --> 00:41:15,280
Speaker 1: if you if you're trying to piece the story together

719
00:41:15,360 --> 00:41:20,040
Speaker 1: that's got described, you typically look at land use history

720
00:41:20,040 --> 00:41:22,759
Speaker 1: and you look at look at how things occurred or

721
00:41:22,800 --> 00:41:27,279
Speaker 1: what might have occurred. And today the greatest obstacle that

722
00:41:27,320 --> 00:41:31,000
Speaker 1: we face is disease. And so chances are that was

723
00:41:31,040 --> 00:41:34,840
Speaker 1: the greatest threat, the thing that caused the most problems

724
00:41:35,440 --> 00:41:39,680
Speaker 1: in the in the eighteen hundreds, uh, along with those

725
00:41:39,719 --> 00:41:42,359
Speaker 1: other things. But but in in my view, it would

726
00:41:42,400 --> 00:41:47,360
Speaker 1: be diseases uh and competition for forage UM and limited

727
00:41:47,400 --> 00:41:52,239
Speaker 1: water in the desert environment. Anyway, Yeah, that's totally very UM.

728
00:41:52,920 --> 00:41:54,719
Speaker 1: Just to give you a perspective, like if you think

729
00:41:54,760 --> 00:41:58,319
Speaker 1: about it, and in terms of grazing and UM, just

730
00:41:58,400 --> 00:42:01,800
Speaker 1: use the northeast organ exam ample that that corner of

731
00:42:02,080 --> 00:42:06,040
Speaker 1: Oregon Williwa County where Health Canyon is located, there was

732
00:42:06,160 --> 00:42:08,560
Speaker 1: about the turn of century there was three hundred thousand

733
00:42:08,600 --> 00:42:14,160
Speaker 1: sheep grazing in that county. Yes, yep, so there was

734
00:42:14,200 --> 00:42:18,360
Speaker 1: an immense number of sheep domestic sheep and sorry, the

735
00:42:18,520 --> 00:42:22,120
Speaker 1: three hundred domestics grazing in Williwa County. So that was

736
00:42:22,160 --> 00:42:26,920
Speaker 1: a county alone dostic sheep. So we're you know, obviously

737
00:42:27,040 --> 00:42:29,400
Speaker 1: it was great grazing land for domestic sheep, and so

738
00:42:29,600 --> 00:42:33,080
Speaker 1: people were grazing. There was no tailor grazing act. It

739
00:42:33,160 --> 00:42:34,960
Speaker 1: was sort of a free for all in the public

740
00:42:35,040 --> 00:42:38,600
Speaker 1: land system, which is you know, probably not fully established

741
00:42:38,640 --> 00:42:42,200
Speaker 1: at that time. Um. And we had a lot of

742
00:42:42,320 --> 00:42:44,400
Speaker 1: a lot of domestics right in the Big Horn habitat.

743
00:42:44,480 --> 00:42:47,840
Speaker 1: So we should probably talk about the diza like disease.

744
00:42:47,840 --> 00:42:50,799
Speaker 1: When we say disease carried them off. Is it a

745
00:42:50,800 --> 00:42:53,360
Speaker 1: host of diseases that hits Big Horns or is it

746
00:42:53,440 --> 00:42:56,279
Speaker 1: a disease it hits big Horns. It is a disease complex.

747
00:42:56,440 --> 00:42:59,960
Speaker 1: So there's clay can fill in the gaps, But there's

748
00:43:00,400 --> 00:43:03,640
Speaker 1: based on our last decade of research. I mean, it's

749
00:43:03,640 --> 00:43:07,000
Speaker 1: been an evolving story over time where people are constantly

750
00:43:07,120 --> 00:43:09,400
Speaker 1: learning new information all the time. Is our techniques and

751
00:43:09,480 --> 00:43:13,040
Speaker 1: science get better and and our experimentation gets better and

752
00:43:13,080 --> 00:43:17,120
Speaker 1: our insights get a bit get better. Um. But what

753
00:43:17,400 --> 00:43:20,360
Speaker 1: all the research points to now is it's one particular

754
00:43:20,400 --> 00:43:25,000
Speaker 1: bacteria that these are are. North American sheep did not

755
00:43:25,200 --> 00:43:29,120
Speaker 1: evolve with so they're hosted by the domestic species. When

756
00:43:29,120 --> 00:43:31,480
Speaker 1: they come in contact with each other, the big horn

757
00:43:31,600 --> 00:43:35,600
Speaker 1: sheep contract that bacteria. They're no longer able to fight

758
00:43:35,680 --> 00:43:40,640
Speaker 1: off other infections, so it compromises their sillia in their

759
00:43:40,680 --> 00:43:44,040
Speaker 1: in their trachea, so they aren't able to move all

760
00:43:44,080 --> 00:43:47,160
Speaker 1: their bacteria out and they succumb to basically pneumonia but

761
00:43:47,320 --> 00:43:49,400
Speaker 1: from other whether it's a back you know, but my

762
00:43:49,560 --> 00:43:54,640
Speaker 1: probably microbial disease, it's the term. So they're very naive

763
00:43:54,680 --> 00:43:58,880
Speaker 1: to this disease. The the mo it's called microplazma ovi pneumonia,

764
00:43:59,080 --> 00:44:03,640
Speaker 1: so we call mo BE for short and m O

765
00:44:03,719 --> 00:44:09,000
Speaker 1: V period ov um and and this this is a

766
00:44:09,120 --> 00:44:13,919
Speaker 1: disease that seems to have originated in a real sheep

767
00:44:13,960 --> 00:44:18,480
Speaker 1: in Europe. They perhaps were exposed to it for the

768
00:44:19,920 --> 00:44:24,000
Speaker 1: correct so they carry it. They're they're not clinically affected

769
00:44:24,000 --> 00:44:26,200
Speaker 1: by we don't see the same symptoms that we do

770
00:44:26,239 --> 00:44:28,720
Speaker 1: in big horns or their coffee and or having nasal

771
00:44:29,000 --> 00:44:33,359
Speaker 1: sinus discharge um. So it doesn't appear to have a

772
00:44:33,400 --> 00:44:36,840
Speaker 1: strong population level effect or no population level effect and

773
00:44:36,880 --> 00:44:39,880
Speaker 1: domestic sheep, so some lambs will succumb to it, you know,

774
00:44:39,920 --> 00:44:42,360
Speaker 1: and you know, once they're kind of getting close to weaning,

775
00:44:42,880 --> 00:44:45,960
Speaker 1: but our bighorn sheep lambs will be infected early on,

776
00:44:46,239 --> 00:44:49,279
Speaker 1: and it's it's very fatal. And the strains there's there's

777
00:44:49,320 --> 00:44:52,560
Speaker 1: many strains, they're all they have different severity and the

778
00:44:52,600 --> 00:44:56,480
Speaker 1: reactions within big horn population. So it's it's a complicated

779
00:44:56,520 --> 00:44:58,799
Speaker 1: disease issue. And that's why it's taken us so long

780
00:44:58,920 --> 00:45:02,600
Speaker 1: to sort this all lout. So was was this disease

781
00:45:02,719 --> 00:45:08,640
Speaker 1: hitting big horns before anybody knew that this disease? Yeah,

782
00:45:09,760 --> 00:45:11,279
Speaker 1: it's just as like, I don't know what happened to

783
00:45:11,320 --> 00:45:14,960
Speaker 1: them all. I mean, if you think about the habitat

784
00:45:15,000 --> 00:45:18,040
Speaker 1: that these animals live in, how frequently do we how

785
00:45:18,080 --> 00:45:20,200
Speaker 1: how well studied our hearts now with our with our

786
00:45:20,320 --> 00:45:22,799
Speaker 1: level of technology and their dedication, But back in the

787
00:45:22,840 --> 00:45:25,239
Speaker 1: eight hundreds, I know that I don't know how many

788
00:45:25,239 --> 00:45:30,400
Speaker 1: people were looking at him you look, um, Yeah, you

789
00:45:30,440 --> 00:45:33,719
Speaker 1: know a great analogy would be looking at what we

790
00:45:33,760 --> 00:45:37,120
Speaker 1: did to Native American tribes with smallpox. It's you know,

791
00:45:37,120 --> 00:45:40,839
Speaker 1: it's so similar. Um. And when we talk about micro

792
00:45:40,920 --> 00:45:44,279
Speaker 1: plasma oa pneumonia as a setup agent, um, you know,

793
00:45:44,360 --> 00:45:47,719
Speaker 1: kind of in in in lay terms, even though they're

794
00:45:47,719 --> 00:45:49,960
Speaker 1: not the same. You know, it's it's kind of HIV

795
00:45:50,160 --> 00:45:54,120
Speaker 1: and sheep uh. You know, HIV is an immune deficiency.

796
00:45:54,200 --> 00:45:56,399
Speaker 1: This is not This is a bacterium. It's a path

797
00:45:56,520 --> 00:46:00,480
Speaker 1: a pathogen, but it's a setup agent. So um. You

798
00:46:00,520 --> 00:46:03,239
Speaker 1: know you Joe was thirty two years old and you

799
00:46:03,320 --> 00:46:05,279
Speaker 1: heard he died of pneumonia, and you go, my god,

800
00:46:05,320 --> 00:46:06,960
Speaker 1: you know, Joe is thirty two years old. I was

801
00:46:07,000 --> 00:46:09,440
Speaker 1: a thirty two year old guy died of pneumonia. Oh well,

802
00:46:09,480 --> 00:46:13,000
Speaker 1: you know he had AIDS, HIV and compromises immune system

803
00:46:13,040 --> 00:46:15,840
Speaker 1: and he got pneumonia died very similar to what's happening

804
00:46:15,840 --> 00:46:18,840
Speaker 1: with sheep is. As Scott had pointed out that the

805
00:46:18,960 --> 00:46:24,000
Speaker 1: microplasmo pneumonia iMovie lays down the cilia in the esophagus

806
00:46:24,520 --> 00:46:27,959
Speaker 1: uh and allows other other bugs, other pathogens, other other

807
00:46:28,200 --> 00:46:31,000
Speaker 1: other bacteria to get down into the lungs. They can't

808
00:46:31,080 --> 00:46:33,479
Speaker 1: cough it out, the silly is not moving it out.

809
00:46:33,960 --> 00:46:35,640
Speaker 1: They get sick and then we you know what we

810
00:46:35,719 --> 00:46:38,760
Speaker 1: used to say, as well, they died of pneumonia. Well,

811
00:46:38,840 --> 00:46:42,880
Speaker 1: actually they probably died of something else. But imovis. As

812
00:46:42,960 --> 00:46:45,200
Speaker 1: we're able to study it more and more and more,

813
00:46:45,760 --> 00:46:48,120
Speaker 1: m O VI was present there's there's a litany of

814
00:46:48,160 --> 00:46:52,840
Speaker 1: other pathogens uh Mannheimia, hemolytica. There's there's new research that

815
00:46:53,719 --> 00:46:58,200
Speaker 1: is looking at um nasal tumors. Is. So it's you know,

816
00:46:58,280 --> 00:47:02,040
Speaker 1: these these sheep, which a mountain sheep. When you look

817
00:47:02,040 --> 00:47:05,239
Speaker 1: at where they live, uh in some of the harshest

818
00:47:05,320 --> 00:47:08,760
Speaker 1: climates in North America. Uh some of the most unique

819
00:47:08,760 --> 00:47:12,560
Speaker 1: climates in North America. The sad thing is is from

820
00:47:12,560 --> 00:47:16,759
Speaker 1: a from a respiratory standpoint, they're pretty darn weak. Um.

821
00:47:17,239 --> 00:47:20,200
Speaker 1: Our Vice president of Conservation Kevin Hurley says that I

822
00:47:20,200 --> 00:47:22,919
Speaker 1: think pretty pretty succinctly says, the damned things are born

823
00:47:23,000 --> 00:47:26,520
Speaker 1: looking for a place to die. UM. So there, you know,

824
00:47:26,560 --> 00:47:30,279
Speaker 1: it's it's a it's it's challenging. UM. It is a

825
00:47:30,320 --> 00:47:33,400
Speaker 1: disease complex. And and every time we we you know,

826
00:47:33,560 --> 00:47:37,279
Speaker 1: Wild Chief Foundations spent millions and millions of dollars into

827
00:47:37,360 --> 00:47:41,120
Speaker 1: disease research. We endow a share of wild cheap disease

828
00:47:41,160 --> 00:47:46,360
Speaker 1: at Washington to Date University. UM. Every rock we overturned

829
00:47:46,440 --> 00:47:49,520
Speaker 1: that we think we've got the solution, we this is

830
00:47:49,600 --> 00:47:52,399
Speaker 1: this is it, this is now. Now there's four other

831
00:47:52,480 --> 00:47:56,319
Speaker 1: rocks underneath it that we un you know, unturned or

832
00:47:56,320 --> 00:47:59,000
Speaker 1: overturned those and there's four more other questions that we

833
00:47:59,040 --> 00:48:01,160
Speaker 1: don't know the answer to. So I want to explore

834
00:48:01,160 --> 00:48:04,360
Speaker 1: the timeline a little bit on on the numbers collapsing.

835
00:48:05,520 --> 00:48:07,640
Speaker 1: But no one really knew where we started. No one

836
00:48:07,640 --> 00:48:11,120
Speaker 1: had done like this exhaustive analysis of where sheep exists

837
00:48:11,120 --> 00:48:13,760
Speaker 1: and how many there were. But it's just like any

838
00:48:13,760 --> 00:48:16,440
Speaker 1: anyone who's paying attention can't miss the fact that they're vanishing.

839
00:48:18,160 --> 00:48:22,719
Speaker 1: At what point do people like this organization or other

840
00:48:22,719 --> 00:48:26,320
Speaker 1: individuals or state agencies, at what point do people go like, wow,

841
00:48:26,440 --> 00:48:28,319
Speaker 1: we need to get on top of this and start

842
00:48:28,360 --> 00:48:32,600
Speaker 1: taking some step And at that time did they were

843
00:48:32,640 --> 00:48:35,520
Speaker 1: they then aware of what was causing the problem? Were

844
00:48:35,520 --> 00:48:40,000
Speaker 1: people doing restoration? And then all the sheep die again

845
00:48:40,600 --> 00:48:43,640
Speaker 1: without even knowing that the real issue was disease, thinking

846
00:48:43,719 --> 00:48:45,680
Speaker 1: it might have been something else. Is that like that

847
00:48:45,760 --> 00:48:50,240
Speaker 1: question makes sense? It absolute good question. Clay and Scott

848
00:48:50,320 --> 00:48:53,040
Speaker 1: can remember, you know, we were we were probably putting

849
00:48:53,160 --> 00:48:57,680
Speaker 1: six sheep into clean sheep, so we were we were

850
00:48:57,719 --> 00:49:00,400
Speaker 1: making some errors back because we just we just didn't

851
00:49:00,400 --> 00:49:03,760
Speaker 1: know we were you know, we didn't know that that

852
00:49:03,760 --> 00:49:07,879
Speaker 1: that sourcerd had mica plasma o pneumonia. Uh, and so

853
00:49:07,920 --> 00:49:11,560
Speaker 1: we plopped in no doubt in transplants, we prop plopped

854
00:49:11,560 --> 00:49:14,040
Speaker 1: in six sheep on top of clean sheet. So that

855
00:49:14,120 --> 00:49:18,280
Speaker 1: became the that became the primary restoration tools. Transplanting sheep

856
00:49:18,680 --> 00:49:24,040
Speaker 1: absolutely absolutely the early years was protection. Every state nineteen

857
00:49:24,040 --> 00:49:29,799
Speaker 1: o five, nineteen ten, nineteen o three, every state implemented something. Uh.

858
00:49:29,960 --> 00:49:35,720
Speaker 1: The first translocation occurred in nineteen twenty two. Uh. Since

859
00:49:35,800 --> 00:49:40,800
Speaker 1: then there have been probably close to fifteen hundred separate

860
00:49:40,880 --> 00:49:46,120
Speaker 1: operations removing somewhere in the neighborhood of twenty two thousand

861
00:49:46,200 --> 00:49:51,480
Speaker 1: animals that have been moved from one place to another.

862
00:49:51,840 --> 00:49:55,560
Speaker 1: In nineteen o three in Texas, they're like, it's bad enough,

863
00:49:55,680 --> 00:49:59,440
Speaker 1: you can't kill one. And it wasn't just cheap. Keep

864
00:49:59,480 --> 00:50:02,560
Speaker 1: that in mind. It was muled here and pronghorn and

865
00:50:02,560 --> 00:50:04,920
Speaker 1: in all wild life in those days. I mean everything

866
00:50:04,960 --> 00:50:08,799
Speaker 1: was suffering. But uh, but it was, there's no doubt

867
00:50:08,840 --> 00:50:15,040
Speaker 1: about it. The tool translocations was that was the tool. Uh.

868
00:50:15,120 --> 00:50:17,960
Speaker 1: You know, we would go we worked with Nevada Department

869
00:50:17,960 --> 00:50:21,120
Speaker 1: of Wildlife and we would we would trap sheep on

870
00:50:21,160 --> 00:50:23,320
Speaker 1: the landscape. I would be on the side of a mountain.

871
00:50:23,520 --> 00:50:27,120
Speaker 1: We would trap sheep. Uh. We had a trailer, double

872
00:50:27,160 --> 00:50:31,200
Speaker 1: decker trailer. Feel that trailer full as many as many

873
00:50:31,280 --> 00:50:34,360
Speaker 1: cheap as they would give us, and then as fast

874
00:50:34,360 --> 00:50:36,719
Speaker 1: as we could get back into the turkey, give them

875
00:50:36,719 --> 00:50:41,960
Speaker 1: a handful of turkeys and and uh no, no, uh,

876
00:50:42,400 --> 00:50:44,680
Speaker 1: give them what whatever it was they wanted, because we

877
00:50:44,680 --> 00:50:48,120
Speaker 1: were beggars, that was the bottom line were at that time.

878
00:50:48,160 --> 00:50:50,879
Speaker 1: So so anyway, go back to Texas in twenty four

879
00:50:50,880 --> 00:50:54,480
Speaker 1: hours later, dumping them on the landscape. Well, we were

880
00:50:54,560 --> 00:50:58,120
Speaker 1: drawing blood samples, but we would never wait for the

881
00:50:58,160 --> 00:51:01,920
Speaker 1: results of those samples. Uh So if something would have happened,

882
00:51:01,920 --> 00:51:03,600
Speaker 1: the cat would have been out out of the back

883
00:51:03,719 --> 00:51:07,400
Speaker 1: by then. So now now we we sample source and

884
00:51:07,480 --> 00:51:11,200
Speaker 1: recipient populations in advance, and we look at those kind

885
00:51:11,200 --> 00:51:12,640
Speaker 1: of things. So we're a lot smarter in the way

886
00:51:12,680 --> 00:51:15,799
Speaker 1: we do business. That's a horrible thought to think of,

887
00:51:16,520 --> 00:51:20,920
Speaker 1: just out of out of a very excusable form of

888
00:51:20,960 --> 00:51:24,839
Speaker 1: ignorance to spend that time and energy. Oh, there's no

889
00:51:24,880 --> 00:51:28,600
Speaker 1: doubt in fact a clean herd. Yeah, there there's no

890
00:51:28,640 --> 00:51:31,759
Speaker 1: doubt about it. Because if you look at in the

891
00:51:32,680 --> 00:51:36,160
Speaker 1: disease itself, it you know that it can only come

892
00:51:36,160 --> 00:51:39,160
Speaker 1: from a live animal and there's there's no doubt about it.

893
00:51:39,200 --> 00:51:42,360
Speaker 1: Now that can be domestic cheap, domestic goats, but it

894
00:51:42,360 --> 00:51:45,120
Speaker 1: can also be bigger horn cheap, and it can also

895
00:51:45,239 --> 00:51:49,880
Speaker 1: be uh, wild goats. So that that bacteria doesn't do

896
00:51:49,960 --> 00:51:52,640
Speaker 1: well laying on the dirt. No, it does not, it does.

897
00:51:53,000 --> 00:51:54,880
Speaker 1: It has to come it comes from a life source.

898
00:51:55,719 --> 00:52:00,799
Speaker 1: So but we've again how how close, Like let's talk

899
00:52:00,840 --> 00:52:02,960
Speaker 1: about Trent, let's talk about the transmission for a minute.

900
00:52:03,360 --> 00:52:05,800
Speaker 1: I don't know what I'm gonna let out of a

901
00:52:05,880 --> 00:52:08,960
Speaker 1: rabbit hole, but yeah, because because it's not what you understood,

902
00:52:09,000 --> 00:52:11,960
Speaker 1: I'm just talking like, Okay, you gotta sick. But let's

903
00:52:11,960 --> 00:52:14,000
Speaker 1: not even bring in domestic you don't have to touch noses.

904
00:52:14,080 --> 00:52:18,360
Speaker 1: Let's just it's but the pens are too close together.

905
00:52:18,520 --> 00:52:21,080
Speaker 1: They you know, w s U has a captive herd

906
00:52:21,160 --> 00:52:23,279
Speaker 1: and they got them. I think one of the early

907
00:52:23,320 --> 00:52:26,439
Speaker 1: trials they got a little too close to their clean

908
00:52:26,480 --> 00:52:28,839
Speaker 1: sheet from the six sheets. We're talking inches or feet

909
00:52:28,920 --> 00:52:33,400
Speaker 1: or yard feet yards, you're talking about in some cases

910
00:52:34,200 --> 00:52:40,200
Speaker 1: maybe kilometers. Uh. If that's the case, then what do

911
00:52:40,239 --> 00:52:42,080
Speaker 1: you mean then, like, what do you mean that has

912
00:52:42,120 --> 00:52:44,600
Speaker 1: to go from sheet to sheep? Because it's just a yeah,

913
00:52:44,719 --> 00:52:48,560
Speaker 1: well that's that's let's go back to the IF. If

914
00:52:48,600 --> 00:52:51,760
Speaker 1: you look at the IF, the issues associated with this disease,

915
00:52:51,800 --> 00:52:53,960
Speaker 1: I mean when when when it comes down to it,

916
00:52:55,120 --> 00:52:59,480
Speaker 1: oh oh, wildlife they adapt to the various pathogens that

917
00:52:59,480 --> 00:53:02,600
Speaker 1: they're induced to in some form or fashion. And so

918
00:53:03,239 --> 00:53:07,120
Speaker 1: how to affects bighorn sheep is you need to have

919
00:53:07,200 --> 00:53:11,160
Speaker 1: a complete die off. I mean they just do terrible uh.

