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Speaker 1: This is me eat your podcast coming in you shirtless,

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Speaker 1: severely vote bitten and in my case, underwear listening podcast.

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Speaker 1: You can't predict anything? Okay, all right? Our guests Diane

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Speaker 1: boy A carnivorre and wolf specialists, but kind of mostly wolves, right,

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Speaker 1: that's your thing. So let's just let's just dispatch with

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Speaker 1: the other one real quick. What we're like. Let's say

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Speaker 1: we're not Let's say we weren't talking about wolves. What

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Speaker 1: would you be a subject matter expert on? Um? Well, wolves,

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Speaker 1: but I also end up taking the lions, otters, bobcats,

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Speaker 1: you know, other fur bears that come in bears. Let's

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Speaker 1: do my colleagues, but I do a lot of it.

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Speaker 1: But I've mostly researched wolves all my life. But I've

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Speaker 1: I've done a few other things to some a little

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Speaker 1: bit of game big game work, um, but mostly wolves.

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Speaker 1: Do you remember what was your first Did you have

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Speaker 1: a wolf? An initial wolf experience that became kind of

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Speaker 1: your personal genesis? Do you know what I'm saying? Like

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Speaker 1: people like to later, it doesn't even feel like it's

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Speaker 1: happening in real life, right in real time. Oftentimes you

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Speaker 1: later look back and you realize that there was like

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Speaker 1: a moment, right, did you have a moment? There are

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Speaker 1: a couple of things I ended up. Um, I was

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Speaker 1: really fascinated by wolves growing up in the Twin Cities

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Speaker 1: because Minnesota was the only place in the seventies that

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Speaker 1: had wolves in the whole lower forty eight. Really, yep,

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Speaker 1: there were none in Wish Michigan, or Wisconsin the last stronghold,

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Speaker 1: and there were none anywhere in the United States anywhere else.

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Speaker 1: So is that really that's true? Yes, you can read it.

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Speaker 1: Look Google. I didn't know that. But but but what

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Speaker 1: about like the Ile Royal head wolves in two they

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Speaker 1: came in. Yeah, there were wolves in IOLs Michigan. There

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Speaker 1: was a handful starting nineteen fifty. But so you're saying

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Speaker 1: that Minnesota never ran out, they never lost him. No,

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Speaker 1: when I was a kid, I think they got down

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Speaker 1: as low as somewhere like seven hundred or eight hundred.

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Speaker 1: And when I left Minnesota in nineteen seventy nine to

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Speaker 1: come here to start wolf work, there were about a

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Speaker 1: thousand in Minnesota then, and there was just a handful

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Speaker 1: in Wisconsin. And I don't even know you p had

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Speaker 1: any back yet. I had him because they were stuck there.

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Speaker 1: But actually, I was just in yellow Stone this week

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Speaker 1: with tick Tale and his wife, and Dave Dick was

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Speaker 1: the first guy. He has been studying looking for wolves

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Speaker 1: in Wisconsin since he was like fifteen, and he told

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Speaker 1: the story over dinner just last night. He found his

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Speaker 1: first confirmed wolf tracks in Wisconsin in nineteen seventy four.

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Speaker 1: There weren't wolves there before that he was looking, and

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Speaker 1: then over the years eventually they got critical mass and

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Speaker 1: they had the first pack. I think it was like

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Speaker 1: in seventies seven or seventy eight, the first pack. They

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Speaker 1: were just coming back, so it's pretty recent recovery, much

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Speaker 1: like us here in the West. I feel as though

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Speaker 1: you can correct me if I'm wrong. I feel as

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Speaker 1: though I cut my first wolf track in Michigan in

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Speaker 1: ninth and it would have been October or November of nineteen.

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Speaker 1: They're there, yeah, I know. They was when they started

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Speaker 1: sending ways out from Minnesota with a Recovery and Endangered

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Speaker 1: Species Act, and that's what allowed them to come back

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Speaker 1: in Wisconsin and Michigan. There's you know, they've got hundreds

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Speaker 1: and hundreds now in Wisconsin and Michigan. I'm sure you

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Speaker 1: did see wolf tracks in ninety four, but he wouldn't

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Speaker 1: have been nineteen seventy, so you grew up in you

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Speaker 1: grew up in the last bastion of of lower forty

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Speaker 1: eight wolves. Yeah, and as a kid, I was pretty

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Speaker 1: fascinated by him. And Dave meach was on campus University

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Speaker 1: of Minnesota. He is um uh, he is the guy

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Speaker 1: for wolves. I mean he is Dave meach l David

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Speaker 1: Meets University Minnesota. He's actually I think he's employed by

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Speaker 1: the federal government at the university. But he started doing

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Speaker 1: wolves in the sixties. He was early on Aisle Royal.

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Speaker 1: He was the first one of caller Wolf in northern Minnesota.

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Speaker 1: I believe close to it. Um and he is now

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Speaker 1: he's the authority for the world. He's he's he's a

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Speaker 1: amazing guy. He's eighty and he's still working full time

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Speaker 1: because he loves what he does. He loves and he's

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Speaker 1: he's consulted from people over the world. And he's very

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Speaker 1: he's very uh. He's publishes constantly. He's the consummate scientist

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Speaker 1: and he's he accepts every viewpoint, looks at every viewpoint.

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Speaker 1: His brain is like a computer. When you asked him

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Speaker 1: a questions like off the goalist and spends on all

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Speaker 1: these realms. This is delightful, Okay. So I started y

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Speaker 1: asked how did I get involved? So he was on

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Speaker 1: campus where I was a student. He started in school's

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Speaker 1: pre veterinary medicine student. There also was a place called

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Speaker 1: Como Park Zoo in St. Paul which had this was

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Speaker 1: a new concept and the teen seventy three to put

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Speaker 1: out pens with wild animals that looked wild that was

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Speaker 1: you know, not everything else was like concrete. That So

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Speaker 1: they built a wolf exhibit and I think it was

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Speaker 1: five acres inside something like that, and I was fascinating.

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Speaker 1: I would go there all the time because it was

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Speaker 1: close to campus, very close to campus, and um I

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Speaker 1: would go to look at the wolves and sometimes you'd

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Speaker 1: see them and sometimes you wouldn't because it was all

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Speaker 1: forced and would it much like outside. And one day

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Speaker 1: I brought my arm folks dog, just a little pound mongrel,

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Speaker 1: really sweet little guy, and we were looking and the

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Speaker 1: wolves came up to the fence and he was sniffing

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Speaker 1: noses with the fence. So I can show you how

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Speaker 1: naive I was. Right, single chain link fence, single, no

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Speaker 1: double barrier. There was sniffin noses through the fence, and

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Speaker 1: then my little dog, being a mail he went up

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Speaker 1: to urinate bras leg mark on the fence because he's

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Speaker 1: a male, and that little foot it was just smaller

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Speaker 1: than the dimension of the diamond in this cyclone fence.

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Speaker 1: And the wolf is there anyone, And he got his

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Speaker 1: leg and he drug his legs to the cycling fence

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Speaker 1: and they were tearing his leg off. This is my

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Speaker 1: first wolf experience, you asked. And I was screaming, and

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Speaker 1: some guys came running over from the parking lot and

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Speaker 1: they threw themselves against the fence, and my dog got

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Speaker 1: his leg back was still attached, and we had some

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Speaker 1: pretty major surgeries and stuff. But you asked, that was

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Speaker 1: kind of my first wolf experience. Really, I was fascinated

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Speaker 1: much as I was sorry for my dog. But he survived,

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Speaker 1: blah blah blah, he did fine. And then I started

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Speaker 1: volunteering on these studies. Each was over many studies in Minnesota, UM.

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Speaker 1: The graduate students study at a preserve not far o

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Speaker 1: the Twin Cities. And then in nineteenth summer of nineteen

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Speaker 1: seventy seven, I had an opportunity Dave me to offered

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Speaker 1: me his internship up in northern Minnesota by Eli where

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Speaker 1: he had his wild wolf study. And I was like,

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Speaker 1: oh my god, this is it. It's like my dream.

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Speaker 1: And I just I didn't have I thought, how am

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Speaker 1: I going to pay for this? I'm not gonna get paid.

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Speaker 1: So I had to sell my motorcycle, show you how

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Speaker 1: important this was to me, kind of motorcycles. I had

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Speaker 1: a Yama already three fifty bright orange, just a little

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Speaker 1: hot ring ding ding, but sold it. And you mentioned

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Speaker 1: a cyclone fence. I call him cyclone fences, and no

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Speaker 1: one knows the hell I'm talking about. Just I know,

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Speaker 1: I know, damned your motorcycle and fences, but no one

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Speaker 1: knows what it's like. No one uses that word anymore. Work.

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Speaker 1: How do you know that word? Did you grow up?

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Speaker 1: Call them cycle and fences? What? I think? Everybody else

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Speaker 1: just calls him chain link. I know when I say

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Speaker 1: something about a cycle and fence, people look at me like,

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Speaker 1: what do you what kind of fence you're talking about?

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Speaker 1: Go on, you sell your motorcycles yea. And so my

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Speaker 1: next wealth experience was I was so excited. I was

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Speaker 1: so thrilled to go for the summer and study. We're

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Speaker 1: going to trap and call her and study wild wolves.

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Speaker 1: And I was driving up in the middle of nowhere

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Speaker 1: and this this is seventy seven. How many wolves are

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Speaker 1: up there at that time, Well, that was probably when

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Speaker 1: there was close to a thousand, nine to a thousand.

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Speaker 1: So I'm driving on the highway at night. I borrowed

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Speaker 1: my parents car to get up there because they had

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Speaker 1: sold my motorcyle coal their second car. And I'm driving

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Speaker 1: along this windy highway and I'm really sleepy and it's

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Speaker 1: totally dark, and all of a sudden, out of the side,

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Speaker 1: no kidding, a wolf shoots out into my headlights and

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Speaker 1: I nearly rented over a jam on the brakes, and

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Speaker 1: I come to rest and I feel kind of sick

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Speaker 1: to my stomach. The adrenaline thing. It's like, oh my god,

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Speaker 1: my first wild wolf when I nearly killed it. But

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Speaker 1: that was my next experience, and then from then then

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Speaker 1: we were out working with wild wolves all summer, and

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Speaker 1: I was thrilled right up by the Boundary Water Canoe

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Speaker 1: area up in northern Minnesota Elie Babbitt area. You guys

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Speaker 1: are trapping them, putting collars on them. Yeah, how are

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Speaker 1: you guys catching them? Back then Foothold traps, modified foothold traps,

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Speaker 1: like you laminate the jaws so they're thicker. Not back then.

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Speaker 1: We do know when you say modified modified, how they

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Speaker 1: had well back then and back now. It's not a

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Speaker 1: whole lot different. But the traps we had springs in

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Speaker 1: the bottom side. We checked them twice a day, so

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Speaker 1: they didn't sit there very long. Um. Some of them

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Speaker 1: had rubber jaws, not back then, but now we have

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Speaker 1: a rubber serrated jaws, so it's more kind of their foot. Um.

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Speaker 1: Then you use it like a serrated like a toothed

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Speaker 1: rubber jaw. Now it's not tooth. I mean that gives

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Speaker 1: an ugly image. They're kind of square flattened, but it's

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Speaker 1: hard rubber like a tire. And they that's the thing

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Speaker 1: you put over the jaw, you know, it's it's part

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Speaker 1: of the jaw there there. I don't know how they

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Speaker 1: make them one piece, but you boil it drops and everything.

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Speaker 1: It doesn't come off. It's on their permanently. And when

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Speaker 1: you say springs underneath, you mean like double coil spring

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Speaker 1: traps springs in the chains. Your double long spring spring

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Speaker 1: under the pan and a spring going to the tensions.

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Speaker 1: So if the wolves pulling, they're not hitting a hard end.

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Speaker 1: And and now we didn't back then, but now we

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Speaker 1: have underpan tensions spring devices to keep all their bycatch down.

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Speaker 1: So you can set that weight. We set it with

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Speaker 1: a measured scale and you can set it for two

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Speaker 1: pounds or twenty pounds or whatever. Do you wolves ten

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Speaker 1: pounds of pressure? That's a red fox? Walk right over? Fox?

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Speaker 1: Coyotes blinks, yeah, walk right over. Well, you think about, like,

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Speaker 1: how much is your average kyote? Pounds? Maybe and it's

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Speaker 1: four ft, So you divide their weight by four for

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Speaker 1: the amount of weight on a roughly, if you had

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Speaker 1: a huge coyot, you maybe catch it. And then how

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Speaker 1: would you so you'd go into a likely wolf area?

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Speaker 1: And would you just make set like dirt hole sets

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Speaker 1: on roads and stuff where they're traveling or you're asking

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Speaker 1: me secrets in my trade, you're really pushing the arms tea. Uh,

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Speaker 1: we don't. I hardly ever use a dirt hole set

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Speaker 1: because that's what everybody else does. You sent post sets

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Speaker 1: some what do you like? You really don't want to

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Speaker 1: tell how you catch blind sets? Some really what the

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Speaker 1: what's a blind set? I don't know? Lure no attracting right.

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Speaker 1: You have to know where the animals are, right, So

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Speaker 1: then you're just working there a trail or a path

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Speaker 1: and you don't do it or you're gonna get a

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Speaker 1: out of bike catch. So you have to know where

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Speaker 1: the wolves are are, like a Runde bows site or

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Speaker 1: something where they're using a particular trail a lot, and

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Speaker 1: you know from like if it's winter, you know they

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Speaker 1: use a certain trail system a lot. In the spring

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Speaker 1: you can look in the mud and if they're still

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Speaker 1: using it, you know, you know where they're danned, or

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Speaker 1: you know where the round site is. You've you've snagged wolves,

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Speaker 1: trapped them, trap, you've trapped travel hooks, you've trapped wolves,

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Speaker 1: no lure, no bait, no nothing, just said where he

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Speaker 1: wants not most you have done that. I have not. Actually,

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Speaker 1: there was one pack in um in the Swan Valley

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Speaker 1: that had a lot of trapping pressure for a lot

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Speaker 1: of years. There was a guy who was really good

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Speaker 1: trapper there and he'd take his limit every year and

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Speaker 1: so these wolves were very very hard to catch. We

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Speaker 1: put out traps. My first year, we trapped, we trapped

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Speaker 1: in trapped. We never had any luck. We did every

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Speaker 1: turk I could think of everything I could think of,

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Speaker 1: and finally and they were actually avoiding him, walking around

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Speaker 1: him digging them. They knew they were there. I finally

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Speaker 1: went to doing a blind trail set, which I don't

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Speaker 1: like to do because you chance catching deer or anything

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Speaker 1: that comes by. But I knew where the randevousite was.

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Speaker 1: I said, okay, I'm going to tiptoe. Can you explain rendee? Oh,

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Speaker 1: I'm sorry, sure, And then I want to get back

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Speaker 1: to Minnesota. So when wolves have pups, they have the

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Speaker 1: den and they dan. I like to tell people, oh,

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Speaker 1: when did they dan? And when did they breat breeding?

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Speaker 1: Pika breeding is about Valentine's Day, Pika danning is about

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Speaker 1: tax Day. Okay, so those are just dates to remember.

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Speaker 1: They use the den six seven weeks maybe eight. But

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Speaker 1: they start moving them away from the den, and they

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Speaker 1: move them to a rendezvous site. And it's generally um

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Speaker 1: a more open area meadow that has thick cover around

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Speaker 1: it that they can escape to safe terrain and their

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Speaker 1: water nearby. And so wolves can't hunt with a bunch

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Speaker 1: of goofball pups dangling along, So they leave them at

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Speaker 1: the rendezvous site. The wolves go out and hunt and

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Speaker 1: they bring food back, and they generally leave an adult

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Speaker 1: at the on site, so it's gets to be this

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Speaker 1: like a pat it's just a pack down area with

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Speaker 1: toy wolf toys and bones and chewed up antlers and scats,

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Speaker 1: and you know, all summer they're there and they move

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Speaker 1: around a few times or not. Some packs move and

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Speaker 1: use different rounde bous sites. Some stay pretty station. They

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Speaker 1: most of them change round. It was site. But there's

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Speaker 1: spokes coming off from these rendezvous sites like a wheel.

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Speaker 1: And if you can find that in the summer months,

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Speaker 1: that's the spot you don't want to catch it. Usually

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Speaker 1: you won't because you've got that spring tension set. So

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Speaker 1: to catch this one wolf. And how come the rendezvous

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Speaker 1: site doesn't go into the fall because it pups become

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Speaker 1: mobile and they start traveling with the adults. They're just

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Speaker 1: station periods only three months, two months. It's iganical to

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Speaker 1: a dog sixty two days. Yeah, two months. Yeah, well

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Speaker 1: I wasn't in my math. That's a cancer. Early February

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Speaker 1: Valentine's at tax day. Yeah, okay, give her take a

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Speaker 1: little it and it's latitude oriented. So yeah, so anyway,

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Speaker 1: that's how I caught the wolf, was finding the rondevousite

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Speaker 1: and putting a blind sin in on a trail leading

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Speaker 1: into it. And I never walked down the trail again ever.

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Speaker 1: I was checked it with binoculars and it was like

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Speaker 1: a little stick or something that had to step over

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Speaker 1: so a place. It's foot in the right place every time. Yeah, alright, Minnesota,

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Speaker 1: there you are. You almost run over one and you

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Speaker 1: set the trap on them. Did you guys have some

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Speaker 1: with collars on him at that time in Minnesota? Yes?

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Speaker 1: Oh yeah. His study had been going on for years

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Speaker 1: in the Superior National Forest. What were you guys primarily

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Speaker 1: interested in looking at everything? Because at that time, I

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Speaker 1: mean you gotta remember, this is the late seventies, and

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Speaker 1: there was there was VHF callers, and there was airplane

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Speaker 1: flying to see them, but that was it. And it's

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Speaker 1: in the thick, thick Superior National Forest with a lot

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Speaker 1: of water and bogs and forest. You never saw them never.

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Speaker 1: It's not like yellow Stone where I just came from

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Speaker 1: you going down and have your theramisic offee and you're

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Speaker 1: you know, muffins and you sit and watch wolves. It

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Speaker 1: just it just wasn't that way. So um yeah, and

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Speaker 1: so we would learn what we could by following them

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Speaker 1: in the airplane. In the summer, you can't follow tracks.

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Speaker 1: So a lot of what I did from ment to

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Speaker 1: my career was tracking wolves on skis in the snow

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Speaker 1: when you can see every place they step, everything, they sniff, everyplace,

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Speaker 1: they mark, scent mark whatever. So this was a lot

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Speaker 1: of interpretive stuff. And you guys were interested in what

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Speaker 1: how far they move, what they eat, what they eat,

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Speaker 1: their ecology were they done, what kind of habitat that use,

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Speaker 1: how many there are, how many what happens when two

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Speaker 1: over packs overlap? Do they kill each other? In trespassing issues?

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Speaker 1: I mean just everything you couldn't see behavior. You could

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Speaker 1: interpret a little bit, you know, but you couldn't see it.

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Speaker 1: I read an interesting thing out go ahead. I was

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Speaker 1: just gonna ask what those wolves were eating. Mostly mostly

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Speaker 1: white tailed deer and a few moose. And actually wolves

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Speaker 1: in the Midwest eat a lot of beaver. That's all

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Speaker 1: going to bring up I read a good already. A

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Speaker 1: thing is they were doing a scat analysis, and you

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Speaker 1: know how you know, beavers disperse after ice out, and

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Speaker 1: it would be that you know, something like and in

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Speaker 1: May and June, nine percent of wolf scats would have

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Speaker 1: beaver remains in them, but then it would taper off.

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Speaker 1: But they would really nail them when they're dispersing. Sure.

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Speaker 1: I mean, if you think about a beaver, a lot

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Speaker 1: of fat in a beaver, very good and slow. If

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Speaker 1: you can get them not in the water, catch them

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Speaker 1: on land, you're pretty vulnerable. I mean, wolves aren't there

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Speaker 1: swimming for looking for beaver. They're not bobbying for beaver

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Speaker 1: in the ponds, catching them on the damns or or houses.

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Speaker 1: Remember the track, the track I saw nine, The first

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Speaker 1: like wolf track I ever laid eyes on in the

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Speaker 1: wild was skirting the edge of a beaver day. And

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Speaker 1: bobcats would hunt those things a lot, and then then

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Speaker 1: they would ice up, and the bobcats and hunt the ice,

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Speaker 1: just going trying to catch them out where they come out. So,

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Speaker 1: you know, over my area we don't have so many beavers,

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Speaker 1: so it's not as much of a diet. So wolves

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Speaker 1: are strictly opportunists. They'll take whatever they can get. They're

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Speaker 1: not out there selecting, well, we're going to go look

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Speaker 1: for a nice fat cow elk to I mean, that's

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Speaker 1: not how they hunt. Whatever they catch is what they catch,

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Speaker 1: you know, people think they can kill it will They can't.

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Speaker 1: If they had, I mean, they wouldn't work. What do

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Speaker 1: you mean people think they can kill it will Well,

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Speaker 1: I've heard people say, well, wolves killed just for fun,

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Speaker 1: or they can kill whatever they want. And the truth is,

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Speaker 1: if if they were that efficient, they wouldn't be living

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Speaker 1: in packs. A mountline is a really efficient, very effective

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Speaker 1: killer because they have all the teeth, and they have

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Speaker 1: sets of sabers on every pond. They can hunt alone

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Speaker 1: and they can jump on a milk's back and kill it.

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Speaker 1: Wolves don't have that advantage. Every time a wolf has

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Speaker 1: to eat, they have to catch a fleeing hoofed mammal

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Speaker 1: with their mouth. Think about it, if you had you

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Speaker 1: want to get a milk steak, you had to catch

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Speaker 1: that elk with your teeth. How successfully you think you

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Speaker 1: would be you'd want a lot of buddies. Yeah, that's

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Speaker 1: why they're they're cooperative, obligatory hunters. They're obliged to cooperate

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Speaker 1: to eat, and their prey base determines the size of

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Speaker 1: the pack. If they were mostly praying on white tailed deer,

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Speaker 1: the packs maybe smaller. If they're praying on mooser elk,

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Speaker 1: the packs maybe larger, but it actually just came from

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Speaker 1: ill the stone and um Erk mcintaro showed me this

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Speaker 1: amazing photo that Doug Smith took of wolf nine eleven.

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Speaker 1: It was a clean jock because the wolf was killed,

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Speaker 1: but he had broken his jaw completely in half, disarticulated,

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Speaker 1: most most likely got kicked. They saw this massive fight.

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Speaker 1: This wolf tried to kill an elk and it nearly

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Speaker 1: got killed. And the wolf was underwater for a long

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Speaker 1: time and the elk was stomping it, and it finally

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Speaker 1: came up out of the water and crawled away. Four

358
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Speaker 1: months later, I get back to the jaw. Four months later,

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Speaker 1: this wolf by itself had killed an elk in the river.

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Speaker 1: They had photos of this interaction. And while it was

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Speaker 1: there with this elk, a pack of eight wolves came

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Speaker 1: along and killed the wolf. The wolf stood his ground

363
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Speaker 1: to defend the milk, and it was killed by this pack.

364
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Speaker 1: So after they had killed it, they got the skull

365
00:18:59,680 --> 00:19:03,000
Speaker 1: back this jaw from the first elk, and counter was

366
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Speaker 1: broken completely in half, and it healed and was all

367
00:19:05,880 --> 00:19:10,040
Speaker 1: gnarly in kelcifite and completely separate, completely separate, and they

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Speaker 1: watched it pulled out and kill this elk by itself.

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Speaker 1: People don't think that wolves suffer. I just think. I mean,

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Speaker 1: if you had a broken jaw that you could never

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Speaker 1: heal and you had to catch things with your mouth, man,

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Speaker 1: I'd beat starved very quickly myself. They have that, and

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Speaker 1: lots of wolves that are flying turn up dead. We

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Speaker 1: had this discussion again over dinner last night. Things was

375
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Speaker 1: a great dinner conversation. Things you find in dead wolves? Wow,

376
00:19:33,960 --> 00:19:37,240
Speaker 1: we were talking all these glary stories. But they suffer

377
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Speaker 1: a lot of injuries in a daily life. So the

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Speaker 1: eight that killed them, they were not affiliated. They were different,

379
00:19:43,600 --> 00:19:47,400
Speaker 1: a different pack, So yeah, did they were? They cannibalize

380
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Speaker 1: them when they kill them. They don't know. I it's

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Speaker 1: very very very rare that you ever hear that they

382
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Speaker 1: kill them And Durham, I mean it. They're not so

383
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Speaker 1: different from us. They defend their home turf, they defend

384
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Speaker 1: their terror tory, and when trespassers come in, if they

385
00:20:02,560 --> 00:20:05,280
Speaker 1: can catch him, they'll kill them. Some most times sometimes

386
00:20:05,280 --> 00:20:07,800
Speaker 1: they drive them out. It's kind of depends on the

387
00:20:07,920 --> 00:20:12,120
Speaker 1: leadership of the pack that's larger might mix right, and

388
00:20:12,240 --> 00:20:15,760
Speaker 1: it depends on if it's if hormones, it tends a

389
00:20:15,840 --> 00:20:18,320
Speaker 1: breeding season depends on if they're missing an alpha breeder.

390
00:20:18,840 --> 00:20:20,879
Speaker 1: I mean this is how packs form. They do allow

391
00:20:20,920 --> 00:20:23,880
Speaker 1: other wolves, and sometimes, obviously because they have genetic exchange,

392
00:20:24,000 --> 00:20:27,359
Speaker 1: packs are not in bread. But most times when a

393
00:20:27,400 --> 00:20:31,360
Speaker 1: pack encounters a trespasser, they will chase it vigorously and

394
00:20:31,440 --> 00:20:34,480
Speaker 1: if they catch it, they'll kill it. Most times, did

395
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Speaker 1: the you know? Oftentimes I see that the people who

396
00:20:36,960 --> 00:20:40,800
Speaker 1: are who research and work on the Yellowstone Wolves, they

397
00:20:40,840 --> 00:20:45,080
Speaker 1: get very upset if a Yellowstone wolf leave the park

398
00:20:45,119 --> 00:20:46,960
Speaker 1: and gets killed by a hunter outside of the park.

399
00:20:47,200 --> 00:20:49,399
Speaker 1: Do they get really upset one one of their wolves

400
00:20:49,440 --> 00:20:51,800
Speaker 1: gets killed by wolves? Does that bother them? You have

401
00:20:51,840 --> 00:20:54,600
Speaker 1: to ask them. You never had that conversation with anyone.

402
00:20:55,320 --> 00:20:58,280
Speaker 1: I don't work down there, You're just there. I went

403
00:20:58,320 --> 00:21:02,280
Speaker 1: down there as a as a guest record. I mean

404
00:21:02,359 --> 00:21:06,439
Speaker 1: I watched there's a lot of wolves. Wolves die. The

405
00:21:06,440 --> 00:21:09,160
Speaker 1: biggest cause of mortality in Yellowstone Park is wolves killing

406
00:21:09,160 --> 00:21:12,040
Speaker 1: other wolves. Oh vast majority. Because there's no there's no

407
00:21:12,119 --> 00:21:14,960
Speaker 1: hunting or trapping within the park. They get killed by ungulates,

408
00:21:15,040 --> 00:21:19,119
Speaker 1: they drawn, they starve, they get parbo iristes temper. But

409
00:21:19,200 --> 00:21:21,720
Speaker 1: the biggest cause of mortality, and said Yellowstone Park is

410
00:21:21,800 --> 00:21:25,280
Speaker 1: wolves killing wolves and these usually these trustpass or inter

411
00:21:25,400 --> 00:21:29,160
Speaker 1: territorial strife things. Oh my goodness, yeah, packs come apart.

412
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Speaker 1: Packs form all through mortality. Do they mostly when wolves? Uh?

413
00:21:36,520 --> 00:21:42,720
Speaker 1: Like when wolves commit frature side? Is it mostly? Um?

414
00:21:43,080 --> 00:21:45,320
Speaker 1: Does it mostly occur as in fanticide? Like? Is it

415
00:21:45,320 --> 00:21:47,960
Speaker 1: mostly killing young? Or is it mostly killing old? Or

416
00:21:48,000 --> 00:21:51,880
Speaker 1: is it just nondiscriminate? First of all, I wouldn't put

417
00:21:51,880 --> 00:21:53,800
Speaker 1: the term fracture side on. I would say because they're

418
00:21:53,800 --> 00:21:58,000
Speaker 1: not friends. They're they're simply defending the resources, much like

419
00:21:58,119 --> 00:22:00,320
Speaker 1: we do in war, or much like you would defend

420
00:22:00,359 --> 00:22:02,879
Speaker 1: your home, or much like Chicago defends its people for

421
00:22:02,920 --> 00:22:05,840
Speaker 1: the police force or whatever. They defend their resources, whether

422
00:22:05,880 --> 00:22:09,200
Speaker 1: it's food or at home or whatever. There's no malice.

423
00:22:09,600 --> 00:22:14,880
Speaker 1: It's not done with usually forethought, although there have been incidences. Um,

424
00:22:15,000 --> 00:22:17,800
Speaker 1: they're generally not going to den's and digging out each

425
00:22:17,840 --> 00:22:20,600
Speaker 1: other's pops and killing them because the dens are They

426
00:22:20,720 --> 00:22:22,959
Speaker 1: generally do not do because the dens are protected by

427
00:22:22,960 --> 00:22:25,240
Speaker 1: the resident wolves. Why would you try and go in

428
00:22:25,280 --> 00:22:27,560
Speaker 1: and take on a pack with its pops, You'd be

429
00:22:27,640 --> 00:22:31,200
Speaker 1: you'd be killed. They do do that with coyotes. They

430
00:22:31,240 --> 00:22:35,600
Speaker 1: o coyotes and killer pops. That's done with forethought, and yeah,

431
00:22:35,640 --> 00:22:39,440
Speaker 1: that's a plan. But wolves just wolves, like any other

432
00:22:39,960 --> 00:22:43,879
Speaker 1: carnival remoteline. They dispatch each other's competitors, that's all it is.

433
00:22:43,880 --> 00:22:45,919
Speaker 1: That's why they don't generally eat the carcass. They just

434
00:22:46,000 --> 00:22:48,600
Speaker 1: kill them and move on. And I think you know people,

435
00:22:48,600 --> 00:22:51,480
Speaker 1: I give it, so it's nondiscriminatory. It's not like they

436
00:22:51,600 --> 00:22:54,240
Speaker 1: target the young because they're easier to kill, or the

437
00:22:54,280 --> 00:22:56,880
Speaker 1: old because they're easier to kill. It's just like opportunistically,

438
00:22:57,000 --> 00:22:59,439
Speaker 1: like do you have the advantage and you take a

439
00:22:59,680 --> 00:23:01,479
Speaker 1: take a vantage of the advantage. And I think this

440
00:23:01,560 --> 00:23:03,320
Speaker 1: is a question you have to ask the folks in

441
00:23:03,400 --> 00:23:06,440
Speaker 1: Yellowstone because they study this intimately. And I don't want

442
00:23:06,480 --> 00:23:09,359
Speaker 1: to be miscoded or lead people of stray. Sometimes the

443
00:23:09,400 --> 00:23:12,399
Speaker 1: alphas are killed because they're out front of the charge.

444
00:23:12,680 --> 00:23:15,600
Speaker 1: And I don't know the ratio of the percent of

445
00:23:15,640 --> 00:23:18,680
Speaker 1: animals are killed at home, anyam are young of the year, yearlings,

446
00:23:18,720 --> 00:23:21,399
Speaker 1: two year olds, alpha's I don't know that you have

447
00:23:21,440 --> 00:23:23,680
Speaker 1: to ask them. But that's the leads, that's the lead

448
00:23:23,760 --> 00:23:29,000
Speaker 1: cause inside the inside Yellowstone Park wolves, yes, they published

449
00:23:29,000 --> 00:23:31,640
Speaker 1: on that and outside of Yellowstone like where I live

450
00:23:31,840 --> 00:23:35,119
Speaker 1: over in western Montana. The lead causes human variety of

451
00:23:35,200 --> 00:23:40,480
Speaker 1: human causes, from hunting to vehicles, everything yep, or complaints yep.

452
00:23:40,800 --> 00:23:43,440
Speaker 1: Do you count livestock complaints as human Yeah, I guess

453
00:23:43,440 --> 00:23:48,720
Speaker 1: you would. Sure, Yeah, I mean wildlife services, UM trains, vehicles, hunting,

454
00:23:48,840 --> 00:23:53,040
Speaker 1: trapping trains. Yeah, they get by trains occasionally, and I

455
00:23:53,040 --> 00:23:55,159
Speaker 1: think in those cases they're probably feeding on animals have

456
00:23:55,240 --> 00:23:59,360
Speaker 1: been hit on the track. There's a cost. So let's

457
00:23:59,400 --> 00:24:01,800
Speaker 1: let's back up and pick up your biography again. So

458
00:24:02,119 --> 00:24:06,320
Speaker 1: you work up in Minnesota. I did, And what happened then?

459
00:24:06,760 --> 00:24:08,320
Speaker 1: You were just like you were a grad student, right,

460
00:24:08,480 --> 00:24:11,760
Speaker 1: So it was really pretty interesting point in my life. Yeah,

461
00:24:11,880 --> 00:24:16,040
Speaker 1: I was a young undergraduate and I just graduated. I

462
00:24:16,080 --> 00:24:18,840
Speaker 1: was still a student when I took on in nineteen

463
00:24:18,840 --> 00:24:22,080
Speaker 1: seventy seven working for Dave Beach, and then the summer

464
00:24:22,080 --> 00:24:25,640
Speaker 1: of nineteen seventy nine, I just finished goal graduated. I

465
00:24:25,680 --> 00:24:28,600
Speaker 1: was working for Steve Fritz up in northern Minnesota in

466
00:24:28,600 --> 00:24:32,000
Speaker 1: a very very tiny, very conservative, little small farming community.

467
00:24:32,320 --> 00:24:35,399
Speaker 1: I was hired as a federal trapper do trap and

468
00:24:35,440 --> 00:24:40,600
Speaker 1: remove livestock depredating wolves. So federal with Wildlife Services, US

469
00:24:40,640 --> 00:24:43,040
Speaker 1: Fish and Wilife Service would be like wildlife services. Okay,

470
00:24:43,680 --> 00:24:46,720
Speaker 1: So for me, I mean growing up a little bit storry,

471
00:24:46,800 --> 00:24:49,240
Speaker 1: I didn't really interested in research. All of a sudden,

472
00:24:49,240 --> 00:24:52,480
Speaker 1: I was thrust into this world of wolf conflict and

473
00:24:52,560 --> 00:24:55,800
Speaker 1: management and mitigation. And wolves were still they were threatened,

474
00:24:55,920 --> 00:24:59,640
Speaker 1: so the landowners couldn't take it into their own hands

475
00:24:59,680 --> 00:25:01,439
Speaker 1: like we can here, but they had to call in

476
00:25:01,920 --> 00:25:04,200
Speaker 1: the game warden like that. When you say threatened, they were,

477
00:25:04,200 --> 00:25:07,080
Speaker 1: they were, Yet there were any yes, listed as a

478
00:25:07,119 --> 00:25:10,840
Speaker 1: threatened species, and so um I was be called. The

479
00:25:10,840 --> 00:25:12,440
Speaker 1: game weren't to be called. I'd be called, and we

480
00:25:12,560 --> 00:25:14,760
Speaker 1: go out to the farm. They weren't called ranches. They

481
00:25:14,760 --> 00:25:17,080
Speaker 1: were called farms, and it was dairy cattle and beef.

482
00:25:17,560 --> 00:25:19,800
Speaker 1: We would look at the carcass and determine if wolves

483
00:25:19,800 --> 00:25:22,680
Speaker 1: had killed it or not through tracks, the nature of

484
00:25:22,720 --> 00:25:24,639
Speaker 1: the bite, wounds, wed skin the cow and whatever. You

485
00:25:24,680 --> 00:25:26,439
Speaker 1: could tell what it killed it? What would you what

486
00:25:26,520 --> 00:25:29,560
Speaker 1: was the most? Uh? Tell me a couple of telltale

487
00:25:29,560 --> 00:25:33,800
Speaker 1: signs that it was wolf? Um tracks? Uh? Leading to

488
00:25:34,040 --> 00:25:37,639
Speaker 1: with the chase scene with bites the bite marks. I

489
00:25:37,640 --> 00:25:39,560
Speaker 1: mean you can't just because wolf tracks are there, doesn't

490
00:25:39,560 --> 00:25:41,880
Speaker 1: mean they killed it, but you go on, you'd skin

491
00:25:41,920 --> 00:25:43,960
Speaker 1: out the cow and you'd see the bite marks in

492
00:25:44,080 --> 00:25:46,280
Speaker 1: various places. And if they had hemorrhaging around them, the

493
00:25:46,320 --> 00:25:49,639
Speaker 1: animal was alive when it was bitten, no hemorrhaging. They

494
00:25:49,680 --> 00:25:51,959
Speaker 1: were feeding on a dead call. So you look for

495
00:25:52,000 --> 00:25:55,000
Speaker 1: that um scats full of cow hair, but you have

496
00:25:55,080 --> 00:25:57,960
Speaker 1: to find the bite wounds. So that was tough because

497
00:25:58,000 --> 00:26:01,320
Speaker 1: if they took a small calf, there wouldn't be any

498
00:26:01,359 --> 00:26:04,600
Speaker 1: thing there, there'd be nothing. Sometimes they take it apart

499
00:26:04,640 --> 00:26:08,800
Speaker 1: and it would be gone overnight. What's the window of opportunity? Um?

500
00:26:08,920 --> 00:26:11,200
Speaker 1: How many how many hours days do you have before

501
00:26:11,200 --> 00:26:13,120
Speaker 1: it becomes too late? Well, it depends on if it's

502
00:26:13,160 --> 00:26:16,160
Speaker 1: a you know, a thousand pound cora eighty pound calf.

503
00:26:16,359 --> 00:26:18,560
Speaker 1: So as soon as you get the call, you go

504
00:26:18,640 --> 00:26:21,720
Speaker 1: out there. And because they were smaller operations, they generally

505
00:26:21,920 --> 00:26:25,199
Speaker 1: could see their livestock. But we're in the West, we

506
00:26:25,240 --> 00:26:27,600
Speaker 1: have allotments and you know, you don't see your stock

507
00:26:28,080 --> 00:26:31,360
Speaker 1: sometimes for weeks um. So people were pretty on top

508
00:26:31,400 --> 00:26:33,960
Speaker 1: of it, but it was it was a really interesting

509
00:26:34,000 --> 00:26:37,760
Speaker 1: turning point for me and my education that you know, yeah, Diane,

510
00:26:37,760 --> 00:26:41,720
Speaker 1: wolves or do cause problems and people don't really love them.

511
00:26:41,760 --> 00:26:44,239
Speaker 1: And just because you had this wonderful research experience, you's

512
00:26:44,280 --> 00:26:46,320
Speaker 1: a whole another world out there. So it was really

513
00:26:46,359 --> 00:26:48,280
Speaker 1: important for me growing in my career. And I had

514
00:26:48,320 --> 00:26:50,800
Speaker 1: to drop these wolves that were killing stock and we

515
00:26:50,840 --> 00:26:53,400
Speaker 1: hauled them down to ground rapids where they were euthanized.

516
00:26:54,280 --> 00:26:59,199
Speaker 1: Um really, yep, Why why would you move them to

517
00:26:59,200 --> 00:27:01,280
Speaker 1: euthanize them? Because at that point in time, we weren't

518
00:27:01,280 --> 00:27:04,360
Speaker 1: allowed to shoot them, So how would you transport them?

519
00:27:04,440 --> 00:27:06,840
Speaker 1: I drugged them. I'd catch them, I sedate them and

520
00:27:06,920 --> 00:27:09,879
Speaker 1: put them in a crate at home to Grand Rapids,

521
00:27:09,920 --> 00:27:12,000
Speaker 1: which was very close, and then they would be a

522
00:27:12,520 --> 00:27:15,879
Speaker 1: Grand Rapids Minnesota. Yeah, okay, that all right? That was

523
00:27:15,920 --> 00:27:18,280
Speaker 1: confusing Minnesota. Yeah, I got you. Yeah. How many when

524
00:27:18,320 --> 00:27:21,320
Speaker 1: you're doing that work? Howming did you catch that summer? Oh?

525
00:27:21,400 --> 00:27:23,600
Speaker 1: If you are handful, I don't know how many. It was.

526
00:27:23,640 --> 00:27:25,600
Speaker 1: It wasn't a lot, but it was enough that I

527
00:27:25,600 --> 00:27:27,960
Speaker 1: could do my job. There wasn't a lot of complaints,

528
00:27:27,960 --> 00:27:30,439
Speaker 1: to be real honest, And Steve Fritz, my boss, had

529
00:27:30,480 --> 00:27:33,359
Speaker 1: told me, well, when you have times when there aren't complaints,

530
00:27:33,800 --> 00:27:35,560
Speaker 1: then I want you to call it in radio collar

531
00:27:35,640 --> 00:27:38,320
Speaker 1: for research. So I was dropping all summer. So I

532
00:27:38,359 --> 00:27:40,639
Speaker 1: don't know ten fifteen wolves. I mean, it wasn't that

533
00:27:40,760 --> 00:27:43,520
Speaker 1: just wasn't that much problems, to be real, honest. But

534
00:27:43,600 --> 00:27:47,240
Speaker 1: if you were the particular farmer that was having the problem,

535
00:27:47,280 --> 00:27:51,159
Speaker 1: it was pretty significant to you. And certain farms chronically

536
00:27:51,200 --> 00:27:54,040
Speaker 1: had problems, in certain farms never had problems, and they

537
00:27:54,080 --> 00:27:56,720
Speaker 1: could be four miles apart. You might not be comfortable

538
00:27:56,760 --> 00:28:00,959
Speaker 1: answering this, but go back to those days, das, Okay,

539
00:28:01,000 --> 00:28:06,000
Speaker 1: those days in that place. Um, if you run cattle

540
00:28:06,119 --> 00:28:08,120
Speaker 1: or have cows, they die from all sorts of things.

541
00:28:08,119 --> 00:28:11,639
Speaker 1: They died during they died during birth, Okay, they just

542
00:28:11,680 --> 00:28:14,200
Speaker 1: get hung up in fences and die, They hit by cars,

543
00:28:14,240 --> 00:28:17,720
Speaker 1: all kinds of plants, poisonous plants, there's another one. Did

544
00:28:17,800 --> 00:28:23,840
Speaker 1: you find then, that for a farmer or rancher to

545
00:28:24,000 --> 00:28:28,600
Speaker 1: lose an animal to a wolf seemed to weigh on

546
00:28:28,680 --> 00:28:32,440
Speaker 1: them more heavily or inspire more rage in them than

547
00:28:32,560 --> 00:28:36,119
Speaker 1: if they were to lose one too poisonous plants, or

548
00:28:36,160 --> 00:28:38,440
Speaker 1: lose one to getting hit by a car because it

549
00:28:38,520 --> 00:28:41,280
Speaker 1: jump the fence, or any number of other causes. Did

550
00:28:41,280 --> 00:28:43,240
Speaker 1: you feel that it was that there was an imbalance

551
00:28:43,320 --> 00:28:49,520
Speaker 1: about how people perceived that death. Yeah, and some people

552
00:28:49,560 --> 00:28:51,600
Speaker 1: there definitely was. And I think a big part of

553
00:28:51,600 --> 00:28:54,480
Speaker 1: it was because they had no ability to control those

554
00:28:54,520 --> 00:28:58,760
Speaker 1: wolves legally, so they couldn't do much about it. So

555
00:28:58,880 --> 00:29:02,200
Speaker 1: when they had the wolf was recovering because they were

556
00:29:02,200 --> 00:29:06,320
Speaker 1: protected and they couldn't do anything, and they might have literally,

557
00:29:06,360 --> 00:29:09,120
Speaker 1: they might literally be seeing wolves in their pen tearing

558
00:29:09,200 --> 00:29:12,640
Speaker 1: some calf or cow apart, and legally, you know, they

559
00:29:12,640 --> 00:29:15,400
Speaker 1: weren't supposed to be doing anything about it, so that

560
00:29:15,480 --> 00:29:19,160
Speaker 1: that sense of helplessness made it worse. Now Here in

561
00:29:19,200 --> 00:29:21,560
Speaker 1: the West Montana, I mean, if a rancher's got to

562
00:29:22,360 --> 00:29:24,720
Speaker 1: wolves and the pan are about to chase cows or whatever,

563
00:29:24,720 --> 00:29:26,560
Speaker 1: they don't even you know, they can take care of it.

564
00:29:26,920 --> 00:29:29,000
Speaker 1: They can shoot them legally and they just call and

565
00:29:29,040 --> 00:29:32,000
Speaker 1: report it. It's called a Senate built two hundred. They're

566
00:29:32,120 --> 00:29:34,960
Speaker 1: legally protective. They can't keep the hide or anything, but

567
00:29:35,320 --> 00:29:36,720
Speaker 1: we go pick it up and it's over and it

568
00:29:37,320 --> 00:29:44,760
Speaker 1: helps diffuse animosity. What was your next move from So

569
00:29:44,800 --> 00:29:46,800
Speaker 1: you did that one summer? So while I was there,

570
00:29:47,120 --> 00:29:49,400
Speaker 1: I just you know, graduated, like I said, I applied

571
00:29:49,440 --> 00:29:51,440
Speaker 1: to graduate schools, and while I was working in northern

572
00:29:51,440 --> 00:29:56,040
Speaker 1: Minnesota on this wildlife services job. I got accepted at

573
00:29:56,040 --> 00:29:59,240
Speaker 1: the University of Montana for graduate school in the fall.

574
00:29:59,400 --> 00:30:02,560
Speaker 1: So when I departed Minnesota, I packed at my little

575
00:30:02,600 --> 00:30:05,440
Speaker 1: car and I drove to Missoula, where I had the

576
00:30:06,080 --> 00:30:09,600
Speaker 1: graduate project. And it was really interesting because I just

577
00:30:09,640 --> 00:30:12,960
Speaker 1: came from all this whirlwind of two years of intensive

578
00:30:13,000 --> 00:30:18,200
Speaker 1: wolf research and university college ecology classes and and now

579
00:30:18,240 --> 00:30:20,680
Speaker 1: this new world of this conflicts going on, and we

580
00:30:20,760 --> 00:30:24,640
Speaker 1: had this opportunity in Montana. In nine was there was

581
00:30:24,800 --> 00:30:29,680
Speaker 1: one wolf outside of Minnesota, west of Mississippi, and we

582
00:30:29,720 --> 00:30:32,680
Speaker 1: had the university to put a collar on it, just

583
00:30:32,800 --> 00:30:35,520
Speaker 1: north of Glacier Park, like six seven miles and that

584
00:30:35,600 --> 00:30:40,000
Speaker 1: wolf tiptoed down occasionally into Glacier Park, and that was

585
00:30:40,040 --> 00:30:43,920
Speaker 1: the only wolf in the west and the only one

586
00:30:44,320 --> 00:30:47,800
Speaker 1: they tried to come down female, And Bob Ream named

587
00:30:47,800 --> 00:30:50,600
Speaker 1: her Kishnina after a creek that was just north of

588
00:30:50,640 --> 00:30:55,280
Speaker 1: Glacier And so people don't realize those wolves walked down

589
00:30:56,280 --> 00:30:58,840
Speaker 1: out there seventy nine and so she came down into

590
00:30:58,840 --> 00:31:01,000
Speaker 1: the northwest corner of Glacier Park and a few wolves

591
00:31:01,000 --> 00:31:03,160
Speaker 1: have been trickling down me and wolves here and there.

592
00:31:03,160 --> 00:31:06,600
Speaker 1: He had a wolf shot you're on Montana occasionally, but

593
00:31:06,640 --> 00:31:09,240
Speaker 1: they never stuck. They're just they weren't allowed to stay

594
00:31:09,240 --> 00:31:12,160
Speaker 1: at the wolves walking in on their own from camp.

595
00:31:12,160 --> 00:31:15,440
Speaker 1: They absolutely walk. So for me to do a master's project,

596
00:31:15,480 --> 00:31:17,280
Speaker 1: I had to think of some kind of an interesting

597
00:31:17,320 --> 00:31:20,160
Speaker 1: project so we can monitor this wolf and still have

598
00:31:20,360 --> 00:31:22,600
Speaker 1: enough data. So what I did was, they decided I'm

599
00:31:22,600 --> 00:31:24,080
Speaker 1: going to look at because I was a good trapper,

600
00:31:24,560 --> 00:31:27,040
Speaker 1: I decided I would look at this wolf and compare

601
00:31:27,120 --> 00:31:30,760
Speaker 1: her food selection, at rice selection, and habitat use with

602
00:31:30,840 --> 00:31:34,080
Speaker 1: coyotes within her territory and outside of her territory. So

603
00:31:34,160 --> 00:31:35,760
Speaker 1: I caught and call it a lot of coyotes. In

604
00:31:35,760 --> 00:31:38,040
Speaker 1: the meantime, I kept trying to catch more wolves, and

605
00:31:38,080 --> 00:31:40,400
Speaker 1: there weren't any. So that was the core of my

606
00:31:40,480 --> 00:31:43,480
Speaker 1: master's thesis. But I was fascinating how they were interacting

607
00:31:43,520 --> 00:31:46,000
Speaker 1: on the landscape. Now, when you were doing that, you

608
00:31:46,000 --> 00:31:49,920
Speaker 1: you presumably had like a course load you had to do. Yes,

609
00:31:50,120 --> 00:31:52,120
Speaker 1: how did you balance that with being in the class

610
00:31:52,200 --> 00:31:54,200
Speaker 1: Like one hand, you're in some classroom with a bunch

611
00:31:54,200 --> 00:31:56,320
Speaker 1: of ding bat students, right, and then the next in

612
00:31:56,360 --> 00:31:59,200
Speaker 1: the other hand, you're up trapping wolves. I alternated with

613
00:31:59,440 --> 00:32:01,200
Speaker 1: queer in the order system. Then so I do a

614
00:32:01,240 --> 00:32:02,840
Speaker 1: quarter in the field and then a quarterer in school

615
00:32:02,840 --> 00:32:04,320
Speaker 1: in the quarter in the field, and go back and

616
00:32:04,360 --> 00:32:07,280
Speaker 1: forth through around through two and a half years. So

617
00:32:07,320 --> 00:32:10,280
Speaker 1: I had to read the classroom part. No, I didn't.

618
00:32:10,280 --> 00:32:13,840
Speaker 1: Actually it was interesting to me, and great professor's back

619
00:32:13,840 --> 00:32:16,560
Speaker 1: then class I'm not hacking. I went to graduate school

620
00:32:17,600 --> 00:32:21,160
Speaker 1: Jouncle Barto Gara, Bobbery and all these old wonderful guys

621
00:32:21,200 --> 00:32:25,440
Speaker 1: who were real good mentors. So no, but I was

622
00:32:25,600 --> 00:32:28,080
Speaker 1: always Jones and to get back, always Jones, going to

623
00:32:28,120 --> 00:32:30,760
Speaker 1: get back up the North Fork. And that Collard, the

624
00:32:30,800 --> 00:32:32,760
Speaker 1: Collard female that you had that was coming down. You

625
00:32:32,760 --> 00:32:34,840
Speaker 1: guys are getting data off that it was still a

626
00:32:34,840 --> 00:32:38,000
Speaker 1: good college. Yeah yeah, and um it's it died out

627
00:32:38,440 --> 00:32:40,560
Speaker 1: in about a year and a half. It should have

628
00:32:40,640 --> 00:32:43,040
Speaker 1: lasted longer, but it didn't. But we continued to see

629
00:32:43,800 --> 00:32:46,000
Speaker 1: tracks of a female because you can tell by the

630
00:32:46,040 --> 00:32:49,120
Speaker 1: yur nation and the snow through her territory throughout the

631
00:32:49,120 --> 00:32:51,520
Speaker 1: winter and using the same travel routes. I mean, I'm

632
00:32:51,520 --> 00:32:54,720
Speaker 1: sure it was her. And then the next she met

633
00:32:54,720 --> 00:32:56,760
Speaker 1: a mate the next year and they produced the first

634
00:32:56,840 --> 00:33:02,719
Speaker 1: litter in mate in what country Canada, of course, so

635
00:33:02,800 --> 00:33:05,200
Speaker 1: just north the glacier. They did, just north the glacier.

636
00:33:05,240 --> 00:33:07,280
Speaker 1: How many miles outside of how many miles north of

637
00:33:07,280 --> 00:33:11,320
Speaker 1: the border, seven or eight? And she's flirting with the border.

638
00:33:11,560 --> 00:33:16,360
Speaker 1: She's flirting. Yeah, she crossed occasionally. So um her died

639
00:33:16,600 --> 00:33:21,600
Speaker 1: that summer and she it was captured inadvertently in a

640
00:33:21,640 --> 00:33:28,640
Speaker 1: barret trap in Canada. They were researching trap research. So

641
00:33:28,720 --> 00:33:32,760
Speaker 1: this female raised she had seven pups, half for gray,

642
00:33:32,760 --> 00:33:35,720
Speaker 1: half for black, with no help. We were worried about

643
00:33:35,720 --> 00:33:41,040
Speaker 1: her their survival because she was really remarkably um proficient,

644
00:33:41,080 --> 00:33:43,440
Speaker 1: apparently because no one was feeding her. I mean this

645
00:33:43,480 --> 00:33:46,480
Speaker 1: was out where their oil gas exploration and log trucks

646
00:33:46,520 --> 00:33:50,200
Speaker 1: and wilderness and wild things and lots of game. And

647
00:33:50,440 --> 00:33:52,640
Speaker 1: by that winner we would still see tracks in snow

648
00:33:52,640 --> 00:33:55,720
Speaker 1: of eight wolves. So they all made it. And then

649
00:33:55,840 --> 00:33:58,920
Speaker 1: about two years later another female came in and the

650
00:33:58,920 --> 00:34:02,000
Speaker 1: next letter was born in five. And then in nighties

651
00:34:02,120 --> 00:34:06,400
Speaker 1: six they moved more down to the park a lot

652
00:34:06,960 --> 00:34:10,759
Speaker 1: and an eighty six the first pack was born in

653
00:34:10,840 --> 00:34:14,480
Speaker 1: Glacier Park in over fifty years first litter, so that's

654
00:34:14,480 --> 00:34:17,400
Speaker 1: the progression kind of went from like one to two

655
00:34:17,440 --> 00:34:22,200
Speaker 1: to seven to fourteen and then they just kept expanding.

656
00:34:22,200 --> 00:34:25,800
Speaker 1: But all of those wolves, all of those wolves prior

657
00:34:25,840 --> 00:34:29,960
Speaker 1: to reintroductions in the bark in Idaho, they all walked

658
00:34:30,040 --> 00:34:33,799
Speaker 1: down and nobody brought them. Nobody brought those wolves. And

659
00:34:33,840 --> 00:34:37,840
Speaker 1: it's so hard people don't grasp that I was there.

660
00:34:38,440 --> 00:34:41,480
Speaker 1: I know that there were many of us hard, you know,

661
00:34:41,560 --> 00:34:45,520
Speaker 1: volunteers and students and starving technicians, following these tracks around,

662
00:34:45,600 --> 00:34:49,120
Speaker 1: and we know that they were not brought there did

663
00:34:49,880 --> 00:34:51,719
Speaker 1: so I didn't know that. I know that people like

664
00:34:51,760 --> 00:34:54,840
Speaker 1: are up there up in arms about the Yellowstone wolves

665
00:34:54,880 --> 00:34:57,000
Speaker 1: being brought there, but there are sort of I guess

666
00:34:57,040 --> 00:34:59,839
Speaker 1: would you'd call them a conspiracy theorist that people think

667
00:34:59,840 --> 00:35:02,400
Speaker 1: that those wolves up there were brought into and they

668
00:35:02,440 --> 00:35:04,680
Speaker 1: didn't walk in. I don't know what you'd call it,

669
00:35:04,680 --> 00:35:06,600
Speaker 1: because I'm not a believer in it. I mean, I'm

670
00:35:06,680 --> 00:35:10,400
Speaker 1: the factual check fact checker there. I was there, and

671
00:35:10,520 --> 00:35:13,319
Speaker 1: they were native. And the interesting thing was, while we

672
00:35:13,320 --> 00:35:15,080
Speaker 1: were killing off her wolves down here, there was a

673
00:35:15,080 --> 00:35:18,880
Speaker 1: big program in southwestern Elbird in southeastern BC to poison

674
00:35:18,920 --> 00:35:21,719
Speaker 1: off wolves. So in the sixties, by the late sixties,

675
00:35:21,960 --> 00:35:24,560
Speaker 1: there basically was kind of a wolf free zone, right

676
00:35:24,600 --> 00:35:27,960
Speaker 1: around the international border. So when Kishnina arrived, she had

677
00:35:27,960 --> 00:35:31,760
Speaker 1: to come some distance, maybe Jasper, but at least mamp

678
00:35:32,400 --> 00:35:34,799
Speaker 1: She had to run that gauntlet down through all these

679
00:35:34,920 --> 00:35:38,239
Speaker 1: hazards and she made it. Yeah. Well, a mountain lion

680
00:35:38,560 --> 00:35:40,719
Speaker 1: you know about this recently left the Black Hills of

681
00:35:40,760 --> 00:35:45,320
Speaker 1: South Dakota and got hit by car and Connecticut it's nothing.

682
00:35:45,360 --> 00:35:47,440
Speaker 1: And so when my tracking, so I call her this

683
00:35:47,480 --> 00:35:51,600
Speaker 1: one little wolf in Glacier and we had her in

684
00:35:51,640 --> 00:35:53,080
Speaker 1: the area for a year and a half and I

685
00:35:53,120 --> 00:35:54,840
Speaker 1: caught her again and I replaced her. Call her. She

686
00:35:54,920 --> 00:35:57,000
Speaker 1: was not very big, and she was an average small

687
00:35:57,080 --> 00:36:00,239
Speaker 1: female And like, what tell me this eight pounds? What's

688
00:36:00,280 --> 00:36:05,200
Speaker 1: a big male? So the biggest wolf I've ever caught pounds,

689
00:36:05,200 --> 00:36:07,080
Speaker 1: which is almost as much as I weigh. So it's

690
00:36:07,360 --> 00:36:13,319
Speaker 1: pretty amazing when you see hundred and fifty pound is

691
00:36:13,360 --> 00:36:17,680
Speaker 1: like the two and I'll yes, I'll get there. But

692
00:36:17,719 --> 00:36:19,920
Speaker 1: what I want to say about this one wolf is

693
00:36:19,960 --> 00:36:23,600
Speaker 1: she she was collared and then she floated around again.

694
00:36:23,600 --> 00:36:25,480
Speaker 1: She'd been for a year and then she just disappeared

695
00:36:25,480 --> 00:36:27,399
Speaker 1: and we couldn't find her. And that happens with these

696
00:36:27,480 --> 00:36:29,840
Speaker 1: VHF collars because they're not GPS collars and you have

697
00:36:29,920 --> 00:36:32,040
Speaker 1: to physically go out and listen for the signal with

698
00:36:32,080 --> 00:36:35,600
Speaker 1: airplanes and ground whatever. She was shot seven months later

699
00:36:36,040 --> 00:36:39,600
Speaker 1: at Poosh Push Poosh Coupe, which is up very in

700
00:36:39,680 --> 00:36:43,719
Speaker 1: northern Alberta b C area, which is north of where

701
00:36:43,760 --> 00:36:46,680
Speaker 1: some of these wolves to Mellowstone were captured to bring down.

702
00:36:47,120 --> 00:36:49,799
Speaker 1: So the moral of the story is that wolf was

703
00:36:49,840 --> 00:36:53,480
Speaker 1: connected with wolves further north than these wolves were taken

704
00:36:53,520 --> 00:36:58,040
Speaker 1: for reintroduction. They are one species here, one population. They

705
00:36:58,080 --> 00:37:03,080
Speaker 1: are not different. Okay, Okay, you're getting That's great, You're

706
00:37:03,080 --> 00:37:05,200
Speaker 1: getting ahead of me a little bit. I'm just sorry.

707
00:37:05,239 --> 00:37:07,239
Speaker 1: I want to back up hit a couple points. Okay, No,

708
00:37:07,320 --> 00:37:08,239
Speaker 1: I want to get to that. I want to get

709
00:37:08,239 --> 00:37:10,360
Speaker 1: to the super Bowl thing. I want to we hat

710
00:37:10,440 --> 00:37:12,040
Speaker 1: to like set the table for that one a little bit.

711
00:37:14,400 --> 00:37:19,760
Speaker 1: The urination pattern females between their legs, males and female

712
00:37:19,800 --> 00:37:21,880
Speaker 1: like a spade female dog will razor leg, but it

713
00:37:21,920 --> 00:37:23,640
Speaker 1: doesn't go up high on it tree, you know what

714
00:37:23,719 --> 00:37:25,479
Speaker 1: I mean. They mark a little snow bank or something

715
00:37:26,080 --> 00:37:28,600
Speaker 1: spade female does. So you can tell from the urine

716
00:37:28,600 --> 00:37:31,920
Speaker 1: pattern from the tracks relative to the where the piss lands.