920
00:53:11,360 --> 00:53:14,239
Speaker 1: Or you see it where you know, a mother will

921
00:53:14,239 --> 00:53:20,319
Speaker 1: pass down out of bodies two two lambs, and and

922
00:53:20,400 --> 00:53:22,960
Speaker 1: at first, you know, when you when you see them

923
00:53:23,040 --> 00:53:25,440
Speaker 1: the first few weeks of life, they seem to do

924
00:53:25,480 --> 00:53:29,279
Speaker 1: pretty well. But about eight weeks, eight to twelve weeks, uh,

925
00:53:29,400 --> 00:53:32,200
Speaker 1: something like that, then then you start seeing issues and

926
00:53:32,200 --> 00:53:34,480
Speaker 1: then you have complete lamb die off. So so in

927
00:53:34,480 --> 00:53:37,400
Speaker 1: other words, you have complete die offs, then you have

928
00:53:37,440 --> 00:53:41,480
Speaker 1: no recruitment for decades. And then the other part of

929
00:53:41,520 --> 00:53:46,520
Speaker 1: that is that you have some sheep that for whatever reason,

930
00:53:46,920 --> 00:53:51,239
Speaker 1: they don't die and they go from her to her,

931
00:53:51,440 --> 00:53:55,640
Speaker 1: from this one to the typhoid mary that so they

932
00:53:55,719 --> 00:53:58,520
Speaker 1: become a carrier, that is a carrier that sheds that

933
00:53:58,600 --> 00:54:03,240
Speaker 1: disease to other population. And so bighorn sheep move, they move,

934
00:54:03,400 --> 00:54:05,319
Speaker 1: and the other thing is there. They are long lived

935
00:54:05,360 --> 00:54:08,440
Speaker 1: species generally in absence of disease. You know, you just

936
00:54:08,520 --> 00:54:11,239
Speaker 1: can live close to twenty years and rams are you know,

937
00:54:11,320 --> 00:54:13,160
Speaker 1: kind of the ten to twelve is a long long

938
00:54:13,200 --> 00:54:16,520
Speaker 1: live ram. So some of these particular carriers can be

939
00:54:16,600 --> 00:54:19,120
Speaker 1: alive for a long time, moving around and keeping that

940
00:54:19,200 --> 00:54:21,960
Speaker 1: disease in the herd, and it's not able to fade out.

941
00:54:22,160 --> 00:54:25,040
Speaker 1: How much do you guys see? Uh, how much have

942
00:54:25,080 --> 00:54:30,279
Speaker 1: you seen big horns move? Like, don't give me the no.

943
00:54:30,480 --> 00:54:33,880
Speaker 1: I'm always interested in the crazy number, but the number

944
00:54:34,120 --> 00:54:36,160
Speaker 1: the normal and then and then it hit me with

945
00:54:36,160 --> 00:54:39,120
Speaker 1: a crazy number. Okay. So the the number that we're

946
00:54:39,200 --> 00:54:42,680
Speaker 1: using based on sort of this estimation from telemetry data

947
00:54:42,840 --> 00:54:45,279
Speaker 1: that was sort of a published a model that we

948
00:54:45,440 --> 00:54:48,040
Speaker 1: use for sort of risk of contact modeling. So how

949
00:54:48,080 --> 00:54:50,600
Speaker 1: likely our big horn sheep gonna go out and landscape

950
00:54:50,600 --> 00:54:54,799
Speaker 1: and contact a particular distance from their home range? Right,

951
00:54:54,840 --> 00:54:57,319
Speaker 1: So all animals set up a home range. Generally, big

952
00:54:57,320 --> 00:55:00,160
Speaker 1: horn sheep do exploratory movements where they leave their home

953
00:55:00,239 --> 00:55:03,439
Speaker 1: range and then may return. So whether it's to see

954
00:55:03,480 --> 00:55:05,799
Speaker 1: what's going on on the next ridge or to look

955
00:55:05,840 --> 00:55:09,040
Speaker 1: for receptive use, but generally the number there is thirty

956
00:55:09,040 --> 00:55:13,840
Speaker 1: five kilometers. So basically of RAM movements over a fourteen

957
00:55:13,880 --> 00:55:18,160
Speaker 1: year data set showed that almost those movements were within

958
00:55:18,239 --> 00:55:21,640
Speaker 1: thirty five kilometers from their home range. How big this

959
00:55:21,719 --> 00:55:24,600
Speaker 1: core zone? If that varies. It could be, it could

960
00:55:24,600 --> 00:55:28,000
Speaker 1: be larger, could be it could be tight habitat and

961
00:55:28,239 --> 00:55:31,400
Speaker 1: particular individual So some individuals may have small home ranges,

962
00:55:31,480 --> 00:55:35,440
Speaker 1: some might have larger. So the crazy number is a

963
00:55:35,480 --> 00:55:37,959
Speaker 1: little ram that came out of the lost in Herd

964
00:55:38,280 --> 00:55:42,920
Speaker 1: just this past couple of years and near Joseph, Oregon

965
00:55:43,120 --> 00:55:47,359
Speaker 1: or Enterprise and Joseph up in the Allowa Range. So

966
00:55:47,440 --> 00:55:50,280
Speaker 1: he took a little walk and he went on a loop,

967
00:55:50,640 --> 00:55:52,759
Speaker 1: so they were they collared him. He showed up, i

968
00:55:52,760 --> 00:55:56,040
Speaker 1: think on somebody's deck and it was just take and

969
00:55:56,120 --> 00:55:58,880
Speaker 1: he took a good photo and they recognized send him

970
00:55:58,880 --> 00:56:01,239
Speaker 1: the Hell's Canyon Initiative folks, and they recognize him as

971
00:56:01,719 --> 00:56:04,960
Speaker 1: twelve l O seven. Hey, that's so we ear tagged

972
00:56:05,000 --> 00:56:06,400
Speaker 1: him as a lamp. So they knew that they had

973
00:56:06,400 --> 00:56:08,719
Speaker 1: a definitive age on him. And he went across the

974
00:56:08,760 --> 00:56:11,719
Speaker 1: Snake River, the Salmon River and then over into the

975
00:56:11,719 --> 00:56:14,719
Speaker 1: Clearwater drainage in Idaho and then put a collar on

976
00:56:14,800 --> 00:56:16,520
Speaker 1: him at some point and actually put three collars on

977
00:56:16,560 --> 00:56:19,160
Speaker 1: them because they kept failing. So he got caught two

978
00:56:19,200 --> 00:56:20,680
Speaker 1: or three times with the helicopter, and I think he

979
00:56:20,719 --> 00:56:23,719
Speaker 1: got darted once. So and he made a three and

980
00:56:23,760 --> 00:56:27,759
Speaker 1: seventy eight mile loop through seven different home ranges of

981
00:56:27,800 --> 00:56:30,240
Speaker 1: big Horns, and he was out in some weak fields

982
00:56:30,280 --> 00:56:33,160
Speaker 1: and crossed a bunch of highways. And so he went

983
00:56:33,200 --> 00:56:35,680
Speaker 1: a hundred twenty five miles from his home range and

984
00:56:35,840 --> 00:56:37,759
Speaker 1: covered in that year and a half time or so

985
00:56:37,960 --> 00:56:40,400
Speaker 1: with the collar, he covered three seventy eight miles and

986
00:56:40,440 --> 00:56:44,680
Speaker 1: then died on a remote point in Hell's Canyon, natural

987
00:56:44,719 --> 00:56:47,759
Speaker 1: causes for presumably that it it was during thing was during

988
00:56:47,800 --> 00:56:49,680
Speaker 1: the winter, so they couldn't get in there with any

989
00:56:49,680 --> 00:56:51,960
Speaker 1: other website the jet boat. So I don't remember how

990
00:56:52,000 --> 00:56:54,040
Speaker 1: long it was when the collar went on mortality until

991
00:56:54,040 --> 00:56:56,680
Speaker 1: they wentn't recovered it, so he just went on a crew. Yeah,

992
00:56:57,280 --> 00:56:59,520
Speaker 1: So I mean it kind of just demonstrates the behavior

993
00:56:59,560 --> 00:57:01,880
Speaker 1: potential of these animals that some of them are going

994
00:57:01,920 --> 00:57:04,759
Speaker 1: to move and they show up in town. You know,

995
00:57:04,800 --> 00:57:06,920
Speaker 1: when when you're when you have a civilization at the

996
00:57:06,920 --> 00:57:09,080
Speaker 1: bottom of a nice canyon that joins up to another

997
00:57:09,160 --> 00:57:12,720
Speaker 1: big canyon they're going to come through, And it happens

998
00:57:12,719 --> 00:57:16,800
Speaker 1: pretty regularly, especially in that in that landscape of health.

999
00:57:16,840 --> 00:57:20,360
Speaker 1: Ganyon lower heuse Ganyon. Yeah, so this brings up like

1000
00:57:21,680 --> 00:57:26,800
Speaker 1: that brings up a big question. So how we have

1001
00:57:26,840 --> 00:57:29,439
Speaker 1: really set up like what needs to happen here? If

1002
00:57:29,480 --> 00:57:31,600
Speaker 1: we know what needs to happen. But if they're gonna

1003
00:57:31,640 --> 00:57:37,560
Speaker 1: go do that, how do you ever protect them from

1004
00:57:37,560 --> 00:57:41,560
Speaker 1: picking up transmittable diseases and spread them to everybody else?

1005
00:57:43,000 --> 00:57:48,240
Speaker 1: That's a million dollar question. Well, when Steve, the protocol

1006
00:57:48,360 --> 00:57:52,840
Speaker 1: of many Western states is when a bighorn sheep comes

1007
00:57:52,880 --> 00:57:56,720
Speaker 1: in contact with domestic sheep, that bighorn sheep is shot.

1008
00:57:58,120 --> 00:58:01,760
Speaker 1: So that's that's a standing acting protocol because the fear

1009
00:58:01,920 --> 00:58:05,320
Speaker 1: is that that big horn could then be the you know,

1010
00:58:05,400 --> 00:58:10,360
Speaker 1: the vector and as as you know this this damn

1011
00:58:10,440 --> 00:58:13,160
Speaker 1: ram did I mean goes on a walk about and

1012
00:58:13,160 --> 00:58:14,960
Speaker 1: and could have gone through a whole bunch of hers,

1013
00:58:15,000 --> 00:58:17,439
Speaker 1: So you know, kind of the standard protocol, it would

1014
00:58:17,440 --> 00:58:21,120
Speaker 1: be the administrative. Yeah, you would kill like a state

1015
00:58:21,160 --> 00:58:23,880
Speaker 1: age she would kill. That would and they're trying, they're

1016
00:58:23,880 --> 00:58:26,320
Speaker 1: trying to get away from that where possible, so that

1017
00:58:26,600 --> 00:58:29,720
Speaker 1: just the setup I was talking about where some animals

1018
00:58:29,760 --> 00:58:31,960
Speaker 1: will show up and say that, you know a town

1019
00:58:32,000 --> 00:58:34,800
Speaker 1: along the Snake River where there's big horn habitat on

1020
00:58:34,800 --> 00:58:38,520
Speaker 1: all sides, and they show up in town, and you know,

1021
00:58:38,840 --> 00:58:42,640
Speaker 1: generally the the old method was let's just let's remove

1022
00:58:42,720 --> 00:58:44,800
Speaker 1: this animal so it can't go back, and and they're

1023
00:58:44,840 --> 00:58:48,640
Speaker 1: removing it for the express purpose to protect that this

1024
00:58:48,760 --> 00:58:51,240
Speaker 1: could have It could have picked up pneumonia, it could

1025
00:58:51,280 --> 00:58:54,560
Speaker 1: have contact, especially if it was seen obvious ones that

1026
00:58:54,560 --> 00:58:58,640
Speaker 1: are document in a pasture with domestic sheep, domestic goats

1027
00:58:59,120 --> 00:59:01,360
Speaker 1: you know most of the time, or but what they're

1028
00:59:01,400 --> 00:59:03,720
Speaker 1: trying to do now is based on the proximity to

1029
00:59:04,000 --> 00:59:06,520
Speaker 1: w s US that we try to put you know,

1030
00:59:06,680 --> 00:59:10,760
Speaker 1: dark the animal live, capture it, then holding test or else,

1031
00:59:10,920 --> 00:59:13,760
Speaker 1: take it to the w s A w s U

1032
00:59:14,160 --> 00:59:17,320
Speaker 1: facility and then becomes to research animal. Basically, I'd like

1033
00:59:17,440 --> 00:59:20,200
Speaker 1: to this. This was like my big AHA moment when

1034
00:59:20,280 --> 00:59:22,760
Speaker 1: I came here, right I was sitting with our biologists

1035
00:59:22,800 --> 00:59:25,520
Speaker 1: across the hall and and he just kind of said

1036
00:59:25,560 --> 00:59:28,200
Speaker 1: it like it was just something that that just happens.

1037
00:59:28,840 --> 00:59:31,320
Speaker 1: And I'm like, so you're telling me I could go

1038
00:59:31,400 --> 00:59:34,840
Speaker 1: get a grazing permit for my domestic sheep going to

1039
00:59:34,960 --> 00:59:38,680
Speaker 1: public land and then that wild cheap comes down and

1040
00:59:39,280 --> 00:59:43,880
Speaker 1: boom they shoot it and it does you know. So

1041
00:59:43,920 --> 00:59:47,160
Speaker 1: we see in the breaks um a couple of years

1042
00:59:47,160 --> 00:59:50,120
Speaker 1: ago there was two young rams. They went within three

1043
00:59:50,200 --> 00:59:53,960
Speaker 1: quarters of a mile of a domestic sheepherden. Boom they

1044
00:59:53,960 --> 00:59:58,200
Speaker 1: were shot. But yep, yep because of them being a vector.

1045
00:59:59,120 --> 01:00:03,160
Speaker 1: So what's like, what's your do you guys have a

1046
01:00:03,680 --> 01:00:07,840
Speaker 1: official stance on the practice? Because there an alternative to that,

1047
01:00:07,960 --> 01:00:10,000
Speaker 1: I mean, just to that part of it right there. Now.

1048
01:00:10,040 --> 01:00:15,160
Speaker 1: We we we you know, our are our objective is

1049
01:00:15,200 --> 01:00:19,479
Speaker 1: to keep the two species separate. So um, if there's

1050
01:00:19,520 --> 01:00:21,920
Speaker 1: non contact, you know, if you can send them off

1051
01:00:21,960 --> 01:00:24,280
Speaker 1: to w s U or send them off to sabille

1052
01:00:24,280 --> 01:00:28,120
Speaker 1: In in Wyoming, great um. But you know you think

1053
01:00:28,160 --> 01:00:31,040
Speaker 1: about that, that's also a death sense. You know, they're

1054
01:00:31,080 --> 01:00:34,800
Speaker 1: going to now be a guinea pig for disease testing. Um.

1055
01:00:35,080 --> 01:00:38,000
Speaker 1: So that you know that there's really not much we

1056
01:00:38,040 --> 01:00:40,840
Speaker 1: can do other than keep the two separated. So you know,

1057
01:00:40,960 --> 01:00:43,880
Speaker 1: we circle back to Washington, d C. You know, that's

1058
01:00:43,880 --> 01:00:46,840
Speaker 1: what we're advocating for back in Washington, d c IS

1059
01:00:46,840 --> 01:00:51,440
Speaker 1: is federal land managers and agencies to to work for

1060
01:00:51,640 --> 01:00:56,959
Speaker 1: spatial and temporal separation of of wild sheep and domestic sheep.

1061
01:00:57,160 --> 01:00:58,840
Speaker 1: What does that need to look like? I can I

1062
01:00:58,920 --> 01:01:05,000
Speaker 1: can imagine where it becomes contentious. Could you mind like

1063
01:01:05,200 --> 01:01:07,280
Speaker 1: sketching out the obvious and how does that become a

1064
01:01:07,280 --> 01:01:10,360
Speaker 1: contentious conversation? Well? You you know, you got I was.

1065
01:01:10,440 --> 01:01:12,560
Speaker 1: I was just back there with a with a producer

1066
01:01:12,600 --> 01:01:15,440
Speaker 1: who's who's this is domestic sheep producer. He's the largest

1067
01:01:16,040 --> 01:01:20,160
Speaker 1: public land domestic sheep producer in uh in Montana. He's

1068
01:01:20,160 --> 01:01:23,919
Speaker 1: a good guy, uh and he gets it and he

1069
01:01:24,120 --> 01:01:27,360
Speaker 1: uh he does his best to keep his domestic sheep

1070
01:01:27,400 --> 01:01:31,600
Speaker 1: away from wild sheep um and he wants more wild

1071
01:01:31,680 --> 01:01:35,280
Speaker 1: sheep on on Montana's mountains. But you know, the the

1072
01:01:35,360 --> 01:01:40,680
Speaker 1: issue there's um litigation. Uh. Whild she Foundations really not

1073
01:01:41,560 --> 01:01:44,600
Speaker 1: a litigant type organization. We we we feel we'd rather sit

1074
01:01:44,600 --> 01:01:48,240
Speaker 1: around the table and and and workout solutions. So you know,

1075
01:01:48,280 --> 01:01:51,240
Speaker 1: our our objective there, Steve, would be to sit down

1076
01:01:51,240 --> 01:01:54,160
Speaker 1: with that producer and go all right, Uh. You know

1077
01:01:54,200 --> 01:01:58,200
Speaker 1: the Western way of doing things is having a whiskey

1078
01:01:58,560 --> 01:02:02,120
Speaker 1: chatting ig olloging that there's an issue first and foremost

1079
01:02:02,480 --> 01:02:06,080
Speaker 1: and then looking for solutions. Is it is at times

1080
01:02:06,080 --> 01:02:09,120
Speaker 1: of year when when a producer's trailing through an area,

1081
01:02:09,560 --> 01:02:11,880
Speaker 1: UH is it is it how he uses or she

1082
01:02:12,080 --> 01:02:15,240
Speaker 1: uses the the upper allotments or you know these high

1083
01:02:15,240 --> 01:02:20,000
Speaker 1: mountain allotments. So UM, we've we've done various programs in

1084
01:02:20,080 --> 01:02:22,600
Speaker 1: various states. There's a few states that have very good

1085
01:02:22,600 --> 01:02:25,600
Speaker 1: collaboratives where you have a wild sheep and domestic sheep

1086
01:02:26,200 --> 01:02:29,520
Speaker 1: UH interaction working group. UH. We don't always agree, but

1087
01:02:29,560 --> 01:02:31,919
Speaker 1: we sit around a table once or twice a year

1088
01:02:31,960 --> 01:02:33,920
Speaker 1: and say, let's, you know, let's come up with solutions

1089
01:02:33,960 --> 01:02:36,840
Speaker 1: that we can UH, we can, we can work this out.

1090
01:02:36,920 --> 01:02:41,080
Speaker 1: Doesn't work everywhere. UM. You know wild sheep foundations of

1091
01:02:41,080 --> 01:02:47,560
Speaker 1: official position as we want healthy and UH expanding wild

1092
01:02:47,600 --> 01:02:51,720
Speaker 1: sheep herds UM, but we also support a vibrant domestic

1093
01:02:51,760 --> 01:02:55,680
Speaker 1: sheep industry. The key is there's often places that just

1094
01:02:55,840 --> 01:03:02,080
Speaker 1: absolutely incompatible in the same landscape. UM. We have worked

1095
01:03:02,200 --> 01:03:08,080
Speaker 1: with um permitees to convert if it's a high conflict area,

1096
01:03:08,160 --> 01:03:12,160
Speaker 1: you've got a large population of big horn sheep, large

1097
01:03:12,200 --> 01:03:15,840
Speaker 1: population of domestic sheep, and we know there's going to

1098
01:03:15,920 --> 01:03:19,080
Speaker 1: be contact. We've worked with some producers to convert them

1099
01:03:19,120 --> 01:03:22,760
Speaker 1: to cattle were appropriate. Uh. There have been situations where

1100
01:03:22,760 --> 01:03:27,320
Speaker 1: we've worked with producers to pay them almost like a

1101
01:03:27,400 --> 01:03:31,840
Speaker 1: CRP program in the Midwest, but pay them to retire

1102
01:03:31,920 --> 01:03:35,160
Speaker 1: their allotment or vacate their lot, just to look at like,

1103
01:03:35,200 --> 01:03:40,000
Speaker 1: what would you make in profits running sheep? Can we

1104
01:03:40,040 --> 01:03:43,400
Speaker 1: take conservation dollars and we'll pay you to not do it?

1105
01:03:44,120 --> 01:03:46,840
Speaker 1: We take private conservation dollars to pay it and not

1106
01:03:46,960 --> 01:03:49,720
Speaker 1: do it. We just have you have a willing seller,

1107
01:03:49,760 --> 01:03:52,920
Speaker 1: willing absolutely and we you know, we we paid a

1108
01:03:54,080 --> 01:03:57,040
Speaker 1: just because we're these These deals are typically confidential, so

1109
01:03:57,080 --> 01:03:59,520
Speaker 1: I won't even mention the state, but we we pay

1110
01:03:59,600 --> 01:04:04,600
Speaker 1: to produce or four seven thousand dollars to vacate uh

1111
01:04:04,640 --> 01:04:09,320
Speaker 1: their allotment. Um. They were also in getting into trouble

1112
01:04:09,360 --> 01:04:13,320
Speaker 1: with grizzly bears and wolves. Uh constant constant problem. So

1113
01:04:13,800 --> 01:04:16,840
Speaker 1: uh the expansion of grizzly bears and expansion of of

1114
01:04:16,840 --> 01:04:20,520
Speaker 1: of wolves has in some ways benefited big horn sheep

1115
01:04:20,520 --> 01:04:24,280
Speaker 1: in some states because the primitives want to get get

1116
01:04:24,320 --> 01:04:26,240
Speaker 1: the hell out of there, and they come to NGOs

1117
01:04:26,280 --> 01:04:28,280
Speaker 1: like Wild Chief Foundation and say can you give us

1118
01:04:28,280 --> 01:04:30,720
Speaker 1: a hand, and we do, and we do, and we've

1119
01:04:30,760 --> 01:04:34,080
Speaker 1: spent hundreds and hundreds of thousands of dollars doing that,

1120
01:04:34,440 --> 01:04:38,200
Speaker 1: and you nailed it on a willing seller, willing buyer deal.

1121
01:04:38,920 --> 01:04:42,120
Speaker 1: But what does it look like? You're talking about big

1122
01:04:42,280 --> 01:04:49,560
Speaker 1: organized producers okay, who presumably have kind of like a

1123
01:04:49,680 --> 01:04:54,480
Speaker 1: business sensibility, they have a sense of profit loss. But

1124
01:04:54,760 --> 01:04:58,560
Speaker 1: what about all the people that just have two or

1125
01:04:58,600 --> 01:05:01,280
Speaker 1: three sheep? Excellent? How do you even know who they are?

1126
01:05:01,680 --> 01:05:04,240
Speaker 1: Excellent question, because I mean I could go like my brother,

1127
01:05:04,560 --> 01:05:08,080
Speaker 1: he has lived and he doesn't formally big Orange country.

1128
01:05:08,360 --> 01:05:11,000
Speaker 1: He's got some sheep, He's got ten acres that irrigated pasture,

1129
01:05:11,840 --> 01:05:14,640
Speaker 1: he's got sheep out there. There's nothing to prevent him

1130
01:05:14,680 --> 01:05:17,760
Speaker 1: from having a buddy come over and say, hey man,

1131
01:05:17,760 --> 01:05:20,320
Speaker 1: I'd love to have a lamp for my place. Nothing.