717
00:37:32,560 --> 00:37:38,240
Speaker 1: You can tell somewhat age of the female, not age,

718
00:37:38,320 --> 00:37:40,799
Speaker 1: you can tell if she's dominant or not dominant, meaning

719
00:37:40,880 --> 00:37:44,400
Speaker 1: within her social structure. And an old female doesn't necessarily

720
00:37:44,480 --> 00:37:46,520
Speaker 1: the dominant one. So what does the dominant one due

721
00:37:46,560 --> 00:37:49,759
Speaker 1: to raised leg your nation. But it's just you know,

722
00:37:49,840 --> 00:37:52,040
Speaker 1: the squat and raise their little leg up because you

723
00:37:52,080 --> 00:37:54,560
Speaker 1: don't off to more of an angle, just a little

724
00:37:54,560 --> 00:37:57,080
Speaker 1: to the side. It's not quite between their legs. Is

725
00:37:57,120 --> 00:37:59,759
Speaker 1: she There's no way to know. But is it that

726
00:38:00,040 --> 00:38:04,319
Speaker 1: she's mimicking a male? Like? What is that? Like? Why

727
00:38:04,320 --> 00:38:06,160
Speaker 1: does a dominant female raiser leg a little bit? You

728
00:38:06,160 --> 00:38:09,480
Speaker 1: ever seen a spade female dog do that. I've had

729
00:38:09,520 --> 00:38:11,440
Speaker 1: spade female dogs that do that, and they had a

730
00:38:11,480 --> 00:38:13,400
Speaker 1: Spade female dog. But I just I feel like she

731
00:38:13,440 --> 00:38:16,200
Speaker 1: would just squat. Okay, well, she probably wasn't a very

732
00:38:16,200 --> 00:38:21,720
Speaker 1: dominant dog. No, I was dominant man, see, as should

733
00:38:21,840 --> 00:38:25,239
Speaker 1: be with dogs. But so the dominant thing, it's just

734
00:38:25,440 --> 00:38:28,840
Speaker 1: it's a higher mark, higher in the leanscape, more visible,

735
00:38:28,920 --> 00:38:33,560
Speaker 1: more detectable. They may have a higher androgen level in

736
00:38:33,600 --> 00:38:36,680
Speaker 1: their body. It's like a female dog doesn't have much estrogen.

737
00:38:36,800 --> 00:38:40,520
Speaker 1: They tend to start raising their leg. It's just that way.

738
00:38:40,600 --> 00:38:44,040
Speaker 1: It's just behaviorally, but more dominant the mark, the more

739
00:38:44,080 --> 00:38:48,320
Speaker 1: dominant the animal. Okay, I know this isn't the most importance.

740
00:38:48,760 --> 00:38:50,800
Speaker 1: Have you ever seen where a female was dominant and

741
00:38:50,800 --> 00:38:54,000
Speaker 1: then lost dominance and stopped raising her leg or once

742
00:38:54,040 --> 00:38:56,920
Speaker 1: they start they never stop. I never. I didn't get

743
00:38:56,960 --> 00:38:58,360
Speaker 1: to see the wolves in the North Fork of the

744
00:38:58,360 --> 00:39:01,200
Speaker 1: Flathead like Minnesota, because it's so forced. That's a question

745
00:39:01,239 --> 00:39:03,440
Speaker 1: for Yellowstone where they can actually see them out in

746
00:39:03,440 --> 00:39:07,480
Speaker 1: the I'm sure they published papers, they're probably documented. I

747
00:39:07,520 --> 00:39:11,040
Speaker 1: don't know. The male, of course, raised like urinates, and

748
00:39:11,239 --> 00:39:13,840
Speaker 1: a dominant male will make a very high mark and

749
00:39:13,920 --> 00:39:16,160
Speaker 1: tail flag and just be like, oh, I'm just the

750
00:39:16,200 --> 00:39:19,200
Speaker 1: boss up. So they'd like to they like to urinate

751
00:39:19,280 --> 00:39:21,440
Speaker 1: on a on a poster or tree. Yeah, in a

752
00:39:21,600 --> 00:39:25,680
Speaker 1: in a real subordinate mail might actually squat urinate when

753
00:39:25,719 --> 00:39:29,200
Speaker 1: he's younger, especially, but yeah, the higher the mark, the

754
00:39:29,280 --> 00:39:34,560
Speaker 1: higher the status. Nice. Um, then that was behind on

755
00:39:34,560 --> 00:39:38,400
Speaker 1: another thing too. Oh, let's not get into the superwolf

756
00:39:39,160 --> 00:39:42,960
Speaker 1: the suit. No, we're gonna get there the superwolf conspiracy theory.

757
00:39:43,719 --> 00:39:47,439
Speaker 1: If that I don't know that that's a conspiracy theory, right, Yeah, okay,

758
00:39:47,480 --> 00:39:49,719
Speaker 1: so we're gonna get into that see. You know what's

759
00:39:49,760 --> 00:39:53,040
Speaker 1: funny is you might learn from us. You might learn

760
00:39:54,080 --> 00:39:56,719
Speaker 1: um besides us just learning everything from you, you might

761
00:39:56,800 --> 00:40:00,960
Speaker 1: learn from us about what sorts of thing creep around

762
00:40:01,000 --> 00:40:05,000
Speaker 1: in the ether among hunting and fishing type folks. So

763
00:40:05,440 --> 00:40:06,920
Speaker 1: I try to heard it all though I am a

764
00:40:07,000 --> 00:40:11,040
Speaker 1: hunting and fishing type of I have not heard at all.

765
00:40:11,160 --> 00:40:13,480
Speaker 1: But do you? But do you ever spend time undercovered?

766
00:40:13,520 --> 00:40:14,839
Speaker 1: Do you ever just sitting in the bar and act

767
00:40:14,880 --> 00:40:17,279
Speaker 1: like you're not who you are? Just absorb what people say?

768
00:40:17,400 --> 00:40:19,120
Speaker 1: I am. What you see is what you get. I

769
00:40:19,160 --> 00:40:21,080
Speaker 1: am who I am. Okay, So you never just like

770
00:40:21,320 --> 00:40:24,279
Speaker 1: get into a wolf conversation bait the person along to

771
00:40:24,320 --> 00:40:26,720
Speaker 1: try to get to try to find out what they're thinking.

772
00:40:26,800 --> 00:40:28,680
Speaker 1: I'm not saying I didn't do that when I was younger,

773
00:40:29,719 --> 00:40:31,440
Speaker 1: but I don't do it now. Before you just sit

774
00:40:31,480 --> 00:40:35,920
Speaker 1: there go you don't say, you don't say so, Um,

775
00:40:36,200 --> 00:40:39,040
Speaker 1: what's the big Okay, tell me in your career the

776
00:40:39,080 --> 00:40:43,120
Speaker 1: biggest wolf you've ever weighed on? We're talking certified scales

777
00:40:43,239 --> 00:40:45,240
Speaker 1: right like you do it where you're getting the actual

778
00:40:45,320 --> 00:40:47,920
Speaker 1: real weight. So the biggest wolf I've ever caught was

779
00:40:47,920 --> 00:40:52,359
Speaker 1: a pounds. He was the breeding male of the Headwaters pack.

780
00:40:52,640 --> 00:40:56,960
Speaker 1: What's the biggest weight, um that you've like, do you

781
00:40:57,000 --> 00:40:59,319
Speaker 1: know the highest acceptable way? Because I know they've gotten

782
00:40:59,320 --> 00:41:01,480
Speaker 1: some bigger weights and Alaska, for instance, a little bit

783
00:41:01,560 --> 00:41:03,920
Speaker 1: the high We were asking this of the Yellowstone folks.

784
00:41:04,000 --> 00:41:07,439
Speaker 1: So the biggest wolves they've ever weighed there, and those

785
00:41:07,440 --> 00:41:10,600
Speaker 1: are very you know, they're doing pretty well. Um. I

786
00:41:10,640 --> 00:41:13,120
Speaker 1: think it was close to like a hundred and forty

787
00:41:13,239 --> 00:41:15,759
Speaker 1: seven pounds or something like that, which is more than

788
00:41:15,800 --> 00:41:20,360
Speaker 1: I wait, that's a really big yeah. And I've also

789
00:41:20,400 --> 00:41:25,200
Speaker 1: heard that when you get those high end weights, it's

790
00:41:25,200 --> 00:41:29,400
Speaker 1: typically something with twenty pounds of meat in its belly typically,

791
00:41:29,560 --> 00:41:34,560
Speaker 1: which you know can really yeah, really like tip it

792
00:41:34,600 --> 00:41:37,360
Speaker 1: to the high end. So in my career, considering starting

793
00:41:37,360 --> 00:41:41,799
Speaker 1: with Minnesota, and I've I've worked in the Canadian National Parks,

794
00:41:41,840 --> 00:41:47,000
Speaker 1: I've colored wolves in British, Columbia, Alberta, Montana, Royal, Romania.

795
00:41:47,440 --> 00:41:52,439
Speaker 1: I mean, I've had a huge Romania in Minnesota. So

796
00:41:53,080 --> 00:41:55,200
Speaker 1: the wolves on average in the West where we are,

797
00:41:55,200 --> 00:41:57,640
Speaker 1: because your audience is the Western audience, we got them

798
00:41:57,680 --> 00:42:02,080
Speaker 1: all over places. Some Minnesota wolves are on average twenty

799
00:42:02,120 --> 00:42:06,560
Speaker 1: maybe smaller. Far more people will listen to this who

800
00:42:06,560 --> 00:42:08,520
Speaker 1: aren't in the West than are on the West Saks.

801
00:42:08,560 --> 00:42:11,640
Speaker 1: I didn't know that. Okay, So they're smaller the Midwestern wolves.

802
00:42:11,680 --> 00:42:14,359
Speaker 1: It's a smaller and it's called the Eastern wolf. It's

803
00:42:14,520 --> 00:42:18,160
Speaker 1: slightly different. Our wolves in the West are slightly larger. Again,

804
00:42:18,200 --> 00:42:20,360
Speaker 1: it's prey based. The wolves in the Midwest live on

805
00:42:20,480 --> 00:42:23,840
Speaker 1: deer and beaver and occasionally almost Wora wolves live predominantly

806
00:42:23,880 --> 00:42:27,880
Speaker 1: almost The wolves out here live primarily deer and elk

807
00:42:28,239 --> 00:42:31,200
Speaker 1: occasionally most, but they have a larger prey that they

808
00:42:31,239 --> 00:42:33,359
Speaker 1: go and the ones that came from Canada they may

809
00:42:33,360 --> 00:42:35,960
Speaker 1: have bread and caribout which again are larger and more

810
00:42:36,040 --> 00:42:39,399
Speaker 1: most so they are what they eat, just like us.

811
00:42:39,480 --> 00:42:41,839
Speaker 1: And if you're you know, if you're if you're taking

812
00:42:41,880 --> 00:42:45,000
Speaker 1: down a hundred forty pound deer, that's your diet. Does

813
00:42:45,040 --> 00:42:47,160
Speaker 1: not behoove you toway a hundred forty pounds because there's

814
00:42:47,160 --> 00:42:48,879
Speaker 1: a lot of you they're gonna eat. So just being

815
00:42:48,920 --> 00:42:52,640
Speaker 1: smaller that just works out. It just if you need

816
00:42:52,760 --> 00:42:54,759
Speaker 1: take down a really big, a thousand pound animal, you

817
00:42:54,800 --> 00:42:58,720
Speaker 1: need a lot of real big beefy animals. So, okay,

818
00:42:58,840 --> 00:43:03,600
Speaker 1: super wolves, are you ready to lay out? I don't

819
00:43:03,600 --> 00:43:04,920
Speaker 1: even want to do it. I'm not even do it.

820
00:43:05,600 --> 00:43:10,319
Speaker 1: Lay out what lay out the super wolf, lay out

821
00:43:10,360 --> 00:43:12,640
Speaker 1: the super wolf. It's been a while since I have

822
00:43:12,760 --> 00:43:14,640
Speaker 1: had to do this or even think about it. But

823
00:43:15,520 --> 00:43:21,359
Speaker 1: I think that the theory goes that I don't know.

824
00:43:21,520 --> 00:43:25,120
Speaker 1: I don't know the reason why or the proposed reason why.

825
00:43:25,239 --> 00:43:29,360
Speaker 1: But the theory is that for some reason, they trapped

826
00:43:29,400 --> 00:43:31,959
Speaker 1: a bunch of wolves. And we even talked to a

827
00:43:32,000 --> 00:43:34,640
Speaker 1: trapper told us who told us that, and he that

828
00:43:34,719 --> 00:43:37,239
Speaker 1: he had an evidences this was true that because he

829
00:43:37,360 --> 00:43:41,160
Speaker 1: knew the trapper that trapped these wolves in Canada. It's

830
00:43:41,640 --> 00:43:44,439
Speaker 1: it's okay, go ahead. But there's there's two there's two

831
00:43:44,480 --> 00:43:48,520
Speaker 1: competing wisdoms about the super wolf. Okay, well, either way,

832
00:43:48,640 --> 00:43:53,239
Speaker 1: that they they picked out and they they picked out

833
00:43:53,280 --> 00:43:57,440
Speaker 1: the biggest, baddest, nastiest, meanest wolves, and those are the

834
00:43:57,440 --> 00:43:59,799
Speaker 1: ones that they brought down and put into els on

835
00:43:59,840 --> 00:44:03,239
Speaker 1: that sational park. I bet again, I don't know why

836
00:44:03,400 --> 00:44:06,680
Speaker 1: or well, okay, and there's that, and we were told

837
00:44:06,719 --> 00:44:09,600
Speaker 1: that by a fella. Yeah, and there's another one that

838
00:44:09,640 --> 00:44:14,879
Speaker 1: they took the wrong wolves, the long species of wolf, right, yeah,

839
00:44:14,880 --> 00:44:20,520
Speaker 1: they're sober, the wrong variety. Yeah, from way too far north.

840
00:44:21,520 --> 00:44:24,560
Speaker 1: And the ones that were here, the native wolves here

841
00:44:24,560 --> 00:44:28,840
Speaker 1: where these little rinky dinky plant very like mild mannered,

842
00:44:29,200 --> 00:44:33,520
Speaker 1: polite little wolves. And they went and got these big

843
00:44:33,960 --> 00:44:37,960
Speaker 1: northern savages that are two fifty pounds, and they cut

844
00:44:37,960 --> 00:44:42,439
Speaker 1: those loose down. As soon as they got here. They

845
00:44:42,560 --> 00:44:47,600
Speaker 1: just reigned holy hell on the north Yellowstone Elkerve. Yeah,

846
00:44:47,640 --> 00:44:51,360
Speaker 1: the heard went from twenties some plus thousand all the

847
00:44:51,400 --> 00:44:58,000
Speaker 1: way down to four because biologists, can you remember to

848
00:44:58,120 --> 00:45:00,160
Speaker 1: within this. I'm just gonna let you run. Okay, I'm

849
00:45:00,160 --> 00:45:01,799
Speaker 1: gonna let you run. Be careful. How much time do

850
00:45:01,840 --> 00:45:04,440
Speaker 1: you let you run? But but I we're gonna see

851
00:45:04,480 --> 00:45:08,319
Speaker 1: how good you are. Um as you run on this,

852
00:45:08,960 --> 00:45:14,319
Speaker 1: however you see fit? Can you also touch on the

853
00:45:14,400 --> 00:45:17,320
Speaker 1: idea and I think this comes from you, the idea

854
00:45:17,440 --> 00:45:24,719
Speaker 1: that the reintroduction maybe it was not necessary. You just

855
00:45:24,800 --> 00:45:27,520
Speaker 1: give me four hours with some materials recover, so I

856
00:45:27,560 --> 00:45:31,160
Speaker 1: will start. Let's do it. Let's start with the super

857
00:45:31,200 --> 00:45:35,880
Speaker 1: wolf first. So the wolves that they captured up in

858
00:45:36,040 --> 00:45:39,200
Speaker 1: a Hinton and for in St. John's are within dispersal

859
00:45:39,280 --> 00:45:42,719
Speaker 1: distance of our wolves here? Where are those places? Tell people?

860
00:45:42,719 --> 00:45:47,040
Speaker 1: Where those places? So? Um one is in Alberta and

861
00:45:47,080 --> 00:45:50,200
Speaker 1: one is in BC. They're close to the Alberta BC line.

862
00:45:51,600 --> 00:45:55,960
Speaker 1: Um there about. One is about three miles north or so.

863
00:45:56,080 --> 00:45:58,839
Speaker 1: One is about five miles north or so of hair

864
00:45:59,120 --> 00:46:02,319
Speaker 1: of Glacier Park the border give you a take. And

865
00:46:02,360 --> 00:46:04,719
Speaker 1: so the crew went up there and they just had

866
00:46:04,840 --> 00:46:08,880
Speaker 1: guys who are trapping bringing you know, call and they

867
00:46:08,920 --> 00:46:10,440
Speaker 1: went out put a radio collar on them to have

868
00:46:10,480 --> 00:46:12,399
Speaker 1: a judice wolf, so then they could go out and

869
00:46:12,440 --> 00:46:14,680
Speaker 1: fly and catch more wolves and dark than whatever. They

870
00:46:14,760 --> 00:46:17,319
Speaker 1: just took the whatever wolves they could get. There was

871
00:46:17,360 --> 00:46:24,560
Speaker 1: not a selection for bigger, meaner, badder, uglier, beautiful whatever wolves.

872
00:46:24,560 --> 00:46:30,480
Speaker 1: They just random sample those locations. I don't need to

873
00:46:30,560 --> 00:46:32,600
Speaker 1: have to ask somebody from Yellowstone. I think it's because

874
00:46:32,640 --> 00:46:35,840
Speaker 1: the Canadian government says, we're really glad to give you

875
00:46:35,920 --> 00:46:38,520
Speaker 1: all the worlds you want. They're free, come and get

876
00:46:38,560 --> 00:46:43,799
Speaker 1: them serious. Because out there they still aerial gun them,

877
00:46:43,920 --> 00:46:47,440
Speaker 1: don't they in certain places. I don't think so, not anymore.

878
00:46:48,719 --> 00:46:51,120
Speaker 1: I don't think so. I'm not sure, but I don't

879
00:46:51,120 --> 00:46:55,400
Speaker 1: think so. Maybe back then they were they were killing them.

880
00:46:55,440 --> 00:47:00,640
Speaker 1: I mean, they economically valuable pelt they have, and so

881
00:47:00,760 --> 00:47:02,720
Speaker 1: they kept them in the wolves that they could catch

882
00:47:03,320 --> 00:47:05,520
Speaker 1: as a family group. Were the wolves that they put

883
00:47:05,520 --> 00:47:07,759
Speaker 1: into Yellowstone and the holding pens with the hopes that

884
00:47:07,800 --> 00:47:10,359
Speaker 1: they would stay together as a pack. And the young

885
00:47:10,719 --> 00:47:13,960
Speaker 1: teenage kind of age wolves that would be potentially good

886
00:47:13,960 --> 00:47:17,960
Speaker 1: dispersers or unassociated with other wolves. They caught those and

887
00:47:17,960 --> 00:47:21,000
Speaker 1: they put them in Yellowstone because the idea wasn't in

888
00:47:21,320 --> 00:47:23,920
Speaker 1: I mean in Idaho. They caught those and put them

889
00:47:23,920 --> 00:47:26,440
Speaker 1: in Idahole. The idea was they wanted family groups to

890
00:47:26,480 --> 00:47:28,640
Speaker 1: stay in the park, but when they dropped him off

891
00:47:28,680 --> 00:47:31,160
Speaker 1: with the wilderness Boundary and Idaho, they wanted them to

892
00:47:31,239 --> 00:47:34,759
Speaker 1: just blow like dandelion fluff in the wind and disperse

893
00:47:35,320 --> 00:47:37,840
Speaker 1: and find each other and pair and form new packs.

894
00:47:37,880 --> 00:47:40,360
Speaker 1: So they were tartly. Oh yeah, So the ones that

895
00:47:40,400 --> 00:47:43,120
Speaker 1: they put in Yellowstone was called a soft release because

896
00:47:43,200 --> 00:47:46,040
Speaker 1: the ones by Frank Church, they wanted them to split.

897
00:47:46,560 --> 00:47:48,719
Speaker 1: They didn't put packs in there, they put in individuals.

898
00:47:49,000 --> 00:47:53,319
Speaker 1: They wanted them. They dropped what wolves there over two years,

899
00:47:53,320 --> 00:47:56,520
Speaker 1: and they wanted them to just go go high and

900
00:47:56,560 --> 00:48:01,120
Speaker 1: wide and find each other. Hot hot release, hard hard release,

901
00:48:01,200 --> 00:48:03,880
Speaker 1: herd release. And was that to so they can monitor

902
00:48:04,000 --> 00:48:08,359
Speaker 1: sort of two different versions of releases and research too different. Yes,

903
00:48:08,440 --> 00:48:11,240
Speaker 1: because you've got to realize prior to the Yellowstone wolf introduction,

904
00:48:11,320 --> 00:48:13,479
Speaker 1: this had never been done anywhere in the world ever,

905
00:48:13,920 --> 00:48:15,880
Speaker 1: and so they didn't know how it turned out. It

906
00:48:15,920 --> 00:48:17,720
Speaker 1: was like, this is our best guest. So we'll build

907
00:48:17,719 --> 00:48:21,960
Speaker 1: these pans with cycle and fences, like we will hold

908
00:48:22,000 --> 00:48:27,000
Speaker 1: them for through breeding season, and just before they're gonna welp,

909
00:48:27,040 --> 00:48:29,359
Speaker 1: we're gonna cut them loose. And those pregnant females aren't

910
00:48:29,360 --> 00:48:31,279
Speaker 1: going to probably go very far. And they've got their

911
00:48:31,280 --> 00:48:33,960
Speaker 1: pack mates now they've made it, and we're gonna hope

912
00:48:34,000 --> 00:48:36,000
Speaker 1: they stick together and stay in the park and Idaho

913
00:48:36,040 --> 00:48:38,239
Speaker 1: it's like, you guys, better run your tails off and

914
00:48:38,280 --> 00:48:40,200
Speaker 1: get the heck away from people and go find each

915
00:48:40,239 --> 00:48:42,799
Speaker 1: other and disappear in the wilderness and mates. So it

916
00:48:42,880 --> 00:48:45,440
Speaker 1: was a totally different starter, and they were literally the

917
00:48:45,480 --> 00:48:47,200
Speaker 1: doors are opened up, the wolves were kicked out, and

918
00:48:47,200 --> 00:48:50,920
Speaker 1: they're gone in idahol it's totally different. So both worked,

919
00:48:51,280 --> 00:48:54,479
Speaker 1: and yeah, they both worked. Interestingly, I had a wolf

920
00:48:54,480 --> 00:48:58,080
Speaker 1: that caught and Glacier Park and he hung around for

921
00:48:58,080 --> 00:49:00,160
Speaker 1: a while and then he ended up going over to

922
00:49:00,280 --> 00:49:04,440
Speaker 1: the Kelly Creek area in Idaho wild Area and he

923
00:49:04,640 --> 00:49:07,000
Speaker 1: stayed there, and the fish and game would keep drag

924
00:49:07,040 --> 00:49:09,160
Speaker 1: of him, and we'd see him occasionally, and he was

925
00:49:09,160 --> 00:49:11,400
Speaker 1: there with a radio collar, and he just bided his

926
00:49:11,480 --> 00:49:14,040
Speaker 1: time by himself up in the Great Burn country. And

927
00:49:14,880 --> 00:49:16,719
Speaker 1: I mean it's a big wolf by himself. He was

928
00:49:16,760 --> 00:49:18,920
Speaker 1: a hundred eleven pounds on e cottom, pretty big male.

929
00:49:19,960 --> 00:49:22,400
Speaker 1: He lived by himself, killing whatever you could do. And

930
00:49:22,400 --> 00:49:27,319
Speaker 1: when they let those wolves kicked him loose in seven

931
00:49:27,360 --> 00:49:29,959
Speaker 1: at the edge of the wilderness, this little black young

932
00:49:30,040 --> 00:49:33,080
Speaker 1: female found her way up to Kelly Create and paired

933
00:49:33,080 --> 00:49:36,080
Speaker 1: with that collared male from Glacier Park and they formed

934
00:49:36,080 --> 00:49:38,920
Speaker 1: the Kelly Creek and he lived to be eleven. He

935
00:49:38,960 --> 00:49:42,799
Speaker 1: lived a long long time. That's an old wolf, very

936
00:49:42,920 --> 00:49:45,719
Speaker 1: very very old. Average life expectancy of a wolf. They've

937
00:49:45,760 --> 00:49:49,480
Speaker 1: calculated it in Yellowstone four point six years, I believe,

938
00:49:49,520 --> 00:49:54,760
Speaker 1: and in Minnesota four point one average life expectancy in years.

939
00:49:54,800 --> 00:49:57,720
Speaker 1: You make it to five, you're doing really well. Eleven

940
00:49:57,800 --> 00:50:02,200
Speaker 1: is very old. So you've only seen a handful over

941
00:50:02,440 --> 00:50:06,399
Speaker 1: ten years. Yeah, I can count him on one hand. Huh.

942
00:50:06,440 --> 00:50:08,400
Speaker 1: They just don't live very long. I had one brought

943
00:50:08,440 --> 00:50:10,960
Speaker 1: in for checking this fall that a trapper caught over by.

944
00:50:10,960 --> 00:50:13,600
Speaker 1: Libby was really interesting because it had been trapped in

945
00:50:13,600 --> 00:50:16,120
Speaker 1: two thousand and twelve. Was an adult already and he

946
00:50:16,200 --> 00:50:18,080
Speaker 1: was brought in so he think he was about nine,

947
00:50:18,120 --> 00:50:20,560
Speaker 1: and that's a really old wolf. The trapper brought him

948
00:50:20,600 --> 00:50:22,719
Speaker 1: in dead. Yeah, he caught. He harvest I didn't know

949
00:50:22,719 --> 00:50:24,320
Speaker 1: if he meant like trapper, like you were a trap. No,

950
00:50:24,920 --> 00:50:27,680
Speaker 1: harvested him for for and um he yeah, he lived

951
00:50:27,680 --> 00:50:30,560
Speaker 1: on that landscape all that time and avoided Oh my goodness,

952
00:50:30,600 --> 00:50:33,120
Speaker 1: I can't tell you how many times he'd probably you know,

953
00:50:33,560 --> 00:50:35,759
Speaker 1: had experiences with humans that he should have died and

954
00:50:35,760 --> 00:50:39,399
Speaker 1: he didn't. So actually he had a bullet, a small

955
00:50:39,480 --> 00:50:41,560
Speaker 1: twenty two caliber lodged in the base of the skull

956
00:50:41,840 --> 00:50:45,520
Speaker 1: that healed over. Really, I'm telling you these wolves he did.

957
00:50:45,520 --> 00:50:47,720
Speaker 1: He sent me the photo. They don't have it easy.

958
00:50:48,800 --> 00:50:53,120
Speaker 1: So back to the super wolves. Yeah, we're digressing. So

959
00:50:53,320 --> 00:50:57,400
Speaker 1: the should I repeat about the glacier wolf, about the

960
00:50:57,440 --> 00:50:59,800
Speaker 1: one that I caught that dispersed. You could remind me

961
00:51:00,480 --> 00:51:02,719
Speaker 1: because you're making because now I think the connection will

962
00:51:02,719 --> 00:51:05,479
Speaker 1: have more potent. So all these people are concerned about

963
00:51:05,520 --> 00:51:07,880
Speaker 1: these wolves not being the same wolf. So this little

964
00:51:07,920 --> 00:51:10,560
Speaker 1: female that I dropped in Glacier Park at about age two,

965
00:51:10,719 --> 00:51:15,920
Speaker 1: and she dispersed in nine seven. This is one of

966
00:51:15,920 --> 00:51:18,359
Speaker 1: the ones that walked in original. Yeah, she was born

967
00:51:18,400 --> 00:51:20,680
Speaker 1: in Glacier Park. I know because we caught her as

968
00:51:20,680 --> 00:51:23,800
Speaker 1: a pup. I know she was born there. Anyway, Um,

969
00:51:23,880 --> 00:51:26,960
Speaker 1: she went up and dispersed and disappeared, and she ended

970
00:51:27,040 --> 00:51:30,200
Speaker 1: up being killed by a farmer. And she was traveling

971
00:51:30,200 --> 00:51:33,200
Speaker 1: with other wolves in July and called it in because

972
00:51:33,200 --> 00:51:35,239
Speaker 1: out of the radio color a phone number. Game Warden

973
00:51:35,320 --> 00:51:37,400
Speaker 1: called me and this is where she was shot. And

974
00:51:37,400 --> 00:51:41,040
Speaker 1: it was north where most of the Yellowstone wolf were

975
00:51:41,120 --> 00:51:45,560
Speaker 1: taken from. It was equally far north as the furthest

976
00:51:45,600 --> 00:51:48,319
Speaker 1: north Yellowstone what was were taken from. So clearly that

977
00:51:48,520 --> 00:51:51,760
Speaker 1: range that she traveled, it's all one set of jeans.

978
00:51:51,840 --> 00:51:55,440
Speaker 1: It's one wolf population. And I can tell that to

979
00:51:55,520 --> 00:51:58,120
Speaker 1: people time and time again. And she's not the only one.

980
00:51:58,160 --> 00:52:00,400
Speaker 1: She was the first one that we documented. She spirst

981
00:52:01,800 --> 00:52:05,480
Speaker 1: five and forty miles straight line. No, I don't know.

982
00:52:05,560 --> 00:52:07,759
Speaker 1: She may have gone further past that. When they do that,

983
00:52:08,600 --> 00:52:12,319
Speaker 1: I'm really interested in the anomalies. What is it that

984
00:52:12,360 --> 00:52:15,480
Speaker 1: made her do that? Because she's a wolf, I mean,

985
00:52:15,520 --> 00:52:18,080
Speaker 1: this is she's not unusual. It's just that it's really

986
00:52:18,160 --> 00:52:20,960
Speaker 1: hard to document it, and not that we have GPS colors.

987
00:52:21,040 --> 00:52:23,600
Speaker 1: Oh my god, they are all over the place. We

988
00:52:23,640 --> 00:52:26,719
Speaker 1: had wolves and Yellowstone go to Colorado and Utah. I mean,

989
00:52:27,080 --> 00:52:30,239
Speaker 1: this is not unusual now that we know, we just

990
00:52:30,280 --> 00:52:33,680
Speaker 1: didn't have the tools to detect it. Average wolf dispersial

991
00:52:33,760 --> 00:52:38,560
Speaker 1: instance is probably average including all habits, probably around fifty miles.

992
00:52:38,600 --> 00:52:42,319
Speaker 1: But there are those that gos and in Canada where

993
00:52:42,320 --> 00:52:44,920
Speaker 1: they're following migratory hurts, Oh my god, they'll go thousand

994
00:52:45,000 --> 00:52:49,720
Speaker 1: miles easily. Remember that we're on Remember what you spose

995
00:52:49,800 --> 00:52:52,200
Speaker 1: you're talking about. Let me let me sidetracking from Matt

996
00:52:53,200 --> 00:52:58,480
Speaker 1: Have you have we yet had um? I'm sure we

997
00:52:58,520 --> 00:53:04,400
Speaker 1: have introduced wolves intermingle with wolves that came in on

998
00:53:04,440 --> 00:53:07,920
Speaker 1: their own. Yes. So originally we had the native wolves

999
00:53:07,960 --> 00:53:11,239
Speaker 1: that walked down from Canada that colonized northwest Montana and

1000
00:53:11,280 --> 00:53:17,200
Speaker 1: started spilling at Idahole a little bit. The introductions were winters,

1001
00:53:19,520 --> 00:53:23,319
Speaker 1: and those populations in Idaho Yellowstone in northwest Montana were

1002
00:53:23,360 --> 00:53:27,480
Speaker 1: separate for quite a long time genetically, and they didn't

1003
00:53:27,480 --> 00:53:32,640
Speaker 1: begin to successfully not just dispersed, but dispersed land and

1004
00:53:32,719 --> 00:53:35,720
Speaker 1: breed that's the sign of success when they're only inter England.