1132
01:05:20,480 --> 01:05:25,560
Speaker 1: There's no paperwork. So the key, the key key there

1133
01:05:25,600 --> 01:05:28,360
Speaker 1: is education, you know. So I mean on this on

1134
01:05:28,400 --> 01:05:31,120
Speaker 1: this podcast, I mean we're we're gonna be educating people

1135
01:05:31,160 --> 01:05:36,439
Speaker 1: that there's an issue. Um you know, Uh, I came

1136
01:05:36,480 --> 01:05:39,000
Speaker 1: from Texas and I go down to to Houston and

1137
01:05:39,040 --> 01:05:41,760
Speaker 1: I gave a presentation, I talked, I talked about the

1138
01:05:41,800 --> 01:05:44,960
Speaker 1: disease issue into a hunting community that you would presume

1139
01:05:45,120 --> 01:05:47,240
Speaker 1: would would know something about it, and it's kind of

1140
01:05:47,240 --> 01:05:50,680
Speaker 1: blank stairs. I've never heard of it, um, truth be told.

1141
01:05:50,720 --> 01:05:52,840
Speaker 1: I came to the Wild Chief Foundation for Dallas of

1142
01:05:52,880 --> 01:05:54,720
Speaker 1: Fark Club, I wasn't aware of it. I've been in

1143
01:05:54,760 --> 01:05:58,280
Speaker 1: the Huntington conservation industry for eighteen years. I hadn't heard

1144
01:05:58,280 --> 01:06:01,880
Speaker 1: about it. So it's it's it's education. Um. While she

1145
01:06:02,000 --> 01:06:06,880
Speaker 1: foundation obviously respects private landowners, um you know, respects private

1146
01:06:07,000 --> 01:06:10,240
Speaker 1: land rights, uh and your ability to do what you

1147
01:06:10,600 --> 01:06:14,280
Speaker 1: you want on your land. But um, you know, our

1148
01:06:14,320 --> 01:06:18,160
Speaker 1: our our effort there would be to educate those private

1149
01:06:18,240 --> 01:06:22,120
Speaker 1: landowners or those recreational producers or hobby flocks or whatever

1150
01:06:22,160 --> 01:06:26,160
Speaker 1: you want. Four h um f a a lot of

1151
01:06:26,160 --> 01:06:28,440
Speaker 1: four h animals out there that could get in trouble.

1152
01:06:29,080 --> 01:06:32,160
Speaker 1: Educate them. UM. I just I just spent two years,

1153
01:06:32,320 --> 01:06:35,960
Speaker 1: two days on the Missouri River with a UM private

1154
01:06:36,160 --> 01:06:40,840
Speaker 1: producer in southern BC who gets it, um. And interesting enough,

1155
01:06:40,960 --> 01:06:44,440
Speaker 1: he's got a small flock of domestic cheap they're actually

1156
01:06:44,520 --> 01:06:48,760
Speaker 1: mouflan sheep, and he's in proximity to Big Horn habitat

1157
01:06:49,280 --> 01:06:52,520
Speaker 1: and he's a part of an Internet interaction working group

1158
01:06:52,560 --> 01:06:54,960
Speaker 1: in Southern BC, and he was the guy that asked

1159
01:06:54,960 --> 01:06:57,400
Speaker 1: the question of them. He goes, well, why don't I,

1160
01:06:57,760 --> 01:07:02,880
Speaker 1: as a producer, test my sheep for amovie? He did,

1161
01:07:03,680 --> 01:07:06,720
Speaker 1: and he's got a nemovie free flock and he's now

1162
01:07:06,840 --> 01:07:10,360
Speaker 1: one of our biggest advocates as a domestic sheep producer

1163
01:07:11,160 --> 01:07:15,160
Speaker 1: for amovie free flock. So that would be potentially one

1164
01:07:15,200 --> 01:07:18,400
Speaker 1: of the solutions. And that's pretty interesting to think about

1165
01:07:18,480 --> 01:07:21,520
Speaker 1: because I mean, you know, a lot of states have

1166
01:07:21,720 --> 01:07:27,240
Speaker 1: managed to get brucellosis out of livestock hurts. Is that

1167
01:07:27,320 --> 01:07:29,600
Speaker 1: an area of interest to think that you could expand

1168
01:07:29,680 --> 01:07:33,920
Speaker 1: absolutely well, they would, you know, they would be amovie

1169
01:07:33,960 --> 01:07:37,600
Speaker 1: free sheep. There's a doctor Tom Besser who's our Rocky

1170
01:07:37,680 --> 01:07:41,000
Speaker 1: Crate Endowed Charities at Washington State University, probably one of

1171
01:07:41,000 --> 01:07:44,800
Speaker 1: the world's foremost experts on this issue, and he's advised

1172
01:07:44,920 --> 01:07:49,160
Speaker 1: us that if you have an iMovie free domestic flock,

1173
01:07:49,280 --> 01:07:53,400
Speaker 1: that's about a nineties seven percent solution to this issue.

1174
01:07:54,560 --> 01:07:59,080
Speaker 1: So that that is exciting. UM, But there's a fly

1175
01:07:59,200 --> 01:08:05,640
Speaker 1: in the ointment Scott. Scott just talked about that ram

1176
01:08:05,640 --> 01:08:08,560
Speaker 1: that did a three hundred some odd mile walk about.

1177
01:08:10,120 --> 01:08:16,080
Speaker 1: So we've got you know, we we know that um

1178
01:08:16,200 --> 01:08:21,599
Speaker 1: iMovie is not endemic to bighorn sheep, but in iMovie

1179
01:08:21,720 --> 01:08:24,920
Speaker 1: is now resident in bighorn sheep. So we have herds

1180
01:08:24,920 --> 01:08:27,240
Speaker 1: and you know we're in Montana, so we have herds

1181
01:08:27,240 --> 01:08:31,559
Speaker 1: in Montana that they test positive for iMovie UM. As

1182
01:08:31,560 --> 01:08:34,519
Speaker 1: Scott pointed out, there's a variety of strains. It's kind

1183
01:08:34,520 --> 01:08:37,360
Speaker 1: of like the you know, not necessarily but again Layman's terms,

1184
01:08:37,400 --> 01:08:39,160
Speaker 1: kind of like the flu or the cold. You know,

1185
01:08:39,240 --> 01:08:41,599
Speaker 1: sometimes you get one hell of a common cold. Sometimes

1186
01:08:41,640 --> 01:08:43,760
Speaker 1: you get a little light one. Sometimes you get a flue.

1187
01:08:43,800 --> 01:08:45,840
Speaker 1: You know, there's a flu virus that you know that

1188
01:08:45,960 --> 01:08:49,080
Speaker 1: just wipes you out. Other times it's not so bad.

1189
01:08:49,520 --> 01:08:53,160
Speaker 1: The same thing with you know, strains of iMovie. Uh,

1190
01:08:53,200 --> 01:08:57,400
Speaker 1: this this big horn may be able to live with it. Well,

1191
01:08:57,640 --> 01:08:59,479
Speaker 1: now here's the fly in the ointment. What if we

1192
01:08:59,640 --> 01:09:03,200
Speaker 1: have a private land domestic sheep producer doing the right

1193
01:09:03,320 --> 01:09:08,559
Speaker 1: thing to tons of money testing his or her sheep.

1194
01:09:08,680 --> 01:09:11,880
Speaker 1: They're a movie free they make sure they only bring

1195
01:09:11,960 --> 01:09:15,200
Speaker 1: in stock from amovie free. And we got a wandering

1196
01:09:15,280 --> 01:09:19,599
Speaker 1: bighorn that's a movie positive. Now we've now we've switched

1197
01:09:20,400 --> 01:09:24,960
Speaker 1: the dynamic there, and you know that the fact is

1198
01:09:25,000 --> 01:09:28,559
Speaker 1: we've got to be intellectually honest and go We're still

1199
01:09:28,600 --> 01:09:32,000
Speaker 1: back into a separation scenario now, we're trying to separate

1200
01:09:32,439 --> 01:09:35,280
Speaker 1: you know, these iMovie free clean domestic sheep from a

1201
01:09:35,320 --> 01:09:40,840
Speaker 1: potentially UM infected wild sheep. The truth of the matter,

1202
01:09:41,240 --> 01:09:45,000
Speaker 1: if we were gonna have to think different, we we

1203
01:09:45,120 --> 01:09:48,559
Speaker 1: can't continue to do the way we've done in the past.

1204
01:09:48,640 --> 01:09:51,840
Speaker 1: And I think there are opportunities that we missed UM

1205
01:09:52,280 --> 01:09:54,360
Speaker 1: and I want to emphasize the work that was done.

1206
01:09:55,240 --> 01:09:59,320
Speaker 1: Great Gray mentioned private landowners earlier. We restored bighorn sheep

1207
01:09:59,400 --> 01:10:03,000
Speaker 1: in Texas with private landowners because you didn't have a

1208
01:10:03,080 --> 01:10:06,439
Speaker 1: choice there. Absolutely absolutely so we figured out a way

1209
01:10:06,479 --> 01:10:09,280
Speaker 1: to do this together. And these are these are people

1210
01:10:09,439 --> 01:10:12,439
Speaker 1: who care and and our goal is certainly not to

1211
01:10:13,080 --> 01:10:16,599
Speaker 1: put people out of business. Uh. To me, the way

1212
01:10:16,640 --> 01:10:19,439
Speaker 1: we do this is we figure out new solutions, better

1213
01:10:19,479 --> 01:10:22,080
Speaker 1: way of doing business. We sit out at the same table.

1214
01:10:22,200 --> 01:10:26,120
Speaker 1: We don't play the politics. We we we stopped denying

1215
01:10:26,240 --> 01:10:29,640
Speaker 1: that the disease exists. It's it's real. You asked me

1216
01:10:29,680 --> 01:10:32,719
Speaker 1: a question, or ask us all a question earlier. Didn't

1217
01:10:32,720 --> 01:10:36,439
Speaker 1: you have any ideas you what's those numbers decline? Everybody

1218
01:10:36,479 --> 01:10:38,519
Speaker 1: had a thought, they had a pretty good idea why

1219
01:10:38,600 --> 01:10:43,200
Speaker 1: it just never was demonstrated or proven. And and later

1220
01:10:43,240 --> 01:10:47,920
Speaker 1: on that information came in a controlled experiment and where

1221
01:10:47,960 --> 01:10:50,360
Speaker 1: we where we knew that it that it did occur.

1222
01:10:50,960 --> 01:10:54,080
Speaker 1: And then the question it became, well, that didn't really

1223
01:10:54,080 --> 01:10:57,120
Speaker 1: occur in the wild. Uh, you guys did that in

1224
01:10:57,200 --> 01:10:59,759
Speaker 1: a controlled setting? It really doesn't occur in the wild.

1225
01:11:00,040 --> 01:11:02,720
Speaker 1: It does. So the first the first thing we have

1226
01:11:02,800 --> 01:11:05,880
Speaker 1: to do is acknowledge that we've got a problem, and

1227
01:11:05,880 --> 01:11:08,840
Speaker 1: then we start working together. And Grace says it best.

1228
01:11:08,920 --> 01:11:11,800
Speaker 1: He talks about, you know, it's okay to have both

1229
01:11:11,880 --> 01:11:14,240
Speaker 1: on the landscape, they just can't be there at the

1230
01:11:14,280 --> 01:11:16,479
Speaker 1: same time, at the same place. And so we have

1231
01:11:16,520 --> 01:11:19,959
Speaker 1: to figure out what that what that does look like. Uh,

1232
01:11:20,040 --> 01:11:22,360
Speaker 1: but we are going to have to think outside the box.

1233
01:11:22,400 --> 01:11:26,000
Speaker 1: How you know, how do how do we do things?

1234
01:11:26,439 --> 01:11:30,200
Speaker 1: Is it? I know? And and and probably will suck

1235
01:11:30,240 --> 01:11:32,200
Speaker 1: the air out of this room. But we allow private

1236
01:11:32,240 --> 01:11:36,000
Speaker 1: landowners in Texas to benefit from sheep tags. There's an

1237
01:11:36,000 --> 01:11:39,240
Speaker 1: incentive there for landowners to work with us, and it's

1238
01:11:39,280 --> 01:11:44,000
Speaker 1: work extremely well. Um landowners are willing to do whatever

1239
01:11:44,080 --> 01:11:48,080
Speaker 1: it takes, we conduct we uh. Landowners allow public hunters

1240
01:11:48,080 --> 01:11:52,440
Speaker 1: on their property to hunt. UH, we hunt each other's property.

1241
01:11:52,520 --> 01:11:56,120
Speaker 1: We we do research, We capture sheep on private land.

1242
01:11:56,520 --> 01:11:59,120
Speaker 1: So there are lots of other examples. That's just like

1243
01:11:59,200 --> 01:12:03,120
Speaker 1: in that mob, you're going for a thing where you're

1244
01:12:03,120 --> 01:12:06,479
Speaker 1: trying to change the landowner perception of what it means

1245
01:12:06,479 --> 01:12:09,519
Speaker 1: to have sheep. It's not just like you're screwed now,

1246
01:12:09,520 --> 01:12:12,200
Speaker 1: a buddy, there's a sheep on your property, exactly, and

1247
01:12:12,640 --> 01:12:17,439
Speaker 1: you'll never as a private landowner or a producer. Why

1248
01:12:17,439 --> 01:12:19,479
Speaker 1: would I care if there were sheep bigger and cheap

1249
01:12:19,520 --> 01:12:22,720
Speaker 1: around here? If I saw no benefit from that? And

1250
01:12:22,760 --> 01:12:25,200
Speaker 1: so I think there are opportunities that we haven't explored

1251
01:12:25,720 --> 01:12:27,400
Speaker 1: that we need to. We need to sit down on

1252
01:12:27,439 --> 01:12:30,320
Speaker 1: the at the same table work through some of these issues.

1253
01:12:30,320 --> 01:12:33,560
Speaker 1: But but we can't do that if we don't acknowledge

1254
01:12:33,600 --> 01:12:36,800
Speaker 1: that the disease exists, and if if every time something

1255
01:12:36,880 --> 01:12:40,679
Speaker 1: major happens or an obstacle comes up a stumbling block,

1256
01:12:40,800 --> 01:12:43,760
Speaker 1: we run straight to d C. Are there are there

1257
01:12:43,880 --> 01:12:48,400
Speaker 1: pneumonia deniers? Oh? Absolutely, It seems to be a common

1258
01:12:48,439 --> 01:12:54,559
Speaker 1: theme across the handful of CD deniers. Absolutely, well, there's

1259
01:12:54,600 --> 01:12:57,280
Speaker 1: deniers and then there's users of you know, we've seen

1260
01:12:57,800 --> 01:13:01,439
Speaker 1: it uses a leveraging tool when they know that we'll

1261
01:13:01,479 --> 01:13:04,960
Speaker 1: pay to play. Hey, you know, hey, we're gonna bring

1262
01:13:05,000 --> 01:13:08,479
Speaker 1: in some domestics in here. What do you think of that?

1263
01:13:09,880 --> 01:13:13,639
Speaker 1: Or you know there's a guy in in gardener somewhere. Um,

1264
01:13:13,800 --> 01:13:16,360
Speaker 1: he got pissed he lost his grazing allotments and said

1265
01:13:16,479 --> 01:13:19,439
Speaker 1: all right and brought in domestic sheep when we lost

1266
01:13:19,479 --> 01:13:23,519
Speaker 1: forty three sheep that winter, because he was like, well,

1267
01:13:24,080 --> 01:13:25,720
Speaker 1: we had a we had a guy down in Wyoming

1268
01:13:25,800 --> 01:13:28,840
Speaker 1: that he was basically a cattle producer, but he had

1269
01:13:28,920 --> 01:13:32,040
Speaker 1: he had cattle a lotments up to eleven thousand feet

1270
01:13:32,040 --> 01:13:37,280
Speaker 1: in the mountains and the in prime prime Big Horn habitat,

1271
01:13:37,880 --> 01:13:39,800
Speaker 1: and he had he was, you know, not not the

1272
01:13:39,880 --> 01:13:41,920
Speaker 1: not the best grazer in the world. And he'd gotten

1273
01:13:41,920 --> 01:13:44,479
Speaker 1: in trouble with the BLM constantly and he lost his

1274
01:13:44,520 --> 01:13:48,280
Speaker 1: BLM cattle allotments. He goes, fine, I'm gonna put domestic

1275
01:13:48,320 --> 01:13:51,200
Speaker 1: sheep on my deeded land up at eleven thousand feet

1276
01:13:51,280 --> 01:13:53,880
Speaker 1: right in Big Horn habitat. Now, what are you gonna do?

1277
01:13:54,880 --> 01:14:01,200
Speaker 1: So so then he just doing just retribution. That's wildlife terrorism. Yeah,

1278
01:14:01,200 --> 01:14:04,519
Speaker 1: that's wildlife terrorism because you know he knows you know.

1279
01:14:04,560 --> 01:14:06,920
Speaker 1: So as as Garrett said, you know you've got you've

1280
01:14:06,960 --> 01:14:09,280
Speaker 1: got people, you've got deniers, and then you've got those

1281
01:14:09,320 --> 01:14:11,880
Speaker 1: that will use me as a weapon. Well, and that

1282
01:14:11,920 --> 01:14:16,439
Speaker 1: that also occurs on just the different public lands issues. Uh.

1283
01:14:16,520 --> 01:14:20,160
Speaker 1: There there are some who would use use the grazing

1284
01:14:20,240 --> 01:14:24,320
Speaker 1: part of it is as or the anti grazing part

1285
01:14:24,360 --> 01:14:27,599
Speaker 1: of it. Uh, bring big horns into that, just just

1286
01:14:27,640 --> 01:14:30,439
Speaker 1: to lay that on the table. In other words, Uh,

1287
01:14:30,479 --> 01:14:33,280
Speaker 1: it's all about where it might be about public land grazing.

1288
01:14:33,320 --> 01:14:35,960
Speaker 1: That's not what we're about either, has nothing to do

1289
01:14:36,000 --> 01:14:38,760
Speaker 1: with that. I don't follow what you're saying. Well, one

1290
01:14:38,760 --> 01:14:40,800
Speaker 1: of the one of the public land guys can say it.

1291
01:14:40,960 --> 01:14:44,080
Speaker 1: Say it better there we have U. There are some

1292
01:14:44,479 --> 01:14:48,719
Speaker 1: groups who would use big horns cheap to say that

1293
01:14:49,280 --> 01:14:51,599
Speaker 1: we don't want any grazing on public land, so let's

1294
01:14:51,680 --> 01:14:54,519
Speaker 1: use big horn cheap to accomplish this. So someone who

1295
01:14:54,560 --> 01:14:57,240
Speaker 1: had an agenda where they felt like they weren't so

1296
01:14:57,360 --> 01:15:02,240
Speaker 1: much pro big horn as they were antirasing on public lands,

1297
01:15:02,400 --> 01:15:03,720
Speaker 1: and they'd be like this would be a great place

1298
01:15:03,760 --> 01:15:06,240
Speaker 1: for some big horns, and I know that I can,

1299
01:15:06,720 --> 01:15:08,640
Speaker 1: I'll be able to manipulate that in the achieving my

1300
01:15:08,680 --> 01:15:11,479
Speaker 1: other goal. And that's not that's not our mission. Our

1301
01:15:11,560 --> 01:15:14,240
Speaker 1: mission is is simple. We put and keep sheep on

1302
01:15:14,280 --> 01:15:16,920
Speaker 1: the mountain. And and if we're gonna do this, we're

1303
01:15:16,920 --> 01:15:19,560
Speaker 1: gonna have to do it together with livestock producers. And

1304
01:15:19,640 --> 01:15:21,679
Speaker 1: I think there are some really good examples out there

1305
01:15:22,040 --> 01:15:25,920
Speaker 1: for people working together. Uh well, I think that the key,

1306
01:15:26,160 --> 01:15:28,760
Speaker 1: Like you know, I've met with and have spoken with

1307
01:15:28,800 --> 01:15:33,840
Speaker 1: a lot of very effective players in the conservation space,

1308
01:15:33,880 --> 01:15:36,320
Speaker 1: people like the people in this room, in this organization,

1309
01:15:36,320 --> 01:15:38,960
Speaker 1: who have a long track record. And the thing that

1310
01:15:39,000 --> 01:15:42,000
Speaker 1: I find that these groups are in is you're in

1311
01:15:42,040 --> 01:15:47,240
Speaker 1: the middle, and you got some crazies off to each side,

1312
01:15:47,840 --> 01:15:50,880
Speaker 1: and you're trying to guide right, You're trying to keep

1313
01:15:50,920 --> 01:15:55,000
Speaker 1: this thing moving along with some pretty radical fringe elements

1314
01:15:55,000 --> 01:15:57,920
Speaker 1: probably barking at you from both sides. Absolutely, you know,

1315
01:15:58,000 --> 01:16:00,479
Speaker 1: and then I think, you know, going back too, he

1316
01:16:00,600 --> 01:16:03,400
Speaker 1: just keeps preaching education and it's huge, huge, you know,

1317
01:16:03,439 --> 01:16:07,080
Speaker 1: I've worked with, spoke to your buddy Ryan Callahan a lot,

1318
01:16:07,200 --> 01:16:09,640
Speaker 1: like you talk to these companies who one of their

1319
01:16:09,640 --> 01:16:12,320
Speaker 1: biggest things is wool, you know, and they're always preaching

1320
01:16:12,680 --> 01:16:14,640
Speaker 1: that they're selling great wool products, but where do you

1321
01:16:14,640 --> 01:16:17,479
Speaker 1: get it? You know, you have some people that are

1322
01:16:18,840 --> 01:16:21,360
Speaker 1: they do and so they're safe, right, same with Sika,

1323
01:16:21,400 --> 01:16:23,720
Speaker 1: they're saying, you know, so talking with Sia in first life,

1324
01:16:23,720 --> 01:16:25,040
Speaker 1: I mean like, hey guys, you guys want to talk

1325
01:16:25,040 --> 01:16:26,720
Speaker 1: about where you get your wool from? Where? Maybe where

1326
01:16:26,720 --> 01:16:30,439
Speaker 1: you shouldn't. You have some groups that say we're environmentally friendly,

1327
01:16:31,040 --> 01:16:33,680
Speaker 1: you know, because we source our wool here locally and

1328
01:16:33,720 --> 01:16:35,760
Speaker 1: there's not these shipping things and all that, and then

1329
01:16:35,760 --> 01:16:37,440
Speaker 1: you go where do you get in? They go Colorado.

1330
01:16:38,040 --> 01:16:40,280
Speaker 1: You go, oh, so you're just killing you know. I

1331
01:16:40,360 --> 01:16:44,519
Speaker 1: sat next to Van Snard up on stage talking about how, yeah,

1332
01:16:44,560 --> 01:16:47,280
Speaker 1: if you're sourcing your wool west of the Mississippi, you're

1333
01:16:47,320 --> 01:16:50,439
Speaker 1: probably contributing to the die off of big horn cheap.

1334
01:16:51,439 --> 01:16:55,880
Speaker 1: And that got an interesting, I mean bold statement. Man. Yeah, well,

1335
01:16:55,920 --> 01:16:58,960
Speaker 1: I mean, you know, and but a statement that people

1336
01:16:59,000 --> 01:17:01,600
Speaker 1: could read into pretty heavily. Yeah it will, and you know,

1337
01:17:01,640 --> 01:17:03,760
Speaker 1: I I should probably should have followed it up more.