1005
00:53:36,040 --> 00:53:38,800
Speaker 1: And now we have shown through genetics and radio collars

1006
00:53:38,840 --> 00:53:45,000
Speaker 1: their one population Idaho, Montana, Oregon, Washington, you know, Wyoming.

1007
00:53:45,120 --> 00:53:48,279
Speaker 1: It's one about the ones in northern California just came

1008
00:53:48,280 --> 00:53:50,920
Speaker 1: from Oregon, which came from Yellowstone. Yeah, I mean nobody

1009
00:53:50,960 --> 00:53:53,120
Speaker 1: put them there, and you could say, well, they were

1010
00:53:53,120 --> 00:53:56,520
Speaker 1: put into Yellowstone? Yeah? Or seven? The thing? Why did

1011
00:53:56,560 --> 00:53:59,440
Speaker 1: they not come out of the frank Church. They may have.

1012
00:54:00,000 --> 00:54:02,440
Speaker 1: I'm trying to think. I'm pretty sure that our seven,

1013
00:54:02,520 --> 00:54:05,000
Speaker 1: I'm pretty sure it came from yellow Stone. But sorry,

1014
00:54:05,120 --> 00:54:08,839
Speaker 1: I don't actually remember. Okay, so now maybe it came

1015
00:54:08,840 --> 00:54:10,719
Speaker 1: from I'm feeling good on the stup. Maybe it can't.

1016
00:54:10,719 --> 00:54:12,480
Speaker 1: It probably came from Idaho. You're right, not the one

1017
00:54:12,480 --> 00:54:16,480
Speaker 1: that wou or seven's the number. Um, I'm feeling good

1018
00:54:16,480 --> 00:54:19,440
Speaker 1: on super wolves? Are feeling good on super wolves? Yeah? Okay?

1019
00:54:19,600 --> 00:54:23,120
Speaker 1: Now what about the idea? Well, the other thing is

1020
00:54:23,160 --> 00:54:25,600
Speaker 1: I've heard that wolves have eight canines. These super wolves

1021
00:54:25,640 --> 00:54:28,400
Speaker 1: were a hundred seventy pounds and they have double canines

1022
00:54:28,440 --> 00:54:31,960
Speaker 1: with eight canines too. I hear it. You really have

1023
00:54:32,160 --> 00:54:34,480
Speaker 1: heard that public meetings, and you can't laugh at a

1024
00:54:34,520 --> 00:54:38,160
Speaker 1: public meeting. Someone told you that at the meeting that

1025
00:54:38,200 --> 00:54:40,640
Speaker 1: they're super heavy and got extra teeth. I've heard a

1026
00:54:40,640 --> 00:54:46,080
Speaker 1: lot when you point out when what are you getting at? Am?

1027
00:54:46,080 --> 00:54:49,840
Speaker 1: I I'm right that you observed that we would have

1028
00:54:49,920 --> 00:54:52,520
Speaker 1: landed We would have eventually landed in the same place

1029
00:54:52,719 --> 00:54:57,600
Speaker 1: had we not done the Yellowstone in Idaho reintroductions, that

1030
00:54:57,640 --> 00:55:00,680
Speaker 1: we would have gotten there. Anyways, do you just point

1031
00:55:00,760 --> 00:55:04,160
Speaker 1: that out as an interesting idea or do you point

1032
00:55:04,160 --> 00:55:06,200
Speaker 1: that out because you feel that there's a lesson there

1033
00:55:06,719 --> 00:55:08,800
Speaker 1: or did you feel that there was a mistake made.

1034
00:55:10,840 --> 00:55:13,520
Speaker 1: This is a very complex question, so I'm going to

1035
00:55:13,680 --> 00:55:15,880
Speaker 1: start with complex show. I'm going to start with data

1036
00:55:15,920 --> 00:55:21,560
Speaker 1: because I'm a scientist, so I believe it was there

1037
00:55:21,560 --> 00:55:25,319
Speaker 1: were two wolves that showed up, one inside Yellowstone Park

1038
00:55:25,520 --> 00:55:29,080
Speaker 1: and one south of Yellowstone Park two years at least

1039
00:55:29,080 --> 00:55:32,440
Speaker 1: two to three before the reintroductions, might have been ninety one.

1040
00:55:32,480 --> 00:55:36,120
Speaker 1: There was a filmmaker here from Bozeman, right Panovich. He

1041
00:55:36,239 --> 00:55:39,680
Speaker 1: was in Hayden Valley filming for Bush Productions filming, and

1042
00:55:39,719 --> 00:55:43,960
Speaker 1: he was he was out monitoring a bison kill and

1043
00:55:44,040 --> 00:55:47,680
Speaker 1: he was filming this. The grizzlies and the grizzlies and

1044
00:55:47,680 --> 00:55:51,240
Speaker 1: the coy its interacting and just just as was getting

1045
00:55:51,280 --> 00:55:54,440
Speaker 1: too dark to film, he's packing up his camera, this

1046
00:55:54,600 --> 00:55:57,520
Speaker 1: form comes out of the dark and he's going, oh

1047
00:55:57,560 --> 00:56:01,120
Speaker 1: my god, I think it's a wolf. And it steps

1048
00:56:01,200 --> 00:56:03,279
Speaker 1: up to the kill with the grizzlies and the wolf

1049
00:56:03,360 --> 00:56:05,920
Speaker 1: like it belonged there, and they're all tearing at this

1050
00:56:06,280 --> 00:56:08,480
Speaker 1: feeding on it. It was too dark to film, so

1051
00:56:08,520 --> 00:56:11,080
Speaker 1: he got up like three o'clock the next morning. It

1052
00:56:11,120 --> 00:56:15,000
Speaker 1: makes his way back out. Um. I believe it was August.

1053
00:56:15,080 --> 00:56:17,239
Speaker 1: It was a summer month and he goes right at

1054
00:56:17,400 --> 00:56:19,280
Speaker 1: sun before the sun is there, and he's there waiting

1055
00:56:19,320 --> 00:56:22,040
Speaker 1: and as the sun comes up, there's this wolf feeding

1056
00:56:22,040 --> 00:56:24,840
Speaker 1: on this kill. Before years before the introduction, he was

1057
00:56:24,880 --> 00:56:27,760
Speaker 1: so excited about it. All the whiologists saw the video.

1058
00:56:28,239 --> 00:56:31,760
Speaker 1: I know him. It was a real thing. That wolf

1059
00:56:31,880 --> 00:56:35,200
Speaker 1: was around. It disappeared, never seen again, and then it

1060
00:56:35,239 --> 00:56:38,160
Speaker 1: was black and silver, kind of your classic wolf that

1061
00:56:38,239 --> 00:56:39,880
Speaker 1: we see here in this equo system. Now it's like

1062
00:56:39,920 --> 00:56:42,000
Speaker 1: an older, middle aged animal. Unlike the rest of us,

1063
00:56:42,200 --> 00:56:43,759
Speaker 1: they get gray hair as they get older. What was

1064
00:56:43,760 --> 00:56:46,520
Speaker 1: the word you just said, You said, we see here

1065
00:56:46,560 --> 00:56:53,160
Speaker 1: in the like we see here now. The classic Sorry

1066
00:56:53,320 --> 00:56:57,200
Speaker 1: too much Catheine. And then in September and that fall,

1067
00:56:57,400 --> 00:57:01,359
Speaker 1: that same fall, a black pound wolf was shot at

1068
00:57:01,400 --> 00:57:05,879
Speaker 1: Fox Park Fox Creek, just south of Yellowstone Park, and

1069
00:57:05,920 --> 00:57:07,640
Speaker 1: it was shot by somebody who claimed they thought it

1070
00:57:07,680 --> 00:57:10,520
Speaker 1: was a kaya. It was unds in black, but who knows,

1071
00:57:10,840 --> 00:57:12,960
Speaker 1: but it wouldn't be in that case, It wouldn't be

1072
00:57:12,960 --> 00:57:15,000
Speaker 1: in their mind that it would be anything other. I

1073
00:57:15,040 --> 00:57:17,360
Speaker 1: don't know, but it was not the one that was

1074
00:57:17,400 --> 00:57:21,360
Speaker 1: filmed because this was black. So I was doing my PhD.

1075
00:57:21,440 --> 00:57:24,120
Speaker 1: We got the genetic sample. I worked with the Fish

1076
00:57:24,120 --> 00:57:26,600
Speaker 1: and Walife Service. We the genetics were done on all

1077
00:57:26,640 --> 00:57:29,400
Speaker 1: of those introduced wolves and then about a hundred wolves

1078
00:57:29,440 --> 00:57:31,560
Speaker 1: that I had samples from collected over the airs, from

1079
00:57:31,680 --> 00:57:35,040
Speaker 1: road killed colored animals, wolves from Canada. We had many

1080
00:57:35,080 --> 00:57:39,120
Speaker 1: collaborators contributing samples. That wolf that was shot south of

1081
00:57:39,160 --> 00:57:42,800
Speaker 1: Wyoming Genetic Lab in Nason Organ said it was most

1082
00:57:42,880 --> 00:57:48,080
Speaker 1: closely related to wolves from nine Mile, Montana. It walked

1083
00:57:48,200 --> 00:57:51,800
Speaker 1: down there. It wasn't native wolf too. So there were

1084
00:57:51,800 --> 00:57:55,640
Speaker 1: two animals that got down there prior to reintroductions, so

1085
00:57:55,680 --> 00:57:59,280
Speaker 1: they were getting there, but they both disappeared overre dead

1086
00:57:59,440 --> 00:58:01,440
Speaker 1: and it's kind know where we were at in seventy

1087
00:58:01,520 --> 00:58:04,480
Speaker 1: nine and the North Montana we had one wolf that

1088
00:58:04,600 --> 00:58:06,960
Speaker 1: made it for a couple of years and finally phoned

1089
00:58:07,000 --> 00:58:09,880
Speaker 1: one other and it was just at that threshold. So

1090
00:58:09,920 --> 00:58:13,040
Speaker 1: in the early years when this reintroduction was being planned,

1091
00:58:13,680 --> 00:58:16,360
Speaker 1: Bob Riem and I keep mentioning Bobby was the father

1092
00:58:16,440 --> 00:58:20,040
Speaker 1: of the wolf research here in Montana, fabulous man. Neither

1093
00:58:20,080 --> 00:58:23,720
Speaker 1: of us supported reintroduction because we've seen the natural recognization

1094
00:58:23,920 --> 00:58:26,880
Speaker 1: work so well. They were making it on their own.

1095
00:58:26,920 --> 00:58:30,040
Speaker 1: And when they when they run or trond the gauntlet

1096
00:58:30,360 --> 00:58:34,080
Speaker 1: down the rocky mountains, those wolves that are too bold

1097
00:58:34,280 --> 00:58:36,960
Speaker 1: or bothers, somebody shoot shovel and shut up, they're gone.

1098
00:58:37,360 --> 00:58:39,240
Speaker 1: So it kind of selects for wolves that are a

1099
00:58:39,280 --> 00:58:42,240
Speaker 1: little more shy and and there it's more accepted by

1100
00:58:42,240 --> 00:58:44,760
Speaker 1: the local people. If the wolves aren't put there, because

1101
00:58:44,880 --> 00:58:46,960
Speaker 1: I'm in the controversy here, most of it's because these

1102
00:58:46,960 --> 00:58:51,200
Speaker 1: wolves aren't native. So we were against reintroduction for those reasons.

1103
00:58:52,080 --> 00:58:54,360
Speaker 1: And then the reintroduction moved forward and it was it

1104
00:58:54,440 --> 00:58:57,200
Speaker 1: truly has been, like I cannot think of a more

1105
00:58:57,240 --> 00:59:01,320
Speaker 1: successful recovery story anywhere in any dangerous species. It's phenomenal

1106
00:59:01,320 --> 00:59:04,640
Speaker 1: because they took over it and they gone everywhere. And

1107
00:59:04,680 --> 00:59:06,600
Speaker 1: I just came from a listen to watching wolves. I mean,

1108
00:59:06,600 --> 00:59:09,320
Speaker 1: I love to watch them, but I still think that socially,

1109
00:59:10,080 --> 00:59:12,440
Speaker 1: it would have been more acceptable if our wolves from

1110
00:59:12,440 --> 00:59:16,760
Speaker 1: northwest Montana could continue spreading and they weren't reintroduce. However,

1111
00:59:17,400 --> 00:59:21,240
Speaker 1: would it take five years fifty five d That was

1112
00:59:21,280 --> 00:59:25,600
Speaker 1: the factor time and the window of opportunity opened through

1113
00:59:26,200 --> 00:59:30,280
Speaker 1: the Administrations in charge Center McClure from Idaho, owns from Utah,

1114
00:59:30,360 --> 00:59:33,840
Speaker 1: Simpson from Myoming. They've introduced bills to reintroduce wolves because

1115
00:59:33,880 --> 00:59:38,560
Speaker 1: they wanted them reintroduced as non essential experimental under the

1116
00:59:39,040 --> 00:59:41,880
Speaker 1: Dangerous Species Act instead of really endangered. And that's how

1117
00:59:41,920 --> 00:59:46,920
Speaker 1: it moved forward because because you feel that they did

1118
00:59:46,960 --> 00:59:49,880
Speaker 1: that because they knew they like you, knew that it

1119
00:59:49,920 --> 00:59:52,640
Speaker 1: was going to happen anyway, and it would be better

1120
00:59:52,680 --> 00:59:55,240
Speaker 1: for management if it happened experimentally, because it gives you

1121
00:59:55,320 --> 00:59:59,600
Speaker 1: greater latitude and lethal control. That's what the reasoning would

1122
00:59:59,680 --> 01:00:01,760
Speaker 1: lead one to conclude. I don't know what's in their brain,

1123
01:00:01,800 --> 01:00:04,080
Speaker 1: but I would think so. You have to ask that,

1124
01:00:04,200 --> 01:00:06,320
Speaker 1: but I would assume so because it would make sense

1125
01:00:06,360 --> 01:00:09,440
Speaker 1: as a as a person in charge of conservative states

1126
01:00:09,440 --> 01:00:12,240
Speaker 1: that you would want to have some control, especially for

1127
01:00:12,280 --> 01:00:15,600
Speaker 1: your live stock constituents, to be able to manage these wolves.

1128
01:00:15,600 --> 01:00:17,720
Speaker 1: And if they were fully endangered, you couldn't do anything.

1129
01:00:17,960 --> 01:00:21,960
Speaker 1: So they're thinking, you're the constituents. Wolves reproduced rapidly have

1130
01:00:22,080 --> 01:00:25,000
Speaker 1: great resilience, they can take it, and they have. I mean,

1131
01:00:25,040 --> 01:00:27,680
Speaker 1: this is there's wolves. We in the West have almost

1132
01:00:27,720 --> 01:00:30,360
Speaker 1: two thousand wolves across scattered across all of the West

1133
01:00:30,360 --> 01:00:32,800
Speaker 1: now from one I mean I was there with the

1134
01:00:32,800 --> 01:00:34,600
Speaker 1: first peop don't realize that there's so many more in

1135
01:00:34,640 --> 01:00:36,840
Speaker 1: the Upper Midwest and the Upper Great Lakes and the

1136
01:00:36,880 --> 01:00:39,560
Speaker 1: Great Lakes has another. So we have almost two thousand here,

1137
01:00:39,600 --> 01:00:41,800
Speaker 1: not quite the Great Lakes, there's a four thousand one.

1138
01:00:41,840 --> 01:00:44,720
Speaker 1: We have like six thousand wolves now in the lower

1139
01:00:44,760 --> 01:00:49,520
Speaker 1: forty eight states connected to one population with Canada. It's

1140
01:00:49,520 --> 01:00:52,960
Speaker 1: a vast meta population is no more isolated. Worry they're

1141
01:00:52,960 --> 01:00:55,280
Speaker 1: going to go extinct, that is not even a concern anymore.

1142
01:00:55,800 --> 01:00:58,520
Speaker 1: When they were kicking around the idea, When when when

1143
01:00:58,520 --> 01:01:02,120
Speaker 1: they were um building a plan to do the reintroduction

1144
01:01:02,200 --> 01:01:06,680
Speaker 1: and you felt that it was not necessary. Were you

1145
01:01:06,760 --> 01:01:09,400
Speaker 1: coming from the perspective of someone who wanted to see

1146
01:01:09,480 --> 01:01:12,320
Speaker 1: wolves return, or were you coming from some of the

1147
01:01:12,320 --> 01:01:14,720
Speaker 1: perspective of someone who was ambivalent about whether or not

1148
01:01:14,800 --> 01:01:17,720
Speaker 1: it happened in terms of like who you were cheering for.

1149
01:01:18,200 --> 01:01:21,520
Speaker 1: I was coming to the perspective of coming from Minnesota,

1150
01:01:21,600 --> 01:01:26,280
Speaker 1: where they success successfully dealt with conflict issues to resolve

1151
01:01:26,320 --> 01:01:30,960
Speaker 1: them where they're still protected but only threatened, not fully endangered.

1152
01:01:31,040 --> 01:01:32,960
Speaker 1: To minute to hear where there was one wolf, and

1153
01:01:32,960 --> 01:01:36,200
Speaker 1: now we're seeing this wave of wolves coming out that

1154
01:01:36,280 --> 01:01:38,520
Speaker 1: we're not bothering a lot of people and the ones

1155
01:01:38,560 --> 01:01:41,000
Speaker 1: that were being bothered while life services going to remove.

1156
01:01:41,120 --> 01:01:43,720
Speaker 1: So I saw a good window of opportunity for wolves

1157
01:01:44,040 --> 01:01:47,160
Speaker 1: to be on the landscape and resolve the conflicts. It

1158
01:01:47,360 --> 01:01:50,160
Speaker 1: wasn't so much of a concern with the hunting community

1159
01:01:50,160 --> 01:01:52,400
Speaker 1: at that time. Was more live stock at that time,

1160
01:01:52,560 --> 01:01:55,120
Speaker 1: because there were so few wolves. I saw it as

1161
01:01:55,160 --> 01:01:58,000
Speaker 1: a great opportunity and I wanted them to succeed where

1162
01:01:58,040 --> 01:02:00,520
Speaker 1: they could be welcome, where there weren't conflicts of livestock

1163
01:02:00,560 --> 01:02:02,760
Speaker 1: that were in conflicts with hunting. There's so much game

1164
01:02:02,800 --> 01:02:05,000
Speaker 1: on the landscape. They had plenty of food, they had

1165
01:02:05,040 --> 01:02:09,920
Speaker 1: plenty of refugia to live in, landscapes where they could

1166
01:02:10,560 --> 01:02:14,680
Speaker 1: be unbothered. They don't need wilderness. Wolves would live in

1167
01:02:14,720 --> 01:02:17,360
Speaker 1: Bozeman if they could. And they don't need a wilderness area.

1168
01:02:17,360 --> 01:02:19,640
Speaker 1: They just need to have someplace where they can raise pups,

1169
01:02:19,840 --> 01:02:24,120
Speaker 1: find wild ungulates to eat, and live long enough to reproduce.

1170
01:02:24,240 --> 01:02:26,640
Speaker 1: They can live anywhere. I mean, the wolf lives from

1171
01:02:26,640 --> 01:02:28,880
Speaker 1: the Arctic Circle down. There's wolves in the Gaza Strip.

1172
01:02:28,920 --> 01:02:30,720
Speaker 1: They can live in any biome. They can live in

1173
01:02:30,760 --> 01:02:33,440
Speaker 1: the desert, they can live in a temperate force, they

1174
01:02:33,440 --> 01:02:35,840
Speaker 1: can live in the Arctic. They are really adaptable. So

1175
01:02:35,880 --> 01:02:38,920
Speaker 1: it's just matter where we will tolerate their presence. And

1176
01:02:38,960 --> 01:02:41,919
Speaker 1: I knew all that, and I could see him successfully

1177
01:02:41,960 --> 01:02:44,120
Speaker 1: making it. That's why I thought we would be better

1178
01:02:44,160 --> 01:02:48,080
Speaker 1: off holding off in reintroduction, allowing the social landscape to

1179
01:02:48,160 --> 01:02:51,720
Speaker 1: evolve as wolves slowly made their way down the landscape,

1180
01:02:51,720 --> 01:02:54,480
Speaker 1: because it's a social issue. It is not an ecological issue,

1181
01:02:54,560 --> 01:02:57,439
Speaker 1: never has been with wolves. So at the at that

1182
01:02:57,480 --> 01:03:02,919
Speaker 1: time when there was this very controversial plan to to

1183
01:03:02,920 --> 01:03:06,600
Speaker 1: to do a reintroduction, Um, did you sort of feel

1184
01:03:07,440 --> 01:03:11,080
Speaker 1: that were you ostracized by the superpro wolf community for

1185
01:03:11,080 --> 01:03:16,200
Speaker 1: for for not wanting, for not uh advocating or condoning

1186
01:03:16,400 --> 01:03:18,760
Speaker 1: the reintroduction, or was it that you all felt like

1187
01:03:18,800 --> 01:03:20,400
Speaker 1: you were kind of striving for the same thing, you

1188
01:03:20,440 --> 01:03:24,280
Speaker 1: just had different approaches to get there. I don't know

1189
01:03:24,320 --> 01:03:26,680
Speaker 1: that I really would care, because I hear both sides

1190
01:03:26,720 --> 01:03:29,800
Speaker 1: all the time. I mean, I'm always I'm I like

1191
01:03:29,880 --> 01:03:32,080
Speaker 1: the wolves the middle of the road. We have to

1192
01:03:32,080 --> 01:03:34,200
Speaker 1: live in the middle. We can't live out on either end.

1193
01:03:34,320 --> 01:03:38,720
Speaker 1: And I've worked a lot with hunting groups and ranters

1194
01:03:38,720 --> 01:03:43,440
Speaker 1: and wolf conservationists and wolf protectionists. I'm a scientist and

1195
01:03:43,440 --> 01:03:46,120
Speaker 1: I'm driven by science, and US science says that there

1196
01:03:46,240 --> 01:03:48,800
Speaker 1: is place on this landscape for wolves and it's not

1197
01:03:48,840 --> 01:03:52,800
Speaker 1: going to be Nebraska, and probably it's it's not gonna

1198
01:03:52,800 --> 01:03:55,960
Speaker 1: be Boulder, Colorado. But there are places where they can

1199
01:03:56,000 --> 01:03:58,240
Speaker 1: be in and and as long as we can handle

1200
01:03:58,240 --> 01:04:01,520
Speaker 1: and manage the conflicts, there'll be anywhere we want them

1201
01:04:01,560 --> 01:04:04,280
Speaker 1: to be. And as a scientist, I was seeing it happen.

1202
01:04:04,360 --> 01:04:07,040
Speaker 1: So that's why I was against reintroduction. And I imagine

1203
01:04:07,080 --> 01:04:09,720
Speaker 1: there where people that would slap me upside the head

1204
01:04:09,760 --> 01:04:11,720
Speaker 1: if they could, saying, well you should love wolves and

1205
01:04:11,760 --> 01:04:13,840
Speaker 1: have them everywhere, or what the hell is what are

1206
01:04:13,880 --> 01:04:15,720
Speaker 1: you thinking? They're gonna wipe out all the deer. Knilk.

1207
01:04:15,840 --> 01:04:18,000
Speaker 1: I don't listen to that. I'm doing what the science

1208
01:04:18,000 --> 01:04:20,760
Speaker 1: shows me and they can do. But here's here's where

1209
01:04:20,800 --> 01:04:23,600
Speaker 1: you're not. Here's it's not where you're wrong. But it's

1210
01:04:23,600 --> 01:04:26,640
Speaker 1: a little bit where you're like misleading because it's not

1211
01:04:27,120 --> 01:04:32,280
Speaker 1: Science isn't telling you. Science isn't telling you that we

1212
01:04:32,360 --> 01:04:37,520
Speaker 1: need wolves or that we need grizzly bears. Right, you

1213
01:04:37,520 --> 01:04:42,560
Speaker 1: can make the people make these claims. Nod, I said need.

1214
01:04:42,560 --> 01:04:45,320
Speaker 1: But here's the thing. It's a decision. It's it's a

1215
01:04:45,360 --> 01:04:48,960
Speaker 1: decision that we that society makes. It's totally a social

1216
01:04:49,000 --> 01:04:52,880
Speaker 1: fabric thing. Yes, yes, so. And I'm not even wanting

1217
01:04:52,880 --> 01:04:54,480
Speaker 1: to push you too. I'm not trying to push you

1218
01:04:54,520 --> 01:04:56,760
Speaker 1: into a thing because I feel like you know, I'm not,

1219
01:04:56,840 --> 01:04:58,240
Speaker 1: because I feel like you and you and me are

1220
01:04:58,360 --> 01:05:02,800
Speaker 1: like very much aligned. I them around. Okay, you haven't

1221
01:05:02,800 --> 01:05:04,920
Speaker 1: said this, but I'm assuming you do. Like I enjoy

1222
01:05:05,160 --> 01:05:08,320
Speaker 1: them being around. It just comes with um. I have

1223
01:05:08,440 --> 01:05:15,600
Speaker 1: certain requests that come with them being around, about conflicts,

1224
01:05:15,600 --> 01:05:18,760
Speaker 1: like how we control conflict and how we weigh out

1225
01:05:18,840 --> 01:05:23,040
Speaker 1: and value the interests of different stakeholders. And I feel

1226
01:05:23,080 --> 01:05:26,440
Speaker 1: that the ranching perspective is valid and important, and I

1227
01:05:26,480 --> 01:05:29,440
Speaker 1: think the perspective of big game hunters is valid and important.

1228
01:05:29,480 --> 01:05:31,480
Speaker 1: And I don't think that these people are being hysterical

1229
01:05:31,800 --> 01:05:33,920
Speaker 1: when they point out that there are some things that

1230
01:05:33,960 --> 01:05:35,560
Speaker 1: need to be resolved in order for them to get

1231
01:05:35,560 --> 01:05:38,920
Speaker 1: comfortable with this. I didn't. I know, I know, I know,

1232
01:05:38,920 --> 01:05:41,720
Speaker 1: I feel like we're on the same team. But what

1233
01:05:41,760 --> 01:05:44,120
Speaker 1: I'm saying, like when you talk about whether or not

1234
01:05:44,240 --> 01:05:47,320
Speaker 1: wolves would have recolonized the lower forty eight on their own,

1235
01:05:47,440 --> 01:05:49,720
Speaker 1: or whether we needed to do a recount, or whether

1236
01:05:49,760 --> 01:05:52,400
Speaker 1: we need to do a reintroduction to bring them back,

1237
01:05:53,440 --> 01:05:57,760
Speaker 1: I don't accept that you had no sense of what

1238
01:05:57,840 --> 01:06:03,280
Speaker 1: you hoped would happen. You had to have hoped something

1239
01:06:03,280 --> 01:06:06,440
Speaker 1: would happen. I can tell you when it came out

1240
01:06:06,440 --> 01:06:08,280
Speaker 1: here in seventy nine and there was one wolf, I

1241
01:06:08,320 --> 01:06:11,880
Speaker 1: thought of it as an interesting and novel idea and

1242
01:06:12,280 --> 01:06:15,080
Speaker 1: experimental to see if if it would make it or not.

1243
01:06:15,440 --> 01:06:17,400
Speaker 1: If you would have asked me in nineteen seventy nine

1244
01:06:17,440 --> 01:06:20,480
Speaker 1: if we'd be harvesting three hundred wolves a year in

1245
01:06:20,520 --> 01:06:22,320
Speaker 1: two thousand and eighteen, and he said, are you oh

1246
01:06:22,360 --> 01:06:24,520
Speaker 1: to your mind? I mean I never would have believed

1247
01:06:24,520 --> 01:06:27,480
Speaker 1: would have been this far along. So, I mean, I

1248
01:06:27,480 --> 01:06:30,240
Speaker 1: think wolves are pretty amazing creatures. I think that elk

1249
01:06:30,280 --> 01:06:33,280
Speaker 1: are pretty amazing creatures. I think cougars are amazing creatures.

1250
01:06:34,120 --> 01:06:38,120
Speaker 1: I mean, I like all wildlife. I'm trying to think

1251
01:06:38,120 --> 01:06:40,720
Speaker 1: there's an exception, maybe not quite so fun of skunks,

1252
01:06:40,760 --> 01:06:43,480
Speaker 1: but I could have a bird dog. But I mean,

1253
01:06:43,560 --> 01:06:46,320
Speaker 1: I like to see all the full complement of all

1254
01:06:46,360 --> 01:06:48,360
Speaker 1: the predators and all the prey in the landscape. And

1255
01:06:48,360 --> 01:06:51,080
Speaker 1: the thing that I would think back you've read Lewis

1256
01:06:51,080 --> 01:06:54,760
Speaker 1: and clark Journals, Undaunted Courage. They came out here. They

1257
01:06:54,760 --> 01:06:59,160
Speaker 1: are uncountable hundreds of thousands of game animals. Right. It

1258
01:06:59,280 --> 01:07:01,720
Speaker 1: was like to Saren Jetty and there was pray animals

1259
01:07:01,760 --> 01:07:04,560
Speaker 1: and they were predator animals everywhere, and nobody was shooting

1260
01:07:04,680 --> 01:07:08,000
Speaker 1: or controlling any of them, and they were just fine.

1261
01:07:08,640 --> 01:07:10,560
Speaker 1: And when people really push me on an issue, but

1262
01:07:10,760 --> 01:07:13,800
Speaker 1: we have to manage this or that, Yeah, we're doing

1263
01:07:13,800 --> 01:07:16,120
Speaker 1: pretty well managing wolves in Montana. We harvest a lot

1264
01:07:16,160 --> 01:07:18,400
Speaker 1: of them. They're still adequate wolves hair, there's a lot

1265
01:07:18,440 --> 01:07:20,920
Speaker 1: of them, They're very resilient. We can go on like this.