1338
01:17:03,840 --> 01:17:07,120
Speaker 1: But people just don't understand. And a lot of times

1339
01:17:07,160 --> 01:17:10,200
Speaker 1: these people building the garments and understand talking, you know,

1340
01:17:10,280 --> 01:17:12,760
Speaker 1: Ryan Callahan is a very educated dude when it comes

1341
01:17:12,800 --> 01:17:15,360
Speaker 1: to conservation and a lot of these things he did

1342
01:17:15,240 --> 01:17:18,599
Speaker 1: had no idea about. So so if we talk about

1343
01:17:18,760 --> 01:17:21,559
Speaker 1: if we look at this like the separation thing, the

1344
01:17:21,600 --> 01:17:28,080
Speaker 1: separation idea, Um, well, well first I'm gonna dress something

1345
01:17:28,120 --> 01:17:30,920
Speaker 1: you just brought up. Is there do you guys have

1346
01:17:31,200 --> 01:17:34,599
Speaker 1: a is there like, is there a the equivalent of

1347
01:17:34,640 --> 01:17:39,320
Speaker 1: like labeling something organic or labeling uh an organization to

1348
01:17:39,439 --> 01:17:43,600
Speaker 1: be of a certain pedigree of four oh one k nonprofit? Like?

1349
01:17:43,720 --> 01:17:45,200
Speaker 1: Is there do you guys have a way where you

1350
01:17:45,240 --> 01:17:48,880
Speaker 1: like are certifying or giving a stamp of approval to

1351
01:17:48,960 --> 01:17:55,880
Speaker 1: certain producers for practicing. No, we we looked into it. Yeah,

1352
01:17:56,240 --> 01:17:59,920
Speaker 1: we had a we had a um, you know, kind

1353
01:18:00,040 --> 01:18:06,920
Speaker 1: of a Wild Sheep Safe campaign and it it's the

1354
01:18:07,000 --> 01:18:10,240
Speaker 1: challenge with that, Steve is it did get into a

1355
01:18:10,280 --> 01:18:18,280
Speaker 1: certification process and we didn't have the staff um and

1356
01:18:18,280 --> 01:18:20,400
Speaker 1: and you know then we we talked to our attorneys

1357
01:18:20,400 --> 01:18:23,600
Speaker 1: and they went, oh, man, you certify one and not

1358
01:18:23,920 --> 01:18:27,120
Speaker 1: you know, so yeah, we kind of backed away from

1359
01:18:27,120 --> 01:18:29,720
Speaker 1: that on the Wild Sheep Safe and and it's and

1360
01:18:29,720 --> 01:18:31,760
Speaker 1: it's it's almost like Scott had said on you know,

1361
01:18:31,800 --> 01:18:37,360
Speaker 1: what is effective separation. What is the distance. It's a

1362
01:18:37,400 --> 01:18:39,759
Speaker 1: real it's a real challenge there. It's like an impuge.

1363
01:18:39,760 --> 01:18:42,040
Speaker 1: It sound there's a thing. There's like a type of building.

1364
01:18:43,080 --> 01:18:45,639
Speaker 1: It's like what they call it salmon safe or salmon

1365
01:18:45,720 --> 01:18:48,200
Speaker 1: country or something in a building can in a building

1366
01:18:48,240 --> 01:18:50,400
Speaker 1: can comply in a certain way and has to do

1367
01:18:50,479 --> 01:18:53,920
Speaker 1: with the quality the runoff. That has to do with it.

1368
01:18:54,040 --> 01:18:58,280
Speaker 1: You've achieved some threshold, some measurable threshold of of acknowledgement

1369
01:18:58,360 --> 01:19:00,720
Speaker 1: that this water is going to be king that and

1370
01:19:00,760 --> 01:19:02,920
Speaker 1: this is this is what Garrett touched on. And so

1371
01:19:02,960 --> 01:19:05,599
Speaker 1: we're we're kind of, you know, we're kind of looking

1372
01:19:05,680 --> 01:19:11,040
Speaker 1: at a concept of conflict free lamb and wool um

1373
01:19:11,120 --> 01:19:13,800
Speaker 1: and we're still flushing that out. I mean, there's responsible

1374
01:19:13,840 --> 01:19:18,519
Speaker 1: wool standards that the wool industry uses. Interesting enough, I've

1375
01:19:18,520 --> 01:19:22,160
Speaker 1: read through most of the organizations that have responsible woolf standards.

1376
01:19:22,160 --> 01:19:27,800
Speaker 1: It's more animal husbandry. It's um. You know, it's transportation,

1377
01:19:27,960 --> 01:19:31,400
Speaker 1: it's predator control, whether or not there's some predator control

1378
01:19:31,479 --> 01:19:34,160
Speaker 1: going on in your area. They may think that's non

1379
01:19:34,320 --> 01:19:39,679
Speaker 1: friendly about wildlife. Nothing in there talks about big horn sheets.

1380
01:19:39,720 --> 01:19:43,760
Speaker 1: So it's more animal rights. Bet so we're you know,

1381
01:19:43,800 --> 01:19:46,360
Speaker 1: we're reaching out to some of those more environmental groups

1382
01:19:46,360 --> 01:19:48,000
Speaker 1: to say, hey, if you're if you're gonna, if you're

1383
01:19:48,000 --> 01:19:50,439
Speaker 1: gonna run down this path, you better put big horns

1384
01:19:50,439 --> 01:19:54,360
Speaker 1: in the picture. But as we as we mature, you know,

1385
01:19:54,400 --> 01:19:58,479
Speaker 1: this conflicts free space, um, it too is more of

1386
01:19:58,479 --> 01:20:02,000
Speaker 1: an education program. I mean, world, we will probably never

1387
01:20:02,160 --> 01:20:07,920
Speaker 1: be able to have completely conflict free scenarios in the

1388
01:20:07,960 --> 01:20:12,680
Speaker 1: Western United States unless you put the wool industry and

1389
01:20:12,760 --> 01:20:15,680
Speaker 1: this lamb industry out of business. And that's not our objective.

1390
01:20:15,840 --> 01:20:18,920
Speaker 1: I mean, that's just not our objective. So the key

1391
01:20:19,280 --> 01:20:23,240
Speaker 1: about that question me ask this, does does the woolen

1392
01:20:23,360 --> 01:20:30,120
Speaker 1: lamb industry in the West absolutely rely on public land grazing? Okay,

1393
01:20:32,840 --> 01:20:37,719
Speaker 1: families and the big horns probably rely on private land.

1394
01:20:39,439 --> 01:20:42,920
Speaker 1: Uh no, more big horns are on public land even

1395
01:20:42,960 --> 01:20:49,960
Speaker 1: in the wintertime. Um yeah still yeah, still um so yeah,

1396
01:20:49,960 --> 01:20:52,519
Speaker 1: it's it's a it's sevent of the time they're spending

1397
01:20:52,560 --> 01:20:54,960
Speaker 1: on public lands. So so there is a you know,

1398
01:20:55,000 --> 01:20:57,720
Speaker 1: there is a public land grazing scenario, and and it

1399
01:20:57,840 --> 01:21:00,680
Speaker 1: just it just varies on states on ten it's not

1400
01:21:01,120 --> 01:21:03,679
Speaker 1: it's not really the issue public land grazings out the issue.

1401
01:21:03,720 --> 01:21:08,920
Speaker 1: It's more education of private recreational herds or you know,

1402
01:21:08,920 --> 01:21:13,760
Speaker 1: our producers. UM. Colorado is probably the ground zero for

1403
01:21:13,840 --> 01:21:17,960
Speaker 1: the public land grazing issue with a lot of conflict zones.

1404
01:21:18,280 --> 01:21:22,760
Speaker 1: The BLM and the Fourth Service have risk of contact maps. UM.

1405
01:21:22,880 --> 01:21:25,839
Speaker 1: You can look at a map and it'll show active

1406
01:21:25,880 --> 01:21:32,240
Speaker 1: domestic sheep grazing allotments UM, occupied big horn range UM,

1407
01:21:32,439 --> 01:21:37,200
Speaker 1: and active BLM allotments and then red conflict zones, so

1408
01:21:37,680 --> 01:21:39,880
Speaker 1: they're mapped out. I mean, we you know, there's there's

1409
01:21:39,960 --> 01:21:43,320
Speaker 1: risk of contact analysis. That's that's going on. The bottom

1410
01:21:43,320 --> 01:21:45,960
Speaker 1: line is we pretty much know where the touch points

1411
01:21:45,960 --> 01:21:48,680
Speaker 1: and the hot points are. UM. You know, one of

1412
01:21:48,720 --> 01:21:52,040
Speaker 1: the solutions that we're looking at is what if we

1413
01:21:52,840 --> 01:21:55,800
Speaker 1: what if we took the top ten hot points and

1414
01:21:55,880 --> 01:21:58,840
Speaker 1: to take pick a state, Colorado, what if we took

1415
01:21:58,840 --> 01:22:03,080
Speaker 1: the top ten hot points that man, we've got you know,

1416
01:22:03,320 --> 01:22:06,759
Speaker 1: real critical core bighorn herds in there in that area,

1417
01:22:07,080 --> 01:22:10,840
Speaker 1: and we've got some pretty significant conflict zones. What if

1418
01:22:10,880 --> 01:22:13,120
Speaker 1: we address those first? You know, it's it's eating the

1419
01:22:13,160 --> 01:22:16,080
Speaker 1: elephant one bite at a time. It's it's a huge issue.

1420
01:22:16,120 --> 01:22:19,519
Speaker 1: It's a huge problem. UM. You know, the disease issue

1421
01:22:19,600 --> 01:22:22,439
Speaker 1: is complex. We you know, we don't have all the answers,

1422
01:22:22,840 --> 01:22:26,479
Speaker 1: but what if we could you know, incrementally, um, you know,

1423
01:22:26,600 --> 01:22:29,680
Speaker 1: ten percent at a time start addressing those issues with

1424
01:22:29,800 --> 01:22:31,680
Speaker 1: a variety of tools. Some of them are going to

1425
01:22:31,760 --> 01:22:34,160
Speaker 1: be bottom line moving a producer out of that area.

1426
01:22:34,960 --> 01:22:38,080
Speaker 1: And but the key there is can we find that

1427
01:22:38,160 --> 01:22:41,559
Speaker 1: producer or other grass de grace? Um? You know, are

1428
01:22:41,600 --> 01:22:43,880
Speaker 1: there private land areas? Are there? Are there? You know,

1429
01:22:43,920 --> 01:22:46,040
Speaker 1: are there tools that we haven't used yet? You know,

1430
01:22:46,080 --> 01:22:51,960
Speaker 1: can can the the wild sheep advocacy community? Um, you know,

1431
01:22:51,960 --> 01:22:53,840
Speaker 1: if we're not going to buy you out, can we

1432
01:22:53,920 --> 01:22:58,120
Speaker 1: incentivize you to go onto some lower elevation pivot point,

1433
01:22:58,880 --> 01:23:01,360
Speaker 1: you know, some alpha the field or some other grass

1434
01:23:01,400 --> 01:23:05,040
Speaker 1: field that you can utilize instead of high mountains summertime

1435
01:23:05,080 --> 01:23:08,600
Speaker 1: allotments where big horn sheep are grazing. So, you know,

1436
01:23:08,640 --> 01:23:10,800
Speaker 1: we just gotta we gotta get clever and and Clay

1437
01:23:10,840 --> 01:23:13,839
Speaker 1: said it, and we we've got we've got a program

1438
01:23:13,840 --> 01:23:15,720
Speaker 1: that we call our new narrative. But you know, the

1439
01:23:16,120 --> 01:23:18,880
Speaker 1: premises we've been doing the same thing over and over

1440
01:23:18,920 --> 01:23:21,519
Speaker 1: and over and expecting a different results. Time to change that.

1441
01:23:21,600 --> 01:23:23,479
Speaker 1: You know, we all know that's called insanity if you

1442
01:23:23,520 --> 01:23:26,920
Speaker 1: expect a different results. So we're we're, you know, we're

1443
01:23:26,960 --> 01:23:29,960
Speaker 1: we want to sit down with with willing producers who

1444
01:23:29,960 --> 01:23:32,880
Speaker 1: are progressive and get it and don't deny that there's

1445
01:23:32,880 --> 01:23:36,120
Speaker 1: an issue, and said, I'm saying, hey, you know, you

1446
01:23:36,160 --> 01:23:39,680
Speaker 1: wanna you wanna keep your family in business, and it's

1447
01:23:39,720 --> 01:23:42,840
Speaker 1: a part of the western landscape. We respect that, you know,

1448
01:23:42,920 --> 01:23:46,120
Speaker 1: as a multiple use advocacy organization, which is what wild

1449
01:23:46,120 --> 01:23:49,760
Speaker 1: She Foundation is, we respect that. But let's let's not

1450
01:23:49,840 --> 01:23:51,640
Speaker 1: do the same thing over and over and expect a

1451
01:23:51,680 --> 01:23:55,520
Speaker 1: different result. Let's let's do different things and get different results.

1452
01:23:55,360 --> 01:23:57,960
Speaker 1: And something Grace says a lot to you. You know,

1453
01:23:58,000 --> 01:24:01,200
Speaker 1: there's those that sue and those that do um. And

1454
01:24:01,240 --> 01:24:04,320
Speaker 1: we're kind of like that first group that knocks on

1455
01:24:04,320 --> 01:24:07,880
Speaker 1: the door, and when we get denied, then we go alright, well,

1456
01:24:07,920 --> 01:24:10,120
Speaker 1: when they knock on the door, it's probably not gonna

1457
01:24:10,160 --> 01:24:12,439
Speaker 1: be as pretty, you know. So we're kind of like

1458
01:24:12,520 --> 01:24:15,559
Speaker 1: that just right at the beginning, saying hey, let's let's

1459
01:24:15,600 --> 01:24:17,680
Speaker 1: work things out. And then when we leave if we

1460
01:24:17,720 --> 01:24:21,240
Speaker 1: get denied, you know, and there's there's unfortunate reality that

1461
01:24:21,280 --> 01:24:26,200
Speaker 1: other groups just come in and let me assume them. Yeah,

1462
01:24:26,520 --> 01:24:28,960
Speaker 1: you have a comment. It kind of got a little

1463
01:24:28,960 --> 01:24:31,800
Speaker 1: bit lost in there, but it's I'll just chime in

1464
01:24:31,840 --> 01:24:33,760
Speaker 1: with the tribe's perspective on some of this. And it's

1465
01:24:33,800 --> 01:24:38,280
Speaker 1: really tied to public land grazing. And so the tribes

1466
01:24:38,320 --> 01:24:41,080
Speaker 1: I work for have a treaty reserve right to harvest

1467
01:24:41,080 --> 01:24:46,120
Speaker 1: big horn sheep, and that's a deal. It's the trust responsibility.

1468
01:24:46,160 --> 01:24:49,480
Speaker 1: But the federal government and they are at this time permitting,

1469
01:24:49,800 --> 01:24:53,479
Speaker 1: through a federal action, um the grazing of domestic sheep

1470
01:24:53,560 --> 01:24:58,400
Speaker 1: that adds knowingly adds risk to our populations of sheep

1471
01:24:58,640 --> 01:25:02,400
Speaker 1: big horns. So they we just basically can't accept that

1472
01:25:03,560 --> 01:25:06,080
Speaker 1: because we really can't quantify the risk, so we can

1473
01:25:06,120 --> 01:25:07,680
Speaker 1: want to find a minimum risk. But I want you

1474
01:25:07,680 --> 01:25:11,639
Speaker 1: to say that a a little more clearly. You're you're saying

1475
01:25:12,160 --> 01:25:14,080
Speaker 1: the tribe has a deal with the federal government that

1476
01:25:14,120 --> 01:25:17,439
Speaker 1: they can hunt big horns, but it's reserved in their

1477
01:25:17,520 --> 01:25:21,320
Speaker 1: treaty of eighteen and they're and they're able to argue

1478
01:25:21,920 --> 01:25:26,800
Speaker 1: that the federal government, by giving the grazing allotments to

1479
01:25:26,880 --> 01:25:31,760
Speaker 1: domestic sheep, is hindering their treaty right. If we are,

1480
01:25:32,240 --> 01:25:36,240
Speaker 1: if we are knowingly adding risk to the population viability.

1481
01:25:37,479 --> 01:25:39,320
Speaker 1: And I think we can demonstrate that with the science.

1482
01:25:39,439 --> 01:25:42,479
Speaker 1: It's like coming through a back door to grazing. Grazing

1483
01:25:42,520 --> 01:25:45,880
Speaker 1: domestic sheep on you know, suitable and prime big horn

1484
01:25:45,920 --> 01:25:50,000
Speaker 1: habitat is very problematic for us in that in that

1485
01:25:50,000 --> 01:25:54,200
Speaker 1: that that's just the nature of it. And I mean, yes,

1486
01:25:54,280 --> 01:25:57,040
Speaker 1: we we are, you know, not against public land grazing,

1487
01:25:57,080 --> 01:25:59,320
Speaker 1: but we just need to take a make a hard

1488
01:25:59,560 --> 01:26:01,920
Speaker 1: take a hard look at where it we're suitable to

1489
01:26:01,960 --> 01:26:05,640
Speaker 1: grades domestic sheep and where's not. And we need to

1490
01:26:05,640 --> 01:26:08,000
Speaker 1: protect the sheep we have, but we have to look

1491
01:26:08,040 --> 01:26:10,760
Speaker 1: at how are we going to expand our sheep populations

1492
01:26:11,080 --> 01:26:14,880
Speaker 1: If we have allotments that are stocked with domestic sheep

1493
01:26:15,280 --> 01:26:19,160
Speaker 1: in historic and prime big horn habitat, that could would

1494
01:26:19,200 --> 01:26:22,080
Speaker 1: be suitable. Otherwise we've got to think about that. So

1495
01:26:22,120 --> 01:26:24,800
Speaker 1: do you does does you're or when you're working for

1496
01:26:24,920 --> 01:26:28,280
Speaker 1: the tribe as a biologist, do you wind up interfacing

1497
01:26:28,320 --> 01:26:33,360
Speaker 1: with these guys a wild cheap foundation? Are you in communication? Yeah?

1498
01:26:33,520 --> 01:26:41,439
Speaker 1: What are the conversations that you guys have private? No,

1499
01:26:41,600 --> 01:26:44,080
Speaker 1: it's it's always a good it's always a great discussion

1500
01:26:44,080 --> 01:26:46,000
Speaker 1: because this is a it's a tough it's a tough,

1501
01:26:46,040 --> 01:26:48,280
Speaker 1: tough question. You know, you guys are coming at it

1502
01:26:48,280 --> 01:26:49,800
Speaker 1: from the same side of the thing, or you want

1503
01:26:49,840 --> 01:26:52,280
Speaker 1: what's best for big horns. We do. That's and that's

1504
01:26:52,360 --> 01:26:55,000
Speaker 1: the we just have it. The tribe has a very

1505
01:26:55,040 --> 01:26:58,040
Speaker 1: different worldview of that. You know, I understand that was

1506
01:26:58,080 --> 01:27:02,320
Speaker 1: something that was taken away and it's still a cultural memory.

1507
01:27:02,360 --> 01:27:05,360
Speaker 1: It's there. They want to be fully fully be able

1508
01:27:05,360 --> 01:27:08,960
Speaker 1: to fully exercise that and a couple of tags is

1509
01:27:08,960 --> 01:27:12,320
Speaker 1: is not sufficient. We do coordinate with the States for

1510
01:27:12,320 --> 01:27:16,240
Speaker 1: for on issuing big horn sheep tags, and so that's

1511
01:27:16,240 --> 01:27:18,160
Speaker 1: a little bit of a sore point. So we really

1512
01:27:18,160 --> 01:27:20,080
Speaker 1: need to figure out how we can move the needle

1513
01:27:20,120 --> 01:27:23,519
Speaker 1: and and and get sheep back where they belong. Yes,

1514
01:27:23,600 --> 01:27:26,679
Speaker 1: so how does that work when they're on Indian reservation land?

1515
01:27:26,800 --> 01:27:31,599
Speaker 1: Then they're technically owned by well, we don't have big

1516
01:27:31,640 --> 01:27:34,679
Speaker 1: horn sheep on the reservation who have a relatively small

1517
01:27:34,720 --> 01:27:37,920
Speaker 1: reservation um, but you have hunting rights offside the reservation

1518
01:27:38,640 --> 01:27:44,880
Speaker 1: and about four different herds of sheep. And so we

1519
01:27:45,000 --> 01:27:47,880
Speaker 1: work with the states and and figure out a tag allocation,

1520
01:27:48,080 --> 01:27:51,360
Speaker 1: a lotment, and we issue we hold a drawing just

1521
01:27:51,520 --> 01:27:54,800
Speaker 1: kind of similar to the state drawing and they'd like

1522
01:27:54,840 --> 01:27:57,720
Speaker 1: to see more big horn tags, which means they need

1523
01:27:57,760 --> 01:28:03,919
Speaker 1: more to see more big horns. Yeah, are you guys? Uh?

1524
01:28:04,080 --> 01:28:05,840
Speaker 1: I know you can't really answer this, but it's gonna

1525
01:28:05,840 --> 01:28:09,719
Speaker 1: throw it out there anyway. Optimistic or pessimistic about big horns.

1526
01:28:10,280 --> 01:28:12,040
Speaker 1: I mean a lot of like good work has been done,

1527
01:28:12,120 --> 01:28:15,519
Speaker 1: right man, I mean we were down to we're up

1528
01:28:15,560 --> 01:28:21,880
Speaker 1: to what what's a livable number for you? You know?

1529
01:28:21,960 --> 01:28:24,479
Speaker 1: That's that is. The tough one is is where do

1530
01:28:24,560 --> 01:28:27,080
Speaker 1: we want to go? Um? And I guess the best

1531
01:28:27,120 --> 01:28:29,120
Speaker 1: way for us to express that is we would like

1532
01:28:29,200 --> 01:28:33,240
Speaker 1: to see bighorn sheep everywhere they are now suitable. The

1533
01:28:33,320 --> 01:28:37,599
Speaker 1: problem is, Steve Um, you know, suitable what does that mean?

1534
01:28:37,640 --> 01:28:41,800
Speaker 1: Where they're safe? Um, It's tough to find places to

1535
01:28:41,880 --> 01:28:45,160
Speaker 1: translocate bighorn sheep that they're not going to get into trouble,

1536
01:28:45,800 --> 01:28:48,800
Speaker 1: trouble being just this trouble, the trouble trouble running into

1537
01:28:48,840 --> 01:28:54,240
Speaker 1: a domestic domestic That is that really that is number

1538
01:28:54,520 --> 01:28:57,800
Speaker 1: one in hitting factor on restoration of big horn sheep

1539
01:28:57,920 --> 01:29:01,320
Speaker 1: is is contact with the stick cheap and goats. So

1540
01:29:02,280 --> 01:29:04,960
Speaker 1: fair to say, like if it wasn't for the disease,

1541
01:29:06,000 --> 01:29:08,960
Speaker 1: not blame, blame whoever. But if if the disease for

1542
01:29:09,040 --> 01:29:13,200
Speaker 1: whatever reason didn't exist, is it fair to say that

1543
01:29:13,280 --> 01:29:17,240
Speaker 1: we might have a million big horns or five thousand

1544
01:29:17,240 --> 01:29:19,599
Speaker 1: big horns in the country. Well, we certainly have more

1545
01:29:19,600 --> 01:29:22,799
Speaker 1: than eighty five thousand, and you'd probably easily say, probably

1546
01:29:22,840 --> 01:29:25,240
Speaker 1: double that and maybe triple that. I mean, we've we've

1547
01:29:25,320 --> 01:29:28,800
Speaker 1: quite you know, we've we've had a threefold increase since

1548
01:29:28,840 --> 01:29:31,720
Speaker 1: the late sixties seventies, and I think we could have

1549
01:29:31,720 --> 01:29:36,799
Speaker 1: another threefold increase. But right now, there's it's tough to find.

1550
01:29:37,720 --> 01:29:40,920
Speaker 1: Um is is Scott's saying, you know, thirty five kilometers.

1551
01:29:40,960 --> 01:29:43,720
Speaker 1: I mean, we're sitting in my office and there's a

1552
01:29:43,760 --> 01:29:47,240
Speaker 1: Montana unlimited big horn ram that I saw in winter Range,

1553
01:29:47,280 --> 01:29:51,240
Speaker 1: and I took him thirty miles away. So that's thought

1554
01:29:51,240 --> 01:29:54,599
Speaker 1: thirty kilometers. That's thirty miles away. You got unlimited cheap,

1555
01:29:54,760 --> 01:29:58,599
Speaker 1: I did. That's an unlimited cheap It's a big unlimited

1556
01:29:58,640 --> 01:30:00,439
Speaker 1: cheap and it's a thirteen and a half year old

1557
01:30:00,479 --> 01:30:04,080
Speaker 1: unlimited sheep. Like to kill me. Oh man, you found

1558
01:30:04,160 --> 01:30:07,240
Speaker 1: you you found that same ram. Thirty we found that

1559
01:30:07,320 --> 01:30:11,200
Speaker 1: same ram. You know, a blind hog can find an

1560
01:30:11,200 --> 01:30:17,000
Speaker 1: acorn every once in a while. That's a big, unbelievable Yeah.

1561
01:30:17,000 --> 01:30:19,519
Speaker 1: That that's the exact on my on the front of

1562
01:30:19,520 --> 01:30:22,040
Speaker 1: my door. I have the live picture of that ram

1563
01:30:22,080 --> 01:30:24,800
Speaker 1: I had. I had a photograph in in winter range

1564
01:30:24,800 --> 01:30:28,240
Speaker 1: of that ram on my desktop on my MacBook for

1565
01:30:28,400 --> 01:30:32,719
Speaker 1: nine months. And we found three rams in a different

1566
01:30:32,800 --> 01:30:35,080
Speaker 1: unit and one of them was that guy. One of

1567
01:30:35,120 --> 01:30:38,280
Speaker 1: them was bigger. That's nice thing about sheep as you

1568
01:30:38,280 --> 01:30:40,400
Speaker 1: can really eat because they don't lose, right, they got

1569
01:30:40,439 --> 01:30:42,280
Speaker 1: a horn and they don't lose it. You got you

1570
01:30:43,200 --> 01:30:46,080
Speaker 1: three chunks of character. Now, you know I need to

1571
01:30:46,160 --> 01:30:48,439
Speaker 1: I need to preface in in case you know your

1572
01:30:48,479 --> 01:30:51,400
Speaker 1: audience thinks I'm a great cheap hunter. I had a

1573
01:30:51,400 --> 01:30:53,719
Speaker 1: great sheep hunter with me. I actually had Kevin Hurley

1574
01:30:53,880 --> 01:30:57,640
Speaker 1: are our conservation director now our vice president conservation. He

1575
01:30:57,720 --> 01:30:59,840
Speaker 1: was our He was kind of our camp Jack and

1576
01:30:59,840 --> 01:31:03,519
Speaker 1: I had the as and ahole. Jack Essington Jr. Who

1577
01:31:03,600 --> 01:31:06,280
Speaker 1: I think has sheep blood running through his veins, was

1578
01:31:06,360 --> 01:31:08,960
Speaker 1: with me. So he and I, he and I backpacked

1579
01:31:09,040 --> 01:31:12,880
Speaker 1: up in and we found the ram in Montana. You've

1580
01:31:12,880 --> 01:31:14,839
Speaker 1: got to get out of there in forty eight hours.

1581
01:31:15,000 --> 01:31:18,519
Speaker 1: You've got to present a a full head and cape

1582
01:31:19,479 --> 01:31:21,760
Speaker 1: within forty eight hours to game and fish or fish

1583
01:31:21,760 --> 01:31:24,240
Speaker 1: won parks and we got we got to the biologists

1584
01:31:24,240 --> 01:31:28,439
Speaker 1: and forty eight after a bivouack and a lot of hoping,

1585
01:31:29,040 --> 01:31:32,760
Speaker 1: just just all the things you love. Huh, that's pretty cool.

1586
01:31:32,920 --> 01:31:35,479
Speaker 1: But the point I realized, the point you were making

1587
01:31:35,680 --> 01:31:39,240
Speaker 1: is just the distance is covered. Yeah, that ram, that

1588
01:31:39,360 --> 01:31:42,200
Speaker 1: ram covered thirty miles and that was just standard for

1589
01:31:42,280 --> 01:31:44,400
Speaker 1: that ram, and he didn't do it by going into

1590
01:31:44,439 --> 01:31:48,559
Speaker 1: straight line. Now, the good news is in in that

1591
01:31:48,680 --> 01:31:53,040
Speaker 1: unlimited area, there's there's no more domestic sheet. Yeah. So

1592
01:31:53,240 --> 01:31:55,760
Speaker 1: I mean you know that that and and the that

1593
01:31:55,840 --> 01:31:58,639
Speaker 1: was in the Still Waters Unit five hundred and those

1594
01:31:58,680 --> 01:32:04,400
Speaker 1: sheep are relative lee clean um and and relatively hardy,

1595
01:32:04,439 --> 01:32:08,439
Speaker 1: but they still have some resident pathogens in them, but

1596
01:32:08,479 --> 01:32:12,800
Speaker 1: they're they're they're living with it. The problem is you

1597
01:32:12,840 --> 01:32:15,439
Speaker 1: then bring domestic sheep back in there, and they bring

1598
01:32:15,439 --> 01:32:18,439
Speaker 1: in another strain of of OVI and that's that's the

1599
01:32:19,520 --> 01:32:22,760
Speaker 1: that's the ticker, that's the straw that broke the camel's back,

1600
01:32:22,800 --> 01:32:24,559
Speaker 1: and then you then you get a die off again.

1601
01:32:25,040 --> 01:32:26,760
Speaker 1: So let me hear with this question. Now that we've

1602
01:32:26,840 --> 01:32:29,320
Speaker 1: kind of like prodded around what the future might look

1603
01:32:29,360 --> 01:32:34,240
Speaker 1: like and what's acceptable? Um do we now? Do we

1604
01:32:34,439 --> 01:32:37,160
Speaker 1: right now know that at least it won't get worse?

1605
01:32:39,479 --> 01:32:41,720
Speaker 1: I don't you know? There there are some and I

1606
01:32:41,760 --> 01:32:46,680
Speaker 1: didn't answer your first question. I am going to yea,

1607
01:32:48,000 --> 01:32:51,720
Speaker 1: because there's there's you know, there's there's those within our

1608
01:32:51,720 --> 01:32:57,160
Speaker 1: community to think that status quo is success. Um. While

1609
01:32:57,280 --> 01:32:59,919
Speaker 1: she Foundation, at least from my perspective, is not gonna

1610
01:33:00,040 --> 01:33:04,639
Speaker 1: up status quo as success. Um. We want to come

1611
01:33:04,720 --> 01:33:09,360
Speaker 1: up with some more unique solutions to this problem. And

1612
01:33:09,400 --> 01:33:13,240
Speaker 1: they're they're out there. Um that while I was in Washington,

1613
01:33:13,280 --> 01:33:15,879
Speaker 1: d C. I had had a beer with that domestic

1614
01:33:15,920 --> 01:33:20,479
Speaker 1: sheep producer and in Nevada they took a little different tact.

1615
01:33:21,080 --> 01:33:24,400
Speaker 1: There were a bit basically willing to accept more risk.

1616
01:33:25,280 --> 01:33:30,400
Speaker 1: Some states would be willing to do that, others would not. Scott,

1617
01:33:30,439 --> 01:33:33,760
Speaker 1: I don't think that. So. So here here's a scenario.

1618
01:33:33,800 --> 01:33:38,080
Speaker 1: Are are we willing um? If there if we can,

1619
01:33:38,240 --> 01:33:42,600
Speaker 1: if we can work more on the movie free, Um,

1620
01:33:42,640 --> 01:33:47,559
Speaker 1: if we can work with producers on better practices, is

1621
01:33:47,680 --> 01:33:53,479
Speaker 1: our community willing to let's say, in Montana, UM, put

1622
01:33:54,160 --> 01:33:57,800
Speaker 1: wild you know, translocate wild sheep into areas that typically

1623
01:33:57,840 --> 01:34:02,200
Speaker 1: we would not because we're fearful of that that the

1624
01:34:02,280 --> 01:34:06,400
Speaker 1: disease transmission. And that's a big question we're facing right now.

1625
01:34:06,479 --> 01:34:08,920
Speaker 1: So there's to spend the money on it. Are we

1626
01:34:09,000 --> 01:34:12,080
Speaker 1: willing to spend the money? Are we willing to to

1627
01:34:12,640 --> 01:34:17,599
Speaker 1: not litigate with a producer because that producer didn't object

1628
01:34:17,640 --> 01:34:24,840
Speaker 1: to us moving wild sheep within arguments operation? You're making it,

1629
01:34:25,120 --> 01:34:27,400
Speaker 1: you're making a sort of treat We're just we're yeah,

1630
01:34:27,520 --> 01:34:29,559
Speaker 1: We're we're you know, this is it's it's a it's

1631
01:34:29,600 --> 01:34:33,599
Speaker 1: a it's an organization wide question, it's a community wide question.

1632
01:34:33,640 --> 01:34:35,639
Speaker 1: And there's those that agree with it, those that disagree

1633
01:34:35,680 --> 01:34:39,200
Speaker 1: with it. But would we then set up protocols that

1634
01:34:39,280 --> 01:34:42,439
Speaker 1: you know, we know that if that big horn goes

1635
01:34:42,479 --> 01:34:45,080
Speaker 1: on a walk about, that big horn is not going

1636
01:34:45,160 --> 01:34:48,000
Speaker 1: to make it. Or do we use do we use

1637
01:34:48,080 --> 01:34:52,720
Speaker 1: unlimited areas as a way to separate big horns from

1638
01:34:52,720 --> 01:34:55,080
Speaker 1: domestic sheep? Are there are there areas and you know,

1639
01:34:55,120 --> 01:34:58,640
Speaker 1: this is again a kind of a Montana unique scenario.

1640
01:34:58,880 --> 01:35:05,400
Speaker 1: Can we use almost no go zones for for bighorn sheep?

1641
01:35:05,479 --> 01:35:08,880
Speaker 1: If a bighorn sheep is in that zone, it's unlimited

1642
01:35:08,960 --> 01:35:11,559
Speaker 1: you can take it. You know, we're we're just trying

1643
01:35:11,600 --> 01:35:13,600
Speaker 1: to think out of the box. Try to try to

1644
01:35:13,640 --> 01:35:15,800
Speaker 1: think out of the box again. Let's get let's get

1645
01:35:16,080 --> 01:35:18,400
Speaker 1: get past this doing the same thing and just fighting

1646
01:35:18,439 --> 01:35:21,439
Speaker 1: over this. The good news And I guess why I'm

1647
01:35:21,479 --> 01:35:29,040
Speaker 1: I'm um optimistic and um realistic, but optimistic is um

1648
01:35:29,160 --> 01:35:32,439
Speaker 1: we are learning more and more and more on the

1649
01:35:32,520 --> 01:35:36,440
Speaker 1: disease issue. If we can get the domestic sheep industry

1650
01:35:36,479 --> 01:35:39,439
Speaker 1: to spend as much money as we do on disease research,

1651
01:35:39,560 --> 01:35:42,800
Speaker 1: that will help their industry. Because there's some there's some

1652
01:35:43,000 --> 01:35:45,640
Speaker 1: the data that show that you know, a movie is

1653
01:35:45,680 --> 01:35:49,599
Speaker 1: not good for domestic sheep either. Uh, it's it's endemic

1654
01:35:49,640 --> 01:35:52,160
Speaker 1: to him and it's resident to him. But it's not

1655
01:35:52,240 --> 01:35:54,639
Speaker 1: it's it's you know, the best or did one study

1656
01:35:54,680 --> 01:35:56,360
Speaker 1: I think that he was he was looking at the

1657
01:35:56,920 --> 01:35:59,599
Speaker 1: live weight and it was like a seven percent increase

1658
01:35:59,640 --> 01:36:01,920
Speaker 1: and then it change so you know, probably shouldn't use

1659
01:36:01,920 --> 01:36:04,520
Speaker 1: those numbers, but there was a kind of a significant

1660
01:36:04,600 --> 01:36:09,080
Speaker 1: weight gain, uh change between in a movie free domestic

1661
01:36:09,120 --> 01:36:13,120
Speaker 1: sheep and a movie positive domestic sheep. The movie free

1662
01:36:13,360 --> 01:36:16,439
Speaker 1: gained weight quicker. Well, then there's a market incentive, so

1663
01:36:16,560 --> 01:36:18,960
Speaker 1: maybe maybe there's some you know, something that we can

1664
01:36:19,080 --> 01:36:22,520
Speaker 1: learn there. We're not there yet. It's it's it's unproven,

1665
01:36:22,560 --> 01:36:26,479
Speaker 1: it's not published, it's not peer reviewed. Um, but maybe

1666
01:36:26,520 --> 01:36:29,240
Speaker 1: there's something there. But you know, wouldn't that be cool

1667
01:36:29,280 --> 01:36:32,960
Speaker 1: if we can use market incentives, uh to encourage domestic

1668
01:36:33,000 --> 01:36:37,479
Speaker 1: sheep producers to uh you know, if they can um

1669
01:36:37,760 --> 01:36:41,960
Speaker 1: have a movie free sheep, you know, like like pretty

1670
01:36:42,000 --> 01:36:45,920
Speaker 1: much eliminating small smallpox. Maybe there is some sort of

1671
01:36:46,000 --> 01:36:49,599
Speaker 1: silver bullet where we can vaccinate domestic sheep and they're

1672
01:36:49,640 --> 01:36:52,840
Speaker 1: all a movie free. You know. We've got two bright

1673
01:36:52,920 --> 01:36:55,000
Speaker 1: guys in the rooms, Scott and Clay. You know, I'm

1674
01:36:55,040 --> 01:36:57,719
Speaker 1: just I'm just a management guy and a marketing guy.

1675
01:36:57,760 --> 01:37:00,760
Speaker 1: But um, you know, there's some very people out there

1676
01:37:00,760 --> 01:37:03,280
Speaker 1: that are working on this issue. We've got the wildlife

1677
01:37:03,320 --> 01:37:08,240
Speaker 1: that community working on it. Um. There's not consensus on

1678
01:37:08,240 --> 01:37:10,800
Speaker 1: on what the solution is. But you know what, we

1679
01:37:10,840 --> 01:37:13,600
Speaker 1: haven't cured the common cold yet either, but at some

1680
01:37:13,680 --> 01:37:16,080
Speaker 1: point we might. But you have an interesting point there

1681
01:37:16,080 --> 01:37:21,160
Speaker 1: about producers being incentivized to get ahead of the problem.

1682
01:37:21,280 --> 01:37:24,479
Speaker 1: And ye, honestly, I had an interesting conversation one time

1683
01:37:24,520 --> 01:37:28,960
Speaker 1: with Wyoming's current governor Matt Mead. We're just talking about

1684
01:37:29,240 --> 01:37:32,240
Speaker 1: we're talking about sage grouse in the extraction industry, and

1685
01:37:32,240 --> 01:37:35,840
Speaker 1: he's saying, the many players in the extraction industry have

1686
01:37:35,960 --> 01:37:40,439
Speaker 1: a very long view and they're very sophisticated, and they

1687
01:37:40,520 --> 01:37:42,679
Speaker 1: know that like for them to be on the ground

1688
01:37:43,200 --> 01:37:46,840
Speaker 1: doing good business, they need to head off problems. And

1689
01:37:46,880 --> 01:37:49,040
Speaker 1: a problem that they have a vested interest in heading

1690
01:37:49,040 --> 01:37:52,559
Speaker 1: off is not letting wildlife get into dire situations where

1691
01:37:52,560 --> 01:37:56,439
Speaker 1: you're gonna then invite high level scrutiny into practices, and

1692
01:37:56,479 --> 01:37:58,759
Speaker 1: that what's good for them to operate in their area

1693
01:37:58,920 --> 01:38:01,720
Speaker 1: would be good sage grouse numbers, and that they can

1694
01:38:01,760 --> 01:38:04,519
Speaker 1: at times be very effective players when they have that

1695
01:38:04,640 --> 01:38:08,680
Speaker 1: long view and not heading into conflict, heading into disaster,

1696
01:38:09,200 --> 01:38:13,360
Speaker 1: courting litigation. But you just have But again, you have

1697
01:38:13,439 --> 01:38:15,559
Speaker 1: to be in it for the You have to be

1698
01:38:15,640 --> 01:38:21,080
Speaker 1: looking to the future to ten years profit, not tomorrow's profit. Right.

1699
01:38:21,560 --> 01:38:24,320
Speaker 1: It's a really good point. I'm optimistic. We've made a

1700
01:38:24,320 --> 01:38:28,040
Speaker 1: lot of progress and in wildlife disease and you know,

1701
01:38:28,160 --> 01:38:30,240
Speaker 1: disease in our domestic life stock. If you think some

1702
01:38:30,280 --> 01:38:32,639
Speaker 1: of the things we've gotten out of our domestic animals

1703
01:38:32,640 --> 01:38:35,000
Speaker 1: over the you know, centuries that we've been doing it.

1704
01:38:35,080 --> 01:38:38,080
Speaker 1: I'm I'm optimistically we can. If we put the shoulder

1705
01:38:38,200 --> 01:38:41,040
Speaker 1: this one, I think I think we can overcome it.

1706
01:38:41,120 --> 01:38:43,640
Speaker 1: I hope, I'm really hopeful. I think the fact that

1707
01:38:43,720 --> 01:38:48,400
Speaker 1: you're you know, honestly, Steve, you're here, like that's the

1708
01:38:48,439 --> 01:38:50,559
Speaker 1: reason to be optimistic, because this was something that wasn't

1709
01:38:50,600 --> 01:38:52,800
Speaker 1: really talked about a whole lot. You know, when you

1710
01:38:52,840 --> 01:38:57,000
Speaker 1: get these these guys that haven't incredible influence on the community,

1711
01:38:57,360 --> 01:39:00,000
Speaker 1: you know, and and understanding really what we're up again,

1712
01:39:00,000 --> 01:39:03,800
Speaker 1: inst you know, imagine this issue flipped onto the elk population,

1713
01:39:05,840 --> 01:39:08,800
Speaker 1: a totally different story and why because you know, North

1714
01:39:08,840 --> 01:39:12,560
Speaker 1: American model is a huge success largely because of opportunity

1715
01:39:12,600 --> 01:39:17,200
Speaker 1: to hunt, you know, relatively low opportunity to hunt wild cheap,

1716
01:39:17,960 --> 01:39:20,960
Speaker 1: relatively low funding for conservation. That's where we come in.

1717
01:39:21,280 --> 01:39:23,840
Speaker 1: If it was elk on the same landscape, man, this

1718
01:39:23,840 --> 01:39:27,000
Speaker 1: wouldn't even be a discussion. Could you imagine if twenty

1719
01:39:27,000 --> 01:39:30,360
Speaker 1: bull elk came down into a domestic sheepherd and they

1720
01:39:30,720 --> 01:39:33,000
Speaker 1: mowed down those twenty bull elk just because they came

1721
01:39:33,000 --> 01:39:37,400
Speaker 1: in contact with him, No way, no way, And so

1722
01:39:37,520 --> 01:39:40,720
Speaker 1: the almost what makes them so aspirational, like you know,

1723
01:39:40,760 --> 01:39:42,519
Speaker 1: you know, it's so difficult to get a tag, it's

1724
01:39:42,560 --> 01:39:45,519
Speaker 1: so difficult to get to their habitat. The things that

1725
01:39:45,560 --> 01:39:48,880
Speaker 1: make them so aspirational can also impede them on making

1726
01:39:48,920 --> 01:39:51,760
Speaker 1: them relatable to our everyday lives and understanding what's going on.

1727
01:39:52,040 --> 01:39:54,360
Speaker 1: If we see a die off of fourteen thousand feet,

1728
01:39:54,880 --> 01:39:57,519
Speaker 1: we don't really take heed to it and it's not

1729
01:39:57,600 --> 01:39:59,880
Speaker 1: something that impacts our freezer. We don't think it does.

1730
01:40:00,360 --> 01:40:03,920
Speaker 1: But we talked about wild Cheap being one point five million,

1731
01:40:04,000 --> 01:40:07,040
Speaker 1: you know, almost double what elk are. Did they imagine

1732
01:40:07,080 --> 01:40:09,439
Speaker 1: if they were imagine if it was something that you just,

1733
01:40:09,920 --> 01:40:11,720
Speaker 1: you know, you went down to Bob Wards and bought

1734
01:40:11,760 --> 01:40:15,000
Speaker 1: yourself a tag, and when when sheep hunting, like they

1735
01:40:15,320 --> 01:40:18,160
Speaker 1: a lot more advocates. That's an interesting point that Callahan

1736
01:40:18,200 --> 01:40:21,400
Speaker 1: brought up after being at the sheep Show because he

1737
01:40:21,479 --> 01:40:23,479
Speaker 1: was like, he's kind of marveling at the amount of

1738
01:40:23,520 --> 01:40:27,320
Speaker 1: people that are spending so much time, so much money,

1739
01:40:27,479 --> 01:40:30,400
Speaker 1: so much energy getting behind sheep conservation, and he's like

1740
01:40:30,439 --> 01:40:32,960
Speaker 1: the thing of it is, most of those guys are

1741
01:40:33,080 --> 01:40:38,360
Speaker 1: never gonna draw a sheep tag. They're just doing it

1742
01:40:37,479 --> 01:40:41,760
Speaker 1: because for the idea you know something. They do a

1743
01:40:41,760 --> 01:40:44,360
Speaker 1: lot of these, a lot of the chapters that they do.

1744
01:40:44,439 --> 01:40:46,920
Speaker 1: It's pretty fun. You know, you sit down at the

1745
01:40:46,960 --> 01:40:48,920
Speaker 1: banquet and they say, all right, stand up if you've

1746
01:40:48,920 --> 01:40:51,880
Speaker 1: taken a sheet, and it's like maybe a fifth of

1747
01:40:51,920 --> 01:40:55,639
Speaker 1: the room. But people are gonna spend thousands of dollars

1748
01:40:55,720 --> 01:40:58,880
Speaker 1: every night because they just believe in it. It's just

1749
01:40:59,000 --> 01:41:02,080
Speaker 1: out of their grasp. They believe in it enough. You know.