1266
01:07:21,600 --> 01:07:23,720
Speaker 1: But if you want to say, you have to manage

1267
01:07:24,000 --> 01:07:27,360
Speaker 1: predators or they'll eat all the game. If they ate

1268
01:07:27,400 --> 01:07:30,960
Speaker 1: all the game, they'd be dead, right, there'd be no

1269
01:07:31,000 --> 01:07:32,800
Speaker 1: more wolves. There'd be no more game. So what I'm

1270
01:07:32,840 --> 01:07:37,280
Speaker 1: just saying before, when Lewis and Clark came out, nobody

1271
01:07:37,320 --> 01:07:40,560
Speaker 1: managed anything. We barely had firearms at that time, right,

1272
01:07:44,360 --> 01:07:49,080
Speaker 1: limited in scope. Yes, animals manage themselves. The wolves in

1273
01:07:49,200 --> 01:07:52,640
Speaker 1: Yellowstone they kill each other off and the population took

1274
01:07:52,640 --> 01:07:55,280
Speaker 1: off rapidly when they were first introduced. It went up

1275
01:07:55,320 --> 01:07:57,920
Speaker 1: to a peak of about hundred sixty animals in two

1276
01:07:57,920 --> 01:08:01,120
Speaker 1: thousand eleven. It dropped down after that to be about

1277
01:08:01,160 --> 01:08:03,240
Speaker 1: a hundred and it's been about that level for a

1278
01:08:03,240 --> 01:08:05,520
Speaker 1: long time. This year there's less I heard there was

1279
01:08:05,560 --> 01:08:10,000
Speaker 1: about wolves. Now nobody's shooting those wolves. They are regulating

1280
01:08:10,040 --> 01:08:13,760
Speaker 1: themselves based on the prey. Prey populations go up and down,

1281
01:08:14,480 --> 01:08:16,920
Speaker 1: the predator population goes up and down. It's it's a

1282
01:08:17,000 --> 01:08:20,640
Speaker 1: leg time just slightly. That is the normal. And we

1283
01:08:20,720 --> 01:08:23,280
Speaker 1: as humans and I'm a hunter, we like to see

1284
01:08:23,320 --> 01:08:25,559
Speaker 1: something always at a level that we're used to, and

1285
01:08:25,600 --> 01:08:28,200
Speaker 1: when it drops below that way panic. If it goes

1286
01:08:28,240 --> 01:08:30,000
Speaker 1: above that, it's like, oh good, it's getting back to

1287
01:08:30,040 --> 01:08:32,759
Speaker 1: the good old days. The good old days is the average,

1288
01:08:33,240 --> 01:08:35,280
Speaker 1: but we don't look at that. And I'm just saying

1289
01:08:35,280 --> 01:08:37,800
Speaker 1: that if we didn't, if we didn't manage elk or

1290
01:08:37,840 --> 01:08:40,200
Speaker 1: deer wolves, and my department may have an issue with

1291
01:08:40,640 --> 01:08:44,919
Speaker 1: differences of opinions, but animals manage themselves in the landscape,

1292
01:08:44,920 --> 01:08:48,920
Speaker 1: and if there's too few. We had after the big

1293
01:08:48,960 --> 01:08:53,519
Speaker 1: winter of seven, there's a huge record amount of snowfall

1294
01:08:53,560 --> 01:08:57,280
Speaker 1: in northwest Montana and Yellowstone. When they die, not and

1295
01:08:58,200 --> 01:09:01,479
Speaker 1: our white tail died in Montana that one in northwest

1296
01:09:01,560 --> 01:09:05,320
Speaker 1: Montana that spring. The wolves are doing pretty well feeding

1297
01:09:05,320 --> 01:09:07,519
Speaker 1: on carcasses until they had these pups. And then there

1298
01:09:07,520 --> 01:09:09,680
Speaker 1: weren't any fonds in June as alike, as most of

1299
01:09:09,720 --> 01:09:12,920
Speaker 1: the dose died, we had a huge pop mortality. That's

1300
01:09:12,920 --> 01:09:14,720
Speaker 1: how wolves reached fond They don't know the food. The

1301
01:09:14,720 --> 01:09:17,840
Speaker 1: pups don't make it. Meantime, the next winter neew was

1302
01:09:17,880 --> 01:09:20,479
Speaker 1: milder and the prey populations built up, and then the

1303
01:09:20,520 --> 01:09:22,840
Speaker 1: wol was built up. Just this leg cycle, but we

1304
01:09:22,840 --> 01:09:24,800
Speaker 1: always want it right here on the average in the

1305
01:09:24,840 --> 01:09:30,519
Speaker 1: middle um. Two things, a thing that I've always laughed about.

1306
01:09:31,680 --> 01:09:33,040
Speaker 1: I have a lot of friends who are just like

1307
01:09:33,320 --> 01:09:36,160
Speaker 1: rapidly anti wolve. Hey wolves and it's the end of hunting,

1308
01:09:36,600 --> 01:09:39,479
Speaker 1: but they all want to hunt in Alaska. I was like, dude,

1309
01:09:39,520 --> 01:09:41,320
Speaker 1: it must be great to hunt Alaska. And I was like, yeah,

1310
01:09:41,320 --> 01:09:44,519
Speaker 1: you wouldn't like it. Bro these wolves running around, the

1311
01:09:44,720 --> 01:09:47,479
Speaker 1: grizzlies running around, why would you want to go up there?

1312
01:09:47,880 --> 01:09:50,840
Speaker 1: But it's like people view it as they don't. I

1313
01:09:50,840 --> 01:09:55,320
Speaker 1: don't know because people like things to be static. And

1314
01:09:55,720 --> 01:09:58,519
Speaker 1: on that point, my wife's reading this book right now.

1315
01:10:00,400 --> 01:10:04,439
Speaker 1: Uh buyout Buddhist monk and he talked about one of

1316
01:10:04,439 --> 01:10:08,439
Speaker 1: the greatest challenges for people is to accept that there

1317
01:10:08,479 --> 01:10:14,680
Speaker 1: there is no static line that every year you intercept

1318
01:10:15,720 --> 01:10:22,160
Speaker 1: everything in life. You intercept everything in life amidst radical change.

1319
01:10:23,880 --> 01:10:26,679
Speaker 1: And there's something that makes you want to hit something

1320
01:10:27,840 --> 01:10:30,799
Speaker 1: a relationship, whatever, a place you'd like to go on vacation,

1321
01:10:31,320 --> 01:10:33,880
Speaker 1: that you want to act like you hit it in

1322
01:10:34,040 --> 01:10:39,880
Speaker 1: stasis and that that's normal. And then you watch as

1323
01:10:39,960 --> 01:10:42,960
Speaker 1: everything changes and it's disappointing to you. But you hit

1324
01:10:43,040 --> 01:10:47,559
Speaker 1: everything mid change. There's no there's no place to feel

1325
01:10:47,560 --> 01:10:52,200
Speaker 1: comfortable or you have to be comfortable with the idea.

1326
01:10:52,520 --> 01:10:55,320
Speaker 1: There's no place to be comfortable that the only constant

1327
01:10:55,479 --> 01:10:58,880
Speaker 1: is change. Yeah, and I see in the literature now,

1328
01:10:59,000 --> 01:11:02,519
Speaker 1: I mean the terms equilibrium is going away. It's nothing

1329
01:11:02,640 --> 01:11:05,320
Speaker 1: is ever in the uniquilibrium things that are always changing.

1330
01:11:06,080 --> 01:11:08,240
Speaker 1: Are you comfortable doing? Uh? We like to play a

1331
01:11:08,240 --> 01:11:10,680
Speaker 1: little game called looking through the crystal ball. I don't know,

1332
01:11:10,880 --> 01:11:13,720
Speaker 1: not looking through it into it? What's your Colorado? What's

1333
01:11:13,720 --> 01:11:16,520
Speaker 1: your Colorado do? Right now? Do you think it's inevitable?

1334
01:11:16,880 --> 01:11:18,720
Speaker 1: Will you ask? Okay, a minute ago, you asked me

1335
01:11:18,760 --> 01:11:21,040
Speaker 1: about how I felt about the change in the Lower

1336
01:11:21,080 --> 01:11:24,400
Speaker 1: forty eight, because Colorado may be affected by that. Okay, ahead,

1337
01:11:24,439 --> 01:11:27,200
Speaker 1: so we'll start there. So this this change of the

1338
01:11:27,520 --> 01:11:30,040
Speaker 1: taking away in and protection of wolves in Lower forty

1339
01:11:30,240 --> 01:11:32,599
Speaker 1: it will have no impact on the Western States essentially,

1340
01:11:32,640 --> 01:11:36,519
Speaker 1: and because we're already harvesting them and managing them. It

1341
01:11:36,600 --> 01:11:38,400
Speaker 1: may have a little impact in the Midwest because the

1342
01:11:38,439 --> 01:11:41,040
Speaker 1: states there haven't had their hands on the management for

1343
01:11:41,080 --> 01:11:44,040
Speaker 1: a couple of years. But what's your perspective on that,

1344
01:11:44,680 --> 01:11:46,640
Speaker 1: the harvest and trap like we do at some at

1345
01:11:46,680 --> 01:11:48,720
Speaker 1: some level they did for a little bit. We're just

1346
01:11:49,400 --> 01:11:53,760
Speaker 1: her jerky over there. It's litigation stuff. But in the West, weird,

1347
01:11:53,960 --> 01:11:58,040
Speaker 1: you know, Montana Idaho, Wyoming harvesting wolves. It's hard to

1348
01:11:58,080 --> 01:12:00,639
Speaker 1: say exactly where're at because it's really hard count wolves.

1349
01:12:00,680 --> 01:12:04,360
Speaker 1: It's very hard. Is it very hard? Yeah? You never

1350
01:12:04,400 --> 01:12:06,439
Speaker 1: see them. Their secret to them, they're elusive. Is it

1351
01:12:06,479 --> 01:12:10,680
Speaker 1: harder to count wolves and grizzlies? With grizzlies they've been

1352
01:12:10,720 --> 01:12:15,400
Speaker 1: doing DNA work care work. Bears are large there. Yeah,

1353
01:12:15,520 --> 01:12:18,160
Speaker 1: they don't disperse us far. I would say, yes, it's

1354
01:12:18,160 --> 01:12:20,559
Speaker 1: harder to count wolves, and we weren't doing DNA work

1355
01:12:20,640 --> 01:12:24,040
Speaker 1: and sampling everyone. We just know that there's this range

1356
01:12:24,040 --> 01:12:26,000
Speaker 1: of this many wolves out there, and there still seem

1357
01:12:26,080 --> 01:12:28,720
Speaker 1: to be a lot and three hundred wolves sounds like

1358
01:12:28,720 --> 01:12:31,400
Speaker 1: a lot. We don't know how many illegal marks are,

1359
01:12:31,479 --> 01:12:33,800
Speaker 1: how many natural marks, but there's still quite a few

1360
01:12:33,840 --> 01:12:37,800
Speaker 1: wolves out there. Motity sorry, mortalities. Yeah. Well, I always

1361
01:12:37,840 --> 01:12:40,360
Speaker 1: say if we start pushing the wolves too hard, people

1362
01:12:40,360 --> 01:12:42,120
Speaker 1: are going to be less able to harvest them because

1363
01:12:42,160 --> 01:12:44,719
Speaker 1: there'll be that much smarter and they're hard to see anyway,

1364
01:12:44,720 --> 01:12:48,040
Speaker 1: and the harvest level will go down. We'll have to see.

1365
01:12:48,160 --> 01:12:49,920
Speaker 1: This is kind of new wolves coming back in the

1366
01:12:49,920 --> 01:12:51,720
Speaker 1: West with a big harvest. We'll just see how it

1367
01:12:51,760 --> 01:12:56,160
Speaker 1: works out. Um. Then your question again, sorry, what's gonna

1368
01:12:56,160 --> 01:13:00,200
Speaker 1: happen in Colorado? Colorado? Because Colorado is like Colorado right

1369
01:13:00,200 --> 01:13:04,280
Speaker 1: now is in other states too. Um. I think the

1370
01:13:04,400 --> 01:13:07,439
Speaker 1: writings on the wall Oregon, Washington is sort of like

1371
01:13:07,760 --> 01:13:10,920
Speaker 1: you're now very like you are in a wolf state

1372
01:13:11,200 --> 01:13:14,200
Speaker 1: and you're gonna see more wolves, um and there because

1373
01:13:14,400 --> 01:13:17,439
Speaker 1: the political leanings of those states, it's less likely that

1374
01:13:17,439 --> 01:13:20,280
Speaker 1: you're gonna see in any time in the near future.

1375
01:13:20,280 --> 01:13:22,360
Speaker 1: It's less likely you're gonna see the kind of control

1376
01:13:22,720 --> 01:13:24,840
Speaker 1: that I think the hunting and ranching communities would like

1377
01:13:24,880 --> 01:13:29,840
Speaker 1: to see. California never gonna see any control probably. And

1378
01:13:29,880 --> 01:13:34,400
Speaker 1: then but Colorado kind of on the fence politically, on

1379
01:13:34,439 --> 01:13:37,920
Speaker 1: the fence state, UM used to be maybe that changed

1380
01:13:37,960 --> 01:13:41,599
Speaker 1: in recent years. Um. And they're gonna have wolves are

1381
01:13:42,120 --> 01:13:46,040
Speaker 1: there's documented wolves showing up there. And there's also a movement,

1382
01:13:46,439 --> 01:13:49,880
Speaker 1: like a social movement of people wanting to move a

1383
01:13:49,920 --> 01:13:55,400
Speaker 1: little faster and put wolves on the ground. Um. Based

1384
01:13:55,400 --> 01:13:58,719
Speaker 1: on the things that you've seen that we've learned from

1385
01:13:59,040 --> 01:14:03,280
Speaker 1: the experience and Northern Great Lakes, the experience in the

1386
01:14:03,280 --> 01:14:07,840
Speaker 1: Northern Rockies. Uh, what do you think will end up

1387
01:14:07,840 --> 01:14:11,320
Speaker 1: happening in Colorado? And what would be your advice two

1388
01:14:11,320 --> 01:14:16,200
Speaker 1: managers in Colorado. Is that a fair question, it's a

1389
01:14:16,200 --> 01:14:18,880
Speaker 1: fair question. I don't. I don't. I don't have the answer.

1390
01:14:18,920 --> 01:14:21,240
Speaker 1: I would say, if they want wolves and landscape. So

1391
01:14:21,280 --> 01:14:25,040
Speaker 1: there's a talk of reintroducing Mexican wolves up to southern Colorado,

1392
01:14:25,120 --> 01:14:28,040
Speaker 1: and there stock of wolves, allowing wolves to migraty and

1393
01:14:28,120 --> 01:14:31,679
Speaker 1: remain on the landscape from Yellowstone. Those are different gene pools.

1394
01:14:31,680 --> 01:14:36,840
Speaker 1: The Mexican wolf is distinctly different genetically, behaviorally, morphologically from

1395
01:14:36,920 --> 01:14:39,200
Speaker 1: all the rest of the wolves in North America. So

1396
01:14:39,200 --> 01:14:41,439
Speaker 1: it's a little different animal which I don't care to

1397
01:14:41,439 --> 01:14:44,320
Speaker 1: get into. But the gray wolves will get there, and

1398
01:14:44,360 --> 01:14:46,720
Speaker 1: I would The best advice I could give about Colorado

1399
01:14:46,760 --> 01:14:50,479
Speaker 1: would be, don't panic there. There's gonna come in. You've

1400
01:14:50,520 --> 01:14:53,719
Speaker 1: got plenty of time to set up a management plan,

1401
01:14:53,800 --> 01:14:56,600
Speaker 1: a system, and get wildlife services in place, get you know,

1402
01:14:56,680 --> 01:14:59,639
Speaker 1: get input from hunters, get all your public input, get

1403
01:14:59,640 --> 01:15:01,840
Speaker 1: people as aligned as you can. It will never be

1404
01:15:01,920 --> 01:15:05,320
Speaker 1: perfect because people are just very controversial either side, but

1405
01:15:06,000 --> 01:15:09,599
Speaker 1: be prepared, and um look at other states. I mean

1406
01:15:09,640 --> 01:15:13,080
Speaker 1: in Montana. I don't have figures on other Western states,

1407
01:15:13,120 --> 01:15:16,400
Speaker 1: but an hour Montana I hear a lot Oh, the

1408
01:15:16,439 --> 01:15:18,760
Speaker 1: wolves have killed all the darren elk, and I hear

1409
01:15:18,800 --> 01:15:23,479
Speaker 1: that a lot from some segments. Is that true? No,

1410
01:15:23,680 --> 01:15:26,720
Speaker 1: That's where I'm gonna go. So we have our harvest data, fish,

1411
01:15:26,760 --> 01:15:30,360
Speaker 1: willife and parks, and we can show through the harvest,

1412
01:15:31,120 --> 01:15:33,600
Speaker 1: the check stations every fall and the spring green up

1413
01:15:33,640 --> 01:15:36,519
Speaker 1: council where we can't recruitment, number, number of funds or

1414
01:15:36,520 --> 01:15:40,040
Speaker 1: cabs per female b darren elk or sheep or whatever,

1415
01:15:41,160 --> 01:15:43,840
Speaker 1: and our numbers. Wolves have been on the landscape for

1416
01:15:43,920 --> 01:15:46,320
Speaker 1: quite a while, though it's not like they've changed greatly

1417
01:15:46,360 --> 01:15:49,040
Speaker 1: in ten years there except that we had one show

1418
01:15:49,120 --> 01:15:52,240
Speaker 1: up at buildings, but otherwise they're kind of it full.

1419
01:15:52,400 --> 01:15:55,080
Speaker 1: The landscape is full of wolves and deer. Nelk numbers

1420
01:15:55,120 --> 01:15:58,400
Speaker 1: at present are in the long term average. They've slightly

1421
01:15:58,439 --> 01:16:00,479
Speaker 1: to the high end. The last two winners are slightly

1422
01:16:00,520 --> 01:16:04,360
Speaker 1: down because we've had pretty long winters um and we

1423
01:16:04,360 --> 01:16:07,840
Speaker 1: haven't had the recruitment. But they're not they're not off

1424
01:16:07,880 --> 01:16:10,280
Speaker 1: the scale in the black hole. So when people say,

1425
01:16:10,880 --> 01:16:13,800
Speaker 1: I used I've hunted this area for thirty eight years

1426
01:16:13,880 --> 01:16:15,000
Speaker 1: and I used to be able to go up there

1427
01:16:15,040 --> 01:16:17,240
Speaker 1: and get an elk and the wolves. Since the wolves

1428
01:16:17,240 --> 01:16:20,280
Speaker 1: have come back. They've killed all the elk, and I'm

1429
01:16:20,520 --> 01:16:22,920
Speaker 1: thinking about that, and our numbers don't support that. The

1430
01:16:22,960 --> 01:16:26,200
Speaker 1: game struct stations in the spring count showed the animals

1431
01:16:26,560 --> 01:16:29,800
Speaker 1: are in the region, But maybe the habitat has grown

1432
01:16:29,880 --> 01:16:32,400
Speaker 1: up there, maybe there's more road access, maybe there's more

1433
01:16:32,439 --> 01:16:36,280
Speaker 1: competition for people going after those animals. There's a variety

1434
01:16:36,280 --> 01:16:38,240
Speaker 1: of things. There's wildfire, and I just say, well, if

1435
01:16:38,400 --> 01:16:40,320
Speaker 1: if you're hunting the same area for thirty years and

1436
01:16:40,360 --> 01:16:42,960
Speaker 1: the animals aren't there anymore, maybe move ten miles or

1437
01:16:43,000 --> 01:16:45,799
Speaker 1: fifteen You don't so you don't accept, like take for instance,

1438
01:16:45,840 --> 01:16:49,160
Speaker 1: the Idaho Panhandle or the Northern Yellows don't hurt. You

1439
01:16:49,200 --> 01:16:56,519
Speaker 1: don't accept that those elk populations were reduced by two thirds.

1440
01:16:57,240 --> 01:16:59,479
Speaker 1: I don't know about the Idho Panhandle situation. I don't

1441
01:16:59,479 --> 01:17:02,679
Speaker 1: follow it. I can only tell you from Montana. Sorry,

1442
01:17:02,760 --> 01:17:05,680
Speaker 1: that's just my limited scope of my job. So I

1443
01:17:05,720 --> 01:17:10,880
Speaker 1: do know. I'm just saying the harvest data shows the

1444
01:17:11,000 --> 01:17:13,360
Speaker 1: animals are still out there, but they may be using

1445
01:17:13,400 --> 01:17:18,799
Speaker 1: the landscape differently. They may be moving during hunting season differently.

1446
01:17:18,840 --> 01:17:23,240
Speaker 1: We do have climate change. Things are changing differently. I

1447
01:17:23,240 --> 01:17:24,800
Speaker 1: don't have an answer to all for it. I'm just

1448
01:17:24,840 --> 01:17:27,840
Speaker 1: saying numbers show that the animals are still out there,

1449
01:17:27,840 --> 01:17:29,960
Speaker 1: and if people aren't seeing them, maybe the animals are

1450
01:17:30,000 --> 01:17:33,599
Speaker 1: becoming more nocturnal. I don't know. I don't know, and

1451
01:17:33,640 --> 01:17:37,720
Speaker 1: I've hunt darn up too, and I'm able to get

1452
01:17:37,760 --> 01:17:39,599
Speaker 1: dar nol and i live where there's a lot of wolves.

1453
01:17:39,760 --> 01:17:44,040
Speaker 1: So um I have in the past. UM. I don't

1454
01:17:44,080 --> 01:17:47,679
Speaker 1: have an answer except to say that wolves can drive

1455
01:17:47,800 --> 01:17:51,639
Speaker 1: population is really low, they can keep some bear. If

1456
01:17:51,680 --> 01:17:54,280
Speaker 1: that happens, the wolf numbers decrease, they gotta have food.

1457
01:17:55,800 --> 01:17:59,080
Speaker 1: How long does that cycle play out depends in the habitat.

1458
01:17:59,160 --> 01:18:02,840
Speaker 1: I mean you've orout up earlier about the Northern Netherland herd.

1459
01:18:02,880 --> 01:18:04,880
Speaker 1: I think, honest, you brought it up. Was it twenty

1460
01:18:04,920 --> 01:18:07,439
Speaker 1: thousand or so? And then wolves came back and they

1461
01:18:07,479 --> 01:18:09,600
Speaker 1: went down to four thousand. I think this year. I

1462
01:18:09,640 --> 01:18:10,960
Speaker 1: just heard the number of this week when I was

1463
01:18:10,960 --> 01:18:13,160
Speaker 1: down there, it's up like six thousand. Now there's a

1464
01:18:13,360 --> 01:18:16,559
Speaker 1: lot of bison. Yeah, I'm reading right now about the

1465
01:18:16,600 --> 01:18:21,160
Speaker 1: Northern herd, and it's the last count in seventeen was

1466
01:18:21,560 --> 01:18:25,960
Speaker 1: five thousand, threety nine, so it has been so that's

1467
01:18:26,080 --> 01:18:29,280
Speaker 1: two seventeen yeah, and it's been stable like that. We're

1468
01:18:29,320 --> 01:18:34,400
Speaker 1: increasing for four years. It so the northern herd. So

1469
01:18:34,439 --> 01:18:39,160
Speaker 1: the wolves went in the winter nine seven. I think

1470
01:18:39,160 --> 01:18:42,280
Speaker 1: they put thirty one wolves in half each of those years.

1471
01:18:42,760 --> 01:18:44,720
Speaker 1: We had that enormous winter. I don't know if you

1472
01:18:44,720 --> 01:18:48,240
Speaker 1: guys were here in n seven. The snow at my

1473
01:18:48,280 --> 01:18:52,400
Speaker 1: out house was five ft deep. That's what killed the

1474
01:18:52,400 --> 01:18:56,880
Speaker 1: elk in one winner. I mean thirty fifteen thirty one

1475
01:18:56,880 --> 01:19:00,080
Speaker 1: wolves over two years. Do you think the eighteen was

1476
01:19:00,120 --> 01:19:04,280
Speaker 1: an elk or fifteen elk in two years? Think about it.

1477
01:19:04,479 --> 01:19:07,680
Speaker 1: I mean the numbers dropped off really fast, and then

1478
01:19:07,720 --> 01:19:10,200
Speaker 1: they've been kept low, and I can't say if the

1479
01:19:10,200 --> 01:19:11,960
Speaker 1: wolves kept him low or not. Probably has something to do

1480
01:19:11,920 --> 01:19:15,040
Speaker 1: do it. There's wolves, there's grizzly bears, there's lions there

1481
01:19:15,120 --> 01:19:17,400
Speaker 1: and the wolves. It's interesting they have switched. There was

1482
01:19:17,479 --> 01:19:20,000
Speaker 1: printed and primarily an elk grocery store when they first

1483
01:19:20,000 --> 01:19:23,559
Speaker 1: got there, and now they're switching to bison because there's

1484
01:19:23,600 --> 01:19:27,599
Speaker 1: more biomasso bison. It's a lot harder to kill a bison.

1485
01:19:27,640 --> 01:19:32,000
Speaker 1: There's less wolves. But I don't want to do. Why

1486
01:19:32,000 --> 01:19:35,240
Speaker 1: do you have shirt written on your hands? Reminder? Something

1487
01:19:35,240 --> 01:19:41,479
Speaker 1: I had to do later today there are Okay, they

1488
01:19:41,479 --> 01:19:43,920
Speaker 1: eat seven pounds of meat a day. They can eat

1489
01:19:43,920 --> 01:19:48,040
Speaker 1: more maintenances, like eight pounds per day. So you have

1490
01:19:48,160 --> 01:19:53,120
Speaker 1: several hundred of something eating pounds of stuff a day.

1491
01:19:53,400 --> 01:19:57,040
Speaker 1: There's has to be there has to be an effect.

1492
01:19:57,400 --> 01:19:59,040
Speaker 1: I thought we had this conversation with one of your

1493
01:19:59,040 --> 01:20:05,400
Speaker 1: colleagues who works mountain lions, where I find that, um,

1494
01:20:05,479 --> 01:20:09,160
Speaker 1: I find that you have these two extreme views. You

1495
01:20:09,320 --> 01:20:14,200
Speaker 1: have the perspective of people who again feel that they

1496
01:20:14,600 --> 01:20:19,439
Speaker 1: annihilate the prey base and eliminate ungulates from the landscape, which,

1497
01:20:19,479 --> 01:20:21,960
Speaker 1: as you pointed out, is counterintuitive because then you would

1498
01:20:22,000 --> 01:20:26,040
Speaker 1: also lose the wolves to die and maybe gone. And

1499
01:20:26,080 --> 01:20:31,080
Speaker 1: then you have the perspective of the ardent apologists who

1500
01:20:31,120 --> 01:20:34,320
Speaker 1: want to tell you that there is no population level

1501
01:20:34,400 --> 01:20:39,320
Speaker 1: impact from wolves, mountain lions, coyotes, what have you, and

1502
01:20:39,360 --> 01:20:43,320
Speaker 1: that they somehow subsist on nuts and berries. You you

1503
01:20:44,760 --> 01:20:49,240
Speaker 1: hear from these you hear from these different views. And

1504
01:20:49,400 --> 01:20:51,960
Speaker 1: when someone tries to sell me on one of these

1505
01:20:51,960 --> 01:20:57,519
Speaker 1: two perspectives, I get frustrated. There there there is I

1506
01:20:58,200 --> 01:21:01,080
Speaker 1: feel like you're tiptoeing around, tiptoeing around it. I feel

1507
01:21:01,080 --> 01:21:03,960
Speaker 1: like you're trying. You're suggesting that there's not a population

1508
01:21:04,040 --> 01:21:07,400
Speaker 1: level impact from having hundreds of wolves on the landscape.

1509
01:21:07,560 --> 01:21:09,960
Speaker 1: I didn't say that, but you kind of. That's I

1510
01:21:10,080 --> 01:21:11,200
Speaker 1: trying to get you. I want you to say it.

1511
01:21:11,280 --> 01:21:13,000
Speaker 1: I want you to say what you think is So,

1512
01:21:13,040 --> 01:21:15,840
Speaker 1: what I'm telling you is that fish wife and parks

1513
01:21:15,840 --> 01:21:20,360
Speaker 1: harvest data data and the spring count data are still

1514
01:21:20,400 --> 01:21:23,200
Speaker 1: within the norm range and a little on the high end,

1515
01:21:23,200 --> 01:21:24,960
Speaker 1: except the last two years where the winter has been

1516
01:21:25,000 --> 01:21:27,919
Speaker 1: bad and there are hundreds of wolves in the landscape.

1517
01:21:27,920 --> 01:21:31,920
Speaker 1: That's for deer. Now do you feel that winter do

1518
01:21:31,920 --> 01:21:33,720
Speaker 1: you feel that winter is more? Is more of a

1519
01:21:33,840 --> 01:21:37,519
Speaker 1: driver of Absolutely is more of a driver. One winter

1520
01:21:37,640 --> 01:21:40,680
Speaker 1: like this es it came in and killed in the

1521
01:21:40,680 --> 01:21:43,320
Speaker 1: white tails. You could have sauce and wolves and the landscape.

1522
01:21:43,400 --> 01:21:45,400
Speaker 1: They're not going to kill forty percent of the white tails.

1523
01:21:46,240 --> 01:21:50,400
Speaker 1: Winter is the ultimate driver. And the when people when

1524
01:21:50,439 --> 01:21:52,840
Speaker 1: wolves look where wolves are gonna live, they say, oh,

1525
01:21:52,840 --> 01:21:54,479
Speaker 1: where are they going to live? They're going to live

1526
01:21:54,479 --> 01:21:56,479
Speaker 1: in place where the winter ranges. They're not going to

1527
01:21:56,600 --> 01:21:58,120
Speaker 1: live up in the snow and rocks in the Wilderness

1528
01:21:58,160 --> 01:21:59,800
Speaker 1: series like some people think they do. It's like, what

1529
01:22:00,000 --> 01:22:02,759
Speaker 1: the hell are they gonna eat in december, there's nothing

1530
01:22:02,840 --> 01:22:05,559
Speaker 1: up there. They come down in the valleys, they come

1531
01:22:05,600 --> 01:22:07,760
Speaker 1: down in the winter ranges, they come down to where

1532
01:22:07,800 --> 01:22:09,840
Speaker 1: people are in calves because it's the valley bottom and

1533
01:22:09,880 --> 01:22:12,320
Speaker 1: they're loud as lousy with deer and elk were starving

1534
01:22:12,360 --> 01:22:14,160
Speaker 1: along with the calves that are being born this time

1535
01:22:14,200 --> 01:22:17,200
Speaker 1: of year. It's you know, there's conflicts set up. Potentially

1536
01:22:17,400 --> 01:22:20,880
Speaker 1: some wolves have conflicts and don't you know, it's in

1537
01:22:21,040 --> 01:22:23,800
Speaker 1: back to this things. So I'm not saying it was

1538
01:22:23,840 --> 01:22:26,920
Speaker 1: all winter. I'm just saying there was a really So

1539
01:22:26,960 --> 01:22:29,040
Speaker 1: if you know, if you saw Yellowstone in the sixties,

1540
01:22:29,040 --> 01:22:32,479
Speaker 1: they were paid people to go out to kill mule, deer,

1541
01:22:32,520 --> 01:22:36,480
Speaker 1: and elk because the landscape was so devastated by the overgrazing,

1542
01:22:36,479 --> 01:22:38,720
Speaker 1: because there was no predators. That's a fact. You can

1543
01:22:38,840 --> 01:22:41,200
Speaker 1: look it up. People gunners were paid to shoot deer

1544
01:22:41,240 --> 01:22:43,840
Speaker 1: and elk on the landscape. So now we're up to

1545
01:22:44,880 --> 01:22:49,360
Speaker 1: it is never Historically it wasn't that high. I mean,

1546
01:22:49,360 --> 01:22:50,840
Speaker 1: if you look at you could go down to the

1547
01:22:50,840 --> 01:22:53,559
Speaker 1: Old Stone knowledge still see major impacts on the brows.

1548
01:22:53,640 --> 01:22:55,760
Speaker 1: You can look at the exclosures, defenses. You know, the

1549
01:22:55,760 --> 01:22:58,080
Speaker 1: story down there it's not new to us and maybe

1550
01:22:58,120 --> 01:23:00,840
Speaker 1: new to your listeners. Wolves him on the landscape. We

1551
01:23:00,880 --> 01:23:04,200
Speaker 1: had this massive hard winter. He died like flies. Additionally,

1552
01:23:04,240 --> 01:23:06,000
Speaker 1: there were a lot of what it has been termed

1553
01:23:06,080 --> 01:23:09,120
Speaker 1: naive elk that had never seen a wolf, and the

1554
01:23:09,160 --> 01:23:10,720
Speaker 1: wolves come running up to him and they just kind

1555
01:23:10,720 --> 01:23:13,160
Speaker 1: of stand look because they don't know what it is. Boom,

1556
01:23:13,200 --> 01:23:16,640
Speaker 1: they're dead. They had fat city, those those wolves the

1557
01:23:16,640 --> 01:23:19,160
Speaker 1: first few years, and they definitely helped take the numbers down.

1558
01:23:19,240 --> 01:23:25,679
Speaker 1: There's no doubt about it. Um, So, is five thousand sustainable? Yeah?

1559
01:23:25,880 --> 01:23:32,040
Speaker 1: Is it socially acceptable some circles know. Is socially acceptable?

1560
01:23:32,200 --> 01:23:36,479
Speaker 1: You bat? Is it ecologically sustainable? No? So you kind

1561
01:23:36,479 --> 01:23:39,400
Speaker 1: of have to think about what is realistic to be

1562
01:23:39,439 --> 01:23:42,000
Speaker 1: on the landscape. Yeah, that we weren't going to hold

1563
01:23:42,040 --> 01:23:45,000
Speaker 1: that as a norm, correct, That's what I'm saying. I'm

1564
01:23:45,000 --> 01:23:47,240
Speaker 1: not saying that that's a really good point because nobody ever,

1565
01:23:47,360 --> 01:23:50,360
Speaker 1: everybody always loves that twenty thousand number. Nobody ever says

1566
01:23:50,400 --> 01:23:53,400
Speaker 1: what it was five years prior. That's when we that's

1567
01:23:53,400 --> 01:23:56,080
Speaker 1: when we came into the country. Man, me and my

1568
01:23:56,160 --> 01:23:59,840
Speaker 1: bro started hunting that herd and how many what was

1569
01:23:59,880 --> 01:24:02,040
Speaker 1: the Oh? Yeah, when they were at there. I remember

1570
01:24:02,040 --> 01:24:03,920
Speaker 1: where I was standing, I remember where I was staying it,

1571
01:24:03,920 --> 01:24:05,400
Speaker 1: and I could figure I could sit and figure it

1572
01:24:05,439 --> 01:24:07,240
Speaker 1: out by year. I remember where I was staying when

1573
01:24:07,240 --> 01:24:11,439
Speaker 1: I heard the first wolf hole down there. Yeah, and

1574
01:24:11,520 --> 01:24:13,840
Speaker 1: you know what we thought it was. I heard it

1575
01:24:13,960 --> 01:24:18,320
Speaker 1: rip out. I thought it was a bugle. Oh sure,

1576
01:24:18,720 --> 01:24:21,719
Speaker 1: because it's just like you know what it was? Well, yeah,

1577
01:24:21,800 --> 01:24:24,040
Speaker 1: I thought I thought it was some kind of crazy bugle.

1578
01:24:24,920 --> 01:24:27,840
Speaker 1: And they we're like, holy ship, that's wolves, man, and

1579
01:24:28,160 --> 01:24:31,160
Speaker 1: all this extreme viewpoint on the yellow Stone or all

1580
01:24:31,200 --> 01:24:33,879
Speaker 1: I can see is just kind of let the rhetoric

1581
01:24:33,920 --> 01:24:36,080
Speaker 1: go in the BS drop and kind of think about

1582
01:24:36,240 --> 01:24:39,160
Speaker 1: the sustainability and maybe you want to see the herd

1583
01:24:39,200 --> 01:24:43,800
Speaker 1: at ten thousand. Oh, that would maybe happen, but it

1584
01:24:44,000 --> 01:24:47,240
Speaker 1: probably won't. It's probably gonna stay about where it is

1585
01:24:47,439 --> 01:24:52,360
Speaker 1: unless there's some huge campaign to kill off lions and

1586
01:24:52,439 --> 01:24:54,120
Speaker 1: wolves and bears, and then you know what's gonna happen.

1587
01:24:54,120 --> 01:24:56,519
Speaker 1: You're gonna have your jump up and they're gonna starve

1588
01:24:56,560 --> 01:24:59,559
Speaker 1: again like they were doing. Uh, what's going on with

1589
01:25:01,960 --> 01:25:07,400
Speaker 1: Isle Royal National Park? So Iole Royal. The two Wolves

1590
01:25:07,439 --> 01:25:10,439
Speaker 1: came out in about ninety or so. Back up, back up,

1591
01:25:11,880 --> 01:25:14,160
Speaker 1: because I gotta say something first. It's an island and

1592
01:25:14,240 --> 01:25:18,880
Speaker 1: Lake Superior belongs to Michigan, right, yeah, yeah, it's the

1593
01:25:18,880 --> 01:25:21,360
Speaker 1: only little free standing national park and it's not very big.

1594
01:25:21,560 --> 01:25:23,439
Speaker 1: I think it's oh my gosh, I think it's only

1595
01:25:23,439 --> 01:25:27,240
Speaker 1: two square miles or something. Okay, our country wolf territories

1596
01:25:27,280 --> 01:25:29,960
Speaker 1: are bigger than that. For one pack. Oh that's interesting,

1597
01:25:31,200 --> 01:25:32,599
Speaker 1: take it away. I just wanted people know what we're

1598
01:25:32,640 --> 01:25:36,240
Speaker 1: talking about. Midwestern wolves, smaller groups, smaller wolves, they have

1599
01:25:36,320 --> 01:25:41,080
Speaker 1: smaller territories. So anyway, Ile Roil has never been colonized.

1600
01:25:41,080 --> 01:25:43,320
Speaker 1: Initially in the fifties, they've had a couple of the

1601
01:25:43,400 --> 01:25:45,320
Speaker 1: wolves that have shown up when the lake is frozen,

1602
01:25:45,360 --> 01:25:47,640
Speaker 1: but it's a rare thing. The lake freezes about once

1603
01:25:47,680 --> 01:25:51,680
Speaker 1: every decade, allowing genetic exchange potentially. But they've determined through

1604
01:25:51,680 --> 01:25:56,200
Speaker 1: genetics the wolves have not had outbreeding and they're all

1605
01:25:56,280 --> 01:25:58,320
Speaker 1: very closely related and so by now they've been in

1606
01:25:58,360 --> 01:26:01,760
Speaker 1: breeding for seventy years. So the the original ones that

1607
01:26:01,800 --> 01:26:04,080
Speaker 1: showed up, they kind of made Ile Royal like a

1608
01:26:04,120 --> 01:26:07,720
Speaker 1: wolf place walked across the ice in Canada. Correct, they

1609
01:26:07,720 --> 01:26:09,720
Speaker 1: were not put there either, They walked and frozen when

1610
01:26:09,800 --> 01:26:11,960
Speaker 1: they documented it, and they showed up and just had

1611
01:26:12,360 --> 01:26:14,280
Speaker 1: and had the running place because there's a bunch of

1612
01:26:14,479 --> 01:26:16,360
Speaker 1: there's a bunch of moves, oh heck yeah. And there's

1613
01:26:16,400 --> 01:26:19,519
Speaker 1: nothing to eat the most except ticks. The biggest predator

1614
01:26:19,640 --> 01:26:22,280
Speaker 1: tick on the Royal Moost is a winter tick. It

1615
01:26:22,439 --> 01:26:26,040
Speaker 1: was more more wolves than than wolves, I think so. Anyway,

1616
01:26:26,080 --> 01:26:28,960
Speaker 1: so the wolves make it out there, and they're all

1617
01:26:28,960 --> 01:26:31,439
Speaker 1: in bred now. And the last surviving two wolves as

1618
01:26:31,479 --> 01:26:33,840
Speaker 1: a father and a daughter, and they were down to

1619
01:26:33,880 --> 01:26:38,120
Speaker 1: two two there don't inter breed and they're wolves don't

1620
01:26:38,120 --> 01:26:40,800
Speaker 1: do well when there's not a lot of exchange. No,

1621
01:26:40,840 --> 01:26:44,040
Speaker 1: they're just so in bred. They've got they've got through

1622
01:26:44,040 --> 01:26:46,559
Speaker 1: the four genetics. Are like siblings. All them are like

1623
01:26:46,600 --> 01:26:49,720
Speaker 1: siblings now. And of course they are not gonna they've

1624
01:26:49,720 --> 01:26:52,840
Speaker 1: been in a breeding for too long, and they've got deficiencies,

1625
01:26:52,840 --> 01:26:55,960
Speaker 1: physical deficiencies. They're not resilient to disease. They got screwed

1626
01:26:56,000 --> 01:26:58,640
Speaker 1: up tails, they got screwed up spines. Anyway, they're kind

1627
01:26:58,680 --> 01:27:02,040
Speaker 1: of a mess. They're done. So then this reintroduction efforts

1628
01:27:02,120 --> 01:27:05,599
Speaker 1: just happened and as of this morning, hot off the press,

1629
01:27:06,080 --> 01:27:09,120
Speaker 1: they have brought fifth They brought thirteen new wolves to

1630
01:27:09,160 --> 01:27:12,439
Speaker 1: Ile Royal to add to the two they calmed legacy wolves.

1631
01:27:12,479 --> 01:27:14,640
Speaker 1: The two that are remaining, they aren't going to be

1632
01:27:14,720 --> 01:27:16,600
Speaker 1: breeding unless they could mix it up with some of

1633
01:27:16,640 --> 01:27:19,160
Speaker 1: the new ones, which is the whole they're bringing in

1634
01:27:19,200 --> 01:27:23,120
Speaker 1: super wolves. They're bringing in those little tiny midget Great

1635
01:27:23,200 --> 01:27:27,160
Speaker 1: Lakes wolves from So they got some from a little

1636
01:27:27,160 --> 01:27:29,880
Speaker 1: island called Coton, which is in Lake Superior, but it's

1637
01:27:29,880 --> 01:27:32,320
Speaker 1: in the Michigan portion. They've gotten some from the mainland

1638
01:27:32,360 --> 01:27:36,160
Speaker 1: Ontario there, and they've taken some from Minnesota close by,

1639
01:27:36,439 --> 01:27:38,200
Speaker 1: and they may now try and get a few more

1640
01:27:38,200 --> 01:27:43,800
Speaker 1: out of you, Michigan to keep the genetic stock variability.

1641
01:27:43,960 --> 01:27:46,559
Speaker 1: They added thirteen. That's the number as of this morning.

1642
01:27:46,560 --> 01:27:49,280
Speaker 1: They just brought some more in this week to mingle

1643
01:27:49,320 --> 01:27:50,800
Speaker 1: with the two that are there. So they have a

1644
01:27:50,840 --> 01:27:54,160
Speaker 1: total of fifteen now it's about half male and half female.

1645
01:27:54,160 --> 01:27:57,160
Speaker 1: They how can such how can two square miles support

1646
01:27:57,200 --> 01:28:00,639
Speaker 1: fifteen wolves because they're so dang many moose there, they

1647
01:28:00,680 --> 01:28:03,439
Speaker 1: can't possibly can't eat them all, I find it. So

1648
01:28:03,560 --> 01:28:06,360
Speaker 1: this is this question about We were just talking about

1649
01:28:06,360 --> 01:28:09,160
Speaker 1: this last night again at dinner. But so the wolves

1650
01:28:09,160 --> 01:28:11,920
Speaker 1: on Ile Royal can eat beaver, and they can eat moose,

1651
01:28:12,720 --> 01:28:15,960
Speaker 1: and there's a few fox and that's that's it. That's

1652
01:28:15,960 --> 01:28:18,080
Speaker 1: their food source. But there are so many moose. And

1653
01:28:18,120 --> 01:28:21,519
Speaker 1: because wolves are territorial, the population of the island, I

1654
01:28:21,520 --> 01:28:24,200
Speaker 1: think that its highest point. I'm trying to remember the numbers.

1655
01:28:24,200 --> 01:28:26,200
Speaker 1: You're really pushing me on this. It might have been

1656
01:28:26,200 --> 01:28:30,200
Speaker 1: about fifty or so that many wolves around them, multiple packs,

1657
01:28:30,560 --> 01:28:32,519
Speaker 1: and then it dropped back down and then it's been

1658
01:28:32,560 --> 01:28:34,320
Speaker 1: lower and now we're down to two and they're gonna

1659
01:28:34,360 --> 01:28:37,559
Speaker 1: they're gonna go to extinction. Driven to extinction, clearly, but

1660
01:28:37,640 --> 01:28:39,360
Speaker 1: it's not due to lack of food. They did never

1661
01:28:39,439 --> 01:28:41,880
Speaker 1: kill the moose up. They never got you. They never

1662
01:28:41,880 --> 01:28:44,559
Speaker 1: did it. But that is different from what we have

1663
01:28:44,680 --> 01:28:50,400
Speaker 1: most other extinction extrapation, well extrapation indicates to me human

1664
01:28:50,439 --> 01:28:53,240
Speaker 1: cause I don't know anyway, a regional, okay, like regional,

1665
01:28:53,400 --> 01:28:57,280
Speaker 1: like very specific regional extinction, the island island would be

1666
01:28:57,280 --> 01:29:00,880
Speaker 1: free of wolves once again. And my thoughts on that

1667
01:29:00,960 --> 01:29:04,240
Speaker 1: are probably over e ens of time and glacial periods

1668
01:29:04,240 --> 01:29:08,840
Speaker 1: and whatever. Ile Royal has had multiple colonizations and disappearances

1669
01:29:08,880 --> 01:29:13,160
Speaker 1: of wolves over time, and interestingly, I was talking to

1670
01:29:13,200 --> 01:29:15,519
Speaker 1: a biologist day Mates who worked on there early, and

1671
01:29:15,520 --> 01:29:19,080
Speaker 1: he said the people who were there around nine ten,

1672
01:29:19,160 --> 01:29:21,440
Speaker 1: they were out there early and they were miners and trappers.

1673
01:29:22,280 --> 01:29:26,200
Speaker 1: Around the turn of the century, the island had caribou

1674
01:29:26,880 --> 01:29:32,640
Speaker 1: and links and there were no wolves, caribou and a

1675
01:29:32,720 --> 01:29:36,040
Speaker 1: few most but remember the ratio of moost to caribou.

1676
01:29:36,080 --> 01:29:39,639
Speaker 1: But the caribou and extinct. And Dave said he saw

1677
01:29:39,680 --> 01:29:42,160
Speaker 1: what was probably the last links track on the island

1678
01:29:42,160 --> 01:29:46,560
Speaker 1: when he arrived there about nineteen sixty sometime in the sixties.

1679
01:29:47,040 --> 01:29:49,800
Speaker 1: And now there's not so things constantly changed. So we

1680
01:29:49,840 --> 01:29:52,360
Speaker 1: want our window to be the right window. So if

1681
01:29:52,400 --> 01:29:55,120
Speaker 1: you look at Isisle Royal nine hundred, there were no

1682
01:29:55,200 --> 01:29:58,320
Speaker 1: wolves and not and there's tons of caribou links and coyotes.

1683
01:29:58,400 --> 01:30:00,800
Speaker 1: There was coyotes and there was no fox. It's a

1684
01:30:00,840 --> 01:30:04,479
Speaker 1: totally different ecosystem now and that's not because we've changed it.

1685
01:30:04,680 --> 01:30:06,599
Speaker 1: The wolves have changed it. But moose got out there

1686
01:30:07,200 --> 01:30:09,280
Speaker 1: and they caribou went away. I mean, there's a brain

1687
01:30:09,320 --> 01:30:11,200
Speaker 1: worm that goes for most to carible. I'm not sure

1688
01:30:11,200 --> 01:30:14,080
Speaker 1: why the caribl went away, if they were overhunted or

1689
01:30:14,240 --> 01:30:17,240
Speaker 1: or died from brainworm or whatever, but it's a completely

1690
01:30:17,240 --> 01:30:20,080
Speaker 1: different ecosystem in a very short lifetime that we can

1691
01:30:20,160 --> 01:30:24,240
Speaker 1: document that happens all over. Are you gonna blame somebody

1692
01:30:24,320 --> 01:30:28,839
Speaker 1: or a species or a fire or whatever. It's everything

1693
01:30:28,960 --> 01:30:32,439
Speaker 1: is so complex. You asked me these black and white answer.

1694
01:30:32,640 --> 01:30:35,680
Speaker 1: I want to know what you have, and it's like,

1695
01:30:36,479 --> 01:30:38,519
Speaker 1: I can't. It's kind of like the change in Big Game.

1696
01:30:38,560 --> 01:30:40,200
Speaker 1: If you aren't seeing Oak, or you've been seeing him

1697
01:30:40,200 --> 01:30:43,040
Speaker 1: for thirty eight years, go someplace a little different. There's

1698
01:30:43,080 --> 01:30:45,800
Speaker 1: places in Montana where they just so bloody overrun without

1699
01:30:45,840 --> 01:30:48,479
Speaker 1: they're giving away to permits, and they're having shoulder seasons either.

1700
01:30:48,560 --> 01:30:51,280
Speaker 1: And it's like if you're living someplace and you want

1701
01:30:51,320 --> 01:30:53,840
Speaker 1: to get to go to one of those areas, I mean,

1702
01:30:54,040 --> 01:30:57,759
Speaker 1: you don't have to go five miles, but the animals

1703
01:30:57,760 --> 01:31:00,519
Speaker 1: are out there. They may be using the lanski differently,

1704
01:31:00,520 --> 01:31:03,559
Speaker 1: they may be more nocturnal. There are some areas where

1705
01:31:03,600 --> 01:31:05,800
Speaker 1: there's more hunting pressure than there used to be. Go

1706
01:31:05,960 --> 01:31:10,120
Speaker 1: someplace where there's less. We were hunting one time and

1707
01:31:10,240 --> 01:31:13,479
Speaker 1: met a guy. I didn't actually talk to him. Do

1708
01:31:13,479 --> 01:31:16,040
Speaker 1: you remember who actually talked to him? We're hunting with Remy.

1709
01:31:16,240 --> 01:31:24,599
Speaker 1: I was there, Yeah, and uh, Pat and uh I think, Yeah,

1710
01:31:24,640 --> 01:31:27,439
Speaker 1: he was hunting deer, and he was on his way out,

1711
01:31:28,320 --> 01:31:32,040
Speaker 1: and he had been hunting following tracks and ran into

1712
01:31:32,360 --> 01:31:35,559
Speaker 1: wolf tracks and just said that that was the norm

1713
01:31:35,640 --> 01:31:38,840
Speaker 1: now there that always his deer tracks always end in

1714
01:31:38,880 --> 01:31:42,920
Speaker 1: wolf tracks, and therefore there's no deer around. He's not

1715
01:31:43,000 --> 01:31:46,120
Speaker 1: killing any deer. He left in a huff, but you're

1716
01:31:46,120 --> 01:31:51,360
Speaker 1: seeing deer tracks and parts of the same place. So

1717
01:31:51,800 --> 01:31:53,760
Speaker 1: I have to tell you the most incredible. I thought,

1718
01:31:53,800 --> 01:31:55,320
Speaker 1: I've kind of heard all the wolf stories, but this

1719
01:31:55,360 --> 01:31:57,680
Speaker 1: is kind of a fun one. I just heard from

1720
01:31:57,720 --> 01:32:01,400
Speaker 1: a friend who had talked to somebody about wolves a

1721
01:32:01,400 --> 01:32:03,040
Speaker 1: few years ago. I said, you know who was really

1722
01:32:03,080 --> 01:32:06,320
Speaker 1: pushing the wolf for introduction. Don't you choose a government employee?

1723
01:32:06,560 --> 01:32:11,639
Speaker 1: She said, no, who, she says, the insurance companies. Why

1724
01:32:11,720 --> 01:32:15,519
Speaker 1: is that? Because the rate of white til der and

1725
01:32:15,640 --> 01:32:18,280
Speaker 1: car collusions is so high in northwest Montana that they

1726
01:32:18,320 --> 01:32:20,240
Speaker 1: want to the wolves there to take down the number

1727
01:32:20,240 --> 01:32:23,599
Speaker 1: of deer, so they pay outlish insurance. I thought, I've

1728
01:32:23,640 --> 01:32:25,720
Speaker 1: never heard that one before. That was a new and

1729
01:32:25,800 --> 01:32:30,800
Speaker 1: unique story for Yeah, please, I heard that it was

1730
01:32:30,840 --> 01:32:34,000
Speaker 1: the Clintons. The Clintons, and let me tell you why,

1731
01:32:34,040 --> 01:32:39,880
Speaker 1: Because if the Clintons could bring in wolves. The wolves

1732
01:32:40,200 --> 01:32:44,160
Speaker 1: would kill all the game, and then people in the

1733
01:32:44,280 --> 01:32:47,479
Speaker 1: Rockies wouldn't own guns anymore because there's nothing to hunt

1734
01:32:47,880 --> 01:32:50,679
Speaker 1: and there would be less resistance when it came time

1735
01:32:50,880 --> 01:32:55,280
Speaker 1: to seize everyone's gun. That's why we have wolves. Wow,

1736
01:32:55,360 --> 01:32:57,439
Speaker 1: you did one up me on that one. I mustn't

1737
01:32:57,479 --> 01:33:03,160
Speaker 1: anyone that's crazy anyway. Okay, well, what did we miss?

1738
01:33:03,200 --> 01:33:09,000
Speaker 1: I've got a couple. Just follow black and white. I hope,

1739
01:33:11,120 --> 01:33:13,280
Speaker 1: I don't know. I don't like them. They're challenging to

1740
01:33:13,280 --> 01:33:19,080
Speaker 1: answer because it's not black and white. Do wolves kill

1741
01:33:19,800 --> 01:33:23,719
Speaker 1: more bulls versus cows? Do they care one way or another?

1742
01:33:23,880 --> 01:33:26,400
Speaker 1: Do they tend to pray? There's a lot of literature

1743
01:33:26,400 --> 01:33:28,920
Speaker 1: out there, and then it depends on species and geographic area.

1744
01:33:29,000 --> 01:33:31,519
Speaker 1: But wolves will take whatever is most vulnerable. And what

1745
01:33:31,560 --> 01:33:33,320
Speaker 1: I can tell you is that is the young of

1746
01:33:33,360 --> 01:33:35,519
Speaker 1: the year. I don't care if it's an alcor fun

1747
01:33:35,800 --> 01:33:40,760
Speaker 1: wolves go into winter. Yeah, they could be a fawner calf.

1748
01:33:40,840 --> 01:33:43,240
Speaker 1: I mean, when you're going into winter, they're the smallest,

1749
01:33:43,280 --> 01:33:45,960
Speaker 1: they're the weakest, they're the slowest. Most of the animals

1750
01:33:45,960 --> 01:33:48,800
Speaker 1: you take are young of the year. Then beyond that,

1751
01:33:48,880 --> 01:33:51,479
Speaker 1: a big fat cow is not very vulnerable if she's

1752
01:33:51,560 --> 01:33:54,920
Speaker 1: middle aged or you know, a good age, but it's

1753
01:33:54,960 --> 01:33:57,960
Speaker 1: snow conditions. They're right. So what I say when people

1754
01:33:58,280 --> 01:34:00,639
Speaker 1: people say they take the oldest sick in the week,

1755
01:34:00,720 --> 01:34:03,479
Speaker 1: I said, you know, that's kind of the outcome, but

1756
01:34:03,560 --> 01:34:06,799
Speaker 1: that's not really the selection factor. They take what's vulnerable.

1757
01:34:07,080 --> 01:34:09,960
Speaker 1: So you could take a seven year old prime fat

1758
01:34:10,200 --> 01:34:13,160
Speaker 1: cow elk and you put her in this crusty four

1759
01:34:13,160 --> 01:34:16,360
Speaker 1: ft deep snow out there, and she's breaking through and

1760
01:34:16,400 --> 01:34:19,800
Speaker 1: the wolves aren't. There's nothing wrong with that elk. She's

1761
01:34:19,840 --> 01:34:23,680
Speaker 1: just vulnerable, and most situations she's not. She's the strongest one,

1762
01:34:23,720 --> 01:34:25,280
Speaker 1: and she might be in the major cow. You know,

1763
01:34:25,800 --> 01:34:28,800
Speaker 1: So it's vulnerable, and it's generally the old the sick

1764
01:34:28,840 --> 01:34:30,639
Speaker 1: in the week. But they're not doubt they're still electing

1765
01:34:30,680 --> 01:34:34,400
Speaker 1: for him, liking for what they can catch. A very big,

1766
01:34:34,479 --> 01:34:39,280
Speaker 1: huge buck or bull elk that goes into the rot

1767
01:34:39,360 --> 01:34:42,240
Speaker 1: and ruts his brains out, they can lose like of

1768
01:34:42,240 --> 01:34:44,840
Speaker 1: the body weight. They go into the winter in really

1769
01:34:45,000 --> 01:34:47,880
Speaker 1: terrible shape. They don't eat while they're breeding. In a

1770
01:34:47,920 --> 01:34:50,080
Speaker 1: couple of months, they hardly anything. They're skinny as are all.

1771
01:34:50,439 --> 01:34:52,960
Speaker 1: They're punched up. They might have puncture skewers that are

1772
01:34:52,960 --> 01:34:56,519
Speaker 1: bleeding from the other bulls. They're pretty vulnerable. You know.

1773
01:34:56,600 --> 01:34:59,400
Speaker 1: We think those are great trophies because they've got bigger acts.

1774
01:34:59,520 --> 01:35:02,120
Speaker 1: But reality is it's maybe it's even at the end

1775
01:35:02,120 --> 01:35:05,320
Speaker 1: of its life. It's done a lot of breeding. But

1776
01:35:05,400 --> 01:35:08,639
Speaker 1: it makes people really angry when they see wolves kill

1777
01:35:08,680 --> 01:35:12,639
Speaker 1: a big bull out. But they aren't selecting for the bulls.

1778
01:35:12,640 --> 01:35:15,200
Speaker 1: It's just that they're vulnerable. What I find really interesting

1779
01:35:15,320 --> 01:35:18,400
Speaker 1: is they helps still have their antlers now too. You

1780
01:35:18,439 --> 01:35:20,639
Speaker 1: will rarely ever, I'm trying to think of I've ever

1781
01:35:20,680 --> 01:35:24,720
Speaker 1: seen in videos. Bob Landis has taken the most amazing footage.

1782
01:35:25,560 --> 01:35:30,240
Speaker 1: Rarely ever, if ever see a bull elk with antlers

1783
01:35:30,479 --> 01:35:34,840
Speaker 1: swing as antlers as a defense tool. They are strictly ornaments.

1784
01:35:35,560 --> 01:35:37,080
Speaker 1: So why do they hang on to all that weight

1785
01:35:37,160 --> 01:35:39,600
Speaker 1: all winter because they're done breeding in October? Why do

1786
01:35:39,680 --> 01:35:42,280
Speaker 1: they pack forty or fifty pounds on their head that

1787
01:35:42,360 --> 01:35:44,599
Speaker 1: slows them down if they aren't able to use them

1788
01:35:44,680 --> 01:35:48,160
Speaker 1: for either sexual selection because breeding is done, or predatory defense,

1789
01:35:48,200 --> 01:35:51,400
Speaker 1: why do they do that? I can your hunters, I'm

1790
01:35:51,400 --> 01:35:53,760
Speaker 1: just asking, I mean amusing ecologists like trying to think

1791
01:35:53,760 --> 01:35:56,439
Speaker 1: about this. Why would they do that? Anyway? I'm just

1792
01:35:56,439 --> 01:35:58,679
Speaker 1: saying the stuff out there. We don't know. Maybe somebody's

1793
01:35:58,680 --> 01:36:01,000
Speaker 1: answered that question. I haven't read on it. I read

1794
01:36:01,080 --> 01:36:04,720
Speaker 1: not long ago that a dear biologist was saying that

1795
01:36:04,760 --> 01:36:08,240
Speaker 1: if you could, if you can take deer in and

1796
01:36:08,320 --> 01:36:13,120
Speaker 1: manipulate him through photo periods, you could create to create

1797
01:36:13,400 --> 01:36:16,640
Speaker 1: no deer that would throw two racks a year. Huh,

1798
01:36:16,680 --> 01:36:18,280
Speaker 1: why would you want to do that? You wouldn't He

1799
01:36:18,360 --> 01:36:20,439
Speaker 1: just we're just talking about when you take a deer

1800
01:36:20,439 --> 01:36:22,080
Speaker 1: from let's say you take a deer from the northern

1801
01:36:22,080 --> 01:36:25,479
Speaker 1: hemisphere or taken out from deer. Let's take a deer

1802
01:36:25,520 --> 01:36:29,280
Speaker 1: from the northern hemisphere and put it in the southern hemisphere.

1803
01:36:29,720 --> 01:36:32,920
Speaker 1: How long does it take that deer to adjust to

1804
01:36:33,040 --> 01:36:37,360
Speaker 1: start right, to want to flip flop when it drops

1805
01:36:37,400 --> 01:36:40,759
Speaker 1: and girls antlers. And he's saying they do it very quickly.

1806
01:36:41,320 --> 01:36:44,240
Speaker 1: And he said, not only that, UM, not on if

1807
01:36:44,280 --> 01:36:46,160
Speaker 1: this has been done, or he suggested that he thinks

1808
01:36:46,160 --> 01:36:48,120
Speaker 1: it could be done. He said, not only that, I

1809
01:36:48,120 --> 01:36:50,600
Speaker 1: think you could put a deer in a an artificial

1810
01:36:50,760 --> 01:36:53,960
Speaker 1: situation and do photo periods and you could make it.

1811
01:36:54,120 --> 01:36:57,320
Speaker 1: You could trigger it to produce two racks a year.

1812
01:36:59,160 --> 01:37:01,000
Speaker 1: Mother nature doesn't do that because it would be really

1813
01:37:01,000 --> 01:37:03,400
Speaker 1: hard on the animal. Yeah, but he but you could

1814
01:37:03,560 --> 01:37:08,000
Speaker 1: point being this point being that it's it's linked to

1815
01:37:08,040 --> 01:37:12,400
Speaker 1: photo period, not not art, not the Gregorian calendar, whatever, right,

1816
01:37:12,479 --> 01:37:15,479
Speaker 1: whatever we live under here. Uh what you put a

1817
01:37:15,479 --> 01:37:17,679
Speaker 1: lot of miles on in the winter in the snow?