1750
01:41:02,080 --> 01:41:04,920
Speaker 1: It's just this aspirational thing that we almost can't can't

1751
01:41:04,920 --> 01:41:07,400
Speaker 1: imagine going after. I would say that we have the

1752
01:41:07,439 --> 01:41:12,000
Speaker 1: most altruistic UM membership in our community. I mean, we've

1753
01:41:12,000 --> 01:41:15,519
Speaker 1: got seventy two hundred members. Steve last year we put

1754
01:41:15,560 --> 01:41:19,280
Speaker 1: four point six million dollars into Wild Sheep concerts four

1755
01:41:19,320 --> 01:41:22,400
Speaker 1: point six million, eighteen point one million in the last

1756
01:41:22,439 --> 01:41:28,679
Speaker 1: four years with a little small sixty eight to seventy

1757
01:41:28,680 --> 01:41:34,280
Speaker 1: two hundred member organization. UM Clay worked on a project

1758
01:41:34,600 --> 01:41:36,400
Speaker 1: UM a couple of years ago and we were we

1759
01:41:36,400 --> 01:41:38,479
Speaker 1: were looking at it and it's kind of switching gears

1760
01:41:38,479 --> 01:41:40,519
Speaker 1: a little bit, but it looks at the auction tags

1761
01:41:41,280 --> 01:41:45,200
Speaker 1: UM and those are a little controversial. We spent tons

1762
01:41:45,240 --> 01:41:47,240
Speaker 1: of time giving both sides of that those are a

1763
01:41:47,240 --> 01:41:52,360
Speaker 1: little both sides of that argument with Crystal clar Look,

1764
01:41:52,560 --> 01:41:54,120
Speaker 1: let me, let me, let me give you, let me

1765
01:41:54,160 --> 01:41:57,439
Speaker 1: give you some facts when it comes to wild Sheep concert,

1766
01:41:57,520 --> 01:42:00,920
Speaker 1: please please seventy four per Can I first explain what

1767
01:42:00,920 --> 01:42:04,040
Speaker 1: you're talking about? All right, We've talked about a thousand times.

1768
01:42:04,040 --> 01:42:07,519
Speaker 1: People always ask us about this, But um, when you

1769
01:42:07,600 --> 01:42:12,160
Speaker 1: have I'm speaking for the listeners right now, when you

1770
01:42:12,240 --> 01:42:15,000
Speaker 1: have a resource that isn't large enough to meet the

1771
01:42:15,040 --> 01:42:17,040
Speaker 1: demand on the resource, you have to find a way.

1772
01:42:17,040 --> 01:42:18,640
Speaker 1: And I'm talking about a wild game resource. You have

1773
01:42:18,720 --> 01:42:20,840
Speaker 1: to find a way to allocate opportunity, right. And so

1774
01:42:20,960 --> 01:42:24,080
Speaker 1: if you live in the great state of Michigan and

1775
01:42:24,160 --> 01:42:27,200
Speaker 1: Wisconsin and you want to go deer hunting, there's enough

1776
01:42:27,240 --> 01:42:29,479
Speaker 1: deer to go around. Everybody goes down, you buy a

1777
01:42:29,479 --> 01:42:32,000
Speaker 1: deer tag, everybody gets to go with a lot of

1778
01:42:32,000 --> 01:42:35,080
Speaker 1: wildlife species. There's just the numbers aren't there, And so

1779
01:42:35,160 --> 01:42:37,320
Speaker 1: everyone throws their name in the hat and it's meant

1780
01:42:37,439 --> 01:42:39,680
Speaker 1: you know that, shouldn't they meant to be? But traditionally

1781
01:42:39,720 --> 01:42:45,880
Speaker 1: those opportunities are allocated democratically. An exception to that case

1782
01:42:46,160 --> 01:42:50,320
Speaker 1: would be what you're gonna now explain, Um, which would

1783
01:42:50,360 --> 01:42:55,800
Speaker 1: be when they take tags, usually for very coveted species

1784
01:42:55,880 --> 01:42:59,080
Speaker 1: or coveted hunting areas, and they take tags and sell

1785
01:42:59,080 --> 01:43:02,960
Speaker 1: them to the highest bit or. And here's the rub.

1786
01:43:03,560 --> 01:43:05,720
Speaker 1: Here's the thing you got paid attention to. And it's

1787
01:43:05,880 --> 01:43:08,599
Speaker 1: usually structured and subtle such a way that like nine

1788
01:43:09,439 --> 01:43:15,080
Speaker 1: of the money goes into the ground for restoration work,

1789
01:43:15,920 --> 01:43:18,559
Speaker 1: so it's not lying in someone's pocket. And this is

1790
01:43:18,640 --> 01:43:22,719
Speaker 1: tightly this is carefully watched. This is a carefully watched

1791
01:43:22,760 --> 01:43:28,200
Speaker 1: flow of money. So at that's that's a that's a

1792
01:43:28,240 --> 01:43:31,800
Speaker 1: great it's a great setup. And and if if I

1793
01:43:31,800 --> 01:43:35,160
Speaker 1: could expand on it, you know, I um Shae Mahoney

1794
01:43:35,240 --> 01:43:37,439
Speaker 1: is a great friend, and he and I give talks

1795
01:43:37,479 --> 01:43:40,479
Speaker 1: around you know the world, and he was listening to

1796
01:43:41,000 --> 01:43:43,360
Speaker 1: some of my talks on this this tag thing that

1797
01:43:43,360 --> 01:43:45,479
Speaker 1: we're going to talk about. The special permits attacks you

1798
01:43:45,520 --> 01:43:48,519
Speaker 1: know where exactly what you said, where you know, one

1799
01:43:48,960 --> 01:43:54,519
Speaker 1: or two or five um special licenses are taken from

1800
01:43:54,520 --> 01:43:58,479
Speaker 1: the pool of available tags and sold to the high bidder.

1801
01:43:58,479 --> 01:44:00,720
Speaker 1: And I used to call that a bad stardization of

1802
01:44:00,800 --> 01:44:03,640
Speaker 1: the North American conservation models used to I support it.

1803
01:44:03,680 --> 01:44:06,440
Speaker 1: I never went that far, but I called it a bastardization.

1804
01:44:06,479 --> 01:44:09,760
Speaker 1: And I've I had Shane Shane Mahoney down in my

1805
01:44:09,800 --> 01:44:12,320
Speaker 1: drift boat. We're floating down the Yellowstone River and and

1806
01:44:12,360 --> 01:44:15,599
Speaker 1: we're you know, probably enjoying a beer in Shane's case

1807
01:44:15,640 --> 01:44:19,719
Speaker 1: againness and he was just having a good time. He goes, great,

1808
01:44:19,760 --> 01:44:21,479
Speaker 1: I want to I want to can you say it

1809
01:44:21,680 --> 01:44:24,920
Speaker 1: the way you can use his accent I'm trying to

1810
01:44:24,920 --> 01:44:29,760
Speaker 1: get I'm trying to get the voice of God, Mr

1811
01:44:29,920 --> 01:44:35,599
Speaker 1: Shane Mahoney, Great, absolute fabulous conservation. But you know, he says,

1812
01:44:35,640 --> 01:44:38,479
Speaker 1: you know, Grey, you know, I've I've listened to say

1813
01:44:38,479 --> 01:44:40,280
Speaker 1: this a number of times in a number of places

1814
01:44:40,360 --> 01:44:43,479
Speaker 1: that you know this this this special permit and tag.

1815
01:44:43,600 --> 01:44:45,200
Speaker 1: And it could also be a raffle tag and we'll

1816
01:44:45,200 --> 01:44:47,479
Speaker 1: get into that. But the special permit and tag is

1817
01:44:47,520 --> 01:44:50,160
Speaker 1: a bastardization of the North American model. He's saying to you,

1818
01:44:50,240 --> 01:44:53,000
Speaker 1: I've heard you've heard me say this, and I talk

1819
01:44:53,120 --> 01:44:55,800
Speaker 1: I you, you know, and I even use capitalism socialism

1820
01:44:55,840 --> 01:44:59,680
Speaker 1: kind of our our our standard system is an egalitarian

1821
01:44:59,720 --> 01:45:02,200
Speaker 1: pro grahmmed is and you know, Steve, as you put it,

1822
01:45:02,200 --> 01:45:05,040
Speaker 1: I mean, anyone can go down and get attack um

1823
01:45:05,200 --> 01:45:07,240
Speaker 1: when it comes to some of the coveted ones where

1824
01:45:07,240 --> 01:45:09,040
Speaker 1: it's a whether it's a big horn sheep or a

1825
01:45:09,040 --> 01:45:12,439
Speaker 1: stone sheep, or a desert sheep, or or a rocky

1826
01:45:12,479 --> 01:45:16,160
Speaker 1: mountain help in a particular unit in Utah, um you

1827
01:45:16,200 --> 01:45:18,880
Speaker 1: can auction off those tags. Two. So now that's that's

1828
01:45:18,920 --> 01:45:23,200
Speaker 1: not egalitariance of color. And I apply for a bighorn

1829
01:45:23,280 --> 01:45:26,240
Speaker 1: sheep tag every year in six or seven states, good

1830
01:45:26,240 --> 01:45:29,280
Speaker 1: for you, and in this state in particular, for thirteen

1831
01:45:29,439 --> 01:45:31,600
Speaker 1: or fifteen or sixteen years in a row, and I

1832
01:45:31,640 --> 01:45:33,479
Speaker 1: haven't gotten one. Just to give a sense of like

1833
01:45:33,520 --> 01:45:35,719
Speaker 1: what we're talking about, we're talking about the slim pickings.

1834
01:45:35,800 --> 01:45:38,519
Speaker 1: You got slim pickings on tag. You've got guys in

1835
01:45:38,600 --> 01:45:41,880
Speaker 1: Montana that have applied for thirty five years and have

1836
01:45:42,040 --> 01:45:46,080
Speaker 1: not drawn attacks. So you know, you're either lucky um

1837
01:45:46,200 --> 01:45:48,559
Speaker 1: or you go into a jurisdiction like Montana that has

1838
01:45:48,560 --> 01:45:50,360
Speaker 1: the unlimited units. But you know, we had a three

1839
01:45:50,640 --> 01:45:53,639
Speaker 1: three to four per cent suc sex. But so so

1840
01:45:53,680 --> 01:45:56,000
Speaker 1: we're on the river and Shane goes, you know, Grey,

1841
01:45:56,000 --> 01:45:58,120
Speaker 1: and he is you know, he and Valor's guys, so

1842
01:45:58,240 --> 01:46:01,599
Speaker 1: the probably the foremost authority on the North American model.

1843
01:46:01,640 --> 01:46:04,800
Speaker 1: He says, you're actually wrong. It's not a bastardization of

1844
01:46:04,880 --> 01:46:08,120
Speaker 1: the North American model. The North North American model also

1845
01:46:08,240 --> 01:46:11,160
Speaker 1: is one of its seven pillars gives the state the

1846
01:46:11,200 --> 01:46:16,400
Speaker 1: opportunity to decide how it funds wildlife conservation in that state.

1847
01:46:17,479 --> 01:46:21,240
Speaker 1: And so a state that decides, like Montana, that we

1848
01:46:21,320 --> 01:46:24,400
Speaker 1: will take out of the pool of big worn sheep,

1849
01:46:24,400 --> 01:46:28,479
Speaker 1: permits one auction tag and one raffle tag. And the

1850
01:46:28,560 --> 01:46:31,840
Speaker 1: key there is one goes to the you know, the

1851
01:46:32,640 --> 01:46:36,080
Speaker 1: high bidder and the very affluent one out of a

1852
01:46:36,080 --> 01:46:38,080
Speaker 1: couple of hundreds. But yeah, yeah, I think we have

1853
01:46:38,080 --> 01:46:40,760
Speaker 1: a hundred fifty tags or so, so you know, one

1854
01:46:40,840 --> 01:46:43,320
Speaker 1: goes as a as an auction tag, and one also

1855
01:46:43,439 --> 01:46:45,839
Speaker 1: is a raffle tag that you know, so us regular

1856
01:46:45,880 --> 01:46:48,400
Speaker 1: folks can you know, buy a raffle ticket and potentially

1857
01:46:48,439 --> 01:46:51,840
Speaker 1: have a little better odds than you know than the

1858
01:46:52,160 --> 01:46:54,000
Speaker 1: you know, you've been in for thirteen fourteen and some

1859
01:46:54,080 --> 01:46:57,080
Speaker 1: people thirty five years. So here's the interesting thing when

1860
01:46:57,120 --> 01:47:00,599
Speaker 1: it comes to wild sheep and and Clay a lead

1861
01:47:00,640 --> 01:47:04,280
Speaker 1: this study with a with an intern seventy four percent

1862
01:47:04,680 --> 01:47:09,320
Speaker 1: and I'll say that again, seventy four percent of WAFFWA

1863
01:47:09,439 --> 01:47:13,440
Speaker 1: Western Association of Fish and Wildlife agencies the Western agencies

1864
01:47:13,600 --> 01:47:17,640
Speaker 1: in United States and Canada UH seventy four percent of

1865
01:47:17,720 --> 01:47:22,479
Speaker 1: their wild sheep conservation agency dollars comes from either an

1866
01:47:22,479 --> 01:47:27,840
Speaker 1: auction or a raffle tag seventy percent. Now, so we

1867
01:47:27,880 --> 01:47:32,080
Speaker 1: will your peeling like let's say two tags out of

1868
01:47:32,080 --> 01:47:37,839
Speaker 1: a hundred plus tags and those two provide seventy four percent.

1869
01:47:37,960 --> 01:47:42,920
Speaker 1: In a state like Arizona, it's about nine. And the

1870
01:47:42,960 --> 01:47:46,479
Speaker 1: other thing that was interesting in this in this research,

1871
01:47:46,560 --> 01:47:50,400
Speaker 1: and we we used waff with data UM forty percent

1872
01:47:51,560 --> 01:47:58,040
Speaker 1: of all WAFFWA wild sheep conservation agency dollars comes from

1873
01:47:58,080 --> 01:48:02,240
Speaker 1: one organization and that's the wild Foundation. Really yeah, so

1874
01:48:02,840 --> 01:48:05,680
Speaker 1: you know, we have a we have a very relatively

1875
01:48:05,800 --> 01:48:11,320
Speaker 1: small footprint when it comes to membership at we cast

1876
01:48:11,360 --> 01:48:15,280
Speaker 1: a very very long shadow when it comes to conservation

1877
01:48:15,320 --> 01:48:18,840
Speaker 1: and putting money on the ground. Um. But you know,

1878
01:48:18,920 --> 01:48:22,200
Speaker 1: there's their sensibilities. Wyoming gives five tags away on on

1879
01:48:22,360 --> 01:48:26,400
Speaker 1: auction um if if while she Foundation went to Montana Fish,

1880
01:48:26,439 --> 01:48:29,080
Speaker 1: Wildlife and Parks in the commission and advocated for another

1881
01:48:29,200 --> 01:48:33,280
Speaker 1: auction tag, our building would be burned down. So you know,

1882
01:48:33,360 --> 01:48:36,559
Speaker 1: it is controversial, it's but you know, check this out. Man.

1883
01:48:36,600 --> 01:48:39,000
Speaker 1: I put it to my brother. Another guy put it

1884
01:48:39,000 --> 01:48:42,320
Speaker 1: to my brother in a conversation, and my brother like,

1885
01:48:42,320 --> 01:48:44,240
Speaker 1: there's nothing he likes more than just like wrestling with

1886
01:48:44,280 --> 01:48:47,160
Speaker 1: ethical questions. So they put the governor thing to him,

1887
01:48:47,200 --> 01:48:52,680
Speaker 1: and he was saying that he feels on auction tags.

1888
01:48:53,200 --> 01:48:56,080
Speaker 1: He feels it in balancing the morality of it or

1889
01:48:56,120 --> 01:48:58,240
Speaker 1: in balancing the ethics of it. You need to look

1890
01:48:58,400 --> 01:49:01,960
Speaker 1: at what are the impacts of the auction tag. Because

1891
01:49:02,720 --> 01:49:05,640
Speaker 1: the auction tag is going to remove an animal from

1892
01:49:05,680 --> 01:49:11,080
Speaker 1: the landscape, but the money, if well spent, is probably

1893
01:49:11,120 --> 01:49:14,880
Speaker 1: going to add a higher number of tags to the

1894
01:49:15,000 --> 01:49:20,000
Speaker 1: general pool by the habitat work and relocation work and

1895
01:49:20,000 --> 01:49:22,759
Speaker 1: putting more sheep on the ground, so that that money

1896
01:49:22,840 --> 01:49:25,240
Speaker 1: might be pulling us sheep out of the pool and

1897
01:49:25,320 --> 01:49:29,439
Speaker 1: returning four or returning five or returning ten. So there

1898
01:49:29,439 --> 01:49:34,160
Speaker 1: are actually possibly more tags made available thanks to the

1899
01:49:34,200 --> 01:49:38,240
Speaker 1: auction tag than in spite of the auction tag. He

1900
01:49:38,800 --> 01:49:41,479
Speaker 1: nailed it. You know, we were talking about that unlimited ram.

1901
01:49:41,560 --> 01:49:44,599
Speaker 1: I can assure you, uh and and and we were

1902
01:49:44,600 --> 01:49:47,639
Speaker 1: looking at some data back in we've changed, we've changed

1903
01:49:47,680 --> 01:49:50,120
Speaker 1: the dynamic in Montana now and now there's an application

1904
01:49:50,200 --> 01:49:53,519
Speaker 1: fee of fifty bucks. But um, the amount of sheep

1905
01:49:53,600 --> 01:49:56,800
Speaker 1: revenue coming into Montana, Fish, Wildlife and Parks on on

1906
01:49:56,920 --> 01:50:01,439
Speaker 1: the unlimited tags and the limited tag eggs was less

1907
01:50:01,439 --> 01:50:05,200
Speaker 1: than two hundred thousand dollars. It was actually a lot

1908
01:50:05,240 --> 01:50:08,360
Speaker 1: closer to a hundred thousand dollars. Around a hundred forty

1909
01:50:08,400 --> 01:50:11,080
Speaker 1: thousand dollars. You can't pay a biologist in a truck

1910
01:50:11,400 --> 01:50:14,280
Speaker 1: and you know, uniforms and like on a hundred hundred

1911
01:50:14,320 --> 01:50:16,800
Speaker 1: and forty thousand dollars. You know that same year we

1912
01:50:16,880 --> 01:50:20,439
Speaker 1: sold the Montana tag for three hundred and fifteen thousand dollars.

1913
01:50:20,479 --> 01:50:23,360
Speaker 1: We've sold that tag as high as four hundred and

1914
01:50:23,360 --> 01:50:27,479
Speaker 1: eighty thousand dollars. And you pointed out earlier nine of

1915
01:50:27,600 --> 01:50:31,480
Speaker 1: that money goes right back into fish, wildlife and parks

1916
01:50:31,520 --> 01:50:35,880
Speaker 1: in a dedicated sheep account. So we retained ten percent. Well,

1917
01:50:35,920 --> 01:50:37,519
Speaker 1: we spend a hell of a lot more than ten

1918
01:50:37,600 --> 01:50:41,120
Speaker 1: percent back in Montana. So one one percent of those

1919
01:50:41,160 --> 01:50:43,800
Speaker 1: dollars go right back onto the ground into Wild Chief

1920
01:50:43,840 --> 01:50:49,240
Speaker 1: Conservation in Arizona. It's one Wild Chief Foundation sells that tag.

1921
01:50:49,960 --> 01:50:52,360
Speaker 1: We spend a million dollars to put on a show

1922
01:50:52,400 --> 01:50:55,000
Speaker 1: to get somebody crazy enough to spend three hundred thousand

1923
01:50:55,000 --> 01:50:57,840
Speaker 1: dollars in a desert big horn sheep tag, and one

1924
01:50:58,160 --> 01:51:01,200
Speaker 1: hundred percent of that dollars is back to Arizona Game

1925
01:51:01,200 --> 01:51:05,320
Speaker 1: and Fish into a dedicated account to restore bighorn sheep

1926
01:51:05,320 --> 01:51:07,840
Speaker 1: and conserve bighorn sheep, and that that probably includes some

1927
01:51:07,960 --> 01:51:12,559
Speaker 1: disease spending. Absolutely, I'm like tipping more and more every year,

1928
01:51:13,200 --> 01:51:15,400
Speaker 1: So I tipped more and more in the direction of Like,

1929
01:51:15,800 --> 01:51:18,160
Speaker 1: it's just like one of those It's one of those

1930
01:51:18,160 --> 01:51:19,600
Speaker 1: things that you want to be like, yeah, man, I

1931
01:51:19,600 --> 01:51:23,360
Speaker 1: see where you're coming from. I'm not digging and you might.

1932
01:51:23,360 --> 01:51:29,960
Speaker 1: I'm not even asking you to esthetically like the auction tags, Like,

1933
01:51:30,000 --> 01:51:32,120
Speaker 1: I'm not asking you to like at the aesthetics of it,

1934
01:51:32,200 --> 01:51:35,360
Speaker 1: but it's almost like you cannot argue with the efficacy,

1935
01:51:35,560 --> 01:51:38,640
Speaker 1: you know. And I getting back to that unlimited I

1936
01:51:38,760 --> 01:51:42,320
Speaker 1: know that I had as a regular guy, you know,

1937
01:51:42,360 --> 01:51:46,600
Speaker 1: a nonprofit employee. As a regular guy, I had the

1938
01:51:46,640 --> 01:51:50,760
Speaker 1: opportunity to buy in effect a bighorn sheep. I was

1939
01:51:50,800 --> 01:51:53,680
Speaker 1: living in or in in Woman at the time. I

1940
01:51:53,720 --> 01:51:56,920
Speaker 1: was able to buy a bighorn sheep tag in Montana

1941
01:51:57,040 --> 01:52:02,120
Speaker 1: for seven and fifty bucks. Back then, as a Wyoming

1942
01:52:02,160 --> 01:52:06,400
Speaker 1: resident and hunt um big horn sheep in Montana. And

1943
01:52:06,479 --> 01:52:10,000
Speaker 1: I was able to do that only because some other

1944
01:52:10,280 --> 01:52:14,360
Speaker 1: crazy guy gal whatever had the wherewithal to spend three

1945
01:52:14,800 --> 01:52:18,800
Speaker 1: fifty dollars on one tag, and that money went to

1946
01:52:18,920 --> 01:52:22,680
Speaker 1: ensure that I had an opportunity to hunt in Montana.

1947
01:52:22,760 --> 01:52:25,120
Speaker 1: So I I look at it. You know, it's it.

1948
01:52:25,120 --> 01:52:27,320
Speaker 1: It can be unseeming. I look at a little different.

1949
01:52:27,600 --> 01:52:30,400
Speaker 1: I look at it as I am grateful that there

1950
01:52:30,439 --> 01:52:34,320
Speaker 1: are people out there that could give money to their

1951
01:52:34,360 --> 01:52:38,679
Speaker 1: alma mater. Uh, they could give money to cancer research,

1952
01:52:38,800 --> 01:52:42,439
Speaker 1: and they do. But there are those that have the

1953
01:52:42,479 --> 01:52:45,920
Speaker 1: wherewithal and they give it to wild sheep restoration and conservation.