1818
01:37:17,720 --> 01:37:21,080
Speaker 1: What do you wear for boots? Uh? These days, I'm

1819
01:37:21,120 --> 01:37:22,479
Speaker 1: not doing it so much too Moore, but I did

1820
01:37:22,479 --> 01:37:26,920
Speaker 1: for most of my other research work. I were I've

1821
01:37:26,920 --> 01:37:30,960
Speaker 1: had snay boots, I've had sorrows. I'm mostly yeah, mostly

1822
01:37:31,000 --> 01:37:33,120
Speaker 1: just ski boots. I mean when I'm talking was, I'm

1823
01:37:33,160 --> 01:37:37,040
Speaker 1: mostly in skis, big heavy, back country three pin boots.

1824
01:37:37,880 --> 01:37:39,160
Speaker 1: I don't like I said, I don't and that's not

1825
01:37:39,200 --> 01:37:40,479
Speaker 1: part of what I do. Know, it's not part of

1826
01:37:40,479 --> 01:37:42,360
Speaker 1: my job to do that winter work anymore. Which is

1827
01:37:42,560 --> 01:37:44,000
Speaker 1: back and you were hard at it. You did most

1828
01:37:44,040 --> 01:37:47,759
Speaker 1: in ski boots. Yeah, yeah, hard hard plastic ski boots, leather,

1829
01:37:48,000 --> 01:37:52,560
Speaker 1: old marrows and uh yeah solos or oslos, depending on

1830
01:37:52,560 --> 01:37:54,800
Speaker 1: how you pronounce it. I got a pair of their

1831
01:37:54,840 --> 01:37:59,599
Speaker 1: sneakers on right now. Um got that question for you

1832
01:37:59,720 --> 01:38:02,240
Speaker 1: and I and other question for you. Let's say you're

1833
01:38:02,360 --> 01:38:06,160
Speaker 1: Emperor of the world. Okay, you control the world. Empress

1834
01:38:06,200 --> 01:38:08,439
Speaker 1: of the world. Sorry, you didn't want to be, but

1835
01:38:08,479 --> 01:38:10,639
Speaker 1: you are. Now you have to make all of the

1836
01:38:10,720 --> 01:38:18,479
Speaker 1: humanity's decisions. Um. Do you do you feel that would

1837
01:38:18,520 --> 01:38:26,120
Speaker 1: you allow wolf hunting and trapping to continue? Um? In

1838
01:38:26,280 --> 01:38:31,439
Speaker 1: areas that have sustainable populations of wolves? Empress of the

1839
01:38:31,439 --> 01:38:35,200
Speaker 1: world of the world. Yeah, so we're outside of profession

1840
01:38:35,280 --> 01:38:37,360
Speaker 1: right now, and now we're talking about the King of

1841
01:38:37,400 --> 01:38:40,240
Speaker 1: the world, Queen of the world. I don't live outside

1842
01:38:40,280 --> 01:38:42,640
Speaker 1: of my profession. Come on, you do too, There's no

1843
01:38:42,680 --> 01:38:44,840
Speaker 1: way you don't. I have the same problem my brothers,

1844
01:38:44,880 --> 01:38:46,640
Speaker 1: who are both ecologists. I'll be like, what do you

1845
01:38:46,680 --> 01:38:51,760
Speaker 1: hope happens? They don't like it. They don't like it.

1846
01:38:51,800 --> 01:38:55,439
Speaker 1: But come on, your Empress of the world. And someone says, oh,

1847
01:38:55,520 --> 01:38:57,439
Speaker 1: first thing, first quick issue we have to take care

1848
01:38:57,439 --> 01:39:00,000
Speaker 1: of is do we let the hunting and trapping seasons

1849
01:39:00,000 --> 01:39:02,040
Speaker 1: continue for wolves? And you have to make a quick decision.

1850
01:39:02,760 --> 01:39:04,960
Speaker 1: You have decide here. You are emers of the world.

1851
01:39:05,360 --> 01:39:07,760
Speaker 1: You're not gonna let the people down by lack through

1852
01:39:07,840 --> 01:39:20,240
Speaker 1: lack of leadership. Don't come on, really, really, wolves wolves

1853
01:39:20,280 --> 01:39:22,920
Speaker 1: can live anywhere that we tolerate them. In order tolerate them,

1854
01:39:22,960 --> 01:39:24,599
Speaker 1: we have to have some kind of a management plan.

1855
01:39:25,479 --> 01:39:28,280
Speaker 1: In a perfect world, wolves would never kill a coward

1856
01:39:28,280 --> 01:39:30,760
Speaker 1: of sheep and wolf, and unulate populations will never go

1857
01:39:30,840 --> 01:39:33,559
Speaker 1: up and down. There wouldn't be any controversies, right because

1858
01:39:33,560 --> 01:39:35,800
Speaker 1: that was a perfect world. Then he would need to

1859
01:39:35,840 --> 01:39:38,640
Speaker 1: remove them. But that's never gonna If there's not a

1860
01:39:38,640 --> 01:39:41,880
Speaker 1: perfect world, undulated population to go up and down, people

1861
01:39:41,960 --> 01:39:46,679
Speaker 1: get livestock taking their horrible and cheap that can happen.

1862
01:39:47,080 --> 01:39:51,600
Speaker 1: So in order for social tolerance to create possibilities for

1863
01:39:51,640 --> 01:39:53,720
Speaker 1: wolves to be you have to do that stuff. Let

1864
01:39:53,720 --> 01:39:55,439
Speaker 1: me hate with another personal one. Well, I just want

1865
01:39:55,439 --> 01:39:57,760
Speaker 1: to add that the perfect world is just perception. It

1866
01:39:57,880 --> 01:40:00,840
Speaker 1: might we might be living in the perfect world right now,

1867
01:40:01,560 --> 01:40:05,040
Speaker 1: but I do I'd say not. Look what's going on

1868
01:40:05,080 --> 01:40:08,639
Speaker 1: across our country, in the world, in the world. But

1869
01:40:08,920 --> 01:40:12,760
Speaker 1: it's been crazier in the past too. Oh yeah, we

1870
01:40:12,800 --> 01:40:16,960
Speaker 1: just have this thing called the Civil War. Yeah. Um,

1871
01:40:17,280 --> 01:40:20,679
Speaker 1: but kind of on that note, you hear a lot

1872
01:40:20,760 --> 01:40:24,040
Speaker 1: from the people that think that they could just survive,

1873
01:40:25,760 --> 01:40:27,080
Speaker 1: But I don't know if those are people that think

1874
01:40:27,080 --> 01:40:29,160
Speaker 1: they can just survive on nuts and berries. But anyways,

1875
01:40:29,600 --> 01:40:33,000
Speaker 1: that when some of these packs have a member of

1876
01:40:33,000 --> 01:40:34,960
Speaker 1: their pack that's killed by a hunter that you know,

1877
01:40:35,000 --> 01:40:39,760
Speaker 1: you have a dog wolf, it leaves the park and

1878
01:40:40,000 --> 01:40:42,519
Speaker 1: get shot and then it really disrupts the pack and

1879
01:40:42,560 --> 01:40:44,040
Speaker 1: it's like going to be the end of the pack.

1880
01:40:44,600 --> 01:40:49,080
Speaker 1: How true or false is that? Like have you seen

1881
01:40:49,439 --> 01:40:51,640
Speaker 1: have you been able to document and research that and

1882
01:40:52,000 --> 01:40:55,559
Speaker 1: see like what it does or doesn't do. You'd have

1883
01:40:55,600 --> 01:40:59,400
Speaker 1: to ask Yellowstone people specifically, because that's the concern down there.

1884
01:40:59,439 --> 01:41:03,000
Speaker 1: I know, when wolves or whatever, when they leave the

1885
01:41:03,040 --> 01:41:06,719
Speaker 1: pack and they get killed at Cook City or around

1886
01:41:07,040 --> 01:41:11,960
Speaker 1: Comin or Basin, it's it's very painful for some people,

1887
01:41:12,479 --> 01:41:16,719
Speaker 1: very painful. They common glued. That's tragedy beyond belief. They're

1888
01:41:16,800 --> 01:41:22,120
Speaker 1: very attached to these animals. As an ecologists looking at

1889
01:41:22,160 --> 01:41:25,559
Speaker 1: the population level, it's a loss of an animal. And

1890
01:41:25,560 --> 01:41:27,920
Speaker 1: as a breeder, it's it's more of an impact on

1891
01:41:27,920 --> 01:41:30,519
Speaker 1: the pack. The pack might split up, the pack might

1892
01:41:30,760 --> 01:41:34,160
Speaker 1: get a new breeder, the pack might fade away, they

1893
01:41:34,240 --> 01:41:38,519
Speaker 1: might have two breeders the following year. They there's this

1894
01:41:38,640 --> 01:41:40,640
Speaker 1: dynamic that goes on all the time, and death is

1895
01:41:40,720 --> 01:41:43,720
Speaker 1: part of it. She said, We as social people put

1896
01:41:43,800 --> 01:41:48,559
Speaker 1: judgments on the animals taken. And I know early in

1897
01:41:48,560 --> 01:41:51,240
Speaker 1: my career when there was only three packs of wolves

1898
01:41:51,240 --> 01:41:54,960
Speaker 1: in Montana, I knew those animals, not by name or anything,

1899
01:41:55,000 --> 01:41:58,479
Speaker 1: but we followed them enough in the snow on the trail.

1900
01:41:58,560 --> 01:42:00,280
Speaker 1: I flew once a week. It was very sense of

1901
01:42:00,360 --> 01:42:02,840
Speaker 1: kind of like here, except you didn't get to see them.

1902
01:42:02,880 --> 01:42:06,240
Speaker 1: And it was hardship early on because every one of

1903
01:42:06,280 --> 01:42:09,840
Speaker 1: those animals was critical to them coming back at all.

1904
01:42:10,040 --> 01:42:13,960
Speaker 1: So if you lost, if you had twenty animals and

1905
01:42:14,360 --> 01:42:17,439
Speaker 1: four were killed or something new, you kind of felt

1906
01:42:17,479 --> 01:42:20,160
Speaker 1: it and you saw the adjustment. But it's like, oh,

1907
01:42:20,400 --> 01:42:23,240
Speaker 1: well there's an adjustment, and that wolf's gone, and g

1908
01:42:23,360 --> 01:42:25,400
Speaker 1: where did this one come from? And none? Next year

1909
01:42:25,439 --> 01:42:28,760
Speaker 1: they got Pops. That one is gone. They move on,

1910
01:42:28,920 --> 01:42:32,679
Speaker 1: they don't think about it. They're wolves, and we put

1911
01:42:32,680 --> 01:42:35,439
Speaker 1: those values on it. And it is hard for those people.

1912
01:42:35,479 --> 01:42:37,920
Speaker 1: I know, they're friends and them are friends of mine

1913
01:42:37,920 --> 01:42:44,440
Speaker 1: from Yellowstone, and it's difficult. And that system has the bonus.

1914
01:42:44,960 --> 01:42:47,759
Speaker 1: I tell these people, my friends, you guys have a bonus.

1915
01:42:47,840 --> 01:42:50,600
Speaker 1: You live in a research bubble here. It's amazing. You

1916
01:42:50,640 --> 01:42:53,800
Speaker 1: can see these animals. You sit on the I just

1917
01:42:53,840 --> 01:42:55,040
Speaker 1: came from there. You sit on the side of the

1918
01:42:55,080 --> 01:42:58,800
Speaker 1: road with your service, then your apple pie or something,

1919
01:42:58,840 --> 01:43:01,519
Speaker 1: and you can watch these of That is not the

1920
01:43:01,560 --> 01:43:03,880
Speaker 1: real world wolves live in. They live where I live,

1921
01:43:03,960 --> 01:43:06,080
Speaker 1: and they're shot and hunting, trapping around over by cars

1922
01:43:06,080 --> 01:43:08,800
Speaker 1: and trains and whatever. That's the world wolves have to

1923
01:43:08,840 --> 01:43:11,360
Speaker 1: live in. And when one gets killed, it is not

1924
01:43:11,479 --> 01:43:16,040
Speaker 1: a tragedy. We don't, you know, it's just different. Yellowstone

1925
01:43:16,080 --> 01:43:20,880
Speaker 1: does like it does so much good. I know it

1926
01:43:21,320 --> 01:43:24,720
Speaker 1: does harm well, I would venture to say that. I mean,

1927
01:43:24,840 --> 01:43:26,760
Speaker 1: like I said, when I first was out there, I

1928
01:43:26,800 --> 01:43:29,000
Speaker 1: was against their introduction for all those reasons. We talked

1929
01:43:29,040 --> 01:43:32,040
Speaker 1: about most of the social fabric and the natural selection

1930
01:43:32,040 --> 01:43:34,840
Speaker 1: of wolves coming down blah blah blah. But now that

1931
01:43:34,880 --> 01:43:36,639
Speaker 1: they're there, I go there a couple of times a year.

1932
01:43:36,680 --> 01:43:41,920
Speaker 1: I so enjoy seeing them because they're they're not they're

1933
01:43:41,960 --> 01:43:45,320
Speaker 1: not remove. If they're they're pretty visible, and it's a

1934
01:43:45,360 --> 01:43:49,880
Speaker 1: different energy down there. Everybody goes watches those wolves, is

1935
01:43:50,000 --> 01:43:52,080
Speaker 1: very in love with seeing them and the experience, and

1936
01:43:52,120 --> 01:43:55,240
Speaker 1: it opens a lot of people's eyes. But that is

1937
01:43:55,320 --> 01:43:58,600
Speaker 1: not where the wolves live in of the world. But

1938
01:43:58,680 --> 01:44:03,120
Speaker 1: they lay the problem is is it? Yeah, it's like

1939
01:44:03,200 --> 01:44:06,760
Speaker 1: ecological has done so much good for recovering species. It's

1940
01:44:06,760 --> 01:44:11,640
Speaker 1: not a lot of good um. But the psychology of

1941
01:44:11,680 --> 01:44:15,680
Speaker 1: the place and its advocates is that they they they

1942
01:44:16,000 --> 01:44:20,960
Speaker 1: lay claim and take ownership of anything that touches it,

1943
01:44:21,920 --> 01:44:25,160
Speaker 1: so that a herd of elk, say that spend the

1944
01:44:25,200 --> 01:44:28,960
Speaker 1: bulk of the year not there, become the Yellowstone elk

1945
01:44:29,840 --> 01:44:34,960
Speaker 1: of grizzly that passes through becomes a Yellowstone grizzly. Um.

1946
01:44:35,120 --> 01:44:38,080
Speaker 1: And if something occurs outside of the park within some

1947
01:44:38,200 --> 01:44:43,759
Speaker 1: number of miles, it's a travesty because it was only

1948
01:44:43,800 --> 01:44:47,040
Speaker 1: a mile, only a five miles out of the park,

1949
01:44:47,680 --> 01:44:51,600
Speaker 1: as though it's footprint is inadequate, and it needs to

1950
01:44:51,640 --> 01:44:56,519
Speaker 1: sort of extend this psychological energy that reaches out like

1951
01:44:56,560 --> 01:44:59,960
Speaker 1: the tenles tentacles of an octopus to grab in anything

1952
01:45:00,080 --> 01:45:02,880
Speaker 1: ing around it. And I think that out of that

1953
01:45:03,040 --> 01:45:09,200
Speaker 1: that mentality drives a lot of creates a lot of

1954
01:45:09,920 --> 01:45:14,479
Speaker 1: like contentiousness and people who are competing over management of things.

1955
01:45:14,600 --> 01:45:16,439
Speaker 1: So when I say it causes harm, I think in

1956
01:45:16,520 --> 01:45:22,160
Speaker 1: that way where people become that The wildlife politics in America,

1957
01:45:22,280 --> 01:45:26,320
Speaker 1: like wildlife in America, is very complicated and there are

1958
01:45:26,360 --> 01:45:28,519
Speaker 1: a lot of factors at play, and a lot of

1959
01:45:28,560 --> 01:45:30,680
Speaker 1: people who need to be heard. And I think that

1960
01:45:30,720 --> 01:45:33,840
Speaker 1: when people are introduced to American wildlife through the lens

1961
01:45:33,880 --> 01:45:39,160
Speaker 1: of Yellowstone, they get a very distorted perception of what

1962
01:45:39,360 --> 01:45:43,400
Speaker 1: is actually what actually happens in the way people's lives

1963
01:45:43,439 --> 01:45:47,439
Speaker 1: are impacted and the different concerns going on. And I

1964
01:45:47,479 --> 01:45:51,760
Speaker 1: think that there's certain agencies like National Geographic is a

1965
01:45:51,760 --> 01:45:54,040
Speaker 1: big driver of this, The Smithsonian is a big driver

1966
01:45:54,120 --> 01:45:56,439
Speaker 1: of this. The people that push this thing that that

1967
01:45:57,439 --> 01:46:01,559
Speaker 1: wildlife just lives in this little protected place. Um, it's

1968
01:46:01,680 --> 01:46:06,160
Speaker 1: only there. It's surrounded by horrible people who want to

1969
01:46:06,200 --> 01:46:09,320
Speaker 1: do horrible things, and it's just by the grace of

1970
01:46:09,400 --> 01:46:12,840
Speaker 1: God that we have this little gem in which in

1971
01:46:12,840 --> 01:46:17,439
Speaker 1: which wildlife can exist. And they push that narrative, and

1972
01:46:17,479 --> 01:46:20,400
Speaker 1: it's it's frustrating. It's like, it's difficult to watch that happen.

1973
01:46:20,439 --> 01:46:22,479
Speaker 1: It is difficult. And when people got to realize, say

1974
01:46:22,520 --> 01:46:26,599
Speaker 1: there's say there's eighty wolves now, and this spring there

1975
01:46:26,600 --> 01:46:30,479
Speaker 1: will be several litters of five to six born who

1976
01:46:30,479 --> 01:46:32,320
Speaker 1: knows how many letters ten and there will be that

1977
01:46:32,360 --> 01:46:34,960
Speaker 1: many more wolves. The population will at least double or

1978
01:46:35,000 --> 01:46:39,040
Speaker 1: trouble based on reproductive and every year. This happens every year,

1979
01:46:39,120 --> 01:46:41,080
Speaker 1: and then by this time next year it'll be back

1980
01:46:41,120 --> 01:46:45,120
Speaker 1: down to every year. So a certain number of wolves,

1981
01:46:45,160 --> 01:46:47,479
Speaker 1: and they don't have percentage, but twice as many as

1982
01:46:47,479 --> 01:46:52,439
Speaker 1: there will disperse, get killed, die of disease, drowned, get

1983
01:46:52,520 --> 01:46:55,040
Speaker 1: killed by an get killed by the wolves. It happens

1984
01:46:55,080 --> 01:46:57,200
Speaker 1: all the time. But when it's a wolf that is

1985
01:46:57,280 --> 01:46:59,479
Speaker 1: seen often and as a number in a radio color

1986
01:46:59,560 --> 01:47:02,240
Speaker 1: and then it's killed by human, that is a beaut

1987
01:47:02,320 --> 01:47:04,639
Speaker 1: as a very large tragedy. And I wish people would

1988
01:47:05,000 --> 01:47:08,080
Speaker 1: I wish people would be more concerned about connectivity and

1989
01:47:08,120 --> 01:47:10,240
Speaker 1: linkage is out on the landscape. I wish people would

1990
01:47:10,280 --> 01:47:12,880
Speaker 1: be more worried instead of Scarface being killed illegal, the

1991
01:47:12,880 --> 01:47:15,960
Speaker 1: big grizzly bear that was killed supposedly illegally, and it

1992
01:47:16,080 --> 01:47:18,160
Speaker 1: was seen for twenty five years and yellow So I

1993
01:47:18,200 --> 01:47:21,080
Speaker 1: saw him and he's very identifiable. People identified with this

1994
01:47:21,160 --> 01:47:23,720
Speaker 1: bear for a long time. And he goes outside of

1995
01:47:23,720 --> 01:47:26,000
Speaker 1: the park and I believe he was illegally killed or

1996
01:47:26,160 --> 01:47:29,280
Speaker 1: killed anyway, but it was outside the park. If people

1997
01:47:29,479 --> 01:47:32,680
Speaker 1: put all the energy and money into thinking about well,

1998
01:47:32,800 --> 01:47:36,920
Speaker 1: let's work on the connectivity linkage between yellow Stone and Montana.

1999
01:47:37,000 --> 01:47:41,000
Speaker 1: Those landscapes between McDonald Pass and you know, the Gallatin Valley,

2000
01:47:41,520 --> 01:47:45,680
Speaker 1: so that bears are are more free to maintain viability,

2001
01:47:45,760 --> 01:47:49,840
Speaker 1: so that it doesn't become this still pretty isolated. That's

2002
01:47:49,840 --> 01:47:53,719
Speaker 1: a bigger concern than the scarface being chop, much bigger

2003
01:47:53,760 --> 01:47:56,760
Speaker 1: in my mind, especially putting all this emotional energy into

2004
01:47:56,840 --> 01:47:59,400
Speaker 1: these single wolves, as you just said, for them to

2005
01:47:59,479 --> 01:48:01,519
Speaker 1: live to be I was a big deal. To big deal.

2006
01:48:01,600 --> 01:48:03,840
Speaker 1: And I I mean, I I love seting and I'm

2007
01:48:03,840 --> 01:48:06,080
Speaker 1: taking in and I love listening stories about who we

2008
01:48:06,120 --> 01:48:09,400
Speaker 1: got who, and I have I have ultimate respect for

2009
01:48:09,439 --> 01:48:11,920
Speaker 1: these people out there every day at like five in

2010
01:48:11,960 --> 01:48:13,640
Speaker 1: the morning. They're out there all day and they know

2011
01:48:13,720 --> 01:48:15,840
Speaker 1: these animals and they dedicate their life to it. And

2012
01:48:15,920 --> 01:48:18,160
Speaker 1: I you and I I mean benefit. I can pull

2013
01:48:18,280 --> 01:48:20,200
Speaker 1: up in my car and get out and ask what's

2014
01:48:20,200 --> 01:48:23,479
Speaker 1: going on. They tell me. I'm very appreciative, But I

2015
01:48:23,479 --> 01:48:27,040
Speaker 1: don't have that attachment to those animals, to the singles.

2016
01:48:27,280 --> 01:48:30,160
Speaker 1: You're interesting in population not down there, But I can

2017
01:48:30,240 --> 01:48:33,639
Speaker 1: understand the passion and they they're very passionate about It's

2018
01:48:33,680 --> 01:48:35,880
Speaker 1: like maybe me and my bird dog. I mean, I'm

2019
01:48:35,960 --> 01:48:38,400
Speaker 1: very passionate about bird hunting and training dogs and when

2020
01:48:38,439 --> 01:48:41,320
Speaker 1: dogs die, it's a tragedy. But the wolves are not

2021
01:48:41,479 --> 01:48:43,800
Speaker 1: my dogs. I don't know how to answer that. It's

2022
01:48:43,840 --> 01:48:48,440
Speaker 1: just challenging. Is there a time in like scientists education,

2023
01:48:48,760 --> 01:48:52,799
Speaker 1: where someone sits you down and says you you don't

2024
01:48:52,960 --> 01:48:56,200
Speaker 1: call animals by names. We do numbers and this is why?

2025
01:48:56,439 --> 01:48:58,720
Speaker 1: Is that like a very strict point thing or does

2026
01:48:58,800 --> 01:49:01,439
Speaker 1: that just naturally come along. That's a really good question, honest,

2027
01:49:01,479 --> 01:49:04,920
Speaker 1: because when we started the wolves, you know, in search study,

2028
01:49:04,960 --> 01:49:08,040
Speaker 1: and the first one was Kishena, and then we had Phyllis,

2029
01:49:08,040 --> 01:49:09,880
Speaker 1: and we had these wolves because there were so few,

2030
01:49:10,120 --> 01:49:11,880
Speaker 1: and yes, we were going down the same path and

2031
01:49:11,920 --> 01:49:14,320
Speaker 1: we saw him a lot. And the park services you

2032
01:49:14,360 --> 01:49:16,840
Speaker 1: can't name those wolves, and the fishing life services you

2033
01:49:16,840 --> 01:49:18,960
Speaker 1: can't name them because what happens when Phillis goes and

2034
01:49:19,040 --> 01:49:22,120
Speaker 1: kills a column. We've gotta take Phillis out. Okay. Every

2035
01:49:22,120 --> 01:49:25,120
Speaker 1: wolf had a number anyway, Some of mad names early

2036
01:49:25,160 --> 01:49:28,760
Speaker 1: on semed numbers. And people would be funny because you'd

2037
01:49:28,760 --> 01:49:31,040
Speaker 1: be talking to something the park service about wolf eight five,

2038
01:49:31,120 --> 01:49:33,120
Speaker 1: fifty and they say who is that, Well, that's Phillis, okay,

2039
01:49:33,240 --> 01:49:37,040
Speaker 1: or fifty three? Who's that? That's mohabb okay, but they

2040
01:49:37,479 --> 01:49:39,839
Speaker 1: knew the name, so it was kind of a trade

2041
01:49:39,880 --> 01:49:43,320
Speaker 1: we played. But and I know within fish Wife and

2042
01:49:43,360 --> 01:49:46,080
Speaker 1: parks they don't want us to name wolves, but all

2043
01:49:46,120 --> 01:49:49,320
Speaker 1: of the grizzly bears that they tag are everyone is named,

2044
01:49:49,400 --> 01:49:53,840
Speaker 1: every one of them. What's the difference? And I don't

2045
01:49:53,880 --> 01:49:57,679
Speaker 1: feel like if if I knew you boy so security number,

2046
01:49:57,760 --> 01:49:59,280
Speaker 1: you can give that to me later I'll follow up.

2047
01:49:59,320 --> 01:50:01,639
Speaker 1: But you are you so security number? I wouldn't when

2048
01:50:01,720 --> 01:50:04,920
Speaker 1: feeling different if you were like the fourteen oh seven

2049
01:50:05,560 --> 01:50:09,240
Speaker 1: versus Jannice, I mean you could and the other thing

2050
01:50:09,280 --> 01:50:11,439
Speaker 1: I mean, I'm turning to a scientist. Our papers are

2051
01:50:11,520 --> 01:50:16,120
Speaker 1: very technical and factual and models and statistics and all that.

2052
01:50:16,240 --> 01:50:18,519
Speaker 1: And I think one of the things that we need

2053
01:50:18,560 --> 01:50:21,639
Speaker 1: to do better is is scientists biologists, and I don't

2054
01:50:21,640 --> 01:50:23,280
Speaker 1: I'd love to hear the input, but I think that

2055
01:50:23,320 --> 01:50:26,639
Speaker 1: we don't do a very good job in reaching out

2056
01:50:26,760 --> 01:50:31,000
Speaker 1: to the general public who has concerns and thinks about

2057
01:50:31,040 --> 01:50:33,760
Speaker 1: being outside and enjoys all aspects of wild life, but

2058
01:50:33,840 --> 01:50:37,160
Speaker 1: maybe it doesn't really know how to predators and prey relay.

2059
01:50:37,200 --> 01:50:39,600
Speaker 1: When do they kill or not kill everything? And we

2060
01:50:39,600 --> 01:50:42,160
Speaker 1: don't put it out in a format that's very user friendly.

2061
01:50:43,120 --> 01:50:47,799
Speaker 1: People just see these papers with his Latin and figures

2062
01:50:47,840 --> 01:50:51,360
Speaker 1: and numbers, and it just gone. I think it's there

2063
01:50:51,400 --> 01:50:53,680
Speaker 1: for people that want it. It's hard. I mean, I

2064
01:50:53,720 --> 01:50:56,200
Speaker 1: go do a lot of public presentations and different groups,

2065
01:50:56,600 --> 01:50:58,880
Speaker 1: different people grasp different things. But I find a lot

2066
01:50:58,880 --> 01:51:01,680
Speaker 1: of groups as soon as you start talking data, this

2067
01:51:01,840 --> 01:51:03,920
Speaker 1: light goes out and I have to ask you, because

2068
01:51:04,280 --> 01:51:07,040
Speaker 1: how do how can I be a better communicator to

2069
01:51:07,080 --> 01:51:10,360
Speaker 1: the public about these very important issues, Like when we

2070
01:51:10,600 --> 01:51:12,599
Speaker 1: do some of these meetings and people say, oh, that's

2071
01:51:12,640 --> 01:51:15,080
Speaker 1: not right, those numbers are wrong, you know you blah

2072
01:51:15,120 --> 01:51:19,040
Speaker 1: blah blah. Well they are what we have. And but

2073
01:51:19,040 --> 01:51:21,439
Speaker 1: but I don't think that you're asking something that can't

2074
01:51:21,479 --> 01:51:24,680
Speaker 1: be answered, because I think that the people have. But

2075
01:51:24,840 --> 01:51:29,200
Speaker 1: that same problem exists everything, with every subject. It exists

2076
01:51:29,200 --> 01:51:31,240
Speaker 1: with every subject. Care if you're talking about if you're

2077
01:51:31,240 --> 01:51:34,120
Speaker 1: trying to explain social services, if you're trying to explain

2078
01:51:34,840 --> 01:51:39,960
Speaker 1: um climate, I'm trying to explain wildlife populations, trying to

2079
01:51:40,160 --> 01:51:43,120
Speaker 1: explain the mility, the budget for the military or whatever.

2080
01:51:44,200 --> 01:51:49,720
Speaker 1: You're gonna always run up against people who um cannot conceptualize,

2081
01:51:51,040 --> 01:51:53,800
Speaker 1: can't make sense of data. There's people that can't look

2082
01:51:53,800 --> 01:51:58,559
Speaker 1: at them, that that can't understand the landscape um from

2083
01:51:58,600 --> 01:52:01,320
Speaker 1: having lived on it and travel across it and occupied

2084
01:52:01,320 --> 01:52:04,520
Speaker 1: it for their entire life. Then you represent that landscape

2085
01:52:04,560 --> 01:52:07,680
Speaker 1: to them in an aerial image, or you represent that

2086
01:52:07,800 --> 01:52:12,000
Speaker 1: landscape to them as a map, and they cannot they

2087
01:52:12,000 --> 01:52:15,719
Speaker 1: can't make that jump. So I think that to say, like, how,

2088
01:52:15,800 --> 01:52:18,000
Speaker 1: because I hear this from wildlife professionals all the time

2089
01:52:18,360 --> 01:52:24,640
Speaker 1: who wring their hands about they're perceived inability to articulate

2090
01:52:24,720 --> 01:52:28,519
Speaker 1: complex ideas to the public, and they're like, well, how

2091
01:52:28,520 --> 01:52:31,120
Speaker 1: do we fix it? There's probably some things you can do,

2092
01:52:31,400 --> 01:52:33,280
Speaker 1: but I think that you would say, well, we're gonna

2093
01:52:33,280 --> 01:52:37,920
Speaker 1: have to tackle it through our public education system at

2094
01:52:37,920 --> 01:52:42,280
Speaker 1: the elementary school level, because I don't know, when you

2095
01:52:42,360 --> 01:52:49,240
Speaker 1: see someone take something that's complicated and beautiful and then

2096
01:52:49,320 --> 01:52:52,080
Speaker 1: you see attempts to like strip it down and dumb

2097
01:52:52,120 --> 01:52:56,479
Speaker 1: it down, it gets really ugly and it becomes not

2098
01:52:56,560 --> 01:52:59,880
Speaker 1: satisfying anymore, and you almost feel embarrassed for the person

2099
01:53:00,240 --> 01:53:01,960
Speaker 1: that stripped it down. I'm not gonna say what it

2100
01:53:02,000 --> 01:53:06,960
Speaker 1: was by recently read an attempt to take something counterintuitive

2101
01:53:08,040 --> 01:53:13,320
Speaker 1: um to take this like counterintuitive idea and demonstrate it

2102
01:53:13,360 --> 01:53:18,720
Speaker 1: to the public, and and and it happens to be

2103
01:53:18,760 --> 01:53:21,400
Speaker 1: a point that I desperately want to see demonstrated to

2104
01:53:21,439 --> 01:53:23,880
Speaker 1: the public. But when I saw it stripped down to

2105
01:53:23,920 --> 01:53:28,680
Speaker 1: its barest, most easily digestible form, I looked at it

2106
01:53:28,720 --> 01:53:31,559
Speaker 1: and all of the wonder and beauty was gone, and

2107
01:53:31,600 --> 01:53:36,439
Speaker 1: it was just stupid. So I don't really know that

2108
01:53:36,479 --> 01:53:41,519
Speaker 1: you're going to get there. I think that, uh, it's

2109
01:53:41,560 --> 01:53:45,880
Speaker 1: just from the ground up, trying to invite people to

2110
01:53:46,080 --> 01:53:51,640
Speaker 1: be invite people to like being surprised. My father was

2111
01:53:51,760 --> 01:54:00,160
Speaker 1: very resistant to any discussion about human evolution. Okay, his

2112
01:54:00,240 --> 01:54:03,759
Speaker 1: resistance to discussions about human evolution is that they change

2113
01:54:03,840 --> 01:54:08,080
Speaker 1: the story too much. It used to be this, Now

2114
01:54:08,160 --> 01:54:11,320
Speaker 1: you're telling me it's this. So what he wanted to

2115
01:54:11,360 --> 01:54:15,720
Speaker 1: see was he wanted to see an explanation that was

2116
01:54:15,840 --> 01:54:20,080
Speaker 1: the end all, be all, final answer, that this is

2117
01:54:20,160 --> 01:54:25,360
Speaker 1: what happened. If someone failed to give him that the

2118
01:54:25,520 --> 01:54:29,519
Speaker 1: absolute thing that in twenty years will not change, he

2119
01:54:29,640 --> 01:54:31,880
Speaker 1: wanted to discard the whole thing because he didn't want

2120
01:54:31,920 --> 01:54:36,800
Speaker 1: to take the energy, the mental energy to follow a

2121
01:54:36,960 --> 01:54:41,640
Speaker 1: constantly evolving narrative that had new inputs in the upset

2122
01:54:41,800 --> 01:54:45,920
Speaker 1: old understandings. It was frustrating to him. So the minute

2123
01:54:45,920 --> 01:54:50,080
Speaker 1: you changed it too many times, he became suspicious of

2124
01:54:50,160 --> 01:54:54,200
Speaker 1: the entire body of knowledge. How do you change that?

2125
01:54:54,720 --> 01:54:59,240
Speaker 1: He was a smart dude, very smart, but some things, um,

2126
01:54:59,280 --> 01:55:02,600
Speaker 1: he wasn't Like there's certain aspects of learning that he

2127
01:55:02,680 --> 01:55:06,000
Speaker 1: didn't enjoy. The journey. You had to give it to him.

2128
01:55:06,000 --> 01:55:07,680
Speaker 1: And if next year you came and told him that,

2129
01:55:07,760 --> 01:55:10,000
Speaker 1: you know what, we're kind of thinking this, but now

2130
01:55:10,040 --> 01:55:12,320
Speaker 1: it looks like this, he's like, I'm gonna I'm gonna

2131
01:55:12,320 --> 01:55:15,760
Speaker 1: forget everything you've ever said to me. So that's maybe

2132
01:55:15,760 --> 01:55:19,800
Speaker 1: what's hard about wildlife issues because it's always in flux

2133
01:55:20,520 --> 01:55:23,680
Speaker 1: and there. And by learn you learn more. I mean

2134
01:55:23,720 --> 01:55:27,320
Speaker 1: the tools they're using now with the remote cameras and genetics,

2135
01:55:27,320 --> 01:55:30,800
Speaker 1: Oh my god, the tools are non invasive monitoring. We're

2136
01:55:30,880 --> 01:55:33,520
Speaker 1: learning things, amazing things that you can't see even with

2137
01:55:33,600 --> 01:55:37,280
Speaker 1: the radio caller. Dear biologists just last week tell us

2138
01:55:37,280 --> 01:55:40,360
Speaker 1: that now the amount of data he can pick up

2139
01:55:40,360 --> 01:55:43,720
Speaker 1: in one day it might have taken him years twenty

2140
01:55:43,800 --> 01:55:47,600
Speaker 1: years ago. Great, And I don't know that it's necessarily better,

2141
01:55:47,920 --> 01:55:50,600
Speaker 1: but it sure is helpful and trying to look at

2142
01:55:50,640 --> 01:55:52,960
Speaker 1: some things, but it opens up a lot more questions

2143
01:55:53,320 --> 01:55:57,640
Speaker 1: looking at Yeah, genetics is an especially powerful tool. I

2144
01:55:57,640 --> 01:56:00,920
Speaker 1: I'm very amazed with what can be or no by

2145
01:56:01,040 --> 01:56:04,680
Speaker 1: picking up a scat temple or urine sample, even from

2146
01:56:04,720 --> 01:56:07,520
Speaker 1: an ungulate and looky whatever it is, but usually a

2147
01:56:07,640 --> 01:56:11,720
Speaker 1: terror or scat and learning, you can glean enormous amounts

2148
01:56:11,720 --> 01:56:14,280
Speaker 1: of information about where this animal came from, how it lived,

2149
01:56:14,320 --> 01:56:17,680
Speaker 1: how it died, whatever, who was related to. It's just

2150
01:56:17,760 --> 01:56:22,360
Speaker 1: an amazing tool. Yeah, people people really, some people really

2151
01:56:22,440 --> 01:56:27,880
Speaker 1: like uh we keep talking about change. Some people like

2152
01:56:28,000 --> 01:56:30,200
Speaker 1: things that don't change. We're just down. We just had

2153
01:56:30,240 --> 01:56:32,720
Speaker 1: our little family vacation down in Baja and we bought

2154
01:56:32,760 --> 01:56:37,200
Speaker 1: a really small bananas like those, a little dinky finger banas.

2155
01:56:38,000 --> 01:56:42,280
Speaker 1: My daughter, who doesn't like bananas, liked these bananas. My

2156
01:56:42,360 --> 01:56:45,480
Speaker 1: son is upset by this for some reason, and it's

2157
01:56:45,480 --> 01:56:49,800
Speaker 1: saying to her, I thought you didn't like bananas. And

2158
01:56:49,880 --> 01:56:52,480
Speaker 1: I said to him, it was like any sentence that

2159
01:56:52,560 --> 01:56:56,160
Speaker 1: you begin with the words I thought you didn't is

2160
01:56:56,160 --> 01:57:01,640
Speaker 1: a not necessary sentence where you're calling someone out for

2161
01:57:01,760 --> 01:57:06,520
Speaker 1: having changed something. But he didn't like it, and maybe

2162
01:57:06,520 --> 01:57:09,280
Speaker 1: he likes his sister to not like bananas because she

2163
01:57:09,360 --> 01:57:12,280
Speaker 1: doesn't like bananas. And I think a big part of

2164
01:57:12,320 --> 01:57:16,080
Speaker 1: the whole wolf thing is in our memory of our

2165
01:57:16,120 --> 01:57:19,120
Speaker 1: parents and grandparents, there were not wolves on the landscape

2166
01:57:19,200 --> 01:57:23,480
Speaker 1: and now they're back and it's change. But if they

2167
01:57:23,480 --> 01:57:27,240
Speaker 1: went back two years ago, the landscape was crawling with

2168
01:57:27,240 --> 01:57:31,000
Speaker 1: wolves and that was the normal. So we are selective

2169
01:57:31,000 --> 01:57:33,000
Speaker 1: in our memory about what we want to think about

2170
01:57:33,160 --> 01:57:35,680
Speaker 1: or how we analyze things. In hunting and fishing, dudes

2171
01:57:35,840 --> 01:57:39,240
Speaker 1: are generally in love with the Lewis and Clark era.

2172
01:57:40,760 --> 01:57:42,920
Speaker 1: They're like, man, if I could do one thing, it

2173
01:57:42,920 --> 01:57:46,200
Speaker 1: would have been out with those boys, all the wolves

2174
01:57:46,280 --> 01:57:51,160
Speaker 1: running up down Chase and everything, killing all the game

2175
01:57:52,840 --> 01:57:56,120
Speaker 1: except for the ten million vice and whatever. Yeah, no,

2176
01:57:56,280 --> 01:57:58,800
Speaker 1: it's it's an interesting concept. So I always ask people that,

2177
01:57:58,960 --> 01:58:02,160
Speaker 1: just instead of thinking of just how things are today

2178
01:58:02,240 --> 01:58:05,640
Speaker 1: or in your mind, try and think on a bigger scale.

2179
01:58:06,840 --> 01:58:09,840
Speaker 1: And the future, I mean the future is there's going

2180
01:58:09,880 --> 01:58:12,800
Speaker 1: to be left less and less landscape available for wildlife,

2181
01:58:12,840 --> 01:58:15,320
Speaker 1: and that that frightens me. And I think I would

2182
01:58:15,360 --> 01:58:17,720
Speaker 1: like to see people instead of hating this or that

2183
01:58:17,920 --> 01:58:20,120
Speaker 1: or wanting to kill all the wolves or whatever, I

2184
01:58:20,160 --> 01:58:23,520
Speaker 1: would be more concerned about protecting and preserving a wildlife

2185
01:58:23,560 --> 01:58:27,680
Speaker 1: heritage on the landscape. And I think ranting community and

2186
01:58:27,760 --> 01:58:31,320
Speaker 1: hunting communities are absolutely key to that. I mean, I work.

2187
01:58:31,840 --> 01:58:33,560
Speaker 1: Do you look at where they look at where the

2188
01:58:33,560 --> 01:58:36,160
Speaker 1: big game winners? Think about these ranchers. Man, you look

2189
01:58:36,240 --> 01:58:40,280
Speaker 1: drive between Livingston and Gardner, Holy crafters. Thousands of animals

2190
01:58:40,320 --> 01:58:42,760
Speaker 1: out there eating up. There's nothing this the grass that

2191
01:58:42,880 --> 01:58:46,040
Speaker 1: looked like this table and they got to raise cattle

2192
01:58:46,080 --> 01:58:48,800
Speaker 1: on it next year. It's private land. They support all

2193
01:58:48,840 --> 01:58:52,040
Speaker 1: that wildlife. Your own people want to get rid of

2194
01:58:52,120 --> 01:58:56,360
Speaker 1: their cattle because wolves get killed. You know what. They

2195
01:58:56,440 --> 01:58:59,360
Speaker 1: provide a huge amount of wildlife resource. I want to

2196
01:58:59,360 --> 01:59:00,920
Speaker 1: see them there. I want to see him stay in

2197
01:59:00,920 --> 01:59:02,560
Speaker 1: the landscape. I got I know a guy down in

2198
01:59:02,640 --> 01:59:05,360
Speaker 1: Utah and they had some unusual snowfall patterns this year

2199
01:59:05,400 --> 01:59:08,840
Speaker 1: in Utah and he lost forty dollars or they hey

2200
01:59:08,920 --> 01:59:11,520
Speaker 1: to a group of elk, And he texted me that

2201
01:59:11,560 --> 01:59:17,960
Speaker 1: he's trying to be cool about us they season. So

2202
01:59:18,320 --> 01:59:21,960
Speaker 1: it's it's really complicated. It's it just does Uh Do

2203
01:59:21,960 --> 01:59:23,920
Speaker 1: you have any final little things you wanted to wedge

2204
01:59:23,920 --> 01:59:26,440
Speaker 1: in there that we didn't get to. I don't think so.

2205
01:59:27,360 --> 01:59:30,680
Speaker 1: Um No, We've covered a lot. I like your point

2206
01:59:31,520 --> 01:59:35,680
Speaker 1: that space for wildlife. That's why I become front. That

2207
01:59:35,760 --> 01:59:38,240
Speaker 1: might be one of the reasons I become frustrated with

2208
01:59:39,520 --> 01:59:44,160
Speaker 1: UM aspects of the animal rights community or people who

2209
01:59:45,120 --> 01:59:51,520
Speaker 1: UM oppose any kind of wolf hunting or wolf trapp trapping.

2210
01:59:51,520 --> 01:59:54,960
Speaker 1: For the hides would be that when I look in

2211
01:59:55,000 --> 01:59:57,320
Speaker 1: the future, like, I see a problem that needs to

2212
01:59:57,320 --> 02:00:02,040
Speaker 1: be addressed, and it's maintaining half a tat, maintaining space

2213
02:00:02,120 --> 02:00:04,960
Speaker 1: for wildlife. And I'm like, how are you so, Like,

2214
02:00:05,400 --> 02:00:07,480
Speaker 1: how do you when you look into the future, how

2215
02:00:07,520 --> 02:00:12,080
Speaker 1: do you see? Um? Why do you Why are you

2216
02:00:12,120 --> 02:00:14,520
Speaker 1: not worried about that? Why are you worried about Why

2217
02:00:14,520 --> 02:00:16,480
Speaker 1: are you bringing so much energy into this thing when

2218
02:00:16,480 --> 02:00:20,120
Speaker 1: the real problem is that the real problem is habitat. Yeah,

2219
02:00:20,120 --> 02:00:23,640
Speaker 1: and the two things That one is that habitat for

2220
02:00:23,640 --> 02:00:28,480
Speaker 1: world life is not not necessarily or at all exclusive

2221
02:00:28,520 --> 02:00:31,160
Speaker 1: to human presence. Like I just point out the ranching.

2222
02:00:31,600 --> 02:00:34,080
Speaker 1: The ranch lands are the winter range for the most part,

2223
02:00:34,640 --> 02:00:36,800
Speaker 1: And I think people get hung up on wildlife has

2224
02:00:36,840 --> 02:00:41,760
Speaker 1: to have wilderness, No, I have to have it. Yes,

2225
02:00:42,680 --> 02:00:45,040
Speaker 1: we all do. I mean that's part of the I

2226
02:00:45,040 --> 02:00:46,440
Speaker 1: do have one more point that I want to tell

2227
02:00:46,880 --> 02:00:49,440
Speaker 1: it's called a concluder. Kind of concluder. So the thing

2228
02:00:49,480 --> 02:00:51,800
Speaker 1: that I think about a lot here in the West

2229
02:00:52,000 --> 02:00:56,360
Speaker 1: especially is but it's true anywhere, is how do we

2230
02:00:56,480 --> 02:00:59,760
Speaker 1: create a value for wolves, Because the only way they're

2231
02:00:59,760 --> 02:01:01,560
Speaker 1: gonna be hilerate on the landscape is if they have

2232
02:01:01,600 --> 02:01:04,560
Speaker 1: a value. That value can be in terms of uh,

2233
02:01:04,760 --> 02:01:09,240
Speaker 1: cultural it can be in terms of hide value selling hides.

2234
02:01:09,360 --> 02:01:11,520
Speaker 1: It can be what's wolf hide worth right now? I

2235
02:01:11,520 --> 02:01:14,080
Speaker 1: think it was told hundred seventy five dollars. So like

2236
02:01:14,200 --> 02:01:18,320
Speaker 1: up in Alaska, some of the biggest opponents of aerial

2237
02:01:18,360 --> 02:01:23,160
Speaker 1: gunning were the trappers because it's their culture, subsistence and income,

2238
02:01:23,240 --> 02:01:25,040
Speaker 1: and they didn't want to see those wolves gonned off

2239
02:01:25,040 --> 02:01:27,840
Speaker 1: because they cont on trapping them and catching them. So

2240
02:01:28,000 --> 02:01:31,760
Speaker 1: that's a value. Another value would be aesthetic. Maybe you

2241
02:01:31,840 --> 02:01:34,000
Speaker 1: live in Des Moines, Iowa, and you'll never see one,

2242
02:01:34,040 --> 02:01:36,440
Speaker 1: but you like to know they're just out there. Maybe

2243
02:01:36,440 --> 02:01:38,800
Speaker 1: you come to Yellowstone Park and your value is seeing

2244
02:01:38,840 --> 02:01:41,440
Speaker 1: them in that environment or potentially hearing them hall. I mean,

2245
02:01:41,760 --> 02:01:43,960
Speaker 1: I don't care what the value isn't those values are

2246
02:01:43,960 --> 02:01:46,720
Speaker 1: on opposites in the scale, and they may be conflicting values.

2247
02:01:46,920 --> 02:01:50,000
Speaker 1: But they have a value because if something lives in

2248
02:01:50,040 --> 02:01:52,640
Speaker 1: our world and it doesn't have a value, it's gone

2249
02:01:52,680 --> 02:01:57,640
Speaker 1: pretty quickly or is innocuous or is innocuous. Well maybe

2250
02:01:57,880 --> 02:02:00,440
Speaker 1: I don't know. Well anyway, I'm just and I think

2251
02:02:00,440 --> 02:02:04,960
Speaker 1: it's really important that you know, we they have a

2252
02:02:05,080 --> 02:02:08,720
Speaker 1: value to survive. And I know in this particular in Montana,

2253
02:02:08,760 --> 02:02:10,960
Speaker 1: for example. What I mean by that is what I

2254
02:02:10,960 --> 02:02:13,000
Speaker 1: mean by that actually clarify the point. What I mean

2255
02:02:13,120 --> 02:02:17,200
Speaker 1: is things that require some level of sacrifice have to

2256
02:02:17,240 --> 02:02:20,680
Speaker 1: have a corresponding value. You could have something like you know,

2257
02:02:20,760 --> 02:02:23,880
Speaker 1: people might not put a lot of cultural or economic

2258
02:02:24,000 --> 02:02:29,560
Speaker 1: value on apossums, but will continue to have apossums because

2259
02:02:29,600 --> 02:02:32,360
Speaker 1: they're not you know, we're not we're not making a

2260
02:02:32,400 --> 02:02:36,600
Speaker 1: decision about their fate. Generally, you provide certain things and

2261
02:02:36,600 --> 02:02:40,280
Speaker 1: they just continue to exist. They're not controversial. Um, we

2262
02:02:40,320 --> 02:02:42,840
Speaker 1: don't need to have meetings in public comment periods about

2263
02:02:42,880 --> 02:02:44,560
Speaker 1: what we're gonna do. I don't know, I don't know.

2264
02:02:44,640 --> 02:02:50,600
Speaker 1: I possum country. Okay, Okay, we don't talk about possums. Okay,

2265
02:02:51,200 --> 02:02:54,560
Speaker 1: damn shoure talking about everything else, right, steelhead deer, turkeys,

2266
02:02:54,640 --> 02:02:58,120
Speaker 1: we talk about it possums. Nope, what's kind of like matlons.

2267
02:02:59,000 --> 02:03:01,480
Speaker 1: So you know, Jimmy, I didn't hear Jim's podcast, but

2268
02:03:01,920 --> 02:03:04,160
Speaker 1: there's three times as many mountain lions and the landscape

2269
02:03:04,160 --> 02:03:07,400
Speaker 1: in Montana's there are wolves. People aren't angry about mountain

2270
02:03:07,400 --> 02:03:09,480
Speaker 1: lions and the landscape. They aren't piste off. They don't

2271
02:03:09,480 --> 02:03:12,040
Speaker 1: want to seem eliminated. They're introducing twelve bills into the

2272
02:03:12,160 --> 02:03:14,720
Speaker 1: legislature this year to kill more mountain lions. And it's like,

2273
02:03:15,240 --> 02:03:17,320
Speaker 1: you know, if there's three times as many mountain lions,

2274
02:03:17,320 --> 02:03:18,840
Speaker 1: it's two and a half to three times as many.

2275
02:03:18,920 --> 02:03:21,560
Speaker 1: Is there are wolves, you can presume that they're killing

2276
02:03:21,800 --> 02:03:23,360
Speaker 1: three times as much, two and a half to three

2277
02:03:23,360 --> 02:03:28,280
Speaker 1: times as mentioned. Game as wolved. Why aren't people concerned?

2278
02:03:28,400 --> 02:03:32,560
Speaker 1: I heard an explanation. Please tell me this is out

2279
02:03:32,600 --> 02:03:34,480
Speaker 1: of a thing that this is out of a research

2280
02:03:34,520 --> 02:03:37,400
Speaker 1: piece in Idaho and they kill people. This is not

2281
02:03:37,520 --> 02:03:44,040
Speaker 1: a research piece in Idaho where you, let's say, annually

2282
02:03:44,920 --> 02:03:49,919
Speaker 1: you lose sixteen seventeen per cent of your elk calves

2283
02:03:50,240 --> 02:03:54,320
Speaker 1: or no, it's like you lose or your elk calves

2284
02:03:54,320 --> 02:03:57,600
Speaker 1: every year two mountain lions. And it's been that way

2285
02:03:57,640 --> 02:04:00,320
Speaker 1: for a long time, and people are used to a

2286
02:04:00,360 --> 02:04:03,360
Speaker 1: certain cow calf ratio. But then you come in with

2287
02:04:03,400 --> 02:04:08,280
Speaker 1: this additive, this new additive thing, and all of a

2288
02:04:08,320 --> 02:04:15,320
Speaker 1: sudden it adds a five mortality rate that you feel

2289
02:04:15,400 --> 02:04:19,840
Speaker 1: that five. You can observe that five in your lifetime

2290
02:04:20,360 --> 02:04:24,120
Speaker 1: because static, your idea of static was the mountain lion presence.

2291
02:04:24,640 --> 02:04:27,680
Speaker 1: So people see a shift the new thing to point

2292
02:04:27,720 --> 02:04:31,760
Speaker 1: to ours, just to change, and so that's where the

2293
02:04:31,800 --> 02:04:36,000
Speaker 1: animosity grows. When all along you've been losing this very

2294
02:04:36,080 --> 02:04:39,160
Speaker 1: high percentage to mountain lions, but you've always you're used

2295
02:04:39,160 --> 02:04:41,360
Speaker 1: to that. When you're out and you see cows and calves,

2296
02:04:41,360 --> 02:04:44,520
Speaker 1: you're used to a certain ratio. The ratio switches and

2297
02:04:44,600 --> 02:04:49,960
Speaker 1: people perceive that new thing as being the problem. This

2298
02:04:50,040 --> 02:04:53,760
Speaker 1: is articulated through something that the buddy sent me. But

2299
02:04:53,880 --> 02:04:56,000
Speaker 1: still the majority of them are being killed by lions,

2300
02:04:56,000 --> 02:04:58,240
Speaker 1: had shown over and over and people don't worry about

2301
02:04:58,280 --> 02:05:03,280
Speaker 1: it because it's And I also think in addition to that,

2302
02:05:03,280 --> 02:05:05,800
Speaker 1: that's a good point. But in addition to that, moultlines

2303
02:05:05,840 --> 02:05:08,360
Speaker 1: have a value. How much is an outfit or charge

2304
02:05:09,160 --> 02:05:12,280
Speaker 1: for a mountline hunt four? And how many does he

2305
02:05:12,320 --> 02:05:17,120
Speaker 1: do it? Year? Many? So it has a value to him.

2306
02:05:17,360 --> 02:05:21,040
Speaker 1: The Houndsmen are very well organized. They're very vocal proponents

2307
02:05:21,080 --> 02:05:23,720
Speaker 1: of keeping lions on the landscape. They're also pretty vocal

2308
02:05:23,760 --> 02:05:28,000
Speaker 1: about getting rid of wolves. From what I've seen, dogs

2309
02:05:29,120 --> 02:05:34,240
Speaker 1: killing dogs and kill mountlines and compete with them. So

2310
02:05:34,640 --> 02:05:38,520
Speaker 1: but my point is, you know, honsman her amazing. They're

2311
02:05:38,560 --> 02:05:40,920
Speaker 1: amazing to learn from when they bring in mountlines to

2312
02:05:40,960 --> 02:05:42,480
Speaker 1: be tagged. At work with a lot of them tagging

2313
02:05:42,520 --> 02:05:44,080
Speaker 1: their lines, and I learned a lot from them. They're

2314
02:05:44,080 --> 02:05:46,920
Speaker 1: really good information sources about where they're seeing wolves and

2315
02:05:47,080 --> 02:05:50,360
Speaker 1: how many lions are out there. But they have that value,

2316
02:05:50,600 --> 02:05:53,640
Speaker 1: and then nobody goes drives and spends thirty five millions

2317
02:05:53,680 --> 02:05:56,920
Speaker 1: annually to go to look at mountainins and Yellowstone Park.

2318
02:05:57,000 --> 02:06:01,480
Speaker 1: That's yeah. I mean, I'm just saying they're sneaky, they're quiet.

2319
02:06:01,520 --> 02:06:03,160
Speaker 1: You don't know they're there, and there's a lot more

2320
02:06:03,200 --> 02:06:05,120
Speaker 1: of them and people don't. I mean, they kill a

2321
02:06:05,120 --> 02:06:09,400
Speaker 1: few people every so often in mal people it's like, oh, whatever,

2322
02:06:09,800 --> 02:06:12,960
Speaker 1: I can tell you when it happens sometime in the future.

2323
02:06:12,960 --> 02:06:16,720
Speaker 1: Who knows if wolves kill a person, Oh my god,

2324
02:06:16,960 --> 02:06:20,520
Speaker 1: it's gonna be really all over the front page for

2325
02:06:20,720 --> 02:06:24,680
Speaker 1: weeks on end. It's happening all the time with lions embarrassed. Well,

2326
02:06:24,720 --> 02:06:27,520
Speaker 1: I mean there hasn't been alone. I mean, yeah, there

2327
02:06:27,560 --> 02:06:29,520
Speaker 1: was a couple of Yeah, there was two I can

2328
02:06:29,560 --> 02:06:34,640
Speaker 1: think of. Yeah, there's a couple of years more in Oregon, one, Washington. Yeah.

2329
02:06:34,680 --> 02:06:37,800
Speaker 1: I'm just saying there's a different value system on these

2330
02:06:37,800 --> 02:06:45,360
Speaker 1: different animals, economic, cultural, ecological, visual. It's something can be

2331
02:06:45,440 --> 02:06:48,560
Speaker 1: interesting to think about. So my point is we need

2332
02:06:48,600 --> 02:06:52,600
Speaker 1: to create value on wolves. Could guided wolf hunts be

2333
02:06:52,640 --> 02:06:55,760
Speaker 1: the salvation of wolves? I don't think. I don't think

2334
02:06:55,840 --> 02:06:58,480
Speaker 1: it's hard. But you know what, some people are taking

2335
02:06:58,520 --> 02:07:00,800
Speaker 1: people out to kill wolves as they learned how to.

2336
02:07:01,000 --> 02:07:03,200
Speaker 1: They've learned how to get them, and they're good at it.

2337
02:07:03,280 --> 02:07:05,959
Speaker 1: And I know some of them and they're they're pretty efficient.

2338
02:07:05,960 --> 02:07:09,040
Speaker 1: They understand wolfee college, they understand behavior, they know how

2339
02:07:09,040 --> 02:07:11,400
Speaker 1: to find them. They mostly calling yea, they know how

2340
02:07:11,400 --> 02:07:14,240
Speaker 1: to call them. And so the sounds are they using

2341
02:07:14,800 --> 02:07:16,840
Speaker 1: so you don't have to ask them? You do know?

2342
02:07:16,960 --> 02:07:21,880
Speaker 1: I don't know, you never got curiousness? Do you need?

2343
02:07:21,880 --> 02:07:25,040
Speaker 1: They're using wolf vocalizations? Do you think they're using pre vocalizations?

2344
02:07:25,160 --> 02:07:27,120
Speaker 1: I'm saying, is there what could be a business for it.

2345
02:07:30,240 --> 02:07:32,520
Speaker 1: There could be a business for it. And and there

2346
02:07:32,600 --> 02:07:34,440
Speaker 1: is business for a wolf. I mean, look at the

2347
02:07:34,520 --> 02:07:37,440
Speaker 1: number of wolf safaris. I mean there's a huge economic

2348
02:07:37,720 --> 02:07:39,840
Speaker 1: value to seeing wolves. But if you wanted to do

2349
02:07:39,880 --> 02:07:44,480
Speaker 1: them for hunting, and right now with the move to

2350
02:07:44,520 --> 02:07:47,240
Speaker 1: pay bounties on wolves, that will incentivize for people. It's

2351
02:07:47,280 --> 02:07:50,160
Speaker 1: a monitory. Does put a value on them. It may

2352
02:07:50,160 --> 02:07:51,880
Speaker 1: not be your value or my value, or might be

2353
02:07:51,960 --> 02:07:53,760
Speaker 1: I don't know, but it puts a value on them.

2354
02:07:53,760 --> 02:07:56,560
Speaker 1: They get a thousand bucks a wolf, they can Uh,

2355
02:07:57,200 --> 02:08:00,440
Speaker 1: it's not called a bounty. It's a compensation program. H

2356
02:08:00,840 --> 02:08:04,760
Speaker 1: and at least got a value, right Liner, It may not,

2357
02:08:05,720 --> 02:08:08,920
Speaker 1: I mean it sit well with everybody. No, it won't,

2358
02:08:11,560 --> 02:08:15,640
Speaker 1: all right, Diane Boyden, Yeah, you got any final concluders,

2359
02:08:16,880 --> 02:08:20,840
Speaker 1: I don't mind, say, Shade, we go on forever. Like

2360
02:08:20,880 --> 02:08:24,560
Speaker 1: you said, there's hours and hours, but what he'll come back.

2361
02:08:24,720 --> 02:08:27,000
Speaker 1: We'd love to have you again. One last yes or

2362
02:08:27,000 --> 02:08:34,120
Speaker 1: no question. You had to go back to seven all

2363
02:08:34,160 --> 02:08:36,760
Speaker 1: over again. Would you have like sold your motorcycle and

2364
02:08:36,800 --> 02:08:38,880
Speaker 1: drove off to work on wolves up in Eale, Minnesota.

2365
02:08:38,880 --> 02:08:42,760
Speaker 1: Wouldn't think twice about it? Absolutely, that's good. No, thank

2366
02:08:42,760 --> 02:08:45,000
Speaker 1: you very much for coming on the show. Thank you.

2367
02:09:01,320 --> 02:09:06,280
Speaker 1: MS convert to prove to feet