1954
01:52:46,040 --> 01:52:51,439
Speaker 1: So um, instead of vilifying those folks, But we can't

1955
01:52:51,479 --> 01:52:54,439
Speaker 1: measure their motivation. Oh you you know, I mean you

1956
01:52:54,479 --> 01:52:59,880
Speaker 1: can't eat horns. I don't, you know. I think the

1957
01:53:00,080 --> 01:53:02,760
Speaker 1: way that I've I've said, you know a lot of

1958
01:53:02,840 --> 01:53:05,360
Speaker 1: us like to say hunting is conservation is a term

1959
01:53:05,360 --> 01:53:07,920
Speaker 1: We use a lot, you know, And I don't think

1960
01:53:07,920 --> 01:53:12,160
Speaker 1: that there's any better depiction of that, honestly than those

1961
01:53:12,160 --> 01:53:14,240
Speaker 1: auctions tag. When you take one tag out of the

1962
01:53:14,240 --> 01:53:19,640
Speaker 1: whole pool that funds seventy whatever percent of that conservation

1963
01:53:19,760 --> 01:53:25,800
Speaker 1: of that species, you know hunting, right, there is conservation. Yeah,

1964
01:53:26,000 --> 01:53:31,040
Speaker 1: the numbers are, Yeah, the numbers are. You're struggling with this, No,

1965
01:53:31,040 --> 01:53:32,640
Speaker 1: I'm not because yeah, because here's the thing. Here's what

1966
01:53:32,640 --> 01:53:35,160
Speaker 1: I like to do. I like take too, I like

1967
01:53:35,320 --> 01:53:37,439
Speaker 1: in wrestling with an idea, I like to take it

1968
01:53:37,479 --> 01:53:40,840
Speaker 1: to the extreme because one might come in and say, well, wow, man,

1969
01:53:41,080 --> 01:53:43,360
Speaker 1: that's a lot of money. Let's take all the tags

1970
01:53:43,360 --> 01:53:45,599
Speaker 1: and auction them all off, because that would be a

1971
01:53:45,600 --> 01:53:49,040
Speaker 1: hell of a lot of money. At which point, now

1972
01:53:49,120 --> 01:53:51,920
Speaker 1: I feel as though you have right. So we all

1973
01:53:51,960 --> 01:53:55,799
Speaker 1: agree that there's like that's that's not a tenable solution.

1974
01:53:56,320 --> 01:54:00,760
Speaker 1: So we all agree that somewhere in here there's a line, right,

1975
01:54:01,000 --> 01:54:04,120
Speaker 1: and we're like trying to like identify the line. Now

1976
01:54:04,160 --> 01:54:06,720
Speaker 1: to have a state do one that's pretty damn conservative.

1977
01:54:07,960 --> 01:54:10,040
Speaker 1: Do you guys have numbers on how much the raffle

1978
01:54:10,439 --> 01:54:13,720
Speaker 1: tag brings in? Um, I don't know if Garrett you

1979
01:54:13,760 --> 01:54:17,760
Speaker 1: have that, you know, Montana, It's it's typically a little

1980
01:54:17,760 --> 01:54:21,439
Speaker 1: shot of two dollars. Oh yeah, but it's significant. I

1981
01:54:21,439 --> 01:54:25,560
Speaker 1: mean it's significant. And that's you know that the you know,

1982
01:54:25,600 --> 01:54:28,559
Speaker 1: the auction tag is the is the main player. But

1983
01:54:28,640 --> 01:54:31,760
Speaker 1: you know, I probably you know hip pocket would be

1984
01:54:31,880 --> 01:54:35,680
Speaker 1: uh yeah, I wouldn't want to say a two thirds

1985
01:54:35,760 --> 01:54:39,600
Speaker 1: one third, but you know, maybe sixty of the money

1986
01:54:39,640 --> 01:54:42,400
Speaker 1: comes from the auction tag from a raffle. Have you

1987
01:54:42,440 --> 01:54:46,040
Speaker 1: guys ever calculated this out? Um, that's pretty good. I

1988
01:54:46,040 --> 01:54:49,280
Speaker 1: think my brother ran the numbers out. I can't remember

1989
01:54:49,880 --> 01:54:53,480
Speaker 1: if he was confident in it is. If the raffle

1990
01:54:53,560 --> 01:54:56,280
Speaker 1: tickets are five bucks, how much do you need to

1991
01:54:56,280 --> 01:54:59,840
Speaker 1: spend on raffles before you're doing better than just apply

1992
01:55:00,120 --> 01:55:03,040
Speaker 1: for the tag? Yeah, I just kind of think it's

1993
01:55:03,040 --> 01:55:06,520
Speaker 1: a surprisingly lower number, where like your odds of getting

1994
01:55:06,560 --> 01:55:12,320
Speaker 1: the tag increased bucks or something like that. No, the raffles,

1995
01:55:12,320 --> 01:55:16,320
Speaker 1: you know anyway, you know, bunch are our our community

1996
01:55:16,320 --> 01:55:19,360
Speaker 1: of chapters and affiliates. I mean that's you know, a

1997
01:55:19,480 --> 01:55:21,840
Speaker 1: raffle is so much better odds than any of any

1998
01:55:21,840 --> 01:55:23,680
Speaker 1: of the state or provincial if if there's an L

1999
01:55:23,760 --> 01:55:25,600
Speaker 1: A H up in the province, but you know, any

2000
01:55:25,600 --> 01:55:27,760
Speaker 1: of the L A H drawings, A raffles much better

2001
01:55:27,800 --> 01:55:30,960
Speaker 1: odds they're just throwing into the state. You're you're better

2002
01:55:30,960 --> 01:55:33,320
Speaker 1: off getting it, you know, if if you're an aspirational

2003
01:55:33,360 --> 01:55:36,839
Speaker 1: sheep hunter and we all are and you know, get

2004
01:55:36,920 --> 01:55:39,600
Speaker 1: into these raffles or you know, we've got you know,

2005
01:55:39,640 --> 01:55:42,960
Speaker 1: the gratuitous plug. But we've got less than one club,

2006
01:55:43,640 --> 01:55:46,600
Speaker 1: which is an organization or club if you will, within

2007
01:55:46,680 --> 01:55:49,880
Speaker 1: Wild she Foundation where for five bucks if you have

2008
01:55:49,960 --> 01:55:54,120
Speaker 1: not taken a Wild Sheep Ram, we're twenty five bucks.

2009
01:55:54,120 --> 01:55:57,160
Speaker 1: You're entered into a drawing for three doll sheep hunts

2010
01:55:57,160 --> 01:55:59,720
Speaker 1: that we give away at our convention. And we've got

2011
01:56:00,720 --> 01:56:04,280
Speaker 1: nine hundred or so, twelve hundred or so in that

2012
01:56:04,440 --> 01:56:08,720
Speaker 1: in that club within Wild Sheep Foundation. Um, you've got

2013
01:56:08,800 --> 01:56:12,840
Speaker 1: three chances. Uh, we we spice it a little bit, Steve,

2014
01:56:12,920 --> 01:56:15,360
Speaker 1: because the first drawn you don't have to be present,

2015
01:56:16,240 --> 01:56:18,600
Speaker 1: the second drawn you've got to be president, and the

2016
01:56:18,640 --> 01:56:21,600
Speaker 1: third you got to be present to win. UM at

2017
01:56:21,640 --> 01:56:25,760
Speaker 1: this last lesson one club reception and the receptions maybe

2018
01:56:25,800 --> 01:56:29,320
Speaker 1: a um one of our colleagues drew one of those. Yes,

2019
01:56:29,720 --> 01:56:32,680
Speaker 1: yeah he did, and and but that receptions maybe not

2020
01:56:32,720 --> 01:56:35,360
Speaker 1: the it's it's basically a beer fest. We went through

2021
01:56:35,400 --> 01:56:37,920
Speaker 1: twenty five kegs of beer in an hour and a

2022
01:56:38,000 --> 01:56:42,960
Speaker 1: half for three sheep takes. You bet, So you know,

2023
01:56:43,040 --> 01:56:47,000
Speaker 1: we maybe maybe our community is kind of a drinking

2024
01:56:47,000 --> 01:56:49,640
Speaker 1: club with a sheep hunting problem. But it's really cool.

2025
01:56:49,640 --> 01:56:52,520
Speaker 1: I mean, the energy in that room is absolutely electric.

2026
01:56:53,040 --> 01:56:56,480
Speaker 1: And you know when someone that has aspired to be

2027
01:56:56,680 --> 01:56:58,800
Speaker 1: kicked out of the club, and that's what we say, Hey,

2028
01:56:58,800 --> 01:57:01,560
Speaker 1: you join the lesson one club hoping to be kicked out,

2029
01:57:01,800 --> 01:57:04,200
Speaker 1: and you're kicked out when you take a ram um.

2030
01:57:04,240 --> 01:57:07,880
Speaker 1: You know, we're giving away opportunities for for relatively low

2031
01:57:07,960 --> 01:57:13,200
Speaker 1: dollars um and trying to augment the state and provincial

2032
01:57:13,320 --> 01:57:16,600
Speaker 1: drawings that that are pretty low. Ots. My buddies, I've

2033
01:57:16,640 --> 01:57:19,240
Speaker 1: been saying how after many years, I'm saying how I'm

2034
01:57:19,280 --> 01:57:23,720
Speaker 1: like taking a break from shot show and I say

2035
01:57:23,800 --> 01:57:26,080
Speaker 1: to my buddies and I'm gonna start I'm gonna spend

2036
01:57:26,120 --> 01:57:27,800
Speaker 1: a couple of years at a couple of other shows.

2037
01:57:28,320 --> 01:57:30,440
Speaker 1: And I've brought it up with multiple of my friends

2038
01:57:30,440 --> 01:57:34,080
Speaker 1: in the in the hunting industry, and they universally are like, dude,

2039
01:57:34,160 --> 01:57:37,200
Speaker 1: cheap show. It's fun, it's a family, you know, it's

2040
01:57:37,240 --> 01:57:40,400
Speaker 1: a it's a um. You know. We talked about the altruism,

2041
01:57:40,480 --> 01:57:43,760
Speaker 1: but what what's cool? And I think there's a little

2042
01:57:43,800 --> 01:57:46,360
Speaker 1: bit of a misnomer about who who we are because

2043
01:57:46,720 --> 01:57:48,600
Speaker 1: you know, the the talk comes about and I threw

2044
01:57:48,640 --> 01:57:50,560
Speaker 1: the numbers out, you know, four point six million dollars

2045
01:57:50,680 --> 01:57:54,280
Speaker 1: last year with a relatively small club. So the the

2046
01:57:54,280 --> 01:57:57,920
Speaker 1: the erroneous assumption is that, you know, it's just a

2047
01:57:57,920 --> 01:58:01,560
Speaker 1: bunch of rich folks. It really isn't it. The demographic

2048
01:58:01,600 --> 01:58:05,080
Speaker 1: our our our show are is you know, the age

2049
01:58:05,120 --> 01:58:08,320
Speaker 1: is going down and down and down because it's you know,

2050
01:58:08,360 --> 01:58:11,760
Speaker 1: there's something bad ass about hunting sheep. There's something something

2051
01:58:11,800 --> 01:58:15,040
Speaker 1: bad ass about wanting to hunt sheep. Uh, there's something

2052
01:58:15,040 --> 01:58:18,839
Speaker 1: bad ass about training to hunt sheep. So we're seeing

2053
01:58:19,040 --> 01:58:23,160
Speaker 1: our our attendants age go down and down and down.

2054
01:58:23,200 --> 01:58:28,160
Speaker 1: We have backpack races, indoor, backpack races outdoor. Um, you know,

2055
01:58:28,200 --> 01:58:30,840
Speaker 1: it's just it's just a fun time. But what what

2056
01:58:30,920 --> 01:58:32,800
Speaker 1: was interesting? And I had a guy come up to

2057
01:58:32,840 --> 01:58:34,480
Speaker 1: me and it was actually at the Lesson one Club

2058
01:58:34,640 --> 01:58:39,000
Speaker 1: this year, and he said, you know, um, I'm sitting here.

2059
01:58:39,040 --> 01:58:42,560
Speaker 1: There's people in there. Because now we let anyone go

2060
01:58:42,600 --> 01:58:44,080
Speaker 1: into the Lesson one Club. You don't have to be

2061
01:58:44,120 --> 01:58:46,480
Speaker 1: in the reception, you don't have to be a member.

2062
01:58:46,480 --> 01:58:50,200
Speaker 1: And people, I mean guys that have taken twenty seven

2063
01:58:50,280 --> 01:58:52,760
Speaker 1: sheep come into the lesson one club, just to see

2064
01:58:52,800 --> 01:58:56,880
Speaker 1: how cool it is for some new aspirational woman or

2065
01:58:57,000 --> 01:59:03,640
Speaker 1: man when their first sheep hunt. The first drawn is

2066
01:59:03,880 --> 01:59:08,600
Speaker 1: a female mountain climber that's dating a sheep and moose

2067
01:59:08,600 --> 01:59:11,920
Speaker 1: guide in Alaska outfit or in Alaska, and I mean,

2068
01:59:11,960 --> 01:59:14,200
Speaker 1: it was just fabulous. When she wants she you know,

2069
01:59:14,240 --> 01:59:18,480
Speaker 1: she wont a incredible Northwest Territories doll sheep bunch. She

2070
01:59:18,520 --> 01:59:21,080
Speaker 1: looks down at her boyfriend, and you know, she told

2071
01:59:21,080 --> 01:59:22,880
Speaker 1: me later she goes, you know, I couldn't sleep that nice.

2072
01:59:22,880 --> 01:59:25,040
Speaker 1: So I'm sitting there poking him, you know, in bed,

2073
01:59:25,080 --> 01:59:26,520
Speaker 1: going do you see what I want? Did you see

2074
01:59:26,520 --> 01:59:28,720
Speaker 1: what I want? You know? I mean, it's just it's

2075
01:59:28,840 --> 01:59:30,960
Speaker 1: it's it's cool. It's the family. But this guy came

2076
01:59:31,000 --> 01:59:32,920
Speaker 1: up to me and he says, hey, look, he goes,

2077
01:59:32,960 --> 01:59:34,640
Speaker 1: I I go to all the shows, and I do too.

2078
01:59:34,640 --> 01:59:36,560
Speaker 1: I mean, I'm a member of every all of the

2079
01:59:36,600 --> 01:59:39,240
Speaker 1: organizations are all great, and we support him. But he goes,

2080
01:59:39,280 --> 01:59:41,920
Speaker 1: you know, I walk around this room and I have

2081
01:59:42,080 --> 01:59:45,520
Speaker 1: the feeling that there are some real big players in here.

2082
01:59:45,840 --> 01:59:48,480
Speaker 1: He goes, I feel I can talk to anyone in

2083
01:59:48,480 --> 01:59:52,920
Speaker 1: this room, and anyone in this room we'll talk to me. So, yes,

2084
01:59:53,160 --> 01:59:55,360
Speaker 1: it's a it's a great family. And there's something about

2085
01:59:55,400 --> 01:59:58,960
Speaker 1: wild sheep. You know, we talk about sheep fever. You know,

2086
01:59:59,000 --> 02:00:01,440
Speaker 1: we talked about as being a sickness. But there's something

2087
02:00:01,480 --> 02:00:04,720
Speaker 1: about the places they live. Uh, there's something about how

2088
02:00:04,800 --> 02:00:08,160
Speaker 1: challenging it is to get up to where they live. Uh.

2089
02:00:08,200 --> 02:00:10,560
Speaker 1: It's something about the training that you have to do,

2090
02:00:10,640 --> 02:00:13,920
Speaker 1: the mental preparation, you know, and and it's probably in

2091
02:00:14,160 --> 02:00:18,080
Speaker 1: you know, Steve, you hunting places, that's just fabulous. Uh,

2092
02:00:18,080 --> 02:00:19,720
Speaker 1: and do it and do it the right way, do

2093
02:00:19,760 --> 02:00:21,320
Speaker 1: it the hard way, and do it the way that

2094
02:00:21,360 --> 02:00:24,440
Speaker 1: we all aspire to hunt. Um. But that's kind of

2095
02:00:24,480 --> 02:00:26,480
Speaker 1: the essence of sheep hunty. You know, you you gotta

2096
02:00:26,520 --> 02:00:28,680
Speaker 1: earn it. You know, it doesn't come easy. There's no

2097
02:00:28,720 --> 02:00:33,240
Speaker 1: easy ram. Yeah, it's for the hard players, it is, Steve.

2098
02:00:33,320 --> 02:00:37,400
Speaker 1: I'm I spent my life on Big Orange Cheap and

2099
02:00:37,440 --> 02:00:46,880
Speaker 1: I am a less than one member really I'm not. Yeah, Yeah,

2100
02:00:47,000 --> 02:00:49,680
Speaker 1: already made a decision. We're going to the uh well

2101
02:00:49,880 --> 02:00:53,080
Speaker 1: Sheep Show. Yeah, I want to go this year and

2102
02:00:53,120 --> 02:00:55,680
Speaker 1: it's not on shot show. It's February seven through to ninth,

2103
02:00:55,800 --> 02:01:00,920
Speaker 1: So we're we're off shot feasibly spread my wings. Man,

2104
02:01:00,960 --> 02:01:03,400
Speaker 1: I gotta check some new stuff out. I gotta checks

2105
02:01:03,400 --> 02:01:08,040
Speaker 1: some new stuff out. Um any uh, final thoughts around

2106
02:01:08,120 --> 02:01:12,520
Speaker 1: the table. We're doing the whole man. If you want,

2107
02:01:13,120 --> 02:01:14,760
Speaker 1: if you feel that it's all been said, you can

2108
02:01:14,760 --> 02:01:16,880
Speaker 1: just say it's all been said. I don't have any

2109
02:01:16,880 --> 02:01:21,120
Speaker 1: concluding bod man. I'm you know, as the preacher said,

2110
02:01:21,160 --> 02:01:23,680
Speaker 1: once I get started, generally I'm too lazy to stop.

2111
02:01:23,800 --> 02:01:26,640
Speaker 1: So I don't know if you want me to do that,

2112
02:01:26,680 --> 02:01:29,200
Speaker 1: but I you know, I do think it's worth just mentioning,

2113
02:01:29,520 --> 02:01:32,760
Speaker 1: you know, Steve and Jannest. It means a lot having

2114
02:01:32,840 --> 02:01:36,240
Speaker 1: you guys here, you know, and helping us talk about

2115
02:01:36,320 --> 02:01:38,959
Speaker 1: you know, what we do as an organization. We reality

2116
02:01:39,080 --> 02:01:42,560
Speaker 1: is we conserve a species that lives at fourteen thousand

2117
02:01:42,560 --> 02:01:45,800
Speaker 1: feet and that lives below sea level UM. And that

2118
02:01:45,880 --> 02:01:48,360
Speaker 1: includes a lot of animals along the way. So that's

2119
02:01:48,360 --> 02:01:50,600
Speaker 1: a good way of putting it. Man, I never thought that. Yeah.

2120
02:01:50,680 --> 02:01:54,640
Speaker 1: I mean when we do Guzzler projects, a frequent animal

2121
02:01:54,640 --> 02:01:57,520
Speaker 1: that visits as a desert tortoise. Right, you know, we

2122
02:01:58,240 --> 02:02:03,560
Speaker 1: just at a rehabilitation UM deal with encroaching conifers and uh,

2123
02:02:03,600 --> 02:02:05,280
Speaker 1: you know, the guy. When we kind of got done,

2124
02:02:05,280 --> 02:02:07,240
Speaker 1: it goes well, actually this is more meal their habitat

2125
02:02:07,280 --> 02:02:10,280
Speaker 1: than anything else. But um, you know, so we can

2126
02:02:10,320 --> 02:02:12,880
Speaker 1: serve that species, and we have to watch that chain

2127
02:02:12,880 --> 02:02:15,920
Speaker 1: of events happen all the way through those different different

2128
02:02:15,920 --> 02:02:19,480
Speaker 1: elevations as they migrate. We have to watch you know,

2129
02:02:19,560 --> 02:02:26,800
Speaker 1: just food, um, predator management obviously, domestic sheep conflict and

2130
02:02:26,840 --> 02:02:29,080
Speaker 1: a lot of people don't know that that happen. Has

2131
02:02:29,120 --> 02:02:31,480
Speaker 1: to happen, that chain has to happen the whole way

2132
02:02:31,600 --> 02:02:33,960
Speaker 1: for this to work. And the fact that you know,

2133
02:02:34,000 --> 02:02:36,480
Speaker 1: you guys are here and helping us tell that story,

2134
02:02:37,120 --> 02:02:39,800
Speaker 1: that just does good things for us, like helping sheep.

2135
02:02:39,880 --> 02:02:42,160
Speaker 1: You're touching a lot a while. But yeah, I mean

2136
02:02:42,600 --> 02:02:45,080
Speaker 1: you're you're you're taking an animal that lives in the

2137
02:02:45,120 --> 02:02:48,720
Speaker 1: wildest places on both ends of the spectrum and probably

2138
02:02:48,720 --> 02:02:51,320
Speaker 1: one of the more wild animals and nature and behavior,

2139
02:02:51,560 --> 02:02:55,200
Speaker 1: and therefore you encapsulate a lot of critters right in

2140
02:02:55,240 --> 02:02:59,400
Speaker 1: the middle. And and so what we do. You know

2141
02:02:59,400 --> 02:03:02,760
Speaker 1: what it has like and wild cheap conservation comes from us,

2142
02:03:03,560 --> 02:03:06,160
Speaker 1: and we conserve a lot of critters along the way.

2143
02:03:07,200 --> 02:03:11,240
Speaker 1: We'll put for me. You asked us if if we

2144
02:03:11,240 --> 02:03:15,200
Speaker 1: were optimistic and and I am. UM. I think a

2145
02:03:15,240 --> 02:03:17,880
Speaker 1: lot of times we focus on just the disease, just

2146
02:03:17,960 --> 02:03:21,280
Speaker 1: the just the negative side of of the story. And

2147
02:03:21,320 --> 02:03:27,080
Speaker 1: if you look at the numbers today, you have uh

2148
02:03:27,320 --> 02:03:32,280
Speaker 1: a better opportunity to see sheep, to hunt sheep. Uh

2149
02:03:32,400 --> 02:03:35,360
Speaker 1: My kids have, my grandkids have a better opportunity to

2150
02:03:35,440 --> 02:03:38,320
Speaker 1: draw a tag then than I did when I started

2151
02:03:38,360 --> 02:03:43,720
Speaker 1: my career. Uh, that's important to me, UM, I I

2152
02:03:43,880 --> 02:03:47,880
Speaker 1: and I do. I am confident that that uh. And

2153
02:03:48,160 --> 02:03:52,240
Speaker 1: I don't know. I've been accused of being Pollyanna. I've

2154
02:03:52,360 --> 02:03:55,200
Speaker 1: heard this one said that to me once. Uh, But

2155
02:03:55,440 --> 02:03:57,920
Speaker 1: but I'm confident that that we can come to the

2156
02:03:57,960 --> 02:04:02,120
Speaker 1: table and try to think outside of the box, think

2157
02:04:02,160 --> 02:04:05,080
Speaker 1: a little bit different. Scott tested on it earlier. The

2158
02:04:05,120 --> 02:04:08,040
Speaker 1: science is improving, We're learning more and more all the time.

2159
02:04:08,760 --> 02:04:12,080
Speaker 1: But I'm I'm confident that that we will come together

2160
02:04:12,240 --> 02:04:15,400
Speaker 1: to find solutions. And I'm talking about both while she

2161
02:04:15,760 --> 02:04:20,320
Speaker 1: advocates and the livestock industry to work together to achieve

2162
02:04:20,440 --> 02:04:24,080
Speaker 1: things that all of us benefit from. UM, I'm confident

2163
02:04:24,120 --> 02:04:27,640
Speaker 1: that that can occur. I I uh, I just think

2164
02:04:28,040 --> 02:04:32,400
Speaker 1: you know, the younger, younger generation, I I think they're smarter,

2165
02:04:32,600 --> 02:04:37,280
Speaker 1: I think they, Um, I don't know about that. Well,

2166
02:04:37,320 --> 02:04:39,760
Speaker 1: I just I just think I think that that the

2167
02:04:39,800 --> 02:04:45,040
Speaker 1: future is promising. And uh i uh, I don't want

2168
02:04:45,040 --> 02:04:47,280
Speaker 1: to go back. I don't want to go back to

2169
02:04:47,320 --> 02:04:50,720
Speaker 1: where we came from. We've we've invested too much blood,

2170
02:04:50,720 --> 02:04:54,680
Speaker 1: sweat and tears, uh to to be where we are today.

2171
02:04:54,760 --> 02:04:57,720
Speaker 1: And and I'm I'm proud of the whil You Foundation

2172
02:04:57,760 --> 02:04:59,280
Speaker 1: and proud of what we do every day. And I'm

2173
02:04:59,320 --> 02:05:02,080
Speaker 1: proud to work for the organization. UM, I wouldn't be

2174
02:05:02,120 --> 02:05:04,360
Speaker 1: here if I didn't believe in the mission. And and

2175
02:05:04,560 --> 02:05:08,000
Speaker 1: so I'm I'm I'm optimistic about where we're headed. And

2176
02:05:08,160 --> 02:05:12,760
Speaker 1: never got a sheep. Not on purpose, I'll say it

2177
02:05:12,800 --> 02:05:17,800
Speaker 1: that way through. I'm just saying, never got a sheep?

2178
02:05:17,960 --> 02:05:21,600
Speaker 1: Do you draw? Do you put in for sheep? Huh?

2179
02:05:21,800 --> 02:05:25,440
Speaker 1: A lot like Steve thirteen Western State? No, probably not

2180
02:05:25,560 --> 02:05:28,800
Speaker 1: that much. I don't know with that many, but handful?

2181
02:05:30,320 --> 02:05:32,480
Speaker 1: Can you guys answer this quickly? Because I heard a

2182
02:05:32,480 --> 02:05:35,880
Speaker 1: little I heard a rumor our Lama's bad. Oh, that's

2183
02:05:35,880 --> 02:05:37,520
Speaker 1: a That's the main thing I wanted to ask is

2184
02:05:37,560 --> 02:05:39,320
Speaker 1: my brother is my brother need to kill all is

2185
02:05:39,400 --> 02:05:44,880
Speaker 1: lamas camel it's yeah, you know, we're we're not as worried. No,

2186
02:05:45,000 --> 02:05:46,960
Speaker 1: just give it to me straight. Yeah, we're not as

2187
02:05:47,000 --> 02:05:49,880
Speaker 1: worried about him. There's there's some new papers coming out, Clay.

2188
02:05:49,960 --> 02:05:52,640
Speaker 1: Maybe you talk about Scott, you can talk about I know, uh,

2189
02:05:52,680 --> 02:05:55,200
Speaker 1: Helen Schwansea up in British Columbia is a little bit

2190
02:05:55,240 --> 02:05:58,080
Speaker 1: more concerned about him, um than we are. You know.

2191
02:05:58,160 --> 02:06:01,560
Speaker 1: It's kind of like pack goats. We're pretty concerned about

2192
02:06:01,560 --> 02:06:03,520
Speaker 1: pack goats. And and you know, as we as we

2193
02:06:03,640 --> 02:06:06,920
Speaker 1: learn more and more, pack goats seem to be more

2194
02:06:07,080 --> 02:06:10,080
Speaker 1: likely amovie free than than uh, you know, just a

2195
02:06:10,120 --> 02:06:14,000
Speaker 1: boar goat running around the so um. But but llamas

2196
02:06:14,080 --> 02:06:18,200
Speaker 1: can carry it. No, they can't carry micap Well, they

2197
02:06:18,240 --> 02:06:20,760
Speaker 1: shouldn't be able to carry micro plasma of a pneumonia,

2198
02:06:20,800 --> 02:06:22,880
Speaker 1: you know, the old of them. You know, the people

2199
02:06:22,960 --> 02:06:25,160
Speaker 1: keep a lot of people keeping texting me to bust

2200
02:06:25,160 --> 02:06:32,400
Speaker 1: my brothers. There's some potential diseases. Yeah, and we and

2201
02:06:32,440 --> 02:06:34,720
Speaker 1: it's it's kind of like it's another rock that we

2202
02:06:34,880 --> 02:06:38,200
Speaker 1: gotta in turn and gosh that we gotta get involved

2203
02:06:38,200 --> 02:06:42,960
Speaker 1: with the even even the pac industry thing. Pack goats

2204
02:06:42,960 --> 02:06:45,680
Speaker 1: are a big thing we're working with the pack goat

2205
02:06:45,680 --> 02:06:50,680
Speaker 1: industry right now to develop some best management practices that

2206
02:06:50,880 --> 02:06:53,240
Speaker 1: we believe would work. They would involve from testing and

2207
02:06:53,280 --> 02:06:56,600
Speaker 1: other things. Kevin Hurley's actually meeting with those folks here.

2208
02:06:56,600 --> 02:07:02,560
Speaker 1: You're distributing goat recipes. No no, uh, if you got

2209
02:07:02,720 --> 02:07:06,240
Speaker 1: a good go to do that. Yeah. So so anyway,

2210
02:07:06,320 --> 02:07:11,560
Speaker 1: it uh for the short version is for us at

2211
02:07:11,600 --> 02:07:14,320
Speaker 1: this stage of the game, it's not worth gamble with.

2212
02:07:14,760 --> 02:07:18,560
Speaker 1: We don't believe that it's worth of gall Have your

2213
02:07:18,560 --> 02:07:23,200
Speaker 1: brother tested, I will, Yeah, he can have his testing absolutely,

2214
02:07:23,320 --> 02:07:26,520
Speaker 1: Just he probably know he's not like, he's not a

2215
02:07:26,520 --> 02:07:29,320
Speaker 1: negligent dude. I just haven't talked about it with him lately.

2216
02:07:29,360 --> 02:07:31,480
Speaker 1: I'm sure that he's doing whatever he should be doing.

2217
02:07:31,560 --> 02:07:34,000
Speaker 1: And he's the kind of guy too. I think if

2218
02:07:34,000 --> 02:07:36,680
Speaker 1: someone like laid out for him, like a really compelling case,

2219
02:07:36,720 --> 02:07:38,160
Speaker 1: I feel like he'd just be like, Okay, I gonna

2220
02:07:38,240 --> 02:07:42,920
Speaker 1: buy a horse, which is smarter anyway. Well, he just

2221
02:07:42,960 --> 02:07:46,160
Speaker 1: doesn't have that that background. Man. People to grow up

2222
02:07:46,160 --> 02:07:50,440
Speaker 1: around horses. You can't catch him his wife a horse.

2223
02:07:51,520 --> 02:07:55,480
Speaker 1: I don't know. I don't want to say whisper. That's

2224
02:07:55,760 --> 02:07:58,320
Speaker 1: almost every day. Her dad grew up around horses. Are

2225
02:07:58,360 --> 02:08:01,880
Speaker 1: great grandfather recommends that he'd does not get involved with horses.

2226
02:08:03,080 --> 02:08:05,160
Speaker 1: Is this the brother that lives in Miles City. Yeah,

2227
02:08:05,400 --> 02:08:09,080
Speaker 1: and his wife comes from a long long line of horsemen,

2228
02:08:09,600 --> 02:08:14,880
Speaker 1: um breeders and you know, and ranchers, and she she's

2229
02:08:14,960 --> 02:08:23,160
Speaker 1: recommended that he temperamentally needs to steer clear of horses. Yeah,

2230
02:08:23,320 --> 02:08:25,600
Speaker 1: you got something? Was that? Was that your concluder? Yeah?

2231
02:08:26,280 --> 02:08:28,280
Speaker 1: Thank you. That's a good one, because I forgot about that.

2232
02:08:28,320 --> 02:08:32,400
Speaker 1: That was top of mind. Did we properly dodge it, No,

2233
02:08:32,560 --> 02:08:35,080
Speaker 1: but it was enough. I said, I got some code language. Yeah,

2234
02:08:35,120 --> 02:08:36,480
Speaker 1: we don't want to poke that one in the eye

2235
02:08:36,560 --> 02:08:39,880
Speaker 1: right now, we gotta get bigger fish. Right. I'll just

2236
02:08:40,200 --> 02:08:43,200
Speaker 1: rewind just a little bit. If there's you there might

2237
02:08:43,200 --> 02:08:45,640
Speaker 1: be some listeners that or maybe a little confused about

2238
02:08:45,640 --> 02:08:48,320
Speaker 1: the setup. Just something about the sheep ecology that in

2239
02:08:48,440 --> 02:08:51,520
Speaker 1: the in the situation that we're in. So historically sheep

2240
02:08:51,560 --> 02:08:55,560
Speaker 1: evolved in you know, in large metal populations of well

2241
02:08:55,640 --> 02:09:01,040
Speaker 1: connected subpopulation, so individual to to a hundred size groups. Right,

2242
02:09:01,360 --> 02:09:05,160
Speaker 1: So all these you're on domestic horn sheep, so they

2243
02:09:05,200 --> 02:09:08,040
Speaker 1: were you know, moving through the landscape. You know, maybe

2244
02:09:08,120 --> 02:09:11,360
Speaker 1: ram groups going to breed, different groups of use, and

2245
02:09:11,680 --> 02:09:13,960
Speaker 1: so we had this sort of network of connection depending

2246
02:09:13,960 --> 02:09:16,120
Speaker 1: on the habitat. Like think about the basin and range

2247
02:09:16,160 --> 02:09:19,480
Speaker 1: in Nevada, those mountain ranges that jump up out of desert.

2248
02:09:19,720 --> 02:09:22,160
Speaker 1: Sheep will go across those, right. So that's where in

2249
02:09:22,240 --> 02:09:26,000
Speaker 1: modern times we've got humans in the bottom sheep you know,

2250
02:09:26,320 --> 02:09:29,280
Speaker 1: fullyar on cheap here on sheep have down on top across.

2251
02:09:29,800 --> 02:09:32,360
Speaker 1: That's where we're running our problems. The river systems. They're

2252
02:09:32,360 --> 02:09:35,280
Speaker 1: traveling up and down, so their ecology and their their

2253
02:09:35,280 --> 02:09:39,560
Speaker 1: evolution is to move in between groups. And so functionally

2254
02:09:39,560 --> 02:09:43,920
Speaker 1: we want to manage four large groups of sheep rather

2255
02:09:44,000 --> 02:09:48,080
Speaker 1: than small isolated groups because there's all kinds of negative

2256
02:09:48,120 --> 02:09:50,760
Speaker 1: impacts of that. So we're kind of stuck in that

2257
02:09:50,760 --> 02:09:52,520
Speaker 1: that problem where we're like, Okay, here's a good piece

2258
02:09:52,520 --> 02:09:55,760
Speaker 1: of habitat, but we've got surrounded by domestics and we

2259
02:09:55,800 --> 02:09:57,960
Speaker 1: can't have sheep shooting out of it and going to

2260
02:09:58,040 --> 02:10:00,400
Speaker 1: talk to their their friends up river. We've kind of

2261
02:10:00,400 --> 02:10:02,760
Speaker 1: gotten ourselves into a little bit of a pickle, and

2262
02:10:02,800 --> 02:10:05,040
Speaker 1: so that's that's a little bit of a pickle. By

2263
02:10:05,160 --> 02:10:08,240
Speaker 1: thinking in pocket mentality, we can have a few here,

2264
02:10:08,240 --> 02:10:10,240
Speaker 1: we can have a few there, yes, but they can't.

2265
02:10:10,280 --> 02:10:12,040
Speaker 1: But if they come out, we can't. We can't let

2266
02:10:12,080 --> 02:10:14,320
Speaker 1: them come out in the valley or we're gonna remove them.

2267
02:10:14,560 --> 02:10:16,360
Speaker 1: So we've kind of got ourselves into a bind in

2268
02:10:16,480 --> 02:10:18,760
Speaker 1: that way. But but look at all this great sheep

2269
02:10:18,760 --> 02:10:20,840
Speaker 1: halitat we have, and we want to have sheep there.

2270
02:10:21,040 --> 02:10:22,800
Speaker 1: But at the same time, it's hard to let them

2271
02:10:22,800 --> 02:10:26,640
Speaker 1: be sheep because their natural tendency is to move around

2272
02:10:26,640 --> 02:10:31,040
Speaker 1: between groups and you know, eventually spread out. Polling excellent

2273
02:10:31,080 --> 02:10:34,480
Speaker 1: point in in in Texas. You know, we've built those

2274
02:10:34,520 --> 02:10:38,880
Speaker 1: populations metal populations. There's constantly interchange between populations and we've

2275
02:10:38,960 --> 02:10:42,600
Speaker 1: encouraged that because we haven't had the domestic sheep issues

2276
02:10:42,640 --> 02:10:45,160
Speaker 1: to deal with. So that's an excellent point. Trying to

2277
02:10:45,440 --> 02:10:48,000
Speaker 1: and trying to restore that connectivity of hers really like

2278
02:10:48,080 --> 02:10:49,920
Speaker 1: it's it's it's the pie in the sky and it's

2279
02:10:50,040 --> 02:10:52,880
Speaker 1: it's right and waff was um. You know, main goal

2280
02:10:52,920 --> 02:10:56,680
Speaker 1: as far as connectivity and metal population management, that that's

2281
02:10:56,720 --> 02:10:58,520
Speaker 1: the that's the goal we're shooting for, not just to

2282
02:10:58,520 --> 02:11:02,240
Speaker 1: have one big population or one robust one here. We

2283
02:11:02,280 --> 02:11:03,960
Speaker 1: need a bunch of them. They are all functioning together,

2284
02:11:04,080 --> 02:11:06,680
Speaker 1: exchanging to the neck material, and they're talking to each other,

2285
02:11:06,920 --> 02:11:09,960
Speaker 1: they're they're more resilient to disease outbreaks when you have

2286
02:11:10,000 --> 02:11:12,520
Speaker 1: a whole bunch of different scattered groups of sheep and

2287
02:11:12,560 --> 02:11:15,000
Speaker 1: they're they're moving their genes in between, and it's just

2288
02:11:15,120 --> 02:11:16,640
Speaker 1: it's it's the setup. We need to go for it.

2289
02:11:16,720 --> 02:11:18,680
Speaker 1: And it seems to give you a situation to have

2290
02:11:19,600 --> 02:11:25,520
Speaker 1: localized disasters horrible winners and and and then hopefully get

2291
02:11:25,560 --> 02:11:28,400
Speaker 1: them back without needing to then have it be by

2292
02:11:28,520 --> 02:11:32,200
Speaker 1: a helicopter exactly. So that was just one thing I

2293
02:11:32,200 --> 02:11:34,760
Speaker 1: think people might missed out on if they're not familiar

2294
02:11:34,800 --> 02:11:37,520
Speaker 1: with sheep and how they've evolved. It's a good point.

2295
02:11:37,520 --> 02:11:41,560
Speaker 1: It's it's yeah, it spans habitat types too generally. Um,

2296
02:11:41,680 --> 02:11:44,520
Speaker 1: and then I guess my my little concluder is I mean,

2297
02:11:44,600 --> 02:11:47,760
Speaker 1: we've we've had a great discussion today and thank you

2298
02:11:47,800 --> 02:11:50,600
Speaker 1: for having me. Um, And a lot of the sheep

2299
02:11:50,640 --> 02:11:53,520
Speaker 1: have tats on public land, So folks listening, if you

2300
02:11:53,680 --> 02:11:56,000
Speaker 1: if this hit strikes a chord, get involved. I mean,

2301
02:11:56,040 --> 02:11:58,640
Speaker 1: it's a public lands, public wildlife. You know, you need

2302
02:11:58,680 --> 02:12:00,240
Speaker 1: to be if you want to be heard, got to

2303
02:12:00,280 --> 02:12:02,560
Speaker 1: be there, you know. And a lot of these decisions

2304
02:12:02,560 --> 02:12:06,000
Speaker 1: are being made, you know, policy level stuff that's disconnected

2305
02:12:06,040 --> 02:12:08,200
Speaker 1: from the science, and if you don't like it, you

2306
02:12:08,240 --> 02:12:11,120
Speaker 1: need to be there. And so that's my main point

2307
02:12:11,200 --> 02:12:16,440
Speaker 1: is get involved. These are these are everybody's sheep and

2308
02:12:16,640 --> 02:12:19,720
Speaker 1: we need to be be there to make good decisions.

2309
02:12:20,440 --> 02:12:24,000
Speaker 1: And uh yeah, so and I hope that everybody listening

2310
02:12:24,040 --> 02:12:28,000
Speaker 1: will be able to someday draw sheep tag. You know

2311
02:12:28,080 --> 02:12:30,120
Speaker 1: you've hunted all over the West. How many big horn

2312
02:12:30,160 --> 02:12:33,240
Speaker 1: mountains have you passed? Sheep mountain, sheep ridge, big sheep ridge.

2313
02:12:33,800 --> 02:12:36,720
Speaker 1: Most of them don't have sheep. I think we need

2314
02:12:36,760 --> 02:12:38,840
Speaker 1: to get We need to get there where big horns

2315
02:12:38,880 --> 02:12:43,040
Speaker 1: and sheep mountains are are restored with sheep, bighorn sheep. Yeah,

2316
02:12:43,040 --> 02:12:45,040
Speaker 1: if every sheep mountain had a sheep on it would

2317
02:12:45,040 --> 02:12:50,360
Speaker 1: be in good shape. One last concluder, one last concluder. UM,

2318
02:12:50,400 --> 02:12:53,800
Speaker 1: Steveana's first, first and foremost. UM. I want to thank

2319
02:12:53,840 --> 02:12:57,880
Speaker 1: you for the opportunity I talked about while Chef Foundation

2320
02:12:57,960 --> 02:13:04,160
Speaker 1: casting a broad concert Baian shadow. Um, you cast a

2321
02:13:04,320 --> 02:13:08,080
Speaker 1: huge communications shadow and a lot about what we were

2322
02:13:08,080 --> 02:13:11,680
Speaker 1: talking about today was education, and you've provided us an

2323
02:13:11,720 --> 02:13:14,560
Speaker 1: opportunity to educate a hell of a lot of people

2324
02:13:14,560 --> 02:13:17,720
Speaker 1: and we're grateful. Um. The final thought that I'd like

2325
02:13:17,800 --> 02:13:20,840
Speaker 1: to to to say is that you know, we we

2326
02:13:21,560 --> 02:13:23,920
Speaker 1: you touched on it on this the extremes. You know,

2327
02:13:23,960 --> 02:13:27,640
Speaker 1: there's extreme on the right, that's extreme on the left. UM.

2328
02:13:27,680 --> 02:13:30,400
Speaker 1: And I've said this a few times a few different groups,

2329
02:13:30,400 --> 02:13:33,120
Speaker 1: and I think it resonates. If if we could concentrate,

2330
02:13:33,640 --> 02:13:36,920
Speaker 1: whether it's the non consumptive community, the hunting community, the

2331
02:13:37,200 --> 02:13:41,400
Speaker 1: conservation community, the environmental community, the domestic sheep industry, the

2332
02:13:41,440 --> 02:13:44,160
Speaker 1: cattle industry, the you know whatever, and the wild sheep

2333
02:13:44,200 --> 02:13:50,600
Speaker 1: Avasacie community, if we could aspire, work and focus on

2334
02:13:50,760 --> 02:13:56,000
Speaker 1: the eighty to ninetent that we agree on and not

2335
02:13:56,200 --> 02:13:59,600
Speaker 1: spend all our time on the ten to that we

2336
02:13:59,720 --> 02:14:03,800
Speaker 1: dis agree on, we can move mountains. So that's kind

2337
02:14:03,800 --> 02:14:06,320
Speaker 1: of our new narrative. Let's let's start looking at the

2338
02:14:06,400 --> 02:14:10,080
Speaker 1: areas where we agree and work on those and not

2339
02:14:10,640 --> 02:14:13,480
Speaker 1: bitch and moan and focus on the areas we disagree.

2340
02:14:13,600 --> 02:14:17,040
Speaker 1: It's an interesting idea that you imagine a big room

2341
02:14:17,080 --> 02:14:19,800
Speaker 1: and everyone's in it, and you make an announcement if

2342
02:14:19,840 --> 02:14:25,640
Speaker 1: you think wild sheep are cool, come over in this room,

2343
02:14:25,680 --> 02:14:28,520
Speaker 1: and most people are gonna wander in the room and

2344
02:14:28,520 --> 02:14:33,280
Speaker 1: then start there. Ye, put our differences aside. Look for

2345
02:14:33,360 --> 02:14:36,520
Speaker 1: areas that we can work together, not areas that we

2346
02:14:36,840 --> 02:14:40,520
Speaker 1: spend all our time fighting. Yeah, you'll get a lot

2347
02:14:40,520 --> 02:14:43,040
Speaker 1: of work done in that space. We'll put and keep

2348
02:14:43,120 --> 02:14:48,280
Speaker 1: cheap on the mountain wild sheep. Now, what's an admirable goal? Man?

2349
02:14:48,320 --> 02:14:51,520
Speaker 1: I think that anyone who you know is up in

2350
02:14:51,560 --> 02:14:55,240
Speaker 1: some high crazy mountain peak where you're just kind of

2351
02:14:55,280 --> 02:14:57,640
Speaker 1: like happy with yourself or just haven't gotten up there,

2352
02:14:58,280 --> 02:15:00,520
Speaker 1: and to see one of those things crashed out and

2353
02:15:00,640 --> 02:15:03,760
Speaker 1: turn his head and there's those curls. It's just magical.

2354
02:15:03,960 --> 02:15:06,200
Speaker 1: Makes it makes the hair stand up on the back

2355
02:15:06,240 --> 02:15:10,120
Speaker 1: of your neck. It's like you are you're seeing, touching,

2356
02:15:10,360 --> 02:15:15,280
Speaker 1: feeling wilderness. All right, Well, thank you very much for

2357
02:15:15,480 --> 02:15:16,960
Speaker 1: coming on everyone. I appreciate the time